From 4dbdddb15be61a0da4d96509f0f9d83053d1462b Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Fri, 27 Jan 2023 11:04:07 +0530 Subject: [PATCH 01/12] Create README.md --- courses/Coursera_Convolutional_Neural_Networks/README.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 courses/Coursera_Convolutional_Neural_Networks/README.md diff --git a/courses/Coursera_Convolutional_Neural_Networks/README.md b/courses/Coursera_Convolutional_Neural_Networks/README.md new file mode 100644 index 00000000000..25ece2f82c2 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/README.md @@ -0,0 +1 @@ +# CNN - Convolutional Neural Networks From 9976b8e76951a142090dbc365a5c9cce81e102c8 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Fri, 27 Jan 2023 11:05:04 +0530 Subject: [PATCH 02/12] Add files via upload --- ...eneration_with_Neural_Style_Transfer.ipynb | 1805 +++++++++++++++ ...us_driving_application_Car_detection.ipynb | 1679 ++++++++++++++ .../Convolution_model_Application.ipynb | 1062 +++++++++ .../Convolution_model_Step_by_Step_v1.ipynb | 1823 +++++++++++++++ .../Face_Recognition.ipynb | 1054 +++++++++ .../Image_segmentation_Unet_v2.ipynb | 1311 +++++++++++ .../Residual_Networks.ipynb | 2034 +++++++++++++++++ .../Transfer_learning_with_MobileNet_v1.ipynb | 1508 ++++++++++++ 8 files changed, 12276 insertions(+) create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Art_Generation_with_Neural_Style_Transfer.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Autonomous_driving_application_Car_detection.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Application.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Step_by_Step_v1.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Face_Recognition.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Image_segmentation_Unet_v2.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Residual_Networks.ipynb create mode 100644 courses/Coursera_Convolutional_Neural_Networks/Transfer_learning_with_MobileNet_v1.ipynb diff --git a/courses/Coursera_Convolutional_Neural_Networks/Art_Generation_with_Neural_Style_Transfer.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Art_Generation_with_Neural_Style_Transfer.ipynb new file mode 100644 index 00000000000..973f337ce98 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Art_Generation_with_Neural_Style_Transfer.ipynb @@ -0,0 +1,1805 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Deep Learning & Art: Neural Style Transfer\n", + "\n", + "Welcome to the Week 4 assignment! In this lab assignment, you will learn about Neural Style Transfer, an algorithm created by [Gatys et al. (2015).](https://arxiv.org/abs/1508.06576)\n", + "\n", + "**Upon completion of this assignment, you will be able to:**\n", + "- Implement the neural style transfer algorithm \n", + "- Generate novel artistic images using your algorithm \n", + "- Define the style cost function for Neural Style Transfer\n", + "- Define the content cost function for Neural Style Transfer\n", + "\n", + "Most of the algorithms you've studied optimize a cost function to get a set of parameter values. With Neural Style Transfer, you'll get to optimize a cost function to get pixel values. Exciting!\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "\n", + "- [1 - Packages](#1)\n", + "- [2 - Problem Statement](#2)\n", + "- [3 - Transfer Learning](#3)\n", + "- [4 - Neural Style Transfer (NST)](#4)\n", + " - [4.1 - Computing the Content Cost](#4-1)\n", + " - [4.1.1 - Make Generated Image G Match the Content of Image C](#4-1-1)\n", + " - [4.1.2 - Content Cost Function π½π‘π‘œπ‘›π‘‘π‘’π‘›π‘‘(𝐢,𝐺)](#4-1-2)\n", + " - [Excercise 1 - compute_content_cost](#ex-1)\n", + " - [4.2 - Computing the Style Cost](#4-2)\n", + " - [4.2.1 - Style Matrix](#4-2-1)\n", + " - [Exercise 2 - gram_matrix](#ex-2)\n", + " - [4.2.2 - Style Cost](#4-2-2)\n", + " - [Exercise 3 - compute_layer_style_cost](#ex-3)\n", + " - [4.2.3 Style Weights](#4-2-3)\n", + " - [Exercise 4 - compute_style_cost](#ex-4)\n", + " - [4.3 - Defining the Total Cost to Optimize](#4-3)\n", + " - [Exercise 5 - total_cost](#ex-5)\n", + "- [5 - Solving the Optimization Problem](#5)\n", + " - [5.1 Load the Content Image](#5-1)\n", + " - [5.2 Load the Style Image](#5-2)\n", + " - [5.3 Randomly Initialize the Image to be Generated](#5-3)\n", + " - [5.4 - Load Pre-trained VGG19 Model](#5-4)\n", + " - [5.5 - Compute Total Cost](#5-5)\n", + " - [5.5.1 - Compute Content Cost](#5-5-1)\n", + " - [5.5.2 - Compute Style Cost](#5-5-2)\n", + " - [Exercise 6 - train_step](#ex-6)\n", + " - [5.6 - Train the Model](#5-6)\n", + "- [6 - Test With Your Own Image (Optional/Ungraded)](#6)\n", + "- [7 - References](#7)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages\n", + "\n", + "Run the following code cell to import the necessary packages and dependencies you will need to perform Neural Style Transfer." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "import scipy.io\n", + "import scipy.misc\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.pyplot import imshow\n", + "from PIL import Image\n", + "import numpy as np\n", + "import tensorflow as tf\n", + "from tensorflow.python.framework.ops import EagerTensor\n", + "import pprint\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Problem Statement\n", + "\n", + "Neural Style Transfer (NST) is one of the most fun and interesting optimization techniques in deep learning. It merges two images, namely: a \"content\" image (C) and a \"style\" image (S), to create a \"generated\" image (G). The generated image G combines the \"content\" of the image C with the \"style\" of image S. \n", + "\n", + "In this assignment, you are going to combine the Louvre museum in Paris (content image C) with the impressionist style of Claude Monet (content image S) to generate the following image:\n", + "\n", + "\n", + "\n", + "Let's get started!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Transfer Learning\n", + "\n", + "\n", + "Neural Style Transfer (NST) uses a previously trained convolutional network, and builds on top of that. The idea of using a network trained on a different task and applying it to a new task is called transfer learning. \n", + "\n", + "You will be using the the epynomously named VGG network from the [original NST paper](https://arxiv.org/abs/1508.06576) published by the Visual Geometry Group at University of Oxford in 2014. Specifically, you'll use VGG-19, a 19-layer version of the VGG network. This model has already been trained on the very large ImageNet database, and has learned to recognize a variety of low level features (at the shallower layers) and high level features (at the deeper layers). \n", + "\n", + "Run the following code to load parameters from the VGG model. This may take a few seconds. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "tf.random.set_seed(272) # DO NOT CHANGE THIS VALUE\n", + "pp = pprint.PrettyPrinter(indent=4)\n", + "img_size = 400\n", + "vgg = tf.keras.applications.VGG19(include_top=False,\n", + " input_shape=(img_size, img_size, 3),\n", + " weights='pretrained-model/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5')\n", + "\n", + "vgg.trainable = False\n", + "pp.pprint(vgg)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 4 - Neural Style Transfer (NST)\n", + "\n", + "Next, you will be building the Neural Style Transfer (NST) algorithm in three steps:\n", + "\n", + "- First, you will build the content cost function $J_{content}(C,G)$\n", + "- Second, you will build the style cost function $J_{style}(S,G)$\n", + "- Finally, you'll put it all together to get $J(G) = \\alpha J_{content}(C,G) + \\beta J_{style}(S,G)$. Exciting!\n", + "\n", + "\n", + "### 4.1 - Computing the Content Cost" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 4.1.1 - Make Generated Image G Match the Content of Image C\n", + "\n", + "One goal you should aim for when performing NST is for the content in generated image G to match the content of image C. To do so, you'll need an understanding of shallow versus deep layers :\n", + "\n", + "* The shallower layers of a ConvNet tend to detect lower-level features such as edges and simple textures.\n", + "* The deeper layers tend to detect higher-level features such as more complex textures and object classes. \n", + "\n", + "#### To choose a \"middle\" activation layer $a^{[l]}$ :\n", + "You need the \"generated\" image G to have similar content as the input image C. Suppose you have chosen some layer's activations to represent the content of an image. \n", + "* In practice, you'll get the most visually pleasing results if you choose a layer in the middle of the network--neither too shallow nor too deep. This ensures that the network detects both higher-level and lower-level features.\n", + "* After you have finished this exercise, feel free to come back and experiment with using different layers to see how the results vary!\n", + "\n", + "#### To forward propagate image \"C:\"\n", + "* Set the image C as the input to the pretrained VGG network, and run forward propagation. \n", + "* Let $a^{(C)}$ be the hidden layer activations in the layer you had chosen. (In lecture, this was written as $a^{[l](C)}$, but here the superscript $[l]$ is dropped to simplify the notation.) This will be an $n_H \\times n_W \\times n_C$ tensor.\n", + "\n", + "#### To forward propagate image \"G\":\n", + "* Repeat this process with the image G: Set G as the input, and run forward progation. \n", + "* Let $a^{(G)}$ be the corresponding hidden layer activation. \n", + "\n", + "In this running example, the content image C will be the picture of the Louvre Museum in Paris. Run the code below to see a picture of the Louvre." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The content image (C) shows the Louvre museum's pyramid surrounded by old Paris buildings, against a sunny sky with a few clouds.\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "content_image = Image.open(\"images/louvre.jpg\")\n", + "print(\"The content image (C) shows the Louvre museum's pyramid surrounded by old Paris buildings, against a sunny sky with a few clouds.\")\n", + "content_image" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 4.1.2 - Content Cost Function $J_{content}(C,G)$\n", + "One goal you should aim for when performing NST is for the content in generated image G to match the content of image C. A method to achieve this is to calculate the content cost function, which will be defined as:\n", + "\n", + "$$J_{content}(C,G) = \\frac{1}{4 \\times n_H \\times n_W \\times n_C}\\sum _{ \\text{all entries}} (a^{(C)} - a^{(G)})^2\\tag{1} $$\n", + "\n", + "* Here, $n_H, n_W$ and $n_C$ are the height, width and number of channels of the hidden layer you have chosen, and appear in a normalization term in the cost. \n", + "* For clarity, note that $a^{(C)}$ and $a^{(G)}$ are the 3D volumes corresponding to a hidden layer's activations. \n", + "* In order to compute the cost $J_{content}(C,G)$, it might also be convenient to unroll these 3D volumes into a 2D matrix, as shown below.\n", + "* Technically this unrolling step isn't needed to compute $J_{content}$, but it will be good practice for when you do need to carry out a similar operation later for computing the style cost $J_{style}$.\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Excercise 1 - compute_content_cost\n", + "\n", + "Compute the \"content cost\" using TensorFlow. \n", + "\n", + "**Instructions**: \n", + "\n", + "`a_G`: hidden layer activations representing content of the image G\n", + "
\n", + "`a_C`: hidden layer activations representing content of the image C \n", + "\n", + "The 3 steps to implement this function are:\n", + "1. Retrieve dimensions from `a_G`: \n", + " - To retrieve dimensions from a tensor `X`, use: `X.get_shape().as_list()`\n", + "2. Unroll `a_C` and `a_G` as explained in the picture above\n", + " - You'll likely want to use these functions: [tf.transpose](https://www.tensorflow.org/api_docs/python/tf/transpose) and [tf.reshape](https://www.tensorflow.org/api_docs/python/tf/reshape).\n", + "3. Compute the content cost:\n", + " - You'll likely want to use these functions: [tf.reduce_sum](https://www.tensorflow.org/api_docs/python/tf/reduce_sum), [tf.square](https://www.tensorflow.org/api_docs/python/tf/square) and [tf.subtract](https://www.tensorflow.org/api_docs/python/tf/subtract).\n", + " \n", + " \n", + "#### Additional Hints for \"Unrolling\"\n", + "* To unroll the tensor, you want the shape to change from $(m,n_H,n_W,n_C)$ to $(m, n_H \\times n_W, n_C)$.\n", + "* `tf.reshape(tensor, shape)` takes a list of integers that represent the desired output shape.\n", + "* For the `shape` parameter, a `-1` tells the function to choose the correct dimension size so that the output tensor still contains all the values of the original tensor.\n", + "* So `tf.reshape(a_C, shape=[m, n_H * n_W, n_C])` gives the same result as `tf.reshape(a_C, shape=[m, -1, n_C])`.\n", + "* If you prefer to re-order the dimensions, you can use `tf.transpose(tensor, perm)`, where `perm` is a list of integers containing the original index of the dimensions. \n", + "* For example, `tf.transpose(a_C, perm=[0,3,1,2])` changes the dimensions from $(m, n_H, n_W, n_C)$ to $(m, n_C, n_H, n_W)$.\n", + "\n", + "* Again, note that you don't necessarily need `tf.transpose` to 'unroll' the tensors in this case but this is a useful function to practice and understand for other situations that you'll encounter.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-3d3bfd0678816054", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1\n", + "# GRADED FUNCTION: compute_content_cost\n", + "\n", + "def compute_content_cost(content_output, generated_output):\n", + " \"\"\"\n", + " Computes the content cost\n", + " \n", + " Arguments:\n", + " a_C -- tensor of dimension (1, n_H, n_W, n_C), hidden layer activations representing content of the image C \n", + " a_G -- tensor of dimension (1, n_H, n_W, n_C), hidden layer activations representing content of the image G\n", + " \n", + " Returns: \n", + " J_content -- scalar that you compute using equation 1 above.\n", + " \"\"\"\n", + " a_C = content_output[-1]\n", + " a_G = generated_output[-1]\n", + " \n", + " ###Β START CODE HERE\n", + " \n", + " # Retrieve dimensions from a_G (β‰ˆ1 line)\n", + " _, n_H, n_W, n_C = a_G.get_shape().as_list()\n", + " \n", + " # Reshape a_C and a_G (β‰ˆ2 lines)\n", + " a_C_unrolled = tf.transpose(a_C)\n", + " a_G_unrolled = tf.transpose(a_G)\n", + " \n", + " # compute the cost with tensorflow (β‰ˆ1 line)\n", + " J_content = (1/ (4* n_H * n_W * n_C)) * tf.reduce_sum(tf.pow((a_G_unrolled - a_C_unrolled), 2))\n", + " \n", + " ###Β END CODE HERE\n", + " \n", + " return J_content" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-d97f213fa1c1ba56", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "J_content = tf.Tensor(7.056877, shape=(), dtype=float32)\n", + "\u001b[92mAll tests passed\n" + ] + } + ], + "source": [ + "tf.random.set_seed(1)\n", + "a_C = tf.random.normal([1, 1, 4, 4, 3], mean=1, stddev=4)\n", + "a_G = tf.random.normal([1, 1, 4, 4, 3], mean=1, stddev=4)\n", + "J_content = compute_content_cost(a_C, a_G)\n", + "J_content_0 = compute_content_cost(a_C, a_C)\n", + "assert type(J_content) == EagerTensor, \"Use the tensorflow function\"\n", + "assert np.isclose(J_content_0, 0.0), \"Wrong value. compute_content_cost(A, A) must be 0\"\n", + "assert np.isclose(J_content, 7.0568767), f\"Wrong value. Expected {7.0568767}, current{J_content}\"\n", + "\n", + "print(\"J_content = \" + str(J_content))\n", + "\n", + "# Test that it works with symbolic tensors\n", + "ll = tf.keras.layers.Dense(8, activation='relu', input_shape=(1, 4, 4, 3))\n", + "model_tmp = tf.keras.models.Sequential()\n", + "model_tmp.add(ll)\n", + "try:\n", + " compute_content_cost(ll.output, ll.output)\n", + " print(\"\\033[92mAll tests passed\")\n", + "except Exception as inst:\n", + " print(\"\\n\\033[91mDon't use the numpy API inside compute_content_cost\\n\")\n", + " print(inst)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " J_content \n", + " \n", + " 7.0568767\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Congrats! You've now successfully calculated the content cost function!\n", + "\n", + "
\n", + "\n", + " \n", + "**What you should remember:**\n", + " \n", + "- The content cost takes a hidden layer activation of the neural network, and measures how different $a^{(C)}$ and $a^{(G)}$ are. \n", + "- When you minimize the content cost later, this will help make sure $G$ has similar content as $C$. \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.2 - Computing the Style Cost\n", + "\n", + "For the running example, you will use the following style image: " + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "example = Image.open(\"images/monet_800600.jpg\")\n", + "example" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This was painted in the style of [impressionism](https://en.wikipedia.org/wiki/Impressionism).\n", + "\n", + "Now let's see how you can now define a \"style\" cost function $J_{style}(S,G)$!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 4.2.1 - Style Matrix\n", + "\n", + "#### Gram matrix\n", + "* The style matrix is also called a \"Gram matrix.\" \n", + "* In linear algebra, the Gram matrix G of a set of vectors $(v_{1},\\dots ,v_{n})$ is the matrix of dot products, whose entries are ${\\displaystyle G_{ij} = v_{i}^T v_{j} = np.dot(v_{i}, v_{j}) }$. \n", + "* In other words, $G_{ij}$ compares how similar $v_i$ is to $v_j$: If they are highly similar, you would expect them to have a large dot product, and thus for $G_{ij}$ to be large. \n", + "\n", + "#### Two meanings of the variable $G$\n", + "* Note that there is an unfortunate collision in the variable names used here. Following the common terminology used in the literature: \n", + " * $G$ is used to denote the Style matrix (or Gram matrix) \n", + " * $G$ also denotes the generated image. \n", + "* For the sake of clarity, in this assignment $G_{gram}$ will be used to refer to the Gram matrix, and $G$ to denote the generated image." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### Compute Gram matrix $G_{gram}$\n", + "You will compute the Style matrix by multiplying the \"unrolled\" filter matrix with its transpose:\n", + "\n", + "\n", + "\n", + "$$\\mathbf{G}_{gram} = \\mathbf{A}_{unrolled} \\mathbf{A}_{unrolled}^T$$\n", + "\n", + "#### $G_{(gram)ij}$: correlation\n", + "The result is a matrix of dimension $(n_C,n_C)$ where $n_C$ is the number of filters (channels). The value $G_{(gram)i,j}$ measures how similar the activations of filter $i$ are to the activations of filter $j$. \n", + "\n", + "#### $G_{(gram),ii}$: prevalence of patterns or textures\n", + "* The diagonal elements $G_{(gram)ii}$ measure how \"active\" a filter $i$ is. \n", + "* For example, suppose filter $i$ is detecting vertical textures in the image. Then $G_{(gram)ii}$ measures how common vertical textures are in the image as a whole.\n", + "* If $G_{(gram)ii}$ is large, this means that the image has a lot of vertical texture. \n", + "\n", + "\n", + "By capturing the prevalence of different types of features ($G_{(gram)ii}$), as well as how much different features occur together ($G_{(gram)ij}$), the Style matrix $G_{gram}$ measures the style of an image. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 2 - gram_matrix\n", + "* Using TensorFlow, implement a function that computes the Gram matrix of a matrix A. \n", + " * The formula is: The gram matrix of A is $G_A = AA^T$. \n", + "* You may want to use these functions: [matmul](https://www.tensorflow.org/api_docs/python/tf/matmul) and [transpose](https://www.tensorflow.org/api_docs/python/tf/transpose)." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-332b0f746ef0069e", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2\n", + "# GRADED FUNCTION: gram_matrix\n", + "\n", + "def gram_matrix(A):\n", + " \"\"\"\n", + " Argument:\n", + " A -- matrix of shape (n_C, n_H*n_W)\n", + " \n", + " Returns:\n", + " GA -- Gram matrix of A, of shape (n_C, n_C)\n", + " \"\"\" \n", + " ###Β START CODE HERE\n", + " \n", + " #(β‰ˆ1 line)\n", + " GA = tf.matmul(A, tf.transpose(A))\n", + " \n", + " ###Β END CODE HERE\n", + "\n", + " return GA" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-fe029fb7600c3fca", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GA = \n", + "tf.Tensor(\n", + "[[ 63.1888 -26.721275 -7.7320204]\n", + " [-26.721275 12.76758 -2.5158243]\n", + " [ -7.7320204 -2.5158243 23.752384 ]], shape=(3, 3), dtype=float32)\n", + "\u001b[92mAll tests passed\n" + ] + } + ], + "source": [ + "tf.random.set_seed(1)\n", + "A = tf.random.normal([3, 2 * 1], mean=1, stddev=4)\n", + "GA = gram_matrix(A)\n", + "\n", + "assert type(GA) == EagerTensor, \"Use the tensorflow function\"\n", + "assert GA.shape == (3, 3), \"Wrong shape. Check the order of the matmul parameters\"\n", + "assert np.allclose(GA[0,:], [63.1888, -26.721275, -7.7320204]), \"Wrong values.\"\n", + "\n", + "print(\"GA = \\n\" + str(GA))\n", + "\n", + "print(\"\\033[92mAll tests passed\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " GA\n", + " \n", + " [[ 63.1888 -26.721275 -7.7320204]
\n", + " [-26.721275 12.76758 -2.5158243]
\n", + " [ -7.7320204 -2.5158243 23.752384 ]]
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 4.2.2 - Style Cost" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You now know how to calculate the Gram matrix. Congrats! Your next goal will be to minimize the distance between the Gram matrix of the \"style\" image S and the Gram matrix of the \"generated\" image G. \n", + "* For now, you will use only a single hidden layer $a^{[l]}$. \n", + "* The corresponding style cost for this layer is defined as: \n", + "\n", + "$$J_{style}^{[l]}(S,G) = \\frac{1}{4 \\times {n_C}^2 \\times (n_H \\times n_W)^2} \\sum _{i=1}^{n_C}\\sum_{j=1}^{n_C}(G^{(S)}_{(gram)i,j} - G^{(G)}_{(gram)i,j})^2\\tag{2} $$\n", + "\n", + "* $G_{gram}^{(S)}$ Gram matrix of the \"style\" image.\n", + "* $G_{gram}^{(G)}$ Gram matrix of the \"generated\" image.\n", + "* Make sure you remember that this cost is computed using the hidden layer activations for a particular hidden layer in the network $a^{[l]}$\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 3 - compute_layer_style_cost\n", + "Compute the style cost for a single layer. \n", + "\n", + "**Instructions**: The 3 steps to implement this function are:\n", + "1. Retrieve dimensions from the hidden layer activations a_G: \n", + " - To retrieve dimensions from a tensor X, use: `X.get_shape().as_list()`\n", + "2. Unroll the hidden layer activations a_S and a_G into 2D matrices, as explained in the picture above (see the images in the sections \"computing the content cost\" and \"style matrix\").\n", + " - You may use [tf.transpose](https://www.tensorflow.org/api_docs/python/tf/transpose) and [tf.reshape](https://www.tensorflow.org/api_docs/python/tf/reshape).\n", + "3. Compute the Style matrix of the images S and G. (Use the function you had previously written.) \n", + "4. Compute the Style cost:\n", + " - You may find [tf.reduce_sum](https://www.tensorflow.org/api_docs/python/tf/reduce_sum), [tf.square](https://www.tensorflow.org/api_docs/python/tf/square) and [tf.subtract](https://www.tensorflow.org/api_docs/python/tf/subtract) useful.\n", + " \n", + " \n", + "#### Additional Hints\n", + "* Since the activation dimensions are $(m, n_H, n_W, n_C)$ whereas the desired unrolled matrix shape is $(n_C, n_H*n_W)$, the order of the filter dimension $n_C$ is changed. So `tf.transpose` can be used to change the order of the filter dimension.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-8f37df6f128c1f99", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C3\n", + "# GRADED FUNCTION: compute_layer_style_cost\n", + "\n", + "def compute_layer_style_cost(a_S, a_G):\n", + " \"\"\"\n", + " Arguments:\n", + " a_S -- tensor of dimension (1, n_H, n_W, n_C), hidden layer activations representing style of the image S \n", + " a_G -- tensor of dimension (1, n_H, n_W, n_C), hidden layer activations representing style of the image G\n", + " \n", + " Returns: \n", + " J_style_layer -- tensor representing a scalar value, style cost defined above by equation (2)\n", + " \"\"\"\n", + " ###Β START CODE HERE\n", + " \n", + " # Retrieve dimensions from a_G (β‰ˆ1 line)\n", + " _, n_H, n_W, n_C = a_G.get_shape().as_list()\n", + " \n", + " # Reshape the images to have them of shape (n_H*n_W, n_C) (β‰ˆ2 lines)\n", + " a_S = tf.transpose(tf.reshape(a_S, [n_H*n_W, n_C]))\n", + " a_G = tf.transpose(tf.reshape(a_G, [n_H*n_W, n_C]))\n", + "\n", + " # Computing gram_matrices for both images S and G (β‰ˆ2 lines)\n", + " GS = gram_matrix(a_S)\n", + " GG = gram_matrix(a_G)\n", + "\n", + " # Computing the loss (β‰ˆ1 line)\n", + " J_style_layer = (1./(4 * n_C**2 * (n_H*n_W)**2)) * tf.reduce_sum(tf.pow((GS - GG), 2))\n", + " #J_style_layer = None\n", + " \n", + " ###Β END CODE HERE\n", + " \n", + " return J_style_layer" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-780a4420d8e9eeb2", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + }, + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "J_style_layer = tf.Tensor(14.017805, shape=(), dtype=float32)\n" + ] + } + ], + "source": [ + "tf.random.set_seed(1)\n", + "a_S = tf.random.normal([1, 4, 4, 3], mean=1, stddev=4)\n", + "a_G = tf.random.normal([1, 4, 4, 3], mean=1, stddev=4)\n", + "J_style_layer_GG = compute_layer_style_cost(a_G, a_G)\n", + "J_style_layer_SG = compute_layer_style_cost(a_S, a_G)\n", + "\n", + "\n", + "assert type(J_style_layer_GG) == EagerTensor, \"Use the tensorflow functions\"\n", + "assert np.isclose(J_style_layer_GG, 0.0), \"Wrong value. compute_layer_style_cost(A, A) must be 0\"\n", + "assert J_style_layer_SG > 0, \"Wrong value. compute_layer_style_cost(A, B) must be greater than 0 if A != B\"\n", + "assert np.isclose(J_style_layer_SG, 14.017805), \"Wrong value.\"\n", + "\n", + "print(\"J_style_layer = \" + str(J_style_layer_SG))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " J_style_layer\n", + " \n", + " 14.017805\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 4.2.3 Style Weights\n", + "\n", + "* So far you have captured the style from only one layer. \n", + "* You'll get better results if you \"merge\" style costs from several different layers. \n", + "* Each layer will be given weights ($\\lambda^{[l]}$) that reflect how much each layer will contribute to the style.\n", + "* After completing this exercise, feel free to come back and experiment with different weights to see how it changes the generated image $G$.\n", + "* By default, give each layer equal weight, and the weights add up to 1. ($\\sum_{l}^L\\lambda^{[l]} = 1$)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Start by listing the layer names:" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "input_1\n", + "block1_conv1\n", + "block1_conv2\n", + "block1_pool\n", + "block2_conv1\n", + "block2_conv2\n", + "block2_pool\n", + "block3_conv1\n", + "block3_conv2\n", + "block3_conv3\n", + "block3_conv4\n", + "block3_pool\n", + "block4_conv1\n", + "block4_conv2\n", + "block4_conv3\n", + "block4_conv4\n", + "block4_pool\n", + "block5_conv1\n", + "block5_conv2\n", + "block5_conv3\n", + "block5_conv4\n", + "block5_pool\n" + ] + } + ], + "source": [ + "for layer in vgg.layers:\n", + " print(layer.name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Get a look at the output of a layer `block5_conv4`. You will later define this as the content layer, which will represent the image." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vgg.get_layer('block5_conv4').output" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now choose layers to represent the style of the image and assign style costs:" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "STYLE_LAYERS = [\n", + " ('block1_conv1', 0.2),\n", + " ('block2_conv1', 0.2),\n", + " ('block3_conv1', 0.2),\n", + " ('block4_conv1', 0.2),\n", + " ('block5_conv1', 0.2)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can combine the style costs for different layers as follows:\n", + "\n", + "$$J_{style}(S,G) = \\sum_{l} \\lambda^{[l]} J^{[l]}_{style}(S,G)$$\n", + "\n", + "where the values for $\\lambda^{[l]}$ are given in `STYLE_LAYERS`. \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 4 - compute_style_cost\n", + "Compute style cost\n", + "\n", + " Instructions: \n", + "* A compute_style_cost(...) function has already been implemented. \n", + "* It calls your `compute_layer_style_cost(...)` several times, and weights their results using the values in `STYLE_LAYERS`. \n", + "* Please read over it to make sure you understand what it's doing. \n", + "\n", + "#### Description of `compute_style_cost`\n", + "For each layer:\n", + "* Select the activation (the output tensor) of the current layer.\n", + "* Get the style of the style image \"S\" from the current layer.\n", + "* Get the style of the generated image \"G\" from the current layer.\n", + "* Compute the \"style cost\" for the current layer\n", + "* Add the weighted style cost to the overall style cost (J_style)\n", + "\n", + "Once you're done with the loop: \n", + "* Return the overall style cost." + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "def compute_style_cost(style_image_output, generated_image_output, STYLE_LAYERS=STYLE_LAYERS):\n", + " \"\"\"\n", + " Computes the overall style cost from several chosen layers\n", + " \n", + " Arguments:\n", + " style_image_output -- our tensorflow model\n", + " generated_image_output --\n", + " STYLE_LAYERS -- A python list containing:\n", + " - the names of the layers we would like to extract style from\n", + " - a coefficient for each of them\n", + " \n", + " Returns: \n", + " J_style -- tensor representing a scalar value, style cost defined above by equation (2)\n", + " \"\"\"\n", + " \n", + " # initialize the overall style cost\n", + " J_style = 0\n", + "\n", + " # Set a_S to be the hidden layer activation from the layer we have selected.\n", + " # The last element of the array contains the content layer image, which must not be used.\n", + " a_S = style_image_output[:-1]\n", + "\n", + " # Set a_G to be the output of the choosen hidden layers.\n", + " # The last element of the list contains the content layer image which must not be used.\n", + " a_G = generated_image_output[:-1]\n", + " for i, weight in zip(range(len(a_S)), STYLE_LAYERS): \n", + " # Compute style_cost for the current layer\n", + " J_style_layer = compute_layer_style_cost(a_S[i], a_G[i])\n", + "\n", + " # Add weight * J_style_layer of this layer to overall style cost\n", + " J_style += weight[1] * J_style_layer\n", + "\n", + " return J_style" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "How do you choose the coefficients for each layer? The deeper layers capture higher-level concepts, and the features in the deeper layers are less localized in the image relative to each other. So if you want the generated image to softly follow the style image, try choosing larger weights for deeper layers and smaller weights for the first layers. In contrast, if you want the generated image to strongly follow the style image, try choosing smaller weights for deeper layers and larger weights for the first layers.\n", + "\n", + "\n", + "\n", + "
\n", + "\n", + " \n", + "**What you should remember:**\n", + " \n", + "- The style of an image can be represented using the Gram matrix of a hidden layer's activations. \n", + "- You get even better results by combining this representation from multiple different layers. \n", + "- This is in contrast to the content representation, where usually using just a single hidden layer is sufficient.\n", + "- Minimizing the style cost will cause the image $G$ to follow the style of the image $S$. \n", + " \n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.3 - Defining the Total Cost to Optimize" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, you will create a cost function that minimizes both the style and the content cost. The formula is: \n", + "\n", + "$$J(G) = \\alpha J_{content}(C,G) + \\beta J_{style}(S,G)$$\n", + "\n", + "\n", + "### Exercise 5 - total_cost\n", + "\n", + "Implement the total cost function which includes both the content cost and the style cost. " + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-55270d5342632932", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C4\n", + "# GRADED FUNCTION: total_cost\n", + "@tf.function()\n", + "def total_cost(J_content, J_style, alpha = 10, beta = 40):\n", + " \"\"\"\n", + " Computes the total cost function\n", + " \n", + " Arguments:\n", + " J_content -- content cost coded above\n", + " J_style -- style cost coded above\n", + " alpha -- hyperparameter weighting the importance of the content cost\n", + " beta -- hyperparameter weighting the importance of the style cost\n", + " \n", + " Returns:\n", + " J -- total cost as defined by the formula above.\n", + " \"\"\"\n", + " ###Β START CODE HERE\n", + " \n", + " #(β‰ˆ1 line)\n", + " J = alpha * J_content + beta * J_style\n", + " \n", + " ###Β START CODE HERE\n", + "\n", + " return J" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-81f82cb4147cc92f", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "J = tf.Tensor(32.9832, shape=(), dtype=float32)\n", + "\u001b[92mAll tests passed\n" + ] + } + ], + "source": [ + "J_content = 0.2 \n", + "J_style = 0.8\n", + "J = total_cost(J_content, J_style)\n", + "\n", + "assert type(J) == EagerTensor, \"Do not remove the @tf.function() modifier from the function\"\n", + "assert J == 34, \"Wrong value. Try inverting the order of alpha and beta in the J calculation\"\n", + "assert np.isclose(total_cost(0.3, 0.5, 3, 8), 4.9), \"Wrong value. Use the alpha and beta parameters\"\n", + "\n", + "np.random.seed(1)\n", + "print(\"J = \" + str(total_cost(np.random.uniform(0, 1), np.random.uniform(0, 1))))\n", + "\n", + "print(\"\\033[92mAll tests passed\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " J\n", + " \n", + " 32.9832\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + " \n", + "**What you should remember:**\n", + "- The total cost is a linear combination of the content cost $J_{content}(C,G)$ and the style cost $J_{style}(S,G)$.\n", + "- $\\alpha$ and $\\beta$ are hyperparameters that control the relative weighting between content and style." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5 - Solving the Optimization Problem" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, you get to put everything together to implement Neural Style Transfer!\n", + "\n", + "\n", + "Here's what your program be able to do:\n", + "\n", + "1. Load the content image \n", + "2. Load the style image\n", + "3. Randomly initialize the image to be generated \n", + "4. Load the VGG19 model\n", + "5. Compute the content cost\n", + "6. Compute the style cost\n", + "7. Compute the total cost\n", + "8. Define the optimizer and learning rate\n", + "\n", + "Here are the individual steps in detail.\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.1 Load the Content Image\n", + "Run the following code cell to load, reshape, and normalize your \"content\" image C (the Louvre museum picture):" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 400, 400, 3)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "content_image = np.array(Image.open(\"images/louvre_small.jpg\").resize((img_size, img_size)))\n", + "content_image = tf.constant(np.reshape(content_image, ((1,) + content_image.shape)))\n", + "\n", + "print(content_image.shape)\n", + "imshow(content_image[0])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.2 Load the Style Image\n", + "Now load, reshape and normalize your \"style\" image (Claude Monet's painting):" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 400, 400, 3)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "style_image = np.array(Image.open(\"images/monet.jpg\").resize((img_size, img_size)))\n", + "style_image = tf.constant(np.reshape(style_image, ((1,) + style_image.shape)))\n", + "\n", + "print(style_image.shape)\n", + "imshow(style_image[0])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.3 Randomly Initialize the Image to be Generated\n", + "Now, you get to initialize the \"generated\" image as a noisy image created from the content_image.\n", + "\n", + "* The generated image is slightly correlated with the content image.\n", + "* By initializing the pixels of the generated image to be mostly noise but slightly correlated with the content image, this will help the content of the \"generated\" image more rapidly match the content of the \"content\" image. " + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1, 400, 400, 3)\n" + ] + }, + { + "data": { + "image/png": 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RF2obgzFbNeNQ/JbpcYeu5XOWN5GlJXePFq0nhW0tkJ2UpJmAdmJQigLCXYu9IzEeNVHKmNnBYGXGbPwlvfqUv1xc0t8fiKMTRCdGXGvk+xrJkug1ZD5OVNLExL/MMWKT3SIhO7JJdxmKMiepLYK8xZlzzWT7GtORyHyLK7asxhrq7Zy6aBM09pSiiGDP6a1Npk6Tk9NHzh/OKZWIdNNkV2+IBnv8zZwXgwzFPSHf1RgXFsu7jB9udyzcBvV4SZp4HG3mOL0IgSE4Aqu4IF83cCZneL0pUSdG3pkYQs3zTqdQ5rwcxxQohHsXtZUSZk8Y4ZCyltAONQvX4XyoIRyMH/XvD2LFoCALBMqUYJbjNXbI3zfpZG0uqiPyQ4OTMKRWdgwlBXVncHIYMPVLmPXJjHNKIcBVP6BtY7r9lEgSuFJUhtmGhnjAcUw6/h2mOiXbZtyoNsu9yO4XKWcbESPe0y6PIe3zJl6y1X26Ny063ZzEE/nzbc5zoOBlTYTdBV5a8RxP+OO2QvuyQauyGHxtQGNFHZ1TOi3afRehU7NZhOz9a+qLD9jBBLNrMys2DLpwmBrMixJvsGGrlTj5hr7lsRFeUz1q9JMls7RgVR7x4D0TiCpaFFIJJWfTI1qSQjw7wooyWnUbU04JymP07xL69YYvWTCyQrqqixGtSRc7Lm8veMxGzLsNSjUg/6bmxTbhhTmje3ID3V9wceQTRwrPpsSLhxbN6QlJY0n9IcQNf+C6jqiWMsLrEMM9oxPpaIVBcxHSm51yqa8JtwGoOkaskpYF31yf0mnBqy/3uKaKf/8RPV2gnYgIcQM/qjHnHzEkHfUI8iacdzSqes+9prBeWvhZhnAcI1rvQFqy/yARP+4J5hukVypZvOYie8RsiAxGxxhCgPpZxZQbPIYut1FK0ymoOktaxg4xibgU51x8XiKmOflKx1V0ZHGNJOVIUkHEkr9r3ZAsbeyioj7+imJkkq1jhH9ccrLIqPYlzWhDumyR14/siwuCboxVyhSfjjnPmsx7Iw7bBaU4w/avGcomAwyOGzpS7SJPbeIjkRvV5YlHnvcWetxBNA/4h4Ssk+E86nRdmaTVQ1hEFNG/y/ePGWXuI4QHzE85fWFLs5GSCy+QtwGyl7APlyySHykD+Lc4O/AvUooyTX0IL2bEYovgi3dY0pjlNEdvb9jrAnLpsfdlirRDvklo914i+dfcVQFFZNG67aKKMsmvVYxxwqIlsdbhj/c9HsqEWG3R8Vz8dMQouqYva/xu4qOfiCzTM6JDgNhYkekF1f6SzEop4h/Y2BpDKafXVlgdVpi6T3Nh0ywVfGHAZjzDiGOEpIHMgaSRomQPbFZNSnlP3+xiB8fsJyrjE9BmEZncpNAaOMKMjqNyo2n8WXFHkn6NeiXx9BCSVipSnBC93vKr9YaTw9es1S2XvkqvPSQ+/BohlfjjzhmT9Qzr64rdpwYvY4+wcU+xe8lCWTO/vqNsG9iSQjLM+d6+Z7yVENSEuFUwXwasrtqMihFL+RYcmTvVJEosXinP5FKf3zkWR3mG6rbYl3ui9QsY3pBNFLJlQB1e4jzF/KorIH3TwzcW9B5rpjmYks8HsSDvgWs32d2+YZeFqK9aGHLIbGKjTQPEnys8yh5y5tOnQypMUESXi7Jm4hds2jpyMaXo6qhvW7T8CEFsc64aVPqMD4ea6tgkLbsMpgt2SMhJRHmyoNBj7PsmlWiSP5rclCe81J+Zf1MhLWyidYQWHXBHJTke7vcCG0NEqTNGaoO3TzpWltAY2AT6HiOIkPI5SvOIpCWR5RlqrCI+OciDLfvuFCcUUXo79DxgPpJ4c9fgaT2nlL9EOZlRGgrCV3ve7lQMIUQaychGjO6nHE0EGBZsVzMi7Q2Nv7NCzD5QBH3iQ0p0NuLsPwhZbg9Q16h1jVGu8O0KsQwQqgmifk3Z7SLJHUL5QF4+/ah/fxCVgJzmNIhJlybWg45XHdMRa/pnPvuGQdc8x9Rr1FFG848WdK4ECv+R1C454cBL0UQ2YiqxYH684pCumE5FBHL+orxDbgdI3jneQkGuAgwtITuDY9NEaTTpzkEbVeCnLMIDuS7wrEzRpREdpYtQ1SjbNdQR+rDJU1/meixzGFYcORGJ3qBXbHHdBKe6oyn0sfSU09rFEwMe24/Ixp6HXOODnKB0CoQkQAlrDnGGdFjxsVIRewXT5YbK2xHnb4nut1hxh1f5CbGUYBoCnilxsbul5bUI4yHbyQw3FliHCo1qxV0kkDt94vyWuBBpj8Ykm48o3XuOlgqXSkG12LOetiive/RqSNXPzMs1O7mmaM6x8wmt3SMPk5jNfo1nZwi5QNEokXSFfuOaF40EU/GI3DFVf07d9jH8mpb+iD5TicdNii/f0pJaaP0OT6rNbH0P76fgP6C290BOX/dpfKtyuephKw51+HP8g8wn/cAi9jnkJudtjS+dHiP1Nf3DKWpa8pjucIpPPObfMVE6rKdzkuSGZL4g2PdJDjWSIDB6lonFEXZXRDY1MuOOwemfc+/O6T1aRA8OahLDscHqPiB71JE6Ge2sJD6csJJ1UvU7di2wlDWy7rPRBIKkw2ook60lBtJr7N4J1TcZq0OHWvIRlQCpEnAMgeYi4yFVcE5fs25uCGWNUkrZld/ysiljWRVWLnDIBMbyG7K2iJsd4XkmCBmlXRGkPfpGRbEZo+UxwX1E8rCB5zfY+RFmIJOum4RlB09xOHpnw0ZFDUNKa04tnfyof38QIVCpBU9JTdkwUQclxWZEuc55OrymoUByvUddg5KMMcuEfdMijEDLRYJ5yjSPCEqTjZ/TyhyG4wjPnNCwJNpBjXDIGacSD8enSMN7zK9lIjlknvS4efSQ7BA9EhmeD2m6I0z3A05bJF7pnByW2Mdb0r2AXTeY73IKsyAyOkjuHQvRY9m9Z1bb3CRTtlswnhKGtYstqQRsOBd6nG37XOY+Z4WEGeuc+AFKd0gddhifqfS4JPErCmdPLKbY+gjJ2TN4F2HvI35+mOMeaj5KT9wVbfxEZnD8xHy45uHoE1ldUV4NGb26p9VU6PVtnLikFZ6jimcET79EHojsyxaFJ9FrrTjrL0n0mkoYoIp3KEoT4ymmCGzalyL+WRPzeE2ruKHe7diudrRWTS5lkN61uJ8WmMYt7axAtCAdNzg8mYhPW4qpT8dokw5qusKBcZaiFiq9Xgn2ADZbcAMqaYejPWBYHxgLe9wvngkTFaM9wsXAOL3jMG6QyjZZ+EywrcnMNTvtgqWko/sNrMcHvi269HyHq4HJ8+keXUmh47Ew1pTxjkW+RchCer9MWWcl8nOF0Jvg9QKCtIW9TDGOz4izJw69BfXeo8xvqZ4PvJFPUHSJdRlz+OgxuPeoRQ8t6/L0WiDljt3ywKAqcF/YlKXLcghG+4jIk5jZIYmxJ5nd8VWxZafaFOIayfw1h/sDqdGkUlSOfqOxraf4vS95EJrMpTbNhwWF+MzGe8NHVcf72Q5XlhHDA5L6BlmzkDKNPRcYTkKuONS1zqGs2NY2YdQl+SFHqX686P+DCAFJrFFlFT3wSSuFTesDz10ZO4uZPKtQ5shajdh4RmqZDD490B2B0OpRH7vo/SaZY9D40qLKOxS3rzmLVV4/+bgtg2Iq4Igrzq+/40+NA3pWUGBQDDe83vkceyXDgYu5ayHMFJqZyPb0DPG1hFqFuFMHpd2hjOcMcokie0CaKcieiD2BZqBx3Q2IX57SfeHSPGoR2T7CZU1XvCA8GKyl77khIdFSOlLAh0VJnN9SSQ9so4JpahMul0BBKz9DqRucJn3mZcE2lvin1pJ1HmLvWihVE+mzjC4WDMUWl+se5rZN9K7Lkj67fM4PRsJDr2bVX2CYKUI75wfzM/L9jr45RM9yVquas3cuxxMHPb1Emw+Quj0UXSJKC5z9HM7AW4dMdJFYfmba0fjeVFl0nugfzSl6LR7aI5SNRGNxT503qBoD5HOd1XOPQ6lQNnWqjoEnJTyfyhTpgoAe+VOEoZ4QiW3mpQ6+QZb59Bx4UxzYfgWZOuDRv8Z/ekRoXrAp9ghH32Aj4Zw1yUSF/VWPdFQQZQ228YbjPGIzKNgsPWb2v8f5fQNVeEP04BDvYsqyIO/28R7bWI8rzChDkwxexgon7ppmOEQ5tnGPxxy6Ju/dIbEVoZVtNEakzQ2RmCBrj4wexyRBzWgS4d95iNuAF9kaDiZvyy2vDk8Yuz6SvKY0THyhgyAazLZtTqYNFo0uxiJE9W54/kZg1gooWz+wtOcU25Ba6yAe/n0aSUmoGSTZmHYYkXUHGNGccPiRpAtZa4Pht3C6Fg/2CO1nx0hfPFL1FpiNFvpfo/ofRAhUmYJkuhS9imo9Jc8spPkpyXTPoFcjliFxatHwdG7/aUSZphRijLFSeeVWVNcZtrugMksUdc/uQmajvOSaU5aqQ/qLjOubBvEa3t4NWX/s0rne4coWy4bFUhmSR3NW2ZqNUxFsY6onF0NtEzYMhq7ATk2J3Ab7tokUdOm2A9a6j9deoMsHeukVw08yQWnxuF7Q3GhsNha/ee0zMTXY2FS5w84omKUNpIbJZDgnfWUQaTPM7l8QSfDz3yh8mfv4Usm62rB/k+O4CS/MUzqehbgX8FyJ5MolXK7xjQO+dULRCWikf0n38wrvuUG/yDhapAS/aVC0j7iKdE4Of48vTBd/vEWRzyiDLslRjN06cKKUHLsptqhiHFSkvUNeZiiP53w2uyRKSq9u00i6SJFIkX7B9LaBEUdUZkbkyNjiGa8yh7Ty2G10HLFiNx4SBwWOGLPNgV2OevSG4kSiNFpMq4jOTsU8E5ldquSigPQYscxUzprPtEUJwx9w5InIYoYjO3RaBn39iX5UobTbDOOKvXrETjJJ9BHTloXXKmhfFByFK9bdBo3mAf2rO/LtCSf+MWePGlFjwT4XsNWQvQz5xECVv+aQCui7B9xiTlX79MMVNlt8Q0cyHjESjzEplWiTyndMW2NuTkYkUoPZRmbjLHkTPuHMfNbit5wFY5znlKpcUWQ+6z+fMdZvoSlgNx7QeEUz/DNkv4tzM0D63mSgh4w6V6xehmzTt7hywnjaQ304EAcn0LMJtYzuPzmj2CScp0OsfZ9qazP69Bax9jF+3WB/2NMyDErxv7Va+J/zBxECZQ6CM2dxa5H2XDStSxaK4DrE+xh1PKSlSkzSNWfnPvm5RzEbst7XXP8TmfXkALWKIQ/xu1uUfciAO1z7I/1tQeOpj/VHG7KrEEfvoBURYt5Gf9hCKjNZLYm2Q4qhS13KLFtf4+UfeN7NqW8M/IOBZAn4A5HpB5GWeYLeV/ji/hXt4oz8rkHlL3FOO+TBFxxGJuQp4k6i/V2AN43RXw5w3JzL3KLR+Exn/MRVJNB8DOn86gv6Uc42kphoV2yOKxqqDeYLPFcmrWqe6wyxaLHojpg8xzSbOs/SiHJSUjolR2FJp/ELqhMBJzsgxTlTo0DohtTRPb9K/zHr8D3/KJmzOmT4hU+vb1MP3nAfyvyjq5Kb+sAqDFm8jlhMwCn/lEXyGduMedFv0h1UiLVCljSpVh7HAdxNVfaTOYreIuuoHFprNo6J1RFJ1ZTtw2+wywvSicq+IaMeSpplhn7YkMhj9geDW93hRpApwh8g1Ek7GokHdWZhix3soste8Bg8NOiMUh7mEavqgrthgnExIGuMWCoCR78waZZDms8q4fcJfJeRGRbbdUJcFlS5yHEk4nset8IBoXbJvgL5jcVFarLVCqYuSAONqaESPnl4ewPRrLEiB9XfIw1g5N6wF75Abr3kcPHH2OEtvTpkE+0RtYrE7rBodBDEiJ34HZuvI1ZnDRpqH/HgcvK6ZG52mDx8ifHul5S7ig8bhWMxwKuWOFuT9G3NJvpMf5rjlmsScpLGkpIFc23B/r9WODmV2TczAuEMSYgRv7rlaC/weNLCj1t0LzS+KQ1mps/c+fHZgT+IEEAoMJ4P9O0Iv2sjHq7B3aG5Ko3eFavGluuyoPN8RLT8GjlpkTYthJGE+uIR51WKm95jUlM1XpNu22i1TJRd0A1uUfwFh31BVg2YplsepDmhNyHr6iTFBs+KeNBEek87NCmiq4gIpzrGPiD9ymOat0jfQvhJ4MVXS+SXz7R9ket6QZh+xBDAOXtC/G5G2/jEi8cGfs+hPO2hJy7iLuD54KMeVNLSZq4cc7cZsHcvqB8TguEz4a6L8ccCy9N78timFcmMxjuUrImcHujvPBRdoa+WWMcV4w8pxlKhW5xgxRG7SqawUrLsBc9yn12rB2OV046PZbZpxUdYSk3D6/OqdLAaxxzIkFdzTusmJ4s+jUHCtOMTfm8xPIG7l7/CaZgshhW7TUQ36xPI72kWoLyZEr2a4VotXoTfsOoved2a03zss2kt0PyYp8DiWNdI/QN1rGMfcupSIr+5JvMc/MZ7HK/A2lZ0P+dU6xOcmYrhS1SShfmbV9TqBuHinpa+RPlFzaF0qBc5g8pGWMko9w9EP9zw7X5BdhOyilZwnuGemdydL9HNd+hntzRIQfV4zBr0aVN0Te7LLbsfTgkjjVh6QOpucN7vEedLwpaJ1JaRezap2CWofbbbEqEUiKUvMTcP8DjDfAfZ8Oc8Cxme8AONxjV5GmEINrtNk/3xiIU8x1UUnlyN6t9ZcXDXGHKGra7Jehtqb8roTyKaHZtteMbsxMVTUg43Z6SFwbrXo272aewktE6GJ+45HySEQY7RqXGmCqHvsF6L3FUZQr0ksTaIh5q3qYGUtCmdTz+q3x9ECEgazLUepu4gB49YSgNvLKDELu61wLjSicw2mTZhK96zWcwgucX0fIRUIosF5pwyy+/YFRMQHpipElVH5nNDJR2IfLVO6UQDTvQjpPSC+LyFl84Yj0u0IKHffstkKFDbHoNsgjqH9rBgeVhxuNrijTT60YHJs8Hi4xRBkJCkKTu5hdCs8VcdItNjs5sSulu6fkBYP1LaLnlLYqxGNDdz1rqKER7RkU8wkpjAkBk6x0zbx8RraGot8m3IvqPzVm1xtXhE0AW2noiv++xWU9Slw1vadFoRXXNHd2gihiY3wYLl+gOVLNKRTdprn839AoqEtCMQOTrqXiTfOmzkZ9oNibVmktYp7WbB8rrNlw82ZycmkjLh9Vqhqq44S3p4gsM7M6RWK4oXIxrtJtXmiMVeYn+Z4NzL3D6PCewn/jhYUNXv+eXRI+guevmewWCOrX6F+MpEuBgibwNKo2Dx0KVUKrZDmZaikh1ZHJoSR4nI+u/csGiIeGLJrpIx325R5B6tgYU/qJFqj2l8wr4t8ZdGk+0uYyeaFO8LjpIWL0UN09ghmi52InFZb+nJAfHtPY2biJao09XfEccbJqnC8+qSXa/GPTEwQ5ndZZO9VjLf75CkPmbnklWgE84+0O184OJ8jzEoOX66xXJrTjsDNpVO6/gI/9bgwos5qSzEmU5cSfS2a7QHj6g8wlk20boiWXvJxr5i+lzwvRLT7q1wp7/jvajT+XKKX31i+JcRrH/N87lOsD5hXrfZdGc4vo+0GWIO9yjCFK3/Bvm8z1dGE42AZ83kaHXP64VC17d+1L8/iHUCamWgKxKF6HAxtfjgtjj2rzFkgcfTHYnUoIg22LaBGhgIXkQkSNTme3bqCfahYj3QGPywxPuFhqMEUJ6gpBKLYZ/iacdybbI426FZKW3bQf5dQS7uOHMDVmsPqW3wg9HmrPhIkZuklkUnmKEQULw1WH0jY0snWE9PXBqXbKIc9asmWRSixyNWixNk8xlVarE8aVLWFxjPj0hZQdQ6JWlOaEUm2aIiEkMGTdjsj/EuD0RKxuVuy8R4ILBUfr4O+cEuaZgJ8qcR+klCL7e4XTwjWyqhUeCHjzhSm0XxyHxSM+4e05U7xL+b0W9aCOWKQyxyOAU7hUy9pCEukE5FglVMS0kJphF1z2BpDKgji66Y8Cg9UFtHsHKJ9AZHn2KkKiNo5NS3DqnwBVpwzT44sPpS5CI2mOcxHcFibN8QWZf46jmFHaNZM4xAQbnostVaHC1y7oSMA0eUdklztqYzDhB7Go1tk9mxypcPzxyEPlGqsr29wZIg7L7BXz6gHC2pbgySUMHtPfE5yzA6M3Irp1GU4OnUBwFdVXle+TQmbeRLjaJuUuKz+V2B6d1je2d0TY3AN9C/tLG0DGU2Y739c7y4iXqwmGxKmulbFOWMxPIw1QNOukXqLGm2BcTp12yDGgoVyRlibu84KH1arQv0p1vqtGDTadF652DvHxj3HQTris15yNgfst+tafy84NVO5UMSUq+6LJwCZTvhwj1BqtYI84KGO0b7wiNXQ5qqRO+QI+wiEHIKVaTTXLIKtsxkC6d+QBds8nc+2+EAzTAoDI8n9Yb8x0cDfxiVQCWmeMmA4nZJai3pixHNloDf6NIftBGzOYOpxvzwGt3QkOJjiumKm6DLNvfZ2C7Npo9uBwgUhJ0XTNv3PGXvsZ9KDK9k1n2JoacYVY8o2eG7DofghPsoxLdl0k8S3UXEzfKIQz2iI2xI92ekLZPhmYA0CZCciO6ZTGbsEZUDRX3KqeziTwU6P19x6mz5Su7xZr4m3uxpHq05FnMuE1DXK2gu+NRrszudIh5MrHzPbOuSbXZ4gsiJ4DGonjC8mLFr0dPaOGIIs5xpGVJLOlET+u2A1lWXp2bKnewgGy7vVzV/kS7Qm5ccHldsQg3vlcfZrk2Vp4yjOc5hy+NuRdFPkPcOO7XPuNSxj2Hnlrw+jblgj3dX4goyr+IxhVMQHErUoonl3tHwfkeiPcPE5oV8ytW9gTULSeyKiaEiphL93Q7tVwbzhYfzdMe8UtlsxrwVIRI6DPU13eUBNT3CW7tkc5+ieiCcB1zrIrv2jljOeF0PkB2XhibQ/UXAzjRJ6jvkNypxD95gcNYNGSkmnegJsSvQ0UosRSZwBaq/f8MHu0VdPZPH56hnX6FefsXsYocqrAiTktVTSfqQkWQ68rZJ2BTwyyVBL2ablAT9Bw5FipHW3Dsb2kmfTeAQ5h7ZfYv2/onEXBIdb0jEBbt6zW40gJchg2TEoZ1RvugQh2Oe5BIjayCVM8qfw9OhZpOcIIUWA0mjEGJeXyyJFQWvaVNoJln9gqmsIl//Gd2Vx5NasdEknG6Pujhj3Z6zPolRXw3I2SEYNf6oz7GqISsV86bC5mAQftP7Uf/+ICqBPK3xDzN0t0FZl1ROzMZ8xe7RZFdHBEOJoMjJjIjcLhj2EuLwDMvIkEMN0WmQfzIZjnU2UsFzlBIkLZTtGru6RznR0bNPtFYNxuk/ITo/B0JWYoKNgZ7KSMdrurVD1Owh+wHOTGcr6fTFNdlNzUyUaAkyXxh9xFDmt4OCF2uZgznH7pZ4D0OO0xWPPXCcDDmZYi8uWPf/MVLV4vYw4ItGTa/3Pd6ywCNHbV3QCyvmo6+p8wfuE4MqGyIvQtSewfbtnAURRX2J/7Al7Au0a4HMX1MYBkexzCFQWNklRjlEqhOOnGtyIeDRO2V66NG5WlMHLrtlTif/km/8PVvnhp1WcBq5GGaHpn+LL9Rs8jGbusPRqOQpekK5XtG8GjNLSoxcQB+bWA8N9vaQ+Liicdck7aYU0gxpfoN71ucm+g5XO0ZXQjQB0uYVaVKhLJ7RGw2m+gNTAS6qDkFjQCTdM2j3EaxnikmBMTMxdJHIFnlaOWjNHHlxT1B5RKaF1bHoCgHhVGMV1BSrGu95TNQVGcsKiXLLQ2jh9mK2fh8KhemRjLV/jz9pcUtEe95EUUGt76EloFkbgtWXJC9qJF8juIlwz2rUbU0+8UgNkUCKOVTHDOIWSUdnMjvgXdo4ewiefXTzgKBfIGw1vNktUSqjddYMFhVzpctC9jnxA/bzPaZ6zLmnEMqwa97jt8fYxa84Eyo2/pbFTMM4bqO1ZNJ3/xTRbWEnOn4W4p4UJLLN5DRHSCKq4pnC+gXOYc5Kq+iGGg/SjithgPN5SfHLgraak72Hw4/49wdRCYiqQX1p4nW71P4x8xsB7fsNcnuPbU0QhB3deseL/ZzLfyyS7kLOMgtt51DHOmH+X2PFt0y2MUzPMNYmPTT64oh4MGK7F+n2FILyiZ1+hth0mCYWdfcTZVenbKwgC9laLuXP9rTP5kidGfWXMecxtNtdfn5UookwDfrcKmtOq48UyWeazyOO7B15+5n7WCKI7/mcpwhSQNp+hyi0yBoC3pFDO/CwlzDJOviCDog8D7ag/4Yoj9EkgW+Emsqu4XGP7jgsim/Q5B2Wt6FDgqcbyJlDvdBpbR+QBJm2GNI8/XNeSAG9xksiw6blqwjFAnfpc+wfuNJr4j9dkl5mDB2PtlXx3XHG0ywiNQpG0iN+uqBUSzalxP7wZ0RGk+eDSWgN2ZypCNMG1bCLOfNo9jZMmp9Y6yv0uiQ/9sibOqPRl6DJqFciYzkkcQJ+Row3muPZE7qNK4x9C3njcyxFiIM9wbTB82TI4MFm31L4UEwpMg3zqMa4jaAOkFKDi1XJMnhGsjaEecxRS6IZxgxGJfWLksffpaiHMa+7NpZhk+5CevIWYXrF0nM5Hq95vVCJylt+s9kR2iqmYLCVXmEKNpLqYwoyQ6+JJUNW2Ig1uHrClAvC7g+spXesH8FVA/R1wNNUZ14b+NIXuHGJu52wjyw2X/d4VwYEu5znNMT8I4HgLKDsNmlqEqoUEJgpyfWI802bRD5jN8uYan2OfyZipTHF8kDr/AKz3Wc2LhD7Kqr0GsED9bsBWl7zMhvQWN+T7mzsUCKP77CqPRm3rH7eJp/oaIWI2vzFj/v3b071H6escvRHg/eba+LRewYDeDIDgmxH5blkb7vEiUxUCRRnJdt8ihfGdIRHamtF7/qC1kihvIZg+ox+KdFLXDTTZC+eo8113JWK5HaYmXN8S0KKcqKwix4esWi+QsDGzx3c31W8O5yw0U7o34TcXq4QWxlOnDMSj9n3M1xXp7o0aKkDMstATQ6kqoU3EriyRgyMr6j9Ec19RZQdId6b6KWJLSrYuYMwUcm7ClXzd+jEKGuP+1rAyzUiM2JgxLgvHzGjt1jnC8KTFMHt8CZv0Nu7JEdb+sMHsjOd9QsRvRLpLVuISsHz7R1rPaU07nmRKewbBU/xAW0ec7lY4nwUUBc2dWagXacoZc5ag6lpka4eUNUp6V1JoyMQ6wqekNGRlqhpyrZ9IMluqYMJvYlI83BAXFUou5oXe5vJasguSYgR2QlQLDdETZGgFyCmHYI0Z3d9Q9YQqPUhD/mcwfwKZZfgRSGr3m8w/N/Sk5oMww1iOsfOZIRFi8I0mBU5/axPUu7pD2qUOmWXtYhlg82nDru2QGKLzBKPeOLgdUaItYMttehlItugRSa8ZGh4aF2B84NM9CAyrPr4hoh+77E+FMTdIaXRJGi5OBORQ9nFcH/N+UcJBZW+K2Oqbep1l4NVcpkmlNsWq21KiIoxlmjOdxRRgSL79HsNlOuS2a7LRjghHl0xPz8hqDwa3h7Vu0HdrTD2I0TbY1J2sdWcuKjZkaJlEXKx5bEjosYfeREW1J01tlOgJX0G3pD6wsdYd9FSi1r8M+YDDf9Go3MwUHtdpvmPvsn/hxEColxS/HHI6OwlatWmf9JHGQoQtjAODcZNl8hsEr+YsdR0OuYVc8mnDK5wYw3jsovSkVH+3p7oOCYMFmTjd6zsANc4sFZlSrOLmuQ4DZfy+leUQk5bfoGllTjVjEVZk7WeCAWRq+WKjeyzUlKOn5osV222jEB5oBF+oGPu6Ek2aRgwMGLM9hVi9ZZd5RP4Ja1dhMSO+cChDnXKaoylTyktMEqbP/7Cx23e0axS5N0KeT/lWBOx3IqDo1PkBqOFyjCScUoR7bNK1NZ5sCNui5xt4jFtCDw/5LjTlKAoWBZb9oc2u+OAF/YSvsvIE42Xd1f0rZc8v3rgaaognq/wFYvlnYmhN7H6zzTCHuFblcdGHzF5RfK1yrJMqPYtxHZNZuQMH/dkyikPhU42MqjEJr3q7xHpKc+nLh9eqljs6DUNutopuS8jzsF53LK/HrOvamqthYnC6POCZ82nVmR2vc8kXR1ZnmOqLQyxRSuuWC8tvvddJmaHOFRxNw6i2gRxy2IrYfRFPl81aI4uWa0f8PISc+rx0DHxJRtDuyPQE7QoppctGUk5zUbJ9s8mzM80QtdivsoQPA2/miL6jzS0HCGewNMj8ecDhtNge3SgnW6BJusjE7OukZb3hIFONNzTfXOP8k2F2czxOwcaryqCdZsjS0ayazZKG2HrsSkCIhrIagdtN+dxsWYQaWRXXebbjKwtsGcDy4xa2/LYcvE8AZo1sbFGHYSY24pt6rCe9Imjl+Tbb3lrL9nUMs7DHEtN2EYFaXRHvW7QCFLSvMFjqKGmzR/379+c6n8dElpRovgqYipwEz0QzEqO9j6ZI+Ifanphjit8i+G1yLUdzpFJ6gaolojCgqdcwO31sNQ2deAiGSNiKWQUS5y5fVIpR1BFPq4THqYewx10v0vYuAuWqk6r7dCzUxxDxe4JGE9biCrSg8lr5QNlS8GQbardge+nPay3OcKuwWSbUM4EemIHIcopxxEbBdplH3nj8ubNjPbRHuGzQFC3Ca2UwE/xV30mfsHLQ5uO2MCJwDiUfKUGVD2ZaX3C1JBo+CnaeUh/kzKYCzRdE2knoHy4wPGGpF6DzJ5TfVPROn7Ecff88HSKNdCZDhPm5pRMFSnmDYyRQRS63Fg653KD5ggcF1xbYP1FgWrXxEMYPj9hZRvGrKmSJp7QIFE0knd/yWgd8ydXKTx9RvD+ET3RoWM1uEhDRk6K2oioVu8Z7ET2r/4UuRoi9AU6YQxkpB2L9LzF9nVBbCfsnAEf28+sswtiDCIzRqxLDrJE39JRhBmCd82mjhBbO/QvXFqWx/rhHP2HBE28QW01kWsDxVnTFR9oVmucTo1Vd5ifqSzMTxxmOrso4niv4U26jAWdYPwFeUfDkCrSrsinto7UP5Av9xReQJkHqPoxU3WD9c7mQuqykUTCU0je+KT9HZQem8MRYbylbltIiYgw+MQ2vEYIu6T9DvJ4g9hv0R9uORGvWekBejSlkc/RSHDzHdI8wf56h+a2qL8rka/vqIwmDbtAnTZwpDY9V8PsxcTHAo1qiz/c4jk2UeygOQ7PJzraiUNfNrhYxIitFQLvMNUtZ94f+KvEYlph7ZsEV2tWZYLiFrSfIgq5g7qecv7KopxaLMsdcmsB8yb1P16jXKr4py2iQmN1l1PUGVGxwjI8NKnL1aHEe5mR5hnTskW7zOgMQD075XkxYxg3WE9MArPHrfkdx4FFN39CiXRU+4jg1TnGdkORGrRKB8OYkBt9dNlmpS1Rx9foE4PsYsC+TCndPaLkcCI9InUyVrHN0/2WpvZL5JbDQNuR3o2JApH61KQe7ZjOQ6phh3C+5cnqUexyyn1EZc84jE/Y3QpQx5zrB6o3SzqZQKgVCE0bkh1/kipE4THbhsDE14nvu5hk9D2HMIvR221Ef85BSfCvY9y2QMf5nk23geAfkzkdluIOaX7OVbUmYUEYjRgPP/Hx4YQT00fqhKx3JuMXLrtY5LAuWe/78LmDZLn0lEfcMGamNtmIFqauUhxd48z3lJFJHNnkIxWed3iuxd5b4glHXE1C7v0YTTxGlxOWuUQ3bXHXkjlxQlaSRNzv4D9eYB89IG1UmoLD3vhE7bpkbZHDX+44M0Meq4jkxEK8zZir3xNtBtRphnVoUfQU4mWGv7WQtJDeEWyWIe4hYCF7xEdLIlyEGsLKQx7otP0cyZBRV2sipaLs7FmJXxJmbzGUr7nQY8qDxu2nmLrr4PklkTwjWyf4ZxXF/itUScIT18jTHNtqI9Z75sqe1TajL6755HVw4xkkDSxBZvZpgBDo5I6GGr4B7YnsUUasM5b3Ora8RzmodMyCYjNFSFQyb0gmzbiuQNNk3G2GZvTwh+/Raw/n8ghjVnIQ1z/u379B138UWbFZKCH7xwRpnlM+jRgIZ7iqSLh9SZQoBMWMk/cW3U8Sdatif2og9StGT2tcvUA9lnCymqqp0RsfGN/BILVYIrAUS8z7NZVn49ZnLO0uib3jvaKgBFvKYoNtnrKQWqTNmHebLXZqMniaczQtMQ8lrvEr7Nph3ZLQ3CXxDlJpQPZ1Sf70zIv0wEn9c2bvPG5qlcXxkLzvYR01SYs16ahka8K6tWShm5wVEv2qw9bK2UsCnZ5Cf99nLaYI9gBtL/H68ZmT0qZ7cJGUFoOqQzgYYPZklFjGSkIq+5GypZCkIU6dYjRERkVElpUMTIliVSIJNZ3GJauxywKL5vIrBsGQxiwly+akwpz2sc7T5Qlx2iayDML+a5p/qtDcKzQnV7RbKm4qg2zx/bPMldkn8zfMOu+Ja4H7+hRZTFCckJc7EKMxZbNi+nXK1NtgRUNO5B4nqo1XOpxOZFZ2Tp1lnN7OMJ5DXFem0EEXEgwrIZ5mpNqG1HuLmusIlxYrdUbPgDo/oG4kqtLkTs8wjXO8XY9SbWNVr9kVF/DRY1VJJNKEeDxHfHFDq/uJTbRAX/XpezvGHYmB6OE9N0jvt5xxRmubocod6mRG1VbJZl3k6hFnsUKufLZVwWzVZbIrcQcaxw7IP+vSCmJiz6CrnyPuK5paha9taPc27IMJUeCz641ot/tI1c9xl3u0pKZtO3gCOF+viS+WOIqKexJzCGSqUKb4VuTkYkvaeiI7S9i5Mp+dL8jcU5RaQsu6qGqA7ib4lclHwccKG+RlTBCaLGSBYfXVj/v3N5FXEIQ7wAdKoKjr+peCILSA/zNwBtwB/4u6rrd/XT85Ka3gjH39D5HkAeVTytTpkOxrzO2v8V8M0M02oX8gz0XMu4L16BI9f6LK+2STHKEWsBSXv7M8MF8e8fyFjON7nOXviCUbbSQiLkV2XoNv9m/Ztdq0/32f5LnFLzoQHAp0Y4+sdGkcd/EOFvHjFr+tU7oyxuYFT6OMP1JuOKQnLOoThJbL8kHG6d1gHH1BvfueQatiLxh0vl9QFBcYJy4fxZqGviJOJ2SWSe/0nmXxDZY04OhNxL7SmF4ntJ1r5uEWuw6QNyafjz2csqQsPIR8QtHb43wI2QsXJMsDmWSiqC6hFdFcmTiNgK0ypScFhKM+J4pEQM3nbYOeUCCKMkX6Ozadz2j7b5h1ElzrgKMJOOGQsnoALWSj+5xsU1Z1j6dkSVLrYGeE6TPK0OfrSOfQbqIIW86dM/KDglEqHGkRhpUTazrIaxrGkFNjjc8T06nEvLtDdRKOQom9sWMaJVSKyPPrPe5KY7A/g7qBnM+4UbooI5nOakbHGaAWMdFkh2+OiDY7bhKXC8VCa8esLo5pPGckQgfxZI7xfIS3u2d3NeDlq4T9dIzoy2yOD6xufFLboWyumIsGehaQTZ7JkpQXjZp9dMtxb8+hMMg9k8Jcc/LzI/Ltn/KwjTCKUzR7gjZ9T9dyuFmekh9PKQ4qr/fHzDoVy+WGpl5jeRZVckVW+bRUhSiIUW91DKmikn4DlxrCXOD+TCOYptSfVLrqnhyFINlxZh6RVgn6bE2knxM3cxrZDvNpz+6PVygLk5k/50w/w/n4hmxZse1saKESxCuinUxiP3CiDam61z/q37+OSuB/XNf1t3Vd//Kv2v8J8F/Vdf0C+K/+qv3XUtWw93zKyyNWDmjHz5TWGlPMKH7ZJDoICI8dmkmEFYg89FzsuY6dVyTNGUoVYj4LJEuLR8kk+5NfUTxu2Po7nhsF1rqmaoTIjTW+l1O7Tez4iufdS5Kxw20AuRphTw0CZ8e+vCcp74leFjhGSLKvWOZtLkWDNDhm9iubUzsksH5Hz/1Ey/53KR5KFlOV1mLHJjtwfdSjc3Jg/VxjixN6/gq57tJBQNyZ9PyISi4JgnPquyaCB2FQobhdksRDr0ZofYFyt0f05+CrLJ9fQuHRK2OsUie/sBk1NM5yG69WeJpu0bpfsG//gnBZEAsbkq1IPKqpzRbNyT3N4Sme+0cE2QO2B8pMgvcWUvo9ajTBiLY044j3yoDnqkflHOG+eaa5UTiaDLG+GxH6GuXhnsyDsFSp3AWSZvI+v6Ce9PFfxKSbgNbW5vPTl+yEI6xBTe5doMsuuSyi+AoFDWTX5avbMbXkoisLGnuBIa/YTifspQfUMkRx4RAf0OwXSAVMzCGjw57VPEB5teErv6QQlzTrmMNsgR49YoxHHFohm6eUVJPBTfBWDQ7GgblQszze4eUN2qlMlfcRK49o0sEzHFRvRHDcR5ZdZrcms6RJGebobXCMGDURGLZfkigviOQYOdjSt3OyTooqW6jNBF9J0eclaxm2M4H7bk2pHujKGbZnYnstDrcGU9ug/t2Bkyimc1xSGwLjrEIIB/hvK8Ii4kO2YV7EjO9VmtkFuzdjjhcubq5T2WfcHnwOr65J2inOrUwQ2SyfLuj32zRUj/QQsH2++L2GwP8//yHwn/7V9/8U+J//qy6ojZKmd4NYlThJjLpJyOMcqREhfVZpf/YwnmTe7U+YaxUnqs2wG1O4TfS9wkVm4AlPBO6SyINyc0pbCkHYEz/8DLE1YmPGVKXF1c0nlkILyb9Fi1d4qw+82BrUiUt9JGL/aoBkdOm0LZrikmchRPYy8tGeYB+RVyFHnoAVbzkuIvadC/zsmVFi0GpbTKQXvEkirGnMx9QhzXO0TGd2cDm5NZkZPnW3ycHWMW6XlOyRrJAvqwSnndH0RVpND62TE89U6tGOn/VK6M0Y7yBsrgmsKRtjgpf4PEoCW3yE/TPDomQcfaa1OWDsdX6z7PBRM1B8hYYs0fwzByFcMntYMuv0WJomv73qcogV3ve7zHcnePGQ2PmKZnngTFqSHmqcG4Wh1SeTzvC6AZW/4z4YIu4dlHrC5DogG1Uc+Ws2XwSYUoXhd1jJD5TWHXkloVQBw9kEab3k4JnES7DTHWa4QxxcU9clh9jkd0rI6tc+J9mBYa3xISmJa5tVw8O1Vmj+mqwTcVLuuDBybq4N/uHDE/NC5nMG5brDRhEIghkXwgPN4JakekZwY7TyN5jrEYPJCc5iwEyJWQo6w5dNNKVGtEVmjRo/KvCiEm234DSQMX7YEbaXGOsV6s6iUwisWyVT8yND/xNV4fMsKqycOTzvcPM+ttkn0k0i40Ap1ozTgkZvgC6C7H8iXyZIBWAX7HttEtNG+K1EQ7Y5eCKxcaD80y29Y59T9RvEQGIdtbjdSMRrFUGbc+NVDD4rdOsOffUb6t9myF4Ox98zbuY0DxC0LYp2Th3MftS/v2kI1MB/KQjCr/5qRyGAfl3X/81fkTOg/6/sJFMIZi/QshT54ZiUK0T9QHV4ppRgFsekrYTxIKVZC2RixvV0D7uMQzXi2ZZpDRx6/oCROERUz8kKEYqKfjqhLgvGdQuGJpUpU5si112wLkN0LlGtmAt7iWKqtKUWenfCvlJwD32KWCDYh5jeDqv3RKsBbv8R/dJF3GfsYxn/QeXxKsTJLc7MPau4Yizp6JmP5w7o93OOBh721VsGvZJQlynVOYq2Q149kDQnxHWCHzZo+g6xY7EYlIzjHcp1h8zWOdqoPDVi0khCKoZ84Tq0n8c0HjZIqsBdyyA77bKSj9g5bYxGD29QoksHrhSRTR0T7AUunQ6DasLgzT1yPuX4d/ckX++wVzXGeE2uKuyDFYHg4Uciu29jNs0lb6MJHirMe1SHF5ShRiNxOUoVXsoDtsvveQ4ErI978sWaVfec90KJfO2xWZwQdHNqU0JauUiBwe6wITOvENwOd63XdLwL0I44KwTk7hNa16JR1cTmmNmDghfrfAobqI7NWbQk7LWJ8hApP0eP/h7utM1RUTOetSnciNiJWDQMnsohjdmIad2kQMIrtyB8pO2J1OWAVErQEo9W7VGdiVg7lR8kg8fJM0m3gTyGuNlFXhxhd23iY4VV84TkMCcJZTw3Q4gdjpdr6kOPZzFmPR0hqwnpWGN47cKgjTmU2UofKZMUKSrw7R7SQMd9GnN8naChoY3buKgEWQ8xdOgs+hTyC256A3YnFYOhjDP0kA+PbJKS47t71KMco4QbYUn8VUTxMkNYlsyVipWf0llbiBsNOx//qH9/09mB/1Fd18+CIPSA/4cgCO//f+Su61oQhH/ptsf/4jZkqtNEbu1wpIjwLGYUHPPJ0UjmMyR3Q69xTl7PKawxiTeiHUd0pDuK0qImZqPpJHpF7+Wex80xjTICcUFzeIZ0nhPeGnwrizyuc9aqi3F4QnPG7IWUdXXgaFAwUmzaQc1MeORhMaRRJyijCd3pCVlvTeNZJu7+GXn5RLhZoSMgyxYvdzqynlHtA4gsFlcep3nBWhewWiqNZcRhVhLICW54zGk6Z1nnbAyD41BDq7uE6xVl3efYPcVr/jnGIefWV1hLAS17RLGoUQ5jzN4eazRCSg8EWp/+9Ik4sJCTPW7vGE8vCfIZrdaXTBcRAgoDsSYrFwR5CG2VZF1gd9qk1yUtVUIfWHg3JbvxHK1tkNyeUDR+y3Cv0Jh4+I6PfzilXepElzLeKmdhPtDY/nsUVUGwCUgaO4zFa7LmrzmJRuyqMU13g7w7wSgLrpIt90qfoukjPuqkqztc18RcbxFMmypvEscHxMgg1nza52MW93cEaQO7K3B8fKA1P/AumuLvPKKigVinmCcelq2T/SDi+l3E45LZ+Qzr8QrPzLndveXVSEBKNPbva3atEdI3UE0iPjyI5HaFPRXJxzsaecJy26Z5tqJxp2HrZ0wXMDb2eOIPFM0GK7HkIPm4ts82k9GCe276Y0qaFMkCJbUwRjW2+R3F9JjDQuLoSEVTSg5ZRaseEuQFclel6Y/JshBNdqm0G0RBBj8gk2palxrGB4tnEYT3ezpKQnhas7BqbH/KwW3Tjl3sykUfF2w7P2B8qvHKSxbrCiXZonWvMcZjwmkfZV8gvcjg17+HEKjr+vmvPheCIPzn/LPdiOeCIAzrup4KgjAEFj9y7T8A/gGAPbiou2uZ7PAFzW7MrnHPsJ7hXxTEdwrNQcBGrBAXMCrviLILdv0urcKkEQu0JJu4ElHm/2zuucw0PFthYTww/pXKl4Mu17sDXV1mxp7aNPhZtUTMvkVJ/xHRx1NE/T2Bcknb1vlFkpDut0RuH8nL+GYjcoOAFaZUOwOh/YLxy3fs31dI0pb4JKUfdchseP0kYGUCz2ZF+LQhP6mp9T7Heoos1Ij9NtZTRj1poQgpxmVCGBakXYE8/H/RMAI2yQVr1UStuqheC016oNJWVIsGSbqlqZ3h/uqOYKghtobIwQE72aDtCgx9yudUoIeP/LFJu9Mgd+9Jd2cY+Y5N2MR2aqTGJ/JgzK4+UNVr1nlB9HnHuG7zrSZy6/eYdmQUSabVdCiK3xIYGlUO5tFrbPcTrUKk0kqK1Stu3SlXcsZ7fUXHbaA/+6jmKWl94NoQqXdt3HGT1bcR23TEIOmyaiq4d/83LO+Shtzm7jzFlec8hw3MrkxhFLhmjnYnc2+3OKcgGwXI6yWzRKG1vmCxFjCOJ8zYoQbXpJ0z/LMthlpyslG4Hdg4E53xsGCTP7H4tMdsvOBEVlhdFgwVH3Xpk16OaK/aRI8lZ+7vcHQT74VI/OcVSkOkzEteyk3C0IfgBjPoU7W/wu8Mmc8/0AP8ZI2/t5FeCGRNkIg5VFvyRYm1PyPtF1Rnn9g+lDS9AZv8LT39I+nRksL8lvZ2zyHwEaOI+aak3amZDzRKP8cQW3i6iSk18AObdZETN1PqfZPg/WuUgYgbbzlVDFZfZ/h7Fy0q2e9+S9YZYC6WP+rx/+DhgCAIliAIzn/zHfifAt/zz7Yb+4/+6rT/CPi//Kv6qpG4L0pS5qhSg7lR0WmXnCsKiqcgI+Kt97jaM5Xa4eGrjHD7CmGVEksSqyTDSRSSqGQ4v+M826K2OrwM37BvqlTPDu7tMzcPFaivsfUhy0gkTB7ZSwWO91s07Rij+MjvZg73p02qoU6wVVEqjyLpIoyg6m+pjxxetTPmf/ESxXmNMJTxpBQ3z/DLOeVYYtoUsMKIgW0QN316Yp/0/Rq7qkDQkb0GveOArbXBr3PsVZvzO50LvWC57rGzNV64Ese5QdbdcdvVuRN7aGpAYoGVfsT5k5ecf33EVo+4PQyJqoLbRslIOOWo1SNeXSKaR6Qf37N48NASmfJ5xMp2IDvQSBqQ32GpOcKrMWLT47jZIPMEyncJ2W5LezRl8LuUVVyTn32N9ySg1QI3mxDrcMpOF8lvbCQLXskpcMUw/QWK/4KDr1OLI6TOEEHN0f05+9/uUaspRdbg4eQzs+yBZfcIo19SLDKytci2+JK2ruI7Ammpo9275F6KIxuI+Qo5cFn7Qw5exXag0VzvGHgxx8GKTJHpPV1TLnVCf8yh+BOunsY42Y7M6uIHxzTPDKKNTPe85Hge4egD7nyL39zoLKUdQfWIrA8psj3hbIpijFgaX3K/OmO6KLhNFGq+Isg09pHKzXLLoXiFMh4i9kaogw7SfUxPgGFiMfTHBGqLh+EG33mPWBpsu5esg+/oThKErcn+ycHc7pnrOx4aFevgkcbXEquBzKuew5t9SfdOILv9Han8GXuxxkuWtKUF7YeQn73p0Gjc8EktWWcuxaSLm4yIHy/xjCMG/Tm+8uOjcqGu/6XV+n+XELgA/vO/asrA/7Gu6/+dIAht4D8DToB7/tkU4eav60vvnNSjn/3vEY4c8sYBs3ZpehuCmwL3qEGcm4TpZwzrmE2s0w03xPuM867Jwa7wH2ySMxVXq3HyCCPbIwQWmWJyaFY0ojV620OsWkhiwN7aYUcVPcWitUtIJQvD1JjtKnZtjzr6S44EC+25TdoWyMwGm6tnlKRL4+MaI79A/PkUNYvY6THOg0TSdbA3bW6aG+xcIJ2Dq6loTQFjldC9AKPeoicj6jDm147IoDKZyDojY8N8csLudMq3eUiaD8jCHUJlUPW3vH/c0no4J+3m7PoZL8onFkWFItSk2yFpfcX+LMCKCxSjj/P/XCAbGZ8bOYK9Q06/phxOofDJ8BFvJOY46K0hJ1XMxFE4SBsaM4HhvM3kaAnzmKSsqNUvUWqJoQORduAHv8LSbunHX7M0LUx3wnw6o6X3MUwbcadTLQIENjReG2wfPBLhgRfNPRv5kue+SfHdltpr0Tw8cDvU+XLpM6k99NTBGsfsg3s29guchkz22SbUfktP+ZZ69ECSLdGfwVQHrB2F0Xud2+E7GusmXdnBESfcTWToviDofcAzuqjbhOfmgG614Xm9Jb84ZqzFJOKBxm8z7pDJxDUvN6/QBhsiY4qlnuDuCubhHYJ9gfy0pza76LXGurrGbVSskwGpuKO5i6mKS0IhwsnBGUbsJzWSs2Yee8jWkCKXqNYrjMuMXu4Q7bZsdg5ld48mmBiTjHAo0R+obMItfjilfTjmuPdIIgqoQsFu2eD+omA4K9GyS/KBg/F+hnxVMd9nqNIc2TpmNV3StUryXU3u5Xiyy/2szeK/+l//6l+Yxfvn/A8eDtR1fQP87F9yfA38T/779FXWKurJB7bYeJtjVmWTVidCOXaZ7X9AWsmIhcXCnGB1z1lEFspVQbwo2dclR0bKJptT2QJVHPPBsOi2TlGqOzrzBpE7pniIUbq/Qhh55N0W988RA09n05bRPmdcnw4wu98TLn10octscIIhX9NMThCXCad9k6reoxQu8uAWoWkQRx3cUKTT3fFdC/RgxYXi0PALngYdtvoPHAUNOqaPUVp8NEf8spGQzXXGehf9ccf4C5GJKCEJBUefLbQjhSB8olh5rLSCV4ZMYl0gCndksY11bePINtNLA+Emw+oL9IstYu7w4d0Mw6iYvZLQ3ZxybqAWBbEyQdxMqFo16/BnyP0AWT2w2G4QooJ+BboyZKiG7M+eOTNSPh9OmegJXb+mcN+zK8asmiGdfUaraJJkH3jTFqn2bfT+Cdvlgad6SlabvDyxUaUQnxbZxZ59YvFQJcyrjGSxQfxSp/+4R7JNiv2anSvjxjnH9panHwp2w68QxJDgdwqykGNdXtLZPrF57FGpAqFuobVnVCuTaa/CKV6iDmt26QNxHrF40aLyNvS0Fun3oFUNBuUBycioNlu0kwpjXRE4LXa2gJfZ1GmTWabjssEtmsw2M0K6xAeFruzz2BLINt+RHPcps5RGY8jaf6ToH2M/n1EfdtSVxWxfoT4GVK6CHmjkRyL2/pF++wzRsHh6JzE/Cek2Oyj6DeccKPs24cKgjl4TxFMaG5l29S2904988i+xOhEntyl7s8ZeDRCyCar5G+pln4Zu4d9ZRFoLda5xUHJML2Qf9LHEFDnYkbk6+un3P+rfH8SKQUGJ2fdk5G9dKnWHpa2Yvt+gtBc0Wi9xhS7ayxChahNmf4lxImFKGvQFslpi6+RUgo6dH1jumvR8iypLmUVnVB0T+SxnNip47F9B/Arx2qP73YFy+4Qv2BSSgDh/Zud7XDoG8sKjRKDIutyTcX2xYuF6iFoH6zIhaB447D0G8Y5inzBF4eVOIjjuE4sx/mUDoxvw2pJwjZR3rR6/rkyCwwJ3/Yr6qEH9sGDxZYndjmkZLs7Rgka8YzHR8Ncq13WIbE54txYx7kQiUSE+Trn6usS9sJH8mqClUsw0bt01m+0OpQ2+XcMsQjJT+tkNQ11BUwOksINWNJHrCIwnTooIJwvQuhqHuY4wPfBP9g8sfYX/99sGoZ/yKpTRvHc4FQTCjvZDzJmeY6gBidvlSdPYxgZZpNA3JTylpJfrmEVIIVvU/iO1ElETM4/GOOOUjtLiamHT1StEd0H7ZR+v7aNqKfMwIG6dIqsKY2FP3W9hny3oxx8wfI28UlBun+nkO/bXHcp1hpJJ7I9jvGyLmEiE9xaDrI1ea1RvPTK3Qfc4Y1Y/MpkJoHmI9wnKs8FJ2sNWFXQvQxU38NUMS9XZxgq52GSRKghSxUI/UOcDHOvv4kpfoJkWaRVwfnbF5S5H0jPC4Vu04ZTmzzMqJWdZWgjmkLN2Tqh1eNxLZIMcyY4JhQ6zyqVhjwi3OpPPCnvHQr1QCXobpH7NtpwzyS3sLCTRDrxVe8yOPCR/jVpBtT9CFPd8WuzYSlCkT2Tilo6okq6+5czbkb3IIBmRzBzKpx/fi/AP490BLIybn2PGK9amhuvkVPkY4eEjoVnjVi3yncW42qHbJ/jxClXqkT1EFF9JeJHCqrXCKU/Yf2mgv9eYzPa8sHSe1Bn9O5WhGbLYd/HbCfZuSkfTqWsZ7mFlNPECDVVaYN4+EQxdOjzi9I7pfN5x3RlRxhbZcomfjVHLDtLLe/Jxi6F9zFP6W/abPpW8o4xEPCUgPYSUuxecjAMGBwlRl/GFDYG0QzuA3cmYlSa+H6MvHDaGjn7xDkEPkWuJQXngeZfjGDpHDZm920LITlh+mDI7WTMOc6bmS4wXLcTwe+p8RVZGHNtfEOchy88u1abNVsmxekt2hURn7sF+i3PuEK+hrbnMljrdozXCex88geH9BfFrFVtJ2e0knN/cEVsu0osxtfhb8vNLqhsTT54Sbaf4uUYewkHfsN1pdByV5V4kVhUQC6rGAQsdnAknv20yjyr2HYmVCk+WjHEtEeUyySuF6vMIxZtTWQLepE8kr8lbNv7iQKUdUJ01VbPPeqJzeSqR7jxGYshfPj6QbA2SnykMjjrMhD3e3sPpx/hJh72cMbjsET42qdwCJxSZiktG+SV7/4BRgnWTUgsm5bhHuAkYHfW4Nrakz+ecaEMMNYFJyu5qTvvzmFKJEKoDh5MU6y9ElMERVS6S2wH10Qkv9HseZi6tuUnVDZG1HZFcgSgjiXOOxIzNIaTRNlG7FsWHhHLyQNu2yPcpVacgLXJ0zcMMCsooQt2pRGFKLaZMNYVqnSKfVpTeDEIBRwvQ0pLsZM60NvDXCtZ5jnuIIVX+Gv/+ABDjgkFfQKCgVQZYs4imKaE9vOLoUeXoxSfUkcHGM4jXOok+wmg4+G2dnX+En2pkDyazoMTbzpl7U/zhDVv3LzkSjygyieX2jAtfw128R0g0AnHAZ+WCSdEgl1WSJCboK6x/WVO9iGCvUxodtp0jfq4UjOf3HBo3NBoGo9Mufn7G6lAi36zotS0auUC8d2jPM1ZPMlbLo/PmiXsi6qM9Sy9hLg94VqZkVcig1nkdFhiagl1WnN088DJUID1ie6QSFS2Gw2+o9xEtpUnj+JgX9Ttcb0XvqcHjZRMvCjDyjMb2a44mCW3tFG3RYj0QKAwXIzR44X6geh5hBTqr9p7JtCDNU/b9GEkTUaucqdiCKxtTHHBnCsjRjLkyYZV/4uni72Ad+3TkOflB5WnusN4duI0f+Dw9xzkXkJOAcfeSv2tpOFsNwXMwE4XjnU5/D8MbmZN1j6fLmmdvx6QRIzQavJpc4toCxcsv0CYeVl1xUkFDcihqlcRfUK1KWrqAeTIkfTxl+fiKcUNF0QLKQchHcULvqMlTa0N8Y7LMc9z7IzbbERNnROzvUQIHYXWMpmxopA7Ws06Bjtq8R9RMUs5Y5Sc4i1dU94+0WseIwp7eMuLL3Y5kFiOJC/p1yFE6ZnB5oJOtaGVjWt+3sbQaO+qjd0SyxgvqZcy81kh7Mk+yy3ghY690Kr+LcumQ93SyUcVU6iH2ulh3CdGFS62aWGobpVTQpAotbiCr15AdWB6pWMmSagB3xhuSvoj4ywGXLRlTiGgnNQ/VgL0FZdEiV/u0qmc6Qcq+K7JPgx/17w+iEqgkiDcHdCfAiy/YByVVsObuyEVd1njvDAJlhiMGNF528BIHp9gTc8+f9AXu/CVWuaJKu2xNE72R8PW+xtZP2AklYt2jaS5ZNR2G5jlWskeix9z9AaU+IKQ9isBglzmM8x5/t/jEzDrBnH5GMi3uyi3N/glDLPbCBsnL+OJBQiwbbMce5UbACx6QzjtUVUq7vOewztlsKvSrMSQTTqojHnObdlRQWY98Ks740sz47U7A9fY8SBbBYxNL2WD/wxVHwhDHrVkobbZiQv+HtyytDvFK5mPdpfMWDCvisZwSGha9QRckAV/8NV06hMUjzb7LxA9Z6R0QJjQ2NX/SDplHBR3hS4SsougYaLJOlwPdxjNLcUuWCSSmSavhg5XC1mEbw25c480PPEoxJ5sutlmSU1GOXLYf5pjfDAk+BQwTF1+6QWl+QaCGTGWJOtIR2y2ujtckB4PcX6FSoHhbrKWF0i7wtS62ZWNloOZLjC8vkfY3MPeZbgKONA2n9pkcPWPsLzCFjyj1GzbRmk55wbIdY8oupbKko8dMZJ2jbkQYVTTnHqHhMc8X1C2PrpgT3E5pm1/z5Ea4X32kSAeo+Yhif4tYOGhVQXrsYhx+y2lls+ucIMkPhHclme5RWE+M2hJPP3g8OxtObwUa1p59s4EazWhrX5MavyPyVcrSo7UsmRZbnOycOvdoHV8zVcZ80/LoZqcskv+SQjaYumPy2kL0Ippzj9pQaFYfOWgSHbeJUTu0dYGqDLjtnuPWAYkgIG52aNEVqv4eTW0gP37L4/+XuT/51aVd8/SgK/r+7ft39WvvtbuvOefkOZlVlVVZprNdWJYRIzxESJ7A/8CUKUyYIcQAEJInDBAIXFCmqpyZp/va3ay919qre/s++j4YZILKzVe2y9j6bikU0h1PhGJy/RT38zxx/6xH6sUer/Ez7ycgySWbbkEiH+GdFGwv5rQvRaztDYZ4iljU2b1u0n69Z5NHbLcf2Ny6FO0209mOZmKSeSMaro5XOtjqnuyZyVT3STYLAvUzpqVxXgiU2w5e6bA3v+HNwaefH9NKSsSWwq/OPMZfG7TKGmqcEMsdzDTlmeDTCjOk7Jj08I6dYLEfO3xav8WVP2NHj7iXXb7SIVdNrGFMs+xyol9R10UWgz6TximC6eGPW5T6CRfPQpbrNhfYeHOdY+UMowOe2qasNXCNBubnO9qHd9RVleTqmKuqJDz2GI+XjJsOuuhz2itR3JTb9QFXlkh0k6CmIXTrbEa3qHmfeq1EzCLSZoJrtun0ZJSlSC5Mae/v2Yjv+bQ3yTWBfXuE15bpvjNZd044XSf41OhoS3RFQhUFjPOcxfOK9WmbzbZHp15gmDZPukxUBQjnKtvjE+7rdVy3AUWbxnHKlXiNaJjUyyfsfsyPTp+OorOUauw/b+mFHf5wn3GumkwvDKTJnou9QVC1MMSMNVN6s2scf0is+0icI2U+lZdjyHUIfsmy+hsBORYyjn2XsrRYrQRuvC3KruKINtY8p7R0rKLPylrAYo9knbPPT1DbIYnRRE10+mmddOYhqH0Wzpa3zg2HB5ekEpj6ax6e2rx9tOhfHRgbp8ROF3v8DqH21zSOTYbjNVfBlpa8INUCdnUfZwBj5R1y4BJlA+T9A7PyHrW2oitYRNUZubZkdPAx5JiGbbCqmrQe2lSeTipL0F9xEGD5ucJ4v0D4ziV7CEnVOovzdwQXsBcz1s0FQ1FD9Uxs+ac6DP5MRKBARl6XKF6A917GuR1Qzi1EU0Qb/JHqTcHRk8Kn7/4eSVSx0nVyoY7sDpkZAxbugZO6xPxVSvfxhuTjBffrL+CgI4cXPFfOKROFeGywzH3yZgszA389IvAK4kHAk3DDTDA4s33ydo+zzmsoY8LGMUvtJbf9nMPhhk79FWEyobeO6etdzooIsSdT/4XAblXSNBJC4QXVMwlNLlCbOs2ojrOc006GDFs1rKrNep4z6eYodxIaJY3FHwmlFFtPGVwoHJ8/IRo6q+iKPbA+lOxNqKUSR1bOYX3LPhVY/6DRbB/o9DNKf8KshEZc0NiDJVsox1+gCd/Q1Qu8jcJj1Gbv6uwdmIwENGvOxTcp9fI78vtjziydQajyqbUm385ZOwt6esncN+nfKyxTkX+4KnnZEKjX94hWQpoPKPQa85mBE+3I7pYM5Ds6h3uUuIWq5RyvFbygwXa2Qei06K513qgZiTLipWAjj5qQhlRNlWU5QZ1HdLYhWwuqZh/OQei/JtN/hX1nM4ozWsWSaTTBKZso9RQ9v0MMJNJaC02MCIWK2q5gbHu8vloRP0+YxxaR3SbZVtCwOZ8G1KQRZRbSOr5nVco4kcjaLvjYanMQLdxUYTXNsSqL806dWIroO0PKlkLD/8TDXOBReqJQZzxdn9J/eMP+Y8Afowmzxhlxq0S3Y8xmSbk4Yia0uL+s6CQVefiMh6MeH+dLbhMoagnjlUxW5rSeTjANg4a04eHynLg6Z75qE74tWDwkFFuZQ56SBBZKVuIoXcwkRP2UchyaWNE5btck8XNG942f5O9nUQ5UZcGFVoN8T9PY4g9ltN93iY5fE0YhoS/xZpLA4BHlwcY8K1C6H5lxST1UOIuH6GuXVuOc3as5YqjyvLihUH20NwduNyKjZkxj9wT1I0rxjqmaYfaa2OUT5VSl2ncoEo37qUN/eItne2zCnJqZYobnHN++JRVSFN3mS73EM1za/S6LJKCxFUgLhQ6nuPsbpPCJxGqQWy1GMxEkk8hK8P01xlajvxapPTPpahLZpMC0LSTrAjs4oPgxTiGxDNtsixlStcPyBMaJxM7Vcbw1gdqgdrREigPcw5C2OiRMJijpGa+yA1HlobsG1dzmpvMONS6pMaPfqLFTplSfagj9nEG5YJb0CUYOV50mftBh7ScU/ROulC3JJqEdHvgwHqAaCYvDCHvg8cenNsW6RBdy1O0Gqenid2doi5fYRoetUmGUR9iDCTVhx0S2WXp75vEVde8Dntbgrqai+zm9twKiIaD1dYLjHq3tO4RFjSP7lijp01FWeFMduS0zGYR87Uf808WUnnFObEhYNQlDyIkjG8VtYiw/YkktHoUnXDFiISn0rYBDS+Owc2CQo+9jRNFner2hNUzpHgL2WYtk7jDu5XjijHCm0jleoQQOs7SNqA9ZbWLM8An76hzX92mqMp7bQdPq9KOMXVxD0yUONNBCEWddMtzeECZnfPg64HgR0WqWWK0U4RqalsPSSJCLDfVaG2HcYrXuYF6UBIGNHBd89Keo/QYj3SV0XfK4hSbeIxkSdWvLZH2KXgVoLYddfctJaSOLF0y2NuKlj7/acdr4mk3zM/y//7P5+1mIQKGIrFsa2aSO1F6yFi5RfhlhhSmp5GDlCaacojRVVFTUsOJp9Rc8a37mupZjne5IHiqW9xl16ZhQX+AnJe1ah4Nk0Bdn2Ms+VVUSH3QuzhPW+zqH5R5JmrLIxuhWAyPNMNOIlfqc5HdbxtoEP3QoD48Uwy6nm5xFKCB0aszUAcJhhlD1kDToSBLi8QozyMgsjUBoU28/IYkye2NAY9EmH32mShLyr16iXmtI1oaqnaEIsLl9TqMWESUVRd1EzU7ZDiUM/55i+zVLY4YkPBJ1fFpVG9sNCc5qOLLHVFHoCBdkcsbCXFJoAhedAvFjySu3QW49Z+tvENQdkhIiXhqYYc5VIHM4yEybOo/iR0rLxHIPGInNVs9oPpYsJEikAFPus6q51PY/IGfnHOUiW1nH6Aq4eRPxW5/XbZ+n8ybtpUG5k0gzAeWopK4n1Ioeh7hgVX/JkbnnKNwSz1Ni1YaqJI7rSPaUkVwjUUd8MiK6L+estw6y1UZ4/IAt+fz2XECIj1FSF9WWaXsl03rC66pkaWrUFZEn7tDnNZr9N0jaRxrTBU7kMD/LOI1cnrwIJX3GyS9S4utHimcaq33MVRSze/+JXtfn8egNh/qMQz8nmwfU9xbDjoP4Uqc2WbNzJfrHG/RuxHsfupKGNVfo9A/Mu58JsjYUOWn7kkTMqUUdVHFCWN/g3vXQFp9xTws81WaQ9djHWxTVIe4IrN61GDanBOMuanTEXjwgfHNL7TxCVQ50nQbzRGe2a1OIBclpSpZINESL6baPXd0i6zW6U42seURzssGy17z7Cf5+FuWAhMQuTMBeUGVjapMEHrZ4VgNHNokzgY1tI0UjhGELL7QxzkrWl010Da6LE55GBfUjjVg74AQBZpDyKEF6vcI7yomef8e3KKTtDf77l1waAuctHcd5zp/VW/T9PfLNAx8+TzkIKo4y4tmuTViEDJUPPNvBU6wxSmD/vYaT64Qdjf4XYLfvcFo5TQ2O9gP0oIGhxPx52cOcHdgtJuTqO/YtmyIN8fQb/Gc64apDp0i5k8dEr6ZIdZ2sW9CRPU7NO0aPG9THY6zOnqNTBfV5SdTsEPlwlzWZ7vr8QVZYXXuEu4B9saeRqYQ1hdvYZ3dc4CsxwnxOUTNYxwWm1kKQEuROyMy6IviFyNQ/YM46OKqMLp8hOwZmLSL6E4/2myFnbzwOisdIitjMIwT9E5t0g9abks06qD82MYYX+E2N7m5Irgfc7T7hDULerQ7omwQ13ZOvHhgKEoWoEd+nJCc1qjAm+CXUVRXvmw3XyhOdZ9/wzJtyEC9Qe5fkvWvO9Iqv0jXuhzXjE58yqmhZTcpWwngPiyRAi+eImzF9xgzGMk6w5FneYNO3WNZTBmENb92m3T7j5NLiyc7Y6CkTPcLQWnyy9jScPrPWL1BqEh2zQ2PY5/xCQTdVaC9wNjJaZ8D4uOLOb+I9qYzsHbtaitmVSYuSg/s1ZZ4QmQp7f4Uk3KAYEYtthzBuEEYHtOGIzAm5WEaEeoAqt3EEHSvwKIWYxcFgOV0g+h6lmNE5q9Ga9xkbDZZmglKeMG7VuRiYoB3Bss7wsCOSLSIlp/4kkNbadBWB+ckG18l/kr+fhQgIVYadLNknFQ3jnhcXAYotYD6KrDOXZuJT60kstAw1KlGYQpIj+T9yMq3o3W/REpdg9QFzs6c6tEjcOrqgc1Ju6PxBIUkzTmoupSzjdb+harW47bzHV55os4OFRjxLWG1GVP94y0P6AT+XuTBlrs/grh1zcd4lagS0j7rU/AOdDz6VJLNN28T3e67DLa5WkbsuvahGKnrkXzU5Vy28URP9O53DvoWtaJiVzLOLNXatQXMR8pqASo8orCHZaIzlVDRtk+RyxKEZUpV78GqcqwaXdoFstVD6U3qKivxKxO1+T02MWPt75G1MsAqJA5lVo4nw3EDcrDmiIH+Ys+012dsp9+6CbVKSJiKhXqM0M56K37EJ71nkMq7XQ9BKgluB+uGB6bai9YsBZlLnoX7C0rPYFirrF1Na7MmbjzjKHW6ocB67ZJMevbVFyjlp1Sb8TR0hFDmZJzjnbSRriHKV4WzqFAufZ4JB673AN7sOnxsNiklO1MpRu8+5EUX++maAYzXRJxFCFLL+8YHFLiPCoDAETCy0kyliZvAhe8mnhcquvKd7GOElKZ1sQ54cKBdTsnzO/rFHKZmwVDBbW7RcJHFK3PyaeiiznkpYnkO0blP1bcIgItK2uKuUKrYoDyuaRknN0MkfM7btBb8PTY43S4pNjJjPKEcVRTmmNSkp5TmoKcmFgrWC9HuQmgm1WULLi3jwn9H6YNA/WiDoXRqpSC1W6QRLdquKt6JCfmuhxjli+IAtjwhaBVl4T/HrGZOoS8v3cPsDvJ5Euo542ldEmcXT785+kr+fRTkgFgKiEOI4ew7bIaqxQTz0aKU51hsfJbhiU19wtDW50+7AGIO5plqekKmP0BLhxGIzzcjrAXqjg3zncB7ekv26CT+oDG5NZnkNQ1sTmA063gbRsmmqTf6jrEXR0ThqOihyxaqTIe0NNrUxURIQ2AM+vF2T9mYUR0d8uRBYazlV/ZTN9zvOfjOk8BaMcpECmS+kGp9nsA6amNgIQUzzoJI/zymyt2y/O+fihYgW9vljP+ZiFuClXXLpgS8qCTMP+CduiHDo0W8/oCQd1MUejvsc7nP2okbHSVgoLl7cpG7pkF8i9Eo6Qoc0PkYcuZSfIwQdhP4C60hE0Jo0ZB1HbrH7VODbHrt7HSlOuVRWPLghmqNRNBNaucbe3bMKv2CXtmin32FlB8J5G3m8wq6WdMQaRu8RlzrvRlBFTQx/z7GyZvnsiOEBqvoI81JlflPy9R9vqDkdPssK67RLIX1GUCvWf/iAYzQJGgfyk5y8pvBs63Bwujx9ijnNlszLks65jtg0yX5fIA46LNrvYdlgv62x7JecnfYJPgWk7KmyEmfooc90HqUDvbdtVlaDxn5OcXqMY8wwzhe0ogp1MeL46ZHPI5NCkMmfamy1Bf11QvN0hzQ+ITTXFB/rSN9YLF8lFIKFcpHzmL+g9umBk1/kVNMeVsdhfhfDWOBM/B75W4NP2YajVofmK5P81sZ5cNm/Ntk+2RiSjajayHGb0fcfUb+qc2uLjJU9+1VAVsuguKQjKtSNAcIhRjN7hF8dmLifWH+SGcoXCOKWpJ8hLVya+4Kie0BayVjRGaF2oK39dGehn4UIKFVJZQ0R1z1quUPd2/DpUkT54YHV1Kdfj9C2AaYdUM++QChzZCmn1D3eGFdsWzb7yRq708J7XHJlP7J7qXJdNUh/J2D3J3g1g6YHvuwTcUw03/BqaFPTPVaSwVfPckK/TRorPPuccj2e4+0yypaD8OBy9YVAV1nxaKm4rSG9wwqaG/qtMdXkjrUjUtvEbEQZtzIZXSX4N2tyOhgnXzDOImTxGs8ZkfdqrNYWwdkjpw2LqSpw6lZ4no3rZuyEPr3eDYUuYDd9lvc5gi0gPezpagNKOWA1yTHlNkXzkWDXIxYOnMs6s3iFU7zAWH+i4BgGU5TQYT6VCZ71GPop4bs19jalmGnYwY7eyyaR1UGc/8hYb7F6SLEaJYaospZ26NKc/dDkxJtzl/2Na093XbBZz5GPOyRrkVawRVd7rPICJ3mgXiQYqsX7xxWdSGFwsqVobfF3N3S0v1lO/OKpxD91SNoZumTwcaDimA16qsAqrJClT4y2bUImDPqnrOImevTE5kREDGdYH45QBjFx84kXro++32Kc9JlkLu0qQSh1bGuP+TAgOomRenu0tUg8NwinEo2uQzSqUOwF3zaXxB+PkQcRRssgtlXiaksU1hlaOQ8LkU7RY/PFWyIlwM5OEKZbjLKPovyN8Y2Lh1Jt6fyyzyGps/38Gu0op7dbIXQ8yiRlOVpQ00y87R1K1OF+azPKE9xugvZ3d+wzlcM+QxRFnLLPxpzQmcfMcgEOJd1WzpK3tCfnnCo+Sk9m7BaIeZ2J7pHWasT+Bskao8QKlmHTtWLk4x/hr/6z+ftZlANSJZNnLq3yCUNf8Mk1yCMdejaN6RFZIJNnA55UhXanIG9FuGsLSZfYRTlh8JlS/cyr2yeOaPGx6BIdQDo0sawWvc4vaKwzPNuk7n1JPQtYWG1WRsaT06IV5ixnsCxjxOcHBFPHLPrEzxscMo2Os6f3KFPc9emGCYV0wDkukesG8q2LGXjY6z0tr86rcs+pYXN4bLDqO2iCjBb+yLL9Lf68JNisKKSEwWWOcRCY/1DD9vrEQptudITUiQmNAKJXjG7rVNOv8A5H3CcD9DIlWHg8yh5HckHnbsevlhKXeYrmXmCgIGwMVsKSQzTCr4d46wTxkPJynHCaPqLUC87HB6x2jbGg0tdCeFrjb++IrBapVTIqnlEqAtedJ2TZp7bvYLzNCBYmPdlke63jHQ3wayc0Ao1e0kFfn1Atbc7o8zF2qA27hGbArzt12sk9yschu/05lF/gblu04hB1cEoY1zgZnLDNbZ4vU5orjfl7j4fY43ebGjdfrgnEDslDgpJv6O8vqMwc6bFBpKUUgoPTPEGp1bHdkh8fM+TDkAtBwZkqbMU62vCJbstgU9Qxdia10zVJH4rmNUeZSCktKe5P6eQlU9vALe5p3QhslT6ae8LMO5DYPnErZbnV6ccyzYlGqfrk5R8Q9wc+zkuCBELVIHGXCN9/h7CRaJYtumKXXL7EzzVGWkIdlW5T4fKyxGzqHKSUPNgi0KUrxLTKLlkGm2qLFjvYVwVi6aBffWJ+8OjSIXVCbpMOfS/hSZPY7SSURGZw7dOULQQktlKCJD1QTXvkXvsn+ftZfAkEFRx8FfkXI9Z/3BOKMmnRQBpk1F4KdAqN2Ids3yMLmigseW4XLKULtrqNVe4J2ydI8pDjfE3ODlURWEkWVrpjvck5OTthsAiYtgZ0ZQV5saHjRtwKOjUhJWoVdBQV7UHmd4FC78Kl3cnI008cCocH9Zigdcv55BRjuCIcZEzvBOaNIS+yhJoo0h5tudcK7OUtf/aLv8u1tOHIq6gsh+qpxmdhgeC3KV+MUJQPRLaKlIsUh4r10Yy6oRAdbNqixOrC5TDtsN1rPHNUMB9xU4P3FSixzENDQgh19j2BNO/QycFNUvbtmBoPPIYa46GC6tYxOzq+EOLsXLBVZuGIqbegf6UiChZedEZlbWjuLYoPJg9fveWXhsJ6FiD6T9jyc+K/m9CYtkkEiRNJRJwe0PoHPqsx40RGrtdIshO2ok3tLGMSjznNJTrqAdeusQ5dahbstjOEpM4QmUUMgV/wXtzzxXDDfC0Rytd8KZjcbeqcnAS0ViWynvOIRb5TcdM9xarAeumywWYdrrFTGfFcYic+pym6CAuR6KRgW25QhR5lUXFzp9OvPVJ139BKD5jcEXywWfZ8BLlFzZ1B7YRXNzHuvmB32mJQfsRXB7gHAVUZ4xQpp0ZMmZyxtbpI3hqlrzDVTrGkiHCWUWvN2fldYsdkOBIxxANzBnxIFZ6nfTpOzv3oE+ukztl1gHDlIQcJbj9msd/S2AwYvl4QB2dEao0XjxJvC5/8xQpz2yIVRWrpH9md9snq5whxhubLPKUDjPstwWBHGVQcNBj7JlpdYe8JWOP/GpqK/P8zSiHhOIHBDxJVzeHZqzHPX+f88nMNS3ZQVm2UIqff8gn8JzLLJq4U4rBC3XxgW0a89iHStqhiwGx7QClc2KVkE4Fez2P5dMDzQurKA2KvS2vQJNkOsD6k7Np9BoaKmhds4wq9pqBvK6THkNNthWDKGM88LnMDRxXYKSPK+2POt3VeaCs8QWRVZsRyg252hHN8xl1WkmbHHLKM2087smiKdqEjKENeuCXfTiy0VKCvxuTiD6jCgbsqJIsllNs9+qpJc2wjOwo9/YGNXacSdRqnG9JWxnq7Qe2LXGVD+uEMNT+wXuWElkMqOhjndcbVI9LeRNgU7CKPbUMh2ocY+5BxLycRD3QXDlZRkj1IrHc+sblCy/ccrve03DM64hWT1oKLjY0QnlHzIxJZ4qmjoSgy+tMIvdmi2UhINn/EEX+PkrRYJI98sO75vapzs28TjnV2ocFCMhh1Cgo5pvJFZGNE4+iMRzunUzuiKY8IXJGxlTJyIU4tsiLgfNyHXozbv+X4tIYVHdivYuq2zZWYM1huqeku+8rF0n3aiY6dnpOtN3Q/KryxM4as0NeP3GxzZuopkXzCwT6jEGocOhWF9g21+gPGQkCPfo8vqmzr9zTaQ8y/8tjmC6ywYLCO6dufOOs0CYs+lgPH1Z7xMCcNj+k5Cl25TnHvISk60XbD6HRJOUxweSJ/GFPLG3iXPQTvE0JSEC1VOmoNS4rRvu8ye2jiTPp8EFtUmYRjJhRVQBatuan/iiJWMD8feIvMyWzAmQ4XY5er/AI7tGnPTJRGSOgprFSL+fZn/gORLqlI9YhMDhmWOesHKD9OOcgTgggOxh2HfIH6ScaMB1yIGxLZobNcE0QR5qLHQhWx5y5RrcWRdEpgpsjtGflYQTj0CbdNmi97XI1NjIlL1K2jnScMnrcQpxnmfs+d2iZ7naOevKfqOrSYYUY6v9rkCP4ztC+72FcShrtjM/0Dwus5jvhElso4ssmmOqOsNQCd2PMwxBt8sSCxx0SdS0L/goGjoZb/lI64Y2Xb6JHJaW+EicTLTCXDpswcOsYGOf0jZ40F60adq0CnMW7yddvky47OxYuYqNXHl3OmT2CJHnLU4It7iVHs8SKFzf4EY5eT5AGREnM5yQiGFp6Vk4h7gm3MW12nhgyDCV3lifjigW11yW38kvudTpYeGJUe2m2d4WGJGc0Y/kJgZLWIpr9BiXP2lsEuuqR68wsKrYF8HPEmT+isGxT+A3VPpsGIfWPFIPuOufaZdBMjDJ8o1T9w++hSPF4xNxWSdUqnuCBJNFyrz6wQELIj0uiBvpsj+edsJg4IIq3RCL00+d7q8a3ZQ8pVhplD1NKZaBq6NqV0VYTKoeYfuO3JvO1rJNGM0UOOTIb96S2al9PPTfZVn5lT4h47iJzhJBWDIMKOdxgtiWJj4qsm84uIa0PifVaxV3dkasl2lBAegTsSOfh7XPMtu3EHP4pwukukxZz8VoYfKlpCSmPnIm/uaHk+RrfAsgsqbUe9Y5KPDV7W79m27pGfzal1fOL4GGGn09ZtuuMmb25U3JOUzkFnee4RiDdsd02Sw4xhzSBsvkeo9aG+oi9U9E9GP8nfz0IE0jLn0eyxi2o8GiOWHqTRjqj7gldI+EkfuXJA1UhGISulhTEs2J8vaH7Rgapk/iTz0HRZPgSsCJkc+pgHmRe6y24GRemwKQ983E04+CHRsmRZ7yCoAmYnIqqn1B4r4iLixX2OejcivhnxEDX42D/ii26A/oOCNp/RNUxOj37DtfsbquIfolcV4vYIOQ4pSw1rfcrzsYmhnWA3h1y2n/BellhHMz6nMbE14CwX6eUpi6MnVoKOtayh6QUvOhbz5yO8fMwmruNpIc3qhpvgE66hET38Ei/NmdsCmjEj71/z1VBi2u5hbh3y7Yq6Cc3zNbLqk50Y3JU1lCebVO0Q7x5ReyGJ2sJUTMaJT3P9kdeuRBz5yIdLzj2FqlR5fpbw1lqA1eD2TOWDDt/JX/OHx5TS+x3t/hTZaLBQQupHApf7ENvugzhEebZFyif0Ig3hV3c8FX/klXyFpJ8Rh30WQguxaNF3M361a1J1G5x8VLDweFQ/sjh+IhZ3NJQOb/Ut1+99XCq0MbTsGlU8QMjn1AWF84c9Xzwc0y5OqGklguSzqJr4S5ntWcHmJCG56HAhWzTEPVkhsDciDolPOtSwnta4voQwMWh9bCG3G0h1HW89JAwtbkkI/yREPUppHUSCsMJ4OqXPIy23Tn/Xw3UaeNMGR48VhiPRj3ucpC3E0KQhnCB5Iqoes3NNMiTEXkLVSCn0X9KXe0w3NVZvVZabNvp1jqubtC4UqvCUJBIIYomouWc/VEg/lHwy6vBgogcrinUCQkwum0iNLlbP4Khbo9pNuNJPOD5kmOrPvZ9AlePUnlDCMV3ZJ7ps8/79Me3sifZep1WoJEOdTqUAOnGZ8FcfYSDr7Ioneud1ah2V5geoXR4IJj06dyHqcUFaFYyGGrVRRr6ViIM+92aFVFR0n+ZISgfnMmO+anGq+3x8OiZUt0Tdf0Lv0zmJnKD4S75LD/wm9Nkfb/Bqz2htd9SGM/xvE9Ruh6tBweEupLgs0ZwSy3fQ6hJVvCLt6rSCFLEY8LUy4UEbcWZ5KHpAI62InABZVtk2IoK5jrS9p2WnVK+P+CBdczwNUXspqRuxcFKMjc9QVQlv56yfN8F8hlwJCJ0EtTziZmoSOAWyu0AJRVbdPUqgENYqOqVFkpa0SplcTPCLKasv2rzxU6rzl6RRifhtG0P6wFDUiLU6olcjtSRao4CzJCPwVxhKl7qmEUdr1ss2D7lGrUhZbzMaSsZMqlNvVxhbByWyKZ4A+Rp1dMwuMlB3d9QSgxVNfEEiNWe4z5Yc0mcU3jtMWUE2KqqDy3G3iZwLmErJe9tl6HvYr7fkic7kwafRFeloEaVZkEYL1PySenONVdSYPEnUC5frlUpPHSJLMmL7D9RXCqfjPnpNgYGBdXjkcCmzeFBwdgWSO0BWp0hNG6uZk6xF7EPCVPQIyhrNswcOjyKO9cB1p+Lyvs52A0ovhUcX6QuVgJQsnIEr4Wo5fvFI+6IJoYI3NylVkUN9i1ELMOQRjeM60e0131s9hsMG4axGEd1jaj5SLaMZjjhe+Bwu5owncGg5TDpfI0wfEXWZdrkk9RtsRwuMjyKq0MPLM7aNiEj4l/D33xTo/7IQVQ2tuCLt1JHSDoZ84Kx+wN23WIkR1c4i8GRum01qdR/R3dJotvhKkhgeEkRjyeZzhKSNSLwmeXSL1mlxXUkQPsJuQfP9Dl9bkfc2qC2Fk2KCUu9y1wxxpxmCUGf+pztqZoj0KuW8bLO5gNmRRPy5jXeb80OaET0MMQyRRa3iaHKNMPqE18rx5zvurZj3iyuEyQ4z81E3KUfdMSeRhrh9oC75lM871Jwe8+g5K7FPJF6w9tps/RY16wpzEGC1SxamyVTeMohdNpVGJ2tgGylftHc0jnTGG+gWA+rLBtEhoxHmaOceSgP8Zy5Ry0OUOqStz3wRbRlUGc3gno2tYnzvsgxLvFxBbJlYH2Kuswz3foo1v8PTMvqjil2hMuo2aTRiRnGI3bJw6yaF0KbYOEyX3+HGj3TLOVSPiPIIxQ6pLfbIsU8QemzNBImYbmdHvTUmmkxRpw9kJwZJNEFvHjG8uuMobSBWf4EwiUmkLmX7lxTvuiy1BVvPQx03WIxjnnsyDR8+fOoj3fZ51YONHiDb73j0rlG0U3behom3ZN1Ned1bE4wNisaCO32L7opc+BfIiYlkFOi+T9lfI1++QKnD8KrCOc9B/IC9hPjGoPooE09d1KiOHowRNJVw1SFNHEr/AiMJ2N98oiN+YvWksqg0wvsz4ixg62XMKxtz9wzRb1A2e1RChR5nSA8yZw8F2/uKXv4jxZPE4PyErKGC+wTaJ+pHLphNum8zBqnE5mSHPG2wNV30/Z7WPOJMN0k2AyKzoGp+x+zJJAwveZJSvttW7IwQ+eN/BUNSQRD+N4IgLAVB+OFfyLUEQfi/C4Lw8W/Pzb/NC4Ig/K8EQfgkCMJ3giD86r+QCqQKjQ8Lkt0eqT9F2cskh5DeWQt9cIX3tYUf1Th0lnjSCidrMggiJnVQLZPWfY1oe8Z0pGLvZUYXOt7pnOdRwS46Qs5TrrsK05mFWypYYQCI1K0b3sQy4xQ0VMbukH6ssd1keIWEuBTRNhIH8ZpeT+P41CAeQe39kstVhG+9wNaPiBc++fSBnujxJ+FfooxhpdnYkUqwq9gHNkUL5rsFVTHDOHyilv5AFewoHpf0hQRxmOPt5oiySu9pzOusTn15hbE85s2qxulWQcpCriOP7mOORJ250aWf9LjQt1RSSufag0Odyx8+89WDQD9d4JzCtGlQGxnIwinHiYM3VGiGJkVk0c8cwpFFfXeBsu0S1ZucvBbZGhqW6jN9q6BvlojZnI2yJE0DbvVXOG6AUGgsBqfI7QbxukV6cUdPCOkeHSFrV9xpLeKLNkbSJA37/CjlhE2JfCQiZh5ap81zEsqtSTmP2N5/YpD9yIAE7+OS8UVCa/+CF+oGKYzIXZ0s2zORQqJEZC7sWExB8Zo8ygPCoCDb7antBZTpBekio74tGOyW1AOHzqFGIc2YN2t8ODlCXnqU/oAiqqPNVlzsXzHLZWYfBWK/gToc0qx2pJJAgUEsH6jaMc/iBYLk0ZJkhHBJZ6sT6wZZESMn99SXx6gPHjw0kcMjjiWZlpZxJFyRJDU2YY/7scK4mRKcPNGoNzi9U+jSRdpPqBUOzaXMcaBRil22QZONVLIzA46aJpvRDU7SZd+0oezjHyqMpoC6MQiFZxwlKpKm4jQlBq9D6lFGUfX+1UUA+N8C/+Z/IvdTfoP/CHj+t8e/B/yv/4toQJnl7IUBllxxuzQoowzj+B+wbU3Y7/Zo/gMvjC1O9sh0EfChHbIYu3+zfTJbs+U5V52Emrhg7s648Y4xyzqR1EEJRfb5JeVuy+t6gfyxwy+eAvK0ZJ+J7GZ15FRgu56y81PuW+9RlwGHQUb9y5Q/URSe9Zuoe4+Tzw36UUEiKkSRTmMhkQ1GDC87LL5sU8gRY1nnYeYy2zyQ9u9Zip8ZeSmdcszQeUl7U2JHLSQaFKHD1Ch4Ctfk6ZZqN+QkLjCqNntXIBNDJlKTD+pLMusl8lrkSvEovOdEqkqvKdMwVeriiqvjCfQrJHVL2rWRZjIzp4m8P6eoBAQKGFooVh/7ZEyrrDFoNTFqAyyrxkl7y/k4JI8DpM0nXMFgNauTTL8ljSW0QYPaNqa9P+DU9rzVTZJnf0rgDJHkiMbRR4JNgtGxcBsbMu+ATIPGTqQeKhw3E+rtGDuX0BSJ5ieLZGKyS0v8dEE8M7E6RxRfO0j5iDND5KFcQ/KRSa/NWntCUq5pLArsRpfBpY3gqqRWmyo0KB87FOUxkwC8sU3TnTN1+ty3F4Qthcb7GWUnop42mPOedHvNE3U+Kha3hy17c0R58wN+bmOfeNAPCGtzdobBqDjlanxMLrcR5Yp74ZhjPyOqVyjnCn7LRzk3UJ06rVpCszNj+1ylOv6nKOqC0tqSDQzM9jXDwzc4tS2XyYiwlfIYd/GTivf8imifUmvUuWz53BsJuXVCLzwn6Tu4NY/VQ8L6uybJ5GsWSY8qL5EePA7GjHzqEmYH3CzlVk15FHfsQh35cwOO61Tq4V9dBKqq+g+B/2TL8J/yG/x3gP9d9Tfxl0Djbw1I/qUhqgVmQ6ejFjh5StVa0c6/p/WppKXvKIo7wsYcfVqiBSadeZ/LbUycSLTHPTwxpFnMCK9T9OOYsX1L3hHwWwFSfcbp8yXWdsT1oUd6vqW0MzaFh5EWZM0DWmfAi+iEeu7SH1hkL064XT0jfe9y6M4ZajrCcMidfU/a0EiSiCcpoant0Q4fuYgTfvFwSuMwRLJsBLdFk1My/0uE+JS3z9cUDR+5+ETcbuKbXTadBo2mRqOeMnp2TKe8oDoP2WRgtG6YJwG2vObvLyz6+o48OlAZGww1wxAyMstiJE55pOBRL1h+NikxWRQWo+Yv2J3JHAkRbvyBTqVDpGHLXUpbprOfsek/Ua6mfLrbkix3fLobM6pSdKHJ543NaFYgGFP+5KjNh20XKXRYa1/xT1sCzcclUk0jxudYfke0dTFilb4fc31IeeeuaMcCA6Hifn/LdJyynxjUvh1SzZdM0imLfsDULnH8iOOkSfysIBTfkxU2t4rJvaSxCIbsTgeItwU11SRYPeNzxyDyD+zCivOvYw49h7YJUvJEdzCha+uU3QNYMb/iCXl6RlmcEJ4OGAgx80rkJHYQ+wPsvUWnEdAxC7yDz0H6Ne33NvrhGYL4hie1T3BWY9b/wM1gS7r10Q4xkZ7zpFT0JyYf9i6qvOU8zdk0RNzWK+bmiFg6kExfUBU9NkuH6mmJ4q+JYo3axQNd/ROW2+IXlYK13ZGWAcppxEoMeJrckEun7NIlD40tR5t31FclRn+FbI0ZDyKW4w2md8A8khC1AVfBksw9wT1WCLbXtLIMO5wTH1aorsql+tPTf/+qcwI/5Tc4Bh7/hXFPf5v7T4UgCP+eIAi/EwThd3kaUEYPZKcFtcs+xwYs1Qap6nLoiGijI4LqBKH8gsJuEi+ecHOPtVTj7VJG6n9k2xQx621yr8kmWLDJbJqdOn72isnSQLYC/vymwtzvWE+GOGWHrGySD2wCyWB1obOdeAj3IsZaoeeF6IKDLpk81YdI5oL+qI+Z1TnqCQxfD9g5NlUwYOVX+B0D9bnErXLgtHPJJEzwO39A9O+peb9EmNvEIsReiNaeU0fHSg2MRR1vJuFbn2kFczRxzUG1eV4XWUQGXi8g9kO66YKu8BKkFq6d4h0yPl42SNoH0m0TMRG5buXUqJh/+JFu/Y601BA+6ejyGTdWh1IpqU9iHs0Yc+9xbGzwZIvYdtn3P/HD8okwjakEnViXEanznSDQ75YcbuYk8wnnW425FhNpG4brA432BZ3jLrWqRb034iI06BxGFKMDbc/AbHXwoj3JoOTjZYQnX1C+rTFbSzSlR3ZxheLW6a0LsKc8bkpG+R3DwKUXz4hWK6QoJr/RaNRd5LZMkOnU9jFm3qAf79h2dMLLI/K6wdpO6SgtmoZDWm+zdTZExYSmd0ygn+IeKWTNHHvvI9ZCoqxgXTlIZYP9mUfUuENR5/SKLaeVjSAI9KgxfOwRNHyCtMmppNB5BnYD/iQekC3fcPBH5I0DdqOizR84UVSukIl1jXU0wWiGuHuJxK6x2QyZzY85iDLrVoNoUNIr9uSyRG1Wxyht1MZ/hJBusT5v0epjJPEl55bArr1BW1rUDw6xE1MVE4YzlXzcRO6GtH9Yc0QbKpFto0m/bSBGOvs0/UmY/yuvDvzL/Ab/c+77/9mQWYPLSqspMDGQFnNWItSrGPlFxfowIQi/RI0KjOITs1dDOm0XP9WQ9g8MDyLh4YzHhksvuwUqrOMTRv5nIuEVsp8SBx7bxgPlsU4e1AkGLn3xjCUJWTJEUFK05R5zNMZWZMKngsEzj50+o0pMhllAld1xG465PI1wvZjBD3XKepft6Il+0UaVKto3Le6dLbH8B56d2FhuxoeBhNMXsKMW/mcRtVFju55Ta8js9hr1rk1tHqOGNksZarWMnuiwlEyMH1c8HAtUI4GJlyJWE+pRHXEJRvkJ912Td1JINNIRtyGvJzJJN0FafsVu95HP9Satfo/dIWakbdD8hFkokLckZB+kXg9LuONoc8xyuWNv/T1qkUu9NsWtTJx2zv1I5F9/KvBLAScKiC4Kqg8ipDqfBA1JjskPFn055ODvCEKF5NmCIjSpjkqKTOLEl/CsNWVogZrQt0tM2+Vx2kbu+Sx5Qh4MKKUcrVNyo7Z4tn3k8x7GdQN122DXjFHjEC0scaTXBIsVfnKH1rRRUwXpUaBjWtS2Mub6iWXyJdskpDc6YjdNsaQZT48SUpShOq+YpQfajQxVFTFyCeXVge50in+io6wsio6Lq6p0tgck+RzKjxTaMXlukK4TZtqaD2aDvrembdwS5S8QBUiDR0ztGbEgs5Mf0d7XGT17TRLByBzwUZwR0OZcusd3LeKFQCEapGOBMynmtikQ9CQ62wZGoRIkOzaTAYJ4INooHCk+81Mde9dkjI6bDVm0JuS2jXZ0j/HjCPwcUhvdWpIpFXe9JhI/vWPwX1UEfspvcAIc/wvjjv429y+NrAC3WdBWliihQmvsoERNdvtbGstjJqlMamVo9RrD/9AlOHXIfYmR4TDpxdirkF5oQFvjUNMoWgH2xmDHhNHYZ4vD2iroCQp+mnFuQHRxTfPaIN9VoO7oD2NK3yEQu9jHD4hmSCX38e7m1HoPBEkf7azJzhWxc4dFyyQIdAaehViu8QdN8r7ESbvBIwX1okPYGHGyd1m4GdpeQ1dLylmKftFDzFKEApYtkKU1VtWmWR1IlieoPRE72jP4M5uDOWD17p+DN8B56fJhIjLO7zH/7JzJ+0fOzyv2tZz2+y62JPBerGGMPpMUC14nGfW+zsyL2B1EFC8mNnNaVR1jXHIdrrAiA39URzNS6tYMkxZa/ZyBf8D1bdrv1sy6ENZUHg93CJvnvPgaXhx9xWr5yPp3Nn+1mVJe6tT7As7jPcJdk5W4QfL2rJIrsuRAflRitZtoAnhXfeT8jpe5SSgr6M2IOBPYc0QZ7en5S8znPb5KZ4iij6vLHO0PTN9Y1B5KisMtiz9tUJ+MKRtwLBUkoYDXHJBKB9YPAWl/RVvYomoJyvgIwdfIjDWWvIfekL4Qk2UKY2tFulO5/zzDilrcjgOGx23W2T3P72IKbYPrZkxaHS6XOpQHvg0/cZTbeNsdrbrNrqFT3+/xHvogeYhLiVVY0OiLbFszXpZb3lYj9BOJWjKmYd9yM+1jWzKtZknsKUjllI1yjLBQMRoFNecIf5GhKyFGL8bvNEn2v+C7JCDezfiFm/KhPMM4SXHvu5ilgDl5idj9PUKzRisL2U/2SHaPk51HcO78JIj/qiLw//Ub/F/wH/cb/D8D/zNBEP6PwJ8Bh3+hbPjJUHKBQWKwE+ok8pqO5nIzy2nFBnrk8+xkguSbBI5J1dohLhu0uw6rbEbwaGBZMtVIQPK7JNsAa/s1K/eJtLFnq6SMyhrR5xHKqz2tnkWwVYhvItxyRO98Q3Cz4J8+HXM+FzCvPlKdn6Lu13jZlvbQoNt/gbTKUbUNpxHMtDrLfELP8CldkWbfYZUWeGpFoqoM7nVmygG1DNC1GkP5mvsTi256QbzOKFKPvZpj6ge6ix5iMkYtQuR2xMo5UCtruIKI+Jhh9T2ys4DariROK0o7Ydo+IUg8BrZEuNaxjDp6qyDWK7zNkkQVkf1zDvUanzcJaiNAMl+zbGzIJ2vIXBbVa65OS3TjPf1BE+mvHumOXzLr9XnutFEAL3vL//IvE37//RMXPYd/1O3TMgdU+ZYXxj3KC5tyBNv/IMXfp3z2t9j+EUs54rXcYN7yuWiKhDcdLGNKcliCpML1geGrGq7nkPXnRKsm3sSl98st40XMo/gnTB4WHJ2qyB90NHnMtDVE+JwSHzLWdkBn5WI3BLYrmyr9SHR/guJU3JcmL6Q/ocoSPPlLtP0HlGHMw51F/bTicfmM9uqRQQdKr8PNbRNtW0M8rXgfXSB9/oFNa0ENnw9VjpX1OKoriIKL702xmwUN44gynqCcXVHaj6gLnftqxbMbnfVxTpVW7CUdX1WQnRaSrNJvHDA2CjdRhYmKVHOYO595Smy+2NYIO8cIic/xyYJw2WEaq3ReuQweAsLJEUojZRGpCL13OFGKnrexPYHFuzmmdoouqeRMqZZfsglvqawhmRFwv/X4dTvhr/yjn+TvP1cEBEH4PwD/GtARBOEJ+J//Lfz/J0EQ/if8rd/g3w7/vwD/feATEAL/4/+85wOUZLx9XKEcaYi9kF6ssxp+iS5MOa6WaLnKRBMQkgh7F9CqKzxkEY2JzusjndCPkWOJf5Zu+Pu6xiHKiOtbflMTKeUA4UZilzik7gl2LrDZ+3THOk73n6O8u0QRKzbeismfG7yZuzh/JaGdOMiqRp6MiWMPZ7ehlmh8c9njeexiuwJ2x+RQV3BWIatUQ/iVzDj02IwVnEAgqbVYxjFXmzZHSZe6IVLlFroXsambyLuKcLxF7/bwwwZiEnE87JEFEc42w7E73OxXjJt9iGUWsU4+MDhhx3QX4m1zekoLMz4w2XXxL2rI5S01qSKPHygfE4bN5yydnCKJyfU9V//GiOxaJfg44etnIy6Pf8Ukc+j+us5spZMvP/FjekNr5VIN3vDllcH5VuPy3zqnpbzA/jwjNj7haF8yeStTnc6oqyZJmJAZr9m3Y073JU8tH/Wm5N4t6OcH7r6VuJAtkliivLRJ1yndo09kqk3UdqlzQfRUsW+VRLOYf7sfsVAN/npsoAkB6rxieanT/3bPuNaia29IP0vMWlskmpzZMt/eL1GtgljziOyMvX/Ae2ribgu0wWf6h4rE3WA3O4TCHXIVoJUtticfEfoHLr9tUQUBXvGMOJVpRhFKLyAo3zARlljdlFjTKeop7meD03qBEcTkzQS7+CW7ywgpeM/NxQNn2gElPSU8j5j8sUtPl5njctTP+Rw0OPY79PKQ907J26HDeKMR1R4YVBKLIsSwIzquyL3dQ/YsytUEW/mM5jZZSmfMRo+8VK5JZwKipSNo9/iewQkC9thgUnUxHvpY+h9JphlfRw//scm6/1IiUFXVv/sTl/5TfoPV37ib/k//i4D/H3sJ1URx2tQyj9JukO7alJcztiuPj2XBtqnx1TuFvb2jMOsYP8j4rxO6ksoP0pTGuYry0OfXkoJ2L3PXO3C8jsiMY4L8DXk3JVxFmJ0pu3WNfmzS+hTj379CqNf5MTbptlMKt0vXEtjG3xOtP9Mcv6IRbvlm0+TFawVXK4i1J1S7SYlFRz+h7twztWC4K9g8GVTGMfJmizmOUbYpHUtFNSp0c4+fxCRHB+Tty79pgvqsQvQdlCxGFDTSrI2z+8i7kYXuFcysT5x6z8iKlO9ln/ZNG0EQiRwL4bNBS1uzbyqsq5Aq27Dar7GDiDg/5VQ0iasnDkJAIcGbbcnRnw/QXnZYqBVBzeDq5DmT2pL23QI3dPjD7B5Zf484V1gVDexmwtdxD+fFAzXTZur9DlGGX1f/gHfk3Ex+ZLu8oZjXyL4ecXF/zS5MyZd17NijWTRJgo8ojQFdY0W/O6SKEk6uRbbnEWmjRjtUeT8rkKtrsuicVXzHL195/A/+e2/49OM1yexA5vjkrRXW7+qUjT2aG3JLiGV0sSYxkSzzbrDlolbw7aeY+0jBCNqcxDtSRUJ9MqnpQ4LtAqm+plFJhLxmYv8TBlKPN6sG78MtmyrmtFT5WC7o2zvagz7r7Q3ZvE3n1ORza0O7ek3HWJJbDs5qw9NRiXcXYm4mxIOIJ2tM056haBWmrLKayJwNIg77lH3T5EtfZL0osUSfx3zNUa6wqAyW2gonN9knIlUsslIT9HUPubUhyT7QX0Dj+IhVXcSbT5CFiI1hEostpDzh3FSZ5iZKrsJS5PjY5+40wzpYBNYGtaf/NH//ZYH9ryPEMkNzSsp9Tqpvye0mx8WesXlEov7Iq+zAdTAgF76A0Yy3F3DpbdmYLeKZxHrTxXALxJZI2Al5ofr0gle4TzGlklJ3ImpnEivRRHAEhFmIenzgGz2i/XhKc+zTyGK8dp0gFSm8Pka/SXhoUq/PsIUlu9kVmD7D/p7JfcBpP2VpzZhnMRe+iy6L1OSUqSHSbBnUGmM+Pu5pdPc4vsoh7dIUXMygTtTwaPkln70tcl5jO+/QOBFR0pTNUQd7k1KcV+TBM9atKa1NmzOpouyHbNSU1Nhx4pzw8DHBN+bs8orLxiOdTCbvnDPbVHyPhz78DfFhxrEHX/zpM8oLgd7tbxkYf4r23/YwPyVMfnjL5F3OovcO71BR/VLjH95biO0WH00B+eY7vGFBw444353Q7iV8dmOKVsWf/rnFVPslZ3+SER5mGNaAf/ZHl+zM5O/9qk6z+YbayuXj5K9p/0mL32invL/d8b+/fuTYdihWC3558hrRXZGtbDbyI+si4aVU0SpMjk6PGP/le/5yJiH0j1jFW6TNKbftBq1sxjrwqOca3ekT/psO8zsHZR/TSp6IamOii4r93qU9CcmVA3EjQ6nOuUsfqKc6I/cLcm3DD3KAUtZRzAVRz0Vc91HlMZtwxnb3hm53wXYg0b05pumuEAZrME+5jXIi0cGsyZxmJet8iykeU362iWp/RaHtaQQ6d9UOy0nwS5E7PNrm12yl7yjLNnc7gVq+RjuBOM3RpxlPcolaVCRiDT1tEuk1Pl4u6Qz3GEmDo37ItXCFGMQ0Z/ekxS3SiUq4bvOptaVftojKa7bTirE8QFaeEbm7n+TvZyECpSCg12Z09VO2noeibFEDlcPhjsOVhhU0OTtNKcSIu+SOsX5E2ahDmFMzG2iPE1Shy2XNJL1r8U5z2VseLXmPouasSg3jQqD5TuehCtDOjqkf53RilaqpoC88wqMGlhvzfl1nFBsYjs1S8XEykSrxKdoL3uQJfGyzsn3uSw1pkVApOnfhjMf+kF/UCqLvEtR6m6ld0b50KaU2D4lIy4G4NLg/6BxlFnf2jjhMOde2LCoTz21htlPqlYsVm2hzg1b1xE1dRXE3CImMKqmYnzMmz6BIfE5HBbv1hkQOSO+u6IsF+9c79rdP2C92iA9wfjriH/7GoBfNULOSsNOnrf7A4VPGw6nNytPwvN9yPhoy7NnEzhusI58L/ZLhpsZfFjt+oRk0FJ1Jw0fM1nQMlZbT55DLtDtr1MOQ9sUYdi2+fHOCeq/Q7viEukfpVPTbYwZKFyNVERs6/+6/d4EXgtjrUFuf8u+87vAf/fD/YncvUSZ7WnYDnTuMQ4e/8+uXTP17/sk/m6F0Cs7cj4jRgMZ+iGLckUaXrMYqqhtRTuDM7KIdH1hpPuHUwVamSH9xQn+xZrE4JrzKqaJjxOYGNSwI8ox93KBd7dFqNaZzEbm0IN/Szl+QXYWEgs0oeODHZoy0Oae9rLFvf2YUjCk3MWtnxWEoU/x4Setkw04TUPZ95LJPvVunlB9J3S59c02RvEEhoO07SIZIx7ap7M80D19xKwvcnfyBYX5Mumnia1tkp0QIof8qJi1rsJ7C7JKvR39ka/dwnyvsdmMGPPBF91u8fhtNC9jt2jRkjYcyZthakgztn+TvZyECCAmOco732aAsHKa9LaI0xilrXH70yGciWyWh/sKll9tcuwY9HPq7GVFHR5AyihOJ+0MNp7eh3cko5k18SSPcLBk1MuYfa/x6MSRvyKTqlnVsYq1FimyFc7REW9bJ889QGgw6XZafPV4Mnig8BamskyWP/PFlj+qzy1nmwtMVdvEJ+6iDbViI5xLV3Ea+7GAaC8ywxC0NUhK6rsWmMaVST3klV9wES/iscS4r5CcGzcxAc5ZU+4RMquNKElpYoKIiuwrrYUr62xXVUKChWbAKyaMExYbgSOWIkie7xA7WPD9uc/2o40xSDnaTv38kwcDgm9zCOKhITx7uzQe69SaLmcT4aIHzdQuzccEfVzpvLJVKN/nDRKBd/yPtfo523kQMPTpRn9SMKYKU+u9KivY5diiz7WjEootZ90h3LaSzJcWyIhMXzGKb2umXxJVAuqvIxS2v9RaedUCLSzbHG9R9hhcEeE9bkkXGtW4QXV7h6x7muE7276/4hb5mPWmTxRqFGLCv/zWl2UWzXfw0I4xMnCBl0c7JhhnxrcvxRYOd95psukFU/oJUDGkcPAblmnVxSliPaE03MBSRtzGPS4uxJtPYSfCm5PPtBnG+hcIjMloMI5FCNFE7vyVL93jRAK8+w041DnGTM2OCU7cI9QXl8JgobrCWPzOaOVj1PZFTR5tYfMpjnnkmUksjFGSOij4b44ZGYqHXClZzjdEyJD0Crxuyd1WUtz38xGf9ssnzxYGpKCBJj3TlhOykQXnTYptmbESoPJv2fkxS/pax6bHwLulQ/0n8fhYiUAoy+WOJXS4x+gJKo04iBhQDB29j4h17nGUWW39C+3TDiWuimwlq1WK1T2mVVyRFTi6UxK6HYIk02h6CnlLJGsI4Z3h4Da2PrO0dpWozXB3TO7yjuHzBqvC4apc8PULXyvmQudhBD2dfYBcmt1WE0+jRvp8R7CUYnREWEecXbQ5ji92Dir3ZY6U9WsaExaKkqUjoLZ/7hYkluPRd8JWEz1GFxQrjpI+n1rD2kHcLqnjNtinQ0nV0VSdQ5pTLnJpuYUyWCBcT/uBeoi1FBi8ltrWId3JOlAq03Wf8g7yG1zijKZv8m/+Wxrc3f8lfmE00Q0bcNzHmAa4/pTI79L7sI/l19PUYuXDYV39N9LsFz5Q+uy9kfrnXscsdatLl++WCV76B7gvIxpwPs5BUkSjGH4nDMYenAvF8jumfsYnWXDR00juJTVuBXKTZyTE3PkFU8XYZ0pNF3PR3NLQemRnwzC/4TmkTBDJff2Vymv45wjORnhmxmod8Vg3Crsh29oL5RcxJNaK5TVgbK7JNE5IPuJrJIBHYXiZIqkLPS/GKE9Z+RG3XwIlXvO+3aekixapPPXlPEi2p6TI7u8Uh8KlVV1SuRvp8hdrM2X0cUZy8J45kCs8gdvaIZhvd+x6l0JGsHsF+jyGc4dUaNJolH1+Y9OOMahdTnFqErRu6f1lRa0kURYun4rfkz3+DLTXZfJji+QrmhUbheZhlh1254+yphRyvaRyrbEuD5rTJ8LRA+DRD99s82FNmoslJvcXHB5PA9dEig9JssRumJJsbXkQWymrHtltwEAakFzmD7cef5O9n8Rehmsn01A7l6yEz4QVSmGOuBZLthlqh0ay5JKw5Fkao0wH7ek7iluz0Li3VxmuWyH7IrvZArT4m9GIW24hUFfkkDqgCgThZEXctjPd1ykmTSRVyI+voVU5nZVFkCSq/plHVeSZoDJ8HfF7JvN9oHHopySEkvW4hx1/j2C3sVocHPWHypDCMRfZln8Tbsk23VM2YdaNHtJFxdAW5UDhIFUttykloM9KGWPcD5HmTZVWgJTP0wiHe+oQfdMRExDJLBEFBjmQmNZGbbICTe0RmwMM/ywkf6iipQOOuz2l8RHOgEtdNvM2WWmrwpy/+AU23opIyNt/vKNW3pA/XjK0MRe+w6/RpBp/oyRbO4GvS5yOEP/eIXRNXkvl0LjJLDVIt5XE6A0njaSrjSweySYYmxcx+94/5J5MZ9xW0nSWNkYMob1Gehcheg3rWZld9ZKL/FbePn5mpa2a7KZebPoNdDV+p8d61CTOVf+3vD/k3/o2/i/3M4lXisNz4fFVrU03fs5/KrMyEo3TD7rtvmLkedvIbxpqLJ8iETsntmU0rP2E22zEXcpAy8p1G0xEx1BOG24CsfIdhVnz+4s+46H5F1CxJpgKqXyEYEc5XnzkEIrnn4kjvOT1oXDwd0Yqa2MLf5zI8xTnyuau1KF2VZFjgvJaQkpj9+geyuwVPU4+l1Ceov0fxSpKjNvuRycfjHK3+Jfp0SU2DblfhKNfxbz8hPDVIr9eorYAgTpm1RvxeGOMVARNzQXwXoV65LHsr+jfH9K6uGHc1eJ6SyBUEFe35R4Tv7zDzPe9qHv5LHySdutJEThpEaecn+ftZiAByyYdiSjHPMKM53qKPHKtk+5z9aAT7c6YdnffPEsLmGWp0RaCELIKQx/UESbWQVIFOfcRB3mM7EnK7DauMKlpxoy2RpJSHTwm738gU/RnO5pFz6wJhvuNB9vkmEImefkA5xLhFxPXnR7R0TjT0qe9lCBZERovN4B2u/wEnduHbHb30QBybWOsSIfWQhQpJPqfKLbK8y+DCZdW3WWUORtRk1lrjqTpI1xzEhJFUJ3ccpvmOU2tI80KmiiK80qW0K8inXHzuUUtjskaLZ1aI2M3Z+D56sqZxpTL41QH/NOT5L3ZIwzV6dU/2l7/HdyJui5xt/3tySeH49BS1GROUJkbps7uouP31nqmxRyxLjOCc0+49t0rEiRby4rXPy69f02+dEerQ05uIeUF0XDA99AmcY96XCZ+++cSyEigzhUPXYRb/mt6ZjGlIDAqL9fWAjhHzfG3THkdstGOmekH1cYk8W+IkPl/rBq/znL9wdlhOyMdVzKeVT9hoY1jvaS8Sph980qEN/YhCe2Bhx8S6hBwP+LXmsD/8QOcLkWP6pI6D0pD4UXvgVvIQ9YIL02BvvkN6mzN1PdjpKA2NskzR/D3WpzZ6M6JR18iTDmtLImj4iN4SYfXPude/RwmOWU+aCNWcUVGSPkK/LTIa1On2apRXGd34jHiWkLp7jrQOT5lEGohc0aAyPfSsYq/6JI0NpZMy0+r4g5zLpAUWfKFOaPLAIIRelEL7mruPFVqc0OlHyP6UW/9AMn+HPYyImhJBp0Ubl7O8hrn+gLuZo80yFPEJafXE9f5n3mMwLEvyQ4GQ6khSQdAteVJCpKMdgfvPOAifsYXPGP4C77FEf3bAGfeQ3S7Gn5rcDgOu7YLDpxxXT1CrAZHYxGkNuZLGPPtxQOfWJ9dDeonCyFSpyyLx54gfLAFp2KTAJG7mfBjDjWTyjD+DRpO0NPCar3j4YsBkcM9JekanOkKKPxIXKdbuHLXXQNrHsPFIyojl9pHeZk/V2REEZ5j6nL6zJ6vZtO5j3FqC8qyO0fQpRi6JkeI3beZ2k0lRYeQHjt0Ka1VDsxqsLh6pOr/kRBkjhlC09rzq7nndfM7zq4Qs6dOUZJS1RbmsEVCinJ2SCTnFzEQ7yFxYL3j9iw41XcRZHTCfVBRpyVEgELsG3dMWiXsgzEcY6QT51mF3e8AM6jSjEu/+gaTY8quwxt8xBM6XTTC/4HkcEcQFy5sDm33K2kuwg4LQ31F4M7g74Uutx32cIv+ZS6vmov5qT71lEpRgfV1Ry0wkMeDjfYqUZZzbSwgD7ocBvzpt8+e9f50sdHjx0qQ47VGnx94f8PjksjO6FI7KJN7iyAqdpzazJw05nNNfeHx1HaN5x/RDnWI1QMgGCOmS7n6L1OlQU0067gClivFHHlW/ZOPXoNkhvYV2dkOrGZK//Aq9OGJDh+NuxPhIIe8U7I82LNKEohMRO7f03TryuMbx4Wuwj0jaa1qrPZ1tyge/TS14jfttQKG3eBq0qK2/oqb+JU0hYFq3eIx87tYd8m5J+oVHJzrGDE9QXrXZl1+hbmwOcsHmdoc06dO8M+gU8GA9UR51+K3ZILP/HiPr72K9fkNkZ8iFwOgo+0n+fhZzAoos0awn5PISq7HBqAqWVoN4c0JTKtk1foshjMh+jKnpW6yFyFaJOT36EZeKUVQx+HGEYi3Z8YrImjPMAm5mManSpX7VI5vNiDotjFIi1xpECWidGrUngbrnojgn5FZCEB+hlwe0dkbitDG9DtnbgsaPOfalwjf7A07foHW7ott4QSD4jA8yTicmEmB7OEfbBDxaDzhRF41HlobEyPdRWwm6ZmArO6KiTrlIUEsR0WogZgeQE9TMo2g2OXw2UdUASzhnb5UMrpegRjx1e+x3NlU74Fix0LIz+qJAmhZs9iWYLTa2yFFS4OoarSaUiz5x4HGbDJH0GKgjnMyQZi0KT+HPLg9Y7tcstSnf/+OAprFh/fdSXg4Nvvnm/4awsDn54hXzuw3l8RGrXKVxLPPi7rf89eEt0+3X/KM/1RjV5twHOsfNiEnawO91KeM7wmLN5ZmGu2rSb9fx/QZz7wHx6Aj70xStHxLth1y1bLx5xaYnMH6e4M425OzpxHOCQY382Vf0ZwVulvPM3WA8e8GJJbPbNdiqAmU3RBUk8l4PKQ0p3Zj8uUG83vN58wHdviCdzQlGLxC7BnV3z3qsI9UmZCud00OfYLcgTAIqu87aAEV4Q9sxaXgpq8rHMhKO9m0OYQex36Fe2qRJB2Oy5aA2SPbQHi0wHZ3QkFDuC4xMRtcVWuYa145ZlCXDD3tENWArqNRWX6CcKmx9Gad8RtMxuVtkaKMutaMW61Cn/cOORpZjuxNia0yKSNVWWW9KtMgi2dm8FQ+Eb2oo3++5E2z0xRK1+gXzbspW+amtQj+TL4EiK1CvmtwJPpvel+heTjbpMGxExJ0b5M0JXqYQnQuILQc/tDCNNn6nQ17YHGW3VBcrtC8jjO4fsdmR7R940yixnRXZjUCsnfPCbGDYG3gLlZxRRD8QdHKydoKvPJLbffr7Fc3hgLhaEsQxy5mA1P2B/Pk1drbDUttcWS3Ojf8WcltnEf+Bu+SBydzBPepzNQ7RLzL4UmHXSvBlGT0WcG2BVlahdUM2KwFvF5C8NPhsdrgXc+JcRBMN6oJOlS7QznIaTo2N8YEkz6gfb5nVQabkRHRgUlHU5/j5R1b1iKxu0xlsaSUJ2tpH1Eu0QqOQI5qvHe5MkSxfEnhQe26Rb5+jaOdsS5ns/oQHdcLj1QnHvWdcyA4XtsPT5wnbHzfciGNyS2LdOEWSEghmtOTPFGmNF60/53/0Jzbj6goWDeodm1mzjeL4PBcfcNYZ8crBVCWGrwJKL6N2n5IqHs1EQ2yfkXRl7rsD7twFv1M/0gtiUrtGUDMQLocMunVayoLGO9j5Irv9DU+ZR2ui8bSZEEU/EE0SxFkP05CxfBf9qeBgNlgmFmJnR+sLGd8S0C5PsFsZp+Ej4XbGPvqeXSlTHmvkiss6tFFVgUTLqNs2tVENQSuxtBYX2ozjfYSvbtmsh+Q7kWwiMW8seBJ+yXHQo9Y5Jkg1PkY5Nn0elBoP0Y5Y11A1l/UyomPZeJHJUH9GhwTtKke8mJC2XPKOwDrcMNqE6LcNpk/3hI9T5o5KyJ7p0OEwuaO0HzAmAoKdkrsazdMD1kmbF16B62s40luKwRHx5ZLxzZ5nPz7/Sf5+FiJQlSrhpk9D6pNdX2PmBb3WAjswOFKPse0abafBy9KkdXxDMdQQqie612ucVMFbvGR7PEOvdWCfoTV3xCrI6wRkE1+uoRo7amuB+DbhONfoJFu2mculDqbWRZVL5HLPSkm5WSzZ+j7SVMAM79ltzuj4f0E6t3l++UeWj7/Hf/Ujj4pPXjsnOjZxFJV8MuO7bYiQhBjzkkyJiVYqQqhTLZoctjJLwSLTAF0iX/ap7yL63p7Gk4RZLanUHNGH1UziNronYYQw8fh0N8SWVXKvhVKG2F9I9OIjvqxqdCSbx1XO9ysX7bCjxoTy047Hm4jiTqQQazipTEtYM9SXxMtrKuORcJGgJkvyzMDMepjzJzZDF/k0pb2doU1sGr/+Ey6OcmRFZny5ItAMqhCi3CW9sHj532nx5tIkNWK+3x8YfKrYzjV4MtlkLbSTAUcXPfaPDRY3Fv/+/+Mtn7MFWsvmzCpZNV0+3085+pyTDHIc7YC88ehMfE4UKFYL1n0JtV3nQzLj61oNwzriUGuxEF2aSgPJz6ibUw69A4Xj0s86hMsj4uwjZ9Ee1e5zmNZQtILOrOLohwjhcYitXjF412Y4v+LqQWYtJ1TJAqdYIjspTWr041vWWcZ2s0AOjpjWJbqhQ7sxR+wUJL0GQ1WjZlzzuM+hfCJXD9RPI4psw5Gl0e7oFFHKeibT91s0NzrCaU7Yjmk/C7kOZSZBgeEWOG89jFJFSQvuqs9Mew16A5NaYGP3LZpFRvqyiVZ/QXOYYT2PKcU77t/2eLE2yW7bWK82SLlMYsyZCxWtlx6Ref2T/P0sygHNgG1bolGKtCODqbImcQSEIqL32SYQejyMvqMKVPKNgvJpwlwScTYhhf4G/cU9tq/j7w5okwph90uaTxarrz9S8xPktoQiZdz7LhPBoHWmENp9IvGIJ09HCbdM9iVHZwWmmJF/ylnIAS/sR9SzVzxtFuSCiBplpHMdu3XK5tFFp4NxtafrjZhJIkP7VxhFyTq65nxRsNm5pFmJow9odgvyIiFvg7NTqWSNRSdiHUYMyzliV6Ms+ijDAHFWIhghq4OEpEZY0oD94h7vMOR1G0qrIjIMUsVgY0PshzTVLVJrwLW24qI85Y/xHv2q4hmnlL7KyPZYVj2c6RzJP0JRSpSrTwRpjdbND3x/E5JrHu34wKbXRVKOuHoe00oFzE6PWZKxyXJeL1zWtoJXH2HORiTWHe62gRXecNIcM++p7G5uWUlrkm8EXv+bXyJNJmwbLuo/TjkXO2zGUDtJObxz+XGXMfJm/Lg2uN6u0FptxNaeM/s7+vl/l08fH7CfXWC6c0RDIKj7XCQK33cdGguf5eMdUfsYMYfW8J4s7aEfbzEqjzPxFKPl0l07PE2PiNozNqpF53JOKHhEhybnPYnqtCTaKGxcnaIl8WMvQ1U0Otoc3xtSTdcIFw6fpA5H3pql/IjU6NNybzmJMv5Qgdyz0Ec5UbLB0wq0TzWOlAObUqChnVGLHonNe/atBmsNskQBf4lRivQLC+fdECN2uBmuObdDNjWFs/Y51re33FQNHouEVjPllZhAoGMaItm2iZQeQXdDOyxYLAqykcbrfMiNZ3PcD2mwpr57wbLt/iR/PwsRSOICcb1HP+uhLRcsyiuUuYjQVPnGEIg2KVeHPk7NJ35S0SwH82RDXoXYhylBHFFLniEPLfKyx8nqiXevbGq1AWGxopAdOruUoJ0wmByzTXwWSkFdXBHHAvJYpxnb9D518MZ31GSLaHtFkcdUlsAXhcL0cUtWU2hcqqyWU8Z9k3R9z4u4QRreoYqv2LxfknyV0mzr7FotjHmdQb1k4UzJzRZJGVCtuiz0OjVxguj6nLqwdS6xyr9Z5QgXM1Ztm3TTpCFoNB2NBy/i/kShkWQ8aRbH4nOejSd8t5/RuatBQ+HSrjMNc+LCJlY3nL0aILYV5o8HLowpn2sdTt963PUKNumCzuE1Q5qUUoF/pZBIIq0P/4znZ0cs1QFiUuG0TO5bHmV6wFtuEMqAj8McPZDY12T238x5+v1n5IbGl4bKqK2w/yAh6Sa94zazRKX53ZplJyK6tjn+RwJNycFfNvH+39/wzx8PvKsOTNQp29+KmBchlawwqv0SP6yTynfYFawff0d4CJHMLp/XOrYwQZ7ZFGpO4BzTHg+xb/6fbH73K8b6D6y/6BAlYwJ5x11aoZcJZ2rOtmjg1CMEaUw89fDMNlZnz4fNX7JLMwbWKUa54aHpobtn7GdLjJqG+nfOsXffkJzW2N8LGMEvyA8Vi+aBWC+J1z5jP2HTNmkMTFLBoIqXeJMRemtFXByYOjXsRptw22P8vOBsKvDbqcXa3oMa4OYuhzjGTGsMcp9d4bDfZnzfSDhC4ehxjZFvqA4qT4MT1M0Co/mOjv6aw63I647OdSugX8VEdYNjAXx3zXItQneBWP+Z7xiUdY2LfM9uc0M//gJ15bFLYsKiRGkFGDWJPJCYepdofCTqWBhRQtML+Kxm9OYV5a4iyHcoxISvA3Q5xnic0jQv8Jp1Zp0m69lv+drz2AxSTj+syR2L3L6kXCSM6k2wHxAjGzWXeZblxM6SvXUK+w+sRx1+I8VM3kbUrRBto9GvFdxFGVVrQPjtnNN6xIYAze/yVvFxIhHTNiifHFr9jEMIorVnuBWYWEeI0p6NmaIePHK6eNoHJq5BswpppDuqIiMPmsRPj9iNFrYXEVof2cldjDlcxJcUYso+1llXGnsxRyw76IWHq97B3kQVxlzTRHs/53HcwIuaWM1b5tMAoX7MpfuWR84g3WHtfokYR6RewKS9p6me8lVLJfgx4UdRpaUpdFcb1t0Q95+kvP3xkUw+sFYusOcC7sSD5xHVpsauPEYufO6iKZ7bxP5SoVhuufUU3q0+8vHb/4Bp/IZsXKFZz/nN//CXxN6Mmb/n/xr/iHD7e3799b/N/Ytr1lELdSxyflNDfjnlw+OSmruF5IzGMEeev8ezbE6TB54cgco1adUr7pttWuuSdu6zelPQfl8D+VuURxv94oyyeCR5dLDNDt2hhrJdUXbOaBVvcZoTlO6IRr9g/aFie/wS6cZAHqfslg8cJIe/0zFZ7iuS1itW9W+RqohGdcH6Q0m3e87a87lQJPqtExbLH6meRAx7gRcdOOw1TiWHbaDwKZcYjZs4wxnyok+mLuiFEz5kQzqNHla9oC+F3FlfMgo/8RfTd9TPLD5EOomScPRK5QcpoxUvOZ0v+H1+gfPyQDlxeX6ogVFnUAS8/Sn+/htk/SdDiDMeoxKn1WRv7hk7R7jGH9nJDazqkUg5odnLmdwtyDsmLw7vCE0BVRjRE5cMqx3XJxZpcsSZPeUpusKOd4hNkXKp8VV3xUbrccqAyYsl2jOVM+slilRjJX9gnfkoUYtb6ZSRUqCOdPzBNaFtsF2CYFh0MHnQLY6VFpXh4EbfsMl1zgcF2YPLkWIR99o8b5v0f/fAXfsN6VHMKgnodiP24hFC4ZNeZ/yVo+B4U5JehhxLaL0IPbVZPRi05z2mZ4+kjYI37R7ZuzV+p83/h7k/i5lm29P8oF/MkREZOc+Z7zx88/72dPauc6pOTd3udpfbFINBvkIGZCNhhJC4wHCFhCxxwSBLSEggDLYE7gbaYLswdtd8qs68529+5yHnOTMiI2MOLs5p1Bh2t10lWed/kytWRsbKm9+jtVZEPA9bn2MjZFPKUs91GAc2xfGQYQkUJDwpg6wq1Go3vNtYKGsDZe5QLL/C9rZs4w/Q10O2oxiTJxjft3H8d4xGMsE2olw+YpZMOFdihHcLgluLdl5hOp6jamMEipRDi6gQ8/PBjFFXIJz3yUk5OpJGWFEZuHnKmQ739yK7zhk7e20WyxJpV6L34gV/v3+L+s2aS7PEUjFpzq6YnycIpzs8zf8lA3ZpKxUqlxH/7n2Du/wV5aRG98onUHTuigrGy5SOVCavhFxufUa+whOtRTXn0U9EIinHIt6w2bg05UdEiznT1hLFvWNZfoZ4cYySr6L7KqkxJci3yUQrMkmBReaKIjbWpkk55zKOTCaTmLA4QM7vIoYL8pMNlQDmmTLrxYrEUfDyNu1RlWLL59It897ugqkJT3sZ5kLCLGMj11tY9TbK/BvGQoOhBU0KJOWET75MWZoehcoeI3XLuJTnXs6h+RJxIhILFitdZHc+Z5VtUdnxGfVXVNSIbiZDzvN4P0npZiqMPmhg0EPZ7iEpLkHTRFqM0PxH38rfr8TGIGpKbkdh767AeC0xK30JaQ1t4jAVdaTMkjOlTNwc82xYJthY6FYBYpdrZ5+rh2VCxaejuEwyJWadd6wrWV5EAWkVJumEu/MBaeLiqRKeU2FZq7JybzHzIvpIY7lo0dmI5DcFDu8F1v0OuVHEU9NH86tk6yueC1nSTQ9ve4MW7aIM9lmc5/AllXl2jFC4p3I35yZTYH86QWiUkIsJ6VYjisesByG+6tAwYeVqZPwmgmCjhRkWkkRROiUoiwSTEMs0MTwBUdxSH5cxpiGX3+QZb8dcbZdkL7vM7CXmRKbq++jJitp2iXZ+jLyKySQ9TGGHiXSA7H/C3FAw3ApHiwLHOxUebWbkX8QcmiUeqAllfwi5OtebHq7wjp2HMUllwn6pyrthTJgtsUgTXpyrhOc2u47AbqlJfFBELofIdoIuvaGRjPmtwyFqqcYy6tKyJKRAZdvLo/YiwspTkh2X0BtxWXdI1TzZgcvPv3zB5Gd/gOr02XkccPprbS7ffMEf3m4ZmXnm6pJx6y2TtoRYVejZe5jZNk9WJtt6lfVmQqkfUdm2+FTWqSBjzWyEvILi3tNd7JNUNczHkNNfsbi+xJ1WaWYGJHlYju5p70csqznWrkrY28XarsjJKaJWpnY+xFgXEcc6PKyjdRy68TEDX6em6ATHAl9ZeRL7BvfKZ/6zNW+tAncHOabFBDXNEF64rG/28f9cYtTL8VkyoR+JzJ5A98BhI16gmh6LpMWDuyXF0gZVjCmvZmzrLd5EG2Z5gWksMPSP+Tw9IuPM8Q2Jr0sWmWmI8qJFcVjDnrlUYwHtoUzyUOStmftW/H4lZgJi7GMvZJaFO+z1Pm5LJs4J7F8fs9nMSaQs+aiModno7Uv8hUjppsOL6B3Zwyz2O51s0MA8iBAKMyqLDraQsooVxrVXlFdNDlYrtsUAzZAxZQW/9xLBf87o0sWQHUpFAX89JwmuSKUmD7G4ykfkLJ+9LPRFhWtjgTAzmRtzZtEM87DBe6sFy7hEsjlAeTvhXSFF2He5k2WUS5OpPUTNK2zGS3J6m3nZJ2da7MS3rCyJhZxloUQ8iCHJrWi3JJrrPLdClntxQFOocNr+mtsvGkQFhS4Gi/GXXK6hmhXRKksytWdEFzorK8HQI44tGXmdRyoOmOVLpLMcu6UIIzZYKFuG62vM6S7x7tfczD20WMbwFdTJmPetDMvmc6yqx46Q44vbDUKhhbZdE7g+a9smY2TRMhmq0QN0eU1iRPR2ajQmLkPdZj/QSWMJrAZ9XWCSvmUyCGh9CK/sHulaJ1cMkdQqaSnFcUOalQBTf8humkO7cvgb+wabx7/Gf/BHXU6KJugNrga3tK7GyLUKElMKiwRHmyEEC9aijvo0h3K+wRNrqIsxS7FLV0tpHB6hrQLi1YJVLua61eDEn+AZC7RlDtcsUtxRmI0citslYVBlkdtQqQn4WoAqNlilNfY9m26mgDHVaUUOueyMq8Ycs+rTW4qUlAytzA739ZBN9gqJMbLno1+mSDObeaFC2FpQWmiE5MkuL0m2BiulzIPSmJ7/CDkOaVbGv7CYm4noLZfVxQYvLGKc1nCzAh3PITAq6LUK8eUWXXHIbIr0jiQ63TUzCuykAc7SZK5syG3rSJnLb+XvV0IEJEkh158x3m3Q8CL0jY7tblnXXazFFkMKCDczrP4aTylSlueQvefjoc7SLOB4Nore49KGxnjKNOywbbWp1Qc4S42WumRUOaFRiZg5NoYvoNIhXg1wnxuYdoy3jRnlBB7uNBgMU1bpCxpmgfL1PYuWgjh4ghgssAwJcy3hVyqIXpab78wovEzwy2uWAzCaEmN7j0x2ixYNcBMf4d5EP6qwkmbEuSqafEaimSTbBC0n0xx6SPmYvCIR+2sEqwqShDA7plsYsshAyVqytSzWzoiOWWEeNcnFnyHN9kF4h1YxuVh22DvtsrrdoZbVuWCNFYKyTNiGI4JIIruWmT3fZ1OYENvPMffKRD+/wM1b5HZX1MQmn9hbpuc7vFRvkdI8YRjSCES6oyucUonv3ee4KxfYP4Ed44SlG3OorDj3da7/fEaUwlFDRC/s8af3A5YXNrPOAY8cFWW4oh0Pif0PCP1ztJaIeedRD3eoCBbRaYFGNcfmfE1y/yWPvSZP3hO5XTukr3PEez5xEBBnQjbaOyaiRvQ6h3VYYesNcMwYpSODFbAVEwJdoT7ZZ5kuEdZXbOIGVjOB+wKbmoifjIn1LN3XU+Sgwe6eSzI/ZTfZguqxiDX8xQz9gyUvtiIlYZeFtSbbt5HZp53KxIKKkZhgp4yCOywpy2oZcWCvWIQuuWKbr4+yNK9qqE2R5jJm1HbITttMJlMU7Yi13+axbHNdtFjaa4Rym6sfXxAGGZq0kOYRqSdSEm3OtRz54A2PpjrXe1XKgYw9+SGCfEDX2JAsNrjZJsvOjIObGqtMl91em+tv4e9XQgSiGKoGXFqfU1r9NtPuGK+kMBJVamgoasJkrLCN9pCEn5CbVIk6DeRWQGc6Inl/l2ShkRktUHYqBLKNGgxR8wLauMnw3mdd8mg4CqqdR2iKLAs2YqSxG3gUdJtJrLJ2u7xbFKiLNaJqDs2R2Bx/xOTWQd0VELYyRmOM3i/SLxWgb+Jc6mTqNvO3EdmORGEW8cy02C/XESpXfLPcpV+5Qvf3qDs1+skKxdRZZyz2JyuE1MFwH/GmdMV6VkMobtEuVQrlgNARyWklfOrkNl0uPIX9xYKFHSAcCeQWD9jqZe63Cfr0Du2yx+3AJSu9I8lItA/28bw+69Mt0nWAVgtImie0IpnVNia9nZAzUmK7gnO4ZiuMifs691mFQiWHkb/kTdzAiiWu9YDxBkphFulxiEWeScFnPO8SCAnaV00i9RVC5hPSisRNo8T1u9dsN0Ns2aVUuiErZalFJ1QLPnbD5uXyAfVBiPa+ju48Rm3GFFrfIA6/w1IQ+W7tQ37zqYZkifw/38osP8qiTAYMzwR2KxsyNYdH1kPiS4cXizV1xSNbbSL05tiRQ5q0aKoKa+kNhYzBek/Hu9I5sDxeSgm75y53zRIqW3YaKpnqAKoNtL0rzqYSsZCiBhnchoty1kau+qT5OSV1l5uSR2UREKYOo9UB7foUZWERHEYI/RzF3TyzXp9FucW+LVEhIFu5YyZWuDsaEyoQvFwhPFU5zbnc9kIGsUqNr3H7DxhpDk8+2ed1JUW71qlmR4w0yKTghRqx0SCarMgVVihmhmW8hzKFHXnIfUXDVdukyzma5yClTWxx/K38/afxGPw3gb8LjNM0ffrLvv8J8C/D/8fH+H+cpul/+Mvv/kfAfwuIgf9emqb/8T9tDFHUeG1NYJ3lYndFS68xW61R/DGrekgzKbMvesxqU3KTAu4jGakI3jjkbpNSmvbIeCoUKjitMuuJi543mb6xyJeXYI8x9DHLnR2qqs3CXVKZKWixSjdYkR0K4G2xOipG9Y75UCLnZ9CSFVe9Akeaw0J4QRqmzN6dMPAL1LZ9itIelTuRXeWIrerhGDOsw8e8G47wBgviept5ZknV1DAXdyxGe+yWB2zCPQJjxXxPxRQ6RMKcVMxSykYYozI4Gy6LTYz6FtGQyTsyTn0XqRDghB/gvrhnmmzJp9AJazg393xeUXlYuIN1mz8y++xSorO4orotYEoTHPcTEmmBaQk4iy56ISH9OGS5WvFyN+RJ1GBslDDKMlrGYF4MMe73+Ki8xglEbqQimY8/QLZHnMkaZtwlF1RRvtpwk1wga1vSeZ4wmPDup13svTyL6IqHGYmH+3kmwTGq22envWJbqlIPbDYLAT2bp6PnedjMUn0+RAyfY7cVnPsZjbSEUTvks/E/xAkDKqMdpmnIk4qCa/mcfPJ7fFoo8mbWZzZ6RfW6ht+Y0s1o1NwjYuEKX95Fylape2Me3G9wOhEbP+Vp5gCpbWOWM5wZIm/FJfXEQPsyRjwtYyojhLDFcp1i2S7lRwt0OUs5E5FXzqg1a1yczQi7bQrViDtDo2JuaftZbtwEI1Qhq2KoCu8EEW8Z4No5jO2GSNoQPCphNRSktcU75Q2FjUbeDghXO6C5FKWIdWOXJ4sZ+dqIV5MCbjmHuFxSDm5JljnY3aO96hPeqex9KDETFBzbp2TrpE9ukIw6d/0Rm7xLkvvr3SL8PwL/a+Df/k/0/6/SNP2f/+MdgiA8Bv5F4AnQAv5IEITTNE3jf9IAgRJxlM+wyjTYBhqGLXBsOXS+3GPQdNhqKopbpL/YoORm+EsByfEpzzVGJxHV9fuM82usio3tXpPRl3TEMnHtmstMyMGjBqIjsI3WLLZNMoLBptEjFfoodpvUKFAuSuT8Ad4wTy7YY4HH55klrcGIRRQQxQ9ZZ/NwOiTfm9GQG0huSPe0Tm74juWhyXOKmGqWbeDilWJOQhCTOWVZADtlZV6Ql4pI0Rn2eYvktECiCdxqW2qhSLQNUSKN7S6IxogKKisxwJcs0ucyj6Ic4psbLhv7EMDLpUsgzAjDLpm1ystJBVU7o+2J3DgqZ12ND35jwJEM06vPyQ8aGOtrlmadYk8lLD9AVqd8WAnZjKrkpyod0ePGV2kUZcb7Eoq/z0K/otFzsYpFArlPupCo7OYIopS4vWL1A4Ht6JZRQWRPfkGqnbLcueVw7VPSTKLyHuUoRJIcJpMh3fQR+9MNan5KsH1EZjOlU9DIqWXuew6C4dHPjLkfTtD/nRk/2ViEgUJBlXjQ+ISX4tcoA527txdEZp2f6yHaQqIX+WQWMgUjYtPJUfRLFGZjzuUHeGWP9+QOSy0iIwjEwphhRkOddNErEdZ1HjGXRc1L5McLUkHGl26pmymmdsC7zZiNsMRWI3biMr3rEYHURnq2oDHPM74sICUO/mZKo7Ll3c0O5rHBR4tzBvkMqeozL5bIlhdsb8oES4e6kbJeimySMsN9iY+8mO16n72bBeuHd2wmb/ESidwqJdoJKY5DFKGEp93hCDrNzRpXP2CbOAgXDl3N5dGeTP+dRumlRrnRw18ndPJzFDvPq7+qCKRp+gNBEPb/aef9sn4f+HtpmvrAtSAIF8AnwI//ST/SYtCTBnFYIX15zfyBgZGY3O528Z0TQqvKtnFHLlPEGydUJdgsZJJEZIRHrr7i4dczllHCblhj81jB709w3Rw7dpbZOKKprkgab0nHJTThMenVEL8IUnWDulch7U0QBZ1hAYLrlKwz4NdzKv3dLYmdJ4pVhJWClugsAwsp06XWKvDoJsPkpEnc9fmqLHLwwqVnr3iUNbnUY/L1K+ZCBWd/j3RmsLhKuKgWOA58XGVO6AtkQpGlkGe+ukRLCzwuxBxuJaZdjbi1S6EwIvNWw5Jn/Ew9Rqh+jtKyMVWT+a3MMp+nP6lSMu+w7RqFVQFbv6Q0TQnun5N0UhR/yv5hjr7ymGS2RskbeFZM8aJFIEwodGxcrU0U3JOJI8J3GbQDj95wSPtxDX2oYgQCPxfL1Bs6DT3B7RZ4eXvL+faSq/lnPKuf4jzQOFhJ7Mkd2moFWS3i52MKV3X+5J3Im+gd1esBs3VMUbb48OOU4+Yx62wZyZFYH8wwV1B+8hv8vTd/jt5ZcBcUMRc+q8wVv2XEHFeL/GUv5G4acjd+iecW8R/tElzOyG4F7KJCPnWo9ANet2X8bYjg1Nk6NuGOQ/ZdgZnso65lCgUfPWNTbxmMbutsHm1Qz0Xsw1PEd12igsc0e0FUrhIlBtnzFbfZIrF/SyEyiRSHQXOBsjaYyxWspUMkV0B9RxC2+eGqjCA4NMyEnOEzittkNQEhlbk3GuiSjRWoPLBNVnMVrXrJZ/kckm7xoeohD7N06WPaVXaMt7xbH3K6bWKMVgyrkMwrsAuW2+A9JyIZvSI1PcR0yXIKq1LMRu7Qbn57PtBf5xbhf/eXycP/5j9KJeavGEPmbaeMrAmKeUut4dPYbggu9onjx4yzFYzCjOaNzjpekigC5U3KUXzHzkmffcnHn8zpH9e5q2Tx1jH+Io+fHrLjpwjFAdq+wzwbEd8+RoyLmIUt2+MSoRQgZCXG23umsotakjEnIr6QxQ5klgI09RyWZaNbCkZ2gaZrGDWJJJ6y3LgM+mNCW0QvWSg9jfXqnODgjsHjAFmboA+O0M9cFr0JGSvCz9ksNhab3VtyQYmoK7MOFqyG1xTyIoWNQjeq4hUjop0sQycgBmxrjptxOdSnaEpANFA5MA/xlB6mp6D5OYJJhdS1aGYDWpGOVmvysLkmV86S34kYXG4pdyvEW40/3nRZud/w+qrHf/Tqij/w5jjilCANaZYU5EciQtQmmyTkrqq8Wdpswy+pqz67NxKyWODGEVlMJPJzmacHn7LvH3Ea/A7Ge0U6mxpK3EIX6nRkCdfdsms77Df22fUDnnxY4oPfOaB1IrB+BO+iOy7e9lm/qHP59orSj15SU3cRr0PqwRpp7aKpJS48A7NicmtOIWuQXT9gkVNpDOYEuS1yQaXat5HGMlE2wpTqSNsBR02PXsFl9sMtc3FMWImg7LNZ1Ng4H7G+smntb6gut+RTk8S8J87cITSyJJMqxtcye1/bBIlGQX2DbJ0yb26ZRQ/Rb0xq3SpNY8jbRp5gm6OwY5JbrBHKAtHqCdPBPjfLQ1JJRZBzKP0V1bWFNl+T79us6TE7ShkGLqWaxpFUIl6VuD9q45TeAz9Hz6hToU5Xsnm1K5IXGgytEeOZy0hYMpeuaPglLPUQLX8AYoacYSEPEoLlt0eT/1U3Bv83wP8USH/5+b8A/pv/WS7wj8eQ5XcepLWcRO6LLIu6SrxoIVa65DIpuqMznVocqEt27DH6JsdkZoLxjFW0JR9OyUoSJdfGtmPyOZlwrFKQLzlrNsmNZ4SPihiGT+UzgTA1sCORjStTcKqcXhpcWmvE/RJnF7cc19fcNdZ43xRY+DLRXR9kFU+fUyLHeNXHViTqYhF3ukV9aGA7VwiTIgECsWVQf3dAeVMh+4HK+lOo9J/TfjkmnSjclx2y6gZ3HfJgYiNWBbbbAkfyjImTJVanzF+5lD4pc5fI5Foeoxcx72kB55ktM0WGnsM6rtMtviG5C2hpEok05VbvUfbLzNIxIyNHOZJY9VJMt0KQXxOudL7oXxLJQ0YbCfUsz0Vvg2a4lD7rcvdgRuf0EOdOheoSKVXIFQ2MBJ6nVYJinvK4ykC9YryK+LzmcpWuSapF9koWDxsfIjZj9rQt64cd2vENxtd3dHsagnjG3lOVVqyQ/f1nxDmfml+Aco9/cP45ulIk9/i7qNo5f/ZnPrJwi1uLsaY1bgeXHDz5PtpwiK3aeLUWv/tUwrkL+Exbc7ixiZrQXlhsFY1sOiCWQ0ZiicS8IJdR2XEtZiUd7aBA0s1Qw0e+gNmpz4OLCbdV+IoNjcSnHOtUv9rS7WiIVzrKYUQ46uMUVVQnYJNELMpZrIXEvqWxvE+QqyMysy3yZo1mpSgDH3NrYrkaC/ucMN9hvX5LyTbprto8MgtMizcc3NYZ7b7Dlpuk9Gm1c/hX9/TGGoXMBnvuYd7vUcp5yOsKUnmIYxyg3IF3r9PMrhlrOo+WV/Qf1/nMHXIkRzjzDOv2LvVFn62gUEj+GuEj3wLw6B+1BUH43wF/8MvDv1IMmZDEBC92GZgBiW5gZBO2RyHWaxnduKBVkGlLAdVclms1R2Q0SedjngxjYklipi653vVZO202mxCzmpKMW0zmG/JmitSX2SYq5+aQ0s4eepRHd86JVYsbA1CXVEZrzM0+vaGMU1yi7G6wFu+xaA0Rh1sCMUu4yLI9NzE+jJDiDKp0Ruh1kI0GgmojxAGPEwgOBwRDHX+hUosNxDjm5LcbTO9m3IsC6tsNaHVm1oiXKxNTgLC1w3Z5zXYdoxg2oyuFbHfK+lMVxdc503Ng7mG+7nFR0bnbrCjGZbynXzAZN5iPHdxSygzYuZEpN1fIvspnqwy/ptikM9goP2E81Em6KWujxBd6Hk1YsPVqxKpGOQnwBA251uXsqxq/VtPgmUN3JjG+Auf1D5lnq7iZL3nS2+f3NJG/v92wFGyMTZmHhxbiQ5/MSoJowrvLzylUD6nla2SeaIy/GpLR29Q/UjC/Ehg+yrC40tCv7vi1kxNycZb1soLQc9HKOk1PRwhttOwhcjRAam8Y3Q748//XBn2yRyZbR9/YGNuAoJLDSBwGxSW2b6JHM5brKlL2gEiAJFyQz+Son4/Qd3XO3srkMzrlrcGdV8TZh9p9naPWjEtJYasZWIZH1FpS6MpsdiuI71x8Lc9ac9FfRDwsL7ltZ4hTiV21wtTzaMcxmZzNSpToJwPSZQU5K6Msexw1pgRykWc7a0q+y3IkMTlJELQPaZ69YHUE8WYfa2DS2EZsOlv2TZ+zhyrRwCYOVExBIF47rIWY0H9LhMyBUeEuV6eQyuRCAz+7JAldSp/lSAsBTknktnn3rfz9lUTgH+UQ/vLwvwS8/GX73wf+z4Ig/C/5xcbgCfCzf+oFExk3K1MrdDHFFmolQPAsVo6AJdxTWh0xKizIWidk8ja9e5lVM2CZQOzWOC1pVNdnFLwQVRUYv+2ytctUT0vEooYR7+KP39EXMkiqS95MORpWmKshqXRNzldZjFSSRkrshWS9BFctkuSvqfXz9EWRolwlEhaoHx5itS7gRiQrfIKW25Adrbkyehxk3uNV5o7gXYfW7oCsssdSybG38Jnfj7m6zaA/nxJ06kiTMbeSQy3cY52R+Wa0YLnW8cQYU1U4kVVcf0RlUqDvDOkaJtXePUGc8MWZzO7DfWZn1yj5Pfpzk4r6DdvXB+Szc8yGw232IeruT4jGZTxHodQt4H8vJL+tYEtzfu1E4yeXnxPJFkJewDQXnGh/A1vZkr2ssVcwuN/JcbAIuO3+xxgZD+c8xaq+JLJ/h3JbZ72/4OhY5ofjLUY+x6TuwyClEwhMdYWZukfghuQjCfk+5KHQ4E6PkSmQUTZwd01Je8jvnnyEa9hs3BHJ3OS/+jsfMRZsRjf73O7/kLJfxexnsa7G9DtdlKmPG8WY9Sua1T6oItd3x+RaOo3eDUGuSs2SEfR7EqmI4FSItpApRCRClbOrHHoFCssaV8oNfqmLGug8+2TN2a1A7miBJdi48w3WNgvxW5zbDlIWElPjSa2Dn4SQs/HfKug5CWsY4OQCloU6eVunvhS5UBUmJXi8ULhtu1SVHbLrHUZxl2groe2Deb1iHBcZlg558CbgWl9hHKeIoYXg1oiWDro4Zmp5yKUci/6cUdilWjbZIFE2IsLiiultm3XQw55mqA6rOOWA6l6fntAlNfYY+dZfXQS+JYbstwVBeJ9fLAdugP82QJqmrwRB+L8Ar4EI+Ff/aXcGfvEvYtp+zHx6SN6W2exDNVsl/o058ahIV7DoTPJI0ZjNnYQhjziwPVzfYjtfIZt32PouXqmLFTXxZ3WkfEDLmHM79lD1kJw/odPKMyknCHOBZZhiZTOs13sMTI3c8RJp4FHLKOSHJdLjLfdrkcFcRGi3GZWmVDyfKD5j1p+iCMfI6jvOB1BqVKmWUnpD0DbvUdx06U0TGpdd5Fjly8IcW7dxdIHpVzp7S5PV0QFbeUNL1+jhM5y/JVdscbRtMj3L8Ma8oBd6tF4KPCrmmU7PGfm7DMIrFMfCuljQLwXEmw5KsmK7OUSmT5z32LhzzLmBNUjpjwMGp0P0zBs2FxJ2Ycs27pCuZhjuQ4bOglatSSSMSBomxizFdQI6T69BFJjeiojtPeajJbqhsdtoYT2IyDYipmcpRifiu+pTvGKD4XbGTnWf+eKWJDjBWl3i2R2s0wxxvkQg5jnWHNI/HvJ50WehO1SGAtbzDqp3iXiVw5m84YF2RCff4Or0msF8QPOmy7tVHaEcE8kVtLKK7sDiNiRtgLvooEo9om0Ps/A+3XKI7AxZLUS0XB4ja/PFjou1UHGepERnY9zUID6d81A4oL/6Ib9de4wxntFuH/F2fodcbpBsU/T6PW5yQE6dcLswya1inEEBjC6KZlE98BnPt/y8aqCOA0pmwF2lgC9fE811nmUn9HwDc7uHnlmRK38OsklEh8HsLbm0hi5f0czDTa7E0yWsNzJ60cGVVnwhPqJwZbKqOtR+GjGsbKnWQa6KKG92mB4suO+LWE7CkVhiWipgWjKTxVfM4yqV9IhoZbD0/hqvEn9LDNn//p9w/r8O/Ov/VPD/sQpSifnpPXFaIvYnlPMVfrxsEaUBv31ocT2awz647j015ZhlLiEMJGZWCXFdYhPPKJSqxE6Gy0XKruph6CrWQmOvoZBJzsCtI5R11MKKyNfZtAVCRyY/nbPsh5hPFszbNYyLa+7UNvtLk5LgsqkNKVWmjN+W2DoqnfaMrm8S02dtiOx7IdGiR7TdwwxrmPUl0kimZsDPBxpF74xMPyEozWkq+0hRiFa+IdyasJS4KfisrAS9KvNkOMOVTfxkQn6ypKqGTL17/rAHT1pbLHnO0H9Oc3dCVz5nMRcoLd6RyEsyZY3A1Cn7LQbTFDVTwiq3CNkShFtGocouPl9cVTE6N3S7Kx5kMwR2yiMrg+bVyAc/oni7y0tpzCwLqa3QFmVioYYrC3QrAkN7gLgJONtGTGKZXPmU9q6AI6XIJZWnLyPO9pu0X13w7800/vnvWfTlKfaNwMlxiuJ7ZHbuaZ1blEclNu930ftZeoUEf7WhkT/hrpphl28IXI9PhCeYHzkYXxfpXw5IlyZjdcGj4xhhXEJ0EsajGYKu4lUrrOyQ06TOqr3meWGHcZxjvdmQvfhzTPGAcsFG1BV8aUkpzCPa9/x69RH7OyJxucL05RgpnDEclTiwHJbTI9Y3a8anTYqmz04qcT7p0twUcR7HOEuV47cK3vcDZAky919yXzvAKyu0UcjMG6TzLUZzQDzUeLcbULgpoLY1Cssy1d0xo7McQTVLxV5gH+rUZwLb1GJjDXkovcLbD9FzJ8RCRCN3xEjPsHNzj9Wu4l04FE9XLLWIjeYhF1xWtEkKLfqrh7T1z7FSj1J6+q38/Uo8MajIKWV3j2yyQbIPENM1e8EbZn7IquhRePcI6YGH7apY0gRuRWTNxip9Tf19lcA5wLnP4CTn1PqHzK0R96FIuW6R3+RxZ5ewZ2BGt0RvDpDaHjs3Lt3SDKcZUZBDAjTCXoZ3+g71TsR9EpAubqh2NNS5iuR7xJWURfmQYHpDxc9Qsj3ixKFc1+ixR2ElcbWOyZcjBn6Ndi5Ed3eJVhI1KwB/xTqQGBU3tGkyMsZ0nBaFRY+N0uIqm5Buh2gFmfXCwKPAtnxPZaCxocgbVcOPXtJKHRY3EQ/dJjYGetzlTs+jmR0COyBLjrBu4K9XPPqtJrpzhjNO+QIdpdpnclPgWeGOLDbGXgYjvaFRy/PNdMQDqcB+QSRYBcRWi6hwgXodUm/raLLLGpHTTI2zKORhsmHphbzuuoiFKbmrlJ8/K3L/VYGTQ49m5YjoJKW1ynMfhRi9MWcPHuMiIQsltsI1+8KaRLCYztvcfvVjZh88p6Lsc99XuOCcR1LAB9kMD369zL93cM/4Z2NylshyojCU5nC7Qd7zCe+r6EGL4d6PiOJPya5X2AUF+forGkKDxs4nRNMxUV7lUWafVaRw1rvl8U6OvU9FZl95dOQCLVPjrS2SS8aclVZ8cnDK09TnqmnTzjdZ//TnmPVd5pM7tl7Ag1oHvxTTvXcpGil96T2KARS/OSORde4zR8iNBEV/RL/TZ9/PcCNl2VkViDUNN5Bpl+a8cVs4cwfVCXi3TiBtYZYPWDpdhkenVGUQPAWzEKHI0CxlmPo9gsqHbMbnBPMGdmNL5nKDahUoihJ68Ro1CZjf1Sj/dZYD/3mUGkNBgc3QoFGRWUcFNmbEThQQdBXUxi2rcEOnVkRZz6md5Emyh2iXY7ysipx4xE8niOOQ2WLIXlgh3DO4USOqn3ssi3kyXp/1lcJBJeVm/Q6qD9kLRMLeCC+XI01MWvGApO7jovLgTmBTEgjHa+J5Hqv2kOzmJ6yXE/RdGI81alONQlbgZ9sOD8OAxO2zn9iESQlPuyV0ivjMifUin9s16gr4wWtmd0Xyu5cU81lW2x6MA84Ni73Xl/imSXzS5Pl8Q2wqzPMmaS5FSLdkr0UcPyWTSiiDFhWjhXd0xSp9gDkbk/HfYG6fEDw6RgtmTKIKxY3P+1qdXmVB8KVM2luzshJuljkyhQL2R+BurxnEOgVhlzephHjvsz8MaHauGCoCcltACjUq2hIl84gNAd2xTSin+HUH5Z3F3P4pk0yD9z4P0PsB91aeJ/VdVpd3PChIRKHKsH6LshnRzvbpPsoTxCWuIh83U+THf/CGZW9LsDcjcG+5oI+06PGXe3niP1kyzd9DWEDZrxOoDlevC1g75+iyQOCbLPMK6BMKdyaF9lcYgcxskqPoVIjKN3z/KM8i3aV8bHA4TblMXMpmmceVHN6XEfbmG971S1QzZUrHfeJhh9/PaXQ6Begc8V+pJ2walyTZj7h8s+TVYZ6byZZtzqWfLaKzw87GxXiyIo5SElTMOCI4HqCc71NJLlkrKlse8yC/5lK4J695rGOH5MAg6QvIShElfUdht806veQy1MjuneJIt+y91ckKC9Iv3yOoiGQKIadkuSm8ZZZmCMsuO4rAq6OY6nhGLApIyQ1epCJnRoxrv+LOQpGQcDnOki5Fwv0Fy8GarKiy7AoYksh+aYIb+vTCEqVBnietHTp7Bp95Ed2Mx2ZW4nCWcivXyR/1KPc2LKYBn+6UWTw5I+ipJJ/l+e5TgfqzlL95+120qs+dpSL9Vp0/u7UprK7xz2qczKF4GpKzWty+fUdo5/GGc5a5S4pBhV1xjLu2GJd9LtOEilhkb1XGSX/ATvw+ix2RvBAx/arG02zEtVoms50RHiuU70MCs0aluIsSijirbzBFsMtZTs8czPIDVuFrpOu/xB69R/vjOfOVjVPNkVsGGPU7/u7pKRvRprZTIj0qsrmp0IwfslK/ItVcFqMrtOEuttxiso3Zidb0TZnZXZuDI5Xh4hUNRcDZm+Hk3pB9kUeoVsgeP2ckX2EECzZBAyEv8Sf9BavFgKePamTmAvOMgjdbs9QXLJxzbuInNMcW1smU+1GNUuRzZxe5YYvwzR2V53VyxZiNIFDaj9mcPWCZVZjP83RO+nzuhPz5z4ZU50MEsUnaPoCwz8+6IUGYI1fT0F5ZvGysyb3ziLYrbi2PJB1RLLcJ3ByRUUHWIwrlMzJnLYxsC1l3ENa7/OaRwKod0ezXefpsD6e0JN9YUx+kSHUVpSCSWa/4ouhwp53we0GX7ZcT6nKF9/+FDjuOzYHsMO96GJkBb8YRJ8WnfPAgR7Md8u/8Ycj5dILlhqBPucl3SQcyC02kVX9MT+ixa4fI1SkF55ZcaBFFKiNP5L2HEe7LJbeWhmQrfOzcE1llercdSkkRvXRJXm4QbxfsKlumkoGzaWAdu2zDFLH0AXZ3jSTMEIoByaTGKAoQ4gLI9wRRkdqywMq2SHIlpIL9rfz9SoiAKKZIxmuS/RaLV2OK7Sy5hslsLWHEMuv9EzI5F/38BaujBt9/lrJQy6hdnzIiknuOrzm0rRN0ycVeg9DxkF5OOHiu8+sHZQKlzGE1R1hzyO/o5EQHoddA2MB/p1iCvTpfZHSO60NSvUTN0ngvY/BnqxHrPZnC3oDv5w9ZOvukQYzsfM4LtwluzDC9oH5aIRfdMvI6BN0Nj98vsbMn4b4uECVL3PMib6N7GgsR83jAerWlvm7B900KrxcE7+VZdmEvF+HqNQSrRpT0eXygMnJylA6hFZqI2yKBlSH3TMKbTck60Eo9hm7AJNPBMC/QxAnbocRuNkWd3OD5bXbVMsNlG+3QIrtU2eiH7NxPCdWAt1+t+W5+iRlMWYQK0WzE8JXEq70J2kpl8SKhOzin67qsH0NlmjC4inm7mfA79TlDU2dYKVKJOkzyS5KDLJVBlu5ygKXusg271C5TGrsC7iTmL+77uNohn60irh2PyYXPTmWfSnJLf7LPqCyxM1CxxyqOFZG+fIC/2OK+9xUCTfTFIY7fYBwv0X2ZwkglvG6RfdrEVq4xhJS/9R0VqV3msLhidyMSbV02YYprTzgvVsnc5Xh8oPMXZ68I5ZTjI4HH1WdkH2T5rhASyRE9N+WHosCxpZCEVT41NhjukHdqBRZrvneskX2TJaOLyPIOxn7A4oXLbANe5Y5VUuZqFvK48JpuZo9M2ULSNqjTAGeyIspU+MhaYm8ljNIe7+5nOAdlonSMLD5Enb2ksnPKZFmhcBgxGhsUSgMexxrZTcLSKLHavkadWwSbmLxpE1+pJC2DorBGzFepymOcasxBXOSH38Lfr4QIhHHI/rrMpBKjSjreWkNs9smUferDDwnfLnl54JPMD/ln9BjSIhf9S/zCHbN5mePcI/TCjKG2ZFfbQ/m9DJ3TGcI0h2xHlCpFZlsNX3pLpw/jSGXrtZFliXV5RWOkscLi6cciFalAFOqEDGmpxxzKEvqjJeb9CfvGHkklZLgdcfWHLdqdLL9WXGJPTknyMeVmxI58QD43IdIijF6dB40e30w9ivIWMzPGDwwqhzs8Hx9hPa+BYnP7cZXNuwFp+5hyxkcyBYx6SiOscK+Ued9XWTsN9NYGTTMJenXMzZB2XKX90YT+rcSjznuURBvr6Xcg7pEGRYju2Zq/yQeyxyu9iPvFPZmJyZtmhvRmgayXeRfneF6f8Na/426hg7GgJWT5IhnQnOzQ2xvyg3BJfdHkw8cCguTyMlQwPq5TWN2SKEWq8wJqU0d457Cnuky0HDfrJa2MgRxdcz+vU1Ik7oMtN1cig36KM/wZq8wjsvcixU4FWxtTEUTC8yWBbNLbmWGrV3hpBTeIkHsO5e4BatNkrVtkWKKGLoo0gnwB9QMTXVnyvY8eIyoW4T3sLhzqRwELbcTNFfirBoV5Qprd4pbfkss02ORMTN3mv9DJUXQm2I0sgr/FG0U4gUiavuGWJsXiAc2Rz0AKWMW3JGaN/b0yDzpLtCRBNgPMeI/lE5Wf/9lrXnVnVFYbPng/w3VwiBsXcQKHPbmC1V0QNrrMtxmaz4+ZjwbEd3cct465m/kY2ybmKaz1EuOBTqrH+GJCY3dNIp/xYvodpNCh88BHWhosXYPvqhmuzZBNI09u+4Y71cRab+moNXLZLZtN8Vv5+5UQAVmKWUox4jzCzS25TptsNin6PMYraBw5Z3xPzHN8fMCzHZeRU+Vov8/NbZ7swwV5s02tVmQ/eo+TzDVaaBJvUm41kdJMI3MvkkrQyYBTyxB2d7monrM/chl6Jlq6w2HDYRmIXK9FGpN7lsUM82VIMRFQvvDASlgt+szHI3o1ld/+Z2SCjUWluEfYjukWRZ5vRYargDSr4zduqSx2qRQb9LwI6W5Fp7WP8p06kpwwWxbJVdZIsYh5F6H7ZWLlknK+TW+TZ2d9y1jNEAUpk2BDrvCOSbfCdZBSFOZElSy2OEJ+dUPVmvPannG3jEk+PyTSQpTCTwjdDrtalsFui6Z6S/p0Rbyu82hwSWmq0M0rfMfzyDo1rkd95KzHNHmGXhJ4bgq8WkrIYUCmf0UsN8gVy4iHbX5tLDFpuJz8NGU48ri1tuS2GbaNDbuLJUcnOSYVFUX2SQY6ivpDrqOnfHk2ZSmnpKUtbvKI4+ycq4ZGY35HsHpMxhcYZreMZItaOKeg1LBvdQgrJJ/cIuvPyQQ+oTylaDrIbhHxto1lBeROCxS8OepyiZ7L0n13zqJp8FG+Qj//Ps7gJZn+hFd6xLgc8UhTEJMVf/uhzDorYyxljEKLdNvjRi6wb6V4kslsvEs2UyMrb8gVY1qFKttrjXBnivxiil1os/UzPFxvGRZlKpkBnz6SMXefkP3ZJR8ah8wOHa7+dM0HmQXvtIhGp0hJfsD7uzq/v5dS1o/4+e033IRLtmqMWoal7rCOKrSq59xbAvqNSVw38TYGzW1KIHi4A5n8pom+KDMrDSlv95B2brhRLYrKGNIIt9ahLA6Zf/kr7iwUeyab4BnR8jUFscMhItWlAl4GvbrgafX3yH/k0hKziKMJYnZJLXfAv/B3HP7gzZCmkMGLVPLXc776fkpuJvN0YnCkJsR7PQL7lGh8g5FtMmZC1Ux5Nu0wLdg0Yolx7Y4Lu8Fq7tAWauiSDxmNwFwj+jqxWkfb9pjORjhehV35GP1piDuVGbu3bMUS0mbNcGuwVTNElk1hcsJNZ86Ba1MORFptg0VZItlO8NcfI7TmvPYFNE/Al/OUTY+WMGIUpmwyJpQl5I1Pqd+mqC25Tx/hbfrI4ynzxwbyYAn3Y4qFE5zxiPurhO7CY7FzjZvOePTvb5geeKiVr7j4CXz63EP52x8QJSEl7YBiOU/NBPFZyvLNDc5BygO1yWKVo7hc4ZgJH4grzmyXVUbl/WaBhlalG3TJRSmbe43d3SO2xOiLEUY+S7S08T7+HcRwyF5hzvQmyyTtk1k28blGLzXAXuHwhKhvc19rE4gT2GbZC4pMnS1H9V26F32SBw3ERcQyaKFZfZ4mj/hLSWY/9BAmAvupySbRWb+noA73UPUrnH6ZL7fvyKw9LiyJbLJiNZL5yOnirCMuBYWKppKfblkWTA4LbdRql7pvUJIDzqw9xt05Sbyl0i7inAW0kXFrKwKxyR0m8pXHaHnP4iuX/DZld7TDWe4GJ+9jyS2i8RQj9vhe+ZQH+1P+D3dXLK8C/u7Hu/z59Q1ZIUDfzvjw+79GZhTyD89vWc8EhFyexnzM+aZDQcqjFt/AwS25F1mM7ZyFp1IQHIrZJlJwg9/epbqIUMyYabTmtVSjVr5hp+eg5TYcz8pMDn3SqyKzzBqn9ivuLJQIIom2RNJyWOYlmQA8eYXaKrO3K1HTTeTbMfcPz0iRSfwms8kUVXQRtID7N3coezaBmdL9aUKratI3xiTWAW03BX9M5aBEFDdxZI9SKBJKEZm5DHtZhEgFP6YwvuHWPif8qEQSGLiHBdIhlBApNCssgiqKZ7NV5/RdB/E+Qmo4RGkVfRlzIc8o9AO8ozJqYUwzsBgPU/K5HFh5Ukeiocf01Tk5X8d0AyRlzlRyUU5UFPHXqa4FsvIlr5cp2lKjk/HYXvj41RVCHCNKMswDDCsgfVrgfD3Eu5W4Lw/Q7taYZ4e0lAk3B/togkDf/Zplbg/fFnn/zYbjR0W0aUTR9MnX1yzKGY4+6fAo36Bw9lOWGQW9WOa667MgoaH7BO92uS0P6RRBdHUEJ0BaNJAOVI5VhWnnHmU7Rf/0AzbhhPCuRqbbx5GH9COfwlrlUgup/WhBfFInKt9jBGVm0YTdmYgwkjmXblCaHnJO4GhXYLzZ4jcfcjwYMpB9Bo7NrrrCiwL26mCoOl4ssSeuSYsJF0GV3FpiLeoc9y84/bRG9+sOov6KNwWdQVLBaJa59wZYwQnlrY9suwy/fEz75IxlTmOzvke5rnG2b1NY/4RU+i2+0dZs7pesRze0fIWt6/Jyvab9Bdzoj1noY+ofqfiGjKWlRLMc0baF05Ex8jrJICArj3hS3cP+2Uf0whHjjIqXucZYVxmYIhO3h5fTWSuPyWVcCnKP0rmGX/ZYV/IspjJJccthaoA/oL8osvUsRjWFrPSGkfoMubQgWfksKir1OECLt0jvDlgEPoXcKZngV31jUAi40y459SR62TqyZOIi8mDr8dzSqJQvWN3laN3Vma+X/PByjJqfMlxrNPeqlAsJ1BQq6xUf5Eqsz1cMzA/I+l/yLjUxd2tU04SNP2BHMImNWzwpJlRlXn0ukzstMA19HitN3FqDTVpkW7/m8bsrpn6HYtsmFR2ssc8b7wBXHWF1Hd57UMCPKjiegjIZkhAi7XyH3DJkndPJXGioWPQaG7I/UVH378lVsxSdBU4a86PNCMI2aj6gNJ2hTBVe6T2MbkR8KCBrW95OsmTZkvm6hvK9HIPSnMzZjDM5wc3vU2HNsrCk/VbBrYlI5hBxUmMnd8EmqLMdRJhZqFfbGIJO0zNx632uPiywtygSJQNuxyvMsylmvkiqzllkM2Qtl5srBy9TY/6+yXc2TZbXNQoLWDmXLE5loukZwjQmG7jUHjfRBj6x4mIPE1ZyhU5Uw4o8Vg80HgdjJprIoL+l7oQI/oTSsk5du+JlecVm7tGaP0L7nk7uL2TsuUEzWGFWixAoSPqCVXrLSfqAQdkkMARiZ05sl5hvXyG87hCaAQ+rS+6FMoVvVA5PUipXz/lGdJHnPtUkYSa5EPXRihW+f+hwXZqxChOMXoQzFRk1hyhyn9lgH7c2YhH75McJfg/Goc8s7bG1VH5eyJDxfoqx3CF55XCXtWhpHjtJnaWasI2XtIQGH/5zCv/+H8f0v1rTeHRCfhvw2dfnvP1BDiGa49gneOEFGzWkHvcZz2Im23vuNxqZVyGJeM772zpOzmCRb+INO4jKhOrinHC4R/Zxwnu5Lu/8OYfqLXLymKlV5La+ZecHHmG6pe6njMxvTyX+lRABmQynloatmuzrNQY390hJhPW8xOIrgXpzTuN4y3wRs8lpbI4iskmWHbGA+M2IZ093ubgLqZplXLOI+L7DJ/pbpCQkGqUs3TVmqDKPQ2xhzWCUwZsFdDZ3zIUedz8VUFWd2vP3KEcq6hBsv8148IqJFSJM+8SdDnm1hlJI2RsXiIUWYm7D8uUCZU/kfFWhYi2Ibr9EKlUh3rLOZln1Exb5EaKfZdY3kDM6O8kDrOQ1newhA3VLfROxVdvkopjnmTKJ5HEtx6ipSOfunvC0xLnQYz7wMc5eY29KlBsGztsxC0NGtmzmC5Xc7nN2Op9x3o3xLkO8hoJefUxo+CwuZzj+DT/3drEkk1zWZPzViEC0mWdT3rfyuG7KheGzF8doeoedByN+MHpJXpqz8CR0bw+r9D5eJ+He+Rp1Du+3FDaHO5iBSJrq3CxFjnYFstMMcm3Gn98MMZQs7o9LTOpb6p+axD3vF89jfLXiLwKJOC5yfBwi3o+YX4J/1CXrSoyUOZIksJlUEY0VoVHjNtUoZDTSZYIwrhLsTtHyTZJshOBUsbdDrCBiGzU5ij9jXCqxF9dQdyWGscPjzIaN52EdZDC1HRr3FlN1wmYpoKRdohsX/f0K9bxJlN8luXzLOr8CWUTOFEhmtzjzffYyCiYFursxWqRR1RKigkzUVzEtWBf6kB4hzCT+1b02W+klmbaAtshQSyr8xVBGsFPauRljOYKsTV9S2KQWmbTMpOCi5WSkFOJNHjlv89Ld8jQNER5FvL7N8XFmRSRbrKwWJ5sWi1mBabglX24RffMlg+cVRMdk3l9wsqf/E/j7FShRC9g1C0yqMzJf5gh36jxEZuus8JplzgsKjakB7pirqzFBpcCUEGe6QT3o801VY/m5zd4mx0YXaEgpQd4A3aJkDVhOFSalmG0qsL7PkF4umOszvulUSWY5TPUbtAVsVpek1YTsdIfTSp4vPyhTv1wwCr9P2+0jGSqnYowj6iSSS/+bHcR6htvuLYI3YHmWhT2H3fp7WHaIjUZYcxj2r7h/MuPX9WMEM2K6vMG+UimU+rD3EDcas7e/w6zo0pZibgr3BH8U0TPHHBS3nA1NYmcH0xLJFx8xbhp4izmZzBE7OysUISWvLklWLqvzFp5gU2g0eG1EKNE7JDVHYW3ygx/KfOcTm2xeYPLDf8jLTZGWfoIp27zO2GyTFk/WawbCltZhBfVnGfIFBTP0yNZ3sdsV4nRIVNb5mz2LmZVnk9+QzKes9Rni2qI0DbHTHd4p98xHMX74nEWywJC+oRSfchUMSSoZlCTBz6tUZZO7pUbQbdMRv0YpbxHmj/mv/y2BN26dl+mKzyZbpJoP7TbF2TnZmxJ+zSFUFnguVMSHeIMuhhJhbhpcVdrEBZVBtE+zWMR0ZS7sn5LRD/mk/H0qjwQ0xeLLdENJdGjmXH4QxVj9HBYSmzjD58M78m5I0rJx7nLoZz1uKx5q/4j8/R3eHnyV+w6/OX1BuXLMye4JVinCtKbcVGJOtk2secj30y5XU4PK737MdK3jThfMdx8SmRNCd8yXahchENGTAyJny24cs/UVtKRFO47xojWzjyaYVy3K6x4jwcN4XUW35ohzC99a48oeEx3y6zLlY4U0HyEVniEpKWl8ycfPqlyU/xoeg/95lO/FxO6Yv7Ff51UR/sW9mCeFfTbfrJAfVsm8EumbffLmAbnylh1NYn0ToloXrPwDvj7TUKQpnydfsD+TcPMqjglxkMeKCixVn6vrOWYzRyrVWOTuMAst8jcXbKc11tUqHTVkZoo8rdTo36X8ePgFiX6EawaUdJPMrE6aD/CX93TtEk8zES/8e7TVhPamTDK9x88HkGtgfxNQLolE5QRtnFJJS3Cwx/xtzFN5ihcK+CWXjSfiLG2szpzr9TnaW4Gf5TSWvRw/HL3lwXOB7ipAiKbcrtec/DzBr+Tpza4Z1ydoj/M82olprNqkR3VuL2AbZLlX/5zZO5NVNc/zuES8FPHVXQpHGdrtHP3xhh/cmWzFEfnYRZVanFg1xGqE3W+wymdYeK8piRH5ssQn7Y+5WGkYkog+1ilO88wPJ1TmMops0n8SI39hk8Fi6fssHr5g8UddBs5jrnMRolBD+8DEuO3z4ayBoZ3wYnvBNitzvMygNX3i3CsSLWCn+T5D+SWXwXOijsP1+R1qOU8aLWFgU/X36BshrUuFXrtDsN4QtjZoS4tGojNQSyRjE3Xtor5Xwr62WQ8cSqclHh1/xKXm4Gk99nSTTCTgqy73SZskHuDlRIYebAZLKn6FKBOwuvRx7mO+aa4Re3X84GuI9yms57ynf0NiFFFLKjuewq3j4GzmVOpZrJZOf2+OcP4+mZLK/ddzXnb/gsFSR1VWTPSAnbdjNprAxuvgPf2atZbgzZ9gCgGOEPAuqqA2TNrinFHZRlgWEFsGDd1HKWtMVgl2kkdJTR68egv5HNEkJNYMlME7DHNNkGvTPhQwh61v5e9XQgQUGX5994Sx3yWtDhBKh3jzCzqPy9zfD3m9LbOUEpr+Twi9CjMjRYgabFMX6eKKTi3PYC5gf1hke5Ul877BPJqz/XnIn5Zd8ssy5cyGd0ODwBWxViqurzGeV1E6KdmoiXE6wWqH9CKNwfIdl7GJ7M44aZcYfX6O/HyJEO3jliyeZBO6N1O0GsxyGlIlJdr9GM2b49lN8uqKl6UpB+RxE4dOVCAzy2GfvOXPZnXS+V9SmO4wLUkUtgbJfZOoN+b6csj00KB6ppCzztmMS6xlA+7OCLU5X7VbFK49rop3HL4qEG03TMpF5AOdeBgilWzMiy3hXY711T0PQgl9J6HVqbMqn/NM2ydzO2Pw4yv05xmqkyyB7+P8oMuffRjzTCxT1M5I/Sq1O4edvT2sL2wM8ZSaPMe0l2i1AB8Tdb6ln+2StRN2BhmKqclPBQVxb8HN1xHdfJ1VaiApQ/LWLbvlZ4i8QVLz1KUtq805+Z7ONnxGriAyy3fprzuI3RsETeD1+C2jQZmpf8A23fCQJm5NZuF5CK06c32AGdXJVDbELuTrOZR1lqkIxUaX4izmOQk/cGYonS3l24f8cHxHqzii+RsFIllF9lT0G53qkzF2mmd9CaVMDkWL2AymuHdT+qKF4K+x+mPGYYi7DGiWemSXCUZHp3SU5UFHYu2+oCpuGUZ1tssVSnjHPjnu8pdkEoO6Dp+bKvevdITGGPtG4WL9APNgQPtxwmhxTEuREM0M9a3DGykBqUdrFhDkoT4Q8dsa+anMUtEoGiMiN+ZELfDoYIeevsLWlwTXI6bvZmzzWayMyj/feYjgJ+w15t/K36+ECAgCTPwsgysTt6XzZrwkwONnS40graIX+7THAgutiRO+xhnqBKlNphzxSNHxlyaz4gbtXZWz+lsQq2TsHLPgHG1S5/VaRLa2zIJXFOMOU3HMajpDeAjjtwZK6y3B1QpVfUxkuIyZMJ/rHKdzBrM1IQrzfyDx4Pcgq9YQ7SWtTg5JyDCeqUzFFZXAZqZLPM+p3DQsvIGPv3Uw8xXuV7ckX6RoxQhBWlLtPWAh93n1WUC6uCMp7OH5X/BmYaN9vaRi5ElauzREDawtgqky9VyOnDkra450nuH+YAyRwg/+oUGrmlI9zbAXPeVHyy1ypUr7b9R4ZM5AOkbHoFRqUGwcEeQGRF5K6facUHLZWEfozYSN7LIM3hGqTeRXI9L2mkkcUnxaQu0tkU/G1CQfY24RFETkvIvlhpTNOjPfx29UOFj6/Kw7ZDiaMA9OeVC9YzNxSEKPiZcSFbNowg2TaZnILhK0IozZEtfp4K1NlM2IkVmmIawxdo7JLyaoBQF5HiEEI/RVnsZiF+n0mskHCvdvZXbHNdbxgLDd5vTDff7lsy7L4xY3isAf3nXpxTuUwjGCeYc/W/BrHx9TSLcorsfWttD2dYKtTb7ZYTu+wZxaKNs1l5Mebi1E8AO89AadFqFZxIgaxIU18ZFDrfiI7+ba9O1b1naDqOhSP9RZSjbOJKIWGzgbk+c5hR+PPebrhFJZYWy4eFGK1jinvjZILmYUhR3CUhd9JrHKKiSOjFl9jzB8QfUzCffJPur8nLXfoCQE5K4tmr/XYcer0Es21I+PmF8uGBhr9P4Wr9jkO4WIw1qJ6t0dZ7Lwrfz9SoiAKMV8tfkB2fSY/kpivoiwsyJzZUJ1eUYpc4j8bMXgNsdNIFPuaaRZgWy8xcg94nqxRhLfoKgdRtMDsnGClpF45XY4yd2yLDSInAf0I4eFfIZcqePfTIjf5KgrFebOiEI5ZHbhkfSGGPtlhFaX3iuJ/QdlloEGjxIytYS1H1Ec5fhhboWySahd+xSqLl5VouRK/MPhf4gbV6jrJV5sFYajGVFmQ+oEHHkej/J1LmorejchsvCGFxWRfHCBvIXs1uRZJ2EwV/BcBy/5EmOxyyhXp74UeSGHxEQ0WgZ9dw/mV4yEiPlmg/bjGuPfypOpybStAkVF4zu1Q/7jS4/3PnAod/d4u7ngrOfiDM65di1yNR0vn1Ls7aDndLTmlo0kso1lShyytm8wBYmgusJ2U+4yHjlPxk8S9KjA9DaHKa9Q9vYIehE3+h2XvZR66zF11eXDDztEm13m5zdc5UUe5N4nkHXSwi35wu+yd6Jx/yOXvz+7p+4OqB3lEJwlRqwRpRtcBqj3DmuzSMHtIGYhClyEn0vMHtdpSCGRJVOY/AbCZE3n8Zjv/3OHvDy75i9Sl5JQZRasyEVtdlsO2SfHHO8cMBVWbEyXncDkNr1FTqvMllPaps83kyVv0w0rw6JYEInTBHUgEAs2J6Muq/d22cm6WKpEPjtmodmkC4lSuuFrP6HoFJEUlYm84N3gFdE2g8Y+acsluFfxtBWpI1JUFEbVFENwufV9Wo6G6IRoO0tuNmu+UyqQRF/xyNvnyW/XWEgSf25rWNo95t4uv/vdPfzzEXHGoDcb0r0SiFoSTalDd6lTkvuU6lXWwYz7bI/LL998K3+/EiIQexlu7h7xnfwZNUcla+WpWlOEdY2aWWA8timca3AxQRL2uCjISLt9+sETZn5Mobwi53xCWMmgKQMuByl6WkJMbO6qArVuj4lsEzomWcngwp7y8MMdkmubK23JXnzAKhGp9xZsHgbMkyLmXZnTmoafM/g4JyBGPvaPBghalvtDeCTW2bRdqmFIlDlgECT8ydvXBF9+xV3lkFZjQmMLqVdD8AdMHYWd509YGBC9TSkWKtiNGs3xkEVegEmKJCm8i05ZBTdogwGvNBX9pEfh1uOz6Rz59IDs2wvsooksOSyqGaxZxF0hRvUKFMYX7D4r8uSDX+PNH7/ij7sn6NUKox8tuT9cMfzhBa+GCyavRKzOguFaIxPscOP8hHakcfs2S2pAvqajKgs6ag4pX+Pu/BZRjEmKT7AFE71ZwwhE8t4N5/tLGluLw6cxxipL9qMDrCihZ3YZd2Xy4gTJGfM8Vult7/FzJeTqhEUvz+wvrvBrJt/dKzK8P+BqEpOOPbLlO/pXG4L9BaehwMjrMCvPie8l3N01YmShXId4WwU3ztE5TgizKmnvmiQuoR7rtMYznIXI3xZ8ascLtpU2fzNbpaPZVLw13WGHcH1BBbBNm6koMF2ukCpVcpceuSJ4Vwrpvk+1/h5x9hhtr8tBu0xGv8VcV6gleSavcsT1l9Bf4Nan/LuTNdViifCdQ+JN+boccfZawKy5LBQb7XUFrWWx1W/Zm6noFYnG/JS+uuTYK3DQKrKfWVAYiqTvLXlqjCj+lob0JuQ41FjNIv7mTp7Xb+6wIxl//IK324THY5upp1BCJVVXmEnKT9nyO90LatUy/+DFZ9/K36+ECIhiyp4R0o8yCL7I28Ka9bRNuWIxWr8i1Dv8bJOjWZA50t6BEGP4CqQT+qKHHkiIns3sZolU0Ek0HXk/YO4E7M52mDkBUZyiWTFa9YSP44Spf4luyugi+PoLxluotKtkXoSo74cc/n6dg0Wer29GXE497lt9DnWZw/UT+uGWeTfF01LC+df8aC7z7uId8kIhrJRRX/QJtw8YBbeokoDm1Bgdrfnq7HMGThF1N2F1UaedL3ObSVEzCtl0iSGq5NQFC23OeLNFrTQJJ1M+X6Y8UDXC4Te87HRYXs/Z2azotHOkSYX8xCdJe4SzOtXkU+ywxjZzw6cFhWjf4mp5wuzHf8Ftcs3yQiKSCkzeNNjUfVYHl3zasfjqTMQU3iDVNjzU3+dGNPk5Io3pjIPKkEEYgVSnkrfYzAeIZo94J4I7j4ftHO5ky9XMQV04zA5SNlc6s+sp/XhK6ME2ESnm3xGUd7h5syVfXbDjydg9lVxi80q8YdPPYMoBy6LGg9TDu9hjHhYwDtcIZhZNzRLHWzZ9g8zOAiO12TdnhEaJehwjDHe51l1+ftdnJaRMpz2aJynjCdT0OXm/hqt4CKOIvD/CV9YEmZR4msdSFaaGzXw1QYrfY7M/xm32eK/WwJvnOf5OA4GQNJ5QEpoMKy6iIvCBV0HeVrk/LfGKBrXejOkX5whRho1/iHMf4ucKDKUh/rjA3FpzIkssKxlKYcpIlGjKM1qnWf7Wp8c8nIgs7nJUTseMq4+puCGjtzbeVkEMy6znU/690V9wE4sEpsRGLpKPMvysKdPIaXCp42d6+GEV9xv4v227PHTf8qK7/Vb+fiVEwItcxLsuT4xdXtSnhJKBKayIVio3fRF2XXKbGePLhNv9DLmqQWGYEnh5DlWD23hNEr/k1Gki5TN0hRWz1zNs8QTJjTFjg2npmtoUGmbKWy1DvaRRzAVIwwUbz8e4q+A9rZD7JOGTZxlENcXbmpiPyhSHGupoTsdV+YoX9IcG09GMaHrJ6HzNqW4yClZY5Hk2l+ntp6xvfLA9nIdjNssq+kuJ3JGAHWVQbj5nurnkxb2Nqa9oHrd44ywIjlR+96Mm2c/rjAcj0ncNzvIGlayLKbVZey6ZOyhIG8KVxCyb5cQQ0NYhntOh9XebLFYvmf3lV3x5saV1UicrLnCHd9xuVpy9ayHlYrb7Cdf3UzqmjHl/hZ+pU288IEuJyeKA28IG59YibkI7fsVC/h2sIEs76KJFX7NIO9ytdWIzIFFkvhZ9xHWPncYJg5Nbvv78DPunW9RWjdxE4XamEJ8umecfo/s6s/iK8fUzpvYNyieXHPZbTNaHJMqCdGxwugLraYjUyJDtKdyP7mDPYBlXOUwGjAwNrgLe+2d1FiuZ3EznRZoSFJb4KaDIPJzBm0+fa4M/2wABAABJREFUkK5v6OyVeBBJ+BWBrR1iZork5SnTUo3BVuebjEDH+ZrFQsaqqzS0Ia8Th6zukkYKxR0DlmNESedQzuExo+o0uLNNJt4NRzsbHDdF8TS6rsJgobFvevj9Lqtsh9tVl+LSoPZEJrHv6Q1ivqsXuSTPnXfOf+Nv13laTqjZl6wOCtQPyoRDD+mgSOHujvgafmyfU5F/g/InB/zJfzDj0ADH8xg+2aP9l0MMt0SmMGZaX2ClBqWtTFPQsesWRs3DCv8aywFBEHb4RfpQnV94Cv5v0zT9NwRBKAF/H9jnFz6D/7U0TReCIAjAvwH8HuAC/1Kapl/8k8aQJJXbdkBuGCGFCRY2wVXENtvnw7zOq/sMZiZCzs1Zl9oIlsXo3qatD5ikZdIUytIDxg2d3Y7C4C6l6czB2aBWTfqFd9SSAnJxw4+FEcWMiazbZEsd9vUWN+M+Zl3gd/YL+J0C0mSAKGQZGXMO1gFr02MmGXwWtsgMv8K7n5BYAnaS0sr4hJ0cuxuNOxr4aYyeFZDkN8wGGhU5T6yFxPqIoCjzuH1AEF7QtWakF0u6j3SUqyyK6rCXtXAGTRbKW9axi6S4PFhfk8YWo/YJt6ULatslTr7CviCzSMu89tf8rZMOt7MKhdwJ69mA+a2N1jjFDj3+6O/9jKUhczkcUxRiZL9B4TzDh4VLZGcP1cow900c8R4kgz3zhtl9B+zP+aS6w6L1HLs7pmbG3DYs5KsshV2botChH76lWjlG1kE8s7hdrfmT4Q3WKsA6OqTlzZgXH9IoXLE8X6PcbchkFGoFj+vAw1pskBKFF0uBrBIjnF5RjcrERw949mGO4e0N8QbSTQdz6mMWpoyWx7g7Q4pBnrJgolTzWKcOu19tWRYbHGsmi0nK4j2Ztr9kfF+n3YZV0ye76jPYHlJzbpg9UCgMxvRfJZSPdKbGITuajab84u3BSCswWA6ozTzKdyK1vMn2+ZTVuchlUkTxmky395y/veLVXY4Pf8ugfa6QU7OoyjnRe3kCI0M7n8W6myMFWdZzAaXRQt9WqZ1kcT2N01KL3zBUIrvEvBOzkXUagz4rNyT9jxY45Qj3BPYvnzFoDpHtNuXSHH/sEmcM6vMxYWuGu7B56H5Mf3rJXT7hew/qnCYbJpknDOd/RDD/tjjS/3QzgQj4H6Rp+oUgCBbwuSAIfwj8S8Afp2n6PxME4V8D/jXgfwj8HX7hMnwCfMovMgo+/ScNoKkySXCMX1kwXFk8iuqoD8/wbZeLyhJ5UsO1Y5RWm0Otz2y0z0Zf0E2KSP0l7bbMOtUJN19zcf0epcBD3cTU6jF+P0KULQIhQS09wgpcCBes+nvs7QjYuwN+Y3+XZE9H0bN4L8c0ihesjh9g3bmMnRnV/Q0d+zsc5H2cdROl9ZTWbMys1iNj5jlbXbFwqmRXA4Rig6ZS5raWpXOQIOkKXhhgVhZ4uR3WmwCv9j2OFgOmtc8o2htWw68JvV0uvh5g5lbUMu+x6zl44RfENRE0GWtyR9HXWQYrOmkdEpOi6rPIbLhZZpB2b8leznnjq+yID6mpIj988w3D5QWpXaKUTbg2U57ki5jjPn79AdErl5yZ5bCzQBmFXExj1vGGfN4isHbZZk7J3MFsJZLsL9kOq3x3sWGsWtypF6hDjYn+Z8y7Jcamg+O6tJwjJNNAd33WRsyJ49A/qPHlVUTtyGaqZMEYkR11+Vlq8y9t6vRXG9zciu+Nv8Nv/tYTumuB0/pbqoVd1O2azx4IyF8mOIKKtOez/9rnwp3zB183+Y3iEqOlURyckTH2+VLUmL51KB/JvJeVKXw3S6ZQQQhBrYw49sYstjHO11/zc1fiJG1Ql1esgxoH65i3M4HA7TOQXRK5yqqWp1O2caKYR+sKl3s2zu2CV3d/H9PxKCoaD96rUY4LDD/Jc2xrlA/+WX4Y3OP712hvXtOriZQLO0g9l6axy5PHKQ9LhzzmT3lPhaCSZ3MekZ5BrSPwJ4mBmb5jUxcplx+xvXqBtJgTreH+/o6CYWI3YefZFmsh8dNtTMuq8V/8Wzb/1jd3PJWK/EY1YpSsYB3w4/NrnNkBcPZXE4FfWosPftm2BUF4wy9ShX6fX7gQA/xbwJ/9UgR+H/i30zRNgZ8IglD4T1iU//+Uh09r+yXzokotKtEPs2jTe9y4ROemQ1RYMGyK2BfnLPM1ykWFWS3A7GVZlBcUcgLZRERc1FlWp5ymIa/3TuFax/90SeFHE8QPZKba13xaOcEaVrh+/A7fb6COdO5KIyzLYdd5RtrQ8HNH2NMMpcItlWGGP/y/9nj64c/wrBRZrfEguic87KDHWezLOacH32VrDqjuHtI8PEacB7TbF6yiZ5ytJviLr1nunXISTvnZ8gV7pXOUFymGInI1TFlEx5zqZcK1gCsXGYVLaGcozVqE6TFKxWEirul8neM+66OvxgilDNF1i8ePZFJ7n51cwiDcEo9cHj++4KdfxvSdS2iAny7x7IhnRRVrc0Ynp+B6KXe/0aF6uGL2pymTtU+qdTnLFnnQNEnrR9hfXrIJfcZGjfe/MFEPE+IPQ/BH5C4G9GYa8tbCs78mik94bnwPDm+ZTAQGNymx4qDVL/Aj+K2nBfKFgLN5zDcvXWTZxSi1MbOP+O1HAn//6ifklg2kpcOHnQ3SpU0zY7B8uEd19oa7goprbkhnS7zBAKP5FF9yuV9MuBU0Ps4/JVuvEa/67PymiFnOsX9R5a7rkbduubdryLJDoKxB9XD8Fjslm7yYUFi8j5q1mBQMWs0rDsP30MNzrHwTLSOT9no4jQK2GxKUNPLJmu+WPmHxKIOZi7BWMb7yjj2jSLBuI5tTTm9vqdUtegK0DzMoiwaN0zver5So7NXIBSEJO8w3GcqRgtsYM3nV5GJ2SSx5NB49YdeoEyev+QvnEdX1NRnlnrQaI72z+c53j2k9q5PztwwyOQ6kAW9XMXv19zjOzNkuKmyPlxx4l7z+D1+zcI1vZfw/057ALzMJPwB+CtT/MbCH/GK5AN8eRfb/JQKCIPwrwL8CYFWrfNL+dS4KIbc3t0jZBCN8n2NxiSlv+Dryqd49wFUTkpcZeDDhNPHpWS4dO8NovqUSWnheCfViyWdWhtWhw6D9hp3pd8i+P8TIW+zMzpEzJj09i2n6bJUtd7ZAfTNnM8zReADLmz6loypJOmO2OEIpLdEe17hZbbCnAUclET/8gO75H3GxmaE0l0jXB+w9L2FkTPaLU/yRyPxahvQHzAYimUpKuavTyxZo9RdsMxm2eh7hQUTrjc8jCzJyyM5K5zNzg/31EGl/h7xpYYcm1Vgku4q5MDTM2Zg7HcphF621JIoUtPCMFk/JVvc53u9hKQcssq8o/mmDJPqFm3IoaARGjs3OitvlkoZc528fH7K5TLmv/jm9zZrUzNGxZbrbJUf33/CV7SFtR2h+yJ+ONrzfmONcB1w1TskkBZq/+QijlNL9+RNaixHbbJfR599g6c/I7PV5/vyYnH/Au1wf5Cb61SFa6zPCSQmCCv/lAwfpS5f17iMmtZ9wvX6FMazi7XRp3VVo1oZ0ZJGqOCD3sAPTlHe5j9n/O2t+1L3kEJnttkQ9Nak83UOVr9iIWz4qPmY+KJCGaxqZEbf+CcbrKVo7oTaS4fsNsrMizvUtr9QNqnNOJb+Hd6FSOijSfTLk0ZXFF1ceD08KVKVjfvqyx/+9UqDsz7G7a9a2ABmfxWJG+qpA64MVtU1E8WGB3eou/k4RayHyaVHiflvF6Pc47qvUnoj4qzEROrJdw63aTPwtHhbf5GbMJiJy4Z6/03jG4HLCdaJRqBjEa5GcuuDacfnee79O62mRtttntE6ItiY/vosQhSXtXAu1pbM66pKsY/7g//FTZjd3LIXhX18EBEHIAv8A+O+nabr+xdL/F5WmaSoIwrcnHv7/qX88huzovUdp81mG8uye7L5IU1vRDFKUne/grvqs9Q2NsxynTy0ulyvEqsX9xQ7TmxFOPGIWFRHKAStRxJzWeZ4OWfQMYvs7HNa2aNEjBiMbO3lGrtdmo8sIyZJJf0jL3ad42kErWpwv+mSSFbqSEDYOCHoTLDPh+J2B+bQJmzpqbc27eYZZoKGMA8xti21BYTy32d9zMSfH/MntHVgv6U9VHjhrbjYhY2ONatxRP6lC87fILiUE/yWZ3/iYk3oeZXGLrFpsf/IOtyqTbjdMqxns4U9ZzzNsRw7RRuXdJuBBuMVhyzIrI65SihWRdtuh1jjGj4vM7occaDE/3ZXpX6SU9lYkdgC9BbnMASWzw++UjqmeKLztZzj0Q6JsGV2ykfUu9vSYdaaOGH/JKqcjyGXMSh7hxmGYKfOsAb5ZofDZlPOGy/Ablx+pX5L5RqBWVxC8FWmnjRjXkK0lVS/H22/6DHNTBq9ioqsNO5U1f7L+kp3WlI9WXX7XK7C7C0Xjhj25zio7RMx8h7U9xN7s06wVCIQVzzyH+G7Bo2caB70ivVKW3Z0ysj6nFQsEQpbplcyNc8ufTmIkb0j51de0jSzy3OTho30SUWBlRHyWiVi4CZXKBq/qITk57mUVfRDQ2Eo0W0uGbsxieYz7YoIXXvBDqU9sJRjXCcNehdVyF0P+nIsfWhxUHL4rttmEtzxOMtyKEuLbezzlM5zriFV7xdPZ71MtyVy9WfK4peHGeSzHoe8PGP98xfyxya/Lu/zoB5f4YcDx8RFNycZ+XELc/Bbj7QZj1UWdytx5KTO1jDBfsFjY/NaxgyzpXPcMWuVXdL8a8Nl/9CMU+S3twwa3P/priIAgCMovBeD/lKbpv/vL7tE/muYLgtAE/tEbCv+Zo8hkX0BRVszqGtJ5lo6XQzmyaPCS1NslM++hf5pHWMOnxQbVwxxn2op6dk7/eof9NOFoL8NMq7DOvsSXEvKrmLE24qo8QbhvEzQEKlqF64GD2YvJ7e9yls+T29PpGhGKs+KL7hArLvPkMkPVXGPlJaThmnIFylWBTWXC/LJGIbngeUHAPzgmzT0mrllU8iFyN6WUyyIpQ+6yNYLZNZv2HtXRgnJ+TjIu8/A73yPZr2PejTnlY6ollaRS5bWv0amWCN5vMzpOmSz+GEuW2KQtVM4QtCWXlDDEIquxTLb4GDHp8uzjMv9v5v4r2JItze/Dfml35vbe7+NdnXL33rr+dve0HQwGAzMgKAAiCImAGAoRooKhCEYI1ItCCEh6kABJIQkSIIkCCIDADGegMd09Pe27r79Vt6pumXPq+HP22d673OlTDz2kJqi5AxCQFP297Ny5cq319P/lymW+f1p6mxNnhiW0kAKBedVi7bzGo8mEUiAQDd1ED9lsVjqkU7vk1lxiN8pUZ+u07x4yfLfG+i2JoVTGebRCxh3hSh2yQRVTFXjJeU4mt0389depKGken17zyfljqvUJ589TLJxrYhmfT8lRmTv47TNUK0rKXlDbXuXB4IDhfIr3VGVujplmReqRJsFcYDSJ8FiYUv7GLqPnAkk5ycXglLBQojSPEEqZvKRvc7x4ii03acyXzC4XeLUZ+6kSdzYHpJQyhg6XwxAjx6B39mMe52PY1pJ5esJNeZPhzQU5Ncdxx2F5KNC3T7jz2g28sE2uFMWY+IwXRzR6TfbWsjTiYbypwuOTcyKrfablIaNWjpgUYyb0WdbS6HOVONc8swIyVho14bKQTjDGRcqiTWme5jdGMrvpXRLviAwbAjmpQ3vhchIesrhfwar16Iym2N0Rdn6TxCOJo2qPVHTISmINT9SpW1P6cYVkS8CrpTCHAt5Soa+7/OTsiMvnl2SzaVqXMW5GLtj56qtIrVf43/6T/4ATv84ylCPbND5ff/8KABD4mdnIQRAEf+cPFf028N8B/ld/8Ptbf+j+/1AQhH/GzyYEJ3/cfABA4Dko9iMKyyqOoPG+0OOu30SrC1yLMGlniN72qM41fmq8y/5mkZS4z1dfKTOqqbyYa7xdVPGXKmq0gJOv8OBZk28LTdaGafrCMeF6ErIuwwEsXJOKm2RlOSIvJ1hGZ5ijDCvRGJJX5uKzQ2J7IhvDOFJEgo0C0qFAfKNFS22QUIvEIlkke5WTRISafAlLjU8XYfzpNTfu1tDMKI+eHTEIBsSlLcKqwCylsiwrvLRYMvBDWHmDYaJMsVenGkkwH87ZD5dwxkP85CqDqwlObITirhPPOMTlCCouk2aSWWbBprJCqWey8UtJphOdRUiknKux8EyW5pKtyzAtJ0xxVMa+p7CeX+dV7zVY9cnPdabqmPBkSXo8xcndIid2aIgdCtUM2diE0VGK3ZCJfvsWFW2FLVaJRCI8bz/AGbk8bk3wE0MGgwlnqRDqaparRghBDqF0I3x7OmPl8DnD8gviwTY9fGLhBK6oMh11GIlh7n5pj8J9i9GjOVdDgS/cCzDrMQoFnWhlRNguInUDZrbK9VBHjJ4S+8otbu6tsN6fMZ4pXEhzkp+FGc9trJ7OUhOIzxa4qkLOTbJfjTPqxxBtj08ffsLuK19k78YXKdBC0DIsL9o8HQ448NvIapiwA5+0LrGmORoXabbnHqqRR7JHnBsu8U2Ra7NNSb9NrrLklYFGPBVitbbPRJnxot/iKrCZRhsk5HU25QYHZxJt1+Wnz0vMD3wOFZ0zuUlp1UQwRSayzsxqUnBmxLwkBeULpAsL9ETAlbBgVU7QiS7JTTKE1kwO3Q5X9WP6xznM2iqJ2ZJ41iX0ZgwmLt/uP8bS5hBx8FohLpYq/+/39H9DCADvAP8u8EQQhEd/cO8/+QPx/5ogCH8duAT+W39Q9i1+tjx4ws+WCP+9f1kHCiHy9pe5jB9jTQWShkRvUqAUqnM5fcYiWULq6TjTBnv5dUxWGdoy1WWErD5ETrksH8ahOqXTllCjHdLbKl843aOW6RPZuEXjasEjI0xVt5j7KteyRTpqEGslsIcOvdkVubJJ+FJCsBw6P54hljRWZhEiKzWOxXMWdoXV9JiFM8fSJdJJn8RKlNZEQbhqMHvg8H/LeNR8F10YEYwlUrEU096ca+OcP3HnLVpBlptRCzVXYaqPyT9/hhyKsPBTdKUrOuYJeixBwd1iYdXJJBTetV3iwYSNUZOJkMQPz2C8SvVuhpWX80SyC7RQkYQwJqMsqagFguoSLR+mMqqz8UaOlb0CzxYNuhmFaDnJ5ccPuQwrXAYXbO3+CkF2wMGzGeXi66zesHi1+BXaK0DNZpGNo79vMG71eDR6zmFSZBaEGOoqlaiIlRoS+yRE6vaIlhXlyhrwulTiJBRmOfmQWPYLZJdtSus6jhZlw7OYns9Y0zfI9WZcCRInvSF34xk24jqTeJpIJETz8orYdZxW/oRPzwM0y+aN4qu4eRe9HsbzslxMfR727pNx+9TrRSIxAz8qMXTCpHI9dMPCaM8pxO8hbXR4M/ESOwT40T6d/pR4WuXDszMuPZO1IEWinKZ/2MQxc8wNgVK8zmReZng949meyqv1BO5CZKNq83LIZyW1wSDR4IO5y4vnn9LLx6mIJsGsjhBJc6tSo5WecHF/jFbY4OSszTAwWaZC5JptBDODqKVwvBE7syxOGqpilq1XJlyYLmNLYGueoFc/wVt9mex0hDYd0O9pNJ+FqI5HvLl2m8hGipE2ovDCpe28y4f/8B+zWfBxezJT1cePj+FzPEn/VVYH3gU+7/TB1/6I5wPgb/zL2v3DYXg2T66OydxKUN2oIn94xMNVm4+WKcbzQ3bLAqVhh9zmCp7sIJ+MyMxslk4VWy2hhq/pvzQldRVjWhowcitUujGqWRWtoyN0fV5akeldhPhx9xhNCRF+PKVdzNPUjkhYYXqpMkWvh5xWaCUzxGYjPhYvWTRivOZV6WSibKp9rltj4lqMfDzBYG6i3z/DiE6YJnxCcYH4+ENGpyXaboNZEGHQ9ImKM46WZfoPh7w0mSNtlCioB5RvlhilBHrynPmoya7qM1wYOIks8+VTbCuFaUmsmR51w+V6meedl8rkMjK+pbGbDWHuZ1kL4qTqcTquCBYMpzZbN2KsfbnL0tIovjSi1QwRLcdRFZ/09SOONZe61UNsRpFeV1k06jTVHq9ZK9xNbhIEK+ysHvGBnePw9IpFcE3mA4NQJYwsjBifq6h+hHq/hS6uIupX9M5EjPSAWBxaFw3U5g3E2B6Dsye0oxpfSJa5vStjfCLSqino1TCbpTLvXT1l6dms+D1mzTfxJhZdJY7eWvI4u+T4+z2MlRmFSgzDKrA16TJIXPKx3UVaeixTVzQfWrQVg8FSJTUx0VZLJDtp1HaD+/mAamjIDdOjGHg8FKfsn21xWQTz4D7OlYq6Emc/VWDQnKJPNNotC+vmcxy5TO94QCoSkPFGTDMzllaZ2GIbUnDSnzMxWtTnIbJyAfFJg2ltgtNd5c5bWYKIyaCXpetMyLgtpstrtNIEORHhQPb4ajyB2rliZI8Q2znsbThUBYT3XIw1j3jI4/DikGu/R6S7x3xi01POmCde4xd/+RsY7SmX/UuclI+ZcDk9nuDaE3qLJNeP61xqMaqjPoOMzOd9EPxc7Bh0HAG617S6VRKpMStfWCfs9BhZKQq52/jxMJFsk4kVJTKdspidMGhmiRWG9HsmoVWZynYKPTljnSjLII4eGxLrZrHiY/wtnXl3zu56jPHC5anv0hRE3NARK50Vrr00y/JDhpfbBCsBoYHHpVTkZm2Defqch8opwjRMJxQhFE2QjLcxvAhhTJRkGtQS4fkRv+2eo7YyfBIZEzvX8TfSpKQAu2QS/3TMoXoEh1Umn7QQt5J8dVEhtXmXWCVAio7wJhLBtEIyazKvb/HO7Smj0DZN38dzLF5r3mVtzyC9XSA1mtMbh3mpZeA6DS7SCeLCKvranO1A5Hrs4xs5/O0E3eWMcS7JdinGrG6hbsRJy9C+f8pbtRpR+5xnx0l8wSC7vkKn4DMPX2MPxwwOf4R6HuG8f8lEvolzNESNuNgpgcAKkbiq0kud4ng1Nhcd5nkZE5uTHKx1Z/RWhuQnM+KpMkuxQdr8GvlvQPU0x6Qh8PyogZRKk8yH6FgD+r7LWlShFRpjqRbO97qUE+vENyCWtkgvZiQ2NnD9Cge/+wjffMDY3mMp9jmLClT7LtFUnpIe4WakwGArz5Xb5/jiCkko4XY/oxcOc/bCwrursViUyFRjbIWHBNFrIskil0EPUa2RGdVoxNfx9E9h6aGfGFBbYWkGRPt1PlQ/Q7isoUkaSA5h/RprZYJsZ3npdYNKKsZUe4Q5WKILJsJoipiSSV94dKsSBbK0X3S5bjisFBz8kElsWMK+oVBMH5G4+DLHwhH35yOU6JRZ54qlOOXRNM6OpnJ4fcLJ3CJWd9hetOitvYq7c42hrfJn5xbf/wcLRCFMP7akokTo8UenGPu5gIAgiTwt+3wp4uCrEY6aHTw/ydNun3ReoW61GHUKrGRdgkSXeL5Mz+1wMrXJGZvU+z2UoE40n8QXKySTCSLzEO5Km5jbou/dI90Z4lY8tu8lcM8HPKtpyPNVzpIGqtviNSNDq6xxPj7ilq5wZ7/IRDLwZxMe9TX00SWBnsdLhJGWCbL5Ks3CAjkcsOhd8r37Q8SnJg4u91a3UMMfceG3ifgKl705mYnNHcnD1rPMtCbKNMbHBynecJvEnSwbRhQ1GWdZLaAWHnEzcoOOaBA/l8n+pRCrP/E5zw3YLeSZWinCqQS1uI6oXqOKMdIRhVk/TDtcIjc+ZbLwuJgPWZ7LbN0ME94NSLkDohRwFz7JRZg7+1VikRjF3pBcpk818zJ7YYGTq4fkV3f59OoZrWdTHjoaaqiCEethqgsGE5/8tIPd28VauSLuC1yLfQ48j9u+SzBWsLYrKOaC3HWV9rYMkQU3Mzr3Qi5GvsLE0xidDTHiAePmGeJqhFz5K+TjKlZ4Tqw+4Ik4IbylERdm5OwbRAyBy8sJg5TCxWdHnJ9DMxtlWe+ghEz06CqL3SR3R10i4QMmN4ZUKfH8/jHeMsxvXx5QlHWk4Rnido54z6Mm7zJw6hQRsE9CKDmTzTWNN9ZiPPjsNhH3CkFMknG7xNYj9A2RpKiiplyCq5soizlmxUY6V9FueoT0BLuZKJoh4xh1OrM59c6CRaLIxcUFe7kE8/UaM2fAvN0l7M25d+MVzGqYjjYhvnxO6nKdT1IVtPAF6mBCcuTjrxQYHwb0A8iKHZbDFabihFd0C2crgjlJ8ZeTNs3BkhepPOmdMtbNB7jPj4jIc7qe/bn6+/mAQCjglXCFkFnD1D/juN7hzJvhdlPMfuRiief0inm61TBfzKR4kbgkON5C9Hu0zBZFcUqhuIk8sVnULIoNmVHEYtmPUMotCPVbiLERQj5LZmZxby+NZi15dnZA4vxVFMFnWIkwPjggW25hpDeo3qkgDFw+baYI9SQcPcOTwxi/sl1kZdzn+Uzk6vRD+sqc5w8Npt0zYuF76KkmvVmTVOkG8/IY90kY7XxAKx4Q8vqUrA2eLsOUIgN8/5yeUMY4kilsjlE8yDWaPJ1k2VEHOJM+s67DWuQ2ufUUW2oFd+rik8BdTthK6rRjJWJRBdHWmceOmXygcerHUZQF6fEUYWUDPOh2uzS9HdL5AGE+plmashG8gimadOQumcMt4oKLtKORur7JKDJlnx3EvRPkscjpVYPA1amKIlrS52zhIFdOmGcqhIzHjK632Y0qGFODRl8n4TrEbY/r7IzkyGJPSXN78ya9QGCETSkG2Xs+/soqoWcqsZJG49kJPadGpVRETLjkFzKRsEE/bBMpzRk1xpwYXcL3ezx5ZuFZIpeLgFQoRU+bUDg5pTmU+D1lgvXRDeJFn9hWD/lCYerNaI3HJJYxyrMEx6/aFLIy4VKPXLdOWKgh6FNeiB7bwwrnsRBWNaB8pGJ7BkcVm1T5JstHx1iZGrHMED+hE739GsmjB0TKN1CDLKb3iP7ZGtHRY95v5bkqanhxC/uJwthJMumPiY5niIU05fUIsbhOMmQx/lii9KrN3ExxeLZg48okMKOEhRDFN9ME1wOelNpMghALL4M3PKRU3EKYdfGmGfayQ860BBJRMssJoVyKhBTlYGmRFRV0pQB0/kj9/VxAQAl85lKNPeWY+FzG1hTmYozGNUz1E15L3+LSL2P8+JT//XqDonHNMBVHPO2RfemMYzvNsP4Ee2by1fRbjKUhaa9PIlXDjK6ztEOch3RSZyJBYs6WlCCi3+FGPMrTxTl1NYXVbSPtRUmUVkiJKYxjnVTK41ZOxMmHyckyxYhEJWFwlZNQrICXcqt8MOnw5VsS9miXH8zPOX12RkbdoBtcYJkJzMGcYs2nWY9jJ6okMi1uuTP67RR6ZYZv+kjlgHDVoNo0cY0c60GDrB8QxKuou6AZBhlLY6QtMZgRiZaop7bIeg4jx4d+l+xA5foySjQrIGoJmqLIVScgseFRvlySHx2QvLVP1JjQXxYppsNY/gBZS1KZrXD4coGINiWpZkmv9RlYGaKFKMmgTPNlB/nxIc+fDugpNrlons7SI9qKozsugbDNlmtgxFT6bo5QIY8xNTATAeuqQliK8AuVArXYlEZK4PjZBVMhyzLu89qqwg8GLyE+OUbpHjISNNYXGv1CiOTdTcY/HaNaE8ymwKinMI1JRJdtolaMunrN2tJjLrwgY2Woz7sEooK5SKB5x7SS0GyFyfoW2ajBl9e+RC2jsLOUeT2mscx1SR4PkOQs7xkKM2NBfHrOg1aFYzVFar5gNj7Fynjo63cpjzxuvn6bzZfSiMfr/HBRQH/0GHecJEwEJ3SGrZ5xdH2N7bdRCkNShsO04WFp19zSwrS1CK3hGlv5gG0nxJa4zTP1Gb1Yj5XDMtlyBlm5YraYEy/ptJRTVGOfZHibykqTpguPPpYJJ1rg3sdfKVJ80eRodkXEt9kVS2jLNLl8ip1ymv5uisFhk40th9PLP1p/PxcQEEybotlCqaRYTgJSqTiVgUTxbYfFxQqGo9Cpf4p6FwZH1zSsGu+UjpDWi9gYlIcapt9lltO5bHbI+gGRRJxsesZzq8RK6JBhashAvs2WmcAZzmjrS17xiky+NOXqhx36nsTtFZfUeYSTZZNt1SFya5X97A2S2TBHMw+ndcI0esyTFwU2cjJaap+kscE0fh9Ml37/El3bYVkXMCIalntBVdlmOemQUnVyQocrxaaoFJD1a3g/zUHqA+TCHVKRm7xntMk4MwJ1lUI1SSAq6KElvfIh8vkGeFPC+zeZiBdIJw6nnkVizaJuGjw+eY8Hp1NixTQN6ylWOKB//5KMPeb1N4u8PH2L0CjE1TKBsphgnPToJ3VS8Wc8uRAI37rg9z6IcbPboLMHu9YuyUoEpWigPVnDPmpQSp4yCAoctDXWi3nOYhbGlQXzGE6sC6ZD3FmBlSVS3yQuw8pSYnbXY6zO2Ba+SlNu86xh8cruBqncAu47FD7p4L+5x/qmTjXh4tg2xYTKNOnjvebQbQioyVU20keU5zd42NbpGb/PijHgKraDpJ1jHnXQnDFiuIZGQD5eINFuIOc90n+mxsvzFV6LxehuLBD9HF0zRuTgKeeDBOOSwfsfPWcsR6m9CPDWBujJY9qhDE9DGcpqj6rVYKV6h7t7EYZXB3zQGkKQ4ihhYdUvqfabHEsLugYsyyZ3jDx9x0MYKiS7S/IrA+SWy+3ElPjXI1x0NVqzGDG/T0sZIYdETOkxBfMm41iJcafOPBrl64VtZsFLnF5/CyJ53P6U9UGGUCChZ/JU317hG5UIY8MkHbuN5io8Dv+A+sTG6Qwxn1vsU6R9/PlbdX4uIDAJQrzXDSMuoJLJ48iwr+u896MGbjZPSzjFyxzR9HWEiMtGKMvCnHBna53oyyvY32kzia+yGkQoy1kCI88wYyF6zyhrK8xzCsunBcrVMO2YR7DIUes2sRMlbsdfpvSlhzwYWkynAc1FgSDjEWxskApMpssLhJ5LvJ9HsiwG4zwlU0RZRGgUTNYTS/qpPN/8/guSY52BaBJRw3TtgLR7k2bGxTqXcKJhjH6ZnvOQ6cBEzJWZinUKroC5fAbvqqQHAj+YdVnZdkgk7xAPTemcTYhFEoixGHFV52LZZXUYRYo+x5B15OMU3cZDhh9F8ZNZjPMBR4unSG6IUUjF+eEP+eCjbcJ/YQ1ffobhyISI0zfzTD4Z8pNun55lkvqhy9HKhPmVT6KfZHJ7iTh/wkpym/PO7/PpyX2CmMPMX4BYxomOiHjnuIGMtL5GYiOCr4i8Ml4hsQ3jvIPtmFxnhihXGrLyZebTJj/47mNufOlrlHQJJ1Tlp/1voe2HKUw0Etk5AWHqio08SWE8mAIClbxKzugwVwxiqCjGTygEIRq5TY7dId3rKLvjCYlKnrhlEVgqS88gkX+b/3DX4JJNpHKbhSwSPnRop6+w2iHeqw9oPT9kWi+wDOUoqpeMqhEUSwVxFa8/IRWDQD2nUE/RSKWwfnRIV1yybF0wW4QoZiyuwnFOuw7RiM6kMiDdMnBFmYQfY14ocBX+Pqtrm2gFhdO0xg3Jx9F1Gr7CZ9Ip0Y5EJVGkva9x+yDBNNdhknmVL74yIWhb/HbnBaX5GtGPDeJBjLfWT2ksatxby1A2Clz2Fiw3RIZOH4YJhrMkHbtPRzQgZFN3rxjGfs5TjlsuHI+X1EJDqqqNr7QIayGsGwJZYUj7vEqs32CjEmAqBfqxOVJmQBAfsmZVMdMqV7EmvRN42n4MmxHeOl1nsGYgLDosellEMcz8qYOSNZm3FQrRyM9SPfk2seo2f1rq8y8u2jj9pyjhKI877zIJrZDZLdOaDBG0Z1S9LZR5hRg94qUh75+fkbDuEXYcdt9Yo/nNh4TCCR5XHGj1iWspms0JfrFIKPGCteM08UaVia/gGBnS3grBeMDYNrlwRjwxG7haku77P0E9OaEQ3iW3HUGRbL5ZPOLO5grVts2nsxVk9z6lSJqk3UW+VGjqY2a+zBNTYJoNEVxZ1D7VkQjzOGwR+3aLh4UQ+mqEnZGGdCvHKc+wSxqtfoxR/T6NZoRgEWNoXeEkDYrNBA+kPp1TyNyoEZ5mcJ0WzTOJdvackmByuXmLYrbAZmmF7c09OoZD+L13Ufw4sxsR9HGAb+ikF5/xI1ulntYoRyYcn3WxL0Re2SwRE9JMHQGnW+KZd4I0TBE4LdobNgk0Sv009rbOaJznk8snmM97OIKPPxRJGDOs2BrGlkqonKR/HSYSVihFDJK1Ou+euYSbRwTlAt3UJrlFgmfTZ8yf1nnamGNH7zD0AyKDBhd+ng1DI4jaKMuA69GIsNmn2L/FJN7n4JMrEkqP5tShJlbRJYXnhsy1kSWRrIOikDsTGcs1FuGAsbTgRrrJtnyXbPYNIrctqsMIc+sEYfKcnJBB7xZRWFLSAk4eKHwouWiJMOupBdGgw8lQwr5qIXgaJxtnRCnzp9ZvoXkhrrYUMp+cMTMs7OUb+Ms+Pa1PN5Fk8tE591s9wokcWr1PSjZpfo7+fi4gQMhiok/4TUPlxfM5X4juUfy6zFuZEYGZxnK66ImXCZYi6ppDpOewbu2TkyUmx+dcmCaaZzAu+jw+nfHq9S2+0+yS3FGpp3xurbXYdd+iXbVQZ0k+8S7RGktSUpVEZEqmp6JHVL6W3+L5cM671wqjbISwMSJnQyrYxx/oyFUBzxiS3o1Qii1YUSrEciFySoAk59n96tcY1a6JfnPBZxEP/8hhU15Dbhu41iaOPmC5oTEYplkTpjjiY/rDNWY1icVsQkyusmgu6Ro+1voZ6rJBfHAD9SLO+nqXYxWapRpxqce2cgd1UeLI+zFHd6IsfktE8JcklzZ2P4XuQDuWZbVsEpu6tM8sJs8tNt9Oov/iPvFii/5QoluXWDm/oGXolPIabqZDcaFiHk6YLDsc2Guo2TkbKJwbBsP6BGdFZs/ewpUWvCb0MGdTci+yLGci2azLgZPi7i2PP7V/g250DXv+nFzP4MOnz/mPX/4al2ePuPmVl5HtBUY4hzMyUMMRxpLH8fGARmxMpGXjaTNSkXUW7n2+3P86WSeBFC7SDRl0On2WsxF6OMGu3+QoNOa2uYGat7CnV4jqJvmFxlnaYP5c4CXNh0SM37t6wIkTItL00K2AJ84BqqCwTCnMBY95dkTILaEIV1RrGoqQJJSM4hsvkynWEc0OFTfNyTJKbeLgRBVi9iPUXpZp1QW1TEqZEfEjpOQBWkjmF166w3qmynHW5OD+h+jSgGToZYLhiNmWTNgd8DycoejCo2WcymSBePkpI62EI9jIsw6fJNbJey6/slpms5hjdDlEOjjmR/0orcDGef4tchcxorMIJ9UAISKQFg3Glk0jvCAWqfGztB//n/FzAYGY77E+E9EHCpIe8Fn2jOmiyq1BmqN+lOpSRN5IkbY0ME3IBWhbMuI4hDU8QJq3mMfyyB2dzGqdD88XaPI5ilrB/cSmObD4weAFenFKhj71mUuuvuS838XTj9kJXgOpx9qtddK/XOIvHql8ezBmYXf4SXPBau8cQ/WILZI8Gd8nErHZ38xT2rmFmmpx9Vxiq2wxyZZZE1eJ/snH5Eav0yiu8eLZFd2oxHrvnO46WI5FPuLTUk3KzibhmI7iiiwKU8Ijh4ucxJ4f5nx+g5ja5bQrE+GK3rVHJ+vyRssjm4ky37WQNZ+S8hq1YRfz3nc4HDu4h0nkkIAhL0iFbM6GNnlMJCkPUoLzhw5/Ym3I6tSnWxVJP+ki+jaL5JjzmU3KCHBLUVKDJdP9dcTWkoI34LPjMIzHTNNjsh2NgS/hBSU8Zc7IbjCoSEQ7HSpPbhL5WpVbN4tIwoBiJY0xD9OLbvILq18mvpZFq6cI5jJhT+HSXlJ2k5w/eMGnwwE92SAz2+S8e4KaLJJW59yM/GkSsxlns095YBlItk8rVKU8FIgxY2H7fGVvh9wk4ItvZGgPYsRvrSKZM5T344w3xjxQJYqPHc7HE1KGRk+4h3N9yf5Kjydjl1U7jBAfE+r1mLQEnJpCxi+wtj2lvTSYuWck6i0GhQipIMmtcZvjzoxFMcCI5bELUWrBGE13mVEkKE/JekU8PUI+F+Mq9IKLTgc/PiQ2ySHWPfyQiHPVxe0lKa6sMlUmaLlP6T6dkUvcxtAc5r5OsrBLSurztZd+gb2yyPnwnBNziNhSGV9ajNOXhJYKVzS5pxRJDhIYdoX1kMFzb0hsqUMs8rn6+7mAQCgS4c1fepnJ8wHU6wwWNuOzF7QTGfRggpov4CUMhITD+fkTErXbROQRubUCxvwGoXgObZTip5NPMWSFshwnnNxh8lmdZb7I4dwkdf4pyrnGp9kXBGoaS4alLjFqhzibHPJKUWX403O+9G9FmK8UeDNcAanMdy5/n8WyTSdcJXHWZbgzJ22M+en35xT3Z4RTIvl+GaJpam2ZmT7Gy23xajxD7MEzZu4Zk2uH62wKWZniLufknDKptkVmTcYYTRm4PsXA5FocsCpXMOdFsu6YWUdnPbdE0GXCdo7Jwx4n8jnar36dyOmEhAiNyFM2s79M/TxHwqgzyB+hdHMkxw5mqIchxJmMonjZIbOsR1yo8/c/avDqfoRiPMkTa0YspLO7ucNGO8aLl1rUdn6Rm7NDBhGHhw8thhOFE2PEaggcdZNl5JhBzGKz4XFBkUwqTj7lEOYdWrs2od6Q3//JJV+6HUXfsMnY94jOTtDvxZkefobjuDwTLDYyFV4VfH77yOXUvmCiywysDbqtOquahj47Zm//NvLLAvWjNh8vkyR7fRRdohK+Iit0SN3ep2dFSMdc5KRHv7iK6w6YJAXs9jOMRId5d42oHSfkP6SmhMllDObTM3pVBduXSFdzXF/PMY0Wx+MipfgVi8MwwcqEzlMBZ3ON0HXAVU9jsWKxu5Q4USYsbrQp9UssFYlw3CGQJ5ipGpJocWOxwsvVFP01i/4ojDa+RMzoFL0bjPUjvOzPsjNHXAd5/SVcYcqsNKYia6yuFVkRYnxSdDE/7bCTlti+U2KDBM0XT8lG5rz3VCRWDVBiHWJ9jUEyYG9ni8mBynirTHXW5nSRx3Ed3KJGLZni8w4T/1xAwFnanP7uNau1Ps7dPWpaj8bRAU8KIdJjgVIJYvFV8u0Bx+0Kzyb3eTW1yijZRy/uEfNNrCLsdRO8plV4PzLEOn+IvshiZCLIsou3FseZd5CzNdINC1/L84k9pyytMk+LfHcwI25e4D2OM52bbOX2Sd7T+auRdzhPWGzu5Gkdj1GuVNKWhrteIWhfwDDGkXaE/yRJ4maBsOdTHesIMYP0LYtOVuZebJfJhkk+vMco7OC0Bhw0L5ieRanvBDjdGH1HIaU0WR6nmMfqmHqMkg0hEnQiMnNVZWnLqIbAWrNHpxJQWMlTcXRsqc5OxOf4iUBGkzmUVHoFCbmzJDNIYAcLrh2VdOgMFI9CEOLRlUH4LIMRX7KXXOesPkTWFpgXBqWKT3n9bfofvIc4eo7s7XGnMOWiWSGkNTGkG5SaBqI6RBi3EaoF8luvEkwiUL/g9IHCuDJlNPRYe/qA8lvbJK4u0dQF809tElkFmxDn4nPya2F6voQb+QKCcUTWOGe5pyI1poghD+G8h7o7YPF0RH9kctSREdwLsoU4ofI+1olHMhchFTWQHZkX7x+CNSZh79A59xHWthlrJRIFk9m1ySSl0W328CYrBGcfMf3CGtr4EqOTxr6xhVMfk/WXdGMSWWlB2DbQhmGkhEhWdNHPMxzHOlgJgaC9gxDTSTtdbG2VsLxFrThlbgrs3tihIvVQzQkLLcpYjDGtD2hvP+HovEQ4VaGQyfDyl7KkG2t8cnbEn0zvIwFrcZPY+haqMySCwLyYIzp3aJ526U5nUNBJlsJ07z+kp8ZYTLLEUz2OnQ7JWITquI+wvIMYrKOE66Q1leJw8rn6+7mAgO96jGcvsM+zjHMdfsGAG6t3mRY9NicqEzeJ8vFTTmNp5Bse/d91OZGuCfZjpAUTq3POeOMWb6YsBpNTZgmbAQG2WkK+PCem5ch3XJo1jXInimVp2NkD4vMolSDJ6aSLHXLQ99c4/SmkIhoPk0Neb5rcP9ZYkWxu9MBuSJjMecgKqYlLIrnDVX3KZjWK1x/gZW7THmdoKw1SV0P8dZ392ZdxvyZTC0noayVuLeqcWgIXL15i0mwhhG0sYUYuJCO2a+jCBVG3hDu1MeMB9okEiymN4RPit3fwKaBu5IivpRiMF7jeKvnWHMGbMttLMbMCMlOLuVIgqxxx9apH+LlEPF3EuAp4OS0x98/ohh2KI4VYkOETuY3CkpVOhqhk03j0bc5TuzzWn9PYShNvpxB7l5QUDcYyjcIcJ2IizaPc3q9wp5DGDfKcdX5M3zJIhnO8cKc8aS242/X55RXI3Umz6K0wzrT5qPEYeaFwQ9nldq1I7Q2Z8e81kYdRhM6MlFalcDNAVpPcKEQxxzZTt0ho0SN/Z8qq9gr6yQvceJJx0COe7ZM7dvlp1GZ9RSRxXabePiNt5onlZNyZyZ42putHCE4GzKcGUfEJi5zLK60GL0ZzsvkUzUUXoRhmNsmR2egjxvI8OnUJy31qp0mMqopbusAemOhXOWzZ4SJw2ElLZLMDpu46+/09gtU5scUpUi6ErS6J5V5wX3AYT9IMLrYprC7JXYxxC1VeUjcZKR1Slkc5ohDPj3AHBgvnkkw5yqOmR8Q06XtzbscCHhob9H/yhA8liWapTdZPIidcaqbO82dh+rdUSqkIYv2M1VtlhmdxQmctvOT/lzIL/f8qJrbH86jBljUk+PaQ79sXKHe3+IZaJRHeJK0YGHGP14tzvjssEzMnPHeSpE0VJyRgGCLmZz0++SWf6niTNxITRL/EgTXHWg55f1qgrF6jKilM3+fE71OchBDqPp3kGbEdhezJhNEySVPt4dsmbnfMB/0ocsMk2H/O7jJN7i2Ng6smhScL/HuvY5kzCrUofkbkautldLPHnuAR00Ik8rs8u/Rwe99i4qwSvvEFusczppaNVNqmI38Xby2KqC/I9DNEnrfo5QIS9h49wcR1PZR0hIHXQRvayHdtnCDPddvl/OklIeEXOT09IndXZpSP8eI4wmWogXyQRp1/ghvdoy7rxKM2wq0NilOfp9lr2jOReaDQNn08XyB9mEG5c4h93+O85GKETzi/2mT5O1cMpBh622TZugBZwIx+wnarRlFcQdJP+LN/5TUKkTWGgxccG4dkKP/sTeX3USMmSVclshjQOumRUsrIno/oZuiJVaLREGpaxBg5dM4eYV4vyGk3MV9xsKPXvHNrE78n0Vcccj2DaKzPpbPgDecmas1AbVZJb73GnbiHuxhzJPZ5K3aT9UyD33zxAaeDMPFqE+m+BQuDdkYgFGQJDBfJH9BMFxj0MhxhItlhXOkx0VmWRWSKZtrY4xWUsyYbVpLgvIuXl5AaKkY5R7UQIj95xCGrlLbCVA2P6aRC1LsgW0zQ1m2uMjqhqoYfJJicZdFP5gQhix2/j9RXSCfvoDojjh99SNCVkVZ20FsKitlGmQ85PYpRXXEpZpbIz+ocpbJ8cDjivuNQKStorSWVfoTIJI8YntJ5ecFmTCYhlcilFRbDJEbiMzJBjI+sDq8UV+HxH32M8OcCAp7oMxqt0VqZMBiWENYirJ6p/PbH56zfcdhPJ0itLOlnFdatDsNfiNIetFiOdzmPjRilasSjI+5FUkQzZXZbGQZbC+7FExw0RNrvxZHTPqm2T0QXWMYFtnNFoo7LotLAMjzsfoKUPcAptpGVKtMfR0itqBTuJFgtbyFnHaJ+ko3xbayKwKTjkDBjDCsByd4lMWGA36rxntbjtZrOR9GnhOINVl99m0XTQO8HJF2JtXe+gDn7hNbdBJ/VFUJzeDRtsLoqYykZLPGKkGUxnxVI5z3mXkA3ZLP0NcqRCNYNhefvdhif1XnrF++wK4wYDTpEm1lenc8YRh2CRJllXSQphLgRfpt0Ycy7nw3ZaassRZdBSiVUX0V0eixWHdzhOe7YILm3Q2pwFzO05FPFZjUUkNFDxHaecGrlWVd3aBYMKuExsXCa1GQVd9Hk494TGtdNlk4emRkF4QaGOuamIzIORtw/fcLD8yv+4j2HwVyk47SQg4CTs5e4HfbZlavEXjVoHnkc+0vubtzDLV4Qa6WYuBq2AuY8xi/IE/xtgd6JxWLq8mdDB3RjJeSkwF41Ru7ZE35XOOWz/ILM9RWtkyjm4Zz4ypTmME1BCUgtPCz9TUbtn7CaSTGw4+gqoMWpmC7DpE5stGQxbiNOK1yqcao0CQUNRo4EHZnqzgx39yu8LojIIRd1RWV6ZPMFaZXsLZHIIkI7Hmb6/TlOLsNynkPZ1Fg76aPEParJPTq2wR15xncuRlTWSnxh2yDb9xnVBZysSjjm4OomyWGFw1iafnTEqlZhT5tjS3Fqmz3U7oJUPknKE6mfjghHTnB1Fb8+YDws0B9fs323Qni9QmqQ48f89I/U388FBKKhMBXtGKs3JZseMb1Oo9htjIjFw1kdy8uzr9dIXUfJ31Z4c1chdR3i/EkXRgn06JSQmaD+KMZCOCKaSnMvv4sbu+L7/9Qh2f4pT05OKWZinAlddMvhR4tVCq0ikfGYZqRMKuuSy0U5fvE2KwWb0IaENfSZC31yao5FY0p6d4PdvT0Mtc3HvR6Nho12GqAtJ8jjLh8aJ+TKKZY5H3kZozbdR9vIklOfYExb/GBgcfDrP0W+KbC7/gqVxJAf//SSeczm0o5SdG0Ss3OG6V3KmSGTro41z7F7J4F71OIy+5hYPkXPt4gNnxD1FAzd41zM0ms/oNut09FkClOVtaSGKctMtO9w6esYoylBOczi1CPQJsRmC9qJNJk6OEqW6BsRlkqXYHOLvLKktfDo9Q1McQWnkqckRNis5InHXax+ikX1jIUzw7I63G7EOF8KOFqGW9U409yQWuDQyqoEvTgbZhXtjo6XDdHhBamDMN5mQDkl4XgSvZU0wbTPzB6wZxW4cZlEjOgEySRT84LJcEZfKREK9zh/odG6PuNOepPQdhVPvSLdWuP3D8ec1c85PLXxfYHrvsZqecR13qG9lIn1VMZOnUHWZxwa87Yfp9sFPWJgNwSQw7hzmRd2g+QihJY+wSnaFN00C79K1haJvRIgDQXS8jZr6Q1OL3+X/Z07jMcL7uopqimX5XRGVnWpXNX4rCyymerSV+PcPx+hx5IokQA5mmRw9IJPVyvkXwshFzfpHAyZJUP4tSnDkcTSTyCP6zjlBcI4TCarUPlGlZQlkRpImHoI8UaGkqjyOz8e8vDkP6VzCOPI7yM5M1bTMd58O0vrNM7xZ8/ZHuY+V38/FxAQPZ9QJIMy1jBViauRwjLtowUChVAM61aW7y5EHpz/kG2xQlnUyUZusfJWi1/7qU84lsT1wzw/mZMpSEREg4n4IT/5gcs3v/mPyLk9mrLP88UE1QsQZA8/85Tu0kIUXZzxGp2sxS/c/AJraxvMlw6mdUpXLBC9GPLuMsUXNnVCVhPT0BkOZPxlgXzqHPMk4D0pzr7QY4hBcT7hYnGbm7qFkgzIXteRalt8OvkB8ZzFhSuhfTIkuXnEUK9hmQJxN8or0hmD0iuMkhkiT7s0IgkEy0VKHTDyfZximKKWwjqxUOMV7lVy1EZRXtyPU6k2+ex2DR7pvLW+inIxYJnrcHzlM29n8VMCZiDgWUnGuSVkFLb0LkunSi43o2GGCRYXBNd5uuUm7mSCGLtD3P6E7VWRTv4WhUKOqbtEaAssxGPuSVDZCnHw4BZC5Tn71j6S9YzJUuaN3TuIoowvSXjeOatrVYzLHFfDJsfzCYONTXaiDvXgktmlRcKXWCxNTEsgWBEpxn1m1wJBYUk0muL+pxJHwhVzQ+DLmsjXfzXPQdtEPGiQvVuiEW3SOXjBxJvg6ham5rIfTfGZWWJFcojkFNL9S85CFm05wepYYTCNYctLspcavdSUTGdGN9ohkc+zuxSRHZ25LaP6EtHXw9w2dIxNgUAPc2/HwVhd8kX7LvGoyLm/iSQmuNx5yO2zNa4kg/qDD/lh/zny/Jx2PQ+uSFgIkDwXLbfkKFhS+k2H0NoWX/7V/4jhaRNlR8ZqbKHTZy2eQt80OR7F6Dsp1Osml/MZlVKSznBMsqzSb89pq4/JpYcsh0XU9oxY8piuHWKj+DKTwOfThw0q6xKrO5vwGz/5I/X3cwGBWETmlUWSpiHT8C1+odhESAUEpshkFCP2sYXzapbs7TUi0TyNxhyx+ISydYc/kx/xyXWbg3EddT1OzBV4erjkTOvx4vRT9MmYcG6bV+dLDrgmFu1hxcBSfYpDk4FWpuykmdlTvvPJj9h2fN5c/ROY9ClrGk7QxJCrhIpfID6xsM8OeNQekFkpMw9WmA9HlPNtglmY1VsKthfHNVW6Fw1cQWe6kyCb1YnOK9yqr3Dnaxpq3cTpzdjPRSn9lXfwj+t8b1piPhvB0zzN1Sg054hTl8TbCWJLl+vYmIIpYFajOLMJDytJzMWEK6lNzp7zSm2bL5VeYzUo0l/7iF/7aIJgLShZCSaHPfoviVhHKao9HdccUZSjhHIh0v6EmXTCopiiFqgoSp+Y3MJPprCdPcxumm98cZs1O0Jr3GcqjrjwQB/ncC5N9moBn35coLhm8X4iT368QNr1eDP+MlpIo/dBjqNzg+fXTbYS+5itEUJMxEr4yK0U10aX9maN+HjJs4LHHXNGN3ROuJTkSh0RdOrIisTdkE7obp+vywqnpzncbptnxTTiwznq/JqzZIn5epLM9wZEpwaJV0y+GEnTfq6RvzFF+DhGMZ2HpYXMEVN/A9lMUK9OWXOnhJU0G/s3EAQTtWoR62xT2czTioSYxBdkegnS3hIvuYZ6K4847KJvbTBOzZg/HjJfLAhPEpzOL/jW736L8998yNNwm6FuIg99UkIC2QyYJgOcYx25n+FYXqC1jil8/W3yqYDHhxo7a09JJ5Nk3CXzuoN4PIJNF9vZYmFeMjsdMTBrfGb1ORcF3hBu8pW3l/zwpz+lQ5eUFlBx8yh+g5XQ1/gTd16h8A2Rp0ezz9XfzwUElp7Dv3j3d3nzC7t8pfZn8GuwY7Y4nTmEWyucS09JDR+g5bJISoxEEKMYkUmEDwhyVb6UrlK4bLIUJ4i5Cv3+OYtGmUxwzGHB5spvIMRg0RVQ3Jv0O1Pk0JIrJuiWTF1bEnGaKNKc/o+vebz5m2T/9DtMYwvMzirZqw6PN854axolmcmhlWwuWw69tEtIt3lj9irj5IRNSaLhLvjp1RnrxhWGF6cUPMe7uEVODPPyhs+kJLIIQJdChKIz9m6+g6c94IO/9/voQph4KsECETlRoSCcMZjkebr4lLJZ4moSZm09zVjqc/Q0giMMeOWNGI4fsF8t0+1c4aTHVFI+X52UKNwTGF+EGY1l1kbHCNkZYk0gngqjTraJXs95YnmEQqskl2nE6Awt47MprdHqShRfN7iz47FdcQl7Lay309xe6Nx1kqyH8vSGGk5mTt5KE8/5RPsz4vslVuU7hM0Rs4bJ88KCs0OXJ1Yfgw+4zHXJzJM0H/tolTjL3QD5aEylMOYr/i7dpcK3L4dIsWPEh1Fu6D4bmT0Gss8XxyuIsstRvcXCF2g0pqTjMnU7RrFUpxy+Tfz1Ak6hh11Z0PmgTNnvMr2Yoa4XqUYdFocGUfXLTL6So6Q1eNbN8FbiLk5kh0wAmZ0SlW6LD1pRrqZN9OH7FLUMqVqE9O0ahVmA5U0YT1scyW1aBx3mB5DYVGm+b/PoB79Lb9glF5MwXBstGUVVHbKWQ8fNoSxnaNoIOZbCkgWkcQL9GUx3o9zMZIjWZLJeAludc9W0eSHmiQ4UFOGSpbnGR9tjhEdDslqanZpExoX21TXVUo25bCFOllyHE1hrZYp+hm6lwU/+r7/DxejfAAJ/jA3Z/wz49+G/SlfynwRB8K0/qPM3gb8OeMD/KAiC7/xxfUzaY/bNY+zIBgv5EVWnyMbLUWb1FIX9EdIRmI0Ug3aaF8UHRIe36FlZqrEMxtM6ye0ohde+ymjepxzuocx1JjGLX/tnL6jOt1C3zuhdO9RyFqa0iSuJFIZR4vFVLKPB3DWIqBJSPEGi+BnHjQhv2jW8RpluTEJJlhh1TpimNlEMiHUXTGc9NpN3CN+ZYxgLlvUZ9csZTTNHaBDnJPcqWttB7MyYOZe4twu8mjSxBvBkZhOfXFNMldix+pyZMqdKhsJixMLMoDstFO2A8xWPZB321QyGG2EQj+G0BwzsHLLe5q03k6jDXfZCBn7sgoV2SONgk8hrG+x+tcK+rfMD+xM2WUU1q6i7YYyYwxu3qjQ/6PF/9x+gJi4R39si4g1Y5kbExwVyOZ3tW+u8spkmtyUjzxx6hCkbMbSITWap8PT930ap/AUsweTGxpR5pEw1sceF1eFo2aXVeszwOEkoLXHq2Nwzp4w8lYx4j2jKx9LDXMgjbk9E7HiOR96MbLdHbuYSCu8x+TRHQp+ye3OLDxNX3JPTRIcKljFj60YCezHh8uKYy1GPedgjYZao1a7pAH57yqivUh62UV/TWDG/gqjlGTo/oXpnC6oFviqO+fG0xrYHtdQeotLAEOfM4hF+Mp7T8BfcH/V5desmN7UwM3tCZagQrXn0bOjaBsMXNVaUOcO1GYumwXe//xsIhT5pdQLbt1l+2GCNGAN3zJEeozpTcZU8LB0mwTVEJPx5jIVuIDzUSL26RO2ohIUepFMcLHSc3QoHL37C3sUxvfwPOP90n1dG97HzNxGfwXk0Q5DdRhndQK5eUVMrvLb1Nt6Ky7f+i/8HH/S6iIGAMvg32zH4eTZkAH83CIL/9X8NGvvAXwJuAmXge4Ig7ARB4H1eB77kcKZIlK3nxKQUSXWN6VThd376A76ehcrGSzwthRFdD7v/MpPmOdc6nC+fQD3EqgUTT2Xn1Ob4i1N+sbbP49gB875LatmleRYlGZ4xGKsUnHPUSh6rMCErRjhPZZlODwkpOwxlHS8+Q34h0XBC/Pvv3CQQ14n6OsreNUJniJK/TXbkMrh4iJW5It0zceMNqpsjztp7RNdNMl6U5/05A6nLcDLjVsYloUT40WWC9nGDifmMe5F9tncdrMMZqrzgr/33tugc5+h/ekU60InUUwz1MIelj1iGE1jtNqI75CKRoTpSmCYm2E9fJrytYoZsfmoavCHtIOwUCeUFll2bylQge8skcWMPYQh6dcCzI5Hnl3UK2Ry7doH60qJZuERPqehFiQQ1hHtvUp71EMx1+vaM2WBMYaOFPNRwp+v8xrd+m9bwGOezf8Cfe+s/4KPcKdn2Eb1xlMGfKtF8NOHIKjDOHpIK5alZqyy3ffLHBRrxHp5j0A5ppOJjLusJkv6CWVRCS2n0TIO18AsavkrYcvnxj1v0Sg5v3mhjLC0y0kvcKm0wnV7gLmNIiyih5C329YDYWZ2e1EZOyLyqFvFXBdIpmJ62eFgfkB9FMVcD6AX8YGpTXp1BQkKMP8RfwuzI48B5hnA44+OnI9S7CZKpCGezEF8tr+GtRDl+uOC99ClyPEwxrxAJF9DD6zyIP2XlW3WmQ50/++/9OwTf9znXzuiHChSzKk4nyqDQxxAdfEGjNFKIW0uuvAxR713yG/8WxZt3cS5MbO2CZ5ZDqjDFDyKcX9T5re//mBVd4rz3W5zrSybf/Be8cfNr7PwPfhWr4hB/OmXteYnErsbT+0948eiSQb9BZpDnuqzwjdtTTj/+14TAH2ND9nnxZ4F/FgSBBZwLgnACvA588HkVRNdhqV7z/vddnuktvvjKOXtfXuWjn/xfeOvtv0b2RpNXhCWGvg3mmGdfURl8YqJMixSzDcaaifv+D5ithcleVrm/NuWj751gWQPMAJxBwMLO4whnjNKbKGmViClwpFgIDxWc7W3m84CCY+EkM2Sibd6Y+WztSDw8/ghfjlJ1wyxCMa6eOjSWC4pvRZmfDxAqBebKAvlyySD+GZWDFFfOmJRaJb4U8EIrXNUuMJIe9vF7CIt1CvtfpZAe0GyKaL0p4yCKm9RZ3bWp3vpF7hqXGKUh7rHOryzK/JPvPqVbNthKZgjO23SrAu48Sbf8nHD6TVbSWXTnJSQuyXkWvcciKTvBKOyjLXVqsslp2+e6M0C1sozHBmbR5Ve/sEld3OK7tUNWGkX239jgMHyCOpqwGxa4NE652x0wDq+QXoicqSYnkzO++eyYX/zFX+GTp9/k8cljDCvPsRQmupgR+tYJYULEJyUi6g7h+JCW9oxNV+ZidwWtGaBlc5SHGoY3ocOSmFKkFDUIOVNMbKYNHTOXxK53aK/7xCybVEIma/j0vC4tN0IoJ/LSZoGrZQZxFsEMz0mefIGXKmf4FgwiMhG3zWCexpQC9mohspkXWNKMq6lMMqIw2t6l1vE5tCw+/qyJ5Hgk359yHOmT336NtVidcB9WSkmWxRyzdy1+qp0zn2TY99JU5RG90Yy8YBBpSgSVm/xHf+V/yleqMv/jj//PaIJAL9+n4YVIKj00fUroOs1SVhjqcZZzi7h8wSe/N+VX/uafZvb8J6SCEl1m9PpXKFKB2LRPSkrgCRrG0iNm+ajWAioxrL0UnnOX6cFn9BfH1G96nLx3hWgUWYbGrIlhrIhAzG8ybic+V7D/JjZk7/Azf4G/CtznZ6OF0R8A4sM/VO2/tCH73HBCMcorVV7eucPJ+0/5rX/yXT760SaGa/AD/wr9cg1/T6B6siRwXfaqW6Tv5NCcFvHgFuIsQew1nUG7zQeDJV/xhgx/+H1miyh6tE8p2gUjyUIrs8wvSJ0PGIQF5FCJfOoaMTFlYXkoWRdpEpBA5en4gD9tfgmSKXo9i8G7M4J8DW91QPkgYBhOENoN6E8uIbKGmI+Ri8a4cGPkrTDKTGARHqNrCroY4+rqFNnKoOanhCcj3PQmF1KMqhziOtrD7YwZmSZx98es6GG2Zjqt7SkR6Q3+Uj7M+ALOJzbz3TKpiEDk/QTZmoK0FWNhZEhmThG1PiNhjcULFbdyijTfYmolkOUSWmbCja2vIsk2y4trJpE09laBaO8Zf763QuFXdA47S/bGDv3ulIEmU1gJk018iczI5LPwjOlplW//+m+wWk3yWXNESL/N7//wn/HmL/7bRGq3eKrlubm4or02I6sGnAXruCTIT4dcAE7qnJMgxW6yTttPQJAlV+shNy2WPZNxzEKvbTOfmsQkkUAUUQ2fO0WfxWyHS22BYc/YF23MWI/pdAcEA6ExY5J0scQR5bnNRMsSmYaJm2Oc9DWxUIjMIkR9MSMeLVLqB0gbDn7HwzBcjIswp8zYcdIciDZCLEo2aeEY62zJNXIJg+5ll3elK5z4Biv+FYJhUs9vIbszcqtvsN/5iC//T/7nFNNRTlsPmbMklAiRvpSZBCLtUIh4b41F5Bo9tIo48Zn6MsIsQWBPaVy0ETM3WHZmjMwxLw7+M5LNAeeDEisxh+ibCa6etFDjeeSMy71+DvH9cxD/BYOsh99RycZCvIhOiUcV7t5Y4fqhhCfUyVYraFoFrup/pP7+TWzI/h7wt/jZPMHfAv43wF/7b9Def+VFqIRkZHXJ2fvfp26uEHlpH+vyguB6zpNf/zHTL4+557xORLD4O9/8u/yHvf+Y5faE52GX+HmB5I0hFWtGcDPGbrfHQUPh+tJkFZeLaYF+2KQaucKR3yY2lBEiNqXFnHGoiRuO4Bx0iYgOOWebviAQG1tctlt4oRnqWOK37FPuxGpEpFOm760xyQhcjnSSCZuBLrLSO+Couk7CGxGaPuGFucEd+QLfrTBq9wj6t4nLDwlCJpoeYXIW5QezKzxPoDM3mNwzOZslKH4cYCctxA3wx3FORh3ubjkkpZfZ/KqAeNnl6qOfMD4MyFcqLNxnfOtTlT8fj1AIPOabMZi/wL65SVPOo0sT8gciT3MGVmaLFz2PWavBeCSTCwVsXNyneDeP/sZdJvVLJvKMO7e2MScGGC6rgczjyzPUtsKnI4mHn/xznozeZ1/5BmFLx1R0prOAH7/7lD/577zDmrjEKcbJuSHOlxPi4ymJVIOj/gpONiA1m1JL9MkOqqz7LepShWCZxbXHeKKCkqoRnQak8haGlOJ8u0x5MMeqOiSME8YhgUnSZtaPEKVA+HjARA1j5eZkD30u2jPa9zRy40uSqsxQVFAnNZILk8lqwLagIsg2jVmeQDEJZwJyzRyH7icUwm0G4wTlUJyWD5fzE26WbnOmjgn1TT47ElnWOvx5R0DQAh5pZWYH32JV/SJP3THZrkRSbdISXBbuCtcvArr5CZnLMGYvgpy3UGMzpEDDta5xlSV6IsmsGmfYtzn46XepfSmJkc4QuopTuV5DPT1lER0xEjNUnDB5q8RidYEzyjHeEpmPLxE/OSIvRDnuN/j6n0nTL+SgkGBtO8JKcp2rD8ekE0ncpPK5WvzXtiELgqDzh8r/AfC7f/D3X8mG7A97EWpKKOie+CTsEcpsBT9v4t1cUKgVKUwTXPzOA1rf/Qn9/S1m9wXe/0qDXC9CMBK5yJyTPLRoTquIypxc1eDZiw9R1CX+wGIzvKRrBFwHN9FlFVcMUPtThLBI5dpHTh2yJoRpRAX6iSmeW6bnLGidj/nuNyf85OwZH33wA0qv/7u4XyxgbK8yW8psqBLtyBx7pqJ4BcrXJ1zEk0zkfWq6hBy8TNgb0E3kyLoTzN4Gy3yD1CSNatZpXEAiU+ZMkBH7TWQxRmhzwYASb790Azc2peqmsGcNVtMWs9Y1xWKa7NpN+vZDls4p7iTH1lCHtySIpjEfXTKXBIx2k04SWOo8d+Zknw4xMyLXizlVEa5TBnLP4cORz3Yqxo3CZ3TDQ+5010koFW6NnyNE0xyLAUetOazrTI81Pnr4PV568wYtawAHP8Bbv83XX9vm9z445vjohEhVIKfJjLwlCSmEPZ7yJBpBnGsU1DPyto4ihkjXLObd2yzdj8k008R2NJ4dSviTSzQ/RUcIEdRPuSEniaUXZA5jXJgaZiaBXGgzIoKpjXghxvCcKHKqQHTbIa9OuZpNcLweJ/EGY2OPl14qEJ8H+COdvrDFlBC5sMxpc0ROa9NYH8M4gVS8Q8+SUGc6uuwgjK45sxym0SP8tTSDmEVc/CWElMLCeMYNweNvfe/H3H3b4MuxLBupDUb5Nun8NrOmQLjZRNMdDHVMNpRgIesEisGyG2JNTDOUJ5jYxBZHOFaOy+sukd/4TR4sHhC2dljPzDnZGJJoV1icSyg3EujmM9YbCaaJm9wtFPlJ6wHH7fuM9jVS2Rvo6j6h0JI1X8Y9uMKSNUZummR1nS/xRX6Nb//rQeDzbMj+a3bjvwo8/YPr3wb+qSAIf4efTQxuA58zJfGzkAKHud9AXEvjNbtgxkh2RWauyMbKhLVshtPzDX773RkpIUf9d5+i/KUkuVyes4efkdCLtGoFZFEiNfD54dM2MX+bINflxJjiKwYxBAg9QZsVMIcVxHmLo70J0UmVu65HWlggKTKji2d0761TcWL8H379HxMbzlD3qixuhClmbBadF2jxNMNrHX+ZZZ42aRoqhGusD2I01lpoVzkmvSVuLcuq2iUyUWlPBMJWinl0TDTvkRQl7ISBvBgTBFX0gsG6vIOellgbXNCL9Vizi9ghmdlYx5+WWA07jKp3+OtplZkRprPUqX9txvHDIebkADGfwnWgOxvy2VIg0W9ymb7LaGVEIf4xyQ+3eJF1qA5KLDZd7O4RwxcpHoybyJ5Kezwj/mhETVQY9C1OZiNm+Qn7vSXf/fV/TjG+RrG3TyxR59F8it1fsF6tkPc+5ej/9L/gv/s3/9s0buyw1UrSdzyeSgZvzoo8XDE4e76HfrfBYi5hKjCJn5B2Q8StOlfWJpXaKouuT0ke0eyZ9DWB0i2R1KMMU3HGmWJT0nooDY0zXcBcRpj5LdYWAubzx5yGYowWM/b8GlSLyK0a0dQK560UDd2i+94xUaPIydqMb+wcUwnVOG/Oee72OO5pLD2FFXWCPZWYxUfcSb5DozdjUJ/xnaXJZkimZAx58CJKWBBJiV3mV1HeW9Y56v2Ut//cX+Nv3PsKM3vARW+Jbc/QchKDXpiMbBLXwRhEiazJ9PtXOMs86YWOVJwzatmkDBfbb1KYBXSCFkv1Ft3rBn5kydpygvywgueo5O5W8c0FgXxOtHSJFk3wzvqrhJYOZ9//LxCXIa4vRN689WUuwkPeXK2yc+PP0bQefq7+/k1syP6yIAgv8bPPgQvgvw8QBMEzQRB+DXjOz1YW/sYftzIAYKFxCwWvAxGrizNq4Ng5FmmVg3aaUNbi5ksjmokLjuUvEhp8xnv/6JI/sXGLyx99RvVPfYNkVmDY6PJ0eMly1iIURFHkAeGYhhVeIzEwMfQc0X4GJ2/Q8mXWW0n66SVnKRujE0KbTZHCUxbWnCtnwaJvc3tUIRWb88l3/wnJ6p/kqr2BlDCwdR9d73BzGGK4HJFQE4S0EMmzMEtxTFWyubpeJRxxGISv8aU8iYKOmfCZz3ZxjGM2/CYLN0IwXxLWa/iFEWqQop6sMZ0ElMNF+vUZXeUBm6kdjnsuttPHHd0mMj7DxKAxfYi9MPByNZJmCSMWZ5nvktJ7nLemGMunlI0Sg0iV4W5AqN1jKD4mOr1FabJDI2+jahZlscpoPc50+IDjII99fsnpUuJ2Lsn3Hnyby+FTwnffZC8NEdmiXN3CkjUuF0vSL5f57OCH/MOH3+LNzCYto8M02KS842EZS5LXKuKaizU1MYUe1rVEUkvQDcAaKewmW3w465EhTlv0MfI+TmuLfi+FHwvQskkcZ0Rm3KGfcshEMkSqS7QHLi37Ba2uyLUwYiM04eNrnUjdxAotMI0Z+dmcPCrfFUfcxkAPZXlxXWDU9DmcR4kXRTLZJnK3gBJLM872WCtM6WfPcPIBxtyhOL+B2x8wqF7R8adEjTyL73yf0GiKZ/b4ZDmh/c//d+Q7fcqvbXCdu8aI9UhOROx5gkXuirIfpxP10ecC9ihBUnVYqyYZWSEWr0qIjQA17CAndTaTcTLrKXJnJmokRemrm2Qyl5z9eM6sJ/OpeU7m9hbh8R7fCN3kqHPEiyePORThRiHAlNb4fvMZb4T28XZmfO87f5f2Byf/+hD4Y2zIvvXH1PnbwN/+l7X9X4YoePjKO5iagx2ZYPUa5FSBiDlgGbTJfOSySGUo5TWE1XNq4SKVD645/vF7XM3GFBZnbNVDcLXKu4+/Sc4oY0tXDD2NFWfJobzCTAR3OeWkWqYaf0ShVUSRfSbunKzQh4rLaCahTWxE+5SMkkVOjhlbDpWlTP1kybu/9UO+eu8GnmwzWl/FiawSOTPZkno0iirXh+fEQ2kqExf/SzLF9jN8L4Fuh9A35iRdgdnIJgilsJwIB1dh1ncLTC88lKrPi7nB+vCYgBFB2uB5wmHaitFX0jz0rllZH7E1yyJqUxqvChy1puQnt2hMn3HMBrfOw/TWlqhxF7HbIBEvU8y1iAUalmcyrccI9qsYz1Uu+ybx0AqStmRFewmh1SEySzEtvIx8VMfczLDVHfCi8YTnB+eUtwu8Vb3H0+YnrGxXKHgO4hs6pz/yCMVfZTuy4PLdIZfh/5x33vkL6GcCHfkW+qyM/MYI6WJCfRylKIOoxTFLC7Z6IToRmYYa4+aKgXxeRUw8Rx+/wZ2czSjzjKi1RdtRuROsEFESjEyLQHA4uIZ0KMTAGpAJb6A2BRZ7jxCTLexRibQoUNfgmE941i5STUoIBZtZq4cbFXh+kWSrOqYbhBj0chjagJcDDSfkEnd1rNNbRMQhK6sVPGvApbZJSH1GR4HymcF79UvG2Q6pNvgrM3xni7/36/9H8tMt3rj1Os2+SlyV0JMwkTUuUw6Ob6LqFeI9j44XIn+xSixtM5tPmecEolkNsdvCasuokUvm6jp39lbx5wPU9G2m0T6pfIRXcl9C/aCP0+7wL3q/Rajm0U1n8cfnuH6BX30zxrvXh3zccbn4/hkz1yVs65+rv5+LHYOBL+MPn3LjG3e4bPQZixpOV2E+9YmoPkFCZDx1uLQ8BPeKfDxH8ov7DF94hOoN+ucHPLn8CbHoDfJOiakqslhq1MIWw45HcfGCZHCLtmjgxe5DS2K2MSW+lKg0dYJlDS9yQUZTkGwNeaBwlp+gl8tMFg0MzSOXLvL4vUe8tH6CkfhFEtIVEXtJX56xcANmapJYKULYi2PGliiTVbzBhHnZwk0FOIcVxOk5uVqVxtQgLy8wZAU33EOqlUiGLtk2C7RjCo9nV4hjBedBlfOgQzjWRGrOiFo13Fvr+F0fabIgHk3S9y+R+isIizOk8oyUtkbXD/FCLxFzE2hCBlGOE2vVeRpaY70pICxknJtjohxRm29TjV7SiGl4swVJInwqBBTCFfJyk2//zncxNJ+Nmy/RuWwQkqY8+TjPvWyM4bKFYK2RCS/hxi6tgx9x9uAh5ZffIrm/RtgxmPUsGM3ZTCy4CvlYloyS0vHHaSJ6n2yhzMIf05rGeV21kM1NBtEu7WqaaSNMJDckpC3o2znGnodXkvGeXaOFJNRJglhyDxyDmd9nKm6T0UzGmzAYt4n0ZizmJZywSGNYp72aJpJx2eguUUsCizOP1dAStxhBX10lPZyzko1zXh+wttYjn4/iD3zOxDEFLU3cVknS5fnkPsNBj/zQYpjS4HrA0Awzl1yuf/KM66cj4nkLX4qjChN0o0im/QKnoiI4c8arPpGrFFexRyTzYQYtgXVHQ1YDlGyWjcIthpGATLSBYEs8jA0h/gW++nIFXJfoow/phXtEyipPnDF+S+KXSx4bf+qXeP3Oa5QSLd79X1qcDdpMFi63inukoiKnhxd/pP5+LiCgih7Fr96mEVZxNjfxDw55sbIEZQW73mBmNTHDDmFNYTy2uQgUVo9HRMZFtKJDXEoiGjOuOh7i2CEUnaMNPUqrK8wSGoIxxPSPCAO5a4fTlIE+03COokTMOcG2RmxaIu2PObE7CEqWsLxHQnBx3E3S+iXm9Rg3KbFIm+RiPdRhHoVjcqUMjwcCtzqXmAdLjlZE0mKROCInayuU7AmnVymEbIzTaJeX/GtWcl9E+3RG+5U5UWtJbnqMJ2pcFafUh0uWWoxdQcC+nrEtGkz8PIvVKudGi8TJlHHCBcemfemTibjkFIeFUmVx6LHMO/jrLpVFgZk7ZKlqtOILovMkd0yRFg1S631EpUTKUUmsjRifOkw0EUtsYS0TrKYdvLbM+7/9Yyxa5GtZSpcu89Uw0/k7FPeOsS5knOUWxZfqJNQMmZHM9UqVnmjx/n/+Hn/hl3aYxELIkSMSOZXBxGWl7hJEogiLLudWmcY4zL3eZ8TUVcJJiWi8xWSUoaTbiHEB3c8hyx6xSRclkcMV+8RO4zzVCiRHMFtdMhy6JKowGItEu3P0sMK0Z1N27jJYbZBoOKyl5hz1XyZot9Bsi7GbYFAJCBJ5bOOUeChCPp9mGOoTnmdJv1TkWm4TkqZMFibhmM7R9SlBaoWwLfHw9DljqU0g2iQL21zUVVZWXbzJEGVZxREd4g2BWHbGcUVHv7zA02TkaxdDGZIwXRKOim0L8HTMjrPO1r0UbVHithhivtImL0ZoDGvsr97ijVKK+YsXfPykg+FZ9KQuYntB0lVJEMdImaS+XiV944t8/O59fvOz38fuWgxnIoFSoPraLlFjAYd/tP7E/7+q/XPC08GNWmTtEKXpkmDRJuqVeDsm83LoBoligrTvMVkmEa0QZtDn4kxlol+xcDIIVz7VGy+zLpu4tQlCtMgwPmSUsqiGMnjmNoKfIVu8gRTNkE2kyY4VHMchnI/QGYnIjghuEnyRSCSDeP0UtTVFSZiYJQdd1kmoIdJKjcKlRGx4ylDwGMdj+EaUDzMJLm9skqyWCaIDrOwQpX/EbOZQXIvzUrTLvtVjqZcZX854Xr2BJVdwz0MUIhHE/Iyhm0Ea5zE6Az7pxrGTHhN5ySJapXsNQTPC6LQHpx0WTwWy0RiLscqBsEZbdBFrIl1zimGqdAsKUngN1ZkS9spYcg4nOWdFMVEXceazEaFJAa81xNJ95PMIYStH29PJxXX87/19Hl30iPg3qN2ocqpnWBFWWbe6vFq9R09wKEUS7Cd9ardzSMYcbWOFtJhCXLR5cPCPiGwpDMSAVe8MdaoQKy6IFw2KyR2+cMPizvYIcjJKIsZmusk0lsSO6TSuJZIPOwTXHtowSSBVEEYzwpcbaPMKm1cTvITJqKexEpEoujFWVh1iQ4WJXMMNyxiJOXcvxiSzKgsrQ8IVme7UEFdqaLs2+xK4S5eEXCCU7KF90qR/OOLw+JLPWn1afoSnA4cFY4bBkEU+S92Ys1worGSzlAsQdjOIVxP2Chksa0KwDKNMTILjLq6+ZDA0EC5trHCG3mwT3wkTBHGSloQTLBhUHOarEcpfuUXuTQdciZ41xq73KYb3eP3Nb9C0evw/75/xwccnTOYt1AMT47mAKScI5yJsvDxjWg9hfryK2J4y9mReDA0OFgKBqiJpSz7rHfPhZ+9/rv5+LkYCkimyjcClNMO/CLMiqgj6nOV0C3mlSfR6n6v5U5RInAhpWp0rzMUnsJom9jjKac1DfGCwkyuS8zU66RqvhyYMHx2QSb3OM21AcjIhpDlMLCjrWa5OLrBLJZ6oV+xPHAbKGsyW1NQsjl5maA1wFAE9lyR50KZXiJMtxCigItZmtHwX1XuJi65CTb+ifxZlKzpi1B1gRXTseptoYRe7NSMIubiuTcpIEURc9O0evj8jZ8jceKtCqJAi1z3l4DDFZ9aEWFglG5twshFCX+ZQ5nNq6TUyi6f0xwWGjQaxcAN7qCBOUwhxiaDY4WwhsyvkeN5UKe2eEbqls+hE2dVe0NT66FmdqRtCGUI1FGDXfML9VRZ6n+J6mpD9jF8ubPGwdcUHl+dUkjLlVA7J3KdotemneoiCx4uzc8L6HQKlizQsMvuoh5WLk10vElr2+ORqRPOgzPZozE5xnfHEZV2coqZfB/sJUkjAU6aEKBAu2Ch2ijO9imi30QIRPwC14KANJ7gLF0HpEJcKqBELY9RHXutSMSIsEBn2Fkx6YYo5lWE8hDM8JW9CWBGYWBFOrS4FOUPEk9m9viDcLTKPGkgFlzfEBEEQMJFXiCZ8lt08ZrpNYfwWz2OXNGyZ6FSgqgvExQkLwWehprgbK9PuQSQewqukiV8GnC9nLLduQsll2byC2YhoUiSdTDNr1LFSS2JKHjk4p157Ff14yWYwpa/NKOgevQ/GvF3Z5NLXqBZydD+bcaj/U4y6wbg15cwJqO2mGKKh1prsChJ7q69QNsPct4/ZLIfZiAwwSjm+sJNjMBU46UyxFyb+0yEd64/OKgQ/LyMBOUCSwjjnQ8xNlXpaJ5FcJZW0qAYDxtkBujYguzkjuy6QLeYoRXKo3hK/5JJcuqxEOzD4hGEwRW/9hPK+iLW/Crc9FNHAVXtc9z3MZIl2TyZ8a5dxYk5aiNLbu8O0JHFtDbhW0ujJEP5KkYS+JLieMlNTWJbJ2uoasZUiw8AiKSq0JwZFt4tld5EycwaWgBsPEe0UsRIJBGvGpjIm1R6QPs3QlLJ82HHR7Bbx0Snba0lmnspYuGZRkTiPPGGnalHgK3CxJH0aJ/rREHOxpDaYQsvBnzUIh1tMjBCxiEzalQmXfFY7DukgSicaYsNucF3P0T4dMxsaNBdhJvINlpcCKwMFQXodvb2H2Y3iOmOSkRRr6QbFL+9wLiz43t/9x3hulIY4xL4h4yhlKkUFK5IgFIujSBlWKgm82BovXBt1XUKQNG4LUXw9RMZKUB15/N7f/U+ZqIfk9B0qsTTV/GNK6QyKOsVZ7HAtL2mjcuU8xpsJ7E+LZKQCe8USQ6GMtuviZafkvU2c6ITBUmFU2Wee/SrNss/MhUDJImQ0Mh0ZNxvFWVUoxRa0R3WOMw67tTu0gn3kocFBz6Ou95ASGqIVsCSHkQ4TfhLjMxZU1vsEQR5ltU5q7rEy6hN4aZrxKtNFlCBcRRJzeMUIy5Uw/WQce2ryIFLHF2Xy4guspkPE0inEHVzHYXnZIu2sEZYT9EIi3vIl4u4R1bt13nw5QjabpfKKReEL+8SzHqF8ksPWIz4wfoAyr6PPBCR5jh1fYEkiUSeM4MX5y6//Vd6+/Zfh1Q2SpSknEwd7SyYuXaOEXkWUNwnacXx7wkZNIultfa7+fi5GAoIo0jt+hhq6iepFEa7ThFkSjURoF0okmkuaSoH8Ikt1YhJOyFghGfksRz+qoqR8LL/B+Vgh1HUpJeI8O7W4PQ1xkI6wt1PkehIlZCUxhAVLjkmqJYr+jKGtwJNHrNdkxkqJyvpzFKVHdWTjmDHG+pRlL0PMkJi8MGiX2zgbIT4wZW5XRxx1A0RbpnhhcP/lJXcuVnmhu2hPXZyCg5ReI2OJnNtD0psQitmIYpyWrRE6NJmmLpAWBooskvEiVGyLJ/ZTYtUiYmJG1J6iBAla7seYUo64Z5LqlMh7Ds3xGG19H9mf07ZE5kWBauspdmGdSklgPAxQ/TCyUsEbiiidBIN713jOBQnNQ0tkcSY6sYtLpkqFxUWPT/7h73PpL9GTAkZqnWa7zb9d63C+PqVi1jk46hJfXeHi7CPecbb4VJUIx4pEUxrRdJggoSJnpgzqPl5nwpO//59x+y/+bfIbN/Dmz5nV9+jevcbqLdib1jj2n3BP8OjFn7E8TeKmTYqJMKOxSlKtIY/bNHYt3OsMV/6IcLJOfBKnZmiclxRCpxJnGx7VZJ5kfoxnN+hVV0goPu48htVXqBYM4l6P8FGBIPsZO4l3OFgM6EtDcGz0hEdhliEdVXCiWUoTmbGwRHRvkM22kMUaGBKRUBNLXiCypNcWqSktcuouI+UKQ4ihpOLoixlWY4Ij7eE4I9yJgXPDIReeELsWwc8RDvns6CuEEut8ORol6kdxn3f5aHHIhT1F1xRWliGsicWqKRIOZfnyG6ts7ukMPxpzaCbxQwGHoU8JTlLknCipbZ+ausmjxpLTk+9gSQlKkTktR+DFTKAlLT9Xfz8XI4GQKHBq+jTcAd7wmm+sxRCsCZHJkHdED1PyCBUqBLUqg7Uc5eVtplMLda3GO+sbFII0oXmUil4lGnapT6OMBw7vanMiBz5WoPFSaZdkdQOfCWEpgdeF6diktPTQYzm0boJCykSevs5o8Qp6epVMZIudaIr1qsSqOcZfGlxfDghaMivSFpJlspGYctvcQchHWXHzBLVrxLFPMkjiqhIjp8dxIDMv2ZwHFuXzgFZrymZ0TjPWY7AwWLayHJy4mOMoBxdt1PUFvXAMphEWsV0SxBGVlynG5vhxl/P9GNNQnOlXikxCLwjP2mRjUapWhmt9jZ5VItyKse3to4ciML2itvBwNh+TPZmCFUbZ1bC8CU11wbK4QvCWzMf3H3B4+IBwaUGuqXJD6PHmRoGZ4zJtFmkfhIjuZUinJ0hKiSYOhcgtfvy9AQ86M46f/b+Y+69na7L0PhN70rvt/d5nH3/O953Pl+1qDxBgkxhANCOKbqiJCd3oD9CNLjUxMTe6kQlxOBL9kBINCM8GugG0764uX583x5t9tvc2faYuukYxoUCRkJmJeiN2ZK6Va+e6en6x1rsi39+QrxYqRNkq9ZsQ3XLpRy/53fN/wNPmQxbDiG7+Y6qTBmvBAjvs85afh2Cb1qsvE2/cJHUgcH1TInmwIp/pMEmOyF0nUWIdy3AodWfMOxM+2r5L7OoYKYXCMuas1KEWtMkWSwQJnZwVUEqLZAdJKo8bJKY+a1Wd7dwOcfsVd30RJ+EwM0UkC6hWCUcFUkEH1RMpLCdUuWaSTZG1F0ydkOXmmJymcqqeoMnX9LMhk5qL5Stkcj7a2YhUc4yTTIOdQPWTiHmX9GJOdpRE1V2Ecoe0YeMFCgXPZ3I15zf/zRE///BPefV0xKDpo4hNuu6AMJnial1i6+Yer9/5q+zffRMxVWLSrqCWEhgrk6yZIL6TJqXd4OF7IZOkQUpc4649J7HeZ80SEGsNrKX3ufx9IUQgCEWSlbdYc236sxWdRYwgC7TmK16cWYRTkelEQCuuKFRlZoVj2voMJaeTurmPfuMbGNNNijmF7a+n2d0oo+s7zEYxi2CMP/iQ2YffR7/8GV+L97gdVbHNApqSYpSArOtyuu7gSwaBeklJ6VEUBUKtjxeZjOUsi7VdxvacV70fY2QS7Ko2yas01WaRZ57HJBOTmk7xhTXk6hRqFmkrh9s2UY05hrki3w+Z5xNciylmZhHVnXA7aeJJJVL5LWZGCT9TxGvdQrxakIyzZHplxGnMRmHJmmojLKbcmnvkb2a51RZ50OpTSYRcHNZQX83YTBSJ5D4TNyaYzNCTlyzNGQN5yDiyeF5OoSg+QySMSZfUrMSabPPzj644+83fYbwY4YxFQmHCW/Vv4usP8A98VkqX9M3XWRNvsOpXmLlDhKpCd21J5qslEt5LtrdjwrDC3/7W1+kshygLiUz4Fie/9QMeXbWJ3D3kxTrT1QYZvUy2lKWlRQwScxJ7IfEyQu+nGRzqZC7rPOkH+M4eQdBBckdYbpmBW+ANcUm60+B6PGVVNak6NtluwOpSw7soUG2rBP4KNQzJpc64vjFl7N4nV1kiCR7XssWRIqC7sKlGzMUJI6ZcS+fMzICX+iUrT6AhSwjHF7zaalOoxtTcPfo/g9KlyqZe4b7ocFf2kd0kt+68w63iBqImcD/sMVdPcJUloWCg5jUkK0BcFQlMEcnIMVs2+CdHz/npT694yUMupRg11WH99TlCy+R/842/zP/yP/vbSLUdLuoRGU0j7aucOTZubkVtVKe+VSKVXfFgv8BIOuTHZ3/MQD9jlhjii2X02QMKySQH0j6Z8ufXE/hCiEAkhuxJLkok86V9AWcviTdV6VsBw8RLlsIQUhErRFxbwTcikrJKdiwR+3PuI7PMK0TZIrG6SSGt8qrf5dZ6hOpfI32yzlRPMlEiHgUdTvyI6kJix6iS6e6RWE9T9FIMRB/bD/CyIcKtG8haHrtdJrXSqNRn7KZ7+OdnBCcOBXXFQprhJxY82OyTCm6S1CtszYrUMxXKBZl8OGT97jbWwsE9V/HKBWJ7gq93GHUWrG2UiCQfIwgIhyv06ArNGiJWl1RNH11/zshaoeoR0eAu7uo+klYnJS7pFTpMwyRH0h7n+gbbOZ/WpoDQXlEIBfKegVjPEJgWTriJe2fARsJCMUqs62Nuj1Ik3C8RugtmJzN+/vf/GdcBqNId9P4Sv3oPe7NAxhBZvN9CDrY5Vh4zVl6wJiYoWnW6T9v4x9cU5zZ7ygbN3pTM2i6GXOReqkhtLDL2V4S+zuE/+wOuW9cc+SZONmAhLPFHl+Q2Q6pSxPo4TdyLSMdnKKUZD0ePiHURf9BhajRYCUvyxRHZ9TU+zm0gXEQY/gD7YknbsnFwKPtLtqNTClsyubVt5q6BN4+oJguUSm2uLZlEqs50u4ykDYjsFupAIa+sCOX3qeDASkcUgLTDZjLmXq2CMlUY7fr0mhIvGj9Gl0yktRrjUOG8vUmsjrix7qGvbeLpacjVKToON/MDpE2Rle2jTm18L4kW+RgsuZw59LszRpkGVVFl/w2Jv/E3/xq3b34Dciprf2WXN8wC90WJiqOg1RqYqsRXv3HAL799h+dWzAf//ts0H/2I25GKnZd582sZ/ovbdzEnHtJMIN4uYYRZ1oIiyiD4XP6+ECKgBA6vBjZ9z+D5UUTwbo9oM8nX136VXPw2tdw+ejlk8eQVveIQa2vJX6hvk6xNaQ0U3FSP0GzTE3KYN2+R+fIBStLBNl+nnk7R37QIGlWkhxMm52dY1jFXqRat7ktku89p7xpz2EHninbD5vzwio+e/gwzDpGCEVJrwovTLIfXKyazDsfDKaFlkdFF/P0Mnn/Bg8yCTTeBU3pBV7URQwfHizi5PiXqhSTiOmbdRq5k2JfW2NUmnB73mM4l1rQUtlYi0EO2S3V2pi9YawbkpTtEcR43O0SJmnhZgbW9HJ4jYbZr1E0Vo3qN0btCdxx2ZhJiqkc/UaT4wKaQN9kfVtCWHex5nflqzFqqQ8aeMJ00WeYn3Fw3efSzb7PR7+Lhs1JfkPlqHtMUMOdntHyZnq5hlDQS/hStOaclnCGv68ySd7HkEDefRlVSHEZNPPeaS3nCVL3N/O08y1rEuFggkVjx9PAfUc83KHSK3IzKbNcsjEGWobRJnFngaU0GDxNohzXWEx5qM6ShTyhNkqhVGa1UpKw0yMUXFPYlthMPSEh51pUkq4zI47U6g/xdwpM+zWuZmBSt7RzeKIS4QfWixbEyItEYoxVCROUmh8aCed4jYebxijBFwZJFxLmOO6nQWFVIuUmSWo5R3Of59SEt8SVa0mDX+CUyvzpB2S1zFZeZzW3GUsxzwUfzdeZmmdJRATtUOXZC9KnA2kUT359Rsm7zVrHCG+WvsHQt9vZeY/2bf4O69waF0n2UuEpQEmi6ObTpBo5wg/OPJCb9u6SdKdcf/YSadIf1m/8pvPm3uG/dY6WX+ODTJgl7waqwRL56ySrSWJSSSHc+n78vRGLQDRJczlsImGx5Lr1aj/4zh/7tMV/OZFjXDNTrJOTSDB/neBZeYfo15iuHrwUO47xFUb6BsFPCOB+gaxH1QUB90yazvks6dBDkPpmvvIb2NGTR7OMrlxjtMm7qIepQ5Gx7i4SbxsRnOE9TmE6ZpwPMnEJRHjA71bBfr2FcztCsV1j6XTKpAqIT8uROndmnRRbLQzojE3tD5oUiUsMh3RqQXCsSXXa4es+k+MBjTaywWIVk8yGNZEQw+QDZlslFX+Y0O6Mg6DytxmyuGkTJFuoqR9KV0K2Il2pIvpQlocpMnQHp8TrKrRhx1GVBDiM0sEyXSRiS7J2RmlgUcwmEIEbNVam6OzzMdihcBYy0S66HT/hR5wXV3QSJwKXUT2FZf52cuiQKda56HdazFpW5wqW/ztHLS+7/UpllwaLc7tDpD9iN97kyCxQSv8zJox9QtLaolosUtNs8//Dn6P46aRN+dtql9OMmb3x1k3OtjajGDC4vKRQs3K05qeUei9fniPMWckMjrCocrA6IBAehscLRP8YdFJBXERzUqcoDTjaXTNIO+eZd5o3nDLMrCpOIryRCPjIbmHOL1yQDL7mOdtsl7hepp8+5OBGx8gppI41KTHc2wl4TMXToLktspEM66Qj9YkVG9vBfTgmScGsjzeWJRDJfRK2PSaS2sG6WeHr1I6LjBHlzhR5kWL5mIYwdFuUVnp0iGSY5z57g6mWyg4hGesFt4U3qW0f0hgFi9QYZt8FFLktgDzg5i7iRS/JX//Ie426Xkz/8OZPIw1/f5fZbt3k7seAyOsD/0Z/Sfyqj7Ufkbqb57eYYSYqJLZUtf5uj1Bwt6XK7Z/Lp5/D3hRABSfS5H5RoZsect+aYYgXfmzAaL2h5HtKpwctEnzvrt7i/VcRzSoziAOHViI/MxzjHETerFcSzY+ZbMQVvk14ux9ZOFX24QG+9IpOSUSILeSkyt7pkxSoDtYciSXiSTlIas5xGlPwqabVDakfDulzgG0smWwds3I7JXgr8qJLm8PmI/+3fjTky84R2SLWlIOTOsXZk1vyYyfUEX8phWAnEbZd4MkIppMn4HtlWSKM8I5gXUMIZ9woJVhjcLTaZTF/Su97C2sxgejVU+YJE5i5CwWE8ruEHpxhrHXqFGfornfymTt/LcCtacp3Lk/evONYz6IsTZk4aV68y00S2FpDZajJeapxNHmMGCZT7Pt7lNb/7B/+WDcdgktqgMHGZb9iUUmWKBZF+/5xVKiKc7VHekHH8j0i9lkTqzImNI6hk2XJDPki+Im3usBkeML2bZdBLoe9V8C/nCLGAtJgw3qsgf9zjx+/9EzbNiM03H9BaVClnS2THHVaBRfZGwGPLxx1bsKoga8eMohnF4ibh8wRB3yK9lcI3r0gmXzFa1ahkF/RXEUt0tMIua7rPzVKPKCXwlhdSCFaoZFmWsyijU7ZrU9rdAjVvwbLjMTcUkmbMvh0xPF6nn4xJLZYoyx6GeYOxJpOelphLK7YnAquuw95GhdVtgWDq0vrRCU/Hc8R5RH7URlwT6I5HaFPwhgVWxQirtyJYD9GjKsobZeSgiXPYxb0/xSkm8F5WCPIa1HSSgwvWZm9wNroieG9Oy52w+NZ9ivoG27shZl/jbHSNbRbxDh/x4z8+wzvIMP1Q4OaPTygVTXobFonBjLA+58EzjR3d4IdFHw7/bP6+ECIg6DLBlkrBzTKUGgQ9n1xaRld0nngLtN08wUWZw945O4qMl7jP6OoCaz3FbiXH5WjF0kkyFVQK7QnPp4/Z3tOp9WC53KOS63JZ0rhrSHTWBvRO4Gv3Yk57aVpVjRuLAYqT5uVakvnojHXbon9pkM45LIyIxkkHY3HJni1wu7DLdv6SQ3FObVPmynGY2T1WqSpG0qP8IoFUi8klBcZjCz2jEAmHuHKSmpZAtvMIR1fsb+u80NKEWsxGocdPtQpaWuauImK0NojSl7SKm6wpNlVf4nh1zXaiSL/RJ4zWEQSVR+qE/fUexyMLs2zRcnR0MUlupeElXFxjzm7s0x9lSZh73IunPBLnhJkQ6PH029+hNNrEy/TYtH1OUiF3vE02hAHzZp1TpcdblXUWkseLixF5vYRU3SY4t2n9bIj5IMd6uEHYaKDWL5kqS9xxgY+UNl9d2cj9OblMBjPbpDeU2CxeMm3W+eH7/5b/1S8rbLCPVIlB1BkoGt3mOcttk+3yCLGVwJkd4GrHJOYdcvkKA9JI5U/pKLuYvQxvFya8Mj3Sp3XKuYBEbYC1WDHPb7KaNHnhRVTOV5jpOf2L5yRvZigOJXZyFsfJCuVXHteZY5qmRVjIYzxRUdw2rlAjk4ypV/u0SxKJkzRC1CWry2xWNRx7zrPvfszpAhKFBAsHMqJGL+pT7ifZ1Fa8nEro6QAhMyeON7nhTThTliQGMpq2gRaestvLkTfKnCQ/ptKd0Rh1MeVD6HtMRga/+kuvs6l8jVJmxVCQeHhywQ/+9E/ZqN5g8PwF3jLLZd4jaJ1DKiDe2ODXbt7it/9wQN4QuJhWKVVmyImQ5+3l5/L3hcgJhGKA7G2zZnlkdhKIhSoDccK6laG2mceZnrEtiKic8qIfcfLRM8qjKy66A8S8yMFenVRtyg1BICeEZJJJapKOcjbjVPiYzo5Pbu6QeVUlea1yUB8y7Uc4Ow3ioUTPLTAYaOxbBmMBRE1GUV1sa8VsWCZdn2JNdwl8i2LX5OpZg3/6X/02/UmHa1kn5aT4cnxN1k0hl2AZOKjRAnnSZ/Gqy7RTxhLKqMwItq5Qtj0OgwXV9ByCKS0xwZ2XOVLzCStxSqzP2d2WOQhdjEgiHHskzREzv4GuGySVGVvGBvXDPZK+RD4bYbo+VSuBOZfwFgp1Y4+t5hZK0UR8QyHWFnQliWLHZCmpfP///AeMny9J5lX6wKet99j21zAe7GMYOv7wT9iolhjPXTa3TJ4NruncXGe0aDK+t8K1dIrZCVOnya8UNpgbLdKvpYjLMl/NqfRO3+N2ssC3HjygoN4mOJ7irdZZrvn4FyN+8K/eI9ZCirpBWdfYSXhU3Arax31On68zT0C6oLHN1xlGGj4ScqZPzUmx3+9Q3xwzzmUpJuu8VrVQUagbu5TKb/CmtoDxghsnMrINepSiqN2i6phkMwkYN9m5GjBPV0gGB3xpXGKto9Cu2li5t1gJKc6iPK+uJPqaj373iurOiN/95N/xg8slP2v+EPvigh1rSWVyQSlqcGNjQXA7oKuuuCz6yEQkFJt8G6qixMgs4wsTfP0ScdGlsqHhBgaNZ4+RErdo/PshzcG79Aa/xDu/8nf5W7/xBte1HL/9e/+W3336ineXA07P/pgbqSadxc/5+acP8Scx4pXHJLfP2to2FTPJzmaRej2BWk5xcH9E+utJKIvsp/7/VGPwf6wQhZhJtUFiFqC4KpNoijNdMM4JFFsmQrPAsOgiVyq0kjLj0GUZmSRG8PHJnKrjsXB6lHWHW7kaycobvHzVwd+ISFp9pKMNpHSDY+8RZtrDaIgohRzJoslZOkB8MWIjajC72KEUptHCMkK+heApmPKA1mOV6vo1cn6JqHhoxzr3vnaHuSViGq9I5WWi5QrdPWG5LBArBk+mXUphiVQyjSQ6BDbkqhb0FTr6jHllRqph4hU9pBaspEvulKqMXvbIZ2Oe2UOSmkWq2eNqZ0yJJItBjlifkXI3yScXSBvXOMs8zFXEjE69J3I1F6nkQHUTzNY1kNPohx7LchbBnGKUTZSTn7JqBpSSKc5TC6JFF2FV5nV9k2n9NZ4urkkofbyNb/J60+LiwzNeV0ySLy9IRioL0Uc3VVRB5I3MrzJSn+Iv9hg/bFBV1xl2VTJbRSrZKno1x6y5YJz8lNFmkm23xOH5lKuL59ydHZHf/Iuc5gesiQ67d1Vwvkl6IiGY14wnI04mMQgik80V+UUW24euJZHyE+zPXTxbwLF7FHcFLsMVJUNGO3Lhls7Gdgr7Yw2zksRz1lBOPkbZXKEW69SzKbZcuI7zXMUqW7NLfNHC5JjMhsSouwJRwPhEI9y+gz//mFVDxr0+ZK4luJmzEIR9UlkfLy/SURvI8zx6lCNSFOTMJYvYRkKjYV1RXhVRogRvSWW69SW3nPs8dy/Qkn0WswodYcWvffU/5eRhj4tnDosSPLr49/TCFzz/ozFykGPztsnZhx7qtyyUVZ57v1Hg/VQX8zTH1tdvspNT8Mw8i0IGp5+id2JRtww6D0oknOTn8/c/IeufG5KgYJ15DJcBVrvKTrDNvrZHvqwx34hJ3dhkEc9Rwzts2kW2JlvUamvoJYn65YiT8TmEUz46izkbw09ffMDRi0M8YYWlf4lEe8ngmcpl1+UilWSavY3rBciTMbnrBSnZZaFZSOIF7lKmk/bxzQLdaIGUnCHqJeyowKOWxqeezzSv8aXyDcIXea79KlehSjhIM9dvgLFkqcbUfZG0lUJSBRytSlE/YyKpZGKBih+TUTeYJ/NEnTrLVI5UZYirLrHLY7yVxFut1/F7MZlUm1GvwHSicddbcXMM9V6XMJvgzksdcbFkuRcyjjr0Ni1UCxaZS8zxkoNOgP2pzfqyya42RO0MiQcPefmPn6IqPmHQo94cUBqUyK+v87wYc9sQka76RPm3yXsh3k0BM/JZr++RTmscO12SFxl4K03nXOSx9wK9EvNWYoerqy6CbRBsaCSzm/TyKw6DmKloY7AGzSyj8QmT0hzzSuCjf/ldjj76LjYO8rVEYbFgJ5gj51pE4msc3FVYM0N2kglSZzF6/oyoIHJAFicboYwNpOmMMJXkshOwWFqwEJipcxJXNXpc8DRo0lAdnPorLsodbL2PV1ERZkuOjTN6iyHlsEEsGRx4MYYt8cZTidtXS+6oc/I3RQxziZqq8Vf+1l/F2zDYe1tjqLpcnUz59KjF6OwJZvo+mwWTxYbDXm2CqQTYZoLEzCExUZFDiQND5N2rFZ3+nD8ZPye5qiGnvsG+OSHC59XPf8p3fvKvee/lt3n3gz9kGmVY9WwEJSRRCvhado9VLUnu8g4H+7e4Wy3yTuYGYXRBvFpDXHuHIC7grRaUc5cI9gKnPsDotBjMJ5/L3xdCBCIf8tImfqaAmYhJNqeszBlRy2RLr5AKkmiDmMHDCzKuR7Tr4VyrJBab5De/xp1BgD71KYVznLnPK++QfrnDxWMXpS9xlrapTkRu7b+Bl81wqr2gxQn2LGbdGKNZCl4mCdMRuiowTq0QjQLr0gNGcpVEcIydhoVVJzUW0PImV7eSyLUa1ocy1iTkRE4xP24SrJcpb41Ze5AHyybh+ZjijEwqRzG06VSK+Omb+FJEcq3PrRszspURU3UDR8iwl/gaM6oI+RIFqUQgGOwmfDaS99DzD8CIUXUBXx0y39Iojqvkh1lev7LwH4bk5Qy1VRpLyHMpTzHKKsN33oJMGjna5l/9k8dcFAeExjnpeM5cnHFHTfKtwi02Y5HH04+o3qgz7oaUFI3j80OMrQxPBw3i0VdRu+sEpoBoa9RvFzj88D0m9gbqywG/cfcWD/3npBIXrPcUJkdrTL/zXTRxyu5rm2TdmMGFz69qRUQlyQ8Cm3/w7d9C7s0QX6thXyXoyQLhZJ14JdNbHHCwoUFlyB0rg5lNkkEh1RGpR3OmpQvaC4lZx6AcTFFXDtHUJ0xsEFsT4m6KxHaO1dmC7guJ4RbM5LfpD5e8fz3gmZvHNAKoCWTvLmnnFrzKxrSUPMkbOkZXQbpWmZy1mHgeSrvBVrrEcrhDqnYLt6gQeH2mG9/kL/1almhLpTrt0Hy1JBIkEoM6i6oOS49hasDZYImodEmKb5ARBbzyK5zhe/Ttj7nyZ3SusniWxZq04PjlgIVc5emgQmmvSv5mBevuG8z8OzSqaTZv3MVG597Wt7DezJBbX1Ic+0RxTJE9PG2XakrBaE8YeT7F/P3P5e8LsR0g1knORfKizYVzile1GI+L1K99sjHYKYe8FhNJd2lszTFP5oR7Nn43QTtYstLrbGVcRquQ/Hyd/daS4T2bftBnaE9Rx8f0ExnU7jE3vRW+VEJ/W8c92eDVVZc9L8tJZsCJ3COzLvI1V6egNTlzIgbDOZ6fpj6TKMQGY2FMplIgbwu4uVcUs2k0DFJKiF7IsLiwWTk5GvGUxHRKNnWPYNymtT2FQKYsGriyQ368jhmdMQ5UKkEZJ5owXnUo1WVyiQz95QdUcyGl+pfJSBNG0z653A52R2eo7bLvT0ipOZ4VEpTnTYxcla73If2whBnUSe9JbExEhEDD5QLHTvLy4pKB6yBdeySSOVoT0P0Wxb/6TRLFt9CUEcveAl+Er+wIzPuXdFY58osMX85kaKbbxGkVZX6N2KmT2dW48espQt/h9p0Drh2V7cMXKLMGWr1KreDTGe9yv1ynsxjx9HJAwtukX6yx2HdJj1X6wStOP/4Re8Uag4zEzbU+rXiJfilw1FARdluUFhVkPc2GJvFKaRDuqmy7GUZyGlkKiIVPGU5rROGC+t0SUyegMU6gKiKpkwFSXqE7XpD5pIZsLmlv7lBae0boj5jKc1bPl9SWIpXyPfRWEfX1Y8zxA0ZKE7kQcbHMkJlLJHfuUBR+l5X8jFuFNI2TBV5oYIpPefe793BWeXKzEZ4+o6+XUTnFmaTw7QDlukY3H7KrrxiJY/r2BVqjTKSE5KVNHDGmnx6wmEY8RqX82h2+9ksyD/94gpwv89WiQb2yy8E3K0jzCVagYVoLMoUT/trKQk5MyN1dch3MsOMh7ecT7HnE3/mVX0NVTe5uxfzOD//dn4nfn6fQqA78BNA+G/9bcRz/7wRB2Ab+DZAHPgH+8ziOPUEQNH5hW/YmMAT+dhzHF/+hOUR/wYXxIdmlRhQnke0U+XDBZmHJs9Q6wtlTNqw7WDdWnNkK24MDDK/DouRyYS8Q112CIVj1EdqmxTxyYdZmYzNFtq3z81aarBBiSQPOzo45SancH8d4iSSG5HAazigFbTYMi7ECL65mbPYTGLubbNodpLnCVHbQ+xFC7pRkmOJ6L8ToC0jCkMnChqJBQryGWESzkuyP7nBkNekZLjuWzDjaptgdocjXTHyNqqViVRIIU4VFYUD1LMnNrMSlvmLPCFEkHXSfnCywXGjoworRiyekljM2kybSjQziTOe1ooDdGROsHJLFMrFf583FkjCUGd4Y4D0JyLsTznttht/5CF1yMMMlw5FNX9II8wW86RWb2Q38usz1xXPeemMXJ7XN0ccf8XpRI5F0YK1L4rBJce8dxj4Mrs84ML9EOvGf8+LkCcYti1nnnNR6QL7lUfmNJPOTJcqtIel1hY/+FYg7eUJlzES/YPapQXYrQhNFPvn9h2zfW2fNuIfzJMSQjpntBRTGd+DQJd6bMl/6TPwAZbxDqT3m1aaCnVywc1Bi8HSTcShRLOUY+j4ZWeTtLZ0jWyZ7KyKVL5GbLVlMfdTRnEIQE+Yr7I9UpGkJTS6Tzi4ZeXMq6QsmTop0QSbUqliDFcaijX+jiH54xOFSYB75/OjnbX6ptMXP3FfMBIF00WJxPWO4K+L3M9TSOh03g7UcgJahtDhmYimMRxu4zoS1VZ6F4lO+Z/D0dIldkrid8MhOSkycmP/Ztza5G2R4LJXRZzLxX3rAVIzxO8+wdmqUUxJl5TYngUz7WUhqINJJl1Dd52zXbpIJJ1wVfsLcOaaffo107/zz+fuPiQDgAr8Sx/ED4DXg1wRB+DLwv+cXNmR7wJhfeA/y2XX8Wf//8bNx/8GIkHEWIc1CgZlps8itUBM+z5wlUdjgyj1hpc+ZjQ1iq8Eyc8Zxas6RK7O0KhSEAs8XBmXhDc7sBPVdnUlUYUdP0cm/xXzpIaQ3WN8pYhTe5g2jhh2UcLwpujPCSfSxowLXURq538TMZWjf3MJYSSRnKZJak3w6gREv2W7cpzgqkB4HKJJLTTeRzDUG/TbKZZVrO0fjUY+L5mNotsj4rwiXEgV5AZHMcSIgrzl0Cg5ryRXapsRBO0OyaFLfgRtxHscLeStbQXSLXByekWlPcOcLJlIPY30brWIgXPURpDapIRSKNeyDAnfGEb/qBSzFKaL3CYookHpwE0Go8c///j/gw0wHsxwyXaty5qa5pxX5tW/cxpJ93p8fMki8oJjKUkiZTA+/z13TREmP+LWv3OXwe5ckbn+dwYlEMghJR12GUYGz3jnppcgfvTxkvZBCDkbIr8m8+ulDbM8jHN5En9zGW7X45S2f3Vt1/NBB7rfJnTzj7qKIviHzL//Vv+VVOOEyZRMl16lufh0tFSPpW6i6TxoJ68JECWzGZgbRHrJmSrRWEUMrRBL7FISASdcnaDnMOm3Cx885frLi6nmXReSh3JEI6yE+ERUnzWYyIp86596DGdPqAOvGgsqdXQplEy33hBfv/rd0M4ck1UuC4DluJSSfmyMPXSLB53g5IZTXWaeC96iNduFgrULGvsN1q8lq1mUWhGhyyHVeZ1b2EaIlB1ZISogoJQK8RQLRHrOrHaBfV6kcJNkxRNaLRZaZBGJS4EueT/56SvnqEqWaJpzMCZcmzV6Xo/ZzxuIJ1TDm6PwxP3o+wxdNOtqEmrnGkaIyHQ942G99Ln9/nkKjMbD4rKl89ouBXwH+s8/6/zvgvwT+W35hQ/Zfftb/W8DfFwRB+Ow9f3YoIo2xhGW5ZCddiqbB8yjkTuQyfVoh2y5RKMJAmdO/cJHlJPY8SaWisrI9NoI2/Y09rt0ZhX4ZJTtCVVdofontmw7uI5Fg4TEi5EoeUrE3KKdGfJofkuzPqHYdPKWPXs6x8suMDZvNQGa6PAddoHSVJmq6PIokkpkOvlijpi5pXp5yrReprmnklDwvrt5l+olNY/qQ0wuVv/h3f430tUUvjNDn1wgribMffY/91/4WrmTQvs7QFi1aQZ+7ukHryOW48ZSkcknUqGFPVRa6x0DP0ezOUDYs4uyMxnhGMi1z4RmUVz7Pj2fs5jS0ZAYjGFG7kUG1fcTuJs5lxP/lT3/MfN4jmy9iD3uIiobYkZBUlfW1r5BOXJO0Q7ILhfKX7zCaxqjBBtWDXXS7yA+bR7QrWZKuh3xzSTCPqc6/wnDVQTBnJDdynD9vcxId4azpJOwqZ70rpLzDwetpzmdDWnfz5Go5bkkb9M//T3QPFkySVe7k8nzc1HCjDN//3u/w937jf858mUGZnTGy0oQEHPZcRMOgHg2QvRSvVn3iKIX1Mks1/QFaOclwuM6F5/NAWTGPy8jDc9yURGjNeHmssqcvmPl98tcSb37DouuOyF2s6F+0OVHKpCdthFNwCm1uhlkuCBmONPLDFSefnPLk298h7ensGyovA5U1zUCJAnzJ47QRIYgjCpsVXn3qsxu5xKbEY9UiMiJcJSLRs5mcJqini/jnGot1ibVkDru3Qr/a5OAdk0iM2HO3uMzE+IsbTJYnTLQ259U3UeVzepUkue/X0cUsRllg5JUwUtvsuB0uXqy4v3eDmTJAMvpMnwkM5h5Pxj/jdkNAuvr8gt9/XvMRiV8s+feA/wY4BSZxHP/3XyX8D63G1oDGZwISCIIw5RdbhsHnvd8PHFpWD45GGI6NWpuQSmaYBCqp3iGnpYiT2GXqKtiXaa5vumy4abzIwInhNGeQc59w3Uyimtuo4gaS5NAfbrIyRTpJKPorrsdFAnPGPPGUsCORGy+hvMfSHRDGApuzBMvFCDO0UOxLxsGUs7GEmdZxyhFBJwRJY6KaiIFOsL7DcHWIPDfxVy7D00suP1YoH1Q42XT5x7/3rxDZRUoZpLxjdrVv0J+tSH+zRH11Sip/H8NwcdbLDJ5GFFMxK9Wnor5BoGdI15fkZ1k+SM+5eeGRXtMJ7Szmao3V9YQoXNFNOdQPYrRUmXtSwMdXPsbhmEwlj2C2+f7omtNnT3gtu8HjqyW7S4tOqcRQeULv9h3aZz7pWpnhwMdxfMx4yMAzuHByCIpHam2K/gOB/+Sr32I1sHkhySTYovgVG+/8iNf21mi/6nPn3jaPLq5441d2mJ2UmZsOFWmddT/Le70nfI0cyX2Zh/1DMssShUjCWJq8f/kxQnGTVGWJ99Eml7VXvPHrIfZEoTIMmS4TiJbPs/ExbTNNqegi+30iRaYrL9kZ3+HMvaKcuWbm5elftYm3L9HT6+xoEqrX46fVJsfpLqlpESWR4umFhC/p/ES65o1UDWsQsFJcRH2b02mfeU9mjQKBnCe7qlI9iBiEV1yfPqM/1CnNXNRNgZVloAxcdjSHqaPRcFdUqgqn9oBMv0S6aGCIMJhdUMqZmPYIV44Z1i2W8z7x1hoHG29wbrR5KQp8bUuh8eglxtShEtyi4xpc9PIcRCZoSbqDEsbiU0LfQx0kWbkFUrrMv3NkKtac+avHdJ49xtcKWD2HRGHJl8+3acuHRGtF6F//mfz9uU4H4jgO4zh+jV+4CX0JOPjz/O8/FIIg/K8FQfhYEISPozgk707JH6RQc2vMFyNmZ2NWH/Q5ki/x7Ate2Cf0Rx3Kezr545Dm0yOen3p40oyL0yyhvcWXN6sE5kOmwQBtHLASMswudKSCRsOArdjGtxWuh1nyb5sE2TrBrICbi7E1ieHcR9EkTjsrLvMydmfBSpgReUnklUcuE1EppPETXWLVZ6Oc4bb+BsNRDTvYITmOuVp8yHtHPu2nMt7TDEcvOpw8fsH18wbJesSVI9OSfL5R3GS83YRhiwfDLtlVB8vSuLWVQF83EF932Vyb0M0+Yy32SGXXmL1K4npLwq0WWtnE2BuxEluI8wJHnSk/m8X0sxaivsSc9Bg8v+LHv/9/o7BX4UnwgMaVy4UX0r4649abN3ltu4bovURLiETyEX0nRd/xiXMas+Il+jTk5Eef4O316Z2+InNnSuXRkO3ZnF1lwf76TZb/YsJGIUvbb1La2KYz+JTU6BTjFPJiyHzxisTaGC8X4HKDzvSI3EGaSLFoKXnOiykGAw3dr1HYWuNHv/UDxscOQdKgW3AQv+KQ2LQ4qGusBZukBB1r8wZbxTo7SZ+lNWDHD3BSGmZBREqW8FjHKeWZ91wu7RVpIvR5hVGxiBtkSL5acH3cQZnrPCzAR82nXI5tGt0h1mjFtFplWuiSCQ/RVm3yI1hmJ7TtgLCgYFZEotgkHcfo0wT99oq5MkQ56zO3dNLROn4hS2o8J+N73I9K3BjtQFxhFWyyqWeRxxFZ9TbiMEO4SHLLHjF2bYLUEmc9xaIQsaULFG/cZjppU57dIz+d4WLwvH/Mh0dzzg9/zOzHP2c0e4LsfUT37GPmQhdpdMWj1Rnfu35FlBXI3nube7c//3Tg/6MjwjiOJ8APga8AGUEQ/vuVxP/Qauz/ZUP22fM0v0gQ/r+/6x/GcfxWHMdvSbLCzNSYdwc4E5fOIEEmivA2pqTWdsh6JWq6RTg/ITr6kGDSwgiWTC4+wDtpEaVUpJXM6dJhurII1BXt2wtOFhM8v0nv/TFBp4BWyJMs5dgQAnxljXw5wMtOqBsp7ukJ5FKEZBvooYB2msPwyuQjDanSoRn7XMYBPSOPcJHm3Q+e0/30EuPZivtGljfubTGb+kSCgBZ0qUQ6mUSL3eyUN8t9yGXon55h5ha0r5d0jCG1UYZcOUtnkOSqss2xkkKM7qPFZcqig3cqkkius1afMa+UWd7JYAYCw0mOcSUmqGbZz4OxN+NNMYMueGwGhyzTLmNJ5L/+nX/OigIdc0TSGnEn08fSYT2Iyb/+OmJ5SLoi8MxV+dK9G9R3IybDNilPpZiuEvZeEusWoiDRz7eJP5EYz33G+pjGqwm3qnlGOY94KDHMuPjJLgxjnvVGrH/9NrZ8wvdP5oTLJWLNpNf6Ibu1e6TEA9atDcLGkrS/gsQFhbHPOLpErUj8g9/8RwyPprjOECV4iD2ok3BKpNUZYeCTmp6TCA1yVoWzokd/rY5qJ4jjNl2hyGycJnVygSiPcAo5lgcm6aFF5eU1Z9lLLpQVtyYymcBgmRqzb/l8//sf8NEHn7Ayq5xEn3JtCijLS7L5Oat3khivFlRzr3OrWsTZLmKUsiR9n4oQkPWyvJMuUslZGP6SwFlgeCP8ssdQ7eJsawRVF9maUdmasGsvyVYtMizpGKdoAxvVSFBtWpQXAcog4sW5wfcHDrP2c1pDnR89/wkPzx5yEZwiKhIv+i2OXn7KH336knYQcGxLnPYVtP07DHYyKAcqka7iZLL8xr37HJQ/n+v/qAgIglAUBCHz2b0BfAt4+ZkY/C8+G/ZfAL//2f0ffNbms+c/+A/mAwBNVMkJVXRNJpuZo6UchpZKb1ZkZS4wxAesQhPkTUJDIMEOo36IHC4wAgeh/YK2/5B59+cMvT7HPYntxpyB8Jhpfox4c0pBG3OmtAkWZ6xiFX+ao5HJ4EY2oVnhXPOQVjn8kgXpKel7C8bVkEVocGSrlL08WlhAvXAZdlw++a3v8Nu/8zt8Ovp9Tj95zOrhEQ+Fa6YbJRKmwFK36ckN/EjhqrGOFhlc6QHqyuf+3TmNkYUmCDi5LBlzQmUxINteku22ORo3eDYImdUcCpJPWnxA0liwlprRUVx816Y4iLhzbVMSXDaXGvFEotfp4wQ3MDSFP3j8XeLehPF0yWLWZLZ6yZkroOTXyL1zC6Ufokgm8o0st1jCjQyZ/pwlWVZXF6wlK1zMUqT1OnrT452hwcnwksJfUul1uwxCuHJOeeuv7vOnwStuOgmUoEDyKoWvbVI3bZw4JLFnElQN6nIVfzVgb03BejNkZ01nuzzhDptkUiketxJoM5/+4wG+LXF88hNUMY84uU2gm+QyEq7SR9YvcB2V4qRDJGp8yR6TzHYxUhJ2sk6lOEYpthDlKp3FLhtChBN5JFSP1A2LILmJ5tZ4sSPgbczZWSQYCnVu3LPI1g/hYk55O8mWVSJcVmgHWWbHj7lenpHMPmWYb5PP2wjJApl6EbccMFlfobKNtZ2kLAes7DlmbFNNb+Cssrj9mGV+RWGs07fzBA8OmK9EQjdge+Vxp7bGpLRAv5fm5/4cK29y0fiAT94/pptK4MgvefTyJ/zWd7/LB60hQ2dA+9H3ed5v4gomwkjg6tGQ1FLh7drr/L3/5K9zf+MrbCbu8ezsBf+HP/pHPHn38wuN/nlyAlXgv/ssLyACvxnH8bcFQXgB/BtBEP5r4CG/8Cvks+u/FAThBBgBf+c/NoHj22i2jLLlEXUNFBlumuss1StWLYl4MsPemFOXPcLrNezXOmhSnqWYZ+w2Cfw6dLOMHjykO7hGnmgMG1WK8RnLwgZumME1Dyn3fgXvcsbWlszUek76QkK93iGULtClEG3LIBMruAuVc3/MhqGTETysMI+WmWO5LkouhW0qSPU1VucBn9w5Z/b0FcXGmxjdJdmUj72voixnDL6nUXWmTF/zCDWdbP8V3rjMkRNiCD0aVznqlZeMzQm+UWfVbNA/vElwq491FSHJCc73x5ipNuUmNE47qFmFrOlg9yxSvkkr5yGWE/TrS+KTGSPfpvUnZ3z84Ucc3DtgPpCYPB0iGr/48OqF5fCl0l9AfPwx0utfo3nlImpz1LaFkKyiKQGrjMBw3kXYL6I4zxmW7zB6esKb9QqOLqLtyDy05zxYrdPXjnldyKKkDXb6MJTzvJ4SOJn5HExNVsElsVrn2ckFpWKR0WjO5sLip1KLZPYuOD5RcZuAF5xRYOcb99hMbdH+6DFG9ATt9rdIbaVZSDrF1inJYpKOWKBTGZAgwDW3yF/MWERTtvUNrgwPabRiMLcQwwknoyylRg7WZwyDALt/jrUNmlTBcQXW9TkvBZ2snaSxZXOunnD7+JdoDI84brf5CzWR7/7pEVdOjTcUnZJj08/oVNcl1Oltxo8+wkmM8QOF6VWHjFomY7qM1DI1FHLLEYZosS/d4KPdOW9t+rQaV9xIf5NtY5Ow3SCZnaCOM3zy7Ajn1KK528SOrum+GuMndS4GHaxRkn37gFypw9myj7L0OHi9Rnlrn+Gffpf8psFa3uX46vf56Q8FWrrD7FrH201gTSd8vxh9Ln//0ZVAHMdP4jh+PY7j+3Ec343j+L/6rP8sjuMvxXG8F8fx34zj2P2s3/msvffZ87P/6Bx+hNM5YvpIR7MFpokCR9MLVrpGMn+bwb5ETZoS5wyWX4o5J2JenaK2Qy6WEitpSLm2QnpVJTUqIpRmZFWfgixiR10qqxxdUeFxq4EaS1yNA+ZHDvN5zETvsQxCokSG/GEW48wjIZfYHd1msrSxYpOxpHLuaqypE9RxE9+eM52eUYyOSDyDe1mf/uKclJdlwSnTjwSc6xI7u0XGu1PyY42uOGdkVOiM8rS//wnF7BwtbLFy4QMhycnzLnEygX9nRrms04tCJltjMi8khodLjlZNLCfBdrOE8TBGGzS52vHpW3kyFzrm1YraUKErNfhnf/ib6G9UuJw/wvKmdOcBT+WYejrmNWmbTSFmb+8OGTXDX1xPonkR7Z8MuT1N86Xqgr3SitCbUV4zWThpBmOdV+kBrZs5Hj1bUNU2WR/7XL434iKqcDNV58mzJSsvInFPIswH+O8f40/2WAQHIEwpr0PfybNUNnlZSFH/9V8hXYsJvRlx8wWDxpyWNCWwGlw+fsLFyODb//qnzC+fYLTPWXWbuOUA35ljpQXsURJdGDMdXWGvICH1mVwPuBmHbGk5nNJT9vbb3NyqkLolo4giatKnKFgovktiCfuyyjRaJ7N4xK3Y4atLlXfGNUqxy2XcJqoK/Ozbf8L77oj8VhU1W2A1eYDbksk0ZjiOg765T6F8k3KtQCJZpPNiwDyrkNMWSDeKaJsF6vc2aGwOKe9skN1JIGszvvrXFOTZj7nSnmCrMd1Oi/effoLTW/LwbMjx8wGaoEL3BV7TwNJmWN/6EuOVijfdYGv7VxhJAY6hQ1LiSpphunP670qcHcU4C5dAaJHoPKZcEpAuL/+/F4H/KUIyIoKKgqxkWIlJFq0hTlLBdaecP3nF4HDEq27EsR0wm2mELYXEXGdYc9i7YZEMalybSeRERFnPkRwoZJQO84yFnixzr2xx0z2g2AwJtgTk8hh5bKCvQiw5JJmcoNdyNMSA5DdLOAqYgCmMyE9mvGVNMOWAq8skxb1tfDViLZlnnl8xbvR48UzGdWeID5bcu/UXMW4peO6Mtj+AZArHn2M8z+O2umjCGZ+s2hhNSOgyk5VI5mmAl+xznBoQyVXCDx0qVyLhcx23G6CPx6yGAbHeYJg9xSs7dPID8p0+tn3Ex+M/wi+9y/lti9Pf/7+Syq+h9BfU/Rx9KQVaH2MRs2q9y0biiuLuhPqdFlp3gBrHKPINZmsirdKE1c3bDM9ybCCRtWK+tJFjXXyXb978ZYTwin29Q2ECG1aGf378J9BrcSWH7O5V6XY/oiJuo2bAzajY5R5bFXj5cM6F5SB2LqDZZmOeQbke4WfSPJIvyExKpB6A0Tlh+QcDpgmwx7C00jwafI+R/Ix59xpVSjEXNxg9GdAyNRqJGRuFJMJ8ziJTxZQDOmZMprBiL11lsaoSnE8w1SyiJGM4VdJiks7QQF9qTEWH6iBNJ1Rob7zOXKsy8k/x1TkdyUazNN7rvELtCQiXTaZnMev3S6zfdsm+4SFsT1m3bCZzGGoGWdXizrfeIVEpcuOXHlBS0vza3/sq4eYWuYscdxT46GcvePkwx3vf+4jvP3zOsLuk2/iU6PJ9/sZ2gTEdVOcMKHLrK3uUZwk2d3XitTqD4YfE6RjZnNFnykJO0frZd1hduJhWmgYpUvkdqnWT3bRKZqeMYuloqzTK9Av+KXHsw/I6RtlJsXqgEBRCvPwBnaVAbCWQSiMEt4JKQKXnkh6MmWsD9JVOa5UglylRCscIUYp1JUkxDBDkTczlOltKgqPUivHGkFDRKF6LOJ5IYnvEDdHhm6kuxi0J+6xFxTjm+PFzWuIMzzsl6Xp4ssK8pnO/eo8qLuQDdsw+mc1d9m7eZfh2AiNRRBXhyTNodroYdhI/tyKTTGINllhujL4RsT5qIydnKNdNTk5Mhn6OYJ7DMHzK8m3C+TrxaEy8I2F8RaLpJxlvGGwXcmxuqkynCq1JyKvOisWJznlUYxKGFBcZpOk7fPKDn2JjUqobjKceD191OT+8JJurcvfrsLv9gNk0YHEhEC9qhIVzLsZjYiTeVAbM2wJT/5zEA5u7Qprw3QWdM4VKVEZw5xQuttHCm5y7Z7zfb7Fow+lPf4iW6XKLBpWiwXS2xOu1uBN6eILNC9Om/JrJ5khi7e0dQlyS4SURLkL7hL+y+XVSdYddaZdK9g2GuSXx7ITVnkzta0ku+nO+9ydduBGTtuZUXIdScZ+1ywWjT3MEH2cIeirN8zHZmUjlOsX8cAHDMpakoIUetxcNKmOdlWKjrZnINzJUM3Nix0BLNtkb1YnGC3ynTr/0IYvdJoP3W5hdg1zNQk1pSLu3ydbyBK6CPEmwSP7Ci0CpX7Gl6dQKCcqlWxTqOd44eBOvUWDxo3NmP41p/vYzZtce7w+esWuZTL0jDp91qLxVZWIUsVN7KNtfZmd7H8dV2cjn2Rg0+ehMZhwPOX3VJS71Ud0SemtOxnepii2qwZJaZg+7bJJrVmifNPhE/xAsFT8wSB4n2MnfZ3i+Tzb3+fXFvhAi4LkCC1fl+vEF6WOJPVGg7LVwnBXevM1GRmV/fUyUCnCHF6irBMFRFifyWet7NK5/zmqssJLnXA+bXKxcrmZzTpNt2ul1Cgd5sqKJg0/q9SVrap3ZLI9VKvMyrmGfFCmXZcyKx0RcUvWLUKgyS64zTcDFxYKzlsPYNnly2UHZfwN51EIbtahJ6wj3C9wuyry9tmRll5hOInQh5FCSCfUDNtffZJM5auUGu+UQf6Tw8bTJzGvSS7zAd1ucGo/RB1OG/hhRkJErPhumznwi8miYZTiuo+fX6d7UCbNjzLcypDdsDrwyeWOdnwyPuf7wBZNgwdpowHY9T1KCSDsm72e4drP0rQRvfP0BRjXDqe5zfuhTjXXcaECgv8muYOOdfYTv9+moNpp0yqX/ikFhi5PxMV6lwc/7z7nKzikls+znloiDK37wr7/NpaSwnctw8er36Hb2MasmoWozee7jjK8Q4w1C12Or/A2uw4jcROfmX/4Kb3z9ryOs5dEmE+LOEYm6grCmsiuppA9djMuQzvn7tI+fM5grPO9EnBb6hOVLSilYJGxSd0UErUsqvEbzLulqc8Zlm1WkoOQl2sM555kQbRITnffY7Cks4oBiVsUdCsTTV+SnUzKhA+03KX+6Tn/1mNZshf+qgeuesb9y+OWNHcQ4xVgVWDk6S7/F6aXMncprPG9PaDTbfPLpH/Cq9yPO3SMm48c8/fQJt/YTuEafxUjiZv0vUk0n2KwWKUo1eosl5qTFoHHFv3j3KVFGQJcsbCmiev6cjCCTMQtknuW5+0aBcV3DKju8enHBk5+OWJkpLGXK0mygegr1SRqxq/OGViX1JZ9cvsjN0pBOqfG5/H0hREARBUxlhOX0iDNpzESB5mCB7sA4mNJrL5GuZVxVZ+qWmAdXlNeWWFGHqRAjTX1aEwdtECGUExQyfbbkLpE+JWN/Qv8np/TOr5hWLniZKCAbMbmlhy/pkPSYCZeYepYoqpMzDCb3AgrTEFHWiVYK+SOftHgKmsTE3cdaLvHXU1zWimyLKxx5Rk/LsWbeYX9yzcy5YvhqQWko4Q9afDq7oH82oHM2oBNvMpYDrgbHTLNgqgcs0zuo6jobpQXivsRZHDB5MmUr51LRq+wtTgndh0hmn8JKZMfYIrrwefWixaJrcZ284uM//l3cREDXjFj5PrPmDNFfIsVbTLSA0Yct6noJxDSsVakvc2iFHU49kzg/4u4dmdFrNs0ozaaiY6xVyZoVaosq8aTIvp/ik0dzngwUei9tEmaO6WJF4WvvID/rcP1bj2nP8qixRb93QeQFVJ8ZrGsq69GX2ZXG2FdLZuKMmzmd7Fxmz7vDq8Mj7lwFXHVKFIpfIZf9FeQXEz7++Jqh6lOzBObjIj/904fEfoHEzQl7hoduQBT79NyA9tWSvL/Fd08lLs0OgSzS6nukxZCPpkOudxVUYQJOgCmn8COVOJsgvRI49UQUwaTv20iRSHWq0xwFKO2IWq2PvoqJT5J05xPOWy94cvbvmbkF3I88zFaPqDfhovkJW0KMJHZR+gW4dimt32a4mUdQTZJFGfyA8izHR+89Y3zpYw0XjD8psTYO6Ps6GaHIN375dWpSRHcpM5Dg4C/dZlTMEBhLDp0z3n1/iN4XWXRWRMYaeuBw/uwTJEVmWZmy0h1K6w77r4sotRRW74Jea4JXMSk7Dz6Xvy+ECMgqhJaAkPMYLk6x22BIIpYtUXVFgpxAK+dQaPaYqQHLdEB/Dla+xtIe4eGj69ckUgZz44pQD7ESW3jzKsO+QBjoTByQlS3044jzxhhbGXFlTGgbHTKZXxTlaAcvcXsJdmOZy82IdLJIJuEhpNr41yK9jRCxEHD43Ob0B2O8xxFNLcdCkDH6JsOyjbhbYqO+zloJdveSuBkPUWoSGbvEVQ/tWRPnaox93SEY+Fw8PuH08hHjjwV6z3Wco2vmi5B+kKJzNEPjkFw8ptPZYthrEfUecak2uC6YJFYRmjXn+7/9R3xpvUqqayI/G/DCNjkbXiKre+Tf8FjfMSh/7T5nnoOXVsmcjXHTI+5t+BTXVwjeBqvBFQtHppjLcXzSocWS6aJC9SvrlCbP0F2DH/3Jp+QDmVRhm0TZRt6psV7dIfxbt3k3/5JXozPqyha3Ngw8acXs/pCJcYbhWfSXbbqVOr4SkViJyHeqiKtzpsOXTDMuZS6YhjBttInL21ipC8L4gmbscWfN5yvCbd7/nT+k2g4ZiVeUn/QQL3RCp8pI2sTrJtHiPrZZIJHaZ0N/zmI0JV1xyDY0hIaGvlxw3J/TXZxiDBycoUGq0mK6XiByfaL5gsXOGKMuEeUUekf7POWA5Ws5hPUFTd1mlBgSmYcsdyd4pTvMd5OMRiNS0jVpPUGkQf5Epznu4Usp0ttZPrkOGfseSs6m8KUsvi7yPJPlVi3C1HXklcJHyks65z9lIkksEg6uHvEn756jCT6OOGbhujy++gBneo5Wtij7Dou4x1xIkhL3SFwnEOOQZtfgMnCZZlfIWhrRCDlMXIP9/9sR4f/o4UVQCtNM/ABdNFgudBKhzyIZMZvJlK4thpUumQuLjNBmZqRBmRN7KzzfRczYaEqFUX1Fv6uiLCTUwgpLGNG8DCjpsK4F6HTpTQPyssJK2kQYhyT1HdxFH1ceMHN8UvkJ41cWlbe2Ga4WNMcjMuUaA8VEkEVS/StuG7uo5TZeLNMaLomliM70kGB+GzGwKYgpwtmA40GOXTNJMTvnVJsjBgrN6iWr4Qb7mRLV5AihHpFYv09SipCuHDQtzw1dR3ZsxtactBMyrE3ZyV3gNtNkUj5GJ81Hi4BVvsqP3zvipPuc+OlbJG9rVBYRVxcuKz8mGseonTQl6zblb9zidnaJc3WJfZkgvbuFYp9ymTUoiS+gYZIf3SJXHDFf6SxHCsJbAcenTWQ3w79rjNFqr5OQVcpWiYuLDrRs5NjnjV+6SfF7K86fHlP8pRx3hCUfvnfBK3eJHKu0SiNu7+9z/p0fYr9RR7t9l61Y5/LjH/LlexEZ4zdIH/j86e9+B7MeMDJkqssKds9j9GaJ17Myjcfvw8UuT9/8kFu8znK7jr4USWXPmRtjEh2DqS5ha3kSnDKUbfLLmHqyAitIbsSsPB9ta0J+tsMoGiEXDDpeDW/7DL/hINZFnHyZwomF2Owi3H9BfbKD61hEiwSbu3Xm+QKn7/eI/Dnj5phcUiJ10+DTPZfu6UtS+HS3c+zFpxxGU2bpHK+ZN3goaLjtaybbS0obC3wly3daP6JsRyy1BM7hivcyI0wkRocBUQSj0CPUJdyMjmG3KcR5QrsEnTktPWbumRwAtnBIQdE41G22tjSyUZfSy/v0LR2xdUpW2SZITD6Xvy/ESkDwI7J+hCRmSA5d/KqJGw2ZeS6267BUbdZnJWK9AHrEwhZRrSQ5OYtgJVjlK0SBir6QUKUQ/Bh/BhvpKhkhy2oRYIkK85HOah4zFUQcb8zs7BXGeQCpgIe9JauNGnY+xXLNYB6tkOU2plRmsbRYZsboL/r0LiImozbS3EWWbOzbAXIxILthkkCjuTqnP7tCiDp4wYDZBCYXEuvaJYIvEp3uIXoeG2smapShuCox6elczy9pZHeJuyt6T4+Yd2IWUsCJleXliYK9SDO8keBlfp+eFFCwHOSxzXvf+xe8mUlTyk9R6iK2r5Pf2ubOwU3UQo7WySmnmYfsI7BwN5jNazwZNXlljfmHP3yJMJgziyRiK4XUOiPjLFky5vTqKcNpxOPHF/ybh/+axZPvoN01KNuvOHv6ihejQxbPe/z+9z+hchiRGG2T3FX49J/8G/6bf/iY55LNBw2JUSvB5Y8TPP2kw/zhFRcfXDFvTFlmZgzI00gW+GlKJKO7bG7K+GMbrTTCSupsJRSav3fOJ0cuYq1C+GCT97/z2zy5umJk5kitH+OMfWbPMsz7Q0w7jdO7RG/YLO0iQRFiZ8HSl5CSAXJ6zDsnGmlXY1erYS/f49YxbDROaUYRo4zExjVw75JNrc7W2W+QvliQb83Il2asAoveB0MuxjqnT0yicMyyf8KoOyLRt3k7v8ZGZZdEcsCLT6YYYzh59oT3Ru+SFDu0pj7vfvd9+tcygpfGLZjM90IKioxup6l1LdpRnVwiRvAdfnk9xZ6SoDSbU4x0zIROYt/EqoGUS3NgOci7Bndq9xD9GlmSSPNT3EUd/WaE0LAYZGvkNhPokfG5/H0hRCAWJZbynIzdxqyJpIQhurDC8nU2di3W7kFsLHHrAkJUIpUz8GohGiorpuRWS8axyKxdIhqUmBp5mhOH6zOThexSXU9zsSiQmPikVJF10SHwLhHMGC/zit5RjLQYkFvqrHe2eRAmuXUxQdDzeFFAdjWnOk+QUwrI39zkUEkzcF2ej5LsfBpR++mEZdci2htwb78ClTXc127x1fUM8Tcirkoep2ERN1tFrnTZsLYYR1Ou+zJHdFi3kxCVsCYvOfHWGFXTHJs+F92AWbRkeWuHi0zMuOOze+2iFCNqBZ/HP/pDHpTe5vTRihNBRD0+Yeha9F4ELAKRbiXg9u0D5vMpH4x/TjF1yGCnyEXW4A8++WPyk4gXH/0mzz79E97/9AdIZsyzFzr+sEMlVaG3kFCvrriRyXHv3m2qsy5zMUf7+pKpIaAWLZYvprz7/IR33t7hTuYmz3Sb0fgxfNpjzzpBL00R7/b5QeOHLNdjWs1XvPzg54TnT9j6ZY2yeptfDx1a7pyXQcgIh61nOvt6QO9lxM72gsW4zxPb5NPzBsaDtzi/yGJeKPTGAtGqQL0qs3SynCpt/PQVEztJagor0eGJC3Gii7e00U5SJNMRE6vJUWtB52yBv+GRCauk3BAaPZqNCxrtp/hGjabSZj4w2LBusGZ9i52dMopzg510kkJpgeFmkXsCcr5DPvwKT02Vy4FMs2FhFjUsTSBlFZi0Eow7Mbm0jpOukq3rhF4LzxMZ6TnaY5+aITL/usxX13qsdJA9l8PEDD3R54YsoSo++8URB3sCC+8G2WmMEGeQZzcIpirh/YgwTHB0cotRGNAaXLMyTda6FaYfwjD14nP5+0JsByIJ7IWGL7qURB9z4dPVS8wWVwjXKQK/RKk0ZzZZEEkC3krhznTGVS6EUxU/1EmmBCpGwFRecajZpIZ5RKnL1NC4aI/YD3zYlxicxSSWIcnkLc5HIBo2ezsmz7oC6mCIn/DJcMC5MCFnzjnZdfCiOmZLYhJOSHVeIOoe7mKHTHPJSvYIlxZXb8PO+0PakUgybVAwVgjrAYmrPYpba8yPVUaHnyDtqLjDDlFfIHfbxTiUiUSPaUdmPFxSjCfMpxXmesjdpUM2sIlbMi+cc+JmlnE9SZxY53f+6f+d81WS5EYBuxDzVfsF82cZvPQZamZG18+xpth84+98i+VJyLd/8HsIhy3Kt79JuvEQ+g5ORaH/PMLQJKaRz5NPHjLwjtlbL7N6NmJr+xaP4hmF2jcxD03KiQ6uFWPvqLwzWnEYjFgqBZ587znfSn2Zj8+m4O6wtt3mfCRSG28RpmdMWg5yokCcyFGPTFLiGHOkwiwkrjv80fMrHlSq3Pibt/ngRYnBp0/43mBMubzGIpXETa1QZYe8XiNrlhgcH/Oz/glf+42/xL1kzLKToG/FqNd5wiBCLonEWR135HK7L1BfLzM8bbLa3OK53UISBgwPBOSuxOjlnA96r9BGOU4uXzL5pEn/I5+MnsNfjTGLATNTYHl5RjrwUPpPMBFQDJulWGc/s0PUEdASDbavfVYbClcvNdxhkT2jDd6cDc2kZ+pklYiiM8MQEnStMdlUgl15nb7ynBNFpTDY4NnJgGzJw8+AbJTRQ5OJtGQQFqBtMZMyFNd9Fq0EnXmLYtXBs5eMjiDe9klGI6S8wAnb+MuHrCoJZl2V+SML+LOdib8QIgACyUyAY0d4wzyKNMSRHDJKlUw1pLu06IVTjGCFGKmkE11y4ww9q8Jq6wijvURRdugmThkHFsWhTJwbY8Q+xtJgLspM9u4S9M8QVzPOdgtkLIWi7mAtFOJ5Cl3pEc7zzI0cj6QZu9mIclTk0XJKxl+wWoiM9Zjymcz0psFMmNNJgVzRybQbJK5MHG0N026gqBbnxQnFlwHt+BnmXMRr2EzSGtuRy2TrBoniHo2L95BKG0gvnpNNuHhRjYUVM1PP2c2VieYtps8yaLsXFCIRz4/oRDn6j/6UoXlMObjP8w8P0csKZ4FMnCtj7zqk+yHtZw12v75B8KMeB39jje+dzCkVDxidTHBsCzfIIPRUZnOB81HAa4UM0yAmiAzaJBjLHbRZm430BhXT5/QAJmYB9fvnrG1bLG4YNHWLyp5Dr23yT//9P6awvkZiNETKVghnLa7u2uzmNMLhmDUpQ8fWKe11mA91jjO3uFUyWSwcmqFI0ZfZlepsTWW61oIL+qjeIU4/Q3i5SWfygps34PHvldArLnNliPXJS44jmWEioKxMuHSWzJ946Ps/IdvfZHA9IhWs8XweMClqZPmIb1S/jBakOB0mubwo88fOM2qWRi+W2FDLJF5Pozafspr0SPoCYjYiJV9he1mGtkK2mmMursi3Fmhej4usSiUbkcrucpQ3yQ+uuaWJdIUO+ts7JE8/IuEXSSohJ5OYXDZLbctAGXks7Czj6gHhnRO0J2PcaYM9zcBpJJnqEuuiRbpQRBxf0Bk5XGZSZKslQqWL2NNYujq7YYxYqsHLDnF2wokpsjhT2di45FIzWL0cIysSRtaHz6kr8oUQAUEAdRnhCCWEKvQOfSxFoRtFdHBRE3P2j4b0BDgRl1j+Noc1ESGaoXTSJOYO/cSAeJWn5C2Z6rfZK0kMg3MCQUYEaq0FTzIB9maaYqaGEqvkQ49OUSJZVfEfZUmsqQi5DMLkjIvpNp3KEnE+IDsoY0QGfsLHSWrc9gOu4y2K+yETa8RI3+LLwKIbcp5LoJds9OUmdnpCqSASNa+QKhlmyxYNKaRgDfjheyf8P35rQOaNElpXYBCOEKVbBONDqrkYpZ1AmrSYZ0zSpoRYvs180EUc1jHUFpO3NIhfUMmFdO0SzTakiz5rgzSrXorEeEgQ7GF9a42rj1do/Qqv/CHiYoHoiJjRkoHWQtItltOQM8NjN91CWkZwIdO6t4cmeJS3E7S8CmurIdKLmOI31lEnG5ynLsglM/BswuZGkUlG53nnMWZaQx1BrlgjHnfoDHzCOmxaEnLvhM5VSK1cZt695MNziULUYNA84zA/x7S2sH5pEz4+Y3alsJpW4fAaR+4TbsgcL4/RRz06jR6WovDRu0dIWh/iNyhqhxwP5mhCAhsDK34ft7wkWHpkrR0m3ohSVublrysMWhD5LrI6RV8KXIVJrFqFuNeikNYobO/R/6DB8y2b0rxA5Fmk7JjNNFwKfcxXecZ4xBt50gsHXQ35WqbA49UzBHcdNTWk6Mo4bpNsNqa9FMiIOn5yiVHqI46/Tt7t4DQ9EtsvaQxv4PnXmAuV2u0dfr54inpdIFgr4bT6dDM5rOvnFASFyusCypOY49AiGPi0oxSL0RlS8BzldAfBVJgZGgs9T5C8wChYvL5W5+rJFU85/jP5+0LkBCQiOnkVjBH6YklYj2hXbJbGkmx3zoQZj3STuSSilWsoCGx1bWLfYJwMGO3XUb2YmTwisiK2MknGssZOdIeDqYKvi7SqPn6YQVT6mM9OKc5PmY4C9GkGqdtE9dp0tRSDeIEdZnkDD4EQtQ+uu6S/YbPwW6xI0BMUFvoFQeOaey/nvBl7DCcyXrrIO4kqN7NjtvIB/VSHytymsiuR3piyFW6y697H/bDNLcVDq+6w5qhEUhnxBLyTJ1S3NQbtiH5/xgB4kNjAc3VSgyWbyIzzIxZv/WWibAnBOkPUdGrjmN38ktV5h8Z5ANXvsPlNi1//Zo1pq8kf/fR9zImCeS3z8/YhSjGmKco4dYlguuKr0wXrowtGrsr5WGOxNecdXyCX2MWT1qgf+Rz1n2B+vUGyVua0YsDTdaTpkGHhBi4qVWVJfqlhjTTiVZrA1iHWuRw2SWgpSgOVe5WbmAMfRdMZDhoczpo8frpgNTd49vMmn34ikN1KseZ1uT2OWUljxPI6gQha7waznk0j5aNszcnlu+SrdYzCBul9lWuhjCGnEWpD1rUhsirxF3bewZlmse46bGVNUuUawaeXSP4ZiXILv2uzoI2qTiH/FG2tj585RxUM1G/sseNpdN0Y6U4VwTHJJDcJ5h62ckIcWfiXPovpgtkzmedWGW87h3wzYFfJ4WdijNmCTlxnYIWYmyO2ugbJTpl8qkJo50gpTRayR14ekqpt4uxnealqBKlbqOkYvztjZcWsnzUJoxSXhTSDHz1l9uQaezqA5CaK0EWQfOYFiU5hSElYsmkGjA0boz8mqC9YuiqHQeVz+ftCiEAcwyp2aAcqsxBkX8YJMiSXPkFcYM2VEXPbyKkE0XKFK3pcBhbTaRYjcJjEh4ROi4Ias0rH+MMp9Y001u4J37ydpawusUd9NClGX5rINR0lKKOpIWa2gZyRUNd00vFL7GcrsoHLu7eOkZpHKHLM5ZaC5kfsrSwq4yVZQ8fvroismLgKV6qLUPIJvRGfzs8ZDlXeX71L1Nc4WXQ4RaE7zZDcqeP0FRqKTbdfQ2lETLsC4VGP6JaOkNxko/MmtZFIaqMMNZOGO6bjtTmeH/FCsMnfKLLpdXl7JOH4eyzUNEIhwotM6utDNKtF39E5PY74/gfv8u0//AhvcM5pxuSF7lKpVOlcaISuj9hQcTPrBPcs3Lt/geS8inAzQ5hYY7ljYBV9spJMvzXFPqnhdu/RaLwgEZxy3voOL0KRTnSGWugxHozZru/jSCtaM53ivIkWLqgbFaLvXDAtLXjiHKLkikjNFWE/Im2HjFJjRFFiI5VmfvWcR0+PyFl3uCGvUTASdMc9Ols5lt0mSlyiNB2yOG1z1lGYqCeE0SXX1+8x6TSZBlmWlxWuSNDWx3w8vsTItpj8/AwhaHH+7CVO+hK/taR39R6NxQ/Q+kPE8TNOftThfd9i0tD4cWuGVZZ5u/INClkJURhznBjQXvXwJymUrMgyvSRZm6LoDnacQuvO2KRKxwp5bCc5GGooYZHCbInyKoPStXAKNs2NNLnlHEfXGEoRyX6WgZ3GWeiU3TmRccateIZ13aP9YsX0wwWzXJqUt8BUFljeCiHtYu3OcaIl7WmF3ZmEslrgrVYMpBXt2KQ2TVFYCUyOLNrGkt3tz1/0fzFEQIjQxJBsSmG6kohxSfdlNFlhHIh0hmu4QRstFPEzEgtdhOIKeThCGMpItsTCEzAHWSret2gqIyLmdDsHjG/GfGnjJqayIilPSPaXSNKA83SHUcrHEHzc2EYceTjzCuXEhJS/wpsaNJyQlS8gBz1EbY2RpjBRfIQdi+TaGu8c/E2uGml6/UP2sw5t+wojVeRyNONASNObHVN1A9T+lNd9k5nRIH37itIi5Mhpk2KMa3fxzVOsZYRr+ZyJ3yO+42IW1vjKl0oM9S4qu6hLk4prousuHbfBYikgvfCwhoe4uZjBfhlH9mn0FujNGgfVHT48s1nYDmsH32RdFdAEHe/K4YQRy9w1KVMmTo5QlXuI3hjhtkPOzVHR3qQw0VjO6wylEPv1OeWqy+xZB1U2Of6jcyTlS+wYGurUpvuuSECaD+MGy91tbPWQYWXC1I+JszmEssaLUw3dy7BRr3LcVRmZMmH2iNlEx1jA0O2ydGzsf/kQx6rSHreJhh6hmSB1lcLaCkh5EWIuIiFvoyYlmEi4Sp6UnkLNpknknxPkz3CVEbLno57OKRm3UPNlTtUAV1sQ52poeYnFx0XsoyKfNHp87AyoFhZ4HzdoaR4Ht/dJGnvMCjlWygJv1qd0MuHp+Sv81gmz7gRVsjmaD0hcDQj1LoPZkvFxF3M8JrPWwbu1oBzu0FOm7EQzloMys6VLcjWh6X3KdWNBeqRir5bkzF0KWY9VtGTlFXhkW4yTBoWcSbDVodedMZ6XEYT7TOsWC9/i8GEeLYqpxhIfiiOapTSjUCFb3mI9kpmMz0isZ9hJO0jxnL1k7XP5+0LkBKJAxOolSRRnXOkqiyCFYKp4VZ3dZZeZEuAaRS5HLklRxpe7rEKI9SV6sCBeiKT1NdRkgGi10JMOk6kPpSteeQq3uIGantAdtomKBUR5Do0Yddmmt9onlkekjClp5RYtw8ZXQ3amu3Q7MjO9R0Zb41TtI8ymlFMtnj0RUJc+D2tNGmaXweWUD8ctmnGfoZLBCsZYlynW1zO8egqb4zUuqjHDBcwyWeTdAVY1jT4cIzRL2EoKaeSyF/ZY3KiQFNKIQpt+v8V2PsNkvOK6tMVGWmPP8Tmf17CdESVBYjjMIYkD8ksLfR5RTkjUXtepiGNejke09Cym00XISvjximJ2A0uOyWXWObhv4EQxtbHBj56tSIcycqFAuTbmqA/JszkJZ4RySyWV2SFM5XnS/BBts8tsd0Y4fknaztPNXzEc1KnV17CDKclbRYLrI1JyhWdXA95YN1HFS+bWXXaNkAQKiauYi3mTcs5iYu+Sn4KUmHKRD3APl1Reu8nTC5etlc/Iv4KDIjNnSHohkDH6tKQkJRV8aYG+krHjGD2xSdbLEfkgGEekhApBrLKeTBEEFTa/XmfWKXElzEkceCRbQzrJIanzAO5ukE7pVBcv+eTHP2bnG/cZFTPEn8T0X55hBusY4j162R6Z6By7pyFpJoexizSfYNbWsM8fo7aXjOUUmiKApFNf7pCvJ+k6DklxyvrVAz7ZvEZZO+bhkcTGdE5l12J60saoVej0I762Z/FpYo3ObAlqlX1rRDdjsJmecfKxx0Y6h7w9p9qwmU2+jROm2VkVOTR1jMSQIFnGPrzg0LTYL+ucrhI8m3mfy98XQgQkCeamQ64rUDY6jBUVS0tjNmXcZAE9HqDOZsR2mTgSkBIzXEFGCJLYRZMUMg1xxK9Ym8TjAaPAJBjN8LwZ0Xqefj5PdUNHzJSYvAqI+xksM6A/vkUylJg9l/FqFqF2hTwxsaY23BkyiVpItsbJ1Rw9Af4szSAyiDM6jhggvfcnmM0ZSkZiqHVIDjPEwSuS6RSP5ucMnr2JYXRpZiTik5fIVRnnKImxBeXBmGs3z/2UzROphKI3kQKZiIhWf8zaMIMrGMiRxqwoULUUcn6JYOoSujHeXRXh0z6KP8Jx7pD2ZNqlCblChSIbCK7JrWKduF6j98c/xdxPkupuMBt0yH39NsJhlzNbwlkuaBkmLa3OfikkXXJZHvusuwqO28fXdQg3cHSbWe4j1IXAmlGm2EnybFYhkRvQ8wogDhhPEqj0iIR1dGePthZyoxrRVDuklS2KzRc8P6yQrZboT3rs5e7RNA7RMwbKQMOzkxi1gB1zhOOH5PIbLDMvmUhLiskCqaLBPEoRr0qUJgsukwLSLEDRixhjByEMkXdtFGfIdR/c0hTlQufT3JBsd4+BNMCYv2QobDAYnpMtJhHjDHE44uTVc8JFn2fVGFfU+ekfntNbmojJmIv5irXlBbuFWxgpm4ab49aGSBSBcD1mVQ9JPWuwL8U8FnOcBWMy2YiL0xP27rn0EutkXz3HG6Y4rzsEl1f4+g3uKC3Geo7exQXq1hoZt8j28pJOs4bsLeifnJO4Y3EVq7z2l5MEQYxliAgDB8tYkExvkot0pPkSce5jbC5wi29ilCQyj+c8J2CrrvPVhUO7fApP/mz+vhjbAVFgR9FYiFmUSEDUUghhhyiOsF2bqaATShrqWpdM8SVZQlQ1oCCZFLsgiGM2y5s0Cnl6ezqD/IRp2UdfWycf5bETfbTwDveUN5Ful1hWFZRgRVEbM1FbJOohiXyB7vmEZr/PSVrlcSgx1HziYoYcCoIpkpBjNC3PtpvgliNghy2kcoWNtTyJxTaGFyFLW1y6ZZyFQc4EZWyxmi+5m8xxK+0h7Vhszu6RdkT2ggbnKR8jjNkTD6gpVd4JPW6oW8g3dYL9BNEdmWi3RFVKcLx7wsvSnGa+hzgaIjh5EpsZJDMge0cGscpX0nUCY4OVZvEgt8Ud5YSbVYMwcFlbd9D2FAZXT7EMgfDiUzqLCZ3sJbVSiZfrG2iOQSrbIsjp5NIp5jsVPGfAtHPN7KqMkS2z2rIYJFK4ZoxjC4jdDBnBQlpcshLTDLxzln6TSisis1oitxQK6hSzcgdlMcbQXIyNmP58l62dOmmriii0qZRk1sIa7jCgO7HZrxjIyZC9zE2ygxri/7O9P4+VZd/u+7BPzVNXz3PveZ/53HPnN1zykSIpyZQpGpIBCZKRIJIQxIidBAkQJ5ERQIANBIidIEAmwDLgIE4iWFZmmaIiURTHx8d733CnM+95757noaprrsof91B5oN+jYkrkve/xfoBC/2pVdfdavff69m+o6oWHsojBXlFsziluR+SCNeXTGUb+mnZJJZzBu4f3+PnjXdqDMm/umTwITKSDcxqvKdhig1u3PZrBhL2ZhM6ama6AZqG075DGhxwW7uM16zybj7jZygRiE9moU3Pb/KV7j2C0Igm+xuvNb/Bo/y5ZqLN4OyWvNMgHO3w1eYOv7P48nWbGdn3IT3/lPdxURXzjDu+9e0hOatGYQvygjumGLG+2KJMlB+Uc+TaIfpeyf8VPPtijsPZpFXd5/K0Nv/PrA/LCEYZfIXU1ykWbn/vrbUZRzDUxR8Nj/us/8zb/+tEtbv+EzJuvy3wt+QbV3Xf51+79xR+af1+InkCSZczTGEdeU8hqWH5G9O5rMOmz8gYYs308f40dGWzVDlHkkQoB46RPVTDwsyKxEqCV1pzdTCgHCpzmcHcsRvoG4bu/yc/v/GUO7DGKfY/nZRG39T7O84hAPkSxHSrhiqGuY+SgVTvk1E/IApX5dsX9By0GzhIJhZ1Wk9LbbyIGPvrZP2bP2kX0dJJWiTB+i0A7gx2N7Jc6lLyUzXGLfrwlVosI0Q7VksRrOZP+7G2M/iW119/mtaLMbDrj1v5brBydRD1n2d0yme3xT88+Zj+TmJVOSSWTeOpTnIWIuBRbMufLFu56zIVT5P6BTX33PXqLD3jRLfMd93dpWG3yUp/J9xLq5Ry27FDZromNXeSKxjKuUpLzHK17nF9bZPdLjL7lEeCT3M5TKL3k5Jdd1ij8bFNjKmSExV1a15f4mcbpQqWQb1OrapRyCqfvP8F7mKdyEDBx17SaO0Sn1wQnElGzxAqZb338bap79ziynqDH79B/ec1MkBHUD1kP71JUJO7L+1z+Tsje/QLTJx72wxxBb8HDo0d89PGakeFz9M57XAzPcT2D3YpCGm3INiJdtYT+2i6K6nBs5FmPhljlA14+tdDzXW5v3+DRT5dwl32E2lcoZTcInNIsvUZOPOaktSK9ucV+NcdBQ6SYqHzXyLHdtTg52SL+5D7HXykjX88x/+wb3P8kRhjFfCjMMe4rdOYr7t/+Of6LX/4EdR82YsYkalI+LvDkZE3VytE1KriiSnK8IWmUCWIN9nW8hUC6GBPe1ihXX0PA5vimzre9c6SqRBYvmTdHIJYQGx3yxg75t+boL1c0j2SGnsvXoxLvp+9gL79N3Ghz+ckz7J/d/tD8+xcpQ/Z/BP4UsHp16l/PsuwjQRAE4H8N/AKwfWX/3h/4HmHC1vSImgUOGo+oFDosN2NerOeEgo6gJ2hKmyBVCOMLFCFPOlvhoJHlajhEFBSZzU0ZI5exXi6pZymz+TXlgypKdp/v5E7JmjE800glFfPsCI8plnxGabBhtCpipB0EOWB+/YQ3WxovYg1tJZGfCQT7EpPLK4JribWv0ZqM0H/iJ9hmK4xmnnygM7g4ZzXr0s6OuGl7vP3wK4ylBnfvD9iVW9x88xwxpxA5W9TJS6KjDpuTlOF7Hup4wj8ej9g5LDMM5zinfZJQ5a3793HKCpwc8vYq4MPWCgkFQ7hDOdSIpIR1PGMjjXnzG3+Vm29/k0ePfp7a4hkfaXl+6qfanP5Dla/+5H2m/XNu3y9T0JeMlbtcD8Yo610Ophpa84Z2KvHdzSVCu8HRSUbYjZC7ZXK2QxZu+SS34Hhjs3j+XTYjj3UiEWmgT0bkCxGm0CZQDXR1yWjr8vbrf5mNu0X3UsYsUe0Jbq5AsWsy/dRBLi04PdV52LDYHQd8PL5BTmeEjxpMa1uUoI21Pkbdvo/zyQlfPb5LrnzIi4drsuuEWbRG72nUjxLyvYjwHhRFjcXLxxztHzN43mP1zpucCUX+QucvU1F/A9OqEq4g3anhlRzs3iHVIpxNVKaOyUJMqZxqfGfymFu37/HJzbc43N9HW8Q03DnvaxP0eYNpEDP/jS7zOEV2Us5yQ2wi6D/i/dX3eKRdsP+gTftfzbG5HKMVVdIXNdL5CduixcFizIvxiOpIoWCWye/bXP/aJVfLEbtijtvLHWyriGDKZNaQ6tN9wsMtw1Wfe8ohpc4OdavOyXzO3ftlZp2MA0sh31nzzSxj83fepxcvMKQurjLAtut/eBHg/1eGzBEEQQF+WxCEf/jq2P8oy7L/2+87/18Fbr/avsZnVYm+9ge9gSLCjmvxcmjTc0YMygnNToQ/czESibIZ0JtdElbz+PKK9iQkJo8iaazcEXK7TNKN2ThPqAgyqbHF1QJMq066WlMO50wfx1x+mjE+6HCn0ubbSw17tKG9OaLSuCbcrWJk8GIbs2lo1MpNej2HwlHCa3u3yLWPyb+l08wc/sn3TjkZPeevlQvwr/wCb3kKtnJEEv4mp84ZmXFMUrfZv4zxXtPIdR8wvOvx9j2bq1mNaSJy/8+8QX4rcaaKvK4rLHaO2JnNCe4eooQ+vzT42zTHOQ7WMneELRfv7bF6fsN+0SNHnb6jMZe3dHIgtz0qL3N875NfYntjcTr6v/B2KCOuxvzS0wvSpMiuntKbfout+xrDaoo2+yVydxocHCkYsynSwVvMLz5EOrFQzYzKTsbCEhkMJuQfPkC/2CIXYKNA9L0SYv4tgqu/x9c7Biejx5iDQ07CT3nz7htMtXPU3Jr+RY+CqJE2V9xcgvHpCe233mG7HfF6U+C7FwJf+/khk08lZvcibo1vM09C8lmT93/5MWbxGaXYpy/H7BerfPfyEmM0Q/YVZKdMHIkohyLjTQGnPqHA6/hPnyIIVRRD5d/+d/4G5eQ+D3ITtKTKPr/A/YdVnPEl+71DNkYC0pYnq7uUpB2K7Tmpq7KeutRGHVbnv8Po8AH5/Lvs1z7g6upT7volRk+e8+HzgKXwCQdWjfgNk9kgYjx4zlt/wWQ0yTNKzthpBMjhPo+9APvNFq2rCyZWhd6nMkdview+tVhqp6zCK/LLJWphzB27ihd2+WAz5y9VbhOPP+Wjyw2Tg1Mko8V1L0MzPZbiR+z9vMbmes78ZMHP7nS4OqsgKA+RzKeYDQ03yCjoC3pZxPKl9IcXgT+gDNkP4y8A/6dXz/tdQRCKgiC0siwb/HAVgNhqoGlFivUpi0bM4lsKh3mTYCgg2veo/aQL6pQ0tcnXDOrllMVyh/tdjw+MPua7Mge9KrbTZtaKuX+j4ZgW/dcSKssFx6Mi52eP0TYx44szCvkG99/Osd1WGFhbjt1dWrdyvDHf8D29jJoOufOeycbP8PMihjfnYlAjekfjK8cSunwbr+FyPF/xacniUB1x1HyH5o3CthQyn8JYEsk+UPjozQQ9EekJu+SFiEazhaqLNL0Su2KVVK8SCQteKwyZbCs8vzrj6+/9NKVVyPCkTmG6xbnymKxrvJ6zSZYWgn1FS44xJhF5420i1vzOskdVyZEZGo9VgULOZiLVeHQWEbR18vIBz4wxu12Bwr6GntNJnJgnUcTuZYhn3WJqxSjX14RFAW054kk4465fYK8BfcUkGQ0QmxXc7oKBWqBzUqKSejwLLbbOmrD5LQ4mGt3ehqh+Ca6Ov9KI1CWLcEZ80uOwcY07bRJxydUnOxSXEfpSx58P8MV9ltMcUXKNHLzBcLbCokTFvmC67KDYGt7lgMMHMaezFKlywNQbU2oppNOQm2DLLdlh7N6n4TdZNFx8MaXg5ikrXRYXJXqzIh8lF7T8CHt3j9FKpBEP2H64JJUUKmWfQNzh4+sjikWPPXeK75uoOypnzneJJB9/26WU3aEmnPPhtzweHa/x5SKffvAc7Aov/nGd5QuZZfQJ6gYMa0BiWGzHeYp1iSeCxuH9FptFn6a2Q5g6PHrzpxCXM148P0QvzGDg0TcTxJ2EjvGvUxTGNI/H1ESTq3bA27HJ4VHIcu8uLPOU7kAsfIdf+oe/ws7dMq34Ng5VSu8KTHLBH14E4L9chizLsvcFQfi3gP+ZIAh/C/hV4G+++sXhf1aG7BW/V6Lsh4tAZhLJKm/UOyhKDtGSsfZF9tMW6+M5F4bB0RsahfQR+0mMeyURlFVeS0O6D+Y8LOkUb92lejRHG1vE1YRRdclRWqSYnzOxKiznKm055SLbcOmL3GoueGrotG9ekh9XmUdd5sOElVnGq8c4Oz7V0xi9fBuudB6vLslVr2n8yju0/sq7BAcZwfqCm96G1Tlo1S2nxX3U9YzJdshi3GawzNPozNh93yXZtZicOxTNI7JeyGXOI+2obNMbnN4jzOKUxXWK5DxBK8r8zO6fJ6htKDcy9uM8O4KOpt9QyVk4toDN1ygGG4xVBaO8x3XB5b8W76OXfxdvU0ecdPGkOokhk1tJeGcqTifmcjbnO0++yTf+3C8QTwbcXEtI1yHV5inN977OxvPRV2VG7jXmUYGfzMGOBN92rlH+6QXW4Xv4eY/UniL/uohrCWzKx9jdFyQzUFcJg9Yui6JPo/+SxeERUeZSqCrYyR7LjcesF7GRl1jlO+yIe1zrZxwYtznf/10SN6OYDGnnC2y35xx+/as4acj1TZdyp0M1mbE9bHKnWmS8Dtj3brFXi7DWCcuFQk7NM6mU+Vf+ta/zSWvGm0uJxDL5dPEUUV2wc1vm2PwagvYxjvIc+yxHfvYCRc6TbWK0R3WOWiWywSU//dp9pIcJO3ORq0CncKzw6T8RqLx+xX21xCQpsXwhc/+eRfORRrIJUJcVCpLHxQsBRcsozmSq1pr5aYPLVg2MAGnmIUx0ImWEmcSswynyFkZPpsyLEXl9zZWWsEx14icxTmVLHK/QZy6ZGTEoZSQzlU8+/JQrlnxqXTE7EXlUjFlmU3qPp5z2JSwlx8v2t2hd9rlQb//w/P7n1AX5/WJQBP6fwH+Pz6oKDQEV+I+BsyzL/n1BEH4J+J9nWfbbr57zq8D/JMuy7/y+1/o3gX8TQBaUd1Rzn4JdQPLWiBWXyjrmqnELPweP1ivmlZRCsYnWDxCjKovyBmM5J5VFhGKM1mpRilUaQcLGreHpE24mHrXdPZbhFfcXK17MV8y1HcyiR1lvk9gJ9o1GK1dksnOBI6kYgx3GcUwShex3bigYtwm+c8GwUqBdP+JRQyOZKLwo5vC6J+y221h3RUaxRzPaZYeQserQ9WWCNKI10lkUIMuPyA0fUlc8hIrGfqzQE30q9hAh10bxKmwbOvln11y2+6iDHXL5iGWnTHzt0H+xQBjm0A8TrlsXHG4spHmKtgdcrHhcsDEGW75eEZmXXKbye9TOpuxLElfeCtHacn3rPvxWj8WeTRrbyEmK4PTxvJRcArO7KaWlxeBZn4fmjPjuMTenFvce9Pnl31yj6yMEY4/CasvKbvD+k0/I2xGN3BStF7K0BQZ+yi11ThYVGZgppSylvMyo2HfxfJ1t/pJuqNHuaORWeY50k1+ZnGFITZz573DnwS4F5Zjr8Zi8ukC22tTcjBf9j9Fyt1g3db660lmKLn0jR97UWbx8iamWGL4YEVdd6gcFKlqbMNORd9e4px2uxBW3LYFcUyeTLMyuhZ9+i8Eig3kRR3SQ9RijWsaSq3SHQ6QooFpasZu/w+X4Cq1VpjccoEVbCmGexXFCepknaxnkrIzECSjf6LhJRi93iR4bCOUqoZuQN6ZslzLoCt5SomnrbPSAzTrErARM5iZ1McKPM6z1iLKksKpo+BufrWARiiHaOmOt+igLGd2UqWgx08RDiIp4pkCkKbRyEpvZAHF6jFv2ieUM05nQiGOeu9vvZln27r+QCLxK3r8FbLMs+19+n+1ngH8ny7JfFAThbwO/nmXZf/bq2AvgZ/6g4YApa5kptVB2thQ8lSt5yR1TZR7UySKVZOshpR5ZLiZVAhy7TckPcKUQYZuibxzWgOikeKRkgkShYBGmGrG2xfYDYjFPgoMQqBiigJLBQglpKia6EzAqCSTpmsCw8D0FVdiSjETKqchGC8hJd8mSKVl5yUqJkOcN0nSGKOnouRIbY0RznVIsN7jyMg5CjRsvI0ggLVyAU8ZKZOJ8RC3LkKaw1QP8hsF2m2AIDmlcIMsvUeM8XphHTPqohTw5V8FLUqwgwi6qTEQXxysgZCpW6qBsMsY5l721x0wpI8cRRbXJSo9Yuz5GtIFdBevgGFZvkkxfMMvyCFufoi6zu+MxCCsMhgGNPYucGJPWpwQTj3RZwwrHDIoHlFYeWl0gFhSkdM5gdcnBxuSitCGd2diTIV4S4IZVJMmnmo/IpJTYC0j8GnHWJ941yYYanVrCspAS9QVanYxut0IU+ZQKIr6UkI1cZOsYJxoRR31apRpqJrJWHKqblJ5iEIQ5WlrC3FhidF1MU2YrwziRKMsS8aKCWx8iRxXs4oq1aaKMbNT5DCEvEekL8q7FSlIRain6PGQtGlhjF+WOzXIj0kw8orBIZG1YLSXs3BZdCtkENsW4QMqG5GjFqlvANDIkw6TsFylIHpe2irKWkXUBIwvJaTAaxLiSgKUkaLLMMO5yyzUZa0XMWGTjR8ilPNU4xGkouNaaKikbMaMelhlNtmx7W4ydmGJcYpRuWZstWo5B25TwtB6mGDNXRIR1k5nmY0qgiiM++eD8B4rA/z+rAzUgyrJs+X1lyP6D3xvnv1oN+IvA41dP+fvAf1cQhL/LZxOCqz9wPgAwSzK/+PBdKvs2S93ltu/wulDlpZ2xk4kkmwihsiD38oDBHZd4cIfWT3/I4TJh4OpMxBj7pYFeU3HSNeN1DcE6wxCL5OYF+tUxtUFEL9yynrskap3SfkjJn2HHDbyCg5/WkLUG/TSloEtsxBW7fYeX6xV3VJPZsY1u/hTLT87I78c8n015kNzjnqYznGeg3EeKl5ybDe76Ze4XV3RVl/VZjcLdu2zcPqu0yB1xwRNfJd87YCd9xmnzPvrDhNtXwErkuplRUqH4Yop0/z0muo6nytjdAXfqHa62UzJ8gr7FWKrwoN0jUFOCXg+rk9DLlSgsauSkIi+3XbKuRVu+xa+JZ+R8hUpBZNgq8tDXWcc6I/U1aEzpdGXivTKdpYuwgLzUwK128dHJX+4yvqczy2k81A024x4CEp2kzKDchTORthIz2LrIos1edYnvxci2ytItIgUaFT3PoOhjzmM2dsByWSa/CbioSdi5hCSnUSwHHNaq3D96xNWlRnFPRYtDVOslq6XB/MUYs1hkv7yHx5Zp3UCKL/DHIeX3UrqZSuvaYhJIKLkbvBMT9Sd3qa3uQPYM66s2Vq/EOB7SqTSZrfqUqROUI8ZinsZ5wvntF/jfa+A0d3jIkJuXl6wv1+xKDb7xi00Oa/to4xlTt0i/OkLTH9FuPKb5XOBJoUWqpTyq73MjSHzDnlBfhWTWHQr+ipmwwu/ZGMMdqH1E/rDEi14e++0Vl70Oj64HoMhI1pq002cm3wFpiHndZBzG1CqXuNMdkumUTztV3sgfEE9eUKNCT7Jpbyaczes0SjXEr2iUxxkzF1x3S618yicf/OA6QP/cnoAgCK8D/ynw/WXI/n1BEP4pUAME4CPgv/1qBUEA/nfAn+OzJcK/8fuHAr+fYkHP/vRbb1FrHlEK11y1InYv6pwW1ujlDGejkluWkSnSa0Yco1LRPmFrHKDJAcLGoFyQqd1usvjglOW7TYpPHby1SrG1JROKGLZAJ1V5NnG52N+gPVPpHG7ZSXaZxQtGNZ+SY2NeSoS1IqIY4uYXuBu4FzQQWh+xGuYx4x1yG5VwZ0GwvYPW8thkF+gLiUmrwN/5D/8OCy1B87f8D//C/5h2c4NQ9DHTNf3iI8rxM6ztMblti7J0wofZLkrmUX04wxvoZDUZrRkRXVrUEXmuCqimhzsqcCvJE7RXtIYyH6wKHO9fk22LbJtzFlOdbWhTn01QWhZSzScfKkRBh3CT8F/89i+zPoOlWuOqe0maOFyYPsYgQFdWLEUVGw09dLHXFZaSj1PogXaMn7umlQVc+i0O+irOrTVe0MS+WLNIn6JvS9hOnxctGUuZYfYTtrtFltcKOgVW7Qm5wQGBtKZZCUlzecSehlfaUBQF5nkNS5K4L+dpHh3w3/obf4nTbYaRrpEylSC4YGHtYToDps8VxPptYmFJLdpQql3SXUEkNQGLd05SZp2UK8ug+uIpSusWqhQh6jLniYEvjNGEGL1VZDWdYm5U5laPw/NblPxr1vceMp5eEVRshFnMf/p//t8ynGTk9a/wb/z1r/NQSdAznZPSmGwSIu4vyQV3KOZGjOc5trUDOpMzRD1FReREW2LH+4S9KfqtCYX4iKsrn3pyhp3uk9uDrVZgMhpQ7rdx6l22loLfsJCmdbR5CLMaTv0Ks2gw3JoEVorw0RnVqoiSEzDHBaSsj7cscFMakN+8zsz+gDuhTmzXWMtPUZIC/97/4u/+4XoCWZZ9Arz1A+w/90POz4D/zj/vdb8fMY2ZiRadRR8/nyE/yzM78LFNncWkh5WT0eoxldjAbXoMVtdsn5rsvO1hSiYst6xEh2jocdRwcB6vWEci0mJBtFK5qE84KimcDSWW4yVvDSJOc2OW4/tIs1N6VpntzCOQ82gK3O895ySR0Op1FGnFZnPOWMvYyir5woi8MmAl7FEyv4e5tREaJvFOyvayTyxsWQ+XWJlO1uzSv6UTnuXIkialaIxUyjFkQrzXJ+/kUaSE+iJk/C2ZwVGP5NrgzgcyA6NGub1AHBRZdjJKsyrjN0TMxzbdZItSnBArHYKSScNI0I5eZ0LEwck+oS0wHn+XTVSgWPCQdJWf/CtvMhNKGL0TrPFfRS0vGHT6qF0JvZ8R7Hmcj3yGc41iFwJbZdPvMt9ccd17Ha8V8SD2CFpwoBoMbzy2xQHLgYaXDdir5ti/X2X73KZyUCGfi8g/1LlX1LjY5MnfqiHuVKgFecq1MdOrQ3YqE5Rj2A5z7Aqv8VOPDnkZq/zW5ScIwpwd4RaD8ZgsyZCtCC+QaLZEsK7Y3ky40StsukcUdhzEeYFL55JxUsJxZ2zNBgu1hs4WLI/yZs5uvsjFWoSczGZ8hvidS7zqARUlZrU7oOdMkD48YefNA05nv440LRN5Lnk3x6F0g228TX84Rb29If/c4UnVxHjsM2gG7KUmW2eIpZVYiiXM2XdY23vYYYcdYcPjfdhfBmyiGTtHBvGntzg9uqIW3iI3y5OWXE6WM3zBpN3bIg0F1OAGpSCT3ImoXQRMJR3LP0W/cRjvevgXOVZ+hqFUqb9WRotmNMMmSbqmhcfcslEQKU9/muU9Afi7PzD/vhBXDIaihnonZvs8ZNy38JUisXvJnXmBxNvnTn7JSmwylT1eP+sxqR5SqJhoQYxvmbi1NbZWQjl1mdc1WmSUtT6zR/vkQx3DXdG7hN24QFtf4QttcuoOYbDGbfioA5Nqc0u8GbNbL/J8KjHVbN5UYkpLl6U3o+rqlG4PmC73KFV26Hga41yKWLVJXJHmScZYCBEcCc03MJoKsr2g0yuSGBFXromkySgnA9a1Ml4sspQt5A8jhB2HdXOHTOjwtmRivevTKRgkhkHDkynIJcLYIxklaLcL9KINdwoVetMRm+ouo9kxotzFqOv0BRh/tKTTPiZX7jOe5Tj3XMphhlS4wsib7C+/TWya5FyRaZRD3E2oaXXysUt2qBB8ZYtRqFCaiixP3+QxMqrs8agiEM7qOOqUZJhj+WDF8vkKf37CqF+iaHt8vOfyM0WLZ+4lmpynL665M9ExJhm1KZT0mA9e5nh4fIfSUUItqbN6TaI0qvDR9QVa64Dd+wXiFwNkb8RdOyNLcox3P0L7OMd5vcxtRnRzuxyUYbuuMhuP2dkzaU8PmOYuiJOAxuUJczPPBhcxXyfaaAjONXl/n5ExZ3d9ivjVB0wHEuIwoKwqjLdb4qM+BU/j7XSXniTiyWXiRxlLR+ROOeYyEwiUkO6dEnu+SSTrLIQFYSgRBweY0TX+xqRkvc1HuR47JyklbUNnkxHEHTZFj+V5id2dgMawhW6K3IgbOrHIQJ1jlvKotTKW56GIZa4nC+qeQq/p0o49JuU1l7ZNURdZTA3y1pxUeYF7OaBi3Obj3pb9hoBTPcDon3CZV6gVZ0QD64fm3xdCBMQ0ZfvhBU/LNUp6gcHkhNI6Y3kgEi4vOXc1co9egiwzi7fMRi/YpibylYNQvM9XczVcb8ygviIsB5jGDlFWofsCVosPaZVkxl5C3+3z1tEdPH+OlZsilMCbylTKa+y+R7Bj0xtOEXYjWknC88hjv6SQeRmRZ7GYlhG8AYKbkBoW09hgNTshcyA1NeSqglj2CMQYI8kzvW4yTM6pqUfkajeEiyFp8S69nE91/RKlUqKzu2VcidlXF2i110jdCdeGjb3y2WQGO89H7N/X+K1WheLpFaaVYvZviFZlym4DfbVkEnvkrAnbbhE13aUlZ+i5M87NNVaUEjcz6tkWyW+RpEOyUGK4VthUSiRVBzvWkJOM6ZsrtIVJZfsEf9tgUijgGBKlQkQYFuhOnrJbS+nmtqSFAqYXcXRHxJ/8Iu6tAMvrcleJkPomavEWbTvHRjxFuy+z3YxIF02y+y/hmU5912Tc/3nkaETDrmB6IbZ9TPfcx5QigvIjioCSeSxVF/9lmWqUQ5HXbOct3mbKx+EBdfsU309ZsUUOA5RViY3ZRbgnsf9CYLkbkwTnpFad5PoQQbshuxrhVpooT2NODqYYTszcUMnEW5TEFPHFgicNFWl4Q7UK+W0Bq5Xymy8K2P6U5sbGqDjsGVu6SpMducTSWJFfTjEpkOY8Br5Eej3Ere7ycaajzPrkrApZHoovp2zzGxbbmNTIs5vNiEOPW0KDb/9/LvkH/f8Xs7RIyRxTTvf42W8cEHiPOKueo60VjpcDlM0bpLfOGXZXlMNdUjlkcjZCbAVMhQbOOOPwtE756yeY/RZL9Yfn3xdCBFQlpvGGQXw+RC7EHAhDCvFtgjxY2RZxUcAdufRbKQfVPeSTG84xqJfXtBYpHx71yT9NEFdNBDFhdjIkXld5Hp7x/q9+QC7YkEotVuUF7lDlq3sKq6XAwaaBmm35XTJM5YhMGtPJt5gux7hRhGpGpNsKw1oLezFBmnVZ3ZGIPq5htTMyu4qxnDO+36QxvcJTblMpvcdxcU2m5tgEGw52d4nRORZkZoWHOCOf+5aIUfjTaLM8hdcHBE8S6qbJ0J5jPncw7jtsHZsg8lmU/jxrA8qbD9GkBvmFRnR3hhK3WQljisEei1LE2t3wtqmT9m7wRBtxs0ehoLHqmZRuf4S2LKCuNPTQ5Lz2CNfc0JqN6KUSylmXaV0mfyaS3PFZdh8itGtMNjHVyObQ+y6T2RYrKOHujGlKC4bDEbl6jURTcCsvWY3yyJsCce0ap+FTICV2XhLGCsFhidx0jyc7G4ykSrtaIrg8pxEECKVrVk6DpS6w17xmZpyirToI6g3dfso8XNJu73GVuaSvR+j9DSdrg42QkPN6RFHGWgJ1sWV1s2bbqtFYF9neCERHJRbzLev6XapGRKUKQVzEXBQJKiKB57I/tFDzc/rdOTVV5Syv8xo93KmOVW7xi3/lL1I0bVbPQlL/JQVhyPnuQ6qXB9yUbXLBhwR6jvCqSVJ5ystpmfiwQDvosqO1WN98RJTdppKvMItOGd/kURc23mXCWkixx9/iLGvyNUPlaVTm2v2QwRMRUR4z1BREa8RaL7PWz2hYEasXCcW8zMIYoM9maNMCXnOMZM24UhTi4i63zl/QbeyweL2AQIEXqxzW7g+fm/9CiIAXi8g9lTgoMOsZtDt15kZCfiIhVIrkJIVpKLC3jbArKc9vF9hZuMRWij/3EGKdMHnKWXabOzcl/KZBzbih/qHHvOgRiB2smyW5RY67LYdxYU0UpvQCmTQWaeQaOOk1vhQRPRdoVTymqk3VcFmUS9hChLpn453b1OdrjmtlPDfGFhScQYnSLGO7L3FPXrL3p77KPBczrTm4vopcDqheKjyprKj6FqWdKpab4B7mMasqV/MY1VFw5SXuVUZsbdDq99kxu7AyefLux9y6amOoEzoPU84mFmZQYFrXcJYqW/EjuElRzLs8CzfUg1MuHJnKYZ50WKGdFzkVI6JyylS+xvKr3IrX9F6s8BMZvdBEVzO6ksDRfsjlKkVTfNaLLkoBFvqElXeLKIjxph8hXAl07D9FefQhZjFjroQEnkghNMheu2LtRRh9k8fdK3RNJm8co7kw6MRUuxFLZ8nqRuCwVeMsmlLOv4ZTTNk6XYL+GtPZJSzKaCsTrTQg6O2TPovZybuYTxUcI6BmfcKlpdOaFBAOKzReRGztl5jSIcbCx831WTcnLLOfxTEctNMLruYOZ2qeTrUEFR2xncOKUozJnM0nTbb6p6j7OsWRzrXcRCuWaMtzLi4bZI0BD0oq5/OM+MCmcR3Q5QRtUCDOb/HWeY7sPqFbRBOuaVy16YZ5PHVAeiAxGCqYkcg8eAdD7VKRXNbRDrXsGlOtkWUhJ4GA7I1pqgbvFyTMmYtrm+SMJhWhgx5nHBYafHO3jCo8o7Ds4ak57L0cxlZkcD4lwibtVvhu8DbKeUDhLZHwqkGoL5Gfxj80/74QtxLLkYoY5DFTj31nzZNZBXGUI7ke0n085wPDob9xWD5R2fjPKMQx0/4K6WKHirRmq1ySa1q82dmwsGMU5YJZbsWzLEKfi0iTED8fse04nA5z+MMm0kLlWcXnVwIHZ3yF3QP5/ILrkssyldgNZlyPKniffsTq2RPyNxmGsEJXSjiqSU8YE6Vj9Lt9BHXGWlrxax+J9OwLrPsRyk6HNzApLu6hWgp7Uod9Zc6gsiY5iIgDlYEX0a68QflrGsGxwqJiYb9hcbWccuWaiLld7g1syv4a08zzTVVkGcn4zgUFR+XGGaIaS9wkJbyI2JtMmS8O2MsSzOERFH3Wmk+BGs18mUpBRpNV0kylvT+jsjdlebQmPSojWxse6yOsSEbsuQheTNqLqU9dSkkM71qM3hJQzTbbRoD2hoUsVfDVHHPBQgtj4u8dUupFTHbnlOwtb1ktlLlIXFuiBgsiqcJe/CbZTwhcFRw6hsZwdMWV/yHe3gzPB+NhhLA4YzWwSS2bu+OA6CBhvnsbzytQ0RyC57c5PMtR68uIH6RcBQMU22Jd2aAUJgizJdr8FvE6pOYWqKsScivGqU6ZLz5BqQlcd5eselPWyzGHD1MKrUPED3Pc365QSgkVOWOSRRhtj/2bATdCi84bBRqFBsNaTMuq4FY9grBMnE54fhAiq7dpjRusNyPqdkLByhF/uqK57HI6WpLGNiEaSZaQr8go4pKZ4jDQVMqTOmkrxq6c0pDg9bfewsgCwjBkfeZhbRcMX0y5e77kaq4ykiyScQ0pyJGkN9ibOrvuLYrmNQedKZomknlbGt2Axr6OqvwL3Dvwx4GsJBQMh1FZQCjq/FnvFqvtgK0cYTohelemZ8js7JUYr2TyWguptkf9uM8wMLmVNihJCs/NHpVLl53Sgp51QEsf8yFFcpaGqAVMQovlXoVm1cVbH+C9EFDsEe5IYHFHp8UB2o3E6taGsbRid2pxXjCpTRpceWU6pSpZHHOz2eKqFzwq3uXZ4i5p0+eIQ+oHOtatMuZER1ib9DtrSupjDrsy19oRflDButgnn0X4NZvYn6HLCem8wEVik+Y/of+dKpZt4kg63dKnjKV76NMthysP09YohgpqUMY/czhau6y3DsZRQhz1+dYiY8ca87Go0kzXHFgpk+UccTrjk/6CUdiGKKXGJVEfZncFCosVI7/MhT6huDZYXS5xNm1KnTHRZsiV20IIB4z+4RUTeYtw7wF73inxRYZmDPA2KbX5kK5cQbvfYj67Jjx/QE055GoacimP2D/J00zKTM2QaX7CnetdNG3CWlDIcnMqqkjejVgVqzRPyzx/TWH3uyOGYwlN8qhfTrgsZoyNMbdLZbTWAn1T4qRYxlwtkfxbLG5c7h2LXL3/HGm3TM7MiKbPMT7eYVEaQMfjTi7PuJFDXw65PZSY3zXQQolLwadpbfGrLzgv6+SOmgTvO5SqLhfzBUsrw3KfIg+PCPpD2k2RXSWiOhep1UucZDP0kUU2mDK1n3OeM5E0CWyH26/5bNyIhZFiTW4Iux5C1mTTG5DtdJidb7HrU15WZzBsceHV6YbnPMhHCFtwDgx6dYN0YyM2EkRljiEZrPsLfGlJs2DSs3OsBQX78hlpNEdZtVFEmTDXw6mZDG92KKi9H55/f4y5/kMRpIRe5rFKDzDDF/Dg14gv99nKJkXDIlca0yKPt8ozmWyQ3zvn7nmOJ3Mfp7XB9jZs1xH5gknXzUjnHuVAYLFI0YQFW8VBkvIUzJCDYIRoZgh9nUNly3RpslteM/QiLqyYlnGBGRlsXBM3jfBuHHKVmJe1a/ZPZM4NCbHU5u3m66Qc8RN399H9Qwq5UyKjyKqY4pdTmv2Ua3/E9FxFns5oqR3W+hgrV+ViN8UWXG5fg+9FiNpdOsYcrZAn1FqsN2saZspUfo3qek6prhCJKwqnDWLF5NNlkXZjQFozmEy/gXZ6TdZZU8dA6O1iNRcMVgHNbxmY3jlTPcFxpqh7Abncm5TUb/OyoXMrHuNFNqPzLi1lzsg4IExCstaa7TJPdjQj+8hHq4iEZpk/t9CJoi5Lv8ayNqE01vCmORarHRA+oT2fkq+9S9USsd01q7bCvVChZznc1pa0BZHCYkluM2Hi3sU87pFPOuxdCdzkx4jyikWujLsK2NyF43UR5X7GVD7kgT4kHL8DNz6LZopbGFORFGJD4Ej3GNW7zCIT++4xYpAgB/sUChazW1Wy2xveWu0yUjxask5241Mvt5m6GlNnRn67JGfv4KlLSk6Kd25hqWPCsk5tustWHFEVC5zOeuQkAdUOuQpeY+b3mG/XGOQQ7RzSbZll8ga74Yog25BdlfACiUwo06wkbEoXlLL7lDcDUiVhXi9R3Uj4qNCaY60cbmYz2uKS7zxNUaUiYkWhENqYi4RttEDbq1DbLPFrOoUsojvc0IhECmQshR0cv8oiO2PVyLg3zDBzE1pOyKz6gwuPwBdEBNIQ5vNdSsmUSnzE1a/HlAopPWVFVZNxFiXG6YjbpYCKZ7Lx1gxLGbmlg9pXOFML7GsB0VmTddwnl7YYv5yCdk1RBtkzma8iKpjMGhbLOy9pCjOMsIx4tYv31TlJ9pDafIEgGEQzEFYGmtFH7eyzXMd0VvfJHWg060NYFKm6BsPqfSTnQ577Z1ihhtbdslw9RtFS/NcbFAoFgsNbcH0KgkpcLjPLh7wRTelN91HKGfbrJaanG4zVkptKG/PBlvQyY3OzIIiPaO7mEMSU2N6n0Gpx2VjxVSePvkmY3TlGu7LIJRWiRYVF3Cc+nFKLbHJpxKQ44tAy6MZFdspFpDsqk6nPKniH/OgaJ2eyiAXutsDp3CN9MsCqHbDayTC5JriqUqnus8312TNtktqa+dDFyMfY35Yw7o+YSTbFwMSya0jGIbmgiBN7OIWUoHCFuRDQNZepVUO1FJZVk/7Ch7HHbV9lm4yxBQ9T6ZBkRdJcSCVzqWCi7E0oXu3Qt2QsdUZdtzkvxzQvC1ylFbJmgGZYhPWUWvcufWFGOWywr004rwjk3DobaUTD91g6Dutri0J7TcwN3/K6ZJtdVEKKcYluz6VSzZiFd3j9dEJyP8dHPZ+4MyOMDrjZhGRajgcq5NZTBv6MxtsjsscBC/0ewSxGFOeo9QrHI5XTO3WM7af0ty0WuSuK5zuEswLevZTMilk/E+lNTykoTYRbDaKBTbjRuBPsM76zphfsIIcDVjOJc+kK/Y2Y/nhNfSIRSVV0EVajgCAfcpWzEG4E5jmRemHIY/JUVyteOgqH7Qc0+lM6Q4W/90Py7wshAogpsXRJvFC54TlukjGz76GvQspGm2dhiP2gxGgjUjF9bj+ZEGUlXnSKHBk2h3GI7Vi8KIfYswLp4grNh+7LCRNJQwnXGJU89ajFfpbjbLjHdhuyLgmou5ecr47x1y45bUaxnXLl6VSPvkon6SGEE3wrop1uKZVUhkuBzJ7wYqGQqN9mHQmcHK45HGVUsyuq9QbVowoX4TMKmsLwIkHdFnBqXQJVxlo5LIo2eSVitJ3AwmbPsun6Gk0nT+HmmrVdoH5nxtCMmV96WGoL/WzOhQ6iEzKrbCgbBUarp5jVNygnGQPH5417DrPTmOFRidhY4PoBM8Gm4lZQCjLnTyXEJGaWZbRRSRYmZWFC369gjqcsih7+ukfmlpltbR5pGUn+kn7XJC9fc77j0g5MeicjNKnISqwzi1MO9CLLxpzx8oaaCmybzJZb3khf51r+iIorU5ZVxh+nzFoVjHaN1e6Cc8/BXgVM1DxKsEE/D7FupywDge/FS3afabw0uhAuCBZ10tIa/YXNuJVQkjSS/ga/IFPIrSDTiLpd5vsr6uNDyqvnXFtr5OoRq0TGedfFykssohhNbNL0MzacY84bTPZH1I2Yp5VbHPQETqtLdro1tvsRuYt99gpwuZhSr0n4Y425UUNXBeTpV0l2xjxqaFyst5T7O0TWnH4lQrV8nEIF0TMpNjb4pzH5Ox7BzRUDoYUhpDTzLmstoSJ4zJw1uYLA6/kK3p2fZnxR4WG84ldWMZqYcDUcoSUFxhOHhRUgHgxpCYfE8y6+c4gt9sltD8n8HTpLSKIFzTChS5+wprO9yf/Q9PtCiEAYiTjFjL1bPu6L27ixz20xwcgVWe9L3H/+lNPHOXbjBs2vqDjOEX4kcztaETsxi6s6i70F0vmaWqnDQj2k612yf+uAipcnJSB3kNKxinS9l+QGbbbFEo2nHW7ecqm5KoWDAFO9T2ee0s5yOFkPoRDApkUnXVI2V4zVDaVRwDbLuNkbsOvfxpBl3t6KBLLKp/cT3rse80mvxN30Hu7aoqJX6RREQn2FLwTc31bo2gGFCniOgrSIWOQvce4GzH/nNTLRxMwNeBkbBHtr3LKDNC2Tr7oI4hR9uCLlFueVDdLJO2TlKb1oQbElM+2bfLLQKToh7lAlV8vB2qTYFJlrp9yaR3zUy6NECuflKapYQBy7aILEYubjhCrzvM692MMviHgzH9HwmGdbVLODe+YhFRxib4uci0hHMnl5hhb0kZdFKllIWjtnYz6nKtt8qs/xuy32qPI8DHGLV+T7VZTlBYdmgTMlz+V5j3cUj9lXYlK3QLou02gfMXD6+HkDIXWRl2XcrEpci0iVGrG0xBVrrPIN7O4pY8kmb9vUbR9DaxLUIsKcgRa4XJgVfuLJCT3vbfaSMx5vNCIk6vWYxrWGpW/5brKD24yorWZcltYcJke83GyoZLuoRp58OeBRt0xFt3l5P8Nwr/GKCfLYZCPnCRZL8pmOrp+Q+FWmooW0ncGTDKwl1qCGUppgCxqlksj5VYh595BK/YrKSmB52kHSY+bfkem+63I38TGTIlN/zj3VJ9HyjAUPbXobtarQVicMBw8R9Awrf0ihOCLwxiznBVStjl8LiNwBDzcya3FCWC9yUgvhN35w/n0hRCAjZa/n4W1VghAObZlVYcmNdExjvAXpPqVVjeh2yup7a0ZVmaa8IJMNbL3MujIhrdlU8iqC5bCUdUoVlWYlYPCJxmo/Y1cWcNIGon1JtBjzQFFp/XmNTvHPYOQm7OfGPF5VCO0x7VyHwJhTcBt8hwLGr3f5zvQanovkKwlHQ41KZLHqTEmWElG1AckLGtvb0G5yy9miuFUWQZUHR+cE4xapA3bmszEEFqbL6SdnHB/5FON9ZNdG1fOUdwPExGG5nKOnt2ifj9gc5OkszpnrRXYXOl5RZC0tqG7XjIsDal4FQdNYbAROpjaPsjnxuYqqSGQGqKUI72rF6lbKzdGMYSFC/06VhtxCqV8Si23663OCOOOrhweMtxFpXqPmRCSWynLm0Ny5h5G74cgtkezqNK5K6K2PKJy2GWYpHxUSctcNZuVvc2tVY6UqLPsDgoMOtw5tlBuVw9TnZH8P07zAz5UwlAK53DWi8zpKtkaSffK6YEgAAB8USURBVOJMIC1K6Psy9et9zKFDVTJQU4nTKiitDf5FkUpksVFc7gcpLw6q6KZDfQIrZY6kHDEmwtOgIq7h2udqsYeqXnCxPURTY3Z9lUTyGVdPmNdF1ssLrKuMSlgjOtIplnxGJ0VkZUS5FDAfpmSvVUiXJyDKNGZzTsIlfk9FvGPyqwODVn5BXVdIvQva7j6Lmzqf+ud0IovdksxsaLKtKYjjkKwpcO6usU93KXR00vGIQm2Pm4M+BwE4oxWmtWFZHiFelukpGnnBxV8apEaEYo1Ypwm3ug5jQ2M092jmmjTVNb+ziTl87ynliwpnDQ1ldZdx6FIc//AfFfmvfCvxHwV5Xc1+5uc6aFch1mEOBZBKLcYv16TZDrZ7Se+gQid9iXG9z+LWfValC6QRVPclqvKayxik5wpezqCEQLUZM3BSDClhrj3iPWWNrsTY1QY7b32VYn6JFRuMn825ym54q/MTbJoLPn5eoBUsGWvXeC9UXhZOsDIJxnlETScuRzwwZSpKCauh4OcinEWBN2pNwmBN3ixzmcaII4U79QrjoEveOmDwMkIyLzBfjxkoFfzfHLO/s8JL3qRcK0HYxWmWiF/6jIWQQ1tDsSaY4hG+f8lMUhilUK9YrJNrip7E5LqIEwvsG3Pk7RQ53GfmX7NUNPZpcKYMiVUB81xmqUgsQh87HCIehyzUHNkgR7aroUx/m87juywPakxXT5DiCvt7MqfxiPa2wMQUiAIJXahTGY4J0iVKu0hd3nCmLVh5NrfUlEHXwHYq6PKG0XERr+sh1deUy/ukzgneRkdK8lTrKu0biZv9Euq6iqeOWROg+RKScEEh3iEL99gspljiHFs0WJkzlDsJ61MV127SWGxhuCRrWgjBiko9zzQ/ZihU2KQX7BtfoffBCNuKUAdzNu1dQmOLolposzE5t4xYHPOkpZLfHqA+fUq5VcNZH5JVBqSySly7wVjsI85NOrsR11OJuX+GGxu0q1N0r8S0sUdLvmE2EJCLTfD6KNmMXHgPN1qwEW/IKQ3mxhwplMhPQQhq9L0BqTwFL0eQ6tSnCtt9jR3pnOvFO+yIDm56jVu26R5FWC8VyFIivY99U2JHbPC+GFDaeOyuxvR2JZyWQ/bNCt3E4/CNApysccwZL4tzdkOdf/T3n/zhbiD64yARdZ5PWuy0VTz9Ck9XkK8vmYd5zMghM3Qcd85lw+Tdgxph+Rr5pcJEAO/SZGjcpXp8wkV5SflAwZSLqMs6Xxdb+A/WlPw2R+oVws+2mYYa4vMVn0YpsRhSryqI2hHLcoYoVSiUe3T/QUzGgMJulduyhKwdk5WvOXbb3CgDqli8kGOKjyVyushqLfJhs49S9vFOP8GW9tGGeR6rA6LcEaSXNCyXvj1D/HZIXFLxPImX/Qa7JZ3ZckRxz+WFM2EvEXBXEePA5PBsxo3tYGsWdNZUuzKGY5F2IsK0jllaokUFLhKBTFWx4y5avkV53mNWWmEWD5g8vsJ7TaUQLDh2FH5r3aboDrEvBSinZNuExU2eqCMwX1ySsxQSp8rzkUwpb+ONThEOO+TtPHEPhBLomcz1VqSh2WRdCbcmsrJbWK0uzjBCr4io/jWrjgQfVRhVZeaWzUP1gK52geTbjPoi5fySC/+K5rCD1JDoZFXMpcdWO+XmKMaYrzDdFv38At+1KD2ZMM3dJYqWGO0cJBHXG5WHuX1OFlOScQOxfI3WqxC3MyqJQGa7WKLCWB1SlQJmzpSiZ9C/IxLf9HE2dyn3Z2ybJYyVw7B6jhWqxMsRe7OM89yU1kGebz8domQFdm4rTGcug2WD+45AQQ9QTYtCOUW/fkla0ujnMuJsSzVOSeJjfGnG9YuIWlbDkCP8PYOKZJJGbxPdzJjnDBxpghImzO1jGqU5I9FlPpfwiwalVYMb45JjwUAs36FQ87CelSgnGXrOwYk9ku/4GG+4eFaFu+U6kr/BsSLWVsLdoMY0lwOe/MD8+0KIgCnHlDc6SWgThSWivE9ekCm/1WMY6OxdyYSZSe1lwNntK0qZi188BnPAYa7AqZqDrMBbP6Pzdm2H7bxIXMvQxTV6ZNKVQwaFIuXJjIm4y83mkv3Z11Baa/K7BYobhb5pc2+mUK/uYr/+HDv35zlZDjF7A54bVzQkg95ijCNMudgpEQwHjIVdBqLCPf1jCr1dkvkeh4bPdSWhW9lQcLdYC4lZI0TwMwSlhqALXK8MascZQsWl3/sY+bKB5eU5aIgopkc9q4P8nMdLjbpXQNzPk4xFIk1nVhnR6DVwE5fnixo7Opi1EoYzYVfZchVtSNQaarJkdzmjqRo8kcf4L3d4PnW4s1umKYyZNpqUHZ/rlUus7iLuVNiRi2irPJu8RTS8omZGLPYfsM6dY20TQm3JqriB0332brv0npfRbqtofQMxUKm4KldZyObCJD72MFZQlCRKyRUfiBaiOaRcD5mdO9QrBUKlRLqYc9gJ8KyU6+GE2l6R1K+Q3OS509wwXnmooUslvcu6YmPaL1ltGiy7c2q9InZpxDp9ibYxmYp7kHWIy+ALQ0paHWc2x4u2FI5EnNkGuR4R6HXaI4M0f0Q9M0haMzbOEQv5Jc7W5/qFyd6Rybm0wl75XDo9tq7FTjGPd/KEaRVEReIm9xBbfcILQaQ2WLMV6mQL0OYRvjgg3XYYHEBJd2mOm2zLMqW5QSRdYszroHT5bXMXww8JmgH6VCDoKfiHQ+ZotHYCVuGMdGiwu06pbhyEwzYJEoPWkFJll3wTzF+p0ihU+FbQob63RI/HOOYRy4VNrCbIhKjeD6lLzhdEBCJB4IH1GCd/CKGGN5e4FECNqtSyhKtSRmm8JejY6F5EFLXJ51TUeosCr/GLNZHya/vMhw3s1e9wlrc5Eg0WW5dZeYKdqCSCzPikSNrYYikJV/lPsM7GfKRIRDcuyUczno5zhPvvUHKfYbxwWYkKqh1x596WaZojmrocLDrME5Vqs8WsHFDbLOn7LbCLmPMX9NQBk1GH249k4jBkXSsyG/kMzS73qwUEb8Y7wS4fR7vEfYvc8pRwekbQeoODaZFTZUBs6vjx2+xbUyqFDadZhhi5aGmKt5CZjFWyRKaQnDOrGtgnC7Y5k+vVnNxml5tHUw6u2nSPt9QKNul8H6m+oZO6yMUFbvYac3dA1plRvYlRahWCdIpAkVacIGdTKncdLmKF2+kZXmiSxTIFx6Iu73Py9hw12kFvpnjZmp3qAl+4SzAvIscui7rI/ipklJNJZZllTmfH2iJMEqJJib1Knul+grL9kFKpwtjIsbmZ4zJCDets3CPkesKHikguF1PQPLbhjNlqSS1psOOscdQMcTelWsuYpjJSBdQ448jSuBzHHKgJ3xIdWo0yq1WAmKg0wrt4kwuGL3Wsww0NSeS0ErFnpCjTBZqRo5ZB7ucMOhch7cMSN098AnWPVPJwdhI0fx9jPEGQBPSj7zJ6XqJa6bEQ1wSKRkvZ40TYstetYdlTcpMKlnwLobBg5swYyw6XPZmGuaZ5ndFsnCFOj4gOa5wMt9QMldymg7vbZbpIqG0egtwgeiQSmQt2lYCL5X3MaUKh/YxF5hE+CBC6xzQlqFZUhI3C2dmSolRkrRR49txFsmzg6Q/Mvy+ECMRZwJV7l7lVpLCeYeRTvGRKQzym9MLhJnUp37mLPk6Rmzp7epX8N2oszRzSdI2sZHjLLdvOkuUnOUpulUZzxbwq0N7+GdpbgYn5klZ8i7SiMB19Ey8n81taHT4ZIvsik7pN0WyD2kVRmoThCbePR6higXBmshnm8EOByABBiFnXa5S6YzrOLpPyEEdyKC1LxLsZRmoyeTpALd1lNA24u/QIW3kuhlsKhRbbwYAsAPHBfYy1QPH2a1y5U3z/DBMbtZ5Ria+4SgNsoUU4DhBSnzSNWBghYiWHFbs0ewXWuQ03+z5V74CRkaddeoktePRGOcxsxLSQUSjayFeg5B1mLwoc7i7wiyX6E4fQ2GE3DgikPaqmyzLMAVMSV+J1Tcet5ykO77Gt3xDkAoJIoKY8ZPJ0RfzGJfGHIu1WgaQ/JtJXyK7CQTzkKqtg1o7QtQBxMcHbygybFhvJIOeOUFcq6TgkKzlowyVpdkpc3GGhqqzKQ1oVh8lNDTd7jtTf4abt0nLqLLUVzYnI0h5h1zWkC4tKIaGLhLC34MlZnXq5xzLuUN1PsasZoZzjxhhSEEt4QYVZO4dZ0Oh1I2q9gKizx/RqS/uuQG0a8yzKE0lTXpx4hOYu7zQMnqtragOBtFrkWNwi1zQ++tRF1mKerErU27s4jkhhI9AyPVxpwHPLRA1OSWelzyoQR8dM9vscPbU5kUYs7QYHS5Nh9JLC2TGF8gjh0zLmT4TYyzuowpj+XGIZTiiXTBLBJh1dsp5E+OKQ6FsR1k4eugbHDZ+4sUB/OadXUKkd54gtn1sXJqumy7bCZ9VDfgBfCBEgExgXXiL3JviFkM11imjVyU5uOLh1zMM7TQS7jB8dUJFlapLDNueyiASkaZ+otMe2VcCenjK9U2T3RiNW79GqviSeXHJzkOMsayJ8+oJhP8IsGEz6Fj/d/oCe0+Y74z5v+3CBQ2NkEQcm/oM630vrtDYegrLP3fqMvjBiXGxRXgzYzEbU5gpK9ZC6/ZTrjcryfkTD2scyXPKOwnl6TX2vzpm+RU5qqGqJ0UWEXauyv5L46Op9jFaFqtzjq7875ntFgTfTKu9PU3YOupQmOtdOwNK/ZK8cY6m7LKMcoZ+ynPTxcnnuv28z1nzUiY93xyFevYEcf0SnVmNxIDC8HiOrMi0jQsr2kLwpya7G5jqhrKqUrQrCNKKSm3Azh85G50p1eTNLGBk2z8OY3FWP9GbC0qmyTJcYxxHKTh97kOKUQ/q1OjtLl+1OkfB8hb9SiQtrZu4c3Y0oLA9ZVd7n/sUuzytr4oGNmAa8phzgihkOp+TTGkNvw6W6oHBTYLzRsBYSptok7kiUojaxsMDs1egfCESXLo4VkJARJiXul8bcjBZIjEi7eyzuz0lHMmo4R5+WqGcCiqjiBhMOmguysEo77jHe3SO7vqCp+vhDCyHvkdNmNKYCT3WQl1M2uxmFfIEwDunNQxx/TXtcpn5gETp5opJL283oyylyzWd9sUcnLzD1IFzWKWsi6o5L7Xsy7wtfQz8ccq8kMJqtIQgQZiWihcpu7SHTzsd0BzpptKSe5vFZwt2QcBWy1jXsrcsk87k7tPj22mdvGLN+MyW2PuXiKseBrDB7FuMYcPRoztMwwA5U3l55/OMfkn5fiNWBUsXM/vTebWrtA9bmBrURouYfUtA1HBL2/JBhx2N/LLHUFMpGlXy2wg0tUvmGRNnDKcBi5JOtHTLHIxdoZA+LzD5ZoRpzNpFHfaYx1QXwDtgtdhnKW8xihx0/omnFn13VVlAwJweknRzMr/G1G3rePjmvj6BJtEch9mGZUxVUP6AufIMwPeek7HE82UGzzmi2JXqnKokFtpzh1WKkszaGlLE2NUJvhba3YrGNcXIZh+sZFxvIZxZC/ZjDZ09wSxZTy6K8dKGdIEYBO+UD3n8ZUz5M6HZVGsYQO7hLXn9KX68QbBWKiodmttgkS+qJTMqS1bJA6WDJldjh4c2Ws90CW1cmyT6hHH+FUF8xGkzQixu8C4VWU2V3lfFiZVCwa9xUl+SVCTVHZKMZBFmO/EpgtOziGQWK5YDm5pDk1jUX3iXmJZjyAYsoQjYj/LBN0p6gOiKDRYO3Mg24xtoGbO7sk6wjOjX45kChGff4dNFkT3YJ6wlVeYI2dnH0PGakM0htgrXM3dpTzmevYx+MUWOZ0C0RTAS2+xsqe5C/mrBNI/ylREgepbaD203YMSYs812WssreOCM/LTKMHSaiSjtVudEDzBCSusOwrHHYy1HRXaaSQhjWcPIm+94pYUFjHmckSkwY5GltBdbpFTtBjSfFgJ3rhOAojzquk44dro5izDThMlWo7Si050ucx1vUVKFYX5ElCeMbjbXdoF9as6M9Y+jplK232AxDrJmOpz5DTYoss3PytSrh1YBWvsxcsRB2HOKnMWYzz+lGYCfaEnCAM78iX1WYJzP+yT/4p1/c1QE1M5m9/acxSzK15RJxOGOepFhhxo0WYqoO8dUaMb1DuTpjFQTI1jGNjgZCmcFWo97XiVMFi4+IXYtz+5Lses3B3h6BoGFpCw7eesThQkTRI/RxlYfvRhj7RWq/XSS1Rd6ttnCKGX6hSlFOkUcd9MN7jJ0a2eUFjxcpDWXKSbqmWPBJWjEfnnd5d3/FXaVF2D+nIesk/TZ+LWRXNilNv8tF/BV23vHpL2L2M/AMj8A4pijIWPkLricyb+oltlsfeR7hh2WU2YqCZ2L7D0g2KdbtFdLyNvvihxQmTWr111hFj9FyAm25wE1cwbb6lDcxjjymkN/lZvOS7VqnoA65HtWZr68ZF4roq4S2GTI9eZPN3gWLTYFsL2avp5GZLnosoxn7RIVrkAZomxqxInJmN1HXM3ItjdKlhH67zdlpQuLHLGrn2AuTgleitHVYeSOKnSW1xTtscxqJ1MCbTQmVCcuqQinJ018XyEcaU1Mh70YEsyVmpcyDmop/NqfQFqkvS1yWc+hZgbE4IHVsJCtlob5O646Ic1pHUEQ2t7fk7ljYJzr6yxlzoUxusKFQFbkR2oTpE4z0iDgYo4UCpmNwrRUwxS2DwCSVRMxjDXmiIRxGiHJEo6thTGB0WKJubNj2R5SCPaZiHmM5w7JCrhWDA3dFZOzjL22GpYxOT0YoN1HjLdNwRMmOiPMN1OkJP9U5YjtNuDhVEaqgRAaz7QjjuAS1LfbCRueCcnoXzZJBnVGXN2SHHUKjxDoIsCfHhN0PyLQOz7QVwiWYK51tNsSYFtjxPmAol5h4MocdhcGLGfXcF/wuwiCNMa6uWMcGDXHFSFLwh+dcJzaH7fskc5V79l3MvMimLCKc2eQO6syXBuqpSVi+Ic5GlNcV1p0augXVsxz1N3Waik998gDX7FM6bNK9l7C72iA+3CetquQRme9JKBWBSRRSiku49S6LZzlajo+8tmnr53SjHAfKjHxRJJuuGZ9o3LIk3hu7XFgppuazzmlsj0Ruda9Q8gK+sOBkZnHlTmDtISUO0X4T87zKLL2miMBgU8c2VdyVQPHWjCTJ6Hdq7K93sbQQo9gHe4exWKeXdtn9eoFxLLHwnqFObrgM9wnTBvnrmHVHZKFL5EpLFh/nCZstTCEjKhiMrgX2CiYToK4PcJzbqGWPsGdRMQe0noScnRq0OzZLNUdwvWHHTlkoOk6wpZifc3ilsejEzOZnxPkOs16EUZER2yr+uYSlFVhuJbyGjHTTwzAMVsUXfNpTuaMcszBMsk3IbjfipW6xn6ZscpdEnsTo5Qq/UeTaj6k2HI4rEecLC/e4jO5kZNsu9/Ucw3KMeeWRjjsI5zfYhzmeZWXuxSKVmxGPRRl9KTNr6wTtiNe2Fqp9zpmYY149Y+plqJs6an6IdSliJBB6I8yjFqvFNZWKhr8sIWU6WaOHaR3h2Jc8CW6RZhPs4wRvJJBTRxSlW4xyS1TVJi4uael5DC1lqI8Zzcu0swGSumbS/Ar5tU81zbgOA8rPy9TKIXrksjqwGEzaFHMblss8BOfUijMm6ypuaUxu2EDzW8zFlMHG41h7TN6psGjXITKxvJSzSo+8YNJzJBbLGbp0BAWHxsUNiVXgsrQgfpH7ofn3hRABgRDDWXIwcvCNDY48pd6qo7b2WAVLrCzm49mISmTQ+96Y+JnP+fpTSqcxUW3FzXmN22bME/efsBkc8GiSkWgLur8rsVrv8OahSE0M0L53Rs2osjGbCNU86tTnZTJlPc1o36RcrzRS6YTlbyxInDxvJnMia8rKF/jI9ajXiuRGItuDDVYQcD0o8qA5RQjzLIcJW1chqsCzUxuxtUXdqriqgeGvCTKBkphx6ka8VU8JZiUCeYGET7gIKTYzXkY6D+Ip3OuQfDzHVBskmwKxJXLPSem5Nl6aoa+GtKolMIAn58R5EX33gHTlMRS2HG2aWLtXlPN3iU+eEZ4ViI0Bmz2N2rVKlzK3w08JKvfQVZkoyXFZBWWps1w/ZqU3WFkxihtSPJaxNJXNQkZUXpIbmphmmYWccD8JuDBMxqlK+3gAa5Wdmky0veD8tQbFZQSZys5bFt74JW5FRtMV0o2Inc44i3WE36zQNA1WHY17uTWqHaApEt1qjvrE5jx+QjiSEZSInL2lOEhxnApu8Ro9NQlLMs1+RtfxOb3WcFyXo6KMcvHZt+hQc5gWK8TfPKOaJIzqRTQ7IZGXTJO38O0xzdhijkhcTdj+bkp6L2KtQNsrkWxiJrkG7k3E3WjD8vqapDdnZlR4VrRoRguWyQytdEMyUAnTNWauwZ4moimHbK0L5AuFyqMuvUhBW/fp+1tagUs3t8f2UqSQLfEXIfNAwjZdvO1DhGVEdOEzv+dwQZdyoYW9LjOYt8mPYmKjhWv4qNuYcBpzYyoc2g6LhUA9kIktEbcj8WG64diNEHZnn5UK+gF8MUQglFEbOda5FU+2Z1ScCp+KIJ88R3V7JLdrMGuR7fjMFmPUXsDM+yrDeyMOu/dYHPmsz6o0vJSOsmHysEXtxSllu4p2E/HJ8DfIXWucbwf4ja8Tjzaot77JsSAynA6Ry2t+Q7M5Uj1K/oyes4cU1fltltQLAf2cwl5RZxpIlI42bMUOSBabqsCvpmui90Mqb6WIkkNkOBT287S3TRAMvE+X5EyVYM9EmZwSJWV+Z1WglMlk+TGCsGGeWSw8iWMhQ96UqF84bO0cUj4jnxZZXYso9RGG+Yyu+yZFrcVHG5fmoUL1ukM8jMiEGc5KpdRasNGmTG0LYzlCMAzu2T622WKSKBCoGJ/At1sxbyQ31GYCJ8WQcB1h7Xc5OG1wc+1hPSwhpDGbYkB4/RxHC5DKx6ymGbn5DYWHLdRoxZvDJSfKLWbfa+N3hlQXORwtxNodUU73WReKFKc95lcCx9VD+m7MueGTXzlUsjLSG1XwZzRmuyydDVVdpyuXWW/7jCUT+7SCJ4fcsRucVq+QQgEpkaiHEd4sRnhs070z4Z1VnpePhhyNQiLdRzx3kaK7rMop5afvMyhXMTot2t+2WVRPKagCO8GvMy0YnBp38ESdN4dzth2JKkOm6RFCaUkaqkhPZY7zCVe6hah1Sd6S4OM9DE/mqVngKGhRdZ5xIygoQw1zv8ZICsl7KotlAXs2pffdLuqozuCrS/TogGeSi6d7tLdbzH5KK3mbUP+Qj1ih6QmVyV2KPGVwXqXmlaEw4m5xwzxsk6+YfKs+4vhFCLaGXisixw20pcr8sMfWqWMsexzOGiT+CFGIWU5u8cOWCL8QE4OCIGyAF5+3H39EVIHp5+3EHwE/rnHBj29s+1mW1X6/8QvREwBe/KBZyx8HBEH4zo9jbD+uccGPd2w/iC/Ebwx+yZd8yefHlyLwJV/yJ5wvigj8x5+3A3+E/LjG9uMaF/x4x/Zf4gsxMfglX/Ilnx9flJ7Al3zJl3xOfO4iIAjCnxME4YUgCKeCIPzNz9uf/6oIgvB/EARhLAjC4++zlQVB+BVBEE5ePZZe2QVBEP43r2L9RBCEtz8/z/9gBEHYFQTh1wRBeCoIwhNBEP77r+w/0rEJgqALgvCBIAgfv4rr33tlPxQE4f1X/v/ngiCor+zaq/3TV8cPPtcA/ijIsuxz2wAJOAOOABX4GHjwefr0h4jhp4G3gcffZ/sPgb/5qv03gf/gVfsXgH8ICMDXgfc/b///gLhawNuv2jbwEnjwox7bK/9yr9oK8P4rf/8e8Fdf2f8j4N961f63gf/oVfuvAv/55x3Dv/TP5HP+g7wH/KPv2/93gX/38/5Q/hBxHPw+EXgBtF61W3x2HQTA3wb+jR903hd9A/7fwJ/9cYoNMIHvAV/js4uD5Ff2f/Z/Cfwj4L1XbfnVecLn7fu/zO3zHg50gJvv2+++sv2o08iy7PfKwA6Bxqv2j2S8r7rAb/HZt+aPfGyCIEiCIHwEjIFf4bPe6DLLst+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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "generated_image = tf.Variable(tf.image.convert_image_dtype(content_image, tf.float32))\n", + "noise = tf.random.uniform(tf.shape(generated_image), -0.25, 0.25)\n", + "generated_image = tf.add(generated_image, noise)\n", + "generated_image = tf.clip_by_value(generated_image, clip_value_min=0.0, clip_value_max=1.0)\n", + "\n", + "print(generated_image.shape)\n", + "imshow(generated_image.numpy()[0])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5.4 - Load Pre-trained VGG19 Model\n", + "Next, as explained in [part(2)](#part(2)), define a function which loads the VGG19 model and returns a list of the outputs for the middle layers." + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "def get_layer_outputs(vgg, layer_names):\n", + " \"\"\" Creates a vgg model that returns a list of intermediate output values.\"\"\"\n", + " outputs = [vgg.get_layer(layer[0]).output for layer in layer_names]\n", + "\n", + " model = tf.keras.Model([vgg.input], outputs)\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, define the content layer and build the model." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "content_layer = [('block5_conv4', 1)]\n", + "\n", + "vgg_model_outputs = get_layer_outputs(vgg, STYLE_LAYERS + content_layer)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Save the outputs for the content and style layers in separate variables." + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "content_target = vgg_model_outputs(content_image) # Content encoder\n", + "style_targets = vgg_model_outputs(style_image) # Style enconder" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.5 - Compute Total Cost\n", + "\n", + "\n", + "#### 5.5.1 - Compute the Content image Encoding (a_C)\n", + "\n", + "You've built the model, and now to compute the content cost, you will encode your content image using the appropriate hidden layer activations. Set this encoding to the variable `a_C`. Later in the assignment, you will need to do the proper with the generated image, by setting the variable `a_G` to be the appropriate hidden layer activations. You will use layer `block5_conv4` to compute the encoding. The code below does the following:\n", + "\n", + "1. Set a_C to be the tensor giving the hidden layer activation for layer \"block5_conv4\" using the content image." + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "# Assign the content image to be the input of the VGG model. \n", + "# Set a_C to be the hidden layer activation from the layer we have selected\n", + "preprocessed_content = tf.Variable(tf.image.convert_image_dtype(content_image, tf.float32))\n", + "a_C = vgg_model_outputs(preprocessed_content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "#### 5.5.2 - Compute the Style image Encoding (a_S) \n", + "\n", + "The code below sets a_S to be the tensor giving the hidden layer activation for `STYLE_LAYERS` using our style image." + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "# Assign the input of the model to be the \"style\" image \n", + "preprocessed_style = tf.Variable(tf.image.convert_image_dtype(style_image, tf.float32))\n", + "a_S = vgg_model_outputs(preprocessed_style)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Below are the utils that you will need to display the images generated by the style transfer model." + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "def clip_0_1(image):\n", + " \"\"\"\n", + " Truncate all the pixels in the tensor to be between 0 and 1\n", + " \n", + " Arguments:\n", + " image -- Tensor\n", + " J_style -- style cost coded above\n", + "\n", + " Returns:\n", + " Tensor\n", + " \"\"\"\n", + " return tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=1.0)\n", + "\n", + "def tensor_to_image(tensor):\n", + " \"\"\"\n", + " Converts the given tensor into a PIL image\n", + " \n", + " Arguments:\n", + " tensor -- Tensor\n", + " \n", + " Returns:\n", + " Image: A PIL image\n", + " \"\"\"\n", + " tensor = tensor * 255\n", + " tensor = np.array(tensor, dtype=np.uint8)\n", + " if np.ndim(tensor) > 3:\n", + " assert tensor.shape[0] == 1\n", + " tensor = tensor[0]\n", + " return Image.fromarray(tensor)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 6 - train_step \n", + "\n", + "Implement the train_step() function for transfer learning\n", + "\n", + "* Use the Adam optimizer to minimize the total cost `J`.\n", + "* Use a learning rate of 0.01 \n", + "* [Adam Optimizer documentation](https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/Adam)\n", + "* You will use [tf.GradientTape](https://www.tensorflow.org/api_docs/python/tf/GradientTape) to update the image. ([Course 2 Week 3: TensorFlow Introduction Assignment](https://www.coursera.org/learn/deep-neural-network/programming/fuJJY/tensorflow-introduction))\n", + "* Within the tf.GradientTape():\n", + " * Compute the encoding of the generated image using vgg_model_outputs. Assing the result to a_G.\n", + " * Compute the total cost J, using the global variables a_C, a_S and the local a_G\n", + " * Use `alpha = 10` and `beta = 40`." + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-dfbcc4b8f8a959e5", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C5\n", + "# GRADED FUNCTION: train_step\n", + "\n", + "optimizer = tf.keras.optimizers.Adam(learning_rate=0.01)\n", + "\n", + "@tf.function()\n", + "def train_step(generated_image):\n", + " with tf.GradientTape() as tape:\n", + " # In this function you must use the precomputed encoded images a_S and a_C\n", + " # Compute a_G as the vgg_model_outputs for the current generated image\n", + " \n", + " ###Β START CODE HERE\n", + " \n", + " #(1 line)\n", + " a_G = vgg_model_outputs(generated_image)\n", + " \n", + " \n", + " #(1 line)\n", + " # Compute the style cost\n", + " #(1 line)\n", + " #list \n", + " J_style = compute_style_cost(a_S,a_G)\n", + " \n", + " \n", + " \n", + " #(2 lines)\n", + " # Compute the content cost\n", + " J_content = compute_content_cost(a_C,a_G)\n", + " # Compute the total cost\n", + " J = total_cost( J_content, J_style, alpha = 10, beta =40 )\n", + " \n", + " ###Β END CODE HERE\n", + " \n", + " grad = tape.gradient(J, generated_image)\n", + "\n", + " optimizer.apply_gradients([(grad, generated_image)])\n", + " generated_image.assign(clip_0_1(generated_image))\n", + " # For grading purposes\n", + " return J" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-0b5e78c25be54360", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tf.Tensor(25629.055, shape=(), dtype=float32)\n", + "tf.Tensor(17735.514, shape=(), dtype=float32)\n", + "\u001b[92mAll tests passed\n" + ] + } + ], + "source": [ + "# You always must run the last cell before this one. You will get an error if not.\n", + "generated_image = tf.Variable(generated_image)\n", + "\n", + "\n", + "J1 = train_step(generated_image)\n", + "print(J1)\n", + "assert type(J1) == EagerTensor, f\"Wrong type {type(J1)} != {EagerTensor}\"\n", + "assert np.isclose(J1, 25629.055, rtol=0.05), f\"Unexpected cost for epoch 0: {J1} != {25629.055}\"\n", + "\n", + "J2 = train_step(generated_image)\n", + "print(J2)\n", + "assert np.isclose(J2, 17812.627, rtol=0.05), f\"Unexpected cost for epoch 1: {J2} != {17735.512}\"\n", + "\n", + "print(\"\\033[92mAll tests passed\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected output**\n", + "```\n", + "tf.Tensor(25629.055, shape=(), dtype=float32)\n", + "tf.Tensor(17735.512, shape=(), dtype=float32)\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looks like it's working! Now you'll get to put it all together into one function to better see your results!\n", + "\n", + "\n", + "### 5.6 - Train the Model\n", + "\n", + "Run the following cell to generate an artistic image. It should take about 3min on a GPU for 2500 iterations. Neural Style Transfer is generally trained using GPUs.\n", + "\n", + "If you increase the learning rate you can speed up the style transfer, but often at the cost of quality." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Show the generated image at some epochs\n", + "# Uncoment to reset the style transfer process. You will need to compile the train_step function again \n", + "epochs = 2501\n", + "for i in range(epochs):\n", + " train_step(generated_image)\n", + " if i % 250 == 0:\n", + " print(f\"Epoch {i} \")\n", + " if i % 250 == 0:\n", + " image = tensor_to_image(generated_image)\n", + " imshow(image)\n", + " image.save(f\"output/image_{i}.jpg\")\n", + " plt.show() " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, run the following code cell to see the results!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# Show the 3 images in a row\n", + "fig = plt.figure(figsize=(16, 4))\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "imshow(content_image[0])\n", + "ax.title.set_text('Content image')\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "imshow(style_image[0])\n", + "ax.title.set_text('Style image')\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "imshow(generated_image[0])\n", + "ax.title.set_text('Generated image')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Look at that! You did it! After running this, in the upper bar of the notebook click on \"File\" and then \"Open\". Go to the \"/output\" directory to see all the saved images. Open \"generated_image\" to see the generated image! :)\n", + "\n", + "Running for around 20000 epochs with a learning rate of 0.001, you should see something like the image presented below on the right:\n", + "\n", + "\n", + "\n", + "The hyperparameters were set so that you didn't have to wait too long to see an initial result. To get the best looking results, you may want to try running the optimization algorithm longer (and perhaps with a smaller learning rate). After completing and submitting this assignment, come back and play more with this notebook, and see if you can generate even better looking images. But first, give yourself a pat on the back for finishing this long assignment!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here are few other examples:\n", + "\n", + "- The beautiful ruins of the ancient city of Persepolis (Iran) with the style of Van Gogh (The Starry Night)\n", + "\n", + "\n", + "- The tomb of Cyrus the great in Pasargadae with the style of a Ceramic Kashi from Ispahan.\n", + "\n", + "\n", + "- A scientific study of a turbulent fluid with the style of a abstract blue fluid painting.\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Free Up Resources for Other Learners\n", + "\n", + "If you don't plan on continuing to the next `Optional` section, help us to provide our learners a smooth learning experience, by freeing up the resources used by your assignment by running the cell below so that the other learners can take advantage of those resources just as much as you did. Thank you!\n", + "\n", + "**Note**: \n", + "- Run the cell below when you are done with the assignment and are ready to submit it for grading.\n", + "- When you'll run it, a pop up will open, click `Ok`.\n", + "- Running the cell will `restart the kernel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%javascript\n", + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 6 - Test With Your Own Image (Optional/Ungraded)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, you can also rerun the algorithm on your own images! \n", + "\n", + "To do so, go back to part(4) and change the content image and style image with your own pictures. In detail, here's what you should do:\n", + "\n", + "1. Click on \"File -> Open\" in the upper tab of the notebook\n", + "2. Go to \"/images\" and upload your images (images will scaled to 400x400, but you can change that parameter too in section 2), rename them \"my_content.png\" and \"my_style.png\" for example.\n", + "3. Change the code in [part(4)](#part(4)) from :\n", + "\n", + "```py\n", + "content_image = np.array(Image.open(\"images/louvre_small.jpg\").resize((img_size, img_size)))\n", + "style_image = np.array(Image.open(\"images/monet.jpg\").resize((img_size, img_size)))\n", + "\n", + "```\n", + "\n", + "  to:\n", + "\n", + "``` py\n", + "content_image = np.array(Image.open(\"images/my_content.jpg\").resize((img_size, img_size)))\n", + "style_image = np.array(Image.open(\"my_style.jpg\").resize((img_size, img_size)))\n", + "\n", + "```\n", + "4. Rerun the cells (you may need to restart the Kernel in the upper tab of the notebook).\n", + "\n", + "You can share your generated images with us on social media with the hashtag #deeplearningAI or by tagging us directly!\n", + "\n", + "Here are some ideas on how to tune your hyperparameters: \n", + "- To select different layers to represent the style, redefine `STYLE_LAYERS`\n", + "- To alter the number of iterations you want to run the algorithm, try changing `epochs` given in Section 5.6.\n", + "- To alter the relative weight of content versus style, try altering alpha and beta values\n", + "\n", + "Happy coding!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Free Up Resources for Other Learners\n", + "\n", + "In order to provide our learners a smooth learning experience, please free up the resources used by your assignment by running the cell below so that the other learners can take advantage of those resources just as much as you did. Thank you!\n", + "\n", + "**Note**: \n", + "- Run the cell below when you are done with the assignment and are ready to submit it for grading.\n", + "- When you'll run it, a pop up will open, click `Ok`.\n", + "- Running the cell will `restart the kernel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%javascript\n", + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Conclusion\n", + "\n", + "Great job on completing this assignment! You are now able to use Neural Style Transfer to generate artistic images. This is also your first time building a model in which the optimization algorithm updates the pixel values rather than the neural network's parameters. Deep learning has many different types of models and this is only one of them! \n", + "\n", + "\n", + " \n", + "## What you should remember\n", + "- Neural Style Transfer is an algorithm that given a content image C and a style image S can generate an artistic image\n", + "- It uses representations (hidden layer activations) based on a pretrained ConvNet. \n", + "- The content cost function is computed using one hidden layer's activations.\n", + "- The style cost function for one layer is computed using the Gram matrix of that layer's activations. The overall style cost function is obtained using several hidden layers.\n", + "- Optimizing the total cost function results in synthesizing new images. \n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Congratulations on finishing the course!\n", + "This was the final programming exercise of this course. Congratulations - you've finished all the programming exercises of this course on Convolutional Networks! See you in Course 5, Sequence Models! \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 7 - References\n", + "\n", + "The Neural Style Transfer algorithm was due to Gatys et al. (2015). Harish Narayanan and Github user \"log0\" also have highly readable write-ups this lab was inspired by. The pre-trained network used in this implementation is a VGG network, which is due to Simonyan and Zisserman (2015). Pre-trained weights were from the work of the MathConvNet team. \n", + "\n", + "- Leon A. Gatys, Alexander S. Ecker, Matthias Bethge, (2015). [A Neural Algorithm of Artistic Style](https://arxiv.org/abs/1508.06576) \n", + "- Harish Narayanan, [Convolutional neural networks for artistic style transfer.](https://harishnarayanan.org/writing/artistic-style-transfer/)\n", + "- Log0, [TensorFlow Implementation of \"A Neural Algorithm of Artistic Style\".](http://www.chioka.in/tensorflow-implementation-neural-algorithm-of-artistic-style)\n", + "- Karen Simonyan and Andrew Zisserman (2015). [Very deep convolutional networks for large-scale image recognition](https://arxiv.org/pdf/1409.1556.pdf)\n", + "- [MatConvNet.](http://www.vlfeat.org/matconvnet/pretrained/)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Autonomous_driving_application_Car_detection.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Autonomous_driving_application_Car_detection.ipynb new file mode 100644 index 00000000000..31940451314 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Autonomous_driving_application_Car_detection.ipynb @@ -0,0 +1,1679 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Autonomous Driving - Car Detection\n", + "\n", + "Welcome to the Week 3 programming assignment! In this notebook, you'll implement object detection using the very powerful YOLO model. Many of the ideas in this notebook are described in the two YOLO papers: [Redmon et al., 2016](https://arxiv.org/abs/1506.02640) and [Redmon and Farhadi, 2016](https://arxiv.org/abs/1612.08242). \n", + "\n", + "**By the end of this assignment, you'll be able to**:\n", + "\n", + "- Detect objects in a car detection dataset\n", + "- Implement non-max suppression to increase accuracy\n", + "- Implement intersection over union\n", + "- Handle bounding boxes, a type of image annotation popular in deep learning\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "\n", + "- [Packages](#0)\n", + "- [1 - Problem Statement](#1)\n", + "- [2 - YOLO](#2)\n", + " - [2.1 - Model Details](#2-1)\n", + " - [2.2 - Filtering with a Threshold on Class Scores](#2-2)\n", + " - [Exercise 1 - yolo_filter_boxes](#ex-1)\n", + " - [2.3 - Non-max Suppression](#2-3)\n", + " - [Exercise 2 - iou](#ex-2)\n", + " - [2.4 - YOLO Non-max Suppression](#2-4)\n", + " - [Exercise 3 - yolo_non_max_suppression](#ex-3)\n", + " - [2.5 - Wrapping Up the Filtering](#2-5)\n", + " - [Exercise 4 - yolo_eval](#ex-4)\n", + "- [3 - Test YOLO Pre-trained Model on Images](#3)\n", + " - [3.1 - Defining Classes, Anchors and Image Shape](#3-1)\n", + " - [3.2 - Loading a Pre-trained Model](#3-2)\n", + " - [3.3 - Convert Output of the Model to Usable Bounding Box Tensors](#3-3)\n", + " - [3.4 - Filtering Boxes](#3-4)\n", + " - [3.5 - Run the YOLO on an Image](#3-5)\n", + "- [4 - Summary for YOLO](#4)\n", + "- [5 - References](#5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## Packages\n", + "\n", + "Run the following cell to load the packages and dependencies that will come in handy as you build the object detector!" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import argparse\n", + "import os\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.pyplot import imshow\n", + "import scipy.io\n", + "import scipy.misc\n", + "import numpy as np\n", + "import pandas as pd\n", + "import PIL\n", + "from PIL import ImageFont, ImageDraw, Image\n", + "import tensorflow as tf\n", + "from tensorflow.python.framework.ops import EagerTensor\n", + "\n", + "from tensorflow.keras.models import load_model\n", + "from yad2k.models.keras_yolo import yolo_head\n", + "from yad2k.utils.utils import draw_boxes, get_colors_for_classes, scale_boxes, read_classes, read_anchors, preprocess_image\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Problem Statement\n", + "\n", + "You are working on a self-driving car. Go you! As a critical component of this project, you'd like to first build a car detection system. To collect data, you've mounted a camera to the hood (meaning the front) of the car, which takes pictures of the road ahead every few seconds as you drive around. \n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "
Pictures taken from a car-mounted camera while driving around Silicon Valley.
Dataset provided by drive.ai.\n", + "
\n", + "\n", + "You've gathered all these images into a folder and labelled them by drawing bounding boxes around every car you found. Here's an example of what your bounding boxes look like:\n", + "\n", + "\n", + "
Figure 1: Definition of a box
\n", + "\n", + "If there are 80 classes you want the object detector to recognize, you can represent the class label $c$ either as an integer from 1 to 80, or as an 80-dimensional vector (with 80 numbers) one component of which is 1, and the rest of which are 0. The video lectures used the latter representation; in this notebook, you'll use both representations, depending on which is more convenient for a particular step. \n", + "\n", + "In this exercise, you'll discover how YOLO (\"You Only Look Once\") performs object detection, and then apply it to car detection. Because the YOLO model is very computationally expensive to train, the pre-trained weights are already loaded for you to use. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - YOLO" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\"You Only Look Once\" (YOLO) is a popular algorithm because it achieves high accuracy while also being able to run in real time. This algorithm \"only looks once\" at the image in the sense that it requires only one forward propagation pass through the network to make predictions. After non-max suppression, it then outputs recognized objects together with the bounding boxes.\n", + "\n", + "\n", + "### 2.1 - Model Details\n", + "\n", + "#### Inputs and outputs\n", + "- The **input** is a batch of images, and each image has the shape (m, 608, 608, 3)\n", + "- The **output** is a list of bounding boxes along with the recognized classes. Each bounding box is represented by 6 numbers $(p_c, b_x, b_y, b_h, b_w, c)$ as explained above. If you expand $c$ into an 80-dimensional vector, each bounding box is then represented by 85 numbers. \n", + "\n", + "#### Anchor Boxes\n", + "* Anchor boxes are chosen by exploring the training data to choose reasonable height/width ratios that represent the different classes. For this assignment, 5 anchor boxes were chosen for you (to cover the 80 classes), and stored in the file './model_data/yolo_anchors.txt'\n", + "* The dimension of the encoding tensor of the second to last dimension based on the anchor boxes is $(m, n_H,n_W,anchors,classes)$.\n", + "* The YOLO architecture is: IMAGE (m, 608, 608, 3) -> DEEP CNN -> ENCODING (m, 19, 19, 5, 85). \n", + "\n", + "\n", + "#### Encoding\n", + "Let's look in greater detail at what this encoding represents. \n", + "\n", + "\n", + "
Figure 2 : Encoding architecture for YOLO
\n", + "\n", + "If the center/midpoint of an object falls into a grid cell, that grid cell is responsible for detecting that object." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Since you're using 5 anchor boxes, each of the 19 x19 cells thus encodes information about 5 boxes. Anchor boxes are defined only by their width and height.\n", + "\n", + "For simplicity, you'll flatten the last two dimensions of the shape (19, 19, 5, 85) encoding, so the output of the Deep CNN is (19, 19, 425).\n", + "\n", + "\n", + "
Figure 3 : Flattening the last two last dimensions
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Class score\n", + "\n", + "Now, for each box (of each cell) you'll compute the following element-wise product and extract a probability that the box contains a certain class. \n", + "The class score is $score_{c,i} = p_{c} \\times c_{i}$: the probability that there is an object $p_{c}$ times the probability that the object is a certain class $c_{i}$.\n", + "\n", + "\n", + "
Figure 4: Find the class detected by each box
\n", + "\n", + "##### Example of figure 4\n", + "* In figure 4, let's say for box 1 (cell 1), the probability that an object exists is $p_{1}=0.60$. So there's a 60% chance that an object exists in box 1 (cell 1). \n", + "* The probability that the object is the class \"category 3 (a car)\" is $c_{3}=0.73$. \n", + "* The score for box 1 and for category \"3\" is $score_{1,3}=0.60 \\times 0.73 = 0.44$. \n", + "* Let's say you calculate the score for all 80 classes in box 1, and find that the score for the car class (class 3) is the maximum. So you'll assign the score 0.44 and class \"3\" to this box \"1\".\n", + "\n", + "#### Visualizing classes\n", + "Here's one way to visualize what YOLO is predicting on an image:\n", + "\n", + "- For each of the 19x19 grid cells, find the maximum of the probability scores (taking a max across the 80 classes, one maximum for each of the 5 anchor boxes).\n", + "- Color that grid cell according to what object that grid cell considers the most likely.\n", + "\n", + "Doing this results in this picture: \n", + "\n", + "\n", + "
Figure 5: Each one of the 19x19 grid cells is colored according to which class has the largest predicted probability in that cell.
\n", + "\n", + "Note that this visualization isn't a core part of the YOLO algorithm itself for making predictions; it's just a nice way of visualizing an intermediate result of the algorithm. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Visualizing bounding boxes\n", + "Another way to visualize YOLO's output is to plot the bounding boxes that it outputs. Doing that results in a visualization like this: \n", + "\n", + "\n", + "
Figure 6: Each cell gives you 5 boxes. In total, the model predicts: 19x19x5 = 1805 boxes just by looking once at the image (one forward pass through the network)! Different colors denote different classes.
\n", + "\n", + "#### Non-Max suppression\n", + "In the figure above, the only boxes plotted are ones for which the model had assigned a high probability, but this is still too many boxes. You'd like to reduce the algorithm's output to a much smaller number of detected objects. \n", + "\n", + "To do so, you'll use **non-max suppression**. Specifically, you'll carry out these steps: \n", + "- Get rid of boxes with a low score. Meaning, the box is not very confident about detecting a class, either due to the low probability of any object, or low probability of this particular class.\n", + "- Select only one box when several boxes overlap with each other and detect the same object." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.2 - Filtering with a Threshold on Class Scores\n", + "\n", + "You're going to first apply a filter by thresholding, meaning you'll get rid of any box for which the class \"score\" is less than a chosen threshold. \n", + "\n", + "The model gives you a total of 19x19x5x85 numbers, with each box described by 85 numbers. It's convenient to rearrange the (19,19,5,85) (or (19,19,425)) dimensional tensor into the following variables: \n", + "- `box_confidence`: tensor of shape $(19, 19, 5, 1)$ containing $p_c$ (confidence probability that there's some object) for each of the 5 boxes predicted in each of the 19x19 cells.\n", + "- `boxes`: tensor of shape $(19, 19, 5, 4)$ containing the midpoint and dimensions $(b_x, b_y, b_h, b_w)$ for each of the 5 boxes in each cell.\n", + "- `box_class_probs`: tensor of shape $(19, 19, 5, 80)$ containing the \"class probabilities\" $(c_1, c_2, ... c_{80})$ for each of the 80 classes for each of the 5 boxes per cell.\n", + "\n", + "\n", + "### Exercise 1 - yolo_filter_boxes\n", + "\n", + "Implement `yolo_filter_boxes()`.\n", + "1. Compute box scores by doing the elementwise product as described in Figure 4 ($p \\times c$). \n", + "The following code may help you choose the right operator: \n", + "```python\n", + "a = np.random.randn(19, 19, 5, 1)\n", + "b = np.random.randn(19, 19, 5, 80)\n", + "c = a * b # shape of c will be (19, 19, 5, 80)\n", + "```\n", + "This is an example of **broadcasting** (multiplying vectors of different sizes).\n", + "\n", + "2. For each box, find:\n", + " - the index of the class with the maximum box score\n", + " - the corresponding box score\n", + " \n", + " **Useful References**\n", + " * [tf.math.argmax](https://www.tensorflow.org/api_docs/python/tf/math/argmax)\n", + " * [tf.math.reduce_max](https://www.tensorflow.org/api_docs/python/tf/math/reduce_max)\n", + "\n", + " **Helpful Hints**\n", + " * For the `axis` parameter of `argmax` and `reduce_max`, if you want to select the **last** axis, one way to do so is to set `axis=-1`. This is similar to Python array indexing, where you can select the last position of an array using `arrayname[-1]`.\n", + " * Applying `reduce_max` normally collapses the axis for which the maximum is applied. `keepdims=False` is the default option, and allows that dimension to be removed. You don't need to keep the last dimension after applying the maximum here.\n", + "\n", + "\n", + "3. Create a mask by using a threshold. As a reminder: `([0.9, 0.3, 0.4, 0.5, 0.1] < 0.4)` returns: `[False, True, False, False, True]`. The mask should be `True` for the boxes you want to keep. \n", + "\n", + "4. Use TensorFlow to apply the mask to `box_class_scores`, `boxes` and `box_classes` to filter out the boxes you don't want. You should be left with just the subset of boxes you want to keep. \n", + "\n", + " **One more useful reference**:\n", + " * [tf.boolean mask](https://www.tensorflow.org/api_docs/python/tf/boolean_mask) \n", + "\n", + " **And one more helpful hint**: :) \n", + " * For the `tf.boolean_mask`, you can keep the default `axis=None`." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-125a819999f836d1", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1 (UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: yolo_filter_boxes\n", + "\n", + "def yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold = .6):\n", + " \"\"\"Filters YOLO boxes by thresholding on object and class confidence.\n", + " \n", + " Arguments:\n", + " boxes -- tensor of shape (19, 19, 5, 4)\n", + " box_confidence -- tensor of shape (19, 19, 5, 1)\n", + " box_class_probs -- tensor of shape (19, 19, 5, 80)\n", + " threshold -- real value, if [ highest class probability score < threshold],\n", + " then get rid of the corresponding box\n", + "\n", + " Returns:\n", + " scores -- tensor of shape (None,), containing the class probability score for selected boxes\n", + " boxes -- tensor of shape (None, 4), containing (b_x, b_y, b_h, b_w) coordinates of selected boxes\n", + " classes -- tensor of shape (None,), containing the index of the class detected by the selected boxes\n", + "\n", + " Note: \"None\" is here because you don't know the exact number of selected boxes, as it depends on the threshold. \n", + " For example, the actual output size of scores would be (10,) if there are 10 boxes.\n", + " \"\"\"\n", + " \n", + " ### START CODE HERE\n", + " # Step 1: Compute box scores\n", + " ##(β‰ˆ 1 line)\n", + " box_scores = box_class_probs*box_confidence\n", + " \n", + " # Step 2: Find the box_classes using the max box_scores, keep track of the corresponding score\n", + " ##(β‰ˆ 2 lines)\n", + " box_classes = tf.math.argmax(box_scores,axis=-1)\n", + " box_class_scores = tf.math.reduce_max(box_scores,axis=-1)\n", + " \n", + " # Step 3: Create a filtering mask based on \"box_class_scores\" by using \"threshold\". The mask should have the\n", + " # same dimension as box_class_scores, and be True for the boxes you want to keep (with probability >= threshold)\n", + " ## (β‰ˆ 1 line)\n", + " filtering_mask = (box_class_scores >= threshold)\n", + " \n", + " # Step 4: Apply the mask to box_class_scores, boxes and box_classes\n", + " ## (β‰ˆ 3 lines)\n", + " scores = tf.boolean_mask(box_class_scores,filtering_mask)\n", + " boxes = tf.boolean_mask(boxes,filtering_mask)\n", + " classes = tf.boolean_mask(box_classes,filtering_mask)\n", + " ### END CODE HERE\n", + " \n", + " return scores, boxes, classes" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-b1c9aaf8e3305fee", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scores[2] = 9.270486\n", + "boxes[2] = [ 4.6399336 3.2303846 4.431282 -2.202031 ]\n", + "classes[2] = 8\n", + "scores.shape = (1789,)\n", + "boxes.shape = (1789, 4)\n", + "classes.shape = (1789,)\n", + "\u001b[92m All tests passed!\n" + ] + } + ], + "source": [ + "# BEGIN UNIT TEST\n", + "tf.random.set_seed(10)\n", + "box_confidence = tf.random.normal([19, 19, 5, 1], mean=1, stddev=4, seed = 1)\n", + "boxes = tf.random.normal([19, 19, 5, 4], mean=1, stddev=4, seed = 1)\n", + "box_class_probs = tf.random.normal([19, 19, 5, 80], mean=1, stddev=4, seed = 1)\n", + "scores, boxes, classes = yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold = 0.5)\n", + "print(\"scores[2] = \" + str(scores[2].numpy()))\n", + "print(\"boxes[2] = \" + str(boxes[2].numpy()))\n", + "print(\"classes[2] = \" + str(classes[2].numpy()))\n", + "print(\"scores.shape = \" + str(scores.shape))\n", + "print(\"boxes.shape = \" + str(boxes.shape))\n", + "print(\"classes.shape = \" + str(classes.shape))\n", + "\n", + "assert type(scores) == EagerTensor, \"Use tensorflow functions\"\n", + "assert type(boxes) == EagerTensor, \"Use tensorflow functions\"\n", + "assert type(classes) == EagerTensor, \"Use tensorflow functions\"\n", + "\n", + "assert scores.shape == (1789,), \"Wrong shape in scores\"\n", + "assert boxes.shape == (1789, 4), \"Wrong shape in boxes\"\n", + "assert classes.shape == (1789,), \"Wrong shape in classes\"\n", + "\n", + "assert np.isclose(scores[2].numpy(), 9.270486), \"Values are wrong on scores\"\n", + "assert np.allclose(boxes[2].numpy(), [4.6399336, 3.2303846, 4.431282, -2.202031]), \"Values are wrong on boxes\"\n", + "assert classes[2].numpy() == 8, \"Values are wrong on classes\"\n", + "\n", + "print(\"\\033[92m All tests passed!\")\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " scores[2]\n", + " \n", + " 9.270486\n", + "
\n", + " boxes[2]\n", + " \n", + " [ 4.6399336 3.2303846 4.431282 -2.202031 ]\n", + "
\n", + " classes[2]\n", + " \n", + " 8\n", + "
\n", + " scores.shape\n", + " \n", + " (1789,)\n", + "
\n", + " boxes.shape\n", + " \n", + " (1789, 4)\n", + "
\n", + " classes.shape\n", + " \n", + " (1789,)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Note** In the test for `yolo_filter_boxes`, you're using random numbers to test the function. In real data, the `box_class_probs` would contain non-zero values between 0 and 1 for the probabilities. The box coordinates in `boxes` would also be chosen so that lengths and heights are non-negative." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.3 - Non-max Suppression\n", + "\n", + "Even after filtering by thresholding over the class scores, you still end up with a lot of overlapping boxes. A second filter for selecting the right boxes is called non-maximum suppression (NMS). " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "
Figure 7 : In this example, the model has predicted 3 cars, but it's actually 3 predictions of the same car. Running non-max suppression (NMS) will select only the most accurate (highest probability) of the 3 boxes.
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Non-max suppression uses the very important function called **\"Intersection over Union\"**, or IoU.\n", + "\n", + "
Figure 8 : Definition of \"Intersection over Union\".
\n", + "\n", + "\n", + "### Exercise 2 - iou\n", + "\n", + "Implement `iou()` \n", + "\n", + "Some hints:\n", + "- This code uses the convention that (0,0) is the top-left corner of an image, (1,0) is the upper-right corner, and (1,1) is the lower-right corner. In other words, the (0,0) origin starts at the top left corner of the image. As x increases, you move to the right. As y increases, you move down.\n", + "- For this exercise, a box is defined using its two corners: upper left $(x_1, y_1)$ and lower right $(x_2,y_2)$, instead of using the midpoint, height and width. This makes it a bit easier to calculate the intersection.\n", + "- To calculate the area of a rectangle, multiply its height $(y_2 - y_1)$ by its width $(x_2 - x_1)$. Since $(x_1,y_1)$ is the top left and $x_2,y_2$ are the bottom right, these differences should be non-negative.\n", + "- To find the **intersection** of the two boxes $(xi_{1}, yi_{1}, xi_{2}, yi_{2})$: \n", + " - Feel free to draw some examples on paper to clarify this conceptually.\n", + " - The top left corner of the intersection $(xi_{1}, yi_{1})$ is found by comparing the top left corners $(x_1, y_1)$ of the two boxes and finding a vertex that has an x-coordinate that is closer to the right, and y-coordinate that is closer to the bottom.\n", + " - The bottom right corner of the intersection $(xi_{2}, yi_{2})$ is found by comparing the bottom right corners $(x_2,y_2)$ of the two boxes and finding a vertex whose x-coordinate is closer to the left, and the y-coordinate that is closer to the top.\n", + " - The two boxes **may have no intersection**. You can detect this if the intersection coordinates you calculate end up being the top right and/or bottom left corners of an intersection box. Another way to think of this is if you calculate the height $(y_2 - y_1)$ or width $(x_2 - x_1)$ and find that at least one of these lengths is negative, then there is no intersection (intersection area is zero). \n", + " - The two boxes may intersect at the **edges or vertices**, in which case the intersection area is still zero. This happens when either the height or width (or both) of the calculated intersection is zero.\n", + "\n", + "\n", + "**Additional Hints**\n", + "\n", + "- `xi1` = **max**imum of the x1 coordinates of the two boxes\n", + "- `yi1` = **max**imum of the y1 coordinates of the two boxes\n", + "- `xi2` = **min**imum of the x2 coordinates of the two boxes\n", + "- `yi2` = **min**imum of the y2 coordinates of the two boxes\n", + "- `inter_area` = You can use `max(height, 0)` and `max(width, 0)`\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-43008d769892f26f", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2 (UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: iou\n", + "\n", + "def iou(box1, box2):\n", + " \"\"\"Implement the intersection over union (IoU) between box1 and box2\n", + "Β Β Β Β \n", + " Arguments:\n", + " box1 -- first box, list object with coordinates (box1_x1, box1_y1, box1_x2, box_1_y2)\n", + "Β Β Β Β box2 -- second box, list object with coordinates (box2_x1, box2_y1, box2_x2, box2_y2)\n", + "Β Β Β Β \"\"\"\n", + "\n", + "\n", + " (box1_x1, box1_y1, box1_x2, box1_y2) = box1\n", + " (box2_x1, box2_y1, box2_x2, box2_y2) = box2\n", + "\n", + " ### START CODE HERE\n", + " # Calculate the (yi1, xi1, yi2, xi2) coordinates of the intersection of box1 and box2. Calculate its Area.\n", + " ##(β‰ˆ 7 lines)\n", + " xi1 = max(box1_x1,box2_x1)\n", + " yi1 = max(box1_y1,box2_y1)\n", + " xi2 = min(box1_x2,box2_x2)\n", + " yi2 = min(box1_y2,box2_y2)\n", + " inter_width = max(0,yi2 - yi1)\n", + " inter_height = max(0,xi2 - xi1)\n", + " inter_area = inter_width*inter_height\n", + "\n", + " # Calculate the Union area by using Formula: Union(A,B) = A + B - Inter(A,B)\n", + " ## (β‰ˆ 3 lines)\n", + " box1_area = (box1_x2-box1_x1)*((box1_y2-box1_y1))\n", + " box2_area = (box2_x2-box2_x1)*((box2_y2-box2_y1))\n", + " union_area = box1_area + box2_area - inter_area\n", + " \n", + " # compute the IoU\n", + " ## (β‰ˆ 1 line)\n", + " iou = inter_area/union_area\n", + " ### END CODE HERE\n", + " \n", + " return iou" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-e990c04efb445600", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "iou for intersecting boxes = 0.14285714285714285\n", + "iou for non-intersecting boxes = 0.0\n", + "iou for boxes that only touch at vertices = 0.0\n", + "iou for boxes that only touch at edges = 0.0\n", + "\u001b[92m All tests passed!\n" + ] + } + ], + "source": [ + "# BEGIN UNIT TEST\n", + "## Test case 1: boxes intersect\n", + "box1 = (2, 1, 4, 3)\n", + "box2 = (1, 2, 3, 4)\n", + "\n", + "print(\"iou for intersecting boxes = \" + str(iou(box1, box2)))\n", + "assert iou(box1, box2) < 1, \"The intersection area must be always smaller or equal than the union area.\"\n", + "assert np.isclose(iou(box1, box2), 0.14285714), \"Wrong value. Check your implementation. Problem with intersecting boxes\"\n", + "\n", + "## Test case 2: boxes do not intersect\n", + "box1 = (1,2,3,4)\n", + "box2 = (5,6,7,8)\n", + "print(\"iou for non-intersecting boxes = \" + str(iou(box1,box2)))\n", + "assert iou(box1, box2) == 0, \"Intersection must be 0\"\n", + "\n", + "## Test case 3: boxes intersect at vertices only\n", + "box1 = (1,1,2,2)\n", + "box2 = (2,2,3,3)\n", + "print(\"iou for boxes that only touch at vertices = \" + str(iou(box1,box2)))\n", + "assert iou(box1, box2) == 0, \"Intersection at vertices must be 0\"\n", + "\n", + "## Test case 4: boxes intersect at edge only\n", + "box1 = (1,1,3,3)\n", + "box2 = (2,3,3,4)\n", + "print(\"iou for boxes that only touch at edges = \" + str(iou(box1,box2)))\n", + "assert iou(box1, box2) == 0, \"Intersection at edges must be 0\"\n", + "\n", + "print(\"\\033[92m All tests passed!\")\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "```\n", + "iou for intersecting boxes = 0.14285714285714285\n", + "iou for non-intersecting boxes = 0.0\n", + "iou for boxes that only touch at vertices = 0.0\n", + "iou for boxes that only touch at edges = 0.0\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.4 - YOLO Non-max Suppression\n", + "\n", + "You are now ready to implement non-max suppression. The key steps are: \n", + "1. Select the box that has the highest score.\n", + "2. Compute the overlap of this box with all other boxes, and remove boxes that overlap significantly (iou >= `iou_threshold`).\n", + "3. Go back to step 1 and iterate until there are no more boxes with a lower score than the currently selected box.\n", + "\n", + "This will remove all boxes that have a large overlap with the selected boxes. Only the \"best\" boxes remain.\n", + "\n", + "\n", + "### Exercise 3 - yolo_non_max_suppression\n", + "\n", + "Implement `yolo_non_max_suppression()` using TensorFlow. TensorFlow has two built-in functions that are used to implement non-max suppression (so you don't actually need to use your `iou()` implementation):\n", + "\n", + "**Reference documentation**: \n", + "\n", + "- [tf.image.non_max_suppression()](https://www.tensorflow.org/api_docs/python/tf/image/non_max_suppression)\n", + "```\n", + "tf.image.non_max_suppression(\n", + " boxes,\n", + " scores,\n", + " max_output_size,\n", + " iou_threshold=0.5,\n", + " name=None\n", + ")\n", + "```\n", + "Note that in the version of TensorFlow used here, there is no parameter `score_threshold` (it's shown in the documentation for the latest version) so trying to set this value will result in an error message: *got an unexpected keyword argument `score_threshold`.*\n", + "\n", + "- [tf.gather()](https://www.tensorflow.org/api_docs/python/tf/gather)\n", + "```\n", + "keras.gather(\n", + " reference,\n", + " indices\n", + ")\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-45dde3252e543bbd", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C3 (UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: yolo_non_max_suppression\n", + "\n", + "def yolo_non_max_suppression(scores, boxes, classes, max_boxes = 10, iou_threshold = 0.5):\n", + " \"\"\"\n", + " Applies Non-max suppression (NMS) to set of boxes\n", + " \n", + " Arguments:\n", + " scores -- tensor of shape (None,), output of yolo_filter_boxes()\n", + " boxes -- tensor of shape (None, 4), output of yolo_filter_boxes() that have been scaled to the image size (see later)\n", + " classes -- tensor of shape (None,), output of yolo_filter_boxes()\n", + " max_boxes -- integer, maximum number of predicted boxes you'd like\n", + " iou_threshold -- real value, \"intersection over union\" threshold used for NMS filtering\n", + " \n", + " Returns:\n", + " scores -- tensor of shape (None, ), predicted score for each box\n", + " boxes -- tensor of shape (None, 4), predicted box coordinates\n", + " classes -- tensor of shape (None, ), predicted class for each box\n", + " \n", + " Note: The \"None\" dimension of the output tensors has obviously to be less than max_boxes. Note also that this\n", + " function will transpose the shapes of scores, boxes, classes. This is made for convenience.\n", + " \"\"\"\n", + " \n", + " max_boxes_tensor = tf.Variable(max_boxes, dtype='int32') # tensor to be used in tf.image.non_max_suppression()\n", + " \n", + " # Use tf.image.non_max_suppression() to get the list of indices corresponding to boxes you keep\n", + " ##(β‰ˆ 1 line)\n", + " nms_indices = tf.image.non_max_suppression(boxes,scores,max_boxes_tensor,iou_threshold)\n", + " \n", + " # Use tf.gather() to select only nms_indices from scores, boxes and classes\n", + " ##(β‰ˆ 3 lines)\n", + " scores = tf.gather(scores,nms_indices)\n", + " boxes = tf.gather(boxes,nms_indices)\n", + " classes = tf.gather(classes,nms_indices)\n", + " ### END CODE HERE\n", + "\n", + " \n", + " return scores, boxes, classes" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-07e64f2138d66235", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scores[2] = 8.147684\n", + "boxes[2] = [ 6.0797963 3.743308 1.3914018 -0.34089637]\n", + "classes[2] = 1.7079165\n", + "scores.shape = (10,)\n", + "boxes.shape = (10, 4)\n", + "classes.shape = (10,)\n", + "\u001b[92m All tests passed!\n" + ] + } + ], + "source": [ + "# BEGIN UNIT TEST\n", + "tf.random.set_seed(10)\n", + "scores = tf.random.normal([54,], mean=1, stddev=4, seed = 1)\n", + "boxes = tf.random.normal([54, 4], mean=1, stddev=4, seed = 1)\n", + "classes = tf.random.normal([54,], mean=1, stddev=4, seed = 1)\n", + "scores, boxes, classes = yolo_non_max_suppression(scores, boxes, classes)\n", + "\n", + "assert type(scores) == EagerTensor, \"Use tensoflow functions\"\n", + "print(\"scores[2] = \" + str(scores[2].numpy()))\n", + "print(\"boxes[2] = \" + str(boxes[2].numpy()))\n", + "print(\"classes[2] = \" + str(classes[2].numpy()))\n", + "print(\"scores.shape = \" + str(scores.numpy().shape))\n", + "print(\"boxes.shape = \" + str(boxes.numpy().shape))\n", + "print(\"classes.shape = \" + str(classes.numpy().shape))\n", + "\n", + "assert type(scores) == EagerTensor, \"Use tensoflow functions\"\n", + "assert type(boxes) == EagerTensor, \"Use tensoflow functions\"\n", + "assert type(classes) == EagerTensor, \"Use tensoflow functions\"\n", + "\n", + "assert scores.shape == (10,), \"Wrong shape\"\n", + "assert boxes.shape == (10, 4), \"Wrong shape\"\n", + "assert classes.shape == (10,), \"Wrong shape\"\n", + "\n", + "assert np.isclose(scores[2].numpy(), 8.147684), \"Wrong value on scores\"\n", + "assert np.allclose(boxes[2].numpy(), [ 6.0797963, 3.743308, 1.3914018, -0.34089637]), \"Wrong value on boxes\"\n", + "assert np.isclose(classes[2].numpy(), 1.7079165), \"Wrong value on classes\"\n", + "\n", + "print(\"\\033[92m All tests passed!\")\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " scores[2]\n", + " \n", + " 8.147684\n", + "
\n", + " boxes[2]\n", + " \n", + " [ 6.0797963 3.743308 1.3914018 -0.34089637]\n", + "
\n", + " classes[2]\n", + " \n", + " 1.7079165\n", + "
\n", + " scores.shape\n", + " \n", + " (10,)\n", + "
\n", + " boxes.shape\n", + " \n", + " (10, 4)\n", + "
\n", + " classes.shape\n", + " \n", + " (10,)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.5 - Wrapping Up the Filtering\n", + "\n", + "It's time to implement a function taking the output of the deep CNN (the 19x19x5x85 dimensional encoding) and filtering through all the boxes using the functions you've just implemented. \n", + "\n", + "\n", + "### Exercise 4 - yolo_eval\n", + "\n", + "Implement `yolo_eval()` which takes the output of the YOLO encoding and filters the boxes using score threshold and NMS. There's just one last implementational detail you have to know. There're a few ways of representing boxes, such as via their corners or via their midpoint and height/width. YOLO converts between a few such formats at different times, using the following functions (which are provided): \n", + "\n", + "```python\n", + "boxes = yolo_boxes_to_corners(box_xy, box_wh) \n", + "```\n", + "which converts the yolo box coordinates (x,y,w,h) to box corners' coordinates (x1, y1, x2, y2) to fit the input of `yolo_filter_boxes`\n", + "```python\n", + "boxes = scale_boxes(boxes, image_shape)\n", + "```\n", + "YOLO's network was trained to run on 608x608 images. If you are testing this data on a different size image -- for example, the car detection dataset had 720x1280 images -- this step rescales the boxes so that they can be plotted on top of the original 720x1280 image. \n", + "\n", + "Don't worry about these two functions; you'll see where they need to be called below. " + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "def yolo_boxes_to_corners(box_xy, box_wh):\n", + " \"\"\"Convert YOLO box predictions to bounding box corners.\"\"\"\n", + " box_mins = box_xy - (box_wh / 2.)\n", + " box_maxes = box_xy + (box_wh / 2.)\n", + "\n", + " return tf.keras.backend.concatenate([\n", + " box_mins[..., 1:2], # y_min\n", + " box_mins[..., 0:1], # x_min\n", + " box_maxes[..., 1:2], # y_max\n", + " box_maxes[..., 0:1] # x_max\n", + " ])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-baa7fe688d21f2dc", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C4 (UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: yolo_eval\n", + "\n", + "def yolo_eval(yolo_outputs, image_shape = (720, 1280), max_boxes=10, score_threshold=.6, iou_threshold=.5):\n", + " \"\"\"\n", + " Converts the output of YOLO encoding (a lot of boxes) to your predicted boxes along with their scores, box coordinates and classes.\n", + " \n", + " Arguments:\n", + " yolo_outputs -- output of the encoding model (for image_shape of (608, 608, 3)), contains 4 tensors:\n", + " box_xy: tensor of shape (None, 19, 19, 5, 2)\n", + " box_wh: tensor of shape (None, 19, 19, 5, 2)\n", + " box_confidence: tensor of shape (None, 19, 19, 5, 1)\n", + " box_class_probs: tensor of shape (None, 19, 19, 5, 80)\n", + " image_shape -- tensor of shape (2,) containing the input shape, in this notebook we use (608., 608.) (has to be float32 dtype)\n", + " max_boxes -- integer, maximum number of predicted boxes you'd like\n", + " score_threshold -- real value, if [ highest class probability score < threshold], then get rid of the corresponding box\n", + " iou_threshold -- real value, \"intersection over union\" threshold used for NMS filtering\n", + " \n", + " Returns:\n", + " scores -- tensor of shape (None, ), predicted score for each box\n", + " boxes -- tensor of shape (None, 4), predicted box coordinates\n", + " classes -- tensor of shape (None,), predicted class for each box\n", + " \"\"\"\n", + " \n", + " ### START CODE HERE\n", + " # Retrieve outputs of the YOLO model (β‰ˆ1 line)\n", + " box_xy, box_wh, box_confidence, box_class_probs = yolo_outputs\n", + "\n", + " # Convert boxes to be ready for filtering functions (convert boxes box_xy and box_wh to corner coordinates)\n", + " boxes = yolo_boxes_to_corners(box_xy, box_wh)\n", + "\n", + " # Use one of the functions you've implemented to perform Score-filtering with a threshold of score_threshold (β‰ˆ1 line)\n", + " scores, boxes, classes = yolo_filter_boxes(boxes, box_confidence, box_class_probs, score_threshold)\n", + " \n", + " # Scale boxes back to original image shape (720, 1280 or whatever)\n", + " boxes = scale_boxes(boxes, image_shape) # Network was trained to run on 608x608 images\n", + "\n", + " # Use one of the functions you've implemented to perform Non-max suppression with \n", + " # maximum number of boxes set to max_boxes and a threshold of iou_threshold (β‰ˆ1 line)\n", + " scores, boxes, classes = yolo_non_max_suppression(scores, boxes, classes, max_boxes, iou_threshold)\n", + " ### END CODE HERE\n", + " \n", + " return scores, boxes, classes" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-8433ee3146a7deda", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scores[2] = 171.60194\n", + "boxes[2] = [-1240.3483 -3212.5881 -645.78 2024.3052]\n", + "classes[2] = 16\n", + "scores.shape = (10,)\n", + "boxes.shape = (10, 4)\n", + "classes.shape = (10,)\n", + "\u001b[92m All tests passed!\n" + ] + } + ], + "source": [ + "# BEGIN UNIT TEST\n", + "tf.random.set_seed(10)\n", + "yolo_outputs = (tf.random.normal([19, 19, 5, 2], mean=1, stddev=4, seed = 1),\n", + " tf.random.normal([19, 19, 5, 2], mean=1, stddev=4, seed = 1),\n", + " tf.random.normal([19, 19, 5, 1], mean=1, stddev=4, seed = 1),\n", + " tf.random.normal([19, 19, 5, 80], mean=1, stddev=4, seed = 1))\n", + "scores, boxes, classes = yolo_eval(yolo_outputs)\n", + "print(\"scores[2] = \" + str(scores[2].numpy()))\n", + "print(\"boxes[2] = \" + str(boxes[2].numpy()))\n", + "print(\"classes[2] = \" + str(classes[2].numpy()))\n", + "print(\"scores.shape = \" + str(scores.numpy().shape))\n", + "print(\"boxes.shape = \" + str(boxes.numpy().shape))\n", + "print(\"classes.shape = \" + str(classes.numpy().shape))\n", + "\n", + "assert type(scores) == EagerTensor, \"Use tensoflow functions\"\n", + "assert type(boxes) == EagerTensor, \"Use tensoflow functions\"\n", + "assert type(classes) == EagerTensor, \"Use tensoflow functions\"\n", + "\n", + "assert scores.shape == (10,), \"Wrong shape\"\n", + "assert boxes.shape == (10, 4), \"Wrong shape\"\n", + "assert classes.shape == (10,), \"Wrong shape\"\n", + " \n", + "assert np.isclose(scores[2].numpy(), 171.60194), \"Wrong value on scores\"\n", + "assert np.allclose(boxes[2].numpy(), [-1240.3483, -3212.5881, -645.78, 2024.3052]), \"Wrong value on boxes\"\n", + "assert np.isclose(classes[2].numpy(), 16), \"Wrong value on classes\"\n", + " \n", + "print(\"\\033[92m All tests passed!\")\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " scores[2]\n", + " \n", + " 171.60194\n", + "
\n", + " boxes[2]\n", + " \n", + " [-1240.3483 -3212.5881 -645.78 2024.3052]\n", + "
\n", + " classes[2]\n", + " \n", + " 16\n", + "
\n", + " scores.shape\n", + " \n", + " (10,)\n", + "
\n", + " boxes.shape\n", + " \n", + " (10, 4)\n", + "
\n", + " classes.shape\n", + " \n", + " (10,)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Test YOLO Pre-trained Model on Images\n", + "\n", + "In this section, you are going to use a pre-trained model and test it on the car detection dataset. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.1 - Defining Classes, Anchors and Image Shape\n", + "\n", + "You're trying to detect 80 classes, and are using 5 anchor boxes. The information on the 80 classes and 5 boxes is gathered in two files: \"coco_classes.txt\" and \"yolo_anchors.txt\". You'll read class names and anchors from text files. The car detection dataset has 720x1280 images, which are pre-processed into 608x608 images." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "class_names = read_classes(\"model_data/coco_classes.txt\")\n", + "anchors = read_anchors(\"model_data/yolo_anchors.txt\")\n", + "model_image_size = (608, 608) # Same as yolo_model input layer size" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - Loading a Pre-trained Model\n", + "\n", + "Training a YOLO model takes a very long time and requires a fairly large dataset of labelled bounding boxes for a large range of target classes. You are going to load an existing pre-trained Keras YOLO model stored in \"yolo.h5\". These weights come from the official YOLO website, and were converted using a function written by Allan Zelener. References are at the end of this notebook. Technically, these are the parameters from the \"YOLOv2\" model, but are simply referred to as \"YOLO\" in this notebook.\n", + "\n", + "Run the cell below to load the model from this file." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "yolo_model = load_model(\"model_data/\", compile=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This loads the weights of a trained YOLO model. Here's a summary of the layers your model contains:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"functional_1\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "input_1 (InputLayer) [(None, 608, 608, 3) 0 \n", + "__________________________________________________________________________________________________\n", + "conv2d (Conv2D) (None, 608, 608, 32) 864 input_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization (BatchNorma (None, 608, 608, 32) 128 conv2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu (LeakyReLU) (None, 608, 608, 32) 0 batch_normalization[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d (MaxPooling2D) (None, 304, 304, 32) 0 leaky_re_lu[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_1 (Conv2D) (None, 304, 304, 64) 18432 max_pooling2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_1 (BatchNor (None, 304, 304, 64) 256 conv2d_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_1 (LeakyReLU) (None, 304, 304, 64) 0 batch_normalization_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_1 (MaxPooling2D) (None, 152, 152, 64) 0 leaky_re_lu_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_2 (Conv2D) (None, 152, 152, 128 73728 max_pooling2d_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_2 (BatchNor (None, 152, 152, 128 512 conv2d_2[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_2 (LeakyReLU) (None, 152, 152, 128 0 batch_normalization_2[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_3 (Conv2D) (None, 152, 152, 64) 8192 leaky_re_lu_2[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_3 (BatchNor (None, 152, 152, 64) 256 conv2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_3 (LeakyReLU) (None, 152, 152, 64) 0 batch_normalization_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_4 (Conv2D) (None, 152, 152, 128 73728 leaky_re_lu_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_4 (BatchNor (None, 152, 152, 128 512 conv2d_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_4 (LeakyReLU) (None, 152, 152, 128 0 batch_normalization_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_2 (MaxPooling2D) (None, 76, 76, 128) 0 leaky_re_lu_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_5 (Conv2D) (None, 76, 76, 256) 294912 max_pooling2d_2[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_5 (BatchNor (None, 76, 76, 256) 1024 conv2d_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_5 (LeakyReLU) (None, 76, 76, 256) 0 batch_normalization_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_6 (Conv2D) (None, 76, 76, 128) 32768 leaky_re_lu_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_6 (BatchNor (None, 76, 76, 128) 512 conv2d_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_6 (LeakyReLU) (None, 76, 76, 128) 0 batch_normalization_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_7 (Conv2D) (None, 76, 76, 256) 294912 leaky_re_lu_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_7 (BatchNor (None, 76, 76, 256) 1024 conv2d_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_7 (LeakyReLU) (None, 76, 76, 256) 0 batch_normalization_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_3 (MaxPooling2D) (None, 38, 38, 256) 0 leaky_re_lu_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_8 (Conv2D) (None, 38, 38, 512) 1179648 max_pooling2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_8 (BatchNor (None, 38, 38, 512) 2048 conv2d_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_8 (LeakyReLU) (None, 38, 38, 512) 0 batch_normalization_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_9 (Conv2D) (None, 38, 38, 256) 131072 leaky_re_lu_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_9 (BatchNor (None, 38, 38, 256) 1024 conv2d_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_9 (LeakyReLU) (None, 38, 38, 256) 0 batch_normalization_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_10 (Conv2D) (None, 38, 38, 512) 1179648 leaky_re_lu_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_10 (BatchNo (None, 38, 38, 512) 2048 conv2d_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_10 (LeakyReLU) (None, 38, 38, 512) 0 batch_normalization_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_11 (Conv2D) (None, 38, 38, 256) 131072 leaky_re_lu_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_11 (BatchNo (None, 38, 38, 256) 1024 conv2d_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_11 (LeakyReLU) (None, 38, 38, 256) 0 batch_normalization_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_12 (Conv2D) (None, 38, 38, 512) 1179648 leaky_re_lu_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_12 (BatchNo (None, 38, 38, 512) 2048 conv2d_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_12 (LeakyReLU) (None, 38, 38, 512) 0 batch_normalization_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_4 (MaxPooling2D) (None, 19, 19, 512) 0 leaky_re_lu_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_13 (Conv2D) (None, 19, 19, 1024) 4718592 max_pooling2d_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_13 (BatchNo (None, 19, 19, 1024) 4096 conv2d_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_13 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_14 (Conv2D) (None, 19, 19, 512) 524288 leaky_re_lu_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_14 (BatchNo (None, 19, 19, 512) 2048 conv2d_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_14 (LeakyReLU) (None, 19, 19, 512) 0 batch_normalization_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_15 (Conv2D) (None, 19, 19, 1024) 4718592 leaky_re_lu_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_15 (BatchNo (None, 19, 19, 1024) 4096 conv2d_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_15 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_16 (Conv2D) (None, 19, 19, 512) 524288 leaky_re_lu_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_16 (BatchNo (None, 19, 19, 512) 2048 conv2d_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_16 (LeakyReLU) (None, 19, 19, 512) 0 batch_normalization_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_17 (Conv2D) (None, 19, 19, 1024) 4718592 leaky_re_lu_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_17 (BatchNo (None, 19, 19, 1024) 4096 conv2d_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_17 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_18 (Conv2D) (None, 19, 19, 1024) 9437184 leaky_re_lu_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_18 (BatchNo (None, 19, 19, 1024) 4096 conv2d_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_20 (Conv2D) (None, 38, 38, 64) 32768 leaky_re_lu_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_18 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_20 (BatchNo (None, 38, 38, 64) 256 conv2d_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_19 (Conv2D) (None, 19, 19, 1024) 9437184 leaky_re_lu_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_20 (LeakyReLU) (None, 38, 38, 64) 0 batch_normalization_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_19 (BatchNo (None, 19, 19, 1024) 4096 conv2d_19[0][0] \n", + "__________________________________________________________________________________________________\n", + "space_to_depth_x2 (Lambda) (None, 19, 19, 256) 0 leaky_re_lu_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_19 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_19[0][0] \n", + "__________________________________________________________________________________________________\n", + "concatenate (Concatenate) (None, 19, 19, 1280) 0 space_to_depth_x2[0][0] \n", + " leaky_re_lu_19[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_21 (Conv2D) (None, 19, 19, 1024) 11796480 concatenate[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_21 (BatchNo (None, 19, 19, 1024) 4096 conv2d_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "leaky_re_lu_21 (LeakyReLU) (None, 19, 19, 1024) 0 batch_normalization_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_22 (Conv2D) (None, 19, 19, 425) 435625 leaky_re_lu_21[0][0] \n", + "==================================================================================================\n", + "Total params: 50,983,561\n", + "Trainable params: 50,962,889\n", + "Non-trainable params: 20,672\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "yolo_model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Note**: On some computers, you may see a warning message from Keras. Don't worry about it if you do -- this is fine!\n", + "\n", + "**Reminder**: This model converts a preprocessed batch of input images (shape: (m, 608, 608, 3)) into a tensor of shape (m, 19, 19, 5, 85) as explained in Figure (2)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.3 - Convert Output of the Model to Usable Bounding Box Tensors\n", + "\n", + "The output of `yolo_model` is a (m, 19, 19, 5, 85) tensor that needs to pass through non-trivial processing and conversion. You will need to call `yolo_head` to format the encoding of the model you got from `yolo_model` into something decipherable:\n", + "\n", + "yolo_model_outputs = yolo_model(image_data) \n", + "yolo_outputs = yolo_head(yolo_model_outputs, anchors, len(class_names))\n", + "The variable `yolo_outputs` will be defined as a set of 4 tensors that you can then use as input by your yolo_eval function. If you are curious about how yolo_head is implemented, you can find the function definition in the file `keras_yolo.py`. The file is also located in your workspace in this path: `yad2k/models/keras_yolo.py`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.4 - Filtering Boxes\n", + "\n", + "`yolo_outputs` gave you all the predicted boxes of `yolo_model` in the correct format. To perform filtering and select only the best boxes, you will call `yolo_eval`, which you had previously implemented, to do so:\n", + "\n", + " out_scores, out_boxes, out_classes = yolo_eval(yolo_outputs, [image.size[1], image.size[0]], 10, 0.3, 0.5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.5 - Run the YOLO on an Image\n", + "\n", + "Let the fun begin! You will create a graph that can be summarized as follows:\n", + "\n", + "`yolo_model.input` is given to `yolo_model`. The model is used to compute the output `yolo_model.output`\n", + "`yolo_model.output` is processed by `yolo_head`. It gives you `yolo_outputs`\n", + "`yolo_outputs` goes through a filtering function, `yolo_eval`. It outputs your predictions: `out_scores`, `out_boxes`, `out_classes`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we have implemented for you the `predict(image_file)` function, which runs the graph to test YOLO on an image to compute `out_scores`, `out_boxes`, `out_classes`.\n", + "\n", + "The code below also uses the following function:\n", + "\n", + " image, image_data = preprocess_image(\"images/\" + image_file, model_image_size = (608, 608))\n", + "which opens the image file and scales, reshapes and normalizes the image. It returns the outputs:\n", + "\n", + " image: a python (PIL) representation of your image used for drawing boxes. You won't need to use it.\n", + " image_data: a numpy-array representing the image. This will be the input to the CNN." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "def predict(image_file):\n", + " \"\"\"\n", + " Runs the graph to predict boxes for \"image_file\". Prints and plots the predictions.\n", + " \n", + " Arguments:\n", + " image_file -- name of an image stored in the \"images\" folder.\n", + " \n", + " Returns:\n", + " out_scores -- tensor of shape (None, ), scores of the predicted boxes\n", + " out_boxes -- tensor of shape (None, 4), coordinates of the predicted boxes\n", + " out_classes -- tensor of shape (None, ), class index of the predicted boxes\n", + " \n", + " Note: \"None\" actually represents the number of predicted boxes, it varies between 0 and max_boxes. \n", + " \"\"\"\n", + "\n", + " # Preprocess your image\n", + " image, image_data = preprocess_image(\"images/\" + image_file, model_image_size = (608, 608))\n", + " \n", + " yolo_model_outputs = yolo_model(image_data) # It's output is of shape (m, 19, 19, 5, 85) \n", + " # But yolo_eval takes input a tensor contains 4 tensors: box_xy,box_wh, box_confidence & box_class_probs\n", + " yolo_outputs = yolo_head(yolo_model_outputs, anchors, len(class_names))\n", + " \n", + " out_scores, out_boxes, out_classes = yolo_eval(yolo_outputs, [image.size[1], image.size[0]], 10, 0.3, 0.5)\n", + "\n", + " # Print predictions info\n", + " print('Found {} boxes for {}'.format(len(out_boxes), \"images/\" + image_file))\n", + " # Generate colors for drawing bounding boxes.\n", + " colors = get_colors_for_classes(len(class_names))\n", + " # Draw bounding boxes on the image file\n", + " #draw_boxes2(image, out_scores, out_boxes, out_classes, class_names, colors, image_shape)\n", + " draw_boxes(image, out_boxes, out_classes, class_names, out_scores)\n", + " # Save the predicted bounding box on the image\n", + " image.save(os.path.join(\"out\", str(image_file).split('.')[0]+\"_annotated.\" +str(image_file).split('.')[1] ), quality=100)\n", + " # Display the results in the notebook\n", + " output_image = Image.open(os.path.join(\"out\", str(image_file).split('.')[0]+\"_annotated.\" +str(image_file).split('.')[1] ))\n", + " imshow(output_image)\n", + "\n", + " return out_scores, out_boxes, out_classes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run the following cell on the \"test.jpg\" image to verify that your function is correct." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 10 boxes for images/test.jpg\n", + "car 0.89 (367, 300) (745, 648)\n", + "car 0.80 (761, 282) (942, 412)\n", + "car 0.74 (159, 303) (346, 440)\n", + "car 0.70 (947, 324) (1280, 705)\n", + "bus 0.67 (5, 266) (220, 407)\n", + "car 0.66 (706, 279) (786, 350)\n", + "car 0.60 (925, 285) (1045, 374)\n", + "car 0.44 (336, 296) (378, 335)\n", + "car 0.37 (965, 273) (1022, 292)\n", + "traffic light 0.36 (681, 195) (692, 214)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "out_scores, out_boxes, out_classes = predict(\"test.jpg\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " Found 10 boxes for images/test.jpg\n", + "
\n", + " car\n", + " \n", + " 0.89 (367, 300) (745, 648)\n", + "
\n", + " car\n", + " \n", + " 0.80 (761, 282) (942, 412)\n", + "
\n", + " car\n", + " \n", + " 0.74 (159, 303) (346, 440)\n", + "
\n", + " car\n", + " \n", + " 0.70 (947, 324) (1280, 705)\n", + "
\n", + " bus\n", + " \n", + " 0.67 (5, 266) (220, 407)\n", + "
\n", + " car\n", + " \n", + " 0.66 (706, 279) (786, 350)\n", + "
\n", + " car\n", + " \n", + " 0.60 (925, 285) (1045, 374)\n", + "
\n", + " car\n", + " \n", + " 0.44 (336, 296) (378, 335)\n", + "
\n", + " car\n", + " \n", + " 0.37 (965, 273) (1022, 292)\n", + "
\n", + " traffic light\n", + " \n", + " 00.36 (681, 195) (692, 214)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model you've just run is actually able to detect 80 different classes listed in \"coco_classes.txt\". To test the model on your own images:\n", + " 1. Click on \"File\" in the upper bar of this notebook, then click \"Open\" to go on your Coursera Hub.\n", + " 2. Add your image to this Jupyter Notebook's directory, in the \"images\" folder\n", + " 3. Write your image's name in the cell above code\n", + " 4. Run the code and see the output of the algorithm!\n", + "\n", + "If you were to run your session in a for loop over all your images. Here's what you would get:\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "
Predictions of the YOLO model on pictures taken from a camera while driving around the Silicon Valley
Thanks to drive.ai for providing this dataset!
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 4 - Summary for YOLO\n", + "\n", + "- Input image (608, 608, 3)\n", + "- The input image goes through a CNN, resulting in a (19,19,5,85) dimensional output. \n", + "- After flattening the last two dimensions, the output is a volume of shape (19, 19, 425):\n", + " - Each cell in a 19x19 grid over the input image gives 425 numbers. \n", + " - 425 = 5 x 85 because each cell contains predictions for 5 boxes, corresponding to 5 anchor boxes, as seen in lecture. \n", + " - 85 = 5 + 80 where 5 is because $(p_c, b_x, b_y, b_h, b_w)$ has 5 numbers, and 80 is the number of classes we'd like to detect\n", + "- You then select only few boxes based on:\n", + " - Score-thresholding: throw away boxes that have detected a class with a score less than the threshold\n", + " - Non-max suppression: Compute the Intersection over Union and avoid selecting overlapping boxes\n", + "- This gives you YOLO's final output. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + " \n", + "**What you should remember**:\n", + " \n", + "- YOLO is a state-of-the-art object detection model that is fast and accurate\n", + "- It runs an input image through a CNN, which outputs a 19x19x5x85 dimensional volume. \n", + "- The encoding can be seen as a grid where each of the 19x19 cells contains information about 5 boxes.\n", + "- You filter through all the boxes using non-max suppression. Specifically: \n", + " - Score thresholding on the probability of detecting a class to keep only accurate (high probability) boxes\n", + " - Intersection over Union (IoU) thresholding to eliminate overlapping boxes\n", + "- Because training a YOLO model from randomly initialized weights is non-trivial and requires a large dataset as well as lot of computation, previously trained model parameters were used in this exercise. If you wish, you can also try fine-tuning the YOLO model with your own dataset, though this would be a fairly non-trivial exercise. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations!** You've come to the end of this assignment. \n", + "\n", + "Here's a quick recap of all you've accomplished.\n", + "\n", + "You've: \n", + "\n", + "- Detected objects in a car detection dataset\n", + "- Implemented non-max suppression to achieve better accuracy\n", + "- Implemented intersection over union as a function of NMS\n", + "- Created usable bounding box tensors from the model's predictions\n", + "\n", + "Amazing work! If you'd like to know more about the origins of these ideas, spend some time on the papers referenced below. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5 - References\n", + "\n", + "The ideas presented in this notebook came primarily from the two YOLO papers. The implementation here also took significant inspiration and used many components from Allan Zelener's GitHub repository. The pre-trained weights used in this exercise came from the official YOLO website. \n", + "- Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi - [You Only Look Once: Unified, Real-Time Object Detection](https://arxiv.org/abs/1506.02640) (2015)\n", + "- Joseph Redmon, Ali Farhadi - [YOLO9000: Better, Faster, Stronger](https://arxiv.org/abs/1612.08242) (2016)\n", + "- Allan Zelener - [YAD2K: Yet Another Darknet 2 Keras](https://github.com/allanzelener/YAD2K)\n", + "- The official YOLO website (https://pjreddie.com/darknet/yolo/) \n", + "\n", + "### Car detection dataset\n", + "\n", + "\"Creative
The Drive.ai Sample Dataset (provided by drive.ai) is licensed under a Creative Commons Attribution 4.0 International License. Thanks to Brody Huval, Chih Hu and Rahul Patel for providing this data. " + ] + } + ], + "metadata": { + "celltoolbar": "Raw Cell Format", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Application.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Application.ipynb new file mode 100644 index 00000000000..40e7acf967f --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Application.ipynb @@ -0,0 +1,1062 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Convolutional Neural Networks: Application\n", + "\n", + "Welcome to Course 4's second assignment! In this notebook, you will:\n", + "\n", + "- Create a mood classifer using the TF Keras Sequential API\n", + "- Build a ConvNet to identify sign language digits using the TF Keras Functional API\n", + "\n", + "**After this assignment you will be able to:**\n", + "\n", + "- Build and train a ConvNet in TensorFlow for a __binary__ classification problem\n", + "- Build and train a ConvNet in TensorFlow for a __multiclass__ classification problem\n", + "- Explain different use cases for the Sequential and Functional APIs\n", + "\n", + "To complete this assignment, you should already be familiar with TensorFlow. If you are not, please refer back to the **TensorFlow Tutorial** of the third week of Course 2 (\"**Improving deep neural networks**\").\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "\n", + "- [1 - Packages](#1)\n", + " - [1.1 - Load the Data and Split the Data into Train/Test Sets](#1-1)\n", + "- [2 - Layers in TF Keras](#2)\n", + "- [3 - The Sequential API](#3)\n", + " - [3.1 - Create the Sequential Model](#3-1)\n", + " - [Exercise 1 - happyModel](#ex-1)\n", + " - [3.2 - Train and Evaluate the Model](#3-2)\n", + "- [4 - The Functional API](#4)\n", + " - [4.1 - Load the SIGNS Dataset](#4-1)\n", + " - [4.2 - Split the Data into Train/Test Sets](#4-2)\n", + " - [4.3 - Forward Propagation](#4-3)\n", + " - [Exercise 2 - convolutional_model](#ex-2)\n", + " - [4.4 - Train the Model](#4-4)\n", + "- [5 - History Object](#5)\n", + "- [6 - Bibliography](#6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages\n", + "\n", + "As usual, begin by loading in the packages." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import math\n", + "import numpy as np\n", + "import h5py\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.pyplot import imread\n", + "import scipy\n", + "from PIL import Image\n", + "import pandas as pd\n", + "import tensorflow as tf\n", + "import tensorflow.keras.layers as tfl\n", + "from tensorflow.python.framework import ops\n", + "from cnn_utils import *\n", + "from test_utils import summary, comparator\n", + "\n", + "%matplotlib inline\n", + "np.random.seed(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 1.1 - Load the Data and Split the Data into Train/Test Sets\n", + "\n", + "You'll be using the Happy House dataset for this part of the assignment, which contains images of peoples' faces. Your task will be to build a ConvNet that determines whether the people in the images are smiling or not -- because they only get to enter the house if they're smiling! " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of training examples = 600\n", + "number of test examples = 150\n", + "X_train shape: (600, 64, 64, 3)\n", + "Y_train shape: (600, 1)\n", + "X_test shape: (150, 64, 64, 3)\n", + "Y_test shape: (150, 1)\n" + ] + } + ], + "source": [ + "X_train_orig, Y_train_orig, X_test_orig, Y_test_orig, classes = load_happy_dataset()\n", + "\n", + "# Normalize image vectors\n", + "X_train = X_train_orig/255.\n", + "X_test = X_test_orig/255.\n", + "\n", + "# Reshape\n", + "Y_train = Y_train_orig.T\n", + "Y_test = Y_test_orig.T\n", + "\n", + "print (\"number of training examples = \" + str(X_train.shape[0]))\n", + "print (\"number of test examples = \" + str(X_test.shape[0]))\n", + "print (\"X_train shape: \" + str(X_train.shape))\n", + "print (\"Y_train shape: \" + str(Y_train.shape))\n", + "print (\"X_test shape: \" + str(X_test.shape))\n", + "print (\"Y_test shape: \" + str(Y_test.shape))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can display the images contained in the dataset. Images are **64x64** pixels in RGB format (3 channels)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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QFU+hmQV4BlmZ6HQfOi2VJjBBAgw+9D2EPLeHufDumkWdg87hmHv4Ync45gS+2B2OOcGMCSdLGuRD09b2VW36iAvRbRdPaZfH5hK4sMZi+giFNiftt/5E2lX171gcoz4ouk+a6rxhBy05TjNtGju9JlF1MaT/jUrj9spghuJzug6m3KYNLkDXf/E73xqXv/Wtb6l2u7syd4UxqRVIqgh1pbG8obktWH1e6exgMjIECQH0w55xCyY4TipACNnXewxvvCJz9b4nf1nVffiDH4VxyFx1U/3sFGAqq5lIxbUVcfEtSzl3tWpTWEsfSaSvpZKIK3BMdg4wmq2majQwilGPPwTMrYeprnV8me5/dlFvDofjXQZf7A7HnGCmYnyel7S1NRSNt29qUeaJ918al9cunFF1CWZaAs+7KNYmjDgBcYi1OewuXz0RUaUi5rY40uIcRnxlufag22uJ6LS+LF5bZWlMgBGYtUpt4ilYRPV8oKP29vel7qUfSDrqjkmVHIGIXDFeVgnLcQzlNGixLwLxPDdiPJrpEhDdkylifBTMOEAFisC0lJn3y+amiPEv/eA1VffhD79XzgWeam/deFO1q9RAJcm0WtYbyJx+5Kk/PS4vNy+odmkmJrosM7z0MUQgmucKReugzHBkAFGGpQ31RhEfIu5YmyLD1LRf6bjVJPib3eGYE/hidzjmBDMV49N+Rld/OORIe2zZBI9A2qUy1iIhQwqfLBWejEpVk0ZgKqeopvvoQ90ekF5UqnoK1lcvj8uNhq7DwJsSgl02t/5EtUM1YbGh1ZU8l+91OlqMf/mPZYy3bgg5BnoGEhE9Dh5ki4n+ve71RdztgNNWN9LiXQ6WjNw48mWFtI3Ae6xqUkjFkAm2Emm5NYKmnMi96JmgmzupqCQ3b+r52NwS1WsRHCdvbGhRneFa6on2WEyAcKPflXaNmra04HuvUVudWHdoybCcL8vk2YyMepgXEkSVZ/qZqNeESCOOUYW13nQ4xyZIZvw8uhjvcMw9fLE7HHMCX+wOx5xgtuQVgaiWD3Wo2oI2m2Wl6KWbt7VO1u+JLvTYadGpmwvahFFh8bw76NxUdTu7V8flU+AJl5bai61SkaipfktHaC2CuQ1Vo85eR7VbXRXzzEGmTW99MAV19rVp77VXhfM9h3ZPrmhzz5NrMsYwMF6EQJzYAZNg3/yuI3dImVgPOlS4gcjiEDElED7YHFhQl1TAtGTScA1K0dn3dvV8/6cXfzgu/+LH5b4vJNrDkkFPv/zYe1Rd2hdTVgFEnb2u1tlL4EzlmiYciSJI52zOnWcw/0Hu2eFUznKdtaohNAG9X6eE1jp7UYBJ0EQq5qNrswGMCH+zOxxzAl/sDsecYLZifBTR0sJQDNpuay+l1QSydJ7S6XeSiog2vQMRlbodHbDQXJYgiJ0dLablhagNAxB9t3a1KpC1hQs9pFrkxOymCXCWLS3rgIV0IO129jVPegSsHW++ockxNm6JyH8KCDx+7pLmbauDKLy9aQKKwJMtgegX62mHhAylkc+DKsORcQtjDJKxPOlwnEA7m013rSZ1AxPUc+0tSV/1i78g3nTnVjXn++KCiMXLRgQvMBNvT+YqKzQ3PIGIT6e0SZcq4Mlmvpd1RPwvMjEdxjU9VwVkyo2a51Udg/l00BVPvkrTmjpFhcgHehzd7eFzVlg7KsDf7A7HnMAXu8MxJ/DF7nDMCWaqs8dRRIsLI1dSkzesAe6F/R3tNtkH4sRl4I2Pcq2zJ5HoQklP91+tihviQiR9tDpal2135VwDs6/Q6YvO1wadKWpo892pJdl/2DN9NJflOm9e06a3UIi+9cRZ0T0fP6N1yL0dcau1OlpZHE1KYQkqDEOFrsLvKRdNa9eBusia7zCqTsZUMSwadXS5NZFi3QOZu7An9/qDFy6rdlEi99oSmpQwP5WquDFzRZszaVH2dKKaduVG0tBsW6cTpxw45Qswifb1M5G2Za+J1/UzEZowfjCXFoned0ogfbblCtkeuRoXA0tEKThO+qdLzPzvmfkVZn6ZmX999Pk6M3+DmV8f/V+7V18Oh+PkcBwxPieivxlC+BARfZyIfo2ZP0xEXySiF0IITxHRC6Njh8PxiOI4ud5uEdGtUbnFzK8Q0eNE9FkienbU7CtE9E0i+sK0vpiZ6iORa3nZpNGpiHi7v6M9qYqeiDM7t8UzbnVVRyfd/rGYzQaGrGHlLJwvlssujAfamcvCN9Zb0pzyravi2YfSUi/VovQAvN96qfau2+qIKY6N+FyFULHzayKyVSL9mxwK5D2bLD6j2cx6VimJeZrblerfkFegJmB57JCsAcx+sUndVAV1rmJo1TIwYe5vilmyv6i54ZMGEEiY0ZdgUoug/6Sqn79oUcx5HOu6fE88G8NA3+sCPOgiUBnYmBhrNRlzbUGnt+aKjD+GcXFiVA1Qh3oHWgXMRg/koRwAgLe1QcfMTxLRzxPRt4no3OiH4O4PwtnJ33Q4HCeNYy92Zl4kot8mor8RQrC8OtO+9xwzX2HmK7sme4nD4ZgdjrXYeeip/9tE9JshhH8x+vgOM18Y1V8ggkgCQAjh+RDCMyGEZ9ZWFo9q4nA4ZoB76uw8JAv/R0T0SgjhH0DV14noc0T05dH/r92rryiKqNEc6sEra3rzfq8lpqxeR7sC1mqi01zfE32+bFiSQ2l3p631/oNIXFNPLYuJrm90e4aIpMcfe0qPEXTIsCftfvEDH1TtOhDpFplsyD9+S3LQxYbYsLMjun4dXIRzk946B7dSqytjJFoEun7EeiD4NcsHj3sJWgc0bDQ8sUodq/6NLtuoiV66ZNx2cXZSMKk1VzURo9Jlu31dB+eL6nLPokWtdUbgEhuMK2oJefci1kumAhF9UQxRarGekAo8w0lT7wkwpPVmyEdQZnoc6ZbsHbS3dDTllBRvct57N6FPENF/SUR/zMx3KU//Ng0X+VeZ+fNE9BYR/cox+nI4HCeE4+zG/0ea/LvxqQc7HIfD8bAwUw86jmOqLQ5FmJy1OLd5Q8xae3uaJ71TihjVSsTm9cRZLWavLT8xLh9c/QNVt7QilxpBaqjldR1BNYAUTFGixcX3v/9jcgB2nIWmITvgD0jZ/E6eOy/eX2+9+oaq27v6gnwPZOQs06rGAMX6Q0SPIMbD5/EhzncklSQN/CAAeYUV4xWrpN7+KUF8DmDqjBpahG00xLx5uqavM0tFPK83wQxqzsVVIH/om9RNEBGXnBLyEa5oEooApB9lT0cqKm2lps1hyJePo7IOiwwqBCfapMsRELlAf4MDvQ3W29uDZvoEY1PfYcL6I8fncDh+iuGL3eGYE8yWvIIjqjWGnkRXf/SqqtvfE9N9YkS9KAg/3coiiGyx3qW+vSXpg6pVHYjQrIq33ToG05zW3kyBRIS7fus7qq4KO/XNhlgT2ibYZVCK19zKghFbq+BJVdG/tUtN2LGF4A42HnSY5iquaJ50jiAwQ+3M2x136NNwuU9CYd4NPZC694yq0YGAlxg47lYizYH/vtOPj8vnGppzLd2XeTx/Tu4ZG274CLwvo0T3X1lEz0n4nvE0Kwfg6ZiYZVEHDjqT/ZVSOV8E99ru2mO2Xcw/YFH0RFQftDQxSZpDOq9C37O8cA46h8Mxgi92h2NO4Ivd4ZgTzFRnD6GkbBTBtrqmCQL64PlUv6C96y5dFPPY5raQEO7uGcJGyA3WCFpHrUHK36QietFPrn5Xt0OvPKMrnzoj+n0D9LjtfW0iKcD3q1b5GVXXbIhp6MwFvV+wBl6FS8vSf92Mo7Mp/d/pGN74juxjFBlExxm1PEI+eGMGxabIw7hrovu2+nJum4p5ETzGlkHPbRjiy7QvEY2PXX5S1VXWwGsO9nGihjZ1lhAVyTUdERcvQDRbInWlJf0oYX8j1ua1uIlRdVopjiEyjWtAjsFmX6EOx2a+UdEuwPTWY51boQdkpQNjfjwY5QMsXGd3OBy+2B2OOcFsPeiYqTYK8KgYAoINED+6N3T6p0ZdRN+Ljwt/+M6W9rQLS3I5seE6G0A6nqs/ERNdYTnRYhERG5EWxZogmg764M1UaJHw9Jrw3ldiPcYUgmSSmv6tffw9T47LEYkpaLelAyJeuSHqyvauJsdo9URdwfTQTZNueR3MXDXjdVWAKS4HETOzqhGYqJaNuWoJxNY6pMWuGLNZXMh4s442YS6tnRuXX7siqaAqH/tF1W7t8iXpz4wxqqMXJIjqiWkHQSw2MCiEyVzsymMNRGudxkmf21JslAFNavK9NNbcg/G68Cg2jVrWOD1cIxXj4YfwN7vDMSfwxe5wzAl8sTscc4KZ6uxlWVKvOzQR7G1os9kAbAalcd/kgdStLQnxRO9A67ILj4vutr91Q9X1e+LWOEhFT7/8p7QJsFbIlAx6mgihFosOubAgqYE5+YFql1REx9vYv6rHWJE9gVPLOmrvPR+Sa9t57Y/H5SjWrr/nFyRiqzYwvPfgZtsHMk0b2dYAPbqRGDdYmKsA5B4Vo8vmcJgY8yASSdYroLPXtM6eg9tnZ18TMixCau2QQo6/qzod9/r7PjwuR7HVlY9+nx0KDrMpp1VbSDlt/FFZfW8y0cdhKkxBDsQcGx1pd9uQv7W6QPCiHwmivDf63LB2AvzN7nDMCXyxOxxzgtmmf0oqtHB2KJrduK7Na1mJRAXaQ+qxD/zyuNxcElF9fVF7rvVBgrve1eYSzkV8rEA6n6Wgf+8akJ6pXNKefOungG8sEq+totAEGN22RPQ165rr7GBbRNXlup7+elVMLVXwzFq7oM0pb70uaX1LE21WgFjcByKHrmmHV73W1EQOOD8HXUjLbDjiUIHol8ZcBdM/yOVszVKL2cvISRdsZB48E2vibVgzkWdaeD7u++vtvOfQ23Aa2dsxiOCIqNPXkXm3tkSlRS7G9o7mho9gjZxq6HvWG6lbEU2OYPQ3u8MxJ/DF7nDMCWYqxmeDAd25PqTD3TOUvzmIQBefeI+qW1i/MC7vbQid7k+u/kS16xUS7J+aLK4HPfHOegyyot54TY8jK8U7bfUxzUHXyyW7bMKSzfNgR/9m5pmIX+vndTADxkDsbevxrxZCsNEsRQSv1rTIdv6CtKuZnfTdloiIPZDoeobsoAJECLnhM2vA7nk/FvF/qarF1AEI0DYwoxuAgw7KCdnsujI/tapWV/BsZV2CTMpD7R7Fd9a03Xd9LzDwprUvKlprV3PhEXh7hoF+rj70oQ8REVG9NnlJP4qz5HA4HgJ8sTsccwJf7A7HnGCmOntRlGNO+MJEP1XqorckhnjwzR9+e1zegJTNdzbuqHYV0Fc6PZPCB37WApiCEkNU0GqLzWj7hjaR9LrQ/4G4Nw262p3pzCWJ6LvxmiYNXDkjutb2gU5RhSmaVmB+8rbeV0Dzz0ZPmxg3wKOuC7/lSUXf6hqkl2oY4ssa6N/VRPpftl5mEDmGOjoRUQREmE24n6sLWtdcgEhCuzeBZJo5nLs45CU3LeX0o4eFup6DblfMuO0D2VtaXtDzsQCpqdtt7V7XaQ33icriPjzomLnOzN9h5u8z88vM/HdHn68z8zeY+fXR/7V79eVwOE4OxxHjUyL6ZAjho0T0NBF9hpk/TkRfJKIXQghPEdELo2OHw/GI4ji53gJJQs3K6C8Q0WeJ6NnR518hom8S0Rem9cVxTNXlodkoGWjxMwYx8/bGlqrb2pbjAXKHVUwqHiBQYEPWUML5bt4RwodTy9pbL0AqntQkBM03wYMOUvicPqeDaU6vCckAr+kpTjtCZlFkWhTLVyAtEASqcEcTYEQR8KRHuv/1JemjDplELZnHuQURkc+saiKREsxyra6YAOsmmiapiji9bLKzBiCDqEF6pqbhua9O48CH+1mCzbK2rE2iPCWI5eQwOd3WXkerh2/ekOe7ADE8Mp6CGdyX5SX93L72xptERNRPdd+I4+Znj0cZXDeI6BshhG8T0bkQwi0iotH/s9P6cDgcJ4tjLfYQQhFCeJqILhLRx5j5I8c9ATM/x8xXmPnK7n7r3l9wOBwPBW9L/gkh7NFQXP8MEd1h5gtERKP/GxO+83wI4ZkQwjNrK0tHNXE4HDPAPXV2Zj5DRFkIYY+ZG0T054no7yHrWK8AAB0ySURBVBPR14noc0T05dH/r92rryiKqLkw1A8XgeubiKgF7rPtba3LlgH01yl85zFczuqiTouLLqEQTEV9wyVYq0FqXWOSQjfHU2dFb2w0tc5bh4i1psn11rwk6ZyTqtY9KQeCjQ3JM1ep6nEsA9Hm5TNaF2+A7tyuQb64XLdrQp81YwpCS1ZlV+5TsAFVoCvbvQPcg6kqwkndLkJd3+yzBNB7M5j7yI43ehR1dg18/tpmMyiDPHMFhAvuHGiTLpKA5LnWzbd390afTza9HcfOfoGIvsLDlRUR0VdDCL/LzH9IRF9l5s8T0VtE9CvH6MvhcJwQjrMb/wMi+vkjPt8mok89jEE5HI4HjxnzxhNVRuab9RXNiY3eU6UxWwxANMH0NtZvanVF/Hqai7r/EvjJa00giTA820kCJqOmrstzMUOFQsq1uhbH63UR3StV7QWl0y8fIkKTcUDqn+i09lda3hYxPu1r2boAvaQCom/X8OnlQIRgUwYpzrgERUdzLiD+yE0fMYj4MYjnsYnSi+CYjWfcAMYYQ9Rb/dQZercBOfrOrulns14R1a5zQXj3um2Tsnkgz9wbP9E8fIMReci05NuPvrLjcDgeCHyxOxxzgpmK8ZVakx77U08TEVFvXweBrIPnECd2WOA9Bdxb6MVGRFRvCqlDbAJtAoiEUYz9H483bCaAMXNDONcCa4/CJoj1C/taPG8Dh1kPLBwcZapdBhleBwMtg9dhpx6pmdnI+zHMXWy82BSdHKouZuc8gFeezZDaG8iO8/pp8dmqL2rvsXcDcDqaiVZXmqvwHGOZHlPtilJUtCfee1nVtbpDJ9f//X/6HyeOwd/sDsecwBe7wzEn8MXucMwJZqqzR3FMtYWhmara1FzrmFUnTnS0j/WUg5p7HEPNIcKDRxGQUnjp8XE529P84fESmPYaeu8jqcjcYRRZZPZBKjBVC02994G5kdC8Vpr7kKIZ1PCpV0E3R/3d+ndhIF1u02xnYN4EkovI5rJ610EbyAKkE8fJyoPejykK8bSrVHT6tKWF4f5GHE9OL+1vdodjTuCL3eGYE8xUjCeKKYrveptZX59oQnk+EdVEVA/V86quzK9DO6PyAFEEAflBUtOmtz6Qyl/d1KHHNQhcGUCAS8vwm+0BIUjTBOvgESYWrRmOeqDdU6QZRERckbaLC6hqvNvFeD0HeZCUYL1UTKdFoe8Zw5q5vXPL1A3nJM9djHc45h6+2B2OOYEvdodjTjBjnZ1Ifl/8d2Y6RC+tLJxTNdmW5AMjY1IbgKlsL4NcbCbHGoOJrj3QHPtbB3IcgynowBAjKGoFk265n0LEWpDvLVeMzg4uuJHpfwWi71ZW3+1M5XKdedlWNSmY1IIyTmqdvQDT5FpTR1rmxZBkJJ5ilvQV53DMCXyxOxxzghMQ4x1vF7EhwMgqwlPfz66puj6IxUgCcpBqk0w+ECE8NsQTFeCFyzIRHauGG74Et0cOuhP00AN6eYqM2akP5raKMcstgqfg4pLh63vXQa6tKDW3XFkczauYVLRnY8LyHAxYe9Dt7A4jI8tyMn2Fv9kdjjmBL3aHY07gYvy7AnqHtbIsQTJF5U9UXQEBKJj1M2RadGS485WgiT56kJ6oDWJ2YoJdGpDFNa5oER/pr3NIQ1UYKbMEtSM2O/rrwDVXqWhPwUcfliFRjpNYq2VpLoFOvb4EvxSFvmeDVKwwg0zv6Hda/dF3XIx3OOYevtgdjjmBL3aHY07gOvu7EHFN0k2dfvJnVN3t26LXHbTEMyup6lu9ugDHhTbLYdrgErjKrTqYxEhMOZlIMgNdPDWklREc24i4ROm9WH5Uo95kgoL2LzQw1wlknbVI+mDWun1oS3Rc36TxLvK7aboegM4+Stv8R8z8u6PjdWb+BjO/Pvr/bvdndDh+qvF2xPhfJ6JX4PiLRPRCCOEpInphdOxwOB5RHEuMZ+aLRPSfE9HfI6L/ZvTxZ4no2VH5KzRM5fyFBzs8x9EQMbaxqoNk1s8Kt9/1W3fG5cwQQzTgZz6Yuh6I1h0QrTumXR2k0apJ8ZoAK0UHAjoywxsfBTHZNaqac+1gU7KA91sitsZ1Ld4OUuk/MiR36FB2MJD+Y8PdnsBxxdRVICDHBpqgKlMGEK1Zq0Yl8Ml1Up26KQXvxmZN7l850HOaQ46tdq+j6rr9obm0tLm8AMd9s/9DIvpbpBWCcyGEW0REo/9nj/qiw+F4NHDPxc7Mf4mINkII330nJ2Dm55j5CjNf2dzcvPcXHA7HQ8Fx3uyfIKK/zMxXiei3iOiTzPxPiOgOM18gIhr93zjqyyGE50MIz4QQnjlz5t2XfdPh+GnBcfKzf4mIvkRExMzPEtF/G0L4q8z8PxDR54joy6P/X3uI43RMQGTMUAvgtpqD/mZNXl3Q/7K+NhN1wdxWQn6xYEx0PdCPU6MsIxFFn8Udt4hMdFwJEV817ba7ee2tcfnl9Jvj8uWfeVq165Tyznr9lauq7lJD8v9d7YtOvWsiz+IY01Rrnf3UmkTf5ZkmlHjilOjYj18Env6aiTIcm8aIsoHem9htCff/zU0hksy6+lwRdHmwqwlHaEQQEh5S1NuXiejTzPw6EX16dOxwOB5RvC2nmhDCN2m4604hhG0i+tSDH5LD4XgYcA+6dzlKEA+JiAjSHC9B5NnunhYJez0RY9Ou7qPflz4yFOmNC10HiC1yS4ChUk9Bu8iY78B0Ffpa0GwfyHEPTG+tvR3Vbv38E+Py9vYdVbebiVi8XJNUz1vpvmpXYsppE923vSOmvnqlpupe/9Eb4/LTl0RlOP+zqplO5TQwfPADOXfn4GBcLky7hVg8JwMb7vlRVGMI9296czgc73L4Ync45gQuxp8grMgVYMc864HHVVsTFSwuADHE7R+pusG+iKdLsKlcNQESd9rSf5bqneleD8R42H1mE6jSRTHeBskg6UUi5WpV91EtZJBlqqpokBydeXfzjt7Nbh+IWJ8V+ju3unLuy5BSKze78Z2A1gQtxnf2Zb4vnNbZh/f2t8flb++ICvGJ5IJqt/Y+6T9tafF8efn0uBwSudftUr+LV1ZFjKdSe9Bt5EMVJUzMeOxvdodjbuCL3eGYE/hidzjmBCegs9/V2R5VAoIHC6uXd8HMtbe1p+qaYAF77boQSS4tac+yC3XRWfdu/FjV9bqg3wM3/Iq507ugw3eMV9ggE1ctjMgKJrJtAKa4Mky5nzAFK1WtU8a5KOqFTWWM5BjwWurnuo88BzNiqev2OzLGbSBzjI15rYeegmb4DJ/sG1KKGIg+bu2K2ez7L2oPt2fPgS3OkEUetMXTfG1NuOJXuK7adQZb43IZ63tWGzWN2E1vDsfcwxe7wzEncNPbA4BNuTMAz6eO8U576yfXx+XkQJtP9roi0r61e2Nc/jDr1Ee3NiRU+GB7W9VFQBSBHljVUgeqnAXvulDRIm0K5qoSvpcZDzrkKD8sPMonTei/UWrxM4BUnJkxMqgaFcV3p0X1Ajjx+8Zc1W2LeL4Zixh/KtGqUVYAwYYxU6IqFudaPF9bEI+6bkfUstfb2kPvie9fHJc/8st/Wo8xE97AdibPS4j1OPYhYGmrp5+rM6uXiIgoSiYvaX+zOxxzAl/sDsecwBe7wzEnOAGd/afD5JaCi+nOjjah9SBqrNXS/N5bm+JSeT7Tc3EHSAx6oP/tbGrdvuhIu35Xm3ESIIcoQZfFFM1ERFEuuuzZmtaBF9fE5LMJw9/v6T7SDFI2G60du2wS6OIm51wO+x1lofX5Mof9ByB9rFq9FFJJp4UxqQEBxIBE325UtVkrwLlTY76qASFIMPNIVTkOmfS/aebqO3/w++NyYqLZTp0X0tDmuuzPJMZeWoeceWXvZVWXJtuj69CkGQh/szsccwJf7A7HnMBNb28DyE9+46Z4PXW6WsyuVcWs0zNi9gD4vrOBFhdvH4hJrdcDvjQTUlam0kee6VCxBERQRs8yE9mGXGqFEf0qYGo6VZNHpG7E224qYiV63RERReBtxzD+3JgpA3igEet3Tx7jGGUcZUWbzRjc63paQqYemDML8PLbN+oEpprqmvlIwLzWXNCc9flATGAFlDs9HZl3tS8i/sqL/0HVnV6RdNSVmpRXzjym2q1fvjwun1mwCZiGF85T1GR/szsccwJf7A7HnMDF+GkwQSx7OxLosLsnHlLMRswG8Xl3T3u4leD51DPpfVog8ndA3D9ItWyaFNK/3cEeYLAK7GZbCmQkpchys4ML143BL4khr6hC2QqPBZJBwNest2GpAlJ0LyozLF6XCchBMT5NTSqrHorxMpBNI8afBaKMwszVLVDTWi29ZJbqcrx9IKJ7atQa5Oi7FvS5K0HUBNRQWvs6FcPO7avj8vn3vFfVXXz6Q8Pvx1rFQfib3eGYE/hidzjmBL7YHY45gevsU5D3te62vSuea13QqSMTJVWtgA5popPiFMgrujqCCvX0fh/MOIaooB5AHzT6ttKJQZ8vTbsCTF5ZZvIcq70KKBtdOYY647hGqN4r0gtDGqG6NH0EeBdhpmS7PxCBzp4Z77QBzDdaMHcirTevgMmrUuj52Ifjfl/vW2wS7m+oi9bjgHa3DSnm6ZrUrSxKHZv9mNaeeF/mP9Lm3rR1MPqvP0ccNz/7VSJqEVFBRHkI4RlmXieif0ZETxLRVSL6L0IIu5P6cDgcJ4u3I8b/uRDC0yGEZ0bHXySiF0IITxHRC6Njh8PxiOJ+xPjPEtGzo/JXaJgD7gv3OZ6TB0hf7V1NQLAPQS0ZpFmyvF8H+9Ku0z5QdUvgSXXQ1UEy/VTq0hSCadgEsTCImUbkLOEYy1QaMR6yrBa2D0sCP8JhnntUGXQfOpvoZPFWHbMV0KFuMq07EWSCzVLtUZgC7xzE7ZChqKd9MBXWzSswB9NnbudgQrqlw5/L8XZk0ku1QIxvCgedcShU96Xb1sFXt38yvE6bIRZx3Dd7IKJ/x8zfZebnRp+dCyHcIiIa/T97zL4cDscJ4Lhv9k+EEG4y81ki+gYz/+ie3xhh9OPwHBHRZfDtdTgcs8Wx3uwhhJuj/xtE9DtE9DEiusPMF4iIRv83Jnz3+RDCMyGEZ86cOfNgRu1wON427vlmZ+YFIopCCK1R+S8Q0X9PRF8nos8R0ZdH/7/2MAc6K6CJam/XklKITt3vSbnb0bp3D3Tx1ES9NYDYot0zEXGgb6LOTsa9sp5M1pVx/EpvNmSOqG/bVMyow6Mpr7T6KtjXSuvCCjqqMpuZPgp1bEx7Qd5FaKyyDqEBdPYiN6Y3IJvI4FqCUfw3YH4u16qqLgbX2q6N2lPbEUjmYcYI82F3RDZhz+csJOhbXtBXintDpSHuTPv56HNjRgUcR4w/R0S/w8PNk4SI/q8Qwr9h5heJ6KvM/HkieouIfuUYfTkcjhPCPRd7COFNIvroEZ9vE9GnHsagHA7Hg4d70BnutEFHPJB29rXpDb3a+n30dtOecCm0y/rag64A8bxt6vpQNwDTXpZrMX4B0h5XjfiszW3l0WV7bMR4hj4DiIWHTG9TxNYK8KUlGLxmzXpg8rKWN6SzR4E2KvQ4SkIxXpsYUR1ClcEaxnZAVD9taqvK21DfiwmWt0PAubIscRsg2J8/kCVptAlKYE4j67E4vk+e/snhmHv4Ync45gS+2B2OOcGc6uyguxlywYOtnXF535jN0NzWg2i21Ojs2K60daBDdvratRFdcNEMVxg9sQMmryg27C5I9Ih6+SE3VWh3yBgEuc0I25k+4FXBxrczAZaZBBTMgdGpA5iTKkYRxWjCGK/ZKvdwPDBzlcKcqkg83YNypd2L9LUgX3uwjD8TTG/2DEgEGUzdHuwJbB2I6W1lUS/PRg1MkeY1zaN5nLaF4G92h2NO4Ivd4ZgTzJEYD6I7eFllLR2Vtr0hXr8tI8b3gFwi7R3tTXfouK/jq7oguvcGum4A3O4DJIQ0hAxtkEcXTYgWHkVoGjOReWxtNwCURvHMwaYyBtE0inT/wN9IFeU9pttV4qM97YZjvnd5eCx9pJa8Ao6tByACazb17aRLTSGEjHLtoTbIJ3ismTEq1cMMow1RjFsduYOn29r2lsSSsqrU/BcURcN7M80U6G92h2NO4Ivd4ZgTnIAYf1cUfMi/M9azDNP0tCVQZe/Opmq3uweZVHuG5wsDYaCcGk+4ARAIJFZUh+O+rYOd5GxwtEhPRHQAJOQXqjVVh55rDKKjne14shRPBe7ig4hsd5FxJ52MmlCFHe0I1A6TMJaUvGtkUBw/bvZbUgfkZD8walMG/O1higcdwqbbOgUugFXjiYgee9P61KqH4eGDL26zjH+npa01C03wrjN3VPgA3YPO4Zh7+GJ3OOYEvtgdjjnBCejsxwwTekddi/5U9rW+PQATW3dfSCn2t3Uutr2OmNt6xqTWm2BuO6Szg/dbbaA9utDc1kutPi+6uTK9WZ0dItG6DX0LFytironht9yq6Mq7znrQgYIJ/BFUmlxvNM0cBtFsEdjU6kZpRx7MaSSNOI5g9gcGmYx/u2N0dvTYUx50Zv8Bv2OGsduTMQ/MXlAOpjfs014Jmt7svWhEMCcQgXjQ0c9OfyDnsh50d82gbnpzOBy+2B2OecEJiPEP8PclaPG27AP3myGe6ByAGA/87wf72oPuoItivFYF+uhB1z+a451Ic5cHY17rwrH19kJihAy9/AyvWgHmpFttLRSegRTCGM9hHNxUSibrWVZOSGN0yOmOJ8uMSICB6ZkSI38W0EdhSDRUlmYcn9E69nqQIrutzVWFErMnQ4WwmPnYgKCnyATJ5IrcAyosuQR8kBidZymRe8agKrW6+r73U7nv9Yoex70Nb/5mdzjmBr7YHY45gS92h2NO8C6MegNO81TztQ/ApNY90Lp4H0xqaVd0b8zfRkTUAr28Z4kkIf3vIO0fWSYiKkEvZ2M2ayE3vCFamGRus6a3HHT22y0ddfW+ZXGfrdSAptH6mPIU0xsSW4SjXWeJtLntkKlJtZsc9YbjCtbFGfRc3EcojNJ+bVfuWTvVc5pbc+ExYPcw2iXuP0wOzVNV5rQ4jNJ0sQVpoJdBf7eexe2ePAeLTb1047vjcNObw+Hwxe5wzAnedWJ8yICTfX9H1XXBS67f0WazDETwvhLjtbjf7k7mgx/0UXRHE5oW4yvIe2bSM7UmEFQQaXE9B8+v3BAkoLnnoKf7uL4n4185szwuW68zlPcsBx2DiF/y0WY4IqIyTI6qQ9NTRBNEXSLK4diKt0r0hYPOQM/HG1uQStvM1SSp9rCnWZhcB4M+VIfc9uAJ1zQmxhY8B5buAjkFcUHWjOrV7cszUVjawAfFQcfMq8z8z5n5R8z8CjP/EjOvM/M3mPn10f+14/TlcDhOBscV4/9nIvo3IYQP0jAV1CtE9EUieiGE8BQRvTA6djgcjyiOk8V1mYj+LBH9V0REIYQBEQ2Y+bNE9Oyo2VeI6JtE9IXpvQUKNBRxmWqmbgqbAgRV5G0R3Xst7SWHu+wDI4LnIFq39uR7na5ul0GAS2522bXojqma9A5wDXbLU0Od3MkwrZMR41F0hz5yQ3eNXmGFURNe3RK15PyCzPGZpsl9CvKozfxpd8XHsLxqUE7MayNWxBNHE2oQ6cyktg457zB109UdraJdh934Q154NAk2lRUc2EexxPHrKgxwOQPWD/sWTeFaOjbTKvTZgVu9EOv9+B54XGaFtWo8mECY9xLRJhH9n8z8R8z8f4xSN58LIdwaniDcIqKzx+jL4XCcEI6z2BMi+gUi+t9CCD9PRB16GyI7Mz/HzFeY+crm5ua9v+BwOB4KjrPYrxPR9RDCt0fH/5yGi/8OM18gIhr93zjqyyGE50MIz4QQnjlz5syDGLPD4XgHOE5+9tvMfI2ZPxBCeJWGOdl/OPr7HBF9efT/a/c+XUlDlZ+I2eSjnaKzhxwIH8Dc1uto77cemNsKE23W64gufnAg3yuMbr8M+jcbXfwATGxIHBlM1FsT1MaO6aM/zTMOdPgcdHFrekM9vTB1u6DXvXRb5uqXLp1S7apIShGMDjkhFXNk7hHqr9azTEXcqa6NrgzXEpk6JMXc7ct1ffetLdWuNwDSkmNyw0/T2e21qD4PRbNBGUxoy1W9tLqwHzMwWyIp9J/CnkPPmlyhzursPI1BdITj2tn/OhH9Jg9X6JtE9F/T8B5+lZk/T0RvEdGvHLMvh8NxAjjWYg8hfI+Injmi6lMPdjgOh+NhYcYedBExN0fle4sdd5F1xFTW3Qde95ZOzzQALrjcBJl0QeRvwff6Pc0f1wPT2L7xjEvBFJeD6L6QadMYTuqOMd8hYUWWTTapKTG+sGJ8PrGuBPHutU2Zt9WavtUfOrN05HiJjOjOk81OCoeyxKJpT8TPyX58dGgHqdWV6/wPb9welzHwhYgon5atdsK5rDoRx9HEOhTjrXkQTX3X2jKuxdVl1W4FAlz6NoUUiP8leC92rMkVhjWwAT6jLicYTYnIfeMdjrmBL3aHY07gi93hmBPMWGcPRHRXlzbum+pY6yNpG/T0triDpkbfzjE/mtGVe+AW2wGX2J5pt1eITt0tJhNCFmA2Y+MSO4Dht4zpDaPZrKsr6t/FhPLwGKLSDJEDmmcGUL5yTZurmmCqeXKtqeoqKmJNcMidFUkprPemyhcnvVidEvXjg1TP4wuv3hqXX7opz0BuXGKnmdsmwX4HiR5jQyoZphBnYD9oXrvW0Sbd9y0tjMtLiXaDTYH3vgfP/sCeC/YVepmuy0bjP8TtD/A3u8MxJ/DF7nDMCfhwyp2HeDLmTSL6CRGdJqKtezSfBXwcGj4OjUdhHG93DE+EEI70S5/pYh+flPlKCOEoJx0fh4/Dx/GQxuBivMMxJ/DF7nDMCU5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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "index = 124\n", + "plt.imshow(X_train_orig[index]) #display sample training image\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Layers in TF Keras \n", + "\n", + "In the previous assignment, you created layers manually in numpy. In TF Keras, you don't have to write code directly to create layers. Rather, TF Keras has pre-defined layers you can use. \n", + "\n", + "When you create a layer in TF Keras, you are creating a function that takes some input and transforms it into an output you can reuse later. Nice and easy! " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - The Sequential API\n", + "\n", + "In the previous assignment, you built helper functions using `numpy` to understand the mechanics behind convolutional neural networks. Most practical applications of deep learning today are built using programming frameworks, which have many built-in functions you can simply call. Keras is a high-level abstraction built on top of TensorFlow, which allows for even more simplified and optimized model creation and training. \n", + "\n", + "For the first part of this assignment, you'll create a model using TF Keras' Sequential API, which allows you to build layer by layer, and is ideal for building models where each layer has **exactly one** input tensor and **one** output tensor. \n", + "\n", + "As you'll see, using the Sequential API is simple and straightforward, but is only appropriate for simpler, more straightforward tasks. Later in this notebook you'll spend some time building with a more flexible, powerful alternative: the Functional API. \n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.1 - Create the Sequential Model\n", + "\n", + "As mentioned earlier, the TensorFlow Keras Sequential API can be used to build simple models with layer operations that proceed in a sequential order. \n", + "\n", + "You can also add layers incrementally to a Sequential model with the `.add()` method, or remove them using the `.pop()` method, much like you would in a regular Python list.\n", + "\n", + "Actually, you can think of a Sequential model as behaving like a list of layers. Like Python lists, Sequential layers are ordered, and the order in which they are specified matters. If your model is non-linear or contains layers with multiple inputs or outputs, a Sequential model wouldn't be the right choice!\n", + "\n", + "For any layer construction in Keras, you'll need to specify the input shape in advance. This is because in Keras, the shape of the weights is based on the shape of the inputs. The weights are only created when the model first sees some input data. Sequential models can be created by passing a list of layers to the Sequential constructor, like you will do in the next assignment.\n", + "\n", + "\n", + "### Exercise 1 - happyModel\n", + "\n", + "Implement the `happyModel` function below to build the following model: `ZEROPAD2D -> CONV2D -> BATCHNORM -> RELU -> MAXPOOL -> FLATTEN -> DENSE`. Take help from [tf.keras.layers](https://www.tensorflow.org/api_docs/python/tf/keras/layers) \n", + "\n", + "Also, plug in the following parameters for all the steps:\n", + "\n", + " - [ZeroPadding2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ZeroPadding2D): padding 3, input shape 64 x 64 x 3\n", + " - [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D): Use 32 7x7 filters, stride 1\n", + " - [BatchNormalization](https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization): for axis 3\n", + " - [ReLU](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ReLU)\n", + " - [MaxPool2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool2D): Using default parameters\n", + " - [Flatten](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Flatten) the previous output.\n", + " - Fully-connected ([Dense](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense)) layer: Apply a fully connected layer with 1 neuron and a sigmoid activation. \n", + " \n", + " \n", + " **Hint:**\n", + " \n", + " Use **tfl** as shorthand for **tensorflow.keras.layers**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "95d28b191f257bdd5b70c7b8952559d5", + "grade": false, + "grade_id": "cell-0e56d3fc28b69aec", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: happyModel\n", + "\n", + "def happyModel():\n", + " \"\"\"\n", + " Implements the forward propagation for the binary classification model:\n", + " ZEROPAD2D -> CONV2D -> BATCHNORM -> RELU -> MAXPOOL -> FLATTEN -> DENSE\n", + " \n", + " Note that for simplicity and grading purposes, you'll hard-code all the values\n", + " such as the stride and kernel (filter) sizes. \n", + " Normally, functions should take these values as function parameters.\n", + " \n", + " Arguments:\n", + " None\n", + "\n", + " Returns:\n", + " model -- TF Keras model (object containing the information for the entire training process) \n", + " \"\"\"\n", + " model = tf.keras.Sequential([\n", + " ## ZeroPadding2D with padding 3, input shape of 64 x 64 x 3\n", + " \n", + " ## Conv2D with 32 7x7 filters and stride of 1\n", + " \n", + " ## BatchNormalization for axis 3\n", + " \n", + " ## ReLU\n", + " \n", + " ## Max Pooling 2D with default parameters\n", + " \n", + " ## Flatten layer\n", + " \n", + " ## Dense layer with 1 unit for output & 'sigmoid' activation\n", + " \n", + " # YOUR CODE STARTS HERE\n", + " tf.keras.layers.ZeroPadding2D(padding=(3,3),input_shape=(64, 64, 3), data_format=\"channels_last\"),\n", + " \n", + " tf.keras.layers.Conv2D(32, (7, 7), strides = (1, 1), name = 'conv0'),\n", + " \n", + " \n", + " tf.keras.layers.BatchNormalization(axis = 3, name = 'bn0'),\n", + " \n", + " tf.keras.layers.ReLU(\n", + " max_value=None, negative_slope=0.0, threshold=0.0\n", + "),\n", + " \n", + " tf.keras.layers.MaxPooling2D((2, 2), name='max_pool0'),\n", + " \n", + " tf.keras.layers.Flatten(),\n", + " \n", + " tf.keras.layers.Dense(1, activation='sigmoid', name='fc'),\n", + " \n", + " # YOUR CODE ENDS HERE\n", + " \n", + " \n", + " # YOUR CODE ENDS HERE\n", + " ])\n", + " \n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "8d3575c950e2e78149be2d05d671c80d", + "grade": true, + "grade_id": "cell-e3e1046e5c33d775", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['ZeroPadding2D', (None, 70, 70, 3), 0, ((3, 3), (3, 3))]\n", + "['Conv2D', (None, 64, 64, 32), 4736, 'valid', 'linear', 'GlorotUniform']\n", + "['BatchNormalization', (None, 64, 64, 32), 128]\n", + "['ReLU', (None, 64, 64, 32), 0]\n", + "['MaxPooling2D', (None, 32, 32, 32), 0, (2, 2), (2, 2), 'valid']\n", + "['Flatten', (None, 32768), 0]\n", + "['Dense', (None, 1), 32769, 'sigmoid']\n", + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "happy_model = happyModel()\n", + "# Print a summary for each layer\n", + "for layer in summary(happy_model):\n", + " print(layer)\n", + " \n", + "output = [['ZeroPadding2D', (None, 70, 70, 3), 0, ((3, 3), (3, 3))],\n", + " ['Conv2D', (None, 64, 64, 32), 4736, 'valid', 'linear', 'GlorotUniform'],\n", + " ['BatchNormalization', (None, 64, 64, 32), 128],\n", + " ['ReLU', (None, 64, 64, 32), 0],\n", + " ['MaxPooling2D', (None, 32, 32, 32), 0, (2, 2), (2, 2), 'valid'],\n", + " ['Flatten', (None, 32768), 0],\n", + " ['Dense', (None, 1), 32769, 'sigmoid']]\n", + " \n", + "comparator(summary(happy_model), output)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that your model is created, you can compile it for training with an optimizer and loss of your choice. When the string `accuracy` is specified as a metric, the type of accuracy used will be automatically converted based on the loss function used. This is one of the many optimizations built into TensorFlow that make your life easier! If you'd like to read more on how the compiler operates, check the docs [here](https://www.tensorflow.org/api_docs/python/tf/keras/Model#compile)." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "happy_model.compile(optimizer='adam',\n", + " loss='binary_crossentropy',\n", + " metrics=['accuracy'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It's time to check your model's parameters with the `.summary()` method. This will display the types of layers you have, the shape of the outputs, and how many parameters are in each layer. " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"sequential\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "zero_padding2d (ZeroPadding2 (None, 70, 70, 3) 0 \n", + "_________________________________________________________________\n", + "conv0 (Conv2D) (None, 64, 64, 32) 4736 \n", + "_________________________________________________________________\n", + "bn0 (BatchNormalization) (None, 64, 64, 32) 128 \n", + "_________________________________________________________________\n", + "re_lu (ReLU) (None, 64, 64, 32) 0 \n", + "_________________________________________________________________\n", + "max_pool0 (MaxPooling2D) (None, 32, 32, 32) 0 \n", + "_________________________________________________________________\n", + "flatten (Flatten) (None, 32768) 0 \n", + "_________________________________________________________________\n", + "fc (Dense) (None, 1) 32769 \n", + "=================================================================\n", + "Total params: 37,633\n", + "Trainable params: 37,569\n", + "Non-trainable params: 64\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "happy_model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - Train and Evaluate the Model\n", + "\n", + "After creating the model, compiling it with your choice of optimizer and loss function, and doing a sanity check on its contents, you are now ready to build! \n", + "\n", + "Simply call `.fit()` to train. That's it! No need for mini-batching, saving, or complex backpropagation computations. That's all been done for you, as you're using a TensorFlow dataset with the batches specified already. You do have the option to specify epoch number or minibatch size if you like (for example, in the case of an un-batched dataset)." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/10\n", + "38/38 [==============================] - 4s 105ms/step - loss: 1.2817 - accuracy: 0.6867\n", + "Epoch 2/10\n", + "38/38 [==============================] - 4s 97ms/step - loss: 0.2121 - accuracy: 0.9133\n", + "Epoch 3/10\n", + "38/38 [==============================] - 4s 98ms/step - loss: 0.2032 - accuracy: 0.9267\n", + "Epoch 4/10\n", + "38/38 [==============================] - 4s 97ms/step - loss: 0.0904 - accuracy: 0.9700\n", + "Epoch 5/10\n", + "38/38 [==============================] - 4s 95ms/step - loss: 0.1064 - accuracy: 0.9633\n", + "Epoch 6/10\n", + "38/38 [==============================] - 4s 100ms/step - loss: 0.0715 - accuracy: 0.9767\n", + "Epoch 7/10\n", + "38/38 [==============================] - 4s 98ms/step - loss: 0.1058 - accuracy: 0.9517\n", + "Epoch 8/10\n", + "38/38 [==============================] - 4s 100ms/step - loss: 0.0689 - accuracy: 0.9783\n", + "Epoch 9/10\n", + "38/38 [==============================] - 4s 98ms/step - loss: 0.0747 - accuracy: 0.9733\n", + "Epoch 10/10\n", + "38/38 [==============================] - 4s 97ms/step - loss: 0.1280 - accuracy: 0.9467\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "happy_model.fit(X_train, Y_train, epochs=10, batch_size=16)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After that completes, just use `.evaluate()` to evaluate against your test set. This function will print the value of the loss function and the performance metrics specified during the compilation of the model. In this case, the `binary_crossentropy` and the `accuracy` respectively." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5/5 [==============================] - 0s 28ms/step - loss: 0.4274 - accuracy: 0.8133\n" + ] + }, + { + "data": { + "text/plain": [ + "[0.42739078402519226, 0.8133333325386047]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "happy_model.evaluate(X_test, Y_test)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Easy, right? But what if you need to build a model with shared layers, branches, or multiple inputs and outputs? This is where Sequential, with its beautifully simple yet limited functionality, won't be able to help you. \n", + "\n", + "Next up: Enter the Functional API, your slightly more complex, highly flexible friend. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 4 - The Functional API" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Welcome to the second half of the assignment, where you'll use Keras' flexible [Functional API](https://www.tensorflow.org/guide/keras/functional) to build a ConvNet that can differentiate between 6 sign language digits. \n", + "\n", + "The Functional API can handle models with non-linear topology, shared layers, as well as layers with multiple inputs or outputs. Imagine that, where the Sequential API requires the model to move in a linear fashion through its layers, the Functional API allows much more flexibility. Where Sequential is a straight line, a Functional model is a graph, where the nodes of the layers can connect in many more ways than one. \n", + "\n", + "In the visual example below, the one possible direction of the movement Sequential model is shown in contrast to a skip connection, which is just one of the many ways a Functional model can be constructed. A skip connection, as you might have guessed, skips some layer in the network and feeds the output to a later layer in the network. Don't worry, you'll be spending more time with skip connections very soon! " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.1 - Load the SIGNS Dataset\n", + "\n", + "As a reminder, the SIGNS dataset is a collection of 6 signs representing numbers from 0 to 5." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# Loading the data (signs)\n", + "X_train_orig, Y_train_orig, X_test_orig, Y_test_orig, classes = load_signs_dataset()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "The next cell will show you an example of a labelled image in the dataset. Feel free to change the value of `index` below and re-run to see different examples. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "y = 4\n" + ] + }, + { + "data": { + "image/png": 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dJuwSG+d8D6dUjrEXpuHVBiSp5Nr5c6Ku1fEmNc7XrlWpuQWfHnmQl+/TOnOXHTSkmy2/JcJUpq6L6+w5dV3FojfZLbD8blE30hjhZMQFVK4DSJ1x8x1vYquvvjsqd5Ve3uoy5p6aJO7cYi7JuXnvIrtyxymEoK9zry6s6REi1kzVLI5EHylMgJEmaezsjwL4JwB+SETfG+7719ie5F8joi8AeAfA51P0ZTAYpoQ0q/F/ifBL8fH9HY7BYLhRmLwH3TWZN2p+2GPXUULBdISTrao3r62ff1PUdRmJRId5d3WVJ1yfibQ9p8gr2LYmi8yxFMsFZnrT0XeOH6dE/DJL6zQ3v8iPkn0Ia2Y6M1Es1XBrUy7ZrL3uzW3tJuO5V2Qb3KS2zlJWA0CdmSbv++jHR2XNgZ820i2mdsi0zKGa5FbouY174cWi11h/Wi0Vz9J4NTh2J8w33mDICGyyGwwZwdQCYZJeW+naxri9KJ2kFEXlkueDb1RkltUe85Qb9MPiFl9x7ir+OC5y9pXnXY6tpOdyXH5WfGNcjC9KDvVZRgBRnpsbe97t7fFjSlYiiH7PB66snfuBqGtu+XvHefh6SoxvsOAXzbE/d2h5VP7Awz8zKnN1Z3u4+0Bosi/ZCZgqoOnlU3YvH+H0Cq2/B+Fj7MtuMGQENtkNhozAJrvBkBHcRLnexnOVh1vF826lhVNRaRsXPTFCryt1yF6Hec0x3bOv9PI+I7PQvO4c2vRWKPt3r2N6f19zwzMdXuc9m1/0nmYlZoZL6Oys/0FCn2fni6jvWxe8aXLt7bdEHU8lzXX2liKo4OmtSRFsvP+h06PywSNHguNNi6iJTqRDjkE/c4HWMU++RC7D8amYkwQvsZGR+p+EfdkNhozAJrvBkBFMwYNu+H8fuAP2bmbx6HYkR9zWuucn7/e1CM5EX+ZB1+spEgqmGiRERyY+C/MagHLZ88OXmEhbUBeTZ6JjqSw55Q+teMKKYqkcHAcXEZ027bFtflivLQN3Vn/08qhcWdsUdV0mnjcZYUdFBbvwgKLFI8dE3d0feXhU5txybrBHMT5SRxHznRCfE6QUJFoG+xeeiDERf/yYtsG+zUEN1kxvBkPmYZPdYMgIbLIbDBnBFExv2zpFlEshticaWhSJXJLE9KNSt6XytFU841anraLZmImt1fTHNeuyjxZr11UusdzltqBSNh9gpBcLrFwuyXdyjumvuaL8CY+dvG1U5nnfEuY1Zs4bDLRL7/h2Wxd+LNpVGCFnR0X+VXguvLonjmxpMyX5Mb7/o4+IukW2/uAiLrxBgswEaGwxeZiOc4v1P17hTmrvEWIVvl7AiUm0WS9C1D86LnL99mU3GDICm+wGQ0Ywvai3KMKcaJTKyJCMGArxpnc7MsUT92rTJh5Rx7nk+rqdC9aBicU5bVJjUn2ZedOVte2NoajSOS8dP+HHGBDH9XbMu661eWVUvvrjvxXtmizNVVOZH9vMfNdm52p0pLh/y/s9n9z77n9Q1AnijIi5TXLmpSR/S3QXIYmjsPgfIuzbDX2c1C44x+LuXUKNvMJgMNhkNxiygomK8Q5hMUOsSEallxjPHIdebh1/5lZN8p51uz5QI5eXq+Wc3rk0473TFlTmUJ6Z1KksrvWqX42mCPX1QATCyHZc/J+ZnRV1CwcD9NHq+gcuLMb3297LbePNH47K1c110Y4TTzRUgEuT3ccO+81KBw6Idg/+7CdH5dmFBVEXWoHflf9cyOxDkRV39eyk5biLZmCilCI+8WdOt2QBUHqMKYZnX3aDISOwyW4wZAQ22Q2GjODmMb3thXgikf4pbXf+uPrWmqjptL2O3WlKs1yb6aVtRmzR6UtzUo95k/W6yguPbedUaqggD4LeZu3mlA5cZmmS+P0ZJCLbWF1bplGu/JhFs126OCq3morMg5kf2z05ylaXc+f7/R988CHR7pY772JjElVBz7IEokSjzKstYl2LEz3S+Ib6fFHvztBBEdNhJCV58lHZWWvf8ctORDNE9DdE9H0ieoWIfmO4f5mIXiKic8P/lrXRYLiJkUaMbwP4lHPufgAPAHiCiD4G4BkAZ5xzpwCcGW4bDIabFGlyvTkA16IaisM/B+BJAI8N9z8P4JsAvrzjGdOYMSIyePToqPmOeSaxwI/K1cuiFedEq6kAF07CwNt1VLBLm9V1FRc6v/y8Mu0J3jlGjpHPhWXOg0eOi6pCkRNWxLzkfP+1C2+Iuo13PQ9ftcYCftrSvNZi19ZRHnRdNv4DR46Oyh965FHRLsfMmQlVY8DFeO7ZiCC0OZNy7HsWl4MjlTEVIiUHnQiSiXkDctOy4h6MfJtdCmL6tPnZ88MMrqsAXnLOfQvAMefcRQAY/j8a68NgMEwXqSa7c67vnHsAwEkADxPRh9KegIieJqKzRHR2fX1jr+M0GAzXiV2Z3pxzm9gW158AcJmITgDA8P9q4JjnnHOnnXOnl5dtDc9gmBZ21NmJ6AiArnNuk4hmAfwcgP8A4EUATwF4dvj/hTQnTOPWl9o9MUYbHyEZ6La9Sa2yflW06jCTWktFaLUZ8QI3O/X6mqDC96HNaVxPL5ck53ue+cESJ61UkXNU9H0cufU98gTcdVfwv8s+2hv+3bz+liSl2FjzLsR1tk6hOd9bzBW4rcgrBuxaPviwT7e8uLwi2/Fxqcg87jI8EPp7mGpC6OgAcjxajlclAtt8LzFe+qSLdsqFABdpx03GKU3QMQ6NENLY2U8AeJ6I8ti+XV9zzn2DiP4KwNeI6AsA3gHw+XTDNBgM00Ca1fgfAHhwzP41AI/fiEEZDIb9x8Q96K5JKbuKXAoh5s0UQbvu+dHqW5LvnHu8SeEccExE7A9YeiOdlpmJo3k1qCITb0vKg67AzS6sT52iqjzn0zotsrTGQNjc1lckHZtvvToqd5RJrcdc3lrM/NiqS0+7bsTEeIRx4d1574d9hfYKG4TJQvrBuogYnODHZ32w69LisuPRZhFZOi4+h/uP9UF7cMNL1jjxfxzMN95gyAhsshsMGcFNEwiz72J9RIyqrfuV6HatJuo4z1xfiZVttjLdZkEyAxUIw0XOZkOSV8zOehF86eCiqJsp+nevoDBQ3lEH5udH5ULCu46tWjPxv375vGhWW2eeg8olbWbGj4OrHfrLwIN68nn5KH3gQZ+6aXbOj9f1w15yMQ+6mIgsKJdVHz12nb3Vn/pmyvOtcOKOUbm0LP3DZJbVsO4YswaJRzPBqzJePE+K5GmpsMfDvuwGQ0Zgk91gyAhsshsMGcHEdfagbiGC9iN1HLsJ7mdmnI13vf466EizU5+lfGo3pLnKMR11lnm/lYqS9JGbv7aU3n/LLUdG5ZWVJVFXzLPIvL43ZWnKdH5cvitTIJNjXn51b1a8+qbkfK9tbrHxKpMXW4MolP2YCm0ZpZdr+2/Fbe+9W9Tdee8Hx/efIL4cH9mmmwovOfXjDnr+N2y9/bqoa711blQu5fz4tcdfj8VtHH3kMVGXL/l1lqQWzcePYLsYuPdewJK3Y68j/T5yYvuyGwwZgU12gyEjuGlMbzG7RcxsEYQSZ7ot7/3VYIQVBxel+Suf9yKb5mSfY1zxszNejC8UpXjb7Xhz29Z6RdQdO+7NOnMqdROYWarT8ipEW/HYcXEUlSuiDle92Fo970ko1i78RDSrMVKKvhKteWCP8JJTZrODh32W1fse/YdyjGV/71wkiGUQlX3Hy/GDplRdquc8Z97mOSnGU495Mxb9/a42ZB/9qn8+DrWl+pbjhCB6iHshT9QIid6Jrvl9VCQdKSaGfdkNhozAJrvBkBHYZDcYMoLJ6+ypiCnC0T7SHJNgIBhzxDaaLKdbi7nIDtT7rsfMOCWVKplvl5mePsei0ACA5rxueGhxXtRx8oqcU3F15HX9/KzXlefm5M+UK/qrq61JnZ1YNF79incLblSkW3CtztMty3FwAs0uI/Aoz8true/jPzsqr9xyUtQNApzvMW74BJgprr/lr6X241dFs403/dpES3H9c922se5NkZsqgm/llDcdclObHqMebVoOywhlvYJ/HpP9MdfcxGd6nwgnDQbD333YZDcYMoKpmd7iQkdMtGPFiKddTglBnaYX2zinueZCzzOCiqUDMoXwTMmL53lGPJFXvGf5nL+t3b6MeusJMVORXvT9GPs93k72X5o7OCpXt6R4XtnyfWxuVth+mZp6fdMf1+5Jk1qXmcq46P7hT0hiovd84INsS97vAeeTi3qWsT0qerC9+vao3DzvTYq1yzJlV53dU/171hrexLjO7pWbk7/th+8/PSpTQU6LeOap8ZXaFCY947T6GSHHkw0jzUyMNxgMQ9hkNxgygsmK8c4FV1/H0xRc2w6IStH1T3lMlRNWMA83KH63xYW5UXlutizqcnzsTBXQ1MOCO03RTHPCB8pJ8TnHPePyZbZfetrNzHqvP6eypzYaXlzn5+p11Ip7m6dukuPgHHf3PfqJUfl9939EtCPG26bvgVilZqvqua5cLe83varRZOQSALB5/u1Rud3gXHiyj3rXi+4byuqwxtSXQcn/to/83GdFu8Mnbx8/+O0L4BuyipXlLYjQUeul9EjmVtksHCwWnwvbsC+7wZAR2GQ3GDICm+wGQ0YwYdMbIR1zfCz9TjrwFEwAUGXEg3lGEjGvSB9LRZZCWPXRZWmJiZmn8or/netPfUWO0WkzL7miIj1khJO5nNfZCwWps4v+FQlDv+N12wJ83Yljkl++zEggqzUZAXb4jjtH5Xse9imW82ocMSJG1/K6c+8qI3qsy+SebRbBVtuS41hb9R5vzSbT2VvSnFljJCMbVdkH19Mf/uzPj8p3flDmJhUEEmHHzChiXnK7yhAdakYx09vOSP1lH6Zt/i4RfWO4vUxELxHRueF/y9poMNzE2I0Y/yUA3Cn5GQBnnHOnAJwZbhsMhpsUqcR4IjoJ4OcB/HsA/3K4+0kAjw3Lz2M7lfOXd+rLJQrXNiMcdKG+Etk8/YGdpjTBtOveBMOlIU08Icws6lU4cF4sznGvuZzyluIZXpUq0GakFJASPopMhSjwDK8kTWNt5iU20Kmn2D3h3GylvMwYe8txn021NH+7qFu524u45Xmv5iTMO8xs2duSGbvbF9/y5S3PdzdQwT9NJpJvKRG8wsTztTXfR60mg1jq7B6Xl6S68rHPeBPbXff660qYv6KIiM/seZGWt1gKqYHaw4JfUov0qs8UAWZpr/i3APw6IEZ5zDl3cXiiiwCOjjvQYDDcHNhxshPRLwBYdc59Zy8nIKKniegsEZ1d39jY+QCDwXBDkObL/iiAXySitwF8FcCniOj3AFwmohMAMPy/Ou5g59xzzrnTzrnTy4dsDc9gmBbS5Gf/CoCvAAARPQbgXznnfoWI/iOApwA8O/z/QqozjuitYzlttevleL0ooUMy/alRkVIEJ4qYKXuz1qCveON7XofsKBMPJ5LMMz29XFK88Yz8odGQ+mWT5YvTuc2KZf9zlJnLbV/pfwO2TVpVy3G935vX9L0qsciuQ0sHRd3SrNfvqcn45XVU2vpFX167LOpaNa9vVzb9eklvIPuoszWMzYqMzKuxPHkbLHX0BiPLBIDjd713VH70ic+JuhPvec+ozN2RkwSNFCjvwLci6ngutvRElMJV3MknPND7nogvr8ep5lkAnyaicwA+Pdw2GAw3KXblVOOc+ya2V93hnFsD8HisvcFguHkwefKKa+JNRDZK6xyUiIZjfdY3pFiZZxFmc/Ne7G5UpVg5f8CLtLNzUlysbPo+1q+uj8qFnGyXZ2J2pyVNbzwi7tBhmf7p8BFvDuMmqo0NKd42GH9aoSBNhzOM277EvMdyOflTF5gYn1PqRL7lI9HyV70Js7q5KdrVKn4cnbYSz+tMBN9gkW0tqTa1mGqwpXjhtpjo3mDmzFMPPyzaffxTnxmVDyTWhULibez5U6YxFxaA+TNIwqMwcjadcjql+B8615gzjIX5xhsMGYFNdoMhI7hJqaTTQQsyfbZa3tqUFMszJX+pHUECIMXgNiN1OHrsiKjj21eXro7Kr73yhmjHCSUOr6yIultvvWVUPn7bLaKuXPaBJvWKF33d4F3R7upVb2noq9RQg6JfSUKrLPUAABQ+SURBVBdinxYd2XZH0S9Xrvhrm2EqT21DprK6wlSZZkuOo8G2N5m431QWjiYbf7Ut61D2ashHH/e01R8+/YhsNiOtIRKhlEna4sMtHKpOeDCGxexYnAoJST0dP10spVPSY87EeIPBMIRNdoMhI7DJbjBkBDdPymYBHdIT2FDN2oxssV3fEnUz7LVWZuYqrssDQKvuI682VtdF3ZEj3qxz/Pgx359KF9RpebPZysoxUVfMMy85xV3OvfJAvp1zcoxFpssWNXchI8sY5Lw+3IQyjTETYD4ndfFmw+vA+ZI35W0qjvorV70prt5ROjvbrjPzY7Uh1wfA7t2t771HVD3wcZ8G+tY77hiVBTFnAmk91xJhY76odOUI36TYESJGHXYaGcp4k1qcQX73qaLty24wZAQ22Q2GjGDiYnxINIlxboekKG19aDExvteVXm0DJroX2DuupCJJuszMMuhLT6pBn/HOlb2J6/Dh46Jdv+/7dwP5PnWMNIEUoUSJ8dTPsXHNbcmgni0WXDNQfeThr7Oc94Ew5bL8qdvOi9YbdekZ16t5sb5Q9GJ2pSG9364wzritpjSbcTHeMVH99g89JNp9+KPeG+74ydtEXbEkOe9G/UXl2zD7W5QjjonuuwmS2RNBXaIqYLPblaRuvPEGg2EIm+wGQ0Zgk91gyAhuStNb1PGPmzCUftZrez3dKVKKVsfrqLNMh1zWkWdHPWFhSZnUiL0be0wn7Q802QF7hyqdus/WARoNlc6Zmc26A1/OzyjeeMZ731IpisvMXRbMbKbNSWVGmDk3I02AbZZKusvudzcnySKrjKRjS5nejt1+16j8kUe9q+ttd75XtCvw8SbSPgdXeAL7x+jb4hlh6yXJA1n3iURqEQSU7KipTfUgUr2l44aPLisEYF92gyEjsMluMGQEUxDjA+mfhPii+OBTSnP9Lk/PJM1mS4yUYn6eeaCVZFpmN/Cmq75KZdztMF44JrUmPK6YiJxTqaF4nw3lTVZjPO+ttjdrVVqS1KHGROZeS4rWPaYmkPN9lBV5Bae9b6jxt9n977OUVxtV6UHnGM/9hx/5uKh76NHHRuUZlmpKy589wXsfFp8lz7u636Jd+LnidVrcp0i0WUxCJiauhw3GO/XCORbTpWVOmh8t6s1gMAxhk91gyAimKMZrhF2HOCdYLACgxzzcmmp1uN334mKZkUu4gU7FwzKkSglZ9M+JEHKajIBxurWb0pOvzcgb6g2Z7qjV8WJ9nQXkVJpSjOdkEEW12s+kbjRrjPq6oKwC7J5WFb0zsTou7l+8KgODFo+dHJXveUjywuWL3oLQ5QQbibxFvCrsnUa5mJjN28m6XG7885LcG+aPE3WRc6dFTMAXsyCWIi3Qa6yFfdkNhozAJrvBkBHYZDcYMoIp6Oy7J5xMqxcVmJ44tyg94+YXDozKeUYM0e/K8fDUSlqbH7B3I3eQ6itPr07Xm9Caigu9wogkN7ckwUaDES6ub/l2VRVRxk/HU1kBwAzzruPmpE5XLkCs1/yaQKsjvfBOnvRRfMRNh4w0AwDufuCjo7JeE2iKtQqu88rvCzdT6jqub+fyebZf9cH06Jz+fvE6rgQnLHSRyDahz8d43UP9pQcnkoxF5iVd6HaeV2nzs78NoAqgD6DnnDtNRMsA/geAOwC8DeAfO+csTavBcJNiN2L8J51zDzjnTg+3nwFwxjl3CsCZ4bbBYLhJcT1i/JMAHhuWn8d2Drgv77m3CKe3ajgqJXkK/LtroHjb+j0WPMK8trTlTTpqyXchF+P7A99HqyXNa1tVT6Khc9JvbHrxfF1nLWWpkS6veUKJRKJWJsbm9RiZvbDH3Pykp5qUAhfnZcBPlYng+bKvu+veB0S7g8uHR2WdrVZ6rrHsqTktqvu6fF7+ZnmmQuSY7pLPSw46yUkXNqVKcVzfVWbeVeY67iU30GpI0MsvPIoYYtJ/jOBlp91A+i+7A/DnRPQdInp6uO+Yc+7i9iDcRQBHU/ZlMBimgLRf9kedc+8S0VEALxHRa2lPMHw5PA0At9xyYg9DNBgM+4FUX3bn3LvD/6sA/hjAwwAuE9EJABj+Xw0c+5xz7rRz7vRKIsOmwWCYFHb8shPRPICcc646LH8GwL8D8CKApwA8O/z/QrpTBqLeRDraUI2Gtp/4d5eyNGHAt5m7rNbwuLknkUuOddJkevpmRZrQrmx4ffvilTVRd3XT6+lrioedb9dqzCW2KH8mrm9qb9A8U/oKTLc9sCDzoR1e8VGACwvSpNZmRB8lZm5bOX6raNcRJjvt4jze3JZT+naeRePlCyp1NCcJ5T+1diPN8yr5/cqHeNhVHwOmEOcU8USOk4SqhSJJVMn2J9x0aWwxgZj7cLrDgkgjxh8D8MfDExcA/Hfn3J8S0bcBfI2IvgDgHQCfTz0yg8Ewcew42Z1zbwK4f8z+NQCP34hBGQyG/cdEPegcxqWa5bXXilpOCwT3q3bci0t7tbW5FxrjjNMRa1yM1yPtsoi1CvN+u7IuRfULq3774po0vVWqXjyvsbRI2/14s1yRmZ20eCuyRKnxl4pepl2Y82YzLrYDwNKS9yicm5MiPuPowOJRH9mWL8jHhYvxTsumwnONeb+p34VxhWCg7jhvKsRz9cPk+fPhVGoo3gcX99U4uDlzkDAPurHttrfZtUXMwrFoNn6vHPFrSU/wkgbmG28wZAQ22Q2GjMAmu8GQEUw46s1hZOyKsHAk2WPG2100cwfnIB84rf/5PotMzyJFR+OYWy1ySu9vedNYpeLNa1fWJYPL1U1f11WutAcXvX4s+WGkLs5VQ72ukGeRbaWC1FGXDjBT2SGvpy8eUOmh2ZpAoyWJL/t5r+sfP7ji2ynWHTV6sUVcl+UusWr9ocC2B05GzrkA97p+Pgrst84nlnu4SY21U2mfBXd7RN9O2s24my2LilRjj9PBc10/vGYkB6krLdebwWAYwia7wZARTJ68YiiK7Ir3OqXpjctKOi1Si6ViLs96UdeptMxdlkKqqwTtatOL8dW2N6HVlRi8tOhF5rvec4scYtGTTZz94euijpMrcBNauSRFznLJi7sLszI11JFlb1I7vOIJPEiJrU3Gsd9U7oYLB734zy1UjbokyBTplLRJikWw8Wi2gja9sd+wGLa4BsuJOq0BskdcetfpZydsNqPIuVVL1rsW/mPhbKxdjJ8igjgZ5Tbsy24wZAQ22Q2GjGDiYrwXg7QsxuUvnUiHi1hcpFcyGwtUqdQUJ/sWy5C65MXUshI/uywFU6MtxfPNOhPjGZf7yoqM5ls+5MXnYkmuMF+45D3qekqFmGHi+uKCXxGfm5U8c/NlL7ovLcogliPL/tqWDi6OyvWW5LGrsWAXl5NjLM36dE2cSy6nVAEKiOoAkBeXxgJhcvKaB2x7oKwfPIXXgJW1Z5kQ44FgnaCx0PzvFPGq5IE8mtiCE1aIWJfdcNDxtE7h4yThhuavv1YXFufty24wZAQ22Q2GjMAmu8GQEUyRN17r5XwjFvXGdD5tZ2G6FidgAIAraz4Sbe2K93ibVTo1f/311ZpAj+VEW1jw5rW5+UXRrs7WC1xLmsbOX7ri69T4Dy6yKLVl3/9sSfaxyKLUVpbkuQ8c8Po2J4oYKOc3HtlWmpMRcZwgkudpU0FvwgstYfoJ0LAncrEJ8oeIrhxpl+fc8wmdevxxyWjH3Njy9nYk1xvvP3TRCeh8d+z5jqr67Dp3QfGSPNpgMPy9hk12gyEjmKwY77jZRJtP0pJXsMADp4Mq/OUUZ6S5qsNMN1ssJdOgr/vwomlJea7NMx63dpNzvL8r2hUZ1/qVzSuirslSQ8FJD72lBT/mFRbQwk1tAHBg0YvqSwekGJ9j4681GNlGQ5reeuT7nFFpnTpMBeKiuza9cdKICOOa+KIkxOBc2KzFt3ngTj4hZvvtguK4KwjzIAvOSXDPx/pPl3qKX3TMQVRz1ktii4A7ne7OyCsMBkMINtkNhozAJrvBkBFMnLzCpSCvSGo83NwWJq/grqkzc/OijuuyBeZ+qnOgOaYnNXtSn6+seZLJgkhRLN+ZtYo38yXTOXs93fWkzr7IXF8Xyr5/TkgBAAeZeU274zbaXt/eqnt335YiYnQ5r7PXVZ42rtsWmdmvp4g+Smz8RZU6ulgMuLdGTFdaV3Zcr46QvsuUzdp8F2gXdYkN6+WJtYlIXQhO3wOhf4dJJcXzHtDnY5q8fdkNhozAJrvBkBHcPOQVEdOb9DQLR8fxyCj9Fmsy8ZmL0lqM59taBOdmon7bm7K6fZ0OmaX4VdfSYtFnBWVqWpj3pr3ZGS+ez89JEbnAzFD9gTx3teFd5aqMl741kOa7TsePg0h6G3IxvsDMcG1FCMJF/FJZpn0ulfx2mYn4xa5UXcqs/25ZjqPM+uyV/HWWlEdhn5lP+wWp1nA1p5DgNkyHPHvOEimbufkxYioT4n5CPOftxFEIbSXNd/vkQUdES0T0dSJ6jYheJaKfIaJlInqJiM4N/1vWRoPhJkZaMf4/AfhT59wHsJ0K6lUAzwA445w7BeDMcNtgMNykSJPF9QCATwD4pwDgnOsA6BDRkwAeGzZ7HsA3AXx5p/7cSIyPeMnpAJcgsYXsY+vK5VG5sSXTLtWZB1mVrT4PBlplCPUugw9IpIlS6kTfb/eVmtBl4v/CnBRHZ2a82FpktNj9vlYFvDjd6sp7tVnxYny969/lTU2ZzSIudGZSfk+kdhXmjxskfk5OyMDuh+agY9emyTx4EE6JifilrrxvxQ5TJ4qyLt/x95Fnwy11tfWgNLYdID0zk0Ey41fxowEzkSCcG4k0Z7kLwBUA/42IvktE/3WYuvmYc+4iAAz/H72B4zQYDNeJNJO9AOAhAP/FOfcggDp2IbIT0dNEdJaIzq6zvOUGg2GySDPZLwC44Jz71nD769ie/JeJ6AQADP+vjjvYOfecc+60c+4052YzGAyTRZr87JeI6DwR3e2cex3bOdn/dvj3FIBnh/9f2LEvMJ094ULH9cSEXW5sua8IIS/9+LVRubohdfY2M3nV677cU+YYbl4rqNRK3MPLMRVYm7+4ztvrSHMVX38oFPXt57z3Xl/tdlT/rFxtSHNVdeD7bLB8yH11T2OEDCHdM2Za0nBCn+dlRTjJ7n9ifYOZBAWxozJJxQIm87x/tm6h10GE+a4vfxeuz+d1tJyIxksXVZdL3EaWokq6/IlWiVTPvIcUP01aO/u/APD7RFQC8CaAf4ZtqeBrRPQFAO8A+HzKvgwGwxSQarI7574H4PSYqsf3dzgGg+FGYQq88e5aQe2PccuJhqPi1qokjVi/9FO/oUTruZK/1PaMF8tqTUnqwLnruCgN6KAHHpCjwMXWvuyjwMTRuup/q+bNZi2ekVapGm1mbmuTNCH1izzdkR9vUasknNQhkbqJedCx4/LKO42bpHgGXQAosvRVRd5OEdlxUgouEgNKnRhPzw5AKXmJ54r9FgNelveUi/hJ8xp7liImtQFPIaX651s6VZYLqLAJT7uId10KBzrzjTcYsgKb7AZDRmCT3WDICCZMOOmYTqIjkMKkFELvYoSNqz95Q7TrsUiuGUXqsMyIIfJMr52fk9FaVzeqo3KlJk17wtWTEyFod0fRTOrKfVa51VQRdwPPN8+54kmZcajox5wrzUKCEWYyPVqTXHCdvaj16ICOrc1Ooq4QMVcVfFmbG/N5FpVWCLupcrIQfS4+rrzS+4sBkskYaWWCvCLiBosQb3yiWVpO+XTQUW9purQvu8GQEdhkNxgyAtoL//SeT0Z0BcBPABwGcHViJw7DxiFh45C4Gcax2zHc7pw7Mq5iopN9dFKis865cU46Ng4bh43jBo3BxHiDISOwyW4wZATTmuzPTem8GjYOCRuHxM0wjn0bw1R0doPBMHmYGG8wZAQTnexE9AQRvU5EbxDRxNhoieh3iGiViF5m+yZOhU1EtxHRXwzpuF8hoi9NYyxENENEf0NE3x+O4zemMQ42nvyQ3/Ab0xoHEb1NRD8kou8R0dkpjuOG0bZPbLLTtt/ofwbwWQD3AvhlIrp3Qqf/XQBPqH3ToMLuAfg159w9AD4G4IvDezDpsbQBfMo5dz+ABwA8QUQfm8I4ruFL2KYnv4ZpjeOTzrkHmKlrGuO4cbTtbuivfqP/APwMgD9j218B8JUJnv8OAC+z7dcBnBiWTwB4fVJjYWN4AcCnpzkWAHMA/h+AR6YxDgAnhw/wpwB8Y1q/DYC3ARxW+yY6DgAHALyF4Vrafo9jkmL8rQDOs+0Lw33TwlSpsInoDgAPAvjWNMYyFJ2/h22i0JfcNqHoNO7JbwH4dcjIqGmMwwH4cyL6DhE9PaVx3FDa9klO9nFxOZk0BRDRAoA/BPCrzrnKNMbgnOs75x7A9pf1YSL60KTHQES/AGDVOfedSZ97DB51zj2EbTXzi0T0iSmM4bpo23fCJCf7BQC3se2TAN4NtJ0EUlFh7zeIqIjtif77zrk/muZYAMA5t4ntbD5PTGEcjwL4RSJ6G8BXAXyKiH5vCuOAc+7d4f9VAH8M4OEpjOO6aNt3wiQn+7cBnCKiO4cstb8E4MUJnl/jRWxTYAMpqbCvF7Qd1PzbAF51zv3mtMZCREeIaGlYngXwcwBem/Q4nHNfcc6ddM7dge3n4f84535l0uMgonkiWrxWBvAZAC9PehzOuUsAzhPR3cNd12jb92ccN3rhQy00fA7AjwD8GMC/meB5/wDARQBdbL89vwBgBdsLQ+eG/5cnMI5/gG3V5QcAvjf8+9ykxwLgPgDfHY7jZQD/drh/4veEjekx+AW6Sd+PuwB8f/j3yrVnc0rPyAMAzg5/m/8J4NB+jcM86AyGjMA86AyGjMAmu8GQEdhkNxgyApvsBkNGYJPdYMgIbLIbDBmBTXaDISOwyW4wZAT/H7toAwJBazhDAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Example of an image from the dataset\n", + "index = 9\n", + "plt.imshow(X_train_orig[index])\n", + "print (\"y = \" + str(np.squeeze(Y_train_orig[:, index])))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.2 - Split the Data into Train/Test Sets\n", + "\n", + "In Course 2, you built a fully-connected network for this dataset. But since this is an image dataset, it is more natural to apply a ConvNet to it.\n", + "\n", + "To get started, let's examine the shapes of your data. " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of training examples = 1080\n", + "number of test examples = 120\n", + "X_train shape: (1080, 64, 64, 3)\n", + "Y_train shape: (1080, 6)\n", + "X_test shape: (120, 64, 64, 3)\n", + "Y_test shape: (120, 6)\n" + ] + } + ], + "source": [ + "X_train = X_train_orig/255.\n", + "X_test = X_test_orig/255.\n", + "Y_train = convert_to_one_hot(Y_train_orig, 6).T\n", + "Y_test = convert_to_one_hot(Y_test_orig, 6).T\n", + "print (\"number of training examples = \" + str(X_train.shape[0]))\n", + "print (\"number of test examples = \" + str(X_test.shape[0]))\n", + "print (\"X_train shape: \" + str(X_train.shape))\n", + "print (\"Y_train shape: \" + str(Y_train.shape))\n", + "print (\"X_test shape: \" + str(X_test.shape))\n", + "print (\"Y_test shape: \" + str(Y_test.shape))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.3 - Forward Propagation\n", + "\n", + "In TensorFlow, there are built-in functions that implement the convolution steps for you. By now, you should be familiar with how TensorFlow builds computational graphs. In the [Functional API](https://www.tensorflow.org/guide/keras/functional), you create a graph of layers. This is what allows such great flexibility.\n", + "\n", + "However, the following model could also be defined using the Sequential API since the information flow is on a single line. But don't deviate. What we want you to learn is to use the functional API.\n", + "\n", + "Begin building your graph of layers by creating an input node that functions as a callable object:\n", + "\n", + "- **input_img = tf.keras.Input(shape=input_shape):** \n", + "\n", + "Then, create a new node in the graph of layers by calling a layer on the `input_img` object: \n", + "\n", + "- **tf.keras.layers.Conv2D(filters= ... , kernel_size= ... , padding='same')(input_img):** Read the full documentation on [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D).\n", + "\n", + "- **tf.keras.layers.MaxPool2D(pool_size=(f, f), strides=(s, s), padding='same'):** `MaxPool2D()` downsamples your input using a window of size (f, f) and strides of size (s, s) to carry out max pooling over each window. For max pooling, you usually operate on a single example at a time and a single channel at a time. Read the full documentation on [MaxPool2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool2D).\n", + "\n", + "- **tf.keras.layers.ReLU():** computes the elementwise ReLU of Z (which can be any shape). You can read the full documentation on [ReLU](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ReLU).\n", + "\n", + "- **tf.keras.layers.Flatten()**: given a tensor \"P\", this function takes each training (or test) example in the batch and flattens it into a 1D vector. \n", + "\n", + " * If a tensor P has the shape (batch_size,h,w,c), it returns a flattened tensor with shape (batch_size, k), where $k=h \\times w \\times c$. \"k\" equals the product of all the dimension sizes other than the first dimension.\n", + " \n", + " * For example, given a tensor with dimensions [100, 2, 3, 4], it flattens the tensor to be of shape [100, 24], where 24 = 2 * 3 * 4. You can read the full documentation on [Flatten](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Flatten).\n", + "\n", + "- **tf.keras.layers.Dense(units= ... , activation='softmax')(F):** given the flattened input F, it returns the output computed using a fully connected layer. You can read the full documentation on [Dense](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense).\n", + "\n", + "In the last function above (`tf.keras.layers.Dense()`), the fully connected layer automatically initializes weights in the graph and keeps on training them as you train the model. Hence, you did not need to initialize those weights when initializing the parameters.\n", + "\n", + "Lastly, before creating the model, you'll need to define the output using the last of the function's compositions (in this example, a Dense layer): \n", + "\n", + "- **outputs = tf.keras.layers.Dense(units=6, activation='softmax')(F)**\n", + "\n", + "\n", + "#### Window, kernel, filter, pool\n", + "\n", + "The words \"kernel\" and \"filter\" are used to refer to the same thing. The word \"filter\" accounts for the amount of \"kernels\" that will be used in a single convolution layer. \"Pool\" is the name of the operation that takes the max or average value of the kernels. \n", + "\n", + "This is why the parameter `pool_size` refers to `kernel_size`, and you use `(f,f)` to refer to the filter size. \n", + "\n", + "Pool size and kernel size refer to the same thing in different objects - They refer to the shape of the window where the operation takes place. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 2 - convolutional_model\n", + "\n", + "Implement the `convolutional_model` function below to build the following model: `CONV2D -> RELU -> MAXPOOL -> CONV2D -> RELU -> MAXPOOL -> FLATTEN -> DENSE`. Use the functions above! \n", + "\n", + "Also, plug in the following parameters for all the steps:\n", + "\n", + " - [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D): Use 8 4 by 4 filters, stride 1, padding is \"SAME\"\n", + " - [ReLU](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ReLU)\n", + " - [MaxPool2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool2D): Use an 8 by 8 filter size and an 8 by 8 stride, padding is \"SAME\"\n", + " - **Conv2D**: Use 16 2 by 2 filters, stride 1, padding is \"SAME\"\n", + " - **ReLU**\n", + " - **MaxPool2D**: Use a 4 by 4 filter size and a 4 by 4 stride, padding is \"SAME\"\n", + " - [Flatten](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Flatten) the previous output.\n", + " - Fully-connected ([Dense](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense)) layer: Apply a fully connected layer with 6 neurons and a softmax activation. " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "f58643806aa8380c96225fc8b4c5e7aa", + "grade": false, + "grade_id": "cell-dac51744a9e03f51", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: convolutional_model\n", + "\n", + "def convolutional_model(input_shape):\n", + " \"\"\"\n", + " Implements the forward propagation for the model:\n", + " CONV2D -> RELU -> MAXPOOL -> CONV2D -> RELU -> MAXPOOL -> FLATTEN -> DENSE\n", + " \n", + " Note that for simplicity and grading purposes, you'll hard-code some values\n", + " such as the stride and kernel (filter) sizes. \n", + " Normally, functions should take these values as function parameters.\n", + " \n", + " Arguments:\n", + " input_img -- input dataset, of shape (input_shape)\n", + "\n", + " Returns:\n", + " model -- TF Keras model (object containing the information for the entire training process) \n", + " \"\"\"\n", + "\n", + " input_img = tf.keras.Input(shape=input_shape)\n", + " ## CONV2D: 8 filters 4x4, stride of 1, padding 'SAME'\n", + " # Z1 = None\n", + " ## RELU\n", + " # A1 = None\n", + " ## MAXPOOL: window 8x8, stride 8, padding 'SAME'\n", + " # P1 = None\n", + " ## CONV2D: 16 filters 2x2, stride 1, padding 'SAME'\n", + " # Z2 = None\n", + " ## RELU\n", + " # A2 = None\n", + " ## MAXPOOL: window 4x4, stride 4, padding 'SAME'\n", + " # P2 = None\n", + " ## FLATTEN\n", + " # F = None\n", + " ## Dense layer\n", + " ## 6 neurons in output layer. Hint: one of the arguments should be \"activation='softmax'\" \n", + " # outputs = None\n", + " # YOUR CODE STARTS HERE\n", + " Z1 = tf.keras.layers.Conv2D(filters = 8 , kernel_size= (4,4), strides = (1,1), padding='same')(input_img)\n", + " A1 = tf.keras.layers.ReLU()(Z1)\n", + " P1 = tf.keras.layers.MaxPool2D(pool_size=(8,8), strides=(8, 8), padding='same')(A1)\n", + " Z2 = tf.keras.layers.Conv2D(filters = 16 , kernel_size= (2,2), strides = (1,1), padding='same')(P1)\n", + " A2 = tf.keras.layers.ReLU()(Z2)\n", + " P2 = tf.keras.layers.MaxPool2D(pool_size=(4,4), strides=(4, 4), padding='same')(A2)\n", + " F = tf.keras.layers.Flatten()(P2)\n", + " outputs = tf.keras.layers.Dense(units=6, activation='softmax')(F)\n", + "\n", + " model = tf.keras.Model(inputs=input_img, outputs=outputs)\n", + " return model\n", + " # YOUR CODE ENDS HERE\n", + " model = tf.keras.Model(inputs=input_img, outputs=outputs)\n", + " \n", + " # YOUR CODE ENDS HERE\n", + " model = tf.keras.Model(inputs=input_img, outputs=outputs)\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "483d626949930a0b0ef20997e7c6ba72", + "grade": true, + "grade_id": "cell-45d22e92042174c9", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"functional_1\"\n", + "_________________________________________________________________\n", + "Layer (type) Output Shape Param # \n", + "=================================================================\n", + "input_1 (InputLayer) [(None, 64, 64, 3)] 0 \n", + "_________________________________________________________________\n", + "conv2d (Conv2D) (None, 64, 64, 8) 392 \n", + "_________________________________________________________________\n", + "re_lu_1 (ReLU) (None, 64, 64, 8) 0 \n", + "_________________________________________________________________\n", + "max_pooling2d (MaxPooling2D) (None, 8, 8, 8) 0 \n", + "_________________________________________________________________\n", + "conv2d_1 (Conv2D) (None, 8, 8, 16) 528 \n", + "_________________________________________________________________\n", + "re_lu_2 (ReLU) (None, 8, 8, 16) 0 \n", + "_________________________________________________________________\n", + "max_pooling2d_1 (MaxPooling2 (None, 2, 2, 16) 0 \n", + "_________________________________________________________________\n", + "flatten_1 (Flatten) (None, 64) 0 \n", + "_________________________________________________________________\n", + "dense (Dense) (None, 6) 390 \n", + "=================================================================\n", + "Total params: 1,310\n", + "Trainable params: 1,310\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n", + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "conv_model = convolutional_model((64, 64, 3))\n", + "conv_model.compile(optimizer='adam',\n", + " loss='categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "conv_model.summary()\n", + " \n", + "output = [['InputLayer', [(None, 64, 64, 3)], 0],\n", + " ['Conv2D', (None, 64, 64, 8), 392, 'same', 'linear', 'GlorotUniform'],\n", + " ['ReLU', (None, 64, 64, 8), 0],\n", + " ['MaxPooling2D', (None, 8, 8, 8), 0, (8, 8), (8, 8), 'same'],\n", + " ['Conv2D', (None, 8, 8, 16), 528, 'same', 'linear', 'GlorotUniform'],\n", + " ['ReLU', (None, 8, 8, 16), 0],\n", + " ['MaxPooling2D', (None, 2, 2, 16), 0, (4, 4), (4, 4), 'same'],\n", + " ['Flatten', (None, 64), 0],\n", + " ['Dense', (None, 6), 390, 'softmax']]\n", + " \n", + "comparator(summary(conv_model), output)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Both the Sequential and Functional APIs return a TF Keras model object. The only difference is how inputs are handled inside the object model! " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.4 - Train the Model" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/100\n", + "17/17 [==============================] - 2s 113ms/step - loss: 1.8412 - accuracy: 0.1574 - val_loss: 1.7942 - val_accuracy: 0.1750\n", + "Epoch 2/100\n", + "17/17 [==============================] - 2s 105ms/step - loss: 1.7958 - accuracy: 0.1694 - val_loss: 1.7873 - val_accuracy: 0.2167\n", + "Epoch 3/100\n", + "17/17 [==============================] - 2s 111ms/step - loss: 1.7894 - accuracy: 0.1815 - val_loss: 1.7838 - val_accuracy: 0.2083\n", + "Epoch 4/100\n", + "17/17 [==============================] - 2s 106ms/step - loss: 1.7854 - accuracy: 0.1981 - val_loss: 1.7798 - val_accuracy: 0.2583\n", + "Epoch 5/100\n", + "17/17 [==============================] - 2s 101ms/step - loss: 1.7799 - accuracy: 0.2176 - val_loss: 1.7750 - val_accuracy: 0.3167\n", + "Epoch 6/100\n", + "17/17 [==============================] - 2s 105ms/step - loss: 1.7722 - accuracy: 0.2815 - val_loss: 1.7679 - val_accuracy: 0.3500\n", + "Epoch 7/100\n", + "17/17 [==============================] - 2s 107ms/step - loss: 1.7629 - accuracy: 0.3037 - val_loss: 1.7589 - val_accuracy: 0.3417\n", + "Epoch 8/100\n", + "17/17 [==============================] - 2s 105ms/step - loss: 1.7517 - accuracy: 0.3296 - val_loss: 1.7477 - val_accuracy: 0.3917\n", + "Epoch 9/100\n", + "17/17 [==============================] - 2s 106ms/step - loss: 1.7383 - accuracy: 0.3546 - val_loss: 1.7341 - val_accuracy: 0.3500\n", + "Epoch 10/100\n", + "17/17 [==============================] - 2s 101ms/step - loss: 1.7222 - accuracy: 0.3926 - val_loss: 1.7177 - val_accuracy: 0.3833\n", + "Epoch 11/100\n", + " 5/17 [=======>......................] - ETA: 0s - loss: 1.7053 - accuracy: 0.4281" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mtrain_dataset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_tensor_slices\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mtest_dataset\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2828\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_define_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2829\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_filtered_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# pylint: disable=protected-access\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2830\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2831\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m_filtered_call\u001b[0;34m(self, args, kwargs, cancellation_manager)\u001b[0m\n\u001b[1;32m 1846\u001b[0m resource_variable_ops.BaseResourceVariable))],\n\u001b[1;32m 1847\u001b[0m \u001b[0mcaptured_inputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcaptured_inputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1848\u001b[0;31m cancellation_manager=cancellation_manager)\n\u001b[0m\u001b[1;32m 1849\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1850\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_call_flat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcaptured_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcancellation_manager\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36m_call_flat\u001b[0;34m(self, args, captured_inputs, cancellation_manager)\u001b[0m\n\u001b[1;32m 1922\u001b[0m \u001b[0;31m# No tape is watching; skip to running the function.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1923\u001b[0m return self._build_call_outputs(self._inference_function.call(\n\u001b[0;32m-> 1924\u001b[0;31m ctx, args, cancellation_manager=cancellation_manager))\n\u001b[0m\u001b[1;32m 1925\u001b[0m forward_backward = self._select_forward_and_backward_functions(\n\u001b[1;32m 1926\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py\u001b[0m in \u001b[0;36mcall\u001b[0;34m(self, ctx, args, cancellation_manager)\u001b[0m\n\u001b[1;32m 548\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 549\u001b[0m \u001b[0mattrs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mattrs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 550\u001b[0;31m ctx=ctx)\n\u001b[0m\u001b[1;32m 551\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 552\u001b[0m outputs = execute.execute_with_cancellation(\n", + "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/execute.py\u001b[0m in \u001b[0;36mquick_execute\u001b[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mensure_initialized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 59\u001b[0m tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,\n\u001b[0;32m---> 60\u001b[0;31m inputs, attrs, num_outputs)\n\u001b[0m\u001b[1;32m 61\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "train_dataset = tf.data.Dataset.from_tensor_slices((X_train, Y_train)).batch(64)\n", + "test_dataset = tf.data.Dataset.from_tensor_slices((X_test, Y_test)).batch(64)\n", + "history = conv_model.fit(train_dataset, epochs=100, validation_data=test_dataset)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5 - History Object \n", + "\n", + "The history object is an output of the `.fit()` operation, and provides a record of all the loss and metric values in memory. It's stored as a dictionary that you can retrieve at `history.history`: " + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'history' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mNameError\u001b[0m: name 'history' is not defined" + ] + } + ], + "source": [ + "history.history" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now visualize the loss over time using `history.history`: " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'history' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# The history.history[\"loss\"] entry is a dictionary with as many values as epochs that the\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;31m# model was trained on.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdf_loss_acc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mdf_loss\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mdf_loss_acc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'loss'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'val_loss'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdf_loss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'loss'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m'train'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'val_loss'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m'validation'\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'history' is not defined" + ] + } + ], + "source": [ + "# The history.history[\"loss\"] entry is a dictionary with as many values as epochs that the\n", + "# model was trained on. \n", + "df_loss_acc = pd.DataFrame(history.history)\n", + "df_loss= df_loss_acc[['loss','val_loss']]\n", + "df_loss.rename(columns={'loss':'train','val_loss':'validation'},inplace=True)\n", + "df_acc= df_loss_acc[['accuracy','val_accuracy']]\n", + "df_acc.rename(columns={'accuracy':'train','val_accuracy':'validation'},inplace=True)\n", + "df_loss.plot(title='Model loss',figsize=(12,8)).set(xlabel='Epoch',ylabel='Loss')\n", + "df_acc.plot(title='Model Accuracy',figsize=(12,8)).set(xlabel='Epoch',ylabel='Accuracy')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations**! You've finished the assignment and built two models: One that recognizes smiles, and another that recognizes SIGN language with almost 80% accuracy on the test set. In addition to that, you now also understand the applications of two Keras APIs: Sequential and Functional. Nicely done! \n", + "\n", + "By now, you know a bit about how the Functional API works and may have glimpsed the possibilities. In your next assignment, you'll really get a feel for its power when you get the opportunity to build a very deep ConvNet, using ResNets! " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 6 - Bibliography\n", + "\n", + "You're always encouraged to read the official documentation. To that end, you can find the docs for the Sequential and Functional APIs here: \n", + "\n", + "https://www.tensorflow.org/guide/keras/sequential_model\n", + "\n", + "https://www.tensorflow.org/guide/keras/functional" + ] + } + ], + "metadata": { + "coursera": { + "course_slug": "convolutional-neural-networks", + "graded_item_id": "bwbJV", + "launcher_item_id": "0TkXB" + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Step_by_Step_v1.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Step_by_Step_v1.ipynb new file mode 100644 index 00000000000..004917628ed --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Convolution_model_Step_by_Step_v1.ipynb @@ -0,0 +1,1823 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Convolutional Neural Networks: Step by Step\n", + "\n", + "Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward propagation. \n", + "\n", + "By the end of this notebook, you'll be able to: \n", + "\n", + "* Explain the convolution operation\n", + "* Apply two different types of pooling operation\n", + "* Identify the components used in a convolutional neural network (padding, stride, filter, ...) and their purpose\n", + "* Build a convolutional neural network \n", + "\n", + "**Notation**:\n", + "- Superscript $[l]$ denotes an object of the $l^{th}$ layer. \n", + " - Example: $a^{[4]}$ is the $4^{th}$ layer activation. $W^{[5]}$ and $b^{[5]}$ are the $5^{th}$ layer parameters.\n", + "\n", + "\n", + "- Superscript $(i)$ denotes an object from the $i^{th}$ example. \n", + " - Example: $x^{(i)}$ is the $i^{th}$ training example input.\n", + " \n", + " \n", + "- Subscript $i$ denotes the $i^{th}$ entry of a vector.\n", + " - Example: $a^{[l]}_i$ denotes the $i^{th}$ entry of the activations in layer $l$, assuming this is a fully connected (FC) layer.\n", + " \n", + " \n", + "- $n_H$, $n_W$ and $n_C$ denote respectively the height, width and number of channels of a given layer. If you want to reference a specific layer $l$, you can also write $n_H^{[l]}$, $n_W^{[l]}$, $n_C^{[l]}$. \n", + "- $n_{H_{prev}}$, $n_{W_{prev}}$ and $n_{C_{prev}}$ denote respectively the height, width and number of channels of the previous layer. If referencing a specific layer $l$, this could also be denoted $n_H^{[l-1]}$, $n_W^{[l-1]}$, $n_C^{[l-1]}$. \n", + "\n", + "You should be familiar with `numpy` and/or have completed the previous courses of the specialization. Let's get started!\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "\n", + "- [1 - Packages](#1)\n", + "- [2 - Outline of the Assignment](#2)\n", + "- [3 - Convolutional Neural Networks](#3)\n", + " - [3.1 - Zero-Padding](#3-1)\n", + " - [Exercise 1 - zero_pad](#ex-1)\n", + " - [3.2 - Single Step of Convolution](#3-2)\n", + " - [Exercise 2 - conv_single_step](#ex-2)\n", + " - [3.3 - Convolutional Neural Networks - Forward Pass](#3-3)\n", + " - [Exercise 3 - conv_forward](#ex-3)\n", + "- [4 - Pooling Layer](#4)\n", + " - [4.1 - Forward Pooling](#4-1)\n", + " - [Exercise 4 - pool_forward](#ex-4)\n", + "- [5 - Backpropagation in Convolutional Neural Networks (OPTIONAL / UNGRADED)](#5)\n", + " - [5.1 - Convolutional Layer Backward Pass](#5-1)\n", + " - [5.1.1 - Computing dA](#5-1-1)\n", + " - [5.1.2 - Computing dW](#5-1-2)\n", + " - [5.1.3 - Computing db](#5-1-3)\n", + " - [Exercise 5 - conv_backward](#ex-5)\n", + " - [5.2 Pooling Layer - Backward Pass](#5-2)\n", + " - [5.2.1 Max Pooling - Backward Pass](#5-2-1)\n", + " - [Exercise 6 - create_mask_from_window](#ex-6)\n", + " - [5.2.2 - Average Pooling - Backward Pass](#5-2-2)\n", + " - [Exercise 7 - distribute_value](#ex-7)\n", + " - [5.2.3 Putting it Together: Pooling Backward](#5-2-3)\n", + " - [Exercise 8 - pool_backward](#ex-8)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages\n", + "\n", + "Let's first import all the packages that you will need during this assignment. \n", + "- [numpy](www.numpy.org) is the fundamental package for scientific computing with Python.\n", + "- [matplotlib](http://matplotlib.org) is a library to plot graphs in Python.\n", + "- np.random.seed(1) is used to keep all the random function calls consistent. This helps to grade your work." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import h5py\n", + "import matplotlib.pyplot as plt\n", + "from public_tests import *\n", + "\n", + "%matplotlib inline\n", + "plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots\n", + "plt.rcParams['image.interpolation'] = 'nearest'\n", + "plt.rcParams['image.cmap'] = 'gray'\n", + "\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "np.random.seed(1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Outline of the Assignment\n", + "\n", + "You will be implementing the building blocks of a convolutional neural network! Each function you will implement will have detailed instructions to walk you through the steps:\n", + "\n", + "- Convolution functions, including:\n", + " - Zero Padding\n", + " - Convolve window \n", + " - Convolution forward\n", + " - Convolution backward (optional)\n", + "- Pooling functions, including:\n", + " - Pooling forward\n", + " - Create mask \n", + " - Distribute value\n", + " - Pooling backward (optional)\n", + " \n", + "This notebook will ask you to implement these functions from scratch in `numpy`. In the next notebook, you will use the TensorFlow equivalents of these functions to build the following model:\n", + "\n", + "\n", + "\n", + "**Note**: For every forward function, there is a corresponding backward equivalent. Hence, at every step of your forward module you will store some parameters in a cache. These parameters are used to compute gradients during backpropagation. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Convolutional Neural Networks\n", + "\n", + "Although programming frameworks make convolutions easy to use, they remain one of the hardest concepts to understand in Deep Learning. A convolution layer transforms an input volume into an output volume of different size, as shown below. \n", + "\n", + "\n", + "\n", + "In this part, you will build every step of the convolution layer. You will first implement two helper functions: one for zero padding and the other for computing the convolution function itself. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.1 - Zero-Padding\n", + "\n", + "Zero-padding adds zeros around the border of an image:\n", + "\n", + "\n", + "
Figure 1 : Zero-Padding
Image (3 channels, RGB) with a padding of 2.
\n", + "\n", + "The main benefits of padding are:\n", + "\n", + "- It allows you to use a CONV layer without necessarily shrinking the height and width of the volumes. This is important for building deeper networks, since otherwise the height/width would shrink as you go to deeper layers. An important special case is the \"same\" convolution, in which the height/width is exactly preserved after one layer. \n", + "\n", + "- It helps us keep more of the information at the border of an image. Without padding, very few values at the next layer would be affected by pixels at the edges of an image.\n", + "\n", + "\n", + "### Exercise 1 - zero_pad\n", + "Implement the following function, which pads all the images of a batch of examples X with zeros. [Use np.pad](https://docs.scipy.org/doc/numpy/reference/generated/numpy.pad.html). Note if you want to pad the array \"a\" of shape $(5,5,5,5,5)$ with `pad = 1` for the 2nd dimension, `pad = 3` for the 4th dimension and `pad = 0` for the rest, you would do:\n", + "```python\n", + "a = np.pad(a, ((0,0), (1,1), (0,0), (3,3), (0,0)), mode='constant', constant_values = (0,0))\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "a14748505131e4100f550b8afcfb2d33", + "grade": false, + "grade_id": "cell-3096786c4bcad84a", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: zero_pad\n", + "\n", + "def zero_pad(X, pad):\n", + " \"\"\"\n", + " Pad with zeros all images of the dataset X. The padding is applied to the height and width of an image, \n", + " as illustrated in Figure 1.\n", + " \n", + " Argument:\n", + " X -- python numpy array of shape (m, n_H, n_W, n_C) representing a batch of m images\n", + " pad -- integer, amount of padding around each image on vertical and horizontal dimensions\n", + " \n", + " Returns:\n", + " X_pad -- padded image of shape (m, n_H + 2 * pad, n_W + 2 * pad, n_C)\n", + " \"\"\"\n", + " \n", + " #(β‰ˆ 1 line)\n", + " # X_pad = None\n", + " # YOUR CODE STARTS HERE\n", + " X_pad = np.pad(X,((0,0),(pad,pad),(pad,pad),(0,0))) \n", + " \n", + " # YOUR CODE ENDS HERE\n", + " \n", + " return X_pad" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "77b102453547ea1396bef12df34e11f8", + "grade": true, + "grade_id": "cell-65f1ed75ba39bc0a", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x.shape =\n", + " (4, 3, 3, 2)\n", + "x_pad.shape =\n", + " (4, 9, 9, 2)\n", + "x[1,1] =\n", + " [[ 0.90085595 -0.68372786]\n", + " [-0.12289023 -0.93576943]\n", + " [-0.26788808 0.53035547]]\n", + "x_pad[1,1] =\n", + " [[0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]]\n", + "x.shape =\n", + " (4, 3, 3, 2)\n", + "x_pad.shape =\n", + " (4, 9, 9, 2)\n", + "x[1,1] =\n", + " [[ 0.90085595 -0.68372786]\n", + " [-0.12289023 -0.93576943]\n", + " [-0.26788808 0.53035547]]\n", + "x_pad[1,1] =\n", + " [[0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]\n", + " [0. 0.]]\n", + "[[0. 0. 0. 0. 0. 0. 0. 0. 0.]\n", + " [0. 0. 0. 0. 0. 0. 0. 0. 0.]]\n", + "\u001b[92mAll tests passed!\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "np.random.seed(1)\n", + "x = np.random.randn(4, 3, 3, 2)\n", + "x_pad = zero_pad(x, 3)\n", + "print (\"x.shape =\\n\", x.shape)\n", + "print (\"x_pad.shape =\\n\", x_pad.shape)\n", + "print (\"x[1,1] =\\n\", x[1, 1])\n", + "print (\"x_pad[1,1] =\\n\", x_pad[1, 1])\n", + "\n", + "fig, axarr = plt.subplots(1, 2)\n", + "axarr[0].set_title('x')\n", + "axarr[0].imshow(x[0, :, :, 0])\n", + "axarr[1].set_title('x_pad')\n", + "axarr[1].imshow(x_pad[0, :, :, 0])\n", + "zero_pad_test(zero_pad)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - Single Step of Convolution \n", + "\n", + "In this part, implement a single step of convolution, in which you apply the filter to a single position of the input. This will be used to build a convolutional unit, which: \n", + "\n", + "- Takes an input volume \n", + "- Applies a filter at every position of the input\n", + "- Outputs another volume (usually of different size)\n", + "\n", + "\n", + "
Figure 2 : Convolution operation
with a filter of 3x3 and a stride of 1 (stride = amount you move the window each time you slide)
\n", + "\n", + "In a computer vision application, each value in the matrix on the left corresponds to a single pixel value. You convolve a 3x3 filter with the image by multiplying its values element-wise with the original matrix, then summing them up and adding a bias. In this first step of the exercise, you will implement a single step of convolution, corresponding to applying a filter to just one of the positions to get a single real-valued output. \n", + "\n", + "Later in this notebook, you'll apply this function to multiple positions of the input to implement the full convolutional operation. \n", + "\n", + "\n", + "### Exercise 2 - conv_single_step\n", + "Implement `conv_single_step()`. \n", + " \n", + "[Hint](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.sum.html)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Note**: The variable b will be passed in as a numpy array. If you add a scalar (a float or integer) to a numpy array, the result is a numpy array. In the special case of a numpy array containing a single value, you can cast it as a float to convert it to a scalar." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "9ef959e74c801cce52d46fb16fb0ba0d", + "grade": false, + "grade_id": "cell-bd1b8f799894d4e0", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: conv_single_step\n", + "\n", + "def conv_single_step(a_slice_prev, W, b):\n", + " \"\"\"\n", + " Apply one filter defined by parameters W on a single slice (a_slice_prev) of the output activation \n", + " of the previous layer.\n", + " \n", + " Arguments:\n", + " a_slice_prev -- slice of input data of shape (f, f, n_C_prev)\n", + " W -- Weight parameters contained in a window - matrix of shape (f, f, n_C_prev)\n", + " b -- Bias parameters contained in a window - matrix of shape (1, 1, 1)\n", + " \n", + " Returns:\n", + " Z -- a scalar value, the result of convolving the sliding window (W, b) on a slice x of the input data\n", + " \"\"\"\n", + "\n", + " #(β‰ˆ 3 lines of code)\n", + " # Element-wise product between a_slice_prev and W. Do not add the bias yet.\n", + " s = np.multiply(a_slice_prev,W)\n", + " # Sum over all entries of the volume s.\n", + " Z = np.sum(s)\n", + " # Add bias b to Z. Cast b to a float() so that Z results in a scalar value.\n", + " b = np.squeeze(b)\n", + " Z = Z + b\n", + " # YOUR CODE STARTS HERE\n", + " \n", + " \n", + " # YOUR CODE ENDS HERE\n", + "\n", + " return Z" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "7e4306fe13522c163e4eb63e7682b7bc", + "grade": true, + "grade_id": "cell-a77e63b4119ac3b9", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Z = -6.999089450680221\n", + "\u001b[92mAll tests passed!\n" + ] + } + ], + "source": [ + "np.random.seed(1)\n", + "a_slice_prev = np.random.randn(4, 4, 3)\n", + "W = np.random.randn(4, 4, 3)\n", + "b = np.random.randn(1, 1, 1)\n", + "\n", + "Z = conv_single_step(a_slice_prev, W, b)\n", + "print(\"Z =\", Z)\n", + "conv_single_step_test(conv_single_step)\n", + "\n", + "assert (type(Z) == np.float64), \"You must cast the output to numpy float 64\"\n", + "assert np.isclose(Z, -6.999089450680221), \"Wrong value\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.3 - Convolutional Neural Networks - Forward Pass\n", + "\n", + "In the forward pass, you will take many filters and convolve them on the input. Each 'convolution' gives you a 2D matrix output. You will then stack these outputs to get a 3D volume: \n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "\n", + "### Exercise 3 - conv_forward\n", + "Implement the function below to convolve the filters `W` on an input activation `A_prev`. \n", + "This function takes the following inputs:\n", + "* `A_prev`, the activations output by the previous layer (for a batch of m inputs); \n", + "* Weights are denoted by `W`. The filter window size is `f` by `f`.\n", + "* The bias vector is `b`, where each filter has its own (single) bias. \n", + "\n", + "You also have access to the hyperparameters dictionary, which contains the stride and the padding. \n", + "\n", + "**Hint**: \n", + "1. To select a 2x2 slice at the upper left corner of a matrix \"a_prev\" (shape (5,5,3)), you would do:\n", + "```python\n", + "a_slice_prev = a_prev[0:2,0:2,:]\n", + "```\n", + "Notice how this gives a 3D slice that has height 2, width 2, and depth 3. Depth is the number of channels. \n", + "This will be useful when you will define `a_slice_prev` below, using the `start/end` indexes you will define.\n", + "\n", + "2. To define a_slice you will need to first define its corners `vert_start`, `vert_end`, `horiz_start` and `horiz_end`. This figure may be helpful for you to find out how each of the corners can be defined using h, w, f and s in the code below.\n", + "\n", + "\n", + "
Figure 3 : Definition of a slice using vertical and horizontal start/end (with a 2x2 filter)
This figure shows only a single channel.
\n", + "\n", + "\n", + "**Reminder**:\n", + " \n", + "The formulas relating the output shape of the convolution to the input shape are:\n", + " \n", + "$$n_H = \\Bigl\\lfloor \\frac{n_{H_{prev}} - f + 2 \\times pad}{stride} \\Bigr\\rfloor +1$$\n", + "$$n_W = \\Bigl\\lfloor \\frac{n_{W_{prev}} - f + 2 \\times pad}{stride} \\Bigr\\rfloor +1$$\n", + "$$n_C = \\text{number of filters used in the convolution}$$\n", + " \n", + "\n", + "\n", + "\n", + "For this exercise, don't worry about vectorization! Just implement everything with for-loops." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Additional Hints (if you're stuck):\n", + "\n", + "\n", + "* Use array slicing (e.g.`varname[0:1,:,3:5]`) for the following variables: \n", + " `a_prev_pad` ,`W`, `b` \n", + " - Copy the starter code of the function and run it outside of the defined function, in separate cells. \n", + " - Check that the subset of each array is the size and dimension that you're expecting. \n", + "* To decide how to get the `vert_start`, `vert_end`, `horiz_start`, `horiz_end`, remember that these are indices of the previous layer. \n", + " - Draw an example of a previous padded layer (8 x 8, for instance), and the current (output layer) (2 x 2, for instance). \n", + " - The output layer's indices are denoted by `h` and `w`. \n", + "* Make sure that `a_slice_prev` has a height, width and depth.\n", + "* Remember that `a_prev_pad` is a subset of `A_prev_pad`. \n", + " - Think about which one should be used within the for loops." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "812d5c174c04b75b9edaf9b77ce3da72", + "grade": false, + "grade_id": "cell-00b35b01091c3cdc", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: conv_forward\n", + "\n", + "def conv_forward(A_prev, W, b, hparameters):\n", + " \"\"\"\n", + " Implements the forward propagation for a convolution function\n", + " \n", + " Arguments:\n", + " A_prev -- output activations of the previous layer, \n", + " numpy array of shape (m, n_H_prev, n_W_prev, n_C_prev)\n", + " W -- Weights, numpy array of shape (f, f, n_C_prev, n_C)\n", + " b -- Biases, numpy array of shape (1, 1, 1, n_C)\n", + " hparameters -- python dictionary containing \"stride\" and \"pad\"\n", + " \n", + " Returns:\n", + " Z -- conv output, numpy array of shape (m, n_H, n_W, n_C)\n", + " cache -- cache of values needed for the conv_backward() function\n", + " \"\"\"\n", + " \n", + " # Retrieve dimensions from A_prev's shape (β‰ˆ1 line) \n", + " (m, n_H_prev, n_W_prev, n_C_prev) = A_prev.shape\n", + " \n", + " # Retrieve dimensions from W's shape (β‰ˆ1 line)\n", + " (f, f, n_C_prev, n_C) = W.shape\n", + " \n", + " # Retrieve information from \"hparameters\" (β‰ˆ2 lines)\n", + " stride = hparameters[\"stride\"]\n", + " pad = hparameters[\"pad\"]\n", + " \n", + " # Compute the dimensions of the CONV output volume using the formula given above. \n", + " # Hint: use int() to apply the 'floor' operation. (β‰ˆ2 lines)\n", + " n_H = int((n_H_prev + 2*pad - f)/stride) + 1\n", + " n_W = int((n_W_prev + 2*pad - f)/stride) + 1\n", + " \n", + " # Initialize the output volume Z with zeros. (β‰ˆ1 line)\n", + " Z = np.zeros((m, n_H, n_W, n_C))\n", + " \n", + " # Create A_prev_pad by padding A_prev\n", + " A_prev_pad = zero_pad(A_prev, pad)\n", + " \n", + " for i in range(m): # loop over the batch of training examples\n", + " a_prev_pad = A_prev_pad[i] # Select ith training example's padded activation\n", + " for h in range(n_H): # loop over vertical axis of the output volume\n", + " # Find the vertical start and end of the current \"slice\" (β‰ˆ2 lines)\n", + " vert_start = stride * h \n", + " vert_end = vert_start + f\n", + " \n", + " for w in range(n_W): # loop over horizontal axis of the output volume\n", + " # Find the horizontal start and end of the current \"slice\" (β‰ˆ2 lines)\n", + " horiz_start = stride * w\n", + " horiz_end = horiz_start + f\n", + " \n", + " for c in range(n_C): # loop over channels (= #filters) of the output volume\n", + " \n", + " # Use the corners to define the (3D) slice of a_prev_pad (See Hint above the cell). (β‰ˆ1 line)\n", + " a_slice_prev = a_prev_pad[vert_start:vert_end,horiz_start:horiz_end,:]\n", + " \n", + " # Convolve the (3D) slice with the correct filter W and bias b, to get back one output neuron. (β‰ˆ3 line)\n", + " weights = W[:, :, :, c]\n", + " biases = b[:, :, :, c]\n", + " Z[i, h, w, c] = conv_single_step(a_slice_prev, weights, biases)\n", + " \n", + " # Save information in \"cache\" for the backprop\n", + " cache = (A_prev, W, b, hparameters)\n", + " \n", + " return Z, cache" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "f19fe38e8004fe3581b0a52ac27dc5df", + "grade": true, + "grade_id": "cell-429520eed87675d9", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Z's mean =\n", + " 0.5511276474566768\n", + "Z[0,2,1] =\n", + " [-2.17796037 8.07171329 -0.5772704 3.36286738 4.48113645 -2.89198428\n", + " 10.99288867 3.03171932]\n", + "cache_conv[0][1][2][3] =\n", + " [-1.1191154 1.9560789 -0.3264995 -1.34267579]\n", + "\u001b[92mFirst Test: All tests passed!\n", + "\u001b[92mSecond Test: All tests passed!\n" + ] + } + ], + "source": [ + "np.random.seed(1)\n", + "A_prev = np.random.randn(2, 5, 7, 4)\n", + "W = np.random.randn(3, 3, 4, 8)\n", + "b = np.random.randn(1, 1, 1, 8)\n", + "hparameters = {\"pad\" : 1,\n", + " \"stride\": 2}\n", + "\n", + "Z, cache_conv = conv_forward(A_prev, W, b, hparameters)\n", + "z_mean = np.mean(Z)\n", + "z_0_2_1 = Z[0, 2, 1]\n", + "cache_0_1_2_3 = cache_conv[0][1][2][3]\n", + "print(\"Z's mean =\\n\", z_mean)\n", + "print(\"Z[0,2,1] =\\n\", z_0_2_1)\n", + "print(\"cache_conv[0][1][2][3] =\\n\", cache_0_1_2_3)\n", + "\n", + "conv_forward_test_1(z_mean, z_0_2_1, cache_0_1_2_3)\n", + "conv_forward_test_2(conv_forward)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, a CONV layer should also contain an activation, in which case you would add the following line of code:\n", + "\n", + "```python\n", + "# Convolve the window to get back one output neuron\n", + "Z[i, h, w, c] = ...\n", + "# Apply activation\n", + "A[i, h, w, c] = activation(Z[i, h, w, c])\n", + "```\n", + "\n", + "You don't need to do it here, however. \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 4 - Pooling Layer \n", + "\n", + "The pooling (POOL) layer reduces the height and width of the input. It helps reduce computation, as well as helps make feature detectors more invariant to its position in the input. The two types of pooling layers are: \n", + "\n", + "- Max-pooling layer: slides an ($f, f$) window over the input and stores the max value of the window in the output.\n", + "\n", + "- Average-pooling layer: slides an ($f, f$) window over the input and stores the average value of the window in the output.\n", + "\n", + "\n", + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + "\n", + "These pooling layers have no parameters for backpropagation to train. However, they have hyperparameters such as the window size $f$. This specifies the height and width of the $f \\times f$ window you would compute a *max* or *average* over. \n", + "\n", + "\n", + "### 4.1 - Forward Pooling\n", + "Now, you are going to implement MAX-POOL and AVG-POOL, in the same function. \n", + "\n", + "\n", + "### Exercise 4 - pool_forward\n", + "\n", + "Implement the forward pass of the pooling layer. Follow the hints in the comments below.\n", + "\n", + "**Reminder**:\n", + "As there's no padding, the formulas binding the output shape of the pooling to the input shape is:\n", + "\n", + "$$n_H = \\Bigl\\lfloor \\frac{n_{H_{prev}} - f}{stride} \\Bigr\\rfloor +1$$\n", + "\n", + "$$n_W = \\Bigl\\lfloor \\frac{n_{W_{prev}} - f}{stride} \\Bigr\\rfloor +1$$\n", + "\n", + "$$n_C = n_{C_{prev}}$$\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "0201a499bc4a2249c65fa3a736985fac", + "grade": false, + "grade_id": "cell-aed533a126205ca2", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# GRADED FUNCTION: pool_forward\n", + "\n", + "def pool_forward(A_prev, hparameters, mode = \"max\"):\n", + " \"\"\"\n", + " Implements the forward pass of the pooling layer\n", + " \n", + " Arguments:\n", + " A_prev -- Input data, numpy array of shape (m, n_H_prev, n_W_prev, n_C_prev)\n", + " hparameters -- python dictionary containing \"f\" and \"stride\"\n", + " mode -- the pooling mode you would like to use, defined as a string (\"max\" or \"average\")\n", + " \n", + " Returns:\n", + " A -- output of the pool layer, a numpy array of shape (m, n_H, n_W, n_C)\n", + " cache -- cache used in the backward pass of the pooling layer, contains the input and hparameters \n", + " \"\"\"\n", + " \n", + " # Retrieve dimensions from the input shape\n", + " (m, n_H_prev, n_W_prev, n_C_prev) = A_prev.shape\n", + " \n", + " # Retrieve hyperparameters from \"hparameters\"\n", + " f = hparameters[\"f\"]\n", + " stride = hparameters[\"stride\"]\n", + " \n", + " # Define the dimensions of the output\n", + " n_H = int(1 + (n_H_prev - f) / stride)\n", + " n_W = int(1 + (n_W_prev - f) / stride)\n", + " n_C = n_C_prev\n", + " \n", + " # Initialize output matrix A\n", + " A = np.zeros((m, n_H, n_W, n_C)) \n", + " \n", + " ### START CODE HERE ###\n", + " for i in range(m): # loop over the training examples\n", + " a_prev_slice = A_prev[i]\n", + " for h in range(n_H): # loop on the vertical axis of the output volume\n", + " # Find the vertical start and end of the current \"slice\" (β‰ˆ2 lines)\n", + " vert_start = stride * h \n", + " vert_end = vert_start + f\n", + " \n", + " for w in range(n_W): # loop on the horizontal axis of the output volume\n", + " # Find the vertical start and end of the current \"slice\" (β‰ˆ2 lines)\n", + " horiz_start = stride * w\n", + " horiz_end = horiz_start + f\n", + " \n", + " for c in range (n_C): # loop over the channels of the output volume\n", + " \n", + " # Use the corners to define the current slice on the ith training example of A_prev, channel c. (β‰ˆ1 line)\n", + " a_slice_prev = a_prev_slice[vert_start:vert_end,horiz_start:horiz_end,c]\n", + " \n", + " # Compute the pooling operation on the slice. \n", + " # Use an if statement to differentiate the modes. \n", + " # Use np.max and np.mean.\n", + " if mode == \"max\":\n", + " A[i, h, w, c] = np.max(a_slice_prev)\n", + " elif mode == \"average\":\n", + " A[i, h, w, c] = np.mean(a_slice_prev)\n", + " else:\n", + " print(mode+ \"-type pooling layer NOT Defined\") \n", + " # YOUR CODE ENDS HERE\n", + " \n", + " # Store the input and hparameters in \"cache\" for pool_backward()\n", + " cache = (A_prev, hparameters)\n", + " \n", + " # Making sure your output shape is correct\n", + " assert(A.shape == (m, n_H, n_W, n_C))\n", + " \n", + " return A, cache" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "41872940d42f284c524d3b66eaf3c205", + "grade": true, + "grade_id": "cell-ae96f27f888cec37", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mode = max\n", + "A.shape = (2, 3, 3, 3)\n", + "A[1, 1] =\n", + " [[1.96710175 0.84616065 1.27375593]\n", + " [1.96710175 0.84616065 1.23616403]\n", + " [1.62765075 1.12141771 1.2245077 ]]\n", + "mode = average\n", + "A.shape = (2, 3, 3, 3)\n", + "A[1, 1] =\n", + " [[ 0.44497696 -0.00261695 -0.31040307]\n", + " [ 0.50811474 -0.23493734 -0.23961183]\n", + " [ 0.11872677 0.17255229 -0.22112197]]\n", + "\u001b[92mAll tests passed!\n" + ] + } + ], + "source": [ + "# Case 1: stride of 1\n", + "np.random.seed(1)\n", + "A_prev = np.random.randn(2, 5, 5, 3)\n", + "hparameters = {\"stride\" : 1, \"f\": 3}\n", + "\n", + "A, cache = pool_forward(A_prev, hparameters, mode = \"max\")\n", + "print(\"mode = max\")\n", + "print(\"A.shape = \" + str(A.shape))\n", + "print(\"A[1, 1] =\\n\", A[1, 1])\n", + "A, cache = pool_forward(A_prev, hparameters, mode = \"average\")\n", + "print(\"mode = average\")\n", + "print(\"A.shape = \" + str(A.shape))\n", + "print(\"A[1, 1] =\\n\", A[1, 1])\n", + "\n", + "pool_forward_test(pool_forward)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected output**\n", + "\n", + "```\n", + "mode = max\n", + "A.shape = (2, 3, 3, 3)\n", + "A[1, 1] =\n", + " [[1.96710175 0.84616065 1.27375593]\n", + " [1.96710175 0.84616065 1.23616403]\n", + " [1.62765075 1.12141771 1.2245077 ]]\n", + "\n", + "mode = average\n", + "A.shape = (2, 3, 3, 3)\n", + "A[1, 1] =\n", + " [[ 0.44497696 -0.00261695 -0.31040307]\n", + " [ 0.50811474 -0.23493734 -0.23961183]\n", + " [ 0.11872677 0.17255229 -0.22112197]]\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "756f8dfdbdba11c66fc0b342d8be23c4", + "grade": true, + "grade_id": "cell-2bc34b23ee92311b", + "locked": true, + "points": 0, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mode = max\n", + "A.shape = (2, 2, 2, 3)\n", + "A[0] =\n", + " [[[1.74481176 0.90159072 1.65980218]\n", + " [1.74481176 1.6924546 1.65980218]]\n", + "\n", + " [[1.13162939 1.51981682 2.18557541]\n", + " [1.13162939 1.6924546 2.18557541]]]\n", + "\n", + "mode = average\n", + "A.shape = (2, 2, 2, 3)\n", + "A[1] =\n", + " [[[-0.17313416 0.32377198 -0.34317572]\n", + " [ 0.02030094 0.14141479 -0.01231585]]\n", + "\n", + " [[ 0.42944926 0.08446996 -0.27290905]\n", + " [ 0.15077452 0.28911175 0.00123239]]]\n" + ] + } + ], + "source": [ + "# Case 2: stride of 2\n", + "np.random.seed(1)\n", + "A_prev = np.random.randn(2, 5, 5, 3)\n", + "hparameters = {\"stride\" : 2, \"f\": 3}\n", + "\n", + "A, cache = pool_forward(A_prev, hparameters)\n", + "print(\"mode = max\")\n", + "print(\"A.shape = \" + str(A.shape))\n", + "print(\"A[0] =\\n\", A[0])\n", + "print()\n", + "\n", + "A, cache = pool_forward(A_prev, hparameters, mode = \"average\")\n", + "print(\"mode = average\")\n", + "print(\"A.shape = \" + str(A.shape))\n", + "print(\"A[1] =\\n\", A[1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output:**\n", + " \n", + "```\n", + "mode = max\n", + "A.shape = (2, 2, 2, 3)\n", + "A[0] =\n", + " [[[1.74481176 0.90159072 1.65980218]\n", + " [1.74481176 1.6924546 1.65980218]]\n", + "\n", + " [[1.13162939 1.51981682 2.18557541]\n", + " [1.13162939 1.6924546 2.18557541]]]\n", + "\n", + "mode = average\n", + "A.shape = (2, 2, 2, 3)\n", + "A[1] =\n", + " [[[-0.17313416 0.32377198 -0.34317572]\n", + " [ 0.02030094 0.14141479 -0.01231585]]\n", + "\n", + " [[ 0.42944926 0.08446996 -0.27290905]\n", + " [ 0.15077452 0.28911175 0.00123239]]]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + " \n", + "**What you should remember**:\n", + "\n", + "* A convolution extracts features from an input image by taking the dot product between the input data and a 3D array of weights (the filter). \n", + "* The 2D output of the convolution is called the feature map\n", + "* A convolution layer is where the filter slides over the image and computes the dot product \n", + " * This transforms the input volume into an output volume of different size \n", + "* Zero padding helps keep more information at the image borders, and is helpful for building deeper networks, because you can build a CONV layer without shrinking the height and width of the volumes\n", + "* Pooling layers gradually reduce the height and width of the input by sliding a 2D window over each specified region, then summarizing the features in that region" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations**! You have now implemented the forward passes of all the layers of a convolutional network. Great work!\n", + "\n", + "The remainder of this notebook is optional, and will not be graded. If you carry on, just remember to hit the Submit button to submit your work for grading first. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5 - Backpropagation in Convolutional Neural Networks (OPTIONAL / UNGRADED)\n", + "\n", + "In modern deep learning frameworks, you only have to implement the forward pass, and the framework takes care of the backward pass, so most deep learning engineers don't need to bother with the details of the backward pass. The backward pass for convolutional networks is complicated. If you wish, you can work through this optional portion of the notebook to get a sense of what backprop in a convolutional network looks like. \n", + "\n", + "When in an earlier course you implemented a simple (fully connected) neural network, you used backpropagation to compute the derivatives with respect to the cost to update the parameters. Similarly, in convolutional neural networks you can calculate the derivatives with respect to the cost in order to update the parameters. The backprop equations are not trivial and were not derived in lecture, but are briefly presented below.\n", + "\n", + "\n", + "### 5.1 - Convolutional Layer Backward Pass \n", + "\n", + "Let's start by implementing the backward pass for a CONV layer. \n", + "\n", + "\n", + "#### 5.1.1 - Computing dA:\n", + "This is the formula for computing $dA$ with respect to the cost for a certain filter $W_c$ and a given training example:\n", + "\n", + "$$dA \\mathrel{+}= \\sum _{h=0} ^{n_H} \\sum_{w=0} ^{n_W} W_c \\times dZ_{hw} \\tag{1}$$\n", + "\n", + "Where $W_c$ is a filter and $dZ_{hw}$ is a scalar corresponding to the gradient of the cost with respect to the output of the conv layer Z at the hth row and wth column (corresponding to the dot product taken at the ith stride left and jth stride down). Note that at each time, you multiply the the same filter $W_c$ by a different dZ when updating dA. We do so mainly because when computing the forward propagation, each filter is dotted and summed by a different a_slice. Therefore when computing the backprop for dA, you are just adding the gradients of all the a_slices. \n", + "\n", + "In code, inside the appropriate for-loops, this formula translates into:\n", + "```python\n", + "da_prev_pad[vert_start:vert_end, horiz_start:horiz_end, :] += W[:,:,:,c] * dZ[i, h, w, c]\n", + "```\n", + "\n", + "\n", + "#### 5.1.2 - Computing dW:\n", + "This is the formula for computing $dW_c$ ($dW_c$ is the derivative of one filter) with respect to the loss:\n", + "\n", + "$$dW_c \\mathrel{+}= \\sum _{h=0} ^{n_H} \\sum_{w=0} ^ {n_W} a_{slice} \\times dZ_{hw} \\tag{2}$$\n", + "\n", + "Where $a_{slice}$ corresponds to the slice which was used to generate the activation $Z_{ij}$. Hence, this ends up giving us the gradient for $W$ with respect to that slice. Since it is the same $W$, we will just add up all such gradients to get $dW$. \n", + "\n", + "In code, inside the appropriate for-loops, this formula translates into:\n", + "```python\n", + "dW[:,:,:,c] \\mathrel{+}= a_slice * dZ[i, h, w, c]\n", + "```\n", + "\n", + "\n", + "#### 5.1.3 - Computing db:\n", + "\n", + "This is the formula for computing $db$ with respect to the cost for a certain filter $W_c$:\n", + "\n", + "$$db = \\sum_h \\sum_w dZ_{hw} \\tag{3}$$\n", + "\n", + "As you have previously seen in basic neural networks, db is computed by summing $dZ$. In this case, you are just summing over all the gradients of the conv output (Z) with respect to the cost. \n", + "\n", + "In code, inside the appropriate for-loops, this formula translates into:\n", + "```python\n", + "db[:,:,:,c] += dZ[i, h, w, c]\n", + "```\n", + "\n", + "\n", + "### Exercise 5 - conv_backward\n", + "\n", + "Implement the `conv_backward` function below. You should sum over all the training examples, filters, heights, and widths. You should then compute the derivatives using formulas 1, 2 and 3 above. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "ac01f3e4e6f7707fb3153d5306020619", + "grade": false, + "grade_id": "cell-651d7957ed306d8d", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "def conv_backward(dZ, cache):\n", + " \"\"\"\n", + " Implement the backward propagation for a convolution function\n", + " \n", + " Arguments:\n", + " dZ -- gradient of the cost with respect to the output of the conv layer (Z), numpy array of shape (m, n_H, n_W, n_C)\n", + " cache -- cache of values needed for the conv_backward(), output of conv_forward()\n", + " \n", + " Returns:\n", + " dA_prev -- gradient of the cost with respect to the input of the conv layer (A_prev),\n", + " numpy array of shape (m, n_H_prev, n_W_prev, n_C_prev)\n", + " dW -- gradient of the cost with respect to the weights of the conv layer (W)\n", + " numpy array of shape (f, f, n_C_prev, n_C)\n", + " db -- gradient of the cost with respect to the biases of the conv layer (b)\n", + " numpy array of shape (1, 1, 1, n_C)\n", + " \"\"\" \n", + " \n", + " \n", + " # Retrieve information from \"cache\"\n", + " (A_prev, W, b, hparameters) = cache\n", + " # Retrieve dimensions from A_prev's shape\n", + " (m, n_H_prev, n_W_prev, n_C_prev) = A_prev.shape\n", + " # Retrieve dimensions from W's shape\n", + " (f, f, n_C_prev, n_C) = W.shape\n", + " \n", + " # Retrieve information from \"hparameters\"\n", + " stride = hparameters[\"stride\"]\n", + " pad = hparameters[\"pad\"]\n", + " \n", + " # Retrieve dimensions from dZ's shape\n", + " (m, n_H, n_W, n_C) = dZ.shape\n", + " \n", + " # Initialize dA_prev, dW, db with the correct shapes\n", + " dA_prev = np.zeros(A_prev.shape) \n", + " dW = np.zeros(W.shape)\n", + " db = np.zeros(b.shape) # b.shape = [1,1,1,n_C]\n", + " \n", + " # Pad A_prev and dA_prev\n", + " A_prev_pad = zero_pad(A_prev, pad)\n", + " dA_prev_pad = zero_pad(dA_prev, pad)\n", + " \n", + " for i in range(m): # loop over the training examples\n", + " \n", + " # select ith training example from A_prev_pad and dA_prev_pad\n", + " a_prev_pad = A_prev_pad[i]\n", + " da_prev_pad = dA_prev_pad[i]\n", + " \n", + " for h in range(n_H): # loop over vertical axis of the output volume\n", + " for w in range(n_W): # loop over horizontal axis of the output volume\n", + " for c in range(n_C): # loop over the channels of the output volume\n", + " \n", + " # Find the corners of the current \"slice\"\n", + " vert_start = stride * h \n", + " vert_end = vert_start + f\n", + " horiz_start = stride * w\n", + " horiz_end = horiz_start + f\n", + "\n", + " # Use the corners to define the slice from a_prev_pad\n", + " a_slice = a_prev_pad[vert_start:vert_end,horiz_start:horiz_end,:]\n", + "\n", + " # Update gradients for the window and the filter's parameters using the code formulas given above\n", + " da_prev_pad[vert_start:vert_end, horiz_start:horiz_end, :] += W[:,:,:,c] * dZ[i, h, w, c]\n", + " dW[:,:,:,c] += a_slice * dZ[i, h, w, c]\n", + " db[:,:,:,c] += dZ[i, h, w, c]\n", + " \n", + " # Set the ith training example's dA_prev to the unpadded da_prev_pad (Hint: use X[pad:-pad, pad:-pad, :])\n", + " dA_prev[i, :, :, :] = da_prev_pad[pad:-pad, pad:-pad, :]\n", + " \n", + " # Making sure your output shape is correct\n", + " assert(dA_prev.shape == (m, n_H_prev, n_W_prev, n_C_prev))\n", + " \n", + " return dA_prev, dW, db" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "fa7b07d566b435decefd8c5bd1b5c4db", + "grade": true, + "grade_id": "cell-ddba321326674547", + "locked": true, + "points": 0, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dA_mean = 1.4524377775388075\n", + "dW_mean = 1.7269914583139097\n", + "db_mean = 7.839232564616838\n", + "\u001b[92m All tests passed.\n" + ] + } + ], + "source": [ + "# We'll run conv_forward to initialize the 'Z' and 'cache_conv\",\n", + "# which we'll use to test the conv_backward function\n", + "np.random.seed(1)\n", + "A_prev = np.random.randn(10, 4, 4, 3)\n", + "W = np.random.randn(2, 2, 3, 8)\n", + "b = np.random.randn(1, 1, 1, 8)\n", + "hparameters = {\"pad\" : 2,\n", + " \"stride\": 2}\n", + "Z, cache_conv = conv_forward(A_prev, W, b, hparameters)\n", + "\n", + "# Test conv_backward\n", + "dA, dW, db = conv_backward(Z, cache_conv)\n", + "\n", + "print(\"dA_mean =\", np.mean(dA))\n", + "print(\"dW_mean =\", np.mean(dW))\n", + "print(\"db_mean =\", np.mean(db))\n", + "\n", + "assert type(dA) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert type(dW) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert type(db) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert dA.shape == (10, 4, 4, 3), f\"Wrong shape for dA {dA.shape} != (10, 4, 4, 3)\"\n", + "assert dW.shape == (2, 2, 3, 8), f\"Wrong shape for dW {dW.shape} != (2, 2, 3, 8)\"\n", + "assert db.shape == (1, 1, 1, 8), f\"Wrong shape for db {db.shape} != (1, 1, 1, 8)\"\n", + "assert np.isclose(np.mean(dA), 1.4524377), \"Wrong values for dA\"\n", + "assert np.isclose(np.mean(dW), 1.7269914), \"Wrong values for dW\"\n", + "assert np.isclose(np.mean(db), 7.8392325), \"Wrong values for db\"\n", + "\n", + "print(\"\\033[92m All tests passed.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " dA_mean\n", + " \n", + " 1.45243777754\n", + "
\n", + " dW_mean\n", + " \n", + " 1.72699145831\n", + "
\n", + " db_mean\n", + " \n", + " 7.83923256462\n", + "
\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5.2 Pooling Layer - Backward Pass\n", + "\n", + "Next, let's implement the backward pass for the pooling layer, starting with the MAX-POOL layer. Even though a pooling layer has no parameters for backprop to update, you still need to backpropagate the gradient through the pooling layer in order to compute gradients for layers that came before the pooling layer. \n", + "\n", + "\n", + "### 5.2.1 Max Pooling - Backward Pass \n", + "\n", + "Before jumping into the backpropagation of the pooling layer, you are going to build a helper function called `create_mask_from_window()` which does the following: \n", + "\n", + "$$ X = \\begin{bmatrix}\n", + "1 && 3 \\\\\n", + "4 && 2\n", + "\\end{bmatrix} \\quad \\rightarrow \\quad M =\\begin{bmatrix}\n", + "0 && 0 \\\\\n", + "1 && 0\n", + "\\end{bmatrix}\\tag{4}$$\n", + "\n", + "As you can see, this function creates a \"mask\" matrix which keeps track of where the maximum of the matrix is. True (1) indicates the position of the maximum in X, the other entries are False (0). You'll see later that the backward pass for average pooling is similar to this, but uses a different mask. \n", + "\n", + "\n", + "### Exercise 6 - create_mask_from_window\n", + "\n", + "Implement `create_mask_from_window()`. This function will be helpful for pooling backward. \n", + "Hints:\n", + "- [np.max()]() may be helpful. It computes the maximum of an array.\n", + "- If you have a matrix X and a scalar x: `A = (X == x)` will return a matrix A of the same size as X such that:\n", + "```\n", + "A[i,j] = True if X[i,j] = x\n", + "A[i,j] = False if X[i,j] != x\n", + "```\n", + "- Here, you don't need to consider cases where there are several maxima in a matrix." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "f0088c2c652d94afd13fcc4cf81ff5a0", + "grade": false, + "grade_id": "cell-75cdfabbbe3c7905", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "def create_mask_from_window(x):\n", + " \"\"\"\n", + " Creates a mask from an input matrix x, to identify the max entry of x.\n", + " \n", + " Arguments:\n", + " x -- Array of shape (f, f)\n", + " \n", + " Returns:\n", + " mask -- Array of the same shape as window, contains a True at the position corresponding to the max entry of x.\n", + " \"\"\" \n", + " # (β‰ˆ1 line)\n", + " mask = (x == np.max(x))\n", + " # YOUR CODE STARTS HERE\n", + " \n", + " \n", + " # YOUR CODE ENDS HERE\n", + " return mask" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "b239ffa3896a12254d087dc617b92a2a", + "grade": true, + "grade_id": "cell-83c1f6349c3fc0ad", + "locked": true, + "points": 0, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x = [[ 1.62434536 -0.61175641 -0.52817175]\n", + " [-1.07296862 0.86540763 -2.3015387 ]]\n", + "mask = [[ True False False]\n", + " [False False False]]\n", + "\u001b[92m All tests passed.\n" + ] + } + ], + "source": [ + "np.random.seed(1)\n", + "x = np.random.randn(2, 3)\n", + "mask = create_mask_from_window(x)\n", + "print('x = ', x)\n", + "print(\"mask = \", mask)\n", + "\n", + "x = np.array([[-1, 2, 3],\n", + " [2, -3, 2],\n", + " [1, 5, -2]])\n", + "\n", + "y = np.array([[False, False, False],\n", + " [False, False, False],\n", + " [False, True, False]])\n", + "mask = create_mask_from_window(x)\n", + "\n", + "assert type(mask) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert mask.shape == x.shape, \"Input and output shapes must match\"\n", + "assert np.allclose(mask, y), \"Wrong output. The True value must be at position (2, 1)\"\n", + "\n", + "print(\"\\033[92m All tests passed.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output:** \n", + "\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + "\n", + "**x =**\n", + "\n", + "\n", + "[[ 1.62434536 -0.61175641 -0.52817175]
\n", + " [-1.07296862 0.86540763 -2.3015387 ]]\n", + "\n", + "
\n", + "mask =\n", + "\n", + "[[ True False False]
\n", + " [False False False]]\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Why keep track of the position of the max? It's because this is the input value that ultimately influenced the output, and therefore the cost. Backprop is computing gradients with respect to the cost, so anything that influences the ultimate cost should have a non-zero gradient. So, backprop will \"propagate\" the gradient back to this particular input value that had influenced the cost. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.2.2 - Average Pooling - Backward Pass \n", + "\n", + "In max pooling, for each input window, all the \"influence\" on the output came from a single input value--the max. In average pooling, every element of the input window has equal influence on the output. So to implement backprop, you will now implement a helper function that reflects this.\n", + "\n", + "For example if we did average pooling in the forward pass using a 2x2 filter, then the mask you'll use for the backward pass will look like: \n", + "$$ dZ = 1 \\quad \\rightarrow \\quad dZ =\\begin{bmatrix}\n", + "1/4 && 1/4 \\\\\n", + "1/4 && 1/4\n", + "\\end{bmatrix}\\tag{5}$$\n", + "\n", + "This implies that each position in the $dZ$ matrix contributes equally to output because in the forward pass, we took an average. \n", + "\n", + "\n", + "### Exercise 7 - distribute_value\n", + "\n", + "Implement the function below to equally distribute a value dz through a matrix of dimension shape. \n", + "\n", + "[Hint](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ones.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "b0a0950ce4306fe20c3345f0108a49bb", + "grade": false, + "grade_id": "cell-636557cd1667f01b", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "def distribute_value(dz, shape):\n", + " \"\"\"\n", + " Distributes the input value in the matrix of dimension shape\n", + " \n", + " Arguments:\n", + " dz -- input scalar\n", + " shape -- the shape (n_H, n_W) of the output matrix for which we want to distribute the value of dz\n", + " \n", + " Returns:\n", + " a -- Array of size (n_H, n_W) for which we distributed the value of dz\n", + " \"\"\" \n", + " # Retrieve dimensions from shape (β‰ˆ1 line)\n", + " (n_H, n_W) = shape\n", + " \n", + " # Compute the value to distribute on the matrix (β‰ˆ1 line)\n", + " average = np.prod(shape)\n", + " \n", + " # Create a matrix where every entry is the \"average\" value (β‰ˆ1 line)\n", + " a = (dz/average)*np.ones(shape)\n", + " # YOUR CODE STARTS HERE\n", + " \n", + " \n", + " # YOUR CODE ENDS HERE\n", + " return a" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "fe23f96c0d977d6414842a72fa08d64d", + "grade": true, + "grade_id": "cell-d34048b69372dc03", + "locked": true, + "points": 0, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "distributed value = [[0.5 0.5]\n", + " [0.5 0.5]]\n", + "\u001b[92m All tests passed.\n" + ] + } + ], + "source": [ + "a = distribute_value(2, (2, 2))\n", + "print('distributed value =', a)\n", + "\n", + "\n", + "assert type(a) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert a.shape == (2, 2), f\"Wrong shape {a.shape} != (2, 2)\"\n", + "assert np.sum(a) == 2, \"Values must sum to 2\"\n", + "\n", + "a = distribute_value(100, (10, 10))\n", + "assert type(a) == np.ndarray, \"Output must be a np.ndarray\"\n", + "assert a.shape == (10, 10), f\"Wrong shape {a.shape} != (10, 10)\"\n", + "assert np.sum(a) == 100, \"Values must sum to 100\"\n", + "\n", + "print(\"\\033[92m All tests passed.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**: \n", + "\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "
\n", + "distributed_value =\n", + "\n", + "[[ 0.5 0.5]\n", + " \n", + "[ 0.5 0.5]]\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.2.3 Putting it Together: Pooling Backward \n", + "\n", + "You now have everything you need to compute backward propagation on a pooling layer.\n", + "\n", + "\n", + "### Exercise 8 - pool_backward\n", + "\n", + "Implement the `pool_backward` function in both modes (`\"max\"` and `\"average\"`). You will once again use 4 for-loops (iterating over training examples, height, width, and channels). You should use an `if/elif` statement to see if the mode is equal to `'max'` or `'average'`. If it is equal to 'average' you should use the `distribute_value()` function you implemented above to create a matrix of the same shape as `a_slice`. Otherwise, the mode is equal to '`max`', and you will create a mask with `create_mask_from_window()` and multiply it by the corresponding value of dA." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "deletable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "857929f83e0cff037571a794aff714de", + "grade": false, + "grade_id": "cell-46629e8e78d1ac80", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "def pool_backward(dA, cache, mode = \"max\"):\n", + " \"\"\"\n", + " Implements the backward pass of the pooling layer\n", + " \n", + " Arguments:\n", + " dA -- gradient of cost with respect to the output of the pooling layer, same shape as A\n", + " cache -- cache output from the forward pass of the pooling layer, contains the layer's input and hparameters \n", + " mode -- the pooling mode you would like to use, defined as a string (\"max\" or \"average\")\n", + " \n", + " Returns:\n", + " dA_prev -- gradient of cost with respect to the input of the pooling layer, same shape as A_prev\n", + " \"\"\"\n", + " # Retrieve information from cache (β‰ˆ1 line)\n", + " (A_prev, hparameters) = cache\n", + " \n", + " # Retrieve hyperparameters from \"hparameters\" (β‰ˆ2 lines)\n", + " stride = hparameters[\"stride\"]\n", + " f = hparameters[\"f\"]\n", + " \n", + " # Retrieve dimensions from A_prev's shape and dA's shape (β‰ˆ2 lines)\n", + " m, n_H_prev, n_W_prev, n_C_prev = A_prev.shape\n", + " m, n_H, n_W, n_C = dA.shape\n", + " \n", + " # Initialize dA_prev with zeros (β‰ˆ1 line)\n", + " dA_prev = np.zeros(A_prev.shape)\n", + " \n", + " for i in range(m): # loop over the training examples\n", + " \n", + " # select training example from A_prev (β‰ˆ1 line)\n", + " a_prev = A_prev[i,:,:,:]\n", + " \n", + " for h in range(n_H): # loop on the vertical axis\n", + " for w in range(n_W): # loop on the horizontal axis\n", + " for c in range(n_C): # loop over the channels (depth)\n", + " \n", + " # Find the corners of the current \"slice\" (β‰ˆ4 lines)\n", + " vert_start = h * stride\n", + " vert_end = h * stride + f\n", + " horiz_start = w * stride\n", + " horiz_end = w * stride + f\n", + " \n", + " # Compute the backward propagation in both modes.\n", + " if mode == \"max\":\n", + " \n", + " # Use the corners and \"c\" to define the current slice from a_prev (β‰ˆ1 line)\n", + " a_prev_slice = a_prev[ vert_start:vert_end, horiz_start:horiz_end, c ]\n", + " \n", + " # Create the mask from a_prev_slice (β‰ˆ1 line)\n", + " mask = create_mask_from_window( a_prev_slice )\n", + "\n", + " # Set dA_prev to be dA_prev + (the mask multiplied by the correct entry of dA) (β‰ˆ1 line)\n", + " dA_prev[i, vert_start:vert_end, horiz_start:horiz_end, c] += mask * dA[i, h, w, c]\n", + " \n", + " elif mode == \"average\":\n", + " \n", + " # Get the value da from dA (β‰ˆ2 line)\n", + " da = dA[i, h, w, c]\n", + " \n", + " # Define the shape of the filter as fxf (β‰ˆ1 line)\n", + " shape = (f,f)\n", + "\n", + " # Distribute it to get the correct slice of dA_prev. i.e. Add the distributed value of da. (β‰ˆ1 line)\n", + " dA_prev[i, vert_start: vert_end, horiz_start: horiz_end, c] += distribute_value(da, shape)\n", + " \n", + " # Making sure your output shape is correct\n", + " assert(dA_prev.shape == A_prev.shape)\n", + " \n", + " return dA_prev" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "cell_type": "code", + "checksum": "eeae810027f56d8418e9a89d7feec967", + "grade": true, + "grade_id": "cell-bf176d59f19c3cba", + "locked": true, + "points": 0, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(5, 4, 2, 2)\n", + "(5, 5, 3, 2)\n", + "mode = max\n", + "mean of dA = 0.14571390272918056\n", + "dA_prev1[1,1] = [[ 0. 0. ]\n", + " [ 5.05844394 -1.68282702]\n", + " [ 0. 0. ]]\n", + "\n", + "mode = average\n", + "mean of dA = 0.14571390272918056\n", + "dA_prev2[1,1] = [[ 0.08485462 0.2787552 ]\n", + " [ 1.26461098 -0.25749373]\n", + " [ 1.17975636 -0.53624893]]\n", + "\u001b[92m All tests passed.\n" + ] + } + ], + "source": [ + "np.random.seed(1)\n", + "A_prev = np.random.randn(5, 5, 3, 2)\n", + "hparameters = {\"stride\" : 1, \"f\": 2}\n", + "A, cache = pool_forward(A_prev, hparameters)\n", + "print(A.shape)\n", + "print(cache[0].shape)\n", + "dA = np.random.randn(5, 4, 2, 2)\n", + "\n", + "dA_prev1 = pool_backward(dA, cache, mode = \"max\")\n", + "print(\"mode = max\")\n", + "print('mean of dA = ', np.mean(dA))\n", + "print('dA_prev1[1,1] = ', dA_prev1[1, 1]) \n", + "print()\n", + "dA_prev2 = pool_backward(dA, cache, mode = \"average\")\n", + "print(\"mode = average\")\n", + "print('mean of dA = ', np.mean(dA))\n", + "print('dA_prev2[1,1] = ', dA_prev2[1, 1]) \n", + "\n", + "assert type(dA_prev1) == np.ndarray, \"Wrong type\"\n", + "assert dA_prev1.shape == (5, 5, 3, 2), f\"Wrong shape {dA_prev1.shape} != (5, 5, 3, 2)\"\n", + "assert np.allclose(dA_prev1[1, 1], [[0, 0], \n", + " [ 5.05844394, -1.68282702],\n", + " [ 0, 0]]), \"Wrong values for mode max\"\n", + "assert np.allclose(dA_prev2[1, 1], [[0.08485462, 0.2787552], \n", + " [1.26461098, -0.25749373], \n", + " [1.17975636, -0.53624893]]), \"Wrong values for mode average\"\n", + "print(\"\\033[92m All tests passed.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**: \n", + "\n", + "mode = max:\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "
\n", + "\n", + "**mean of dA =**\n", + "\n", + "\n", + "0.145713902729\n", + "\n", + "
\n", + "dA_prev[1,1] =\n", + "\n", + "[[ 0. 0. ]
\n", + " [ 5.05844394 -1.68282702]
\n", + " [ 0. 0. ]]\n", + "
\n", + "\n", + "mode = average\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "
\n", + "\n", + "mean of dA =\n", + "\n", + "\n", + "0.145713902729\n", + "\n", + "
\n", + "dA_prev[1,1] =\n", + "\n", + "[[ 0.08485462 0.2787552 ]
\n", + " [ 1.26461098 -0.25749373]
\n", + " [ 1.17975636 -0.53624893]]\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations**! You've completed the assignment and its optional portion. You now understand how convolutional neural networks work, and have implemented all the building blocks of a neural network. In the next assignment you will implement a ConvNet using TensorFlow. Nicely done! See you there." + ] + } + ], + "metadata": { + "coursera": { + "course_slug": "convolutional-neural-networks", + "graded_item_id": "qO8ng", + "launcher_item_id": "7XDi8" + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Face_Recognition.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Face_Recognition.ipynb new file mode 100644 index 00000000000..f41d0056ef6 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Face_Recognition.ipynb @@ -0,0 +1,1054 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Face Recognition\n", + "\n", + "Welcome! In this assignment, you're going to build a face recognition system. Many of the ideas presented here are from [FaceNet](https://arxiv.org/pdf/1503.03832.pdf). In the lecture, you also encountered [DeepFace](https://research.fb.com/wp-content/uploads/2016/11/deepface-closing-the-gap-to-human-level-performance-in-face-verification.pdf).\n", + "\n", + "Face recognition problems commonly fall into one of two categories: \n", + "\n", + "**Face Verification** \"Is this the claimed person?\" For example, at some airports, you can pass through customs by letting a system scan your passport and then verifying that you (the person carrying the passport) are the correct person. A mobile phone that unlocks using your face is also using face verification. This is a 1:1 matching problem.\n", + "\n", + "**Face Recognition** \"Who is this person?\" For example, the video lecture showed a [face recognition video](https://www.youtube.com/watch?v=wr4rx0Spihs) of Baidu employees entering the office without needing to otherwise identify themselves. This is a 1:K matching problem.\n", + "\n", + "FaceNet learns a neural network that encodes a face image into a vector of 128 numbers. By comparing two such vectors, you can then determine if two pictures are of the same person.\n", + "\n", + "By the end of this assignment, you'll be able to: \n", + "\n", + "* Differentiate between face recognition and face verification\n", + "* Implement one-shot learning to solve a face recognition problem\n", + "* Apply the triplet loss function to learn a network's parameters in the context of face recognition\n", + "* Explain how to pose face recognition as a binary classification problem\n", + "* Map face images into 128-dimensional encodings using a pretrained model\n", + "* Perform face verification and face recognition with these encodings\n", + "\n", + "**Channels-last notation**\n", + "\n", + "For this assignment, you'll be using a pre-trained model which represents ConvNet activations using a \"channels last\" convention, as used during the lecture and in previous programming assignments.\n", + "\n", + "In other words, a batch of images will be of shape $(m, n_H, n_W, n_C)$. \n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "\n", + "- [1 - Packages](#1)\n", + "- [2 - Naive Face Verification](#2)\n", + "- [3 - Encoding Face Images into a 128-Dimensional Vector](#3)\n", + " - [3.1 - Using a ConvNet to Compute Encodings](#3-1)\n", + " - [3.2 - The Triplet Loss](#3-2)\n", + " - [Exercise 1 - triplet_loss](#ex-1)\n", + "- [4 - Loading the Pre-trained Model](#4)\n", + "- [5 - Applying the Model](#5)\n", + " - [5.1 - Face Verification](#5-1)\n", + " - [Exercise 2 - verify](#ex-2)\n", + " - [5.2 - Face Recognition](#5-2)\n", + " - [Exercise 3 - who_is_it](#ex-3)\n", + "- [6 - References](#6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages\n", + "\n", + "Go ahead and run the cell below to import the packages you'll need." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import Conv2D, ZeroPadding2D, Activation, Input, concatenate\n", + "from tensorflow.keras.models import Model\n", + "from tensorflow.keras.layers import BatchNormalization\n", + "from tensorflow.keras.layers import MaxPooling2D, AveragePooling2D\n", + "from tensorflow.keras.layers import Concatenate\n", + "from tensorflow.keras.layers import Lambda, Flatten, Dense\n", + "from tensorflow.keras.initializers import glorot_uniform\n", + "from tensorflow.keras.layers import Layer\n", + "from tensorflow.keras import backend as K\n", + "K.set_image_data_format('channels_last')\n", + "import os\n", + "import numpy as np\n", + "from numpy import genfromtxt\n", + "import pandas as pd\n", + "import tensorflow as tf\n", + "import PIL\n", + "\n", + "%matplotlib inline\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Naive Face Verification\n", + "\n", + "In Face Verification, you're given two images and you have to determine if they are of the same person. The simplest way to do this is to compare the two images pixel-by-pixel. If the distance between the raw images is below a chosen threshold, it may be the same person!\n", + "\n", + "\n", + "
Figure 1
\n", + "\n", + "Of course, this algorithm performs poorly, since the pixel values change dramatically due to variations in lighting, orientation of the person's face, minor changes in head position, and so on.\n", + "\n", + "You'll see that rather than using the raw image, you can learn an encoding, $f(img)$.\n", + "\n", + "By using an encoding for each image, an element-wise comparison produces a more accurate judgement as to whether two pictures are of the same person." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Encoding Face Images into a 128-Dimensional Vector\n", + "\n", + "\n", + "### 3.1 - Using a ConvNet to Compute Encodings\n", + "\n", + "The FaceNet model takes a lot of data and a long time to train. So following the common practice in applied deep learning, you'll load weights that someone else has already trained. The network architecture follows the Inception model from [Szegedy *et al*..](https://arxiv.org/abs/1409.4842) An Inception network implementation has been provided for you, and you can find it in the file `inception_blocks_v2.py` to get a closer look at how it is implemented. \n", + "\n", + "*Hot tip:* Go to \"File->Open...\" at the top of this notebook. This opens the file directory that contains the `.py` file).\n", + "\n", + "The key things to be aware of are:\n", + "\n", + "- This network uses 160x160 dimensional RGB images as its input. Specifically, a face image (or batch of $m$ face images) as a tensor of shape $(m, n_H, n_W, n_C) = (m, 160, 160, 3)$\n", + "- The input images are originally of shape 96x96, thus, you need to scale them to 160x160. This is done in the `img_to_encoding()` function.\n", + "- The output is a matrix of shape $(m, 128)$ that encodes each input face image into a 128-dimensional vector\n", + "\n", + "Run the cell below to create the model for face images!" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from tensorflow.keras.models import model_from_json\n", + "\n", + "json_file = open('keras-facenet-h5/model.json', 'r')\n", + "loaded_model_json = json_file.read()\n", + "json_file.close()\n", + "model = model_from_json(loaded_model_json)\n", + "model.load_weights('keras-facenet-h5/model.h5')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now summarize the input and output shapes: " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[]\n", + "[]\n" + ] + } + ], + "source": [ + "print(model.inputs)\n", + "print(model.outputs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By using a 128-neuron fully connected layer as its last layer, the model ensures that the output is an encoding vector of size 128. You then use the encodings to compare two face images as follows:\n", + "\n", + "\n", + "
Figure 2:
By computing the distance between two encodings and thresholding, you can determine if the two pictures represent the same person
\n", + "\n", + "So, an encoding is a good one if:\n", + "\n", + "- The encodings of two images of the same person are quite similar to each other.\n", + "- The encodings of two images of different persons are very different.\n", + "\n", + "The triplet loss function formalizes this, and tries to \"push\" the encodings of two images of the same person (Anchor and Positive) closer together, while \"pulling\" the encodings of two images of different persons (Anchor, Negative) further apart.\n", + " \n", + "
\n", + "
Figure 3:
In the next section, you'll call the pictures from left to right: Anchor (A), Positive (P), Negative (N)
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - The Triplet Loss\n", + "\n", + "**Important Note**: Since you're using a pretrained model, you won't actually need to implement the triplet loss function in this assignment. *However*, the triplet loss is the main ingredient of the face recognition algorithm, and you'll need to know how to use it for training your own FaceNet model, as well as other types of image similarity problems. Therefore, you'll implement it below, for fun and edification. :) \n", + "\n", + "For an image $x$, its encoding is denoted as $f(x)$, where $f$ is the function computed by the neural network.\n", + "\n", + "\n", + "\n", + "Training will use triplets of images $(A, P, N)$:\n", + "\n", + "- A is an \"Anchor\" image--a picture of a person.\n", + "- P is a \"Positive\" image--a picture of the same person as the Anchor image.\n", + "- N is a \"Negative\" image--a picture of a different person than the Anchor image.\n", + "\n", + "These triplets are picked from the training dataset. $(A^{(i)}, P^{(i)}, N^{(i)})$ is used here to denote the $i$-th training example.\n", + "\n", + "You'd like to make sure that an image $A^{(i)}$ of an individual is closer to the Positive $P^{(i)}$ than to the Negative image $N^{(i)}$) by at least a margin $\\alpha$:\n", + "\n", + "$$\n", + "|| f\\left(A^{(i)}\\right)-f\\left(P^{(i)}\\right)||_{2}^{2}+\\alpha<|| f\\left(A^{(i)}\\right)-f\\left(N^{(i)}\\right)||_{2}^{2}\n", + "$$\n", + "\n", + "\n", + "You would thus like to minimize the following \"triplet cost\":\n", + "\n", + "$$\\mathcal{J} = \\sum^{m}_{i=1} \\large[ \\small \\underbrace{\\mid \\mid f(A^{(i)}) - f(P^{(i)}) \\mid \\mid_2^2}_\\text{(1)} - \\underbrace{\\mid \\mid f(A^{(i)}) - f(N^{(i)}) \\mid \\mid_2^2}_\\text{(2)} + \\alpha \\large ] \\small_+ \\tag{3}$$\n", + "Here, the notation \"$[z]_+$\" is used to denote $max(z,0)$.\n", + "\n", + "**Notes**:\n", + "\n", + "- The term (1) is the squared distance between the anchor \"A\" and the positive \"P\" for a given triplet; you want this to be small.\n", + "- The term (2) is the squared distance between the anchor \"A\" and the negative \"N\" for a given triplet, you want this to be relatively large. It has a minus sign preceding it because minimizing the negative of the term is the same as maximizing that term.\n", + "- $\\alpha$ is called the margin. It's a hyperparameter that you pick manually. You'll use $\\alpha = 0.2$.\n", + "\n", + "Most implementations also rescale the encoding vectors to haven L2 norm equal to one (i.e., $\\mid \\mid f(img)\\mid \\mid_2$=1); you won't have to worry about that in this assignment.\n", + "\n", + "\n", + "### Exercise 1 - triplet_loss\n", + "\n", + "Implement the triplet loss as defined by formula (3). These are the 4 steps:\n", + "\n", + "1. Compute the distance between the encodings of \"anchor\" and \"positive\": $\\mid \\mid f(A^{(i)}) - f(P^{(i)}) \\mid \\mid_2^2$\n", + "2. Compute the distance between the encodings of \"anchor\" and \"negative\": $\\mid \\mid f(A^{(i)}) - f(N^{(i)}) \\mid \\mid_2^2$\n", + "3. Compute the formula per training example: $ \\mid \\mid f(A^{(i)}) - f(P^{(i)}) \\mid \\mid_2^2 - \\mid \\mid f(A^{(i)}) - f(N^{(i)}) \\mid \\mid_2^2 + \\alpha$\n", + "4. Compute the full formula by taking the max with zero and summing over the training examples:$$\\mathcal{J} = \\sum^{m}_{i=1} \\large[ \\small \\mid \\mid f(A^{(i)}) - f(P^{(i)}) \\mid \\mid_2^2 - \\mid \\mid f(A^{(i)}) - f(N^{(i)}) \\mid \\mid_2^2+ \\alpha \\large ] \\small_+ \\tag{3}$$\n", + "\n", + "*Hints*:\n", + "\n", + "- Useful functions: `tf.reduce_sum()`, `tf.square()`, `tf.subtract()`, `tf.add()`, `tf.maximum()`.\n", + "\n", + "- For steps 1 and 2, sum over the entries of $\\mid \\mid f(A^{(i)}) - f(P^{(i)}) \\mid \\mid_2^2$ and $\\mid \\mid f(A^{(i)}) - f(N^{(i)}) \\mid \\mid_2^2$.\n", + "\n", + "- For step 4, you will sum over the training examples.\n", + "\n", + "*Additional Hints*:\n", + "\n", + "- Recall that the square of the L2 norm is the sum of the squared differences: $||x - y||_{2}^{2} = \\sum_{i=1}^{N}(x_{i} - y_{i})^{2}$\n", + "\n", + "- Note that the anchor, positive and negative encodings are of shape (*m*,128), where *m* is the number of training examples and 128 is the number of elements used to encode a single example.\n", + "\n", + "- For steps 1 and 2, maintain the number of *m* training examples and sum along the 128 values of each encoding. `tf.reduce_sum` has an axis parameter. This chooses along which axis the sums are applied.\n", + "\n", + "- Note that one way to choose the last axis in a tensor is to use negative indexing (axis=-1).\n", + "\n", + "- In step 4, when summing over training examples, the result will be a single scalar value.\n", + "\n", + "- For `tf.reduce_sum` to sum across all axes, keep the default value axis=None." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-f05732f7068382cb", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1(UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: triplet_loss\n", + "\n", + "def triplet_loss(y_true, y_pred, alpha = 0.2):\n", + " \"\"\"\n", + " Implementation of the triplet loss as defined by formula (3)\n", + " \n", + " Arguments:\n", + " y_true -- true labels, required when you define a loss in Keras, you don't need it in this function.\n", + " y_pred -- python list containing three objects:\n", + " anchor -- the encodings for the anchor images, of shape (None, 128)\n", + " positive -- the encodings for the positive images, of shape (None, 128)\n", + " negative -- the encodings for the negative images, of shape (None, 128)\n", + " \n", + " Returns:\n", + " loss -- real number, value of the loss\n", + " \"\"\"\n", + " \n", + " anchor, positive, negative = y_pred[0], y_pred[1], y_pred[2]\n", + " # YOUR CODE STARTS HERE (β‰ˆ 4 lines)\n", + " # Step 1: Compute the (encoding) distance between the anchor and the positive\n", + " pos_dist = tf.reduce_sum(tf.square(tf.subtract(anchor,positive)),axis=-1)\n", + " # Step 2: Compute the (encoding) distance between the anchor and the negative\n", + " neg_dist = tf.reduce_sum(tf.square(tf.subtract(anchor,negative)),axis=-1)\n", + " # Step 3: subtract the two previous distances and add alpha.\n", + " basic_loss = tf.maximum(tf.add(tf.subtract(pos_dist,neg_dist),alpha),0)\n", + " # Step 4: Take the maximum of basic_loss and 0.0. Sum over the training examples.\n", + " loss = tf.reduce_sum(basic_loss)\n", + " ### END CODE HERE\n", + " \n", + " return loss" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "grade": true, + "grade_id": "cell-440ff81e6bcda96a", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loss = tf.Tensor(527.2598, shape=(), dtype=float32)\n" + ] + } + ], + "source": [ + "### YOU CANNOT EDIT THIS CELL\n", + "\n", + "# BEGIN UNIT TEST\n", + "tf.random.set_seed(1)\n", + "y_true = (None, None, None) # It is not used\n", + "y_pred = (tf.keras.backend.random_normal([3, 128], mean=6, stddev=0.1, seed = 1),\n", + " tf.keras.backend.random_normal([3, 128], mean=1, stddev=1, seed = 1),\n", + " tf.keras.backend.random_normal([3, 128], mean=3, stddev=4, seed = 1))\n", + "loss = triplet_loss(y_true, y_pred)\n", + "\n", + "assert type(loss) == tf.python.framework.ops.EagerTensor, \"Use tensorflow functions\"\n", + "print(\"loss = \" + str(loss))\n", + "\n", + "y_pred_perfect = ([1., 1.], [1., 1.], [1., 1.,])\n", + "loss = triplet_loss(y_true, y_pred_perfect, 5)\n", + "assert loss == 5, \"Wrong value. Did you add the alpha to basic_loss?\"\n", + "y_pred_perfect = ([1., 1.],[1., 1.], [0., 0.,])\n", + "loss = triplet_loss(y_true, y_pred_perfect, 3)\n", + "assert loss == 1., \"Wrong value. Check that pos_dist = 0 and neg_dist = 2 in this example\"\n", + "y_pred_perfect = ([1., 1.],[0., 0.], [1., 1.,])\n", + "loss = triplet_loss(y_true, y_pred_perfect, 0)\n", + "assert loss == 2., \"Wrong value. Check that pos_dist = 2 and neg_dist = 0 in this example\"\n", + "y_pred_perfect = ([0., 0.],[0., 0.], [0., 0.,])\n", + "loss = triplet_loss(y_true, y_pred_perfect, -2)\n", + "assert loss == 0, \"Wrong value. Are you taking the maximum between basic_loss and 0?\"\n", + "y_pred_perfect = ([[1., 0.], [1., 0.]],[[1., 0.], [1., 0.]], [[0., 1.], [0., 1.]])\n", + "loss = triplet_loss(y_true, y_pred_perfect, 3)\n", + "assert loss == 2., \"Wrong value. Are you applying tf.reduce_sum to get the loss?\"\n", + "y_pred_perfect = ([[1., 1.], [2., 0.]], [[0., 3.], [1., 1.]], [[1., 0.], [0., 1.,]])\n", + "loss = triplet_loss(y_true, y_pred_perfect, 1)\n", + "if (loss == 4.):\n", + " raise Exception('Perhaps you are not using axis=-1 in reduce_sum?')\n", + "assert loss == 5, \"Wrong value. Check your implementation\"\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " loss:\n", + " \n", + " tf.Tensor(527.2598, shape=(), dtype=float32)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 4 - Loading the Pre-trained Model\n", + "\n", + "FaceNet is trained by minimizing the triplet loss. But since training requires a lot of data and a lot of computation, you won't train it from scratch here. Instead, you'll load a previously trained model in the following cell; which might take a couple of minutes to run." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-953bcab8e9bbba10", + "locked": true, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [], + "source": [ + "FRmodel = model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here are some examples of distances between the encodings between three individuals:\n", + "\n", + "
\n", + "
Figure 4:
Example of distance outputs between three individuals' encodings
\n", + "\n", + "Now use this model to perform face verification and face recognition!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 5 - Applying the Model\n", + "\n", + "You're building a system for an office building where the building manager would like to offer facial recognition to allow the employees to enter the building.\n", + "\n", + "You'd like to build a face verification system that gives access to a list of people. To be admitted, each person has to swipe an identification card at the entrance. The face recognition system then verifies that they are who they claim to be.\n", + "\n", + "\n", + "### 5.1 - Face Verification\n", + "\n", + "Now you'll build a database containing one encoding vector for each person who is allowed to enter the office. To generate the encoding, you'll use `img_to_encoding(image_path, model)`, which runs the forward propagation of the model on the specified image.\n", + "\n", + "Run the following code to build the database (represented as a Python dictionary). This database maps each person's name to a 128-dimensional encoding of their face." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "#tf.keras.backend.set_image_data_format('channels_last')\n", + "def img_to_encoding(image_path, model):\n", + " img = tf.keras.preprocessing.image.load_img(image_path, target_size=(160, 160))\n", + " img = np.around(np.array(img) / 255.0, decimals=12)\n", + " x_train = np.expand_dims(img, axis=0)\n", + " embedding = model.predict_on_batch(x_train)\n", + " return embedding / np.linalg.norm(embedding, ord=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "database = {}\n", + "database[\"danielle\"] = img_to_encoding(\"images/danielle.png\", FRmodel)\n", + "database[\"younes\"] = img_to_encoding(\"images/younes.jpg\", FRmodel)\n", + "database[\"tian\"] = img_to_encoding(\"images/tian.jpg\", FRmodel)\n", + "database[\"andrew\"] = img_to_encoding(\"images/andrew.jpg\", FRmodel)\n", + "database[\"kian\"] = img_to_encoding(\"images/kian.jpg\", FRmodel)\n", + "database[\"dan\"] = img_to_encoding(\"images/dan.jpg\", FRmodel)\n", + "database[\"sebastiano\"] = img_to_encoding(\"images/sebastiano.jpg\", FRmodel)\n", + "database[\"bertrand\"] = img_to_encoding(\"images/bertrand.jpg\", FRmodel)\n", + "database[\"kevin\"] = img_to_encoding(\"images/kevin.jpg\", FRmodel)\n", + "database[\"felix\"] = img_to_encoding(\"images/felix.jpg\", FRmodel)\n", + "database[\"benoit\"] = img_to_encoding(\"images/benoit.jpg\", FRmodel)\n", + "database[\"arnaud\"] = img_to_encoding(\"images/arnaud.jpg\", FRmodel)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load the images of Danielle and Kian: " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "danielle = tf.keras.preprocessing.image.load_img(\"images/danielle.png\", target_size=(160, 160))\n", + "kian = tf.keras.preprocessing.image.load_img(\"images/kian.jpg\", target_size=(160, 160))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(160, 160, 3)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.around(np.array(kian) / 255.0, decimals=12).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "danielle" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, when someone shows up at your front door and swipes their ID card (thus giving you their name), you can look up their encoding in the database, and use it to check if the person standing at the front door matches the name on the ID.\n", + "\n", + "\n", + "### Exercise 2 - verify\n", + "\n", + "Implement the `verify()` function, which checks if the front-door camera picture (`image_path`) is actually the person called \"identity\". You will have to go through the following steps:\n", + "\n", + "- Compute the encoding of the image from `image_path`.\n", + "- Compute the distance between this encoding and the encoding of the identity image stored in the database.\n", + "- Open the door if the distance is less than 0.7, else do not open it.\n", + "\n", + "As presented above, you should use the L2 distance `np.linalg.norm`.\n", + "\n", + "**Note**: In this implementation, compare the L2 distance, not the square of the L2 distance, to the threshold 0.7.\n", + "\n", + "*Hints*:\n", + "\n", + "- `identity` is a string that is also a key in the database dictionary.\n", + "- `img_to_encoding` has two parameters: the image_path and model." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-ba2f317e79e15a2f", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2(UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: verify\n", + "\n", + "def verify(image_path, identity, database, model):\n", + " \"\"\"\n", + " Function that verifies if the person on the \"image_path\" image is \"identity\".\n", + " \n", + " Arguments:\n", + " image_path -- path to an image\n", + " identity -- string, name of the person you'd like to verify the identity. Has to be an employee who works in the office.\n", + " database -- python dictionary mapping names of allowed people's names (strings) to their encodings (vectors).\n", + " model -- your Inception model instance in Keras\n", + " \n", + " Returns:\n", + " dist -- distance between the image_path and the image of \"identity\" in the database.\n", + " door_open -- True, if the door should open. False otherwise.\n", + " \"\"\"\n", + " ### START CODE HERE\n", + " #Step 1: Compute the encoding for the image. Use img_to_encoding() see example above. (β‰ˆ 1 line)\n", + " encoding = img_to_encoding(image_path,model)\n", + " # Step 2: Compute distance with identity's image (β‰ˆ 1 line)\n", + " dist = np.linalg.norm(encoding - database[identity])\n", + " # Step 3: Open the door if dist < 0.7, else don't open (β‰ˆ 3 lines)\n", + " if dist < 0.7:\n", + " print(\"It's \" + str(identity) + \", welcome in!\")\n", + " door_open = True\n", + " else:\n", + " print(\"It's not \" + str(identity) + \", please go away\")\n", + " door_open = False\n", + " ### END CODE HERE \n", + " return dist, door_open" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Younes is trying to enter the office and the camera takes a picture of him (\"images/camera_0.jpg\"). Let's run your verification algorithm on this picture:\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "grade": true, + "grade_id": "cell-014d077254ad7d52", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "It's younes, welcome in!\n", + "( 0.5992949 , True )\n" + ] + } + ], + "source": [ + "### YOU CANNOT EDIT THIS CELL\n", + "\n", + "# BEGIN UNIT TEST\n", + "distance, door_open_flag = verify(\"images/camera_0.jpg\", \"younes\", database, FRmodel)\n", + "assert np.isclose(distance, 0.5992949), \"Distance not as expected\"\n", + "assert isinstance(door_open_flag, bool), \"Door open flag should be a boolean\"\n", + "print(\"(\", distance, \",\", door_open_flag, \")\")\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " It's younes, welcome in!\n", + " \n", + " (0.5992949, True)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Benoit, who does not work in the office, stole Kian's ID card and tried to enter the office. Naughty Benoit! The camera took a picture of Benoit (\"images/camera_2.jpg). \n", + "\n", + "\n", + "\n", + "Run the verification algorithm to check if Benoit can enter." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "deletable": false, + "editable": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "It's not kian, please go away\n" + ] + }, + { + "data": { + "text/plain": [ + "(1.0259346, False)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "### YOU CANNOT EDIT THIS CELL\n", + "\n", + "verify(\"images/camera_2.jpg\", \"kian\", database, FRmodel)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " It's not kian, please go away\n", + " \n", + " (1.0259346, False)\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 5.2 - Face Recognition\n", + "\n", + "Your face verification system is mostly working. But since Kian got his ID card stolen, when he came back to the office the next day he couldn't get in!\n", + "\n", + "To solve this, you'd like to change your face verification system to a face recognition system. This way, no one has to carry an ID card anymore. An authorized person can just walk up to the building, and the door will unlock for them!\n", + "\n", + "You'll implement a face recognition system that takes as input an image, and figures out if it is one of the authorized persons (and if so, who). Unlike the previous face verification system, you will no longer get a person's name as one of the inputs.\n", + "\n", + "\n", + "### Exercise 3 - who_is_it\n", + "\n", + "Implement `who_is_it()` with the following steps:\n", + "\n", + "- Compute the target encoding of the image from `image_path`\n", + "- Find the encoding from the database that has smallest distance with the target encoding.\n", + "- Initialize the `min_dist` variable to a large enough number (100). This helps you keep track of the closest encoding to the input's encoding.\n", + "- Loop over the database dictionary's names and encodings. To loop use for (name, db_enc) in `database.items()`.\n", + "- Compute the L2 distance between the target \"encoding\" and the current \"encoding\" from the database. If this distance is less than the min_dist, then set min_dist to dist, and identity to name." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-a04ff2b5fd1186f8", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C3(UNIQUE CELL IDENTIFIER, DO NOT EDIT)\n", + "# GRADED FUNCTION: who_is_it\n", + "\n", + "def who_is_it(image_path, database, model):\n", + " \"\"\"\n", + " Implements face recognition for the office by finding who is the person on the image_path image.\n", + " \n", + " Arguments:\n", + " image_path -- path to an image\n", + " database -- database containing image encodings along with the name of the person on the image\n", + " model -- your Inception model instance in Keras\n", + " \n", + " Returns:\n", + " min_dist -- the minimum distance between image_path encoding and the encodings from the database\n", + " identity -- string, the name prediction for the person on image_path\n", + " \"\"\"\n", + " \n", + " ### START CODE HERE\n", + "\n", + " ## Step 1: Compute the target \"encoding\" for the image. Use img_to_encoding() see example above. ## (β‰ˆ 1 line)\n", + " encoding = img_to_encoding(image_path,model)\n", + " \n", + " ## Step 2: Find the closest encoding ##\n", + " # Initialize \"min_dist\" to a large value, say 100 (β‰ˆ1 line)\n", + " min_dist = 100\n", + " \n", + " #Loop over the database dictionary's names and encodings.\n", + " for (name, db_enc) in database.items():\n", + " \n", + " # Compute L2 distance between the target \"encoding\" and the current db_enc from the database. (β‰ˆ 1 line)\n", + " dist = np.linalg.norm(encoding - db_enc)\n", + "\n", + " # If this distance is less than the min_dist, then set min_dist to dist, and identity to name. (β‰ˆ 3 lines)\n", + " if dist < min_dist:\n", + " min_dist = dist\n", + " identity = name\n", + " ### END CODE HERE\n", + " \n", + " if min_dist > 0.7:\n", + " print(\"Not in the database.\")\n", + " else:\n", + " print (\"it's \" + str(identity) + \", the distance is \" + str(min_dist))\n", + " \n", + " return min_dist, identity" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Younes is at the front door and the camera takes a picture of him (\"images/camera_0.jpg\"). Let's see if your `who_it_is()` algorithm identifies Younes." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "deletable": false, + "editable": false, + "nbgrader": { + "grade": true, + "grade_id": "cell-9c88c8ab87677503", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "it's younes, the distance is 0.5992949\n", + "it's younes, the distance is 0.5992949\n", + "it's younes, the distance is 0.0\n" + ] + } + ], + "source": [ + "### YOU CANNOT EDIT THIS CELL\n", + "\n", + "# BEGIN UNIT TEST\n", + "# Test 1 with Younes pictures \n", + "who_is_it(\"images/camera_0.jpg\", database, FRmodel)\n", + "\n", + "# Test 2 with Younes pictures \n", + "test1 = who_is_it(\"images/camera_0.jpg\", database, FRmodel)\n", + "assert np.isclose(test1[0], 0.5992946)\n", + "assert test1[1] == 'younes'\n", + "\n", + "# Test 3 with Younes pictures \n", + "test2 = who_is_it(\"images/younes.jpg\", database, FRmodel)\n", + "assert np.isclose(test2[0], 0.0)\n", + "assert test2[1] == 'younes'\n", + "# END UNIT TEST" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + "
\n", + " it's younes, the distance is 0.5992949
\n", + " it's younes, the distance is 0.5992949
\n", + " it's younes, the distance is 0.0
\n", + "
\n", + "\n", + "You can change \"camera_0.jpg\" (picture of Younes) to \"camera_1.jpg\" (picture of Bertrand) and see the result." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations**! \n", + "You've completed this assignment, and your face recognition system is working well! It not only lets in authorized persons, but now people don't need to carry an ID card around anymore!\n", + "\n", + "You've now seen how a state-of-the-art face recognition system works, and can describe the difference between face recognition and face verification. Here's a quick recap of what you've accomplished: \n", + "\n", + "- Posed face recognition as a binary classification problem\n", + "- Implemented one-shot learning for a face recognition problem\n", + "- Applied the triplet loss function to learn a network's parameters in the context of face recognition\n", + "- Mapped face images into 128-dimensional encodings using a pretrained model\n", + "- Performed face verification and face recognition with these encodings\n", + "\n", + "Great work! " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + " \n", + "**What you should remember**:\n", + "\n", + "- Face verification solves an easier 1:1 matching problem; face recognition addresses a harder 1:K matching problem.\n", + " \n", + "- Triplet loss is an effective loss function for training a neural network to learn an encoding of a face image.\n", + " \n", + "- The same encoding can be used for verification and recognition. Measuring distances between two images' encodings allows you to determine whether they are pictures of the same person." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Ways to improve your facial recognition model**:\n", + "\n", + "Although you won't implement these here, here are some ways to further improve the algorithm:\n", + "\n", + "- Put more images of each person (under different lighting conditions, taken on different days, etc.) into the database. Then, given a new image, compare the new face to multiple pictures of the person. This would increase accuracy.\n", + "\n", + "- Crop the images to contain just the face, and less of the \"border\" region around the face. This preprocessing removes some of the irrelevant pixels around the face, and also makes the algorithm more robust." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 6 - References\n", + "1. Florian Schroff, Dmitry Kalenichenko, James Philbin (2015). [FaceNet: A Unified Embedding for Face Recognition and Clustering](https://arxiv.org/pdf/1503.03832.pdf)\n", + "\n", + "2. Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf (2014). [DeepFace: Closing the gap to human-level performance in face verification](https://research.fb.com/wp-content/uploads/2016/11/deepface-closing-the-gap-to-human-level-performance-in-face-verification.pdf)\n", + "\n", + "3. This implementation also took a lot of inspiration from the official FaceNet github repository: https://github.com/davidsandberg/facenet\n", + "\n", + "4. Further inspiration was found here: https://machinelearningmastery.com/how-to-develop-a-face-recognition-system-using-facenet-in-keras-and-an-svm-classifier/\n", + "\n", + "5. And here: https://github.com/nyoki-mtl/keras-facenet/blob/master/notebook/tf_to_keras.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Image_segmentation_Unet_v2.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Image_segmentation_Unet_v2.ipynb new file mode 100644 index 00000000000..642218e4e05 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Image_segmentation_Unet_v2.ipynb @@ -0,0 +1,1311 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Q3NVDfXY4__X" + }, + "source": [ + "# Image Segmentation with U-Net\n", + "\n", + "Welcome to the final assignment of Week 3! You'll be building your own U-Net, a type of CNN designed for quick, precise image segmentation, and using it to predict a label for every single pixel in an image - in this case, an image from a self-driving car dataset. \n", + "\n", + "This type of image classification is called semantic image segmentation. It's similar to object detection in that both ask the question: \"What objects are in this image and where in the image are those objects located?,\" but where object detection labels objects with bounding boxes that may include pixels that aren't part of the object, semantic image segmentation allows you to predict a precise mask for each object in the image by labeling each pixel in the image with its corresponding class. The word β€œsemantic” here refers to what's being shown, so for example the β€œCar” class is indicated below by the dark blue mask, and \"Person\" is indicated with a red mask:\n", + "\n", + "\n", + "
Figure 1: Example of a segmented image
\n", + "\n", + "As you might imagine, region-specific labeling is a pretty crucial consideration for self-driving cars, which require a pixel-perfect understanding of their environment so they can change lanes and avoid other cars, or any number of traffic obstacles that can put peoples' lives in danger. \n", + "\n", + "By the time you finish this notebook, you'll be able to: \n", + "\n", + "* Build your own U-Net\n", + "* Explain the difference between a regular CNN and a U-net\n", + "* Implement semantic image segmentation on the CARLA self-driving car dataset\n", + "* Apply sparse categorical crossentropy for pixelwise prediction\n", + "\n", + "Onward, to this grand and glorious quest!\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Content\n", + "\n", + "- [1 - Packages](#1)\n", + "- [2 - Load and Split the Data](#2)\n", + " - [2.1 - Split Your Dataset into Unmasked and Masked Images](#2-1)\n", + " - [2.2 - Preprocess Your Data](#2-2)\n", + "- [3 - U-Net](#3)\n", + " - [3.1 - Model Details](#3-1)\n", + " - [3.2 - Encoder (Downsampling Block)](#3-2)\n", + " - [Exercise 1 - conv_block](#ex-1)\n", + " - [3.3 - Decoder (Upsampling Block)](#3-3)\n", + " - [Exercise 2 - upsampling_block](#ex-2)\n", + " - [3.4 - Build the Model](#3-4)\n", + " - [Exercise 3 - unet_model](#ex-3)\n", + " - [3.5 - Set Model Dimensions](#3-5)\n", + " - [3.6 - Loss Function](#3-6)\n", + " - [3.7 - Dataset Handling](#3-7)\n", + "- [4 - Train the Model](#4)\n", + " - [4.1 - Create Predicted Masks](#4-1)\n", + " - [4.2 - Plot Model Accuracy](#4-2)\n", + " - [4.3 - Show Predictions](#4-3)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "F57bqletV992" + }, + "source": [ + "\n", + "## 1 - Packages\n", + "\n", + "Run the cell below to import all the libraries you'll need:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "0exJ9KsDrwck" + }, + "outputs": [], + "source": [ + "import tensorflow as tf\n", + "import numpy as np\n", + "\n", + "from tensorflow.keras.layers import Input\n", + "from tensorflow.keras.layers import Conv2D\n", + "from tensorflow.keras.layers import MaxPooling2D\n", + "from tensorflow.keras.layers import Dropout \n", + "from tensorflow.keras.layers import Conv2DTranspose\n", + "from tensorflow.keras.layers import concatenate\n", + "\n", + "from test_utils import summary, comparator" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Load and Split the Data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "FWpkuq4tfU4i" + }, + "outputs": [], + "source": [ + "import os\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "import imageio\n", + "\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "path = ''\n", + "image_path = os.path.join(path, './data/CameraRGB/')\n", + "mask_path = os.path.join(path, './data/CameraMask/')\n", + "image_list = os.listdir(image_path)\n", + "mask_list = os.listdir(mask_path)\n", + "image_list = [image_path+i for i in image_list]\n", + "mask_list = [mask_path+i for i in mask_list]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Check out the some of the unmasked and masked images from the dataset:\n", + "\n", + "After you are done exploring, revert back to `N=2`. Otherwise the autograder will throw a `list index out of range` error." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 347 + }, + "id": "RZhnXflBl6Xm", + "outputId": "dcdd7563-53b9-4ce3-f400-e011f4df9cdc" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Segmentation')" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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iuSkfEh5eT3JtKOvZ9hXpvgm/YYb+cRzjdO/q8yLHydjqc4nTvJp3VZUqVapUOX3yusTUMPOPAPiRl30dYFCZebua97NHJBxkQHMBItNFKwB9eIm7BDwssBUdSmAXSI7O7CYSFPADyFFCQ20D9JwTgNBmvsCJIxcST0yAIw5MbDwPQ4jpiCI74hV9EFTCJ2ITjo2XBDGzgSFvBAXBVC5PyTwbK2jnkFHEopyftjPL2SUKzLNB5pKsGdKbxQ/kpKS8TRzpMVmWl+Aem96susdIIfegkBnTgQUMK2FbEQq9ubwk2seeIjtKyK7j7N5RW5T3u9wzweNYNJpKiL5DsquXaJ8CeOfkzWidehiSd0Suj55MiScpn0W1oNrHxvqk5ykRXYJMRrjyvtGzqR0PJBIvnhZGeKZdui9DX0bOpaVqFAmJ2C48/nFp6AoWrISGMi+RO+FBzW65+FCUP4lBN5/sNJiLMERG7W3vR71/RL/PNXml76oqVapUqXL65DOWKKAUC2oTMErnLLBCWo6lL2qXAS4FVnJgSHDk5c6mkbCaS+Ji1EsjIEZmk5v4OQAZj96H2BdHhD4GE8tsrzYZ1rPJIhkgzPxaQiKEYzUAQVr608isMARIcZy5ldJyYVAiLRlKs9wn2z+dNuB3VfyPkgEDNjPr5+OR4eHSS0ZYuTJO28g1Heif2ZmMBjkpocFFlC0XswSNCsKgiQWsnkWNZgwygMhKCOzMfipSDErgh9pYMTK5dbnQwcbRZByl1CvvD+XuTG0/63PZX04rIOWsEJeGnJKaqEzmFYj3aAqShz5fYgOh1izeLDblzB2r95eOd+7xsWOVD6L1mA68HLGNxrlIzij9HqjHhNNf9dBQvIfCZ9GlIY3JEXOrh7W0s+qRe4kZwl19ImGclpzJcrN0zztLrKU++4Q4c6xKlSpVqlS5e+XUkJoMiIMSVit9CkJExMuRMgVxmovOAKqdpSybC9cZkG1AUJj9VCiQAFdkS0JuAAfvQrBu7xm9Iyx7RpfpYUF8QDSirWBnJg2S95baGfWTZhQ8RwHUEDwTKBEbrGhLr1tlCAZrpMyAUZIqmerFiqVlOfFhA7ZPIlLDCsuaKOMVxZcsOVdJqQbdLcC3ZUwyRsnToQOdtUXmwnIJF5CTtRJkp3Ji5BX2UH5I2cFVvMI8Ktpc8sBFHUkSHBgCYPSmQSXWvkooUvmkvxyS5yNc5+IzkYLfEZZqZUAb6hWwQfJkngkZAo4fJPRKtCLE5xaSVVDu9XBMYuAo6WgJkD4PGpCfmzfR4vicp3ggpxkShVQkD00aBKk7SCI0cZmZfZL0KdckDTq4uoVYmoCJJz00s5lHngGuJMs2Vkv7KseUNN35Aa1SpUqVKlVOv5weUpPAN+WgzpCbcpbVwA/zTnZZOZ2TNLOVGUui9MbX17+KhwKZ0nMCmXlFMGTvGUsfsyTFVLChDqNSmtpWCJd5jQhp2QuZdpRPRUtwAIMKrCikc40zt1l/C0mxO1EXsiVLJmAQkmBesiTEeDQMJF3ZamYGBOJTtqkxEzCDpkzrTntuZNzopJlnOw5SryUoq3RJ5YsOFETOuj4KB0osTmmMbRax1FZZ53Ct2Ilt5CQzz8Bnl6xRZlyrO9KStXRusEwxXwqoE/5K8luztCoQHMA+k2kJlhAap56adA+ZrAp6n4jRhOGIRzWfNsi8qqp2RtXAAJFL5MqWs7VJTFAiNPGe8V7uDdu6ud+iHbVv+sxm5pThTbePIYD56CTGInE/DKSU1jnPlKWE+ZIyKirM7EGqS6U2VapUqVLlbpVTQ2oy0FUA6wGwTDPR+i2Pf8hJkeBHO3me6l7VlgFZBCUlxCH9q53rZei6+JCiluGI4yy0Ehs2081l2t6MFlgWZvQTgGKX6nghJC5APOclvWsgOLkYUgJjxxIzG71yAmLMP2Q/d3KoZO1nELkkULYxcyhPfRD/LSoLJM8CvEK/RJYsuSLkc/cC5of6aappax1tkAub6FjGkS2zwJGZzy+4i91XJJUyD0jG9ayCtpgqFWO/hCGgEJuYQLW3uhvLqP6A1ucYDeJ+L04JS/ksAZI0QAPlS84mWcKiIdJ9Z5f2iXetnCdI6qzojz5jADlky8DsLZeIvpAZQpbhLHiIJZqF7IWQ54mgCQBKLqzkgTISQeafnJ+SmCLrs8T+ZOOQLtG6h79vnH4/YM+bRB1VqlSpUqXK3SinhtQAA9iae2yiyGtZSICZLFaAYAGjXmg+5BDN7MyRt0TIXvKekZarZeAOCg7aJoIZx2g8wfWMjjkkD4DMLw8VSyB1wCCibUj6HkERAU1cdiZ2Ixe+9xwu8N6n8oURCmLCOZAS8jOcfE4Xa3lWj0u6UD4jkskIzrNKlMCVAc5MpYUKlmQ6lWFvKMDNGVlug4xAAhqHkrNNbS51i80xBbHpkkxFQcvSd1NX0kTrUNBbAOGiH9JH6ZP032a/K0yUK1bYIdnGNKbXio0pz4iX+qiB/0JmwkaWuQlFj5Q9zElyAFORdj/d00TqubGkIssulryNoSNCVGSpV/6bEAkH5Rte2oQSkkZb9q9pnYOLjiZJBEDyjHLcFFe6kIiExr+kDIzQPavkd0XjtmIdiXirzuUvIAMm3bReZ+NppI6MMKX6lMxQNgBl6SpVqlSpUuXuklNDaobrug3Yp/KYfQFzkQegmIE0Z/TVrevVbRkPNp4Q0SsPMRbYaGeGbSwEAXAOGDHBE+DIw3nC0odlK16oGBfNRyQpoN5nM8C5/qFNSst4OIHAAMwdOGwISi4SnCIVsGlYgW1gFxTBUZlxLG3zySXsETCVdSTUnZGBkimYuCnDprRkQWLsRzMgOYDjATC0VWUWZUoxJ+nkKjxX8qn43WX0lPPz9pJoEtkQcuUYWJvalH7loMkAxA7b/XmszRLRs/0lsW553KB9264pm8qlPnI6LskAwvIzG3eiJFYAfduEpAHyrCdIX3IuQtqPiWJ78swxci8FmX9CO+olSkvRCjPmsTyA7OEjlEA8TrIPDcBmCWmui8TUhGffJjpIET9mSdww+1saM8nAJj0pOEZMrphtrin7VSmhcsj2GDLemJj6RImSaULj34bEtUqVKlWqVLlb5JSQGhtHQ+mPmXe0ZwqQSubzqk0YS5hM2QtdEIHM0HpwDMIP5ERgr53ZZG1poEdSkSJ1cmEvEkeEjgSQoFwhl32XZWXZRp5QICVg0EM38AsZkFiJTUNwHJakhWQCJajV2WnD4OI5B5n5TkSjAOQlsUm1WjC9esCgbCQ/L2Ht4t2wFeV7shtDmJnuVameM+9DYAKIRROsJsnNXV6l/CH2zRA4Q3YzZD6ox254aXXNuqflU98JK1Msm+VIqzahTc3YOge2K8ArWZ0okQ5baxbLJOQdwKhxGgyPfHmkxJIQ6V41CdBLddmyPLVB6AKnTWaZw6RA74Wgu7gsjZNZstTQQALwdmJCyEXyLRaPQcrY1oTsbRLDUhLXRDLsmCSr6WSBTdlMUSGO97jxM8swZEvHkOrShAhC6Fj/0Q0547OfbrdyLAqCp/MmKwh0lSpVqlSpcpfJqSA1slxEwEACVWYZVsLd8g9ruSwTFVkQtwL4lZORaTZZSRXH42l5B4X0yY1eVChTTuhT9qdJM7VsMpZpSl0BWaJ3mIUlkEdGRnSG2IXyMmNNmkEqEBBOoNdRzMqWwJkSFQCy5Y01SGwrQX6k5TlA4ZXJRQKUV5zIbM2RxeVbJgrmp8KucSwTWCsHMNud1daWOqjfOBIkaStC5xUqD4lBujszveSGNVQkHU+lCYmspUxzhvCx0cWm201jleJh4k1vlmMNe6z3o7ZgD6gNrKKWx7BRQe7LcnGmI8kKVnpEKKY8D9QYkWyEZWeGTEA9I/bZthRKAvJ7IRAcNcnSXVPSR+dFVFeXWIXEkkifcpEldIHQmA0x4/Ohz17QpY/62FutdHqJxyX7fUvPs/xGcdLfdCDrhoyB1SHUS2gyN/XqBAF2bLSk/qagsGmVKlWqVKlyN8qpIDWAbmopL+GAFS2QKmYwycxwkgVxBAXkcsTUkgHVPPsW2WPxei/6xVnZiE3yekgXtFnsTdC8T44AaoLHBJwH85dkiEFhVtppyta07C0imtSmAVIpvTURvFfgBEdhMtaQP4bss8PwBsELvi7g1SoOMwCGueVoZbm8vnIHHB5cM4xzSWjb6CvAWMmc4QmZfROhyVgLY8Bs7Cm5Ms3Ix7ukWIuXOVbI9DWjRHI0gspUrYO1W4KcqW+kShk9pKNShAd9tjrEksyZTYZjW/RrRW2yREuXcomXJt9Y0i5Ls04aTp1XohEOxaxmLDaTjF+a0ACgbH8hoiHpknYzbyEbu8qfqGfjgFETlps18cEKm2pqxjHPHCcIOBGs0nbFT1byvMD8vikxNVpHG1gSku7x1L7aLvP+kR0jqSNfbpb/7oXniomzDHbDeL8qVapUqVLl7pFTQ2qUsJh/MyAbX9cFSLWfMpAdAUvCPive1jS8KrVrd0q35IaY0lIsKq6xc+xywmqYYKkjNMxo4rKwXOkgnkJb3nMgNyw6GDRviIF4ktIyIEfoQSDPqV1PeTth9QoFTwDr8SGysYjI+iv86mKSdSupWABOs6wujTNruXSd4R053dGDep/ILL49bkaEM5Ol4wLw8o16THdTayZovSAXtvJVJE2WlFHWl1C4JNlqI1PRCnae9E73gBB8A9hN2eSRNHbOrGrKq8PAUACjq4MhNE7TNwuIliWR4ZymcA58SpjFCsCdQHtYdpbIg/VqxodTNr/Nl8oFS9i9bzJDGJIgdmuirhI/I54dIQ+irveMzgOdB3pvnnXpA2C8JJzInSVsmZiBJ9JrJXlB0pejPYwtbJcpi+6i1N5wGZuYWO1BIN2H6CQ9q1SpUqVKlbtETg2pAWxcTZyLLN6xdm49m4HNSggWyJeYZLObUoFO/SYQnFebowJGWIZGkUWQ2YeC85oyxpMAulU8AsEGMiudz9I7DuDfE4F88OpI8LRUZTBt1scAzBiOgS4gyfifKhWAHaOBmTlfQfKMWTPiFr6u3hOo/JxzKUXHtrXBnivpQumVWVRYgPwse13sF9sCK+BaqqJQ1Dpfhvhfdc83tNT7pKBvcUmethoyia3Qn/O28gxwJavRGfbBfSeb0JLSNm2eMwXzlNJKYNRrQtkzIfea9cRke84kMmMIDwLBlrHW5VdKgsSiPp7vY+xM7w2Rp3APBB1cIJcm34cQHAfVSxQO2dTZmJHSH0eEpiE0jVOvCmudnoMunVcvTbq3iFMWt9wrEn7LxJOqdi1/w9QzI/YK9YRSzEgbbXpzjRUy45VNtBhClRGZlOab0/fqoalSpUqVKp8NcnpIjQH7OfmQP5SBr3Qs4TwlRQGMskn9esIrO+MsFgDz8BJTd88REDLQkgZEh/Or5zt1vT2naxUkWmgi9TCcjwkLKHzuhNgkj0K+pIUhS3coAklG60IgfIrjgc5UeyZ4iskEcmogSgRNCi5Y2gtAnEG2s75FOTM7bolQSXw4Tb9LGad8wlyUQKLE8ZQshYuWRKcTmFdoI48JStdz2aesC4N4hCwmxSidUiMP2DpFlQW0cwTi0lFV0vbH2k3TIOdVkxk8yWiX4sKzuspYI6krbygs1Yoba8pGm2ZvGucisTGeAmturVcIQPjsffDMhPTnIQZMCU242mW66KQHx98FITXJbNJJkt8K7biNoQlL44TQxKQbXr0jkpzAkkVRREkMp98Bu8xO751wJOt7vFb37KH0WwCYZXcMnJQEoyRI6bj5LpkNpWF9dqIt7FNf2U2VKlWqVLlL5VSQGgtu5EDAMfkbVrL46IvXwHDKr5X9JNiU1EuUDFggKMSJEyCLQKTUL14ns7iS4silCk3dqnwEnoW+sVwCNakPIbA6gKqQOY3i5pp9RFcy6y1wSoCXEJe07CeSISfERgB0BEtp9VnofM4/ChIyEMGJBozpiZIJyJkVxK90RgxKUFbMwRCadFpnuEkA/IomUq9IR8nGzKQMaUDuyUkEbng/mMuy5Vs2XS7Fk4Y3ZOVTAHu6h3hwn1AsOUwLruHv9vHIPWDS0Kpk1Lavq84G/aw3JmxMqUH6QnLyzR9JJxhY66ZIMGTioWfxhhQbS8ZLqAD15E54fjO/RPazAHFfEDjuQ6MxQdpjzVDYm6Vm8l/yOVFOYOS3SZ49LgiMjJHc/fK4yNIz5yhsCgr5bSF49skWSjDzeCh7a5I9SlpWrrW/gVKnJUJVqlSpUqXK3SyngtSI5IQF6aWfvphP4RVc7Mtga4qggQ1ASsmjCpzOBTiwH1Qnu15erotekxSdTZowIFVjkVgJ5tl8ioCZ4uaFRGFpGEdCQ4GkdBzIjbQtMTkekqdMyY003xgiJZv2+dgvimv0OYLJcgjUFtFogvQHJKT8UhhZiBOXI6kH0zgYIpFWTMlyGZh6iiVaZeyKNnqCihnqp2EZLstnChXtmqGWagfkR9NjZ2SFrUXkIiVo6VzJVsy9n6yzAtGT6O1iW+YByEAtlV22/Qr3tvXQJEBOSLE1Tm4VRO9FbFM8gVY5JRBxDyevmcVysoJ0C4Y/8d4tAH6q1xgtEQipgjTeJgH+iO5t/EyI5xlOEnhwWl4mvRhQ9MEDpOMpnVAPTVyuFxMpiHfGexN3RvZpyiMBsyeOir+2rNTBmvY9fxhNzF+VKlWqVKlyF8rpIDUZSADExZJmEnXtlpYxIEbrMUcJQ28N6WwxUQmyrMehxIYlulLgkIgNAHiAXQzYL1Rb0WlkUMWAeA8Ts+CCTuTChprkwzWaOU1nYC2hYQZ6aPIAJ8BU6pfro2fGAWCv+mTgVr7YIJ7IPiL01tLZcicFfnm53PJsRzQtxYpWKgJQAikoiQWGehSql8cwrCKvqSQkKfuWtbjeYytnui3LkfEuCFtWLLWthbRuc1+y2IVSPQabajkgW4Kl1+UdV0JUxJSxemHUS5PH02SZzyyYjsBdYjqEcKZHhSWrH2ckIi3tLJ6LrF6oTqBoLzZLxIRQISkfyEdx+xKp0jbDWPrP2pEoEhs7vgUVKMiUJQ0pziY26WCSLDj5/WO1DcskjPVO84qJAU71i73sL6P+rrBJkCBX2iVqxf1epUqVKlWq3GVyOkgNNB1xgqYGfWTgMyM2Kz6ZF7NzOeCTFKxhd3BDBgzOs+99jteYeORQLDZEGUCQesN3yQaVgWZeRZoMWE/FOHlTXOzHiCnE1sTMT8s+xB+I7uWMvoA7mxWN4kln+u8EJUFikEgm9ROQKlQ1R1xBaDjvb1bOnh8SGzVCToQy+MZqe6tJqJZWtm3DpLNYkhWkSD0gchcKiQoETbmHni2BYHLaZfoNQfrqJWw27bNC9KQN6ximtmDr0e0ch1P5JB3JCtjyNjkBAWk5VONMQHsC40h71CixCddbLw6QbxgZSExYbsasS728WXYmd0BOQtRTKvvfUNKf4AnqoTFjqyC/+G7JDHRywmZbk3JiqbA0LL/3ynuoJGGhCkNm5LOTVNKUYoU8tH25LuuT7O1E2rq0I+Njs6iBtH8SU2ST4ymhkWVqlPWnSpUqVapUuZvk1JAaC0qp/JfKo7jDu1crEZAhL3UbcyCz7oB6WpQY5IBbQI9jqTdf0iLHbHpmgQeNBcOGmK3aLJ7jCSEWEi8jGZYcKCwhEhTqKYLBk8iEki0hZjLDTXHxvuy94+KBhddyYNtXn2yULfsqsghw1htbDpZtpbNZ5iVDmsh80dlyC/Bie3H23MD5bPmRXfJXTFQXR+SzYQocSVHyzghVMb6laPvBErR4Po5mqjuREzMzL3bURAFqDAtwRUdN6VAQQ05aDYhLvOEH9wlpieyUgP8sKxfk2ApvjbPxYBGQQ4lL5gXx+Yaa3gB3AeeijxALAuJzYDwXsWMymcDRBuJ1UC+Tue+tuYRMJNKlxN6if+spUQnPi13ear0l1r7JPqQEJ2WII0NevBqBYPdcsvsQkdE8HLRL2cj0Wck8Ry5LxdJbNuSzYEpVqlSpUqXKXSanhtSweRkPEXoRJLwamcWKysstAaH0L5ebL0LISyhT+gkCOaAM26QlN0RZil0p6xAAU+NW9Crrj4X22jvPupzMGXUbAqgJ8UQdxWDmBPKt5gbUghI4TEtNKO5pkwARg7sQsF3OOgc2hciOLJJDIQKOBFlxXk55ABRmKppKCQzkEgNwV4W3K+iz6ZMLpQa6WoIS9VjVnwgiw5gXSLWs2u7pYk5asp7TvGTMzLuT11LA8FXrg6LLJ/cQGQwuAHlwnfRfCnEkW0pmkmcBZI7rHjRyXklErl/mBQEnItPHjGKeORuaRGCKflidUt+kC8bzIAA/AXtDaBwNyYCQPTbXB6BP8bgl0WTNNHjGQjvDmDlJqGBJjCWCKpQGrfQM2ru+XGJpvT+Sxjq7s83zxgy9JyyZkXOV1VSpUqVKlbtYTg2pAcwMPa0gLlHylLsryhCwCqGWtMLW08S3vBCCNFuLIR4OAC2D1XGGmrLzygoCYHYZQhlok4CnzvzqWc/I4sKl6tYJ8DQJAATgQvtAtr2IYxL4FyDbIDlSjjuxBeemjORNd1LPQRADgyB4BeIy84wVQlD8SIY/sP5loz+7eEmCspkVszYyfcQwJVwEhhch15csP1t9byb1spvGQlE2+ug4SRtZogTRg/IuBBtHME0U7wtzc2S9ENBNyfMG+7ecATDkQWJnAKTsYOItFEKTalhBaOSceEHsX4lX8cjJSrCFLvdMhEbaTza1dtYOJU+RUUX2yEmUhnRpmX2G078xq5pn3ctJnhEuH8KgcLZXjU2iIfEykmVNntXk1VpNN1Od4Z7L7x8yz3eajJAMdAgTE2C9l1JyFPNwUmwjjdNwHWOVKlWqVKly18mpITU2LbGBYjkYi5K9emkIUOz3bKkK6bUCcoh0xjfM+iMBSbu0BEM1IlCLgCjOlqaypMva5LCjFF2C4k+mtwAdnRG2fbQAkNFSWDqm8QAKGgGdpbVkZkBy4nfnCGMwlt5j6UmdCRbHUa5z6i/bpVOrRMdh1a73htckS2gQ/rCqFEejGqQlNkPwHhvj3Oh62gZg66Iuw8cieM8r1pTSuvdQdp10kY0akUyEvhkFpS7xvGSdQDK+6KvrAyma1nQqahSW5ZkxynSwemmq8cwTAyUZdkmYAOXgIbCeFbFFcS9KVrMiq5gznkO52npXYNu3umd2ZjgD9O2zJiTd9j/PNGfr0f4KAZB65WmkaE8ZNrEXIplx6SET+wix0WV8JfkTD6MoYpfJAoCPBrfEHSYbYvKSRd2lfbnvOKUVj3XE5zmcz726K+hVlSpVqlSpctfIqSE1eQC9EIX42eIAg26yzR6z2XG7dEOQdGooATk9FCsogLLs56IT/AVKilV7ATpJZy3AUIIhl2TLawZMwAJd/RO2w1G72NiWhkI2M48Q19Ow9dyYSsja1TRrdHeOMGkIPRjeU7IDpe4aA7AlAAZtFn3JgL38EwHXAHKzjo7sGB88EdaKSRlztQH8pkzmrTC0Kd9F3RAhUxMQZ7EpXpt2Y6dEghMhEPYoXCPVbI1cemdsCopIZIolVqtYIkN7sMorZblcap2NBys3ddKSIkFI3g0hLrZxQgaoJVbEPpcSR9MbYiP7K0nacCH3eRxOQWiyY+aZyE0a/8oYh37I8ioZc58Xgyzss32VOuW+HOyXE1tI3iO7RMx+trZzlnwUAyDtQUiHEDG9ucWLjKwdymxV/i6IDqAwDgSkJBBs4u8CEc91qVKlSpUqVe5WOUWkBhnwTuCs4DTpW0EGcqBeAkEa/IsSEGbMqLjKlFNek+tpRWaES70JMc2yAUQlFZDjekz2n4mz20YPNVX4IjE8zLprvGy4mbMo3XFcYlJk1pYAtI3DmD3mBiBlnFHA3kljY76nJWwF+GbS3GnaC5kTL2pKBCBYQcGpRaKmsMW/nCrIyxfEMYzr8HjpKkyfkiHi+dKlRCgR5rBfUK+HQnJtRWbTy1uasrrY1GPsHUfNeiGzdjPyJpFklGI/LGi2VyZwLvdw/MxGDyExsoGljzE0YcgMgI9q2pgde0+l9klsY9I2J0JjY+aCiAco2V0ukGci9TNfngbkGQzTqJjnLPOQYCgZ2XBmaVoiFTo2Op5IN4H+5pkyFD1CySuXt2PT4bOZdsiTekhKZyUyXPznLcGpUqVKlSpV7jI5HaQmgg+y6AIFEEsv+sGFKIoNv+RIdFiFAQsKOHIwawEXFboEEhM/G/SfEhoZNNsgrNfX2CHBGSWhUpRnl3blRE91kCUoIb4m7kcj5IGNLlJ7BJMCTr0PtfkIAFtHcXZdOqbXpqzA1gLDKe3UDy7LGnH2SFbxEGCt2pwz8Io7RbkU9TGKZWqWSFHG3rIsZ6ZbifwwVtgi1imZLyxRy9YC5t2wm8imTGowZNSQLSZDSDg/beNrUin5znE8MjMrcG+IIuFGtuwsxSqV3SRTRZS0x0r6rMvN5PEmkuTIGmeSPV+pXWTkgUVxNmNj7JNdJ9dYS8dzrohzUVPkS7AsISBQ5nE5yRaig2Q1C1dzZqQ8qYPSNS76r32yerI5P/wtAhGSeyb+COXeVfN7ZX6zPIelgZXWVKlSpUqVu1VOBakJ4Ibse1gBU1YmFriDsAEvJR4EUIRV2BldC2IkXWsOehLAgAC/1eQmZX0iQDwgvkQLFJaJJSBDeT3S3iCFsl1nZwEfFIhKLEUClHGZGLEG60vsRJr9JooJDUKBlghMjHkXMZIB3cOFXhFIMwyAMkQgGzIyxVlL8nBsjFUh+H6w5KqwC5eH7E1QEoLyfsriWczYysx2ukzqKqPAxItgdTQ3siE5gyAQsWlma9IbRHhjGnM2dQ6MYSwR9LPPFOWdASjGZDjroSnjXSgjgSEWRDyIBrDLf/IMQDcT1Wcm1OBWtGVJjD1mvS3Injv13CmRyO7M7N+0N0z0oiSAL54MuS42SjGdtV3ipV4U/f2woyCxdVrfMCGA1cvHmtSrg0S+0u+YPCQ5hRn8UBIQEhVKnwbjYT6zetIkBqpKlSpVqlS5W+VUkBoAGQjM1+iHYwyOKZXt7LMFvsgukhd4WopiSth3d44L85J5xrJC2QKIWcmIDSuwE50kBscbwKibXQpuVJTCqau2/wbcQqCOAi9HhIYp2+TQkca3CADMZqOZQazxQa0DfAMs+xwiZ9bidPUAbK6SlHnKgkND7oYSwbRD9FhZElJeZ0lDMiTSHjAZidHkABGiIwXxWPXJftS6mYT6KsAd3IZWFZOVCrGtzIe1kqMYskCmO+YekJivIYdSr1ZqP1MuaQZASK4QXQXvFC2lphMmIvfyilrTPR/1M8+gEiVdAlmSm9CEnufEPCg1D2k7bkgpG4XKGLMoEuuVPjSOQiIE8aL44MkoCQ1FI6xaFicErbxjizurOJeT5fI5kt+R0AcXNtl1BJfVZp7VtBDV/E6I7eN/diPR9BsUP3vP6NnD+7DPTyU0VapUqVLlbpdTRmqGcSgJpKUAcp2vzMHsoEYAZuNJA7gTUIpo0ELl4VK2VWjb0okANu3adgBgV5KbgAQTsRE8yUE/L7OzRgkpkiBZQfSQAKNpl/QsEdASxeVoOdSSmXu5NmVxEoQc8+2OIUtTElo23IEHtgmnyBbKGo2hAyvGbgWqSih/RapmrK6HQBkJlJJ5HMqqCozNLVMqx74gUkIcAGSJD3LQupJ2aeVZnTlBKhK2xc+DnhRnZcNP2yLBtiebvAKcvHYjJ/dwqeWwV/kGtJTG1ZL3pIHtg70Gxd4q2b2bP2MgCsv3TN1KNnQZ2yp7iPOGKM9AtpLIyK/LCjIz8DjmO1necVTsdbZc8K4q2SGCJhdI1uCiBpfsrdkeImFJ3tnwV0it/d0JMU4+ZaVL9axIC16lSpUqVarcLXJ6SA0ooQYLw+zsdb5sSM7Ritd+Lh7I0rAi1mk3vJT6YADGALBTsYwku5yyj+mQAeU2tgCIhKcA+am/rGBMPmRAOQPthT7JTsE2TQKcqaoBwXFxuQ37AB4bF8A9OULbMHxvw+iFzGQRMUM17EBFfRgC67TDCdAb0Eq2/Kq+RmCe1Q+9J2wnOQOsUrAY33LqvDx4kg6RWJbj6mDwZqzA0gxVrlAlAmWO7Q1Bsob4h6QAlJlZ78K47OvE+BstmdIOO6PZIJ12ULS4C2BrsnTKRnKUZDRb2ma8MzDlw+3I6UAi9mlIONXlyMTlGCsJ8SLkCRAApLTNOiVAmW4ZwYKSrHBtbNvBTLbYPZ1I741cWwCRfJHZi8YQvMYheao1Ts8uC5R61EcorTDHjHPeJAuIlpOlZr33ceNTpAmXkrxVqVKlSpUqd6OcHlKTmIuFGCbbl+DnkunIeZSgDtlb2gbiJxIkb3MDLFlychmyYUH1gOxYREACNmjFrDEZr42Z5I0AxgYfZ91L4GZI3laBEIXvAtKgwI3sEhhjGwOggtsotOOiHVoPdGS8S+ZqAWS2O4PAZMrPWwqXjnFEpsxZPyn7G/sm5MxabAAkFXjbW8dSV8tdVnlEhIgYHCnK5miwqDEVPZEokd4AxSAKZcnsmMhZqCiNcJxdVxrO6W8Wi1Ua07RGkA0izT2Xrs07wGR1M+WoANtEyXtp9bXKlES1NKcsk5LHytsBYmQgP21CSfY5p7ScS1IrDxpjAjmGJmYwOpPRx/7uxGNaVuoM9jHmMp0BUMRy2dshZGFzaNMYcPqtEFuVMU7M+ixLxjnPPrtOyKX3YY+gzntN5FDMReTPZZUqVapUqXL3yekgNeZtXWCdVCA7nlC0gAS2pVKRfHaUMoxhy9n2Bl4BUpIxoBXihaHiOhOXYDcuTIQGgPcMdko4QlmKJIYNIFVPgGQms/qVs+D2QEgWUGz6mRBVjmoyn4ALKXmNI0KDn03thpNl5CSD9gbAZdbLgDabz2WHcqpkz9qZcSGpZQB5TmiitikLWYHsbHOirWGYLHuhGEUSpTBumUDiGLBjGKvhrP0Bo0lkIk+5XOrIUMMWaFsNkfVcmxBSpeQ7bLZZ0uG8bqFLdgDT45fdG7LfjnmsWY9LOuVMK8umYBN7588MYLrHZAgN0vMSHY7Jc6OxY8Z2md4U64PROdePUzyUXGfOk6kzu51IbWnGuowbCt6Z8F8ae5ZxCArlcYHmCYzkxEM3O2VzziMmAvAenfHOAIQ8GcVwyWCVKlWqVKlyt8mpIDXKaQyxKadFzdnBJLnM0q/w3pRo4+TZ65VTl7FaG3OjED3HpYqUBBxYQJOIQZwpdS5fyiM2kFnZFBURAZdnAWzDIGOpX4CXxOVYHJcDUFNHZmYK2c+YwJ7hWRM0KHGUS1wIYrZ8xPRXvlgSBMDG7qsN2ZyIwF8XthlKZMiBECblQ9qWeinCSGQANZXOe5OgtNE/z34nZEAUkNaKJXipL9kNpGa2awBzpbLlapR9iYWKG/8kQqX9sQSqLKBkWvIjJOJi+yzpzlmoltSvTykX+khCCocYnD6YdLAQXe4mSnbJ77ScSFmbSIyM9CNygfisUfor9uDY72Czwrzm+Uj1cU6qcu3T02V0LUWJVjpCMskQvDMuLp9LHhpzrZAxqx+zJh1JqbO9T785ngH2kej4kKY5xc7cgbFobM3JZapUqVKlSpXTLKeC1AS4kzEXDLL7ABlQ16LmOoODsKIkbJEBvirbywlSFhxO5UyzSUggfyNJUG+NmaElAUsKjMRTEzxKZgkWU0giELGpzVZEsaFi5V6wE+U9kPTDFpTq7HdBk1iDyD0TfDSqoxL4lHEXqTUD4lWnjLxksoqorShqG9NAnBW12fJChhIrHIJ8MreNLOliFH2zhaSXcQ+gSAQ4pgBGQUi0yUGlqZ2salXGtGVjrOK54lbN6yD7x6ijIJyAsOwsO6qgPiypkrq19mwJY2kjStqacvnzl/csPPu6RFHvTJvlTcqmZywSFhtLQ/GE7q9jGxw+s6vTLIcPEmyf7neSdk1cDgBKzwfSQMrTY59Bm+lNNv6U79k8C9tNSu1x+c0IHzyE0HBaUpbiZDgsRRMyEzy8wTujcTpIA57ibjIjVKlSpUqVKneXnBJSU85m2sBrGhSiFWBpiMiy2otvrO2wAT88vFZnrg1wQUFsCMjwkQE+cj3Fa0C64zsnkOFMmZwAgWOYCwcA3bsIpBNp0r4YTpNoYgnMBxRAwKssQYk2EEjqofEZvLqGTPR6ZGAwAHrVwaZHFgI4mCku9p4Z4i0lJDlNU2CpY2qZn0F26Z6C8fBEAGhaH5IOC9Q58hXKTyWAavQtbJW8ToO6c2tnq4UQboBh3EspRuvMiDnJkPtFiE52ktW+HBWRe8surQSpjgnAr9AukTvzdNs2kyfRxsClez3X2UHIOyufgsaz5X0pKEwaa1HSkLZEaOQBzImS5cZSZyILqf95XJ14aBrjmdHnUw1dRpTZuCp5PiVdc8hixmY/KoDZp3KB+JhnwvBgWQaZZYBDlSpVqlSpcvfKKSI1BZko0FVJNfJZdxJsvqKOVa9qKsrEzxGF2SD7QZtROBZwSCoMiJhgaTJoTEnSCr0S0jGAJxZzEZA4H2aGdTNPTQJgAaKCpiLKRMCRsYSjsHcOG6RGCXwRQD5yEu2XpQ/hj5A3Bq923wzFYm7lF9YgeRsrrisgcVGOs0MDomz5jYBmY9fsr4nDGTZPRUbcaGczJsJVBKwPkkxnpMNMow/6C+ReqhW2ZkCXwPHQXkKqlfoVz8pwpxVDMdI9I+Nt2Ybwg7DPTEmTJE4ku4HS46C20j1qLKGxXhnxfqru5l7PbiY1LBkEr8sM9TdEijMQ72GNOxp4Zw3p99KL6GEN3hy5PupLcdPPrF9IRDi0y/oMGptIIgBmht0oUwkNJwIdCE3+kGdEBnnsTRoDMxFTpUqVKlWq3I1yikgNMABoCQ2WZ8helBGbvJRFmqayk3QA8mVmBehJNVGCZwmsZlmhokgqaS1T9lMyNpUgQ9tKS9kkSB1hhtpbz4rRC9A9ZxL4NP1hyKaFEUQBplxILMCEEFMDwYeB7cmMve2BjgXnXpq8EFBaR5Z9RUSXlradREIGQxfJAReHU9UCnsOGOwa+p+vZkINyb8pBvRnis5ZI3dcNOVkyhQ3vOoqAPiN/K3YeDbzE3n9Gr9xtU9gqKGM331S8nhMc9X6UO9+YsSK1G8VaMs8OuWxZIiV9Yz/dqmGL9rHeRZjLIicJnhghFja4Xcoq8RCCAHPc3lCyCajooD2U3ikpkCqE0NhnSJ45hhANSn125LIlZ6lu4khmzO8VqUVhiEr8mthMTmbC555johFmSLrmXDeSHg+IjHh00m+WQ7JxcatVqVKlSpUqd5WcClKTAZLBSUUJFiAOQNjg8nxBjYCgPB1wgWSRVyPz7GYhSsKRZYZYUYGKOvwQ4sT/scVYK2CynnOmVufMcjBWfQRUyp9suY4xj3gUvIB6YwXpgyy9kZnoUIcFikOxmzEaqwzK5MA38g6TUjfvQTGdbxHnCe1k9wUDTC77vlLfdBGnLmYrk0ydeVJjLnTSUbTak60Idg+a2F5x+zLHneQt8AXMvWv1HmaFY1AkaUUWvfSc6I3i4zWOh5tXpucya1cfRln+Ze+fMLSkyygzcjd8uqyNCAZsk3x2ZomeNqbzGSd4GGI8EEs8lbFh1kfbr9RPVk8l5B5VUpglDiCA4j02uP/ZppumWHZ4f3hDqCS+RVyxNraHmcNeM+yzW6980sTWEkPDHLMZxnqEqKkHSsjXCjtWqVKlSpUqd4mcClKTZi1PeqlGIG69AKuLFqCtKGfjW8IBc7ZEhhkZiYTCnE1L3YplG8M2dAbVB4iWAvxVDRtWrd1IoFJxZKrfEpk0Q0s5aJPkBTYuSFPXRlCZwJECeiFpEtTsZa1bckVYO3H+kYQoDZe9CQg0hbHC8ADCUjgiF3G7INmyDBS0owT3uV66Q31BHwXlcXbUXOuVsJg+BIKmY2N5UcEwVvT5DhKJit51cWClcaMnZ+XKy21bJySITmAdySsn5ZOnJJazBCS1ZGyvQDqP7Wrk+bCMLH7OlusByRuzaqkX4IAsk5qOqV02KPdyTmUoOyd6WD2teuolMqaSWyC275jALv9NkK5JeSJET5W0Z+/BYHi7CaY+i3mMWyAlHD020ob9/TCdNb9/PpKZnjXxRUshY1xT2kD0qsymSpUqVarcpXI6SA1wMtkw5+XUEMoV5ZiKCgfVxM/5krITCyI1WgBIC5a06RIQIR5nW8EAuOXfB16WzBNgCIMQGYozsYLPE0HRNfuybl6WMKUaWXQTVKXr/hsCfKw7Q4FG77S0y2LWsmcGbClly8GkGDNwIwO6CmMmklSOUV5oFVdCRh+L+IWVl0m+4xWw/uQGTbmMt9llXoyhi0Z0tESTjGdH60s0ZZVKSQ0hQmFshVuIHvZ2DPeKVubE0wGznDEjPUpg1ITmHiWKaYuRvifVxGshYw3xXBIsSTWtRVPE1sy4Ja+r3F+cnBwZ+GejlyVEVt+MXK0cy6CHBPrLmZQlrZC0TI+Mb8+uFYs6+vxQqE/IpuwvA6hHsyAk0lgwS7gzeu+x7OP+NQhEpnWEhkya6zT+cn+c+KtapUqVKlWqnHo5NaTGLgO5I1iFvoztrGhWLgOqij6ypTJFzStf52ZmmeJsPsdZ7CzdbQSjwTOicSuaREAQmNKSsgmFKZyBFiEXAixl9lYKZI6T5I1QvTR+JoInLSylDFCW9mUGmsCO0YPgfQ7qczuqYTmpsRptC1iX8ctS1yZQn+eAGkiZzrlkIqpEcdD0PZVhPW/Ih8DgLK20sS+tCuY5ERLyiq8BSGbVmPuDkjFMkuNsNv6EutNhSv2z5irjUkxWcQjjFSJMlG/8KJxCnhbNMmafHkocI/dgDomEEJtkc1NeDluCnlW2qvesqYmtx3LwzJPqlpZEmn7lXcnvxJwUCxnMiT0h7kFT2AAQYsKJm9kYGECPeZbsZXIuX07q9E4BELOhIVzX9R5LL4SU0ERCo8k/dDNesXNJUKtUqVKlSpW7TU4RqaGVn08oHcsZDHpCmfzjMIg9W6UDGICTKZeuscG+Angs5LEAiqFgATAkA0ADSk4AJS2qYwKKEpNgiA6b/6x6Ra/TajHZ28Z7oIvTvuRIHTNSn5nZFuDUgNBA40CSjVIb+c4iuRZCHoqp6KS3LR/IXKbDKsBejlc8GGFfrK5AtHaJmuhe3AjD7GdlW2bXleJ43tes8ow8abKCvO28uaENmSVrWEnM8pvVqqVxYKT8L7s51GJq8lAflXqS7KE0bMesjsx6ZemLrLbU6+wNa4gyG12yTWbL+4AMAczb8nYjUsuG0uBaMG+8X8gJX3aJEbkHsuVhRd8bVyYMKIkWJW9MVjfLJphx7xujuwOnPXL06RAixGmJWudDIgEioHUODQFtI/FBwWOTLTMEkgc3M2aVKlWqVKlyl8kpIjWAXY6jQGVIRIorBwAsB3ArkMmgYVNeJlJPfLmXsNSALwO0wACT7qhTZlCSnb8bp3EvaVkLK1iUfVMEjRMoreu3aZ1t7SmuhyOccgrEewBLZvg+TzebAeBYj2Tncg4gG3SxgkkOvGX5bqXRHmUGMmOrAmAO+wUzrgpnWeIzcm3SDL/1AOaQNvcGUFGe2XoMY4kMRRd9BSeAnto2xRghnorZ6zGGSSMulxfELCNlQvrEK6D39qpsbSQnTFnxFKyeOBDFhISF62R/FenPKlCscN9SjPzT8IwcNRMDWT+KZA5SynIieyCy9MzPR0W52AlOz1P+rMv31CxB7cE6MSGf0/VEw/ga5I+M9HGVFynF1UAJF4jjEj7KCE1assaIe9UAfdxokwCMmkBmmrjJZ+Nscgtrv6F/unKaKlWqVKlyt8qpIDUkc6bZbKEuh9DJ7pz0lDOk6dPgTf1ypiGH169cyWQQa04pFMJJ5jOHmN45Hk84CXFTTYkxIOgSkaJjmSdLaiIzU2wJDln1AtjqAYB0GZ33RtMIpoMasraeIo4PALiJhMiawOoysI3kOJZND0mX5mUwl6H6pjqEXRjykrVIwaIZ4C8kI7ZCECxaRbJhXr68qzh5DcqZ/ORVImsHKvTnrGpJj51B74xZadscmU4eq4IUWyEXpeayh2J1CuvBcqhBt5WNyfKzAIqNZqRXpl4P4jwoB/3JEnnb4UP5NOf3lXqpzLHi5yIQCIJNQe1sZw27kGWPmTcljqGTviW2oeTEQz+niYdEjHQRnt0PathXpX9ikZCgTfqoCTryvXqkG5JmgOHBKQkASIgnKZmh4JnJ7k0zDnrbGUL6ol7yKlWqVKlS5XTK6SA1FDwWLEtOIiAsVurnoI9y0mNPD/ChnM3A46qXtwGPq5GmhioMykvbCiASABKQaPSzV/cc8Iwjs3N5EX+Qa5PvK5LgkQA2c4F4UBwAdgD5cFAwt92rRoFbnIGXlM8s/KEYjwSJhDSEMkljYpRUhqBkR4Gc8awAK4GVkiw9wigtgaRvhmejYfLlbrZu+Uc8GTQoK3qJnTRxAmel0v3L8j368mL5RAUYaemeXK99W0VgdCwy8wQTFw9BbCWSIj2hS9J00OX00I6N09l+O0apfpKaRV/xW4q9kR67oGu6IJxHMlOpDEAS98GJcKgVVtwiUS9Hpg21WrpAYuI0mYfa2pnfiCzNstzecRgTAcpcM5TIDIg0IYB2WNW018Ry5DRBgXhss5+ZeHGPSGyiLR0BaMJyVvnu4iSELivjpH+orrRlSXuqVKlSpUqVu09OBalpCNgeOyx6YMkSJKuv2dUvWkMoCABbkLUC/KXLVhzMSA6VJzIpl5gkOJtjKTvRm322VabsaQz0TCm7gCNCozXnwFBaLTCoxKNkM/aikynXOELLDE9CRnJAI7DUc56VaQCkDeCWvUyG5iptWlAx0wnhOKuv18tD1xRUJ2i8mskWdYlhWD9mMmAH6bvdhDHYhpTsmXJyZUklhCR7mKVjhjRSlvFBZ/tLZ8Pg9qUYGzWItwFAw4mBpG9xj+TGC+SgdSHIXJ4npEtK4+WxHomUm/pF9wTtxbNTgv9YTyPeyxXPPxFnaksV1sOZx06JndUeNoYtTCRomT6NrxLW1KK0bW870ieJE4kon67VYr0qulFpbmGWdM7QZ9KlQCXVS5I6uILMqKdR7eOS983cI5XRVKlSpUqVu1hOBakhAtZbwqSRfRWApQ//dWZ2NJa2V67+SHiZL2oagtyM6KyG5UMcnWhIDrriB4+wyWHZXLZHCANN9KY0DjlYNO2WhIVNhrZV/Y47vqB1wb6OGb0Jxk5UgwK0dyQZlUKdZZauQRtZezpbn/TF6jEZBu6vFptSeqXPq2QSmS5WyIDRspHyoJKntJwHAa52MdWulyVtbGbqgWypmnjfwqaYMUMXaxkaNE2JXGZkiTD0AEQymEdDGROw1pFlkObiezoe+tvKbH+0bUpbTDJmxkdGCN+IQJwTjrJv6QkxsT4Z1Y3X2I07yz65YoyUH5LxRnBqXy0QCZd5BlWnUKZjhvfh3s+9ffnnnHQAKZ4q2ntIxij1D8xwjtDEZ9yZ5zYfXU529/GekQ0zB3e18fLqM0VJWRe9aMkrY35XrF4vnqSlSpUqVapUOZ1yOkgN9GXdILyUheB0jOTB6S2aHzKQ9ImBwcz3ardNQUuyIvnxEIOcgyIg/3ySt0DnRE1sDSsQEekZYVMYOchCMIr1/wPwTgpGBsBXihAcMxoAI1DalM+buth0QbxFgGZsSyA7ouEBtIqYPqWLNXEWCtALpGjNzEaZDLfqzP6AVWbExm7AKYDOory8AjllFbJgVeoQUiNjIDvE93YPEQpLgnQDVEr1yVKg4AXgkB6btMwqIyoRKMgKEcC+OAa9JusiYaXNcQKhQSBsacNXskvOCMn7QHmtAqCVjOS2TsO1+pHV1OewNkbmPVm5HCtenfoMJK9JeQsBJgV1RrDic8mcxtOnsxqfQ+A8aYDtil2WSXpFeddL0H5DLpCZtCRO/uPMVkEv6X8eI5S8SFlf9JiQUUdIpAYIdYg9YcjYapZfpUqVKlWq3D1yKkhNEJMyNoIHR0HBcUPoPbDwwCKmLOUTUFk2Q5ojvBWFh4vJyrpY0ZJyjVidM59tooOMc5yAK3sErw1DQZ16XQq8Dk2Laz03qR1pKMt0Zfsu4JIAZ2egCXOfp5ZNAIs1jS9BY210GU76xzRl0zvnVifzr3pditnsQSxC1kEjtp8W6J3AS0ljYUpmmJuq3BwTyebCkZK3DRGgxss9UySJMWscc4xtkPiGkKEKHmaZnboMUvwLUyINMg5Jl9QnSZlmOkwrbzXIfbIq9iizZSJSAtopJrHIrJVRrJzg5ExBPDe2iVWDo+orcSHS+JJEsrKrGBoLxmmyQUpQBtBDxyyh4WhYsbFnjptcaspvigH2WZpxZpTrPh1Z8lNqGZeDIaRVbmTzS6e6eY8sVifVYH4DNR7IjATZqRLbrj6zsgzQ/rbItarmsO4qVapUqVLlbpRTQ2qyl276R0mKbCA3YcIykpu0NG1QWQ7ltdYXe2nnwEzaz9FYHtwdDw30L1NRZ5glquIzPRGXJqmW7AF2SMDZESmm4txOegAK4I3uUraJdUwoBDq7zmPeK4lSIA304NwrFYP+zcR9YS+lW+WGgrZ8Dqo4t01h60wyD0Q+sx3GwAC0FRieUnKCoi07Y53poTPy9qyPqXYTgaZAdBxT3ME9SEOElgKg5shehRh5i2ITeRKPHKdZeuslIzVgPLYi3oQBJp/XK2WzsSwsrzcNJAYjJLlYTYRSTjZWYiNt2THKn+XYpuhl9BPw7UgD5UNRygC/xJbogFDyLCVPn9P2pCG5/dKEQSQrzLnXRfRx5JJtZZkgZyRa0llHHZDfI3YfGvGyaNIF0SMQYV32ZacEol0jC1MTFL895seOot0IlD7nZVcI2+fojiWrVKlSpUqVUy0vSmqI6B8A+M0ArjPzu+KxCwD+KYBHATwN4JuZeYfCm/lvAvhNAI4B/D5m/sWXooh9aZfLbgSUyZrxhoCRC+Rm7vOAdnvNEI+93Jd2iYrjPwZc0wnFy9VvrixEel7A1nA5FKGLxIZBaOIsf0M6mz9s3iDFE/rRCAgnhiMHR4xFH9bth+IU1/CX3qAhWdMmVJuM9hWgd6i1M3iaizEroaIVhmRWU9DLyk+SwUn364kAN5HdjJSRqRfitsi7KAAcEndibokIlr2uDDPJBWL5tHSJw7gidtxp66l+UWEVOwNgUwAPdLfrF+9I5M11kRTGbit5iKezZZcsZE7AvvZXYL9dLma9KIi8Mi2BIqRAfd1TJfccSC80YD4SihgpZrtu7agVUYpJQXkeCJMJlO4K9VCa68WDJUsRk6c43Vv2Hgjj28cfphAbRyn2R8ql2CqoNyXLesihCVmymnldho9RIoUnrSLj0lj200shQKdYPl3vqSpVqlSpcnrlzuuvgnwPgK8rjv0pAD/BzI8D+In4HQC+HsDj8b9vB/C/vBQlGJRgiiU0diYUpC99cmHWc9ISNkeESWPSoAoYseXlf/Ri/9k6yPylYT0WiLjwn8a/UATElH2HAA4Bc6XOkJn8sMdNjwBoeg7L7zoOBK43M/gDIWOrk08nADluCGutw6QN2a5c9OA0aWZZAJ3C7aGtMLSJGT+KM9Qu2dPl5YGhrSlrMabgzf9z8S7RY64YH1pRt4NL/RjaP79meF5smFLnpoBv/euc/HWhPQrnWkcYNYSRU9s65+DIxWVqFPcWCbqKdzLtN2JsA8IKWxl9oedBQxsj65u5Z8UO8bvEDBHifW6eL/2Q2wemDmf+k6VXjswYxuc57Ycjz0EkVT1rJj4b78KQ9NnaLBMlgmW9Mj56RazHpHEu2Tk+EXAIx9uG0DQOrXMYtQ7j1mEyclgbNRi3Tbi+0bHSZwToesas85h1HgvPWMb/5vHYvPNYeh88dWyfEbVN+M/F+yfoFP4TGwWbkdxrDaFtgt6pT2ZsErWl3F7p98A8z3ctq/k0vKeqVKlSpcrplhf11DDzTxHRo8XhbwLw1fHzPwLw7wH8yXj8f+MQGPE+IjpHRA8w85UXbQekM5IwmAnqlYiT+TJZDCAA26YFWsmWBqTpRzsLOXxXE2QH8pOnKV/sDW/Pc0J2or/uTyPnFMiEgnHGO85er2qNOdhFZoU7AE1M/aw20vZUA6OeOmAGahOAxjFajmmlWe2WFpExctBaVsJIKYWJaJCeWZb75FdR6lPR4UJZnQnPVSjiX0AnKWq1SNeGpg0CjrPw2pL1gphZfpKyEVAmEG6JpniRADKpdoGwRC3Ej3h0HuketHuFCCAHNMao5+gFIjWRHSe1CRdeQmFAGNo6qcvZvUMU+2sfDwG9xdiWQDmNSc4UUxHx/bmCPNp02WxITDgmnhDTU2OvrF1odjmrYiAsZNphwEfPDGkgfhuJlU3OQaQ6EUsMD6ffI89A5xnLnrHoPTqvy8UI4XnoiePYh+WkYleZXEgpltM4medJfqtA8feDDXnNB4NZPEBs7mv7LNkBYTtgyIx2l8mn6z1VpUqVKlVOr7zSmJr7zAvgKoD74ueHADxnyj0fjw1eFkT07QizZLjvvnsB6AtXAQGKVzYM8JR6wvuemjCz3XEgNz4Bg/y1r+3EM9nJEsyaQyeCZZGTdrCxdZW9UeBiVZGUynYGHoDGEsRLZbPO1CfhAxbbU3ZJYU9dluMFvENnuAW9usLmSWJUtUD4fGPSoR1Y/l2hkGI2U5rs1bndJCVyIiesNuRyDOWqdNj0xoI6o6XdKJI594YIGc2+Czlhisv2OAJml7xUDB0bRw6NCwwhgObc9rL5o3iUGiDF5CTQD8T0w0jjQHGJm45Dge7ZfpH+R+KdyIB4g3Q0krcDcl/mJJG1qjgOOaFRD4zxCkA3wgR0HxZdnoXkKYKxj80alg1hpg/H+zKQhlETPB0MCc5XYhBSdYvXJbeaLG8MJCuSBTDYK5kRQtNFD4wdt3wzTCRjuLgHkBAt+9zI76BmUovfgXgDuaK/ck+ofgBCinfz+5fFM0kp8/nupTQnymv6nmrOn3/9NK1SpUqVKq9aXnWiAGZmsptyvPTrvhvAdwPA2972Nh7OOtpZ8xx3yhIhG0DcADFbWtiLpYueGzbl8vn5VTDfNGKPU/HBXrKqijtJBjb1QrtxoPTVAqMS9HhjcQlETyCQJV5GwbflEWoJaVC8B+Z4JCwnWUk0DUDWjhTSdbaXmqir7KiVOxEZLcJQ8JkjdUqAUqgNyTVpZj8cDRsxYsDC9L4qyID56CgCxghQ5bRDjEsyY6fdoUQG0rIsLzSP02aPkmVOiYKh4Kk+QgMOSxIdTIbnksxpQL/puvY96xshz12noy7PT5njC2BDrJWgZ9m3TP+lP9n9DQQvH6t3JjyzQkzUTycgXAg3U0hkkTKbZboFIjFqLKEJtko12nEi9Qh7jqm6vRKp5C2SnnOImRFS46Ny1sPTkC67bITEEKFt4lJPFz1WiUhxMc4YbrJrvgTd2CQ80DEg0rFko3i2lZX5zRBCexc7a+4or8V7avKGRz5LrVOlSpUqnx3ySknNNXHXE9EDAK7H4y8AeMSUezgeewkSIW9CQQH+rJ6N5QRGAJjMzBQBfQjiHjnCkqFB2QBWZr9aoUf5fQgXDWCz9WV5hYcgMOurbcWAY9uicRjobH9RyhIcojCDv2SCY90jJXi0IsQtQJIjRuNCDA/HyrylAJnxE8LNSM9JkkOwVWcMeIZNsEBZyXKWOa9DrufsXB5HnxMmigg20yqx3xU0LgbmB7BqwbBpT+5LOWLGTmrMiKPT8SsTs8ltJZnS2ByT1oKXAyGRRJkTOKN3xdHsoALfPBUyTlzNF8gJ6X5EolFGZliD1sWLtsqs8R9JpyzeyHQPkLGN6Yis3JNHzhmPB3P4TQhkBmhc0NR7TkREyIqmEA/HOq/71cj+MAROz1GwS0j/nJYEQvaD0SczJT6Qvy4QmTZ6lNOSRNLxsKNlMwQOfkWsV88QEYKDc2yuSWwpf9wMgfEM9N4HgiyxPp898jq8p6pUqVKlymmVV0pqfhjA7wXwV+PfHzLH/ygRfR+ALwOw91LXKccwEaS3bwL5CpwG72YBPaYeAf4yg9wy0LsYb8OA7LWSQeoBFsyJDJJuyK41sF8PlC6VDJFkkDs7ks1qx1lfATbeXO1M+eRzshvogaLnhkOiAY7ZpVh3FQ/9oQSoCAFojURtj1QHa7XmAyyv0WPZAHF2SDJrDcSytnLEswtWoDupPxFJyqelzUBJuux0nfFE2Tayu4NNl+I/MvNeetaCaYwHqWTBdhbdnPaGSNlZeAdZYhdoErNPz4gAYkex757Uw0OitwwQD3VZEcBFMa5GjWruVbIdysmO3JuyZNIJYDdeQjjli/YJZqMam7pyJkZxY1M9rjXoATvJERJd6DI12YOm8xL74tH1NiU8x3ud4NknkhCSCjDa1BE2y9C0LXvfkllq5hDIVkuU9qmR2JlE/kjvRelvuS+P3bspLc0T25lnWNpPT5CyncyjE5bNeSw7j6UPm/CyeV4/i+Q1f09VqVKlSpXTKy8lpfP3AvhqAPcQ0fMA/jzCS+L7iegPAHgGwDfH4j+CkCbzCYRUmd/6UhVhprRvCxBB6KpZynA2AVLFa1pYIEaDgN/CunrEDGKELoGSDD2lOjJMZ77kZCa7arUMSI6ADAOC5KvlRiXAjzr1gn+L6XNvYj5EZdnfI+73mAiRBC570u+hiTAb7YnALgIgitmvEvAqe268I4wsk3C+3EtBVzoiZo+Ad0h5dIDVNIa8JcNwMT65v0Yk3UsrEhFAjlvQLYQgg9CkwN1WIQZgpHHIgukjyciIuYyjD30v7ROy3wXUHWJqHATGp7THcWwaJ7E1MWYkzsCz1V/wvyUvYhiE8XKR8q++obPRW3mahNBIEovifO4EEEMJucmfxeyrJTJk4mwQN7CluDls9DI6Cv3pIvIPKbQ9vAeWns3zH+uMvwU2tkwIRyBoebwTIfTRknqCkt1GlhemLII261tuTTWFPofW1JyODu2uJEZ/u+QeF5LNzPDea/xP72P8T/BI2dsj/5W7u+TT9Z6qUqVKlSqnV15K9rPfecKpr1lRlgH8kVeiCEV0byZkIzg2L1wBZiTAPbZrXsQWZFjiE8AGUpavMEMZQEwBpwZ1WCUFNJSzqckGK47lnVS9svIWBdog9aKVoZ46c2vbdAQNvPYKth3EnmQ+R6BGjMaF9vs4ABRnsz1RAUpX9D59tDvVRLoSyUciFvayAZmIHxNfuYNVC8+YkNiBqnJDnbSeKoFDNjPnlmgQxBsgxRMvFqVNF9K8N+v1MtNvsLoB9Hl3CAyyCQooTwwhZZM3jzjMuIMCeGUhOYYw2odINCA7HCnKpShX2okH50S3zEMjpKW4QnqrtjD3uwDyeC4sA6PkjfSmIvFWivfEWB3sOZH5cEyvJ5jxM+0Tic1tLExI9ixkz8WG86V2iMQzkB1Nh44UP2U9sfnvRU5oX4w8ir2IVvwGmedGbBKWltlkBgwfjZjIJ+nI352U5tP3nqpSpUqVKqdXXnWigNdECGZm32JMfcWm2eUB0zDXwGweaEql0hQ31nPRc8NIyy/u/Do305nSgK3UgEALM2R+dUCSign0QY9oSNSk2bAESdq34JPMpoSUABiD0343YLORH9gsSZPlVBTBWTgvhM/uam8BOQDdxd12wCzfUzUtcF9la84HDQpaqSyW8Si2pxIoz+4m1rrkkM59E7JgjQjvTpoZF0nLJTncu7yC8THnBELAOvIj2vU0rHEJoSzbgvEMCX/K7iGGiyy253Bvc2QEQ/phepKIXqm4eElL+B2vzhm43j8x+D2/KgtXT58sochTUoeWlPAp+QOK+DEO7UrMXEmGQlyP6AzVMwbeyDMhXpn44IVnQMhZvN4Rpcx1Nk032d8UQ2BcbDBtvpqZn804yu8CWw4s5sjKMWxWO5f/FEpMEseYIIkf6j2WPhDeZBOnz3r6/Vn5Q1SlSpUqVarcPXI6SE2SAukXh0UGFMSA5ITTqIiPKICgBBU3FDw3HQdAmAHPDHzfQbe0u3hZpoy/0S9k/2b9Mt4qizdJ4btHWHaTVRQrzgBjBFwB5Cl0FJBI0ftCpLE3UpsESIsuA6xjbWSxuz0Vv+Qcxo5erJ8jDTkJUOnaMa138C2ATbDawWgxvGeys8ablJoz9xRrLQlkQwliapO1jO2tfLCgO2FowwltjIkYVUhaeUtm+wBxILSepI2wlIxc8GL0ZoA4s04Y2ZzCcXpWsmVqyVI5GQMCAWtjHAvEqzGghQHwh3vPp8uzezL2ONhIb/40RsyD9OJpD6doWOGRaaNXSwSi4eW+kf2jJP4FQNpEVx4tOSfkRZekGVJjPTNAOrfq+U7WEHIVB56T0Qt7k45ckcA9fGKkxAXyX99HQsOc4olkWVzavFXslY1Q5TRVqlSpUuXulVNCahTw5IdXx6tQPDc4FlFECWjJIIx0lWAmFwhCg5BIoPdAP2j0RV71MoW+spgCl+QtWImwNTOZkgGjf8YUrMfF7pBDWdUJtBUNngS0fHGcWUlS4lARcKonTVG5qlgqXEInZCW1xdwow+gYHcAcnFsFzQHB3umwHSeCza9gbZSAe2Fz+SAz/K7MEGvGtyQnCl7Vnmk5G8eYELP0KhAeAeUFCZQ6iuYtKco380zbqJoexvuKOJCixC6osJnUzWkJGBWpyJwzz1hqMymSDmTExZTihNz1e7qHI1HhaAfmfAlesgojxb4kQpKzong82jB6m4SwSBGXzkladCUuyQsT61Ivpy41g6lPaWROXnVsdD8dFSX3JyUiE4+MJCyQ7zYrGyMun2sl/YpqE5IGUCSAGZ0d/gZXqVKlSpUqd4mcClIjwAA4+aVK+T8YfKKirAE0A2wKnSkVkBh0CAH04rXxK4Ljy3hy+TBYJjXogNHKFMyIgD1ZVGazhyVgawiOvWRI6gJ4S/tRRH0Iqn1pd0YEPbDeFERT58TEfirbXtUZS180C9mQ3miuNls5m6/l4FrIT6VCsXLTY2PqrC2Z8l85oJq1SxI0CEzXW6KsjdJsPBfJBxLQ5xikbomNdizFP0mXWQYllvWmRQuKWYhtXGKpG0yy8Cx0bLwZloMZcwgJGCYSiH2gkO7AQ8ayIGLCzGNduuKTjVeI0ndxUWhMnfEn5SbMnh2TjCz/HUiE0MSSkf1rCA7pckzdBNdukqkeG3tNMiHp74QdEyE0yXL2JGu9pmOwXZYMZpKtLJFYQ5ZBIZ29esyQMp4xEPc0MosvT1g6WaVKlSpVqtxtcipIDaBAzEBS6PyiKZf+gQFbBTnICquUS5xSOwb/OoqbKMZgeUkmIA0MlkiJ3hZoQVCNLZwVuKMIYLegaLCyzdSaQ/khtZBlMWHpjiy1MhdBY5GybsVzIZsUQuasjHzYnFUKvtPZbNmYkok8HmRokwwMpqsUUAogzkfelJY4BXAqV3rICKQJAbKxLRBzsmjcmpIR9kVizqycYi/SlaJLhJCkGcukZiE7orqAeW0vB9+pHdbU5SGJQ/hgg/QZNk26ntN01KGCTtqWrjBnnpKSFebaic05ZS+0hEGyipXJDXx6NMq0BGYZ1orW071L5ox55ob3g31eTHC/Oa7LUE0sDHSPnVQ22iyNB+lEjD5jliyIxtaPavtU/GKROco6tsEL4zUZAue/W/Y51n10kLx+Nv205ckDL9/AclWqVKlSpcrdJaeG1EhAr3pCFDDkEB1IkD/hqpOWqeVHT4zZiFXLZoKEmAaawsxzz8UGngN98o+Dxgg5K+EV15jZ6axrRcGSGg1IDg2PChCTrGD2v4BtLVgyMNConICsAUTZ4jBjHAvAOasBcemSsQNJ3WZ0BfSamey8RxmSK48YUC1QGQXpNB2UGy61d9JNEntlxsieseRD2lOvhhhCllBJ0/Ih9sDWKZnPLLA2atu8ZmSy8WlX1DPRRLjtKM+gxsTg/kVsnfXV3LiMmE85gn2jqyjRJGYjhqEY32EBPOk+NjB70qRmGGD1qA6eGTlW3AD2idH7X8ZQl5nZOBiZ0LA2KB/jjMyYa/V5zZ/OQcqJVczB/PYJIelN4L/EaklZu+pRvTBmDx01btZInmhAnw0PIU9DslOlSpUqVarcLXJqSE2KJylAf8IqXIDkBF5OAKEFg6Hi00qCY3CyzCQ7Dvu3tASTTOAk4KsVDTD0nZgIpC9Q5kEyk7+ifHbMGqz8VvCnBGg51e9lWVRRfqhy9BKQlpMNC8UTMRQ2AEyMu6qBE8bKgOkM96docUuWhoCt9AbkmrHZ+cW2d5IF5EJDVOJ3S2ikBrlPWa4B0s2tapJV11yNdD9k2tv7M9YyXG4V/vqYPKCROBhommJZStj5GJtFQrIGRkoAn4sTcj9Jv5M3EAr8pYxczYhER8bNZMJISx2Zsmx7afKitA8onyewhMraIiMreh/b4H8QpyQA5W1syY0lMGkM0rifwAZYic2gROyXZwb7PE7GyyxDWTj2lTnG//kQQwNLou9ATCR2SsiQj1ng2GaQq1KlSpUqVe5CORWkZgAmBJjYpWVmNlOwvgYP4A4EJwetd6YjEfEZKJkt24k4o+dAcIZB4TmwPGnJWF5ag7dTOWfOkOmzYSi2TiknBCI/ZyFlDsyAAD5lg01vg4aT0Vntba4ve2ABvdZRZjS7kyXyIHkrDCqWrAF6IKNtA2KDVZoxMo9Jfi6xiewwAcg3IM2D7i0gLG1ug1wsSA94P49xCumUWSsizbqV7nOjojWM0oVQb8vaR/HOuFhIZvddJBmckcLYVspZDX2+chOYmBMlNtLlwfPI9k9cnpjUlZgjvY+zWI/0WzBE7aaW4Al0SOmeNQMaGf2UwASSR7BB/lan1C8a3vdKPI1exe9BuidM3+3SMO+VYCTyburX9iRzXCjfxVT0PVsyan8kcpH4G4nJsUkGGPq5SpUqVapUuVvlVJAaESre5ALkssNUgv2C+MQXs/dLEDVwrskrM2B3NcQ2oDNTh9ISOcmW1nughwUxeY0lnC69UElpC1KNZmT6LAcM7Rik3U1xHAb6FTAssxch4FYXvUM9yaZ9CDumWzZp9WEFeVlYSsEzyADuzDOS8xAIwC2BnBWSflGpF9kC5lBoW/TKArRJtSoUKUBlQYScDarWdtkiVijIz+KPzBIx1dfGr1hGKiQugnFovZbQUjwoewVZbxE4pv3OiCWnLIPeezTO6T5D8YES6utS/5VQZndOalNJf05o5D6ON0sC1UJp5D4wqcYFWCc7Uzpux7fMnia2sDFF6llBIpLilcljYzTY34r4WiW2Jg2Ztb3RQhNpKKspiYQN7pelZemZifeaXQJrf0GCqQgePmyk6Q0xKfSx19glbB4hxbOOgyxfjISJ2Fi0yusu1tgn/O5VqVKlSpWXLqeH1Kxc90Erf+zlkMccvu/QNhsgcgAHMjOf7+H29V/AxuaDOHfpCw2YNLThRPBMedEoiT/ZXd5dIDcCLLz5nK4ZdKkAtubjSUtf5EROVFbYJn6XVMw2RXPCovFLAt1C1BwwAkXwIwkSyjnxCIMMQRwCvvy8XhfqLvcZSVcPxiMnCiAdm2w2HXHFnlnKZDQ1jowcAIfxLJVJi+lMyVyfQGzMsUiYsr6vaDOrq1zCVnQ73FuyJEpJT+kP0xgWExsiZ9k0gzzmJuBZh6bR5YNBLTNeJN9XpNU2N5NdlgXYRARah4DoFDdj+qAmcvnxaFsB5iJ2vyVNjCyGsx5Iq7Fdiqj3UIoxSudyopbfZ5zGRo/pP5aYaaYxDkSCYchEZkxDVLUvKTtcrN5zXGYWyUxvCI0xgI471BOX2jXnQoOBmFIketaeVV5baeYENyd0mx4c59jAwOiQsHEZ8CPCwWO+EpsqVapUeZVyakhNNjNZYNzIJQyk85guruNg9hEcHdzEmfEX4Z57HgeIsJjdwK0r78Ph8XV0s12sbz6Itc1LSDEhK1qV9lbPeBblTQEJfxGy4OLeD2mG1Oo/bPWE9lYTLrHPHcmP1BsbdOBEtJTwLNH5F9A2l9DQZgI5IYA77owOoGWJIZKYGzaV561mS6MUGp5o0JP6x6WViv1Q8k6mf4ZkMZWxKDRB38Q3QixQqUXetzRylgCRsUXqpuls0WZSzyw1yxSRmyhiTQeGI1eMdZbCAYhAnaAZ+wQMq1dI61ZQH6R1w8HJ9uaRI1xs1Wm6SKacbOro8quVmECIrcnrZx4ENldp2/osKSEYklNwnpXPmp+yXodrhcjYv5ZY2B7oR332U7+irZW0hefN+zzIX5Z1MiwJBEi2xjXENZChSGRiwgAhNF1crib7JCVzsKaFSEvJzKilXpBsxsuqTDxhN9qt8toIeaA9Ipx9EmhnHocPORw9HN4Kazcczj7tQQz4hrE45zA/X4mNCPXBRvOLDD864R1QpUqVKoWcGlJjf8yp+K4pegGA0fkj3Dx+H7rFLSybDld3fhrz2TEefOhdOJ5dxa3uJpiXWEx3gBf+A+5/w1djff0SEnB8ERVoBUBWAGXwqAFCDN0QU4CreBDSTKntywrittIcL0JgVvVFQJMklJXA4rB05RNY9h8F8yVQ+6VwtBX0It2AMZAbxhgh4DyQG02lvBL8rLTrcFpaCZ7UYr9RfokB0OUSJDFiCcsVrFkfhC3CosqK61fpvYLMZBA01GLv2XxJkIXr+VIzRgSZFKBn2sQREmhfaB9JHsXrdN8Uww8o/JOlUZa/ZozyJ0rIR9QurSlUqimwl7L6wo0le9gUPhhtxz488eq8fSUFNlW0kpmcXBjaA1nCJ1Xb+4QMcbKtyl49ksaZjK1XxZUM4mFYgvoBzT6mJCcdjxcJwWxIEygo55QNbgNhCUvLwhIz2478J33O7WzuqkRiKdpGCaiMcyBxXPR15dNS5VWIWxDOPA20s2DXtZsMdg7T+z2auf6cuB44+6TH3lscFuf8yRV+rggDmy84bF7xmO8S9t9MldhUqVLlJcmpITXDZV8Fy4kgoOMpDhdP4eDwKuCXWEwc2rM9rl7/GRAWWNBNdN0StOgBYuzOroOv/wIee8OvR+PGg9d2ORNuAXuBn8NLyCw/yl8/hIYU0CLVoYCDgeTJyRrI9BjqYyB/LKtnqLhm1begPwO8i85/Ch2WYL4K4k9izX0BCA0QwbW1P1HI+tawJkfoecWceIEEkx0ph0m5fSkBMKurZMEqe5FiaVawEFlEZQcvJU/ICvJAJ70+EE6JucgH35YSMKJ1hb1ZdJz7dJmywGxiPNYr4RcU9bcbPaa/xhrBExK9aau4AqtJLa3L73HJXGbNbAgGM0ArYofE+EJMI/EhuKS3Ll9ThaQHSvTsXc2ZDgyxSeGzy5ZsRgLGsTfZGJu4JeKkqxUhMymJQGnH3JwpzscjD+oX0sKxkI824WQrTTAQ/rosbb314oSU8R5dz+gMkRFCmWKNZDzKn8r0jZF7FIePiz6DK06euOFslZcrzZyw/Umgneqd3M4ZZ55jNDOHZp7/CrkeWL8WSM/y7OcwsWGgmRHWbgX7TPYYG1ccDh/hem9WqVLlReXUkJr8B8u8tRUXAsSYddewv3gCS7/EWuMw6j16dpisMW4e/Gdw4+G4A4cdNAH2uH1wFef3XsCFc2/QxAHDRtORwex3OhmOuEy9fDNLSzcIAJPuTZIAipQxIGdFeEcGRoc6rwisZ6NmiUnRY+E/ip4P0fcdFuSB5nms0dvgaDMjBJYMEeLMNgDnGX3clNSb9uAE6A7VkTqElDBKMmgr0j4mUCn6DGJmbCOkfxNkUz/KCoZizpSEyA4um3EqfQtKaNLyL+lbimMY3EHxGyWCJXWl1MwGV7K5Qmb4WyE0BdcYdi9ngPauGYSYlf2SZy5nFllJ8XA08S8YKWubjQIKno3A4IhzCyKOkgXuJVXXZ1FtLpbNqD5pfaFIQWiiXdOyM5NhUJZsqV4aF+O92f9FyrDqnNIwQ+qP9iWCMyQrZCyLWc9iKuaOfcpiNtxjxjw/0sVENklJvr23Bss1c5KZbm/Oz+Y9r8jxVUv84VqcIYyOy982YOPGatIy2WPMLlX7n/0U0CzUbus3PKb3EfrJ0JZVqlSpYuWUkBqBvvo1vY7TYY/j7jJuHn8As9ktuDGwbELsgVt4MPfo+gWmRx60DBVQx3DLDn7kcfvGR3Bm4x6srZ3JyNKLaVXqtApDCvANf5XAkL3QglDIey+CvkQ8IsxmApyJPUAOqU/U0k60FgCXeQfL/iYWfYfjfgZaerQ4Ao0WaGhzCFqBfP0/A+QoeG0QMr9Zr5Ms9SlD7UPzoQJHcZ8MVpuF+gX4WcITlzqJLVfFzBhdebA0TJb/GWOQ1hsLGUJkxzM1WpC0eDxmO0gg2dhKmE5/h/evLuSKJANiB+NF0T9pqVlDhMbprveAGbZifZ5dxmXrki8EJQp650XbEdKYpW5kHyjzckidLm8lsXXZQDNbvieAXNA5qS1SleaLNk9qbGZ7xswUFOmpSdNiE+nmmXJlTqgMWYF4U7R6+c8G/hNFX6ftq4mv8ZHQ9EJqonfGG3Kkqqqd0vPPSNkIHRm6XrCU9PtUZI/TYSufoYIQuRffgavKySIxNGDC1nOM8eHL87gQhyVq3TqhX//cBPDNgtAs8mOuA8a7hOl9n5s2qVKlykuXU0JqoiSQlAP1AMp7HPfPY9btYr6co+uX2NmfYXtjhDGP4b3DcrZEs2BQQwF0jIAeHq1rsfD76PwMjDMROA5nchGagiy/mc+OMJ8d4Oy5+1Mx9h0W8z1M1i6AnCu0NaAQxfx8uf9JxHJsAFYAVpJsIAJnUkZ0EiRJgFTQUdYX+TwG8Rks/XU4IizB6DHDwj+Bxn0xGmqzWWHBmwOQHfV3DelyG+Skq/RMSWCP4Cqy5+Ixif0BIwdkZOG/nDOymsWlsquW9Q3KJTYifSdzL+pxu6Qt2IYTQJa6SDwSduY9p7/I0yyHa6SH4vmRqwKZCZ8bpzE3Q/hpbqz0zdxoVowLgKBjl2lJmmZbaBKn0mxSHec9tE1I247i3jsSD8OWAJsxMPcDayXpfkhL3lYRXQ7EdpAhDmZZX/HMSwC/9ZDoc7iK6JhzIBAxGuOl7DlkG0sZz4TMJCJv29ExyT2yJXCL5JK13JB4lPc05Q9y9tujz0SyMa2spsrLFU9ojwjEGkfzcmVthzG7x70sUuOWhPaQsDjvs2PjHcLs0t2VfGC8S1huMprd/HgzA6iHZo+rUqVKlRVyekhNRMysH4Mww2OJeXcT0+4aGB6+79F2IQXx8fES3jFoOcLxfoflcomtc2N0DIAdDvaW2NpwWB/v4vj4GjY37gHg7EqlgR7ed7h+7eN4/qkPoF8u8c4vfi82t85jMbuFo/2ncbz/DO59+Ksx2bgIxBlgi0UyrGWZh/wlZCBFCU744lkyjg31WwHJ09FEkBQ7A2B4PsRh/ys4Wl4Gdz2oJUxGDTCfoxvdBDdLMI1y0ERah0OYKUbUq4Gke9bxyrw6K8wqIDFkdYKJQchBOAPwGbhbAdhgzc3paALMAvstsIMuXTKHChogxzUgXkCxtXiKjTDXDMbcs8aYJPBv+xL0kKxl1nYpWQB0uRSB4ewyP8lVbYgs2w6JTpFJWo+OJaKZtyXrFaXq++RRiEQhbUpTLIFMprWAPSphiOJgZE1Qu61HwPxgw03z1f5emKizpFuKaYntiP00kN8sf4OYU2OAJH5GntcUO5Q+B69lx5JqOdzfaV+apDPrn8xopZRGeOkS5g9yW2XfBk0SVi9Xq/JyhTqC6wPw3rrsQa8iLKYfM8gjLKG+U5s+xJ+sXyU0c0a3SeCW4eaEjSuEtdsey+27Y9kW9eHvZIcx2Rvqu3HNw48cjh+4u0halSpVPr1yekgNFPSk72AssYdb8w9gOr+GbnEM9h3cRoP5vMcEDuP1FjwFmo5w5twExx3AvUPLwHLh4TuPq1eOcTj1aNc/iM2t+7G1cSk2kcFZAAEA7O48g49+6F/iaG8f3AHug/8H3vr5X4WDnV/C3vQ6uOvRXPk53PfGr0E72ohVUVaHiDMAJmE1ymemZdbZgk0gkBTGEN4MiU0BmQVrM+C5w5xfwFH3LI4XR/B9h0nTBNDVeXT9PjzvosVG3o7B42nO2xAXMOBLTGQvJk5xIqV9ldyYTFYcyAzHYJ20+M4GHJEFxAYas+l/ETCiNUlHyF6W2zIRmnBUlpY1lHtP8gvs0UieOBCRhhhLtsDcFGe1pTN/U3C5HItgXQK7y9HmOBgleSYhORnZitflJho8d4b/xHEkpLTeolPh5ZFzamM2Hhf16rCQLKk/USAyn9WLINWF1NKGliYbWmKlN0KwISVbyIXDvaSoIDac/SWxv1PPZB/jaHyfl/eICQWSKaNudmkgmXE0egyecvsDkQ3Q4K5NFVkPTDaeAyapPxB54ozTD35Pq5z9FDA+CL/Wr4bQAMD5jzGOHnI4vv/OAN4tCGefAEbT0OD2E4TDRwhnntJjZz8F7D1++rOHjXcdmhkwPlhtvG6N4E8RWqlSpcrplNPxM0HyQlbkmCCOJ2y6RzDvbqGbr+PW3h6aZonJ1hgtOfABo591WE47OAYmTYO57+B7YEINzp9pcWG7xbXbM1y5cYxz525ic+NSAolADgLY97hy+aO4ff0mlvsdumUPNB/B5sURqJnhuOnQLD2OZjcxO76Jre03IHvzCNBfEQOS9rVBji0GoD8DosiIjUY/CFJRYpa/tgLInPMncbz8GObHe9i7uQc3duBFi6VntK7BpDvC2D+Btr0Eh3G4slTdsCUB4k3spzcN56uBCB66b4lubBhnlGN8jnhrpJ8OjKWnFM8QYjcohrFw8uJwMXjJIZBZEjE4PRSiYsf00u72qCyxagCzfCkSEVNKas/SEVPc68cBYyZ0Pma1kms5pCEWW0p9stQsJw2saiU727FnlFmrlKuUe4+8eNLebOhJs7JZ4mjv3dwNwCvtqB6YeNOwJRZ5pjX5bIlLqpEoESGJPckfMwnSFz21AombyUkepaVndmlZiGGK9SPc496HPWOWPafAftEleNLsfckpeUJu1OKOI9PFNIZJiRM4RiBhxUBlhSWh96pUGYOrCHCM5CW+Q+halVXCQDslHDwGbFx26NeBtRuM8dErJxH9mLDYZrRTQrdejjXSYI53Ce1MScD4gLH9BMF1nB0b7TnM7zndpGZ0CEx2TyaEoymjnRHcguDHK2xSpUqVKjgtpAYYkAAGo/PHOO6fx+7iY5jhCEueYTqd4vbuMdaaEe7fPoP1xgFzh53dGQ4P57h0dh1947HgDnMijEDYXhvhkQe24GmO27sfw8XzD2FrYxv2l5EBTI9v49kn34fnP/V+dLMlevSA89g8D/jmKpZTB24ZvneYNj3m/QxbMChqdVey2ecMEOoV6V82FzHF/6JHw7MtCZ0JNlUq1A0AseUttMSYTEZYWx+h73vcvnmIriFcunQOPXsc8/NYww2M6aEClEZQbGeswSmFsSNdGJTjN9HPLr+xAfFRTzGG4SeNI7Q+EJsuAUekmfeQbEDhegbbiY0d7Ay+7MFBA5KYDRAhu1pTLCN5TRpDRjTpgy41G1QFwijGVsjeI3CU4kIAs9yMlEBJZcnCjIwAyb/ijWHrDTBtp6oYxbkhSSlvSwHqq5ZMJa9J1qRk5TLEBBTVN+QCQgRzXUJxY1iod8bWn+55okz3jDvI2KQlgFpPiHnhbGmZ3I+SUECuDUH9cfPLuI+MT2OXGkn9YVjSWYo9TvnR7AEWpm6vNfd2GS8jdjNlU82yZHCVcYhAA4JU5eVKMyNs3AbG+4x+EgLbX42MpozJLYd+gkBqCiEGNp912LjhB55ymzVMZOMaY3EuLE07rTK/wFi7decym1c8qHM4eOz09qNKlSqfWTk1pKaYRAUALP0B9hYfx9HsNpbTGab7xxg3IbXwtZ1jbI82MZ4QOu/ROMbm5gjHPsTVYEJgzzheADd29tHAYet8j/sfuoC2bbW1+I5fLo/xyU/8H7h2+SOYLw/QbgEjbnDu0jnc//g9IAd0/RLdFPBzD3CDvb3L2D77KEajtRxIxc/DwN4ceKzCEhZ7EGk6XE6A3oBFqccQhnCEE1DyfIzj/hCH0ymWyyUOD6bYpBZLBo6mC7SjEZrOw488KKRwSpPFJekLY0RmWU4kOqTdt9jM2jhB/hJjWjIYm28aQuvCvjiS8jacCyCtobBUzXO5PC+jVNomFN5ztGGWkpqGZYVgiOdEiIfFq4mcMcWYo7znukcRYdQQGmeAtJjD1F0Ki6GM66wkIGr38Km8q2xiBY1v0TrILocyNtD2aMXeQeY+sLTD3ARK+PL+2P/szU560yUvlm4CmhMFe7+r/kqaQh1I48FQz4puYim6KkkV2/QeKdg/ZC3z6TodBLWBTzfESfyATvishpE7hcXVNKghlsiSX+RPm60vlXA5qRyUi8vqKq955bL5AqNZMHxLaKcM17/6OrkBFttDwumWhNEeYXzw0pe5uS7sg9Ofmrf9UMZ7hGb54h1abn0alKlSpcpdK6foZ264tnvc3IPN0Ruw7JboZh5uzQPLHq5tcfF8i/Gax9wz9g/nOJp2WFKP9XWH+bLHGbcBcgxedtjbm2J3r8f4xgLjyTU8cKkHjwXIBNJweLSP3d1rmM2Psew7cMMYTUa4+Og59C2hZWDjXAtHjCPvwZij627Dcx+BLiuoYQa4A3UzsO/D8hTXwJELICNCsh4NwD1ADVyMQWEikGvRe8T17h4eLgLBsLDEw4J5A8cFqJppX+89ZrsNbux0cJ3H7LDDvWdb7C6WwKLHU1cPcaa5Bdp+Kx555OEEYsu5ZvmeyE0CmrpHiwbQRx10ih9CvmAA4GrwFso2FDb9HDukvXH6CEKZQ9UBr6ktcjKjBMSSSwYiGIgnCtAvo5MtBbPqpuLG+lnDOQGRuJSgr8Y3rOB0plpOngMkUqFtykAnypR4TyQ2bJ0diXmFfpn60t44VmHk5QEZRlrp7RFFwinODp8Uu5KKGE+jvUb6QHFZF0fSwpzHddm/soQxLW8DYjIABns7GWDsCqE8cXmZ11TLmpJbvHCsvxdiaYYmbIApDyUhJ4thfTT4aEhxQSbtMyQEsqxaYgUTcxYCJiA5r/dkz1KVlyIHjwJu4dBOgfEeMD589bZ0i0BsUNxe61cJo0Neuf/NSdLOwoafkjDArw1jdTbvPcLXP/qRlddfm5/BT//S21+8IQbc7EWyG5xwXfsSl+uNDoFug9Bt1fu1SpUqQzk1pEYgYsKZRHA0wYXJl2KreSuWkyP0vsON9kM4t/Y0pvND9MslpssOy0WH5XSJ/YMO+2DsTxdY93PcOlyid4xH7t/C2x/bwHh9hOn8SXz8qf+Ad771/4LxeCut0z8+PoSnEXwPLKY9xmdGePAtD2C0sYY+RvazA5Zjj+t7U5w/s4bN5S3Q/ArW6Sxa6sBuBPgl/HwfFPOD+b4Hk4NrxyByAPo0K9z4UAayJp8akGswnmyCPYN9DwaBmnX0GGOBMTqMQNTG2BLNQiYWVDAMeD/HYnYTTz15C5969hCTtQZrm2t46Owabi1aHFyZ47mP30J3sMTxu5/GGx95D5wzHoZitt0h3zhTjvvYppAbxX765gyz7/qGphX1iCRAKECcgIbDcrReADxLSl4LH5WoCOBFaldLUsNoQHHPHENCDFFIe88YwGnFpnIWW1mvBcNifPV2CEEYwOCM5eSJiSnLokUFICHZFgWyR0oA6iGGSIZBoj5WkyoTCyJlrAaGFIp9hURbjloS7aidek0IkKQBYj+b8MHAbEiaa2nLku3SBClYn9XuaVNMSxoM2esjcfFeN8VMY6HdTJ8t81ByNCQ0aeyyUysAWHkpIU1GiA7B+WcVkfYp2dUmwSg4+gC4Wk+dJpGwd0L12LxsIWB5JtxYi57QrROWh4RmxljbfeXAe/Oax9oOYe8thOUWp7FfngFm9wKjD728ZW6z+zuMz8/wRQ8/j7/y8A/jnMvJx4RabLjxymt79th/+EdftI3LPeHPP/eN+Oj1+zB9/gwAvCRvUntEKzOerRJugH6jEpoqVaqsllNDamCASsokRgBRg/HoPLpFj1vXPoS9nX1M5zNQ22PkWsxmC+zuT3HjxgwHez2OZh6jcYvluMdk3WG29Lh2a46D2RIP3n8W9z/QoKEbODi6jPOjt4LAWC7meObJj+L41j5818OTx5nza9jYXsPCE8iFAPXpbIHJZAS0jGdf2Ee3cDg3+QC2730TXLuG0WgCcg79iNF3PZgajEYbcZbYo++XYL+A91PAz0HNOPW57xVYLY89iJYg18M1BOccGtdggrNoeQ0dr6NvN8DNNjyN0VM7IDaAx7T/JI6nl3HzxhFmRx129xcYjYD7yeHqzGPn+h72rhwCHnjuhaexXMyxvr6RjYnUZ3FVOGZ3b0dsEdEboGRArhFgGHBUXpmZ+9aLMtRMiTQxFA9q4Hih8IpAeuutaaIeTIMrM+KlID0na2S8GDbrmE14ICdy8kCxXG63kF1LvRSZcCCELuolRUpMnGoitRcMSHaJSBUkJWkQ/6XYSgLv1kiK8i2RTNamnAzLXjcQVXTgMtKGRMgsYVEly3tvJaGB3qccdXQR5fcMcPzbGRLDlpzZusW+JbmLX22ZXMgMeB7fldVRVpQ1PuA6SkCYARfHKe0hFLLTDfqg9GzQLkfSPtStYItVXroQwA2jmRMmO68+AxoAuI7h5g7rR4Tp/R5uSZjsAO7ay4/b2XyqxXf+uh/Eb9vaB/Dy1nA15HC+2XjRcucb4J+/+d9i59FjXP0S4FcWD+B/eOI3YNk77Dx5YaVN3Jww3o+xXS9B1m4xpvd+7m5OWqVKlTvLqSE1lL1Qc9hCBHi/xOHRTdy6+TwuX72CZcd44N6zwAK4fctjOm0w7xiHyx40X+Dc+U34mKlofY1w/sIENCLs3lzgwqTH5nIPdPsjuHFrB1f3l7j5zCdBywUYhK2z6zj3wLmQsrgJr/1+2WG57HF7d4EejKN5h1uHU3zg2adxZnIW73jkcbimQd/38MslHC/g3AhNE/rS9wt4B6BxIDoD15wH+w7gHm27BteMAUfofQ/uFvDcAeRC3AjN4Zp9oL8Nv2Q470DLdSyXawDW4UZn4NoJeO08mBp4asAgTNwbMKYOD9/f4cbOJ+AXHeae0fMY070lFsc9QB5MjBu3LuOFFz6Ft7zl85ECiIEcgOpEr4xM/GuPIWU9UzKjY2nB76q7QD8K8KeEtRohBRF/+fg3vd64yLQlOpoZdUtOHAOawtl4DBIxQVqyk7JtSZnUH/2cSE9ExDnxSPPrEZTKSSVfspxOrwgtZSA/8zzoiz2RAcPUZNmWxD3JQdU9ktABlrV9LY4z4kaaYkfKu4JA+gRQr4pf5+x72JiTig1JEx8FktUSaTcVeAuG4jhZC/Yg9J6xsGQmNS2xPJZNxAFMk+M5LbUMqyRmtpiSCatPQTAo+2ba0+cqPUOR3KYWReW0zBOJFEptOu1g2mX7/BlCmkpUVvNKZe2Gw8ZVRrN8bQB3t0ZYnmV869f/O3zs6D7sL9YBAB96/2NY+4WXV9fZZzy+8yPfgPf+qn+Mhl7BErGXIeebDZxvgM8b7+Gb3/3PseQeP/WOMZbc4i898Q24tb+J+e4a3GGD0QFhcZax+7jDuU++OBNsloz1Gw6Hj3C9VatUqTKQU0NqLKLJMS+h7+bY2f8EFosXMJ/ugfwce7emuPLMDh598DxeuLKPuWuBpkGz0cIBeOyeNVw57PD8QYcbe8e4sbPAPfcu0Y7nmPseD2xtYGu0hp/8qQ/gE5dv4uh4gUnb422Pn8W7v/RxtOMGBwdHGK9N0K61mNMSbuRwz4UxxpMxnrs8x97uEuvjEZ65eRVvvv8xUNdjOTtCtzhG047RwMP7OagZoe9D1i5ygO8WYD8F+gWaBuB2hvUz9yCAQAbGG4BrATC47wF3BqCL4GaJno4wPboK7w4wGnks50v4gx00oxbt8iaonaBrNrDEGMtmhpZu4YGzPT7cAo4Za44wboB+1gev0jJAvMXxMXZ2r8LzuyKALzKryWTxiheJS7PpGqfgoZnSTMlQggxsW+1yQEJ8pECPKNywstyqoYJQGcCe4zgqwGOc/yb9Jv3N4jIIeVC6AZuAJHEQTGk+J4xs9SDTthKD8ni+HEv7rR6IVR4A24wBr1D9k9ZpeZ4sA7M2N4xVYnFKKTNzFaTCWlgP6f40iaTYakxKall2xqzG1CGhrAwg3pjYRmyQY8ayrmfMe5N1zox7RkiyL0iK0apTWo3WxxwD7vMykkhgSF1UX5ddZ/ZUktrZkGVTKn0SInxCFrOk6oB0ZWeRk68qr0Qkg1ezRNo489V6bLhl/P1f/gqc+6k1TPbDWN37Cutqf/QcfuULl3j3ZPLqlHqZMqIGX7PeA+jxdV/wLwAAPzPz+ODsjfiun/9abH14gnb60utbv+5x9ODpzuZWpUqVz4ycGlJD6BHWVuQvV88ex9Md3L72CYzZ4ezWWSyO5zhoGXvzI7g+xNMcTWcYb60BzFgul9h4cBObjtEsl4ADpkcLXL7isbbVYzlnPHZ2F4dHR9ja6vDF79zEE08B+9M5MGL06DBfLLFzNMPRraOQQnNjhPmiw4WNNUzW1vDQGzfx1McPcWE+wbO3r+H9n/gVfN6Dj0bdJ+iWjCaib6Jl6CMB3C0B7+Gcgxuvh3iRyUYCJs1oA3ANwi6UDEYXlr91cxA1aCdnwPNp2F9itIHlmHB0eIjlfA5wj1HToAVjPBph0jaY8RHWRh5nXIPOOWysMbZagp8tQD1hfWOCxfEMy2WH69eeQt8v0bQTJDCpAwQyoIu5AGBkZpQRI4qYdG8WlDPButcIsuNIJZUc5HCLbHFWYqOxJZRd7y3zSX3JSUQC4QJGjWqie75szHgWKNdZ6zLL3NKl4gUwBQf0xCgjgD0aN6UoZiBNuLLtg5AmQxylpyzJAUI67rJFG2chNs69KtYaqqN24ySQQYLQ03dZJpdn81I9BzsKkSXIZE0DTsvclMgso2cmax+ZdWM/XfTG5bqvoItCYeJhW7eQLVHIcHXK69BqKcVK2QQbpZC1XaymfFJIGj/J/gzVMRFtJc2D/bOqrBbilUMpsnaTMNkPLKYfEciHfbdeCbHpJuEG7y8sQT29JsvZ1nYZv/MX/iA+9BX/6HX31ryYfOWaw1euPYfv+Nq/hz/37nfjn/3YV2J0FPrJLiQ3qFKlSpWXK6eC1Dh/iPXDX0TfnEMfgxUZDktusLN3Fbf2P4auOUZ7OMfW2GH7874I7/78i1jeeBrcX8HHntnD7t4Ci50e6IHeeVDnMWoa9EdTdPBoxg3uacd4cHsbR/MFnr+xg8PlLjZpDiw7bLeM5bjB5j2boAlhfrzErRtHuL2zxGK/h6cWbkL44i9Yx7ht8fADGzjYWeK53WNsLkfY6T6JC2fO46GLD4F9j25+jG5+jKZt0bQt2rZF6xy896BmhKYZw7VjuKaFa0cg58DsQ5Y018C163DNCH55FNCr34jAhNC0YyxneyBymIwJa6NNzKY99vePsXvrFs5fOIf1cQMsjnFvcx4XLgAP/dptHB0foe+P4JoFnnvmFp66PsVD9xCWszEOZsDs4CkcH1zF2QtvBFDMUieg5gFyg3gWAd0yCy4b+knsTYKFJJ90Jj4hswTYctiWzyUXyWljNSk5QmovMawCNCMFTJOpNbVmiAwVQNcuU5J4DAt+NZTHAHCjX/S7GP3N0rIMdIu3Qk4p9cq4hRRyK9mH2jyShNxDQXmpjGPZXhVxJ+aLlhKjDYlp7r2wwFuIgPGusVZPxWWiU44ptY3Oe8x7xqLXfWTKuC61/yodSrSakyrxLmXLu8xmQ+oNCQOe8d34qYylCvsVWXK5wn4lyyjvZVsfDff1ic2k3ucDSckwfCIhrSLy9nPX8cW/+kO4Nd9MxzwIH/rgo1i/6rB+Q23Yzhmz8wT+ul3s7W7g0r+d3HFZmp1EObrPYfYVh+gWDdY/vo5zT8SEMq+BbP3IFv7wG78S/+vDP/ea1PdqpSGH9577AN7+3st4an4vLs+38QVbz+NvfPBrAACjj2zg7FM+S5NNDIwOCYtzd7BJZelVqnxOyqkgNcSEDXbgfhcEB89LzOe7WMxuYP/2AZazJRowjpoOrSdsun08cAa4cPFBXLt5iC9/xwP4pU/dwuWdI7gFod1occ+FTbz74fvxJW9/Iz7y1GUcLha4fTAFLQ/Ruh6z5RwXNxn9sodrG9A2Y41GWMwZx4c9Fkcd+lmPftphbdLiwj0bWJusYW20hcWRx8L1WJs43Fj2wCGhxwzXj3bw5ofeDCKgHzss51OAGd736JYdRhtnsba+CTcaw7VrcWa8CWCkX6Jb7GM0XgO1Y6BfgjnE3LDv0C9n8N0MfjEFA2hG63DtCP38COSX2FhrMBmNsb15Bn0/Qz8/Qt/3aJsR1tcvYHurwXIxRbdcgMH47V/zAF64fAP7Bwe4ev0WdqaHODNZ4Na1j2L7whuSl2HZTzGdvYDN9TdiMdvB9PB5bN/zBXCutVPRaRZ7CLrDF5+VlLgb0pljIIGy0sOQvZdYIb4SJXMvpVloPRdSZedqab1cAO/YDNsy2lUNLh8Gy6f2C7eAkJ00N06qO6Vr7Ax/0FtAc+RJQ/0sSaHcvnJN0DUyTEs+UiIDaxGIoisMIue0nsEIFckR5HLjZMjiOfI/ujTNEjlCtLng79gnz+KN8XEvGU6Z+WyyAU1jbFUqdIgmQqZbfheCYfYiMlcnkm4I2glYy45VspdLGSIyEQIl/Ze6c1ovTFn1tbTFJsdI/WGJKzI1VeD3kmQEh7//hv84OP49992Lv/jzvxnbT+XZw0aHwMH7L+Dce26B3QR7jzlsPzV0uSy2CA//10/ilz/0KNAD5z7K6C5voD0mbFx5bcnmaMr48Q++CzglpAYA3jMZ4T2TmwBupmN/5Ku/BwDwqa88xNPdNr7tp38fzv/sOCzB45Dy2s4qkQdGew7Lsx7tkcNkBzh6xK9cLl2lSpXPXjkVpMYRAf0Mvmewa9BO1jEeX8LR3i6OfYcpL+GXHagFwIzZ8hhXjxZomn00owV+45e/Eb/uSx7HJ67u4GbfY9nP8cDGOi5ub+Hzv+ht+KqvALplh2s3bqEjxtW95/H8tcuYLY/hJwx4oN1wwBK49cIhXnhyH861OD5e4OCox2OPXsAjm2cxPrOG6dEcy2mHawcz3DzusOwdxo3DctnhY1eew9seegPuO3tPyFo2buD7HsvFHMv5EZzz6JZjoAG879A263DjTYA9mqYByKPv5+C5B9gHQNvPwX6J471rGE3W4dgDLhCU/W6GZrHEbHcX3XyKhx9/K9bWWsyPj7HoZ+imM4wma2DnMZ/1YM9o2jHINdjeXsfW5kV477G/f4jrN67i1uwW+ukuuF+gHa3B+w77hx/EdPYpEAizW0+hm99Gd+ZRTNYvFDPzWA3maHg6zZgzInlSYCiL2la9iyxfsB/t1ToBvSpWwQJQAcgWLAaRVUsZ4YJwAxN7k1GT8N32UThAmiMn1UITMZjeUGgzm90nadf00noM0rIiK9YO0nvOSxGl2fl82IbeAj0sbIyyc7zyCjJ6rvIfRFCdCF9OCLOsZukvo2Ng2fu0KSubGtMWUKx6kOmnpSn2yLAX5s6SMZQbJrv/CBlxktOJjayuN9GJdHOsIFlyjBk2sYZ9NhLxye4Bk8o7ihciI3ZMheXuEBI5JIBVTpY9P8VX/PwfBH5hG/evICvNknHuCcaVx86gfQfwl977vbjVb+G7fvY34v6faNNExfEDhB98/MeAx8P37zs4j3dMruAvPveb8cvucdzzS6+t3ud/scVPfI3EuayWD87neOuITkzz/FJlz0/xa97/B/Dff/4P4Os25i/7+jePtvDmUY8nv/bv4we/cgs/vf9W/Jt//auxeZmx2Cb4SVjet/GCw+YVj703O2xeZrRTxnLTYX7Pa7Bu7zMoowNCt8kpRqtKlSp3llNBapg9mlGL8foERC2YgZ2DHRx2M+wfTDE7XqBbdvBtB3LAuF/geLfFdDrBA+e3cfaMQz9f4N52C+54gWU3QjftwaMJlgwwN1h6j4uXHgAcsL4+waKb4hPP7eP4eIGWW7DzGK032Bgxrjw7w+7+AksC3viGbbz7C96Is5MRptxh0oywzg6bkwlmz+zj2t4+RmcmaFqHT9y+gf/8zC/hy+97FP1iESdiww5qbjRCt5hjOQJu802M3Qj3NmfDsjMPzKYH6OaHaNsGG1sXQEToF3P45RH6xTGWxwchq1o7Ao1HWHYLfGrnMrA/x3j3AG9406NYO/cg2vEGthiYH9zAwY2n4f0C3fwAx/sH2Dh/CaNRC7iQVc2jQ+Mczl+4gHPntrGYT7HoOriDp0Dbj2HZ7WK+eBLMMxwd/GfwrEO/PMJ8/ylM1s+nIG0FkDoDDNiJNMoAvpwQXJ9H51gPALJ6VoPvPHDe4skE4BKcDY2OHID5PubNVpgpNzPa9hWYxwyVy83yEtnZomBaqmZtUPRYA/YVzMo3ux9JvgRKGrNtRb2SvlRcVC7nEzvlwfslVVIgDhO0b8gKq305u8bUk64tyFQxuD72w3OwnQeSN6ZjTiRFVt0JkZB+lNWuCoHPaUQ2MOaMTQWuPsTyjpTljAO+dwJBEA4UV5Ma8m0utg9VcccISSUzVmVGQYlL8vqQJf3I1J/qJKDippcn224df+BtP4fv+Zmvu2O5+/5dixtfynjH5Ap+9vjNaG+PUD63Vr7lzA6e7Tocd2Nc+NDJ5V6prO0yvv2Hvg3/y2/5+/jajeXKMk93F/Fbf+x34cz9B/jl93zvK27r52bnsPXPzuKPzX8HPvFr/7dXXA8AvHfzEO/d/EX85T/48/gzV78M1+Zn8TMfeQvGV0fYvOJBjLhUL0g7A+bDH+27QsZ7Dvf8Uo9uPaTvvvHFlDZPrVKlyslyKkgNQGjH63DNGIvZMfZuvIDr09u4NdvB0i8xaRv0iyXW18foqMd8xrhx5QANO1wbE/p2EzuzI8znC8xaxqgdYTGe4AC3Md7bhRtdQseMETaA5QLOL7Gx0WC8RtjZ6bDsGM3IYX2zRTsKO5Dff+4sjnyP2YxxcHSM9fUzWMxmQM/wzmEyHuNL33EfmAkv3DoGHzusjYErR0e4tVjgwmQDa+vb6LjB8cEhzm9OwMS4xjt45uB53DM6h/vW34R+PgUIaJsJJmfW0TQObdNiOd3FdPcq/HKB0WQN5IHFbAoa9wA6XN+7hb2dXRCAd77lEdzzwCPw3RTHhzfRL5ZYHB9gsnkBa2cv4vDWC1jM5rj00FsBAhbHu5ge76GhHk0zBjlG3wNuMsLauEV//ClQdwvjlrHBLfZB4OMd9EsPTw7Tg6ewdeFtGE3OoPdLLJfHGK9tQ+FjvpGiXQKUZrKRB4gPfq5NpqzyvLaS04qS+ITJdQG7SKt0PAhuvJ3Hesf6JPsZCXA0tRt8OfBAWNKRlkqJ5gn0lvvqcDZTLxSDtYEB0C6dYzZFc6ok1qnbyijolpTHMibqZFBCmAwxwNixrbQsTustqQQNrg0fvBwg0T0v1LMQl3iYOXkaPKJXN3k4OIH3ZGo1pIL3ZLMhKEj362CZmiEwiSiuqkVAlMvuiSEJNzWTtBktSncuf0edoYRGl5aVhoeSGTvoRZ3l5EKVO8uen+LYjzG9n7F1+eRyrgfu/U/AN238t9j+0AiXbqz2HjzfHeIvX/v1+FsP/ize0G7h0a3beOq9F3Hm32wNAucXm4TRlNFNCM2SX9K+Nd0k/CY0C8aZpxz+ylO/CV/7zh/Kyiy5x5V+ih/f/dW49L4Ge28+h/mvWmJCoxdvoJDr/RH+7Ee/GWMG2l/Zwjc//DX4/jf9xMuup5QJjfDXH/hFAMBTD/1r/PGnfxs+tPYYLvwKoZ2rndavM6b3EfyIQT3C700zvPdPoyzOetx6R4ONq4zdd3Dy1Fep8rKFAerjTe8++71+p4PUsMfejedwtDgE5h5+uUCHOTrfYzpb4Hhvhq4D1pctNs+Ncbw/xe39KS5sbGG5c4gpLbFYdti9OcOy73Hp/CZGG2P0a2ewvnkOt/wunl7u4X43wr0TRuPnaNsZ3vjAOrZah2c+NUW/9OiOe7zt4Qew3q/hS975JtBkA0cNY7/fx/7BEdB36JnRNA0W3GN7A3jPu+5Fd3AWn3z+Fq7N93DtygIfOLqNUX+M2ewFbGxsonXHePMbWzSXRrh2dB1L6nB7fhuX9z6GB7YexdraWXC/jB6ZIxxND7A43odvCGubZ8GuAZPHaH0Dx4s5bkwPsNNN0bQjdGBc6+Y4Mz3EWe8BIky2zmNt+z5QM8b84CaOdm7AOWD/xpOgxsF3C8wO9uH7DufufRCj8RoWsym8c6BmBPY9mrYH3Bjr/hI2Fi0WPMUBH8OD0S8PsTh8AePJ23C0+wSODp/GvQ/9OrSjtQiq8nn+MkoG2VkppOBfypK5Nq8vJw2pNYIJvFZkyxnYjaCYYjIDaTvW5wwqTuSJoEu1dPo/EYqEm2Psh4eQB83KZTOy2R6Jtj1z1rb21HQnZ0vxeKQWbKyjQTyZrhlpgk3gUBgYBiibuJ6kkdnUU7wziaxIRax2td0J3gklQ2FjzNB/ICyV6lNjSsQCTzPxT2RpLKE0nYzHaiJiVIr2cQSw77GYXUbTbKEZnTPkKb9Gkw30WDSfAjxhxI+CMILd6HXlxXZILfmCIdUAbKyO3SrT1kPRVZU8X5RdGu+1qCvjBFtY9lmB00uRb332q/A77vlP+KXp4/jXz78Ll37xxe1GDDzwkw1yX7DKnJf4ul/4Q9j4obP4rb//HH748R/Fb7vwfvzoz30hll87Ba6s4d73h7K+Bfa+Zoqz/2Edh7/uCG+7/zo+9PSDuOffTTJQX8qZ//oFfN72NfzYT34x3ILxpskx/s3xGr5hY5bKfOPHfwtu/pM3oFkA7YJx/mPA5/3EH8J//6v/edy4cyhL7uHhB8Tn1/zv/w9c+BAHD8qnPD78I2/Dt33TDH/vkZ95UXu9VHlstIUffPzHsPfmKf6H3/Cl+Mcf/lXYet8G1m94dBtAexz2wVm/5rB2i7HzTtwdcTaE5Dr9bAehVV6eUEdYu0Xo1oHl2Ze2vPLcx4F2yth/zGF+8TVakllArU+b5LOoAzk1pOZXPvpBPL1/E/ecO493vOFxwPdoO8L6pMXGhTOYwGHpeiyaHuvnGjw4OQPAY7GcYTFfYjln7O8vcDRd4Nb+Me69sInttS3cJI8byynQe+xwh+3Jg2h6B+6ewM3np7hxa4HJRoPN7RF66vDc9Co271mDd1M8fGkDt5fAjesL7O4dYty3mDSEvcUhfEtYnOlw37lzaNseD65t457xFi5sr+ORe8+BO49lN8ZycYjl5Bi3N4I35Nb0EBtrE7Bj3O5vY2u2AVoco2km6ObHON69AWoIo61t3BwfYqc5xEV/Dhvn7oNzDZbNAZaH+2iXHZaNB7zH7tEBnmmv4fMeejvG5HC8fxPT/dvouwVG4zWsnT0P1zRYHO+j7+aYnLmIMxcfRjuaYH37Io5vX8bBtRewtn0O7doWmmaEbnYA165j0q7h0uYlYGuEw6N93Dy6iWO/xGK5g+V8D0c7H0O3PMD86ApG5x6LODCAOQGMkmp5JVwX3JeW/+TEJhyxpEipDBmkluiB8XrEyfy4jw4p6CNTayRTligpyDT+B+tNMSjUx9l2ihXnjgGCR9pu0yy3K/0aoT8+2SiPFQEYjpF7Ukwboajdi8X0T4Bs4V3xUr9liklXs0llImVazhIcWSaWa6u9k31WxC72/exjv0NmNvE2mBqMByK1MEhFbZItcL5EjMgp4E96L+H5NgjnQTTOkjQsp1exd/M/YXP9fqyffxdce9ZklsupNAHoeA/Hx0+gdT3aUQOiN4BolMrb+1a1YjBH2ivrzzKrEXx3iMXiCsbtJdB4u6D1XN6k5quJ2TJEPEudLicL6bspFvPr6PuXH/fwuSbv+9HPxy9dexcOvmqKz3voKl44eyntIfNK5MzTjPd81/8NaweMds64+g8ew2/5/V+H33jpw/iCL3waH716HzY+5SCEyHXApR9eA8DYXTTwTLj30j5oec8d23nq4w/gR977A/jvfue/wyLeG2MiAJt436zHH/votwDffw/Ghhi5Hrj47yf45S98BL9t68ODOpfc423/9tuw9Utr+Jbf9xP4M/d8HADwn+ZLrN0guF7r2n7S46d+/AvwA7/jV04kSK9Utt06vvPSh/GdX/1hfPDL5/gd/+nbcOEHNzA6Yuy+lTDZDXE2k5sOs3vv7jibKp/94haE0SFhuckh7tvI6JBw5hmPxVnCoSN0W3f+7WkWhGYRnuXRIdBtEvq1Vz+B1cwJazcJs4uMfv3TMyHmloTxDgXP6wlyKkjN0WKKT167hpnvsOh20PHTuHjfOTx47hIe3r4PV3ZuYL6Yh5nXloARY9QQ+n3GqGNsLEdwa2MszxBuHc6xmHbg3SmunD+CP+cxdQs4OEyXUzxx/BwObuzh8vPXMTtcAA2A1sNPPJx3OD5Y4vbhAof7jG5jjAN0YPLouh63bs/wzktncf7CNm5TBzSMvfkM921u4C1feC/WN9bQTsYYewfnCYt+jg985GNYjjwurt+Pzi9Byw6L2RxLcqDzhN3JHrabcykwf+PC/RhtbGG/v4W9w6uYTo9x9swZjDe2sew9bu5dwdH+IfZu76MdE/pxi/myx357gOevPYHNRYet9bM4e/4SmskaxpvnQdSimx/imAjjs/eiWduGA6EZrwPcw/NVnH3ozdi88AjgxujmB1jefAbTg1tw7QSuXUffz7A+WcMbN96Iw+kejrHA8d6T6Oc74L5HN9vBcnE/vPeYrG8mxwIQwW9E2NmtXzKdVP5Oy2AswQn1CVBOM99sUF/E7fkzEEFeAnjaojO1I3ohZPnWKglzr6K4xDnk2icSEAE0swGfA/oi7eo35rCLky0rQD4DvEkNzjbVTGSKkHk6sol/Oz7xuG7zoj3yCDEtWdC5IUKZxJvAxtD0CfCrpBgaqc9kZxOyGC2XbCvXC+fgwtOXwfy0lK7HYvlJePcs2vZhtHgc4DGYPZZHz2G++yE0LaPz1zA/8Jic/UJQs4l+eYR2tAmiJhmu80eY9R8D0RxMHgt8DGPXoeU3If2sFmQPYBzsX8at67+ES/d/MTbP3GcGQP50ONp/Avt7n8SZjUdx9t53g6g1lVDusZI+GptSnCDIw4RyQpZGhAHPPfZ3n8D+7sfgu5exC+LnmHz0+Dze/vf+MM48wxhNGQfPruOZ978J84eA+QXC2adfPlhebIW9WTavmFiQOePqP3wM/2D8GCb7jIsATvLw+M5ho11g+mOPYdPfuf3NZxp808ffi7eevY6vOPMEfs36c7i32cT/6/rn44f+yVfhzLOrU0dTD/zElbfhG85+EO+ZqDdmzkt89+5bMPnUGrYue/yrF96Fbzr7Qbx9NMEf/cjvwtbloT7tMeGHbr0bt/on8K1nn8OImpdippcl755M8IGv/G78nXd8Pv5///g3YHILGB9EQtgHwEgerwmwq1LlNRcGJjvh92SxRdh7CyVis/W0w/qtED822WOMjoD9NzoszzDcEuARstgr6oGznwxLTgFg/YbHcjPEEd8pRqs9Iox3CdwC0/uGzzF1hPaQsPWCh1s4HD/4+j9PQmi2n/JoFieXOxWkZrZYYOaWGG80WM4XeOHy8zi/NcK73vbl2DnewdM3XsCN2RHggc31dRD36Bcetw6mmIxaNBsTbK8TNs+O0N4c4fBggf1+gadv7WC2fojzF9dwvHOE+fQYy70pjndm6JY9MGa4ljA76rH39AJnNyaAY4wnhKmf4YWDQ4w2xuAOODtZw/jCGLvLBdZnhFv7cyzQ4YEHW+zv7+FcR1iubeFqt4+H24t4eONhHN7axbKdY3x+E0s/x+HhIfaeuY3uaA63PoKbTMBnHNoz5+F8i3HToF07A88dDnefx7SbwQN4YfYCfLOBR869CdsHt3Bl/hz2l8do0cBNCQfzOagh7K+v48GH34nz59+IZrwBcg1ALbifoWknaMfrgJuA2jXAjUAuvKDOP/rlADmwD+mjGQ6TrYuYbF2AoxZ+Ocfs+BCHuzfQLTucvXgvttcmOOwOcewIx8sOxwfP4fqVq5gdH+FdX/5etK1mzVFvBPJ35jBA5A53CWV4VfbBC+gtHExUJksNjUh8otckAc1QSZjgL/UgxdUGTOYlFLHKZH/ZHwnwV39BdqVcVPYyXatAV3wl+XI3MgQhm7w3eiihCDbxK/QUkpTOS9MZt4r7v3AeF+OkdQHSqRPq85E9jUJ8jNjAZjcz40XChXJiJ5qKnlkPTJ8GZJg5ZqxjLPvL6PAkPC0BfhJoO7Td5+H6c7+M+cEnMV4DvGPMPaH31zDrfg6H+x5Hh8/j/ge+Ahfuf2esknE0v4J5dxXHmAJ9jzFN0bYfwvb6ISbuHQDW1bix79OjXTz90Z/A4d6zON7bxZve8XVY3ziXyvXdDIe7n8DR7Bn41uNo+jTGOz3Wzr0DrjkTx9b2MrdNwXSQyGZRzNpmvtjD0eFT2Js+DfbLvI4qmdDtFhc+qi/4Sx9kHDxM+IHf+9fxjf/+j+Ls0y8/7qQfExbnADBl6Z7bGaOdnXhZkgd+bITn/s/HMXoJM6WjfcZbztzEiHp811/7FvyFNwK/45t+Cr9w+w3YuHoHgDNnXH7iEv7s6L/EP3z8e/FwuwUAOPZL/I0f+3rc94no9/1Hl/B7fvfvxc9+8T/Gjetn8cCquo6BD/zwu/DTb34rvvLX/y28c7z+4p18BbLl1vAnL34SX/Ztn8If/9A3o/+B82gWjMktDoBsyth76+vSdJUqr0rGey5OMADjQ8a5TxCO73doj4D1Wz6Ln3NdWNq5XA8xdsf3Ohw8ps/yeMdhdKy/K64P5acXHQ7fAPjx8LlvjwjbnwTauUc3ISy3Qga+JAyceYawfjPUu3HDY7JH2H1rUe61Eg7epq2ngbXd+Ftzh2ZOBanpOsbR7SXm4w5rZ1qMt9dxaznDz37iP+Lm4RF2D45wfLgEOo9u5sENY7LWYPv+EbolY+rnwJGHwxggYLkENi44dGtLNG2LkQdc02Ln5hI8XYJ9j549jnY67B92YYlSA0zbBdY3W2ydWcP2pQs4e24Ly67Dgnos0GN9YwT2DaZY4My5BvtHHtPbHXYWh1h7bIINzzjY28Oz7RRb3Rgv3Hwa/qzD+j3ncHywh8Nnr2O+P0UzARaHUxxc2cXhmUMcrd/AJp3BZPMiiBiL2R4OuyMcdx3ge/RocG12DcubCxwcXIdrG2xe3EDf91jnCZpJg447TJoNrI+2sDi6jRG1aNfPgaiBX04DIKUR2sk23GgDcE2Ycfd9AJd9B3ItGB5MLdr1C/DLQxAD47OXMDpzCWvbh+iWS7STLfSLOc6vbWDSvAXPXn0S89lNHN0+xs6tPdy+/iTuffDtaeJ8MQ/xP03ThvXBLCB75bxg7kRYBcjUCWO8IgqK0zIswdtQMGhPKQmQc7nXxNlrAPUeJMAohKmcR81BN2VaAmSDHlhnzS2Gtx6KzKfDWjYt+yJCPt/JhpBQ+gXg+FlokHh6mtiMj+SiZ0pZs0zyrLxH4nUy9SgP6WP6akp98GDYeWDrMUqxRMn7o2OpiRB0JMgcSxnZjG7GqMl7s+jm2D1+Fh0dguCBvsPahkczB64/+370fg/N+hbObm5gvLGGGS3Q7V7G8598BoweWKzDjVpsn38T5ssZnrn6MZzdOobbYMxmHY6mC5w/57CkFzBuzqHhNwA8SsT48GAHH//FH8Vi+gJo5LG3+xQ+/uF/hUsPfikefPBtcM6h6zsczq4Dbomtsy2OjpbYPXoG50ab2DjzFji3pvc0DSlxSjttj7FuhUPpfPhv2R1j5/YH0B3fAhEwb+u+HneSVbbZesHjN/+ffwzn/vMIJ3lT7iTrtz3Wb6+u+6VKPyZM7yOMn7wzoFjbZbz/b30x9t4CXDhiXPgI8K+/6J1w/+IiRos7X3vxFx0e/7Ib2CRdQHrbe2x/Ivu1RvMDF/F5t74DF//jGOWvBgBsXvO4+psW2Dozw7/c/yK8856Pvay+vlz56nWPX/jSf4Jvv+/X4md/9Atw/mMe46OQYGH9qguz0PJM9XdPIoEqr42Qj8/eKRlz6gjr10KacpFmzmhmhM1rJ/++jKbhWRsdMtauhyWW1AOj49UEYP2Wx+iIsPu2fClaMydsP4EUm9fOGdufJOy9ldCth2ejPSZMdnNdmgXj7JOEvcdfm6VtSSKhufChl5YMBTglpIZAaF2L0chh7ewGzlw4j0Xr8MytnbCUzAPzxQLrG2PMqYPvGce7C5zdXMf61gh9x9jdO8bST3HuvEPTnsHm+QbvfPwsNtbWwpKi9Rb3LTpcefIIjh3G1GA07nH+UoumcdhYbzBZa0CjBuPxCJtnzmCx7DDvlnDOYTxuw/pjD6AZAROHzfNr8B3hwWYTaxcIcz/FRuvQEeOZ+XXMxwucPXces+kxDq7vYjFdoBkR2rGD7z3mtw5wePUqmvNvxmT7AkaTM5hPb2PaT3F0dIAbT1/G+uYazlwa4Wi+h9n8CGPfgOHhOw/PHn2/RNf3GAHYPdrF3uEutta24HpGQ+MAfj3QLzt4EHh+DMyn8P0C3vdwzQSgEcAhyQC5FuQ7OAoxKPPpDpa71zDZOI92NEHbEPrpLRzt3oYbrWG0vonHHnwbbu/fxOUnfhHz40Ncf/Z9OHfpYYzHW1gupvjQz/0LPPSWL8H9j7w9m8lXYEr5XxvUrug2/c0mq81dVH4sAa+L5+Q3rFwmpuSjeCgtQA6unZJfxbgdUTHoqZt+hhlzWWaVURzjmpG9S+zu7uK10E0/IS4gJWYkHg8kT4wbTM8nBhRTSxMckJap9THY3ydyp2RIehAOD1M3CKEhAN3yGFde+HlMxpu4eP+XQKgI55fkKYjVfZbGIAujibZauVFoDuvBNEPf3Ab1Z0A+zCgTAzcOruDy/tO4cM5jsuixdzDFaL5EM72KnnbArgd3R+i6Ecb9GNODQ+xcvonJhNBujHF0/CSuPLOPzs9xc854+sp1bE0O8ebHtgEmbG2uY9I2cCOHZXMVTfcAgBEIwGw+xXPPfhTXrjyFhmegSY/OM27uXcG13V/G1pn7MJlM8MILvwzyN7BxTwsaAy0R5nsd/v/s/XewbWl61gn+Prfcdsdfm6aysrKcSqoqGaSSQUjYEYgeGIQYgYCGUDdmZhQMBAQzER0z03/QTQfT0I0Z4aKhBUIdgLqnsZJoRra8UVWlN9ffY/fZdrnPzR/r2HtvVmZWZVZmSvlEZN6z1157rW+tvfZa7/M97/u8i3aMcUuy9Fj9OU++vxKO+0CdNmcFG2fMl9ssxnex7SEhRJq2pgwVLnyFZOXf4OhtldhCYMozv4sIl37+5Q0AXi2+FnMrXUdGr0BojqHajswcY/rMGhv2lT8bDPgo+L9tfx9/68rHsdHzP06+jcWjkH3+/FjyZ1JEePltDj+dsfK7x/z42ueB7FWN+2uBEl3T1M//0Z/n9/3in+oMFepI7y60K6dB2Moz0KxJyovhLRPkvoM3CBHSsSSZwvxdX/8aq2QiUQ24ImIHR/dzJ8h3Bens/Hikh972qxujKSPFdlc3078ByeLlP6friGzlKQmJYGb3T4yJCMUdwezdEb0QFDsC6e7/fdv+mQnFr/H3o+qubiaZCHrb4VUTGniLkBrnA4vGcmFzgC5SPB6coC4tUUTyoWZrZYDD43xERoFvPULCctpQlZYsMWSJxBQpDz2Usb5ZINKIEwFnA0YqBut9JrNVdm4tMcqy+lBGXTliC1Xl2b/rKIaKzYczTJ4ihUS0gfncMz4oGawa8kECostpVFGgjUT2IqKQCOsQSGJwVGJJttZnNpmwnM5p5iX1siW0UJcRpSD2ItvzQ16c3uDx3jqxmnDt1lOUfsm1G9dZ7C6wRctwbY2aGunB15qqbfEiIpTEJFlndasF43rBi/sv8Z6tx4mL/Y60CElslyfBuA/16Yy/kATvqBd7CClRJu8clVyDt0sQApOPEKplsneLJC0YrF8mL1ZI+psIlRBjxLUVly+uk/6mIZ//7MeZ799hMX6OtQvfxMHuNcbbL5L1RmxdeRzva6ToFCGjc84G3FGcUXCOgvezYezZUE7cSzzO4iy5EOffODYO6NyuzigHnFdvjheEe5Z3xOLB5EdwJrQRZ4wSTpSpbv3jsPE47e3sto+P8Vi9ObGWPpplj2fJhjiq5zl5eUoUPeebmkohkGdOx9nTEo626zklTicGaies6SzBPDnEc/uIMTId3+DWcx8nyQuS/BK94WWOm44en7fjYzt/5u59fX6d06MBxLGqde/noPU3mNpnKHiUQn0AIRQuOA5m20yXDTI6VnPJYND9xlU/wVUNi/0pratQIcM3guWkpKkaVB4JjSQQWc738Td/nrFL6SeCy1t9RCrJckH0kda3yKqCtE8QS5RIAM3+eJvPfeFXme0ckCpFlA6RS5LU8w0f+SZWhqssqxmTepeNLUgHXe1OPzUMdKCcHFI3u2TZGh0VPSb356/CY+OMrlnrWeInT86edQtu3PxF9m7dJs1SnHdkSlP7hpg8oC7qHZxgPi5QX8Fd7O2IrU+/uvWSeeTff/GD/K5v/BLf8YXfz/JnL5BOIhvl/ecj340nOfwP3NYssjMdfLVD/qrx4TTlue//e/zx93wvn/p338Dq04FsX7K8Ek+KqQnd7L20XV8YVYuvWxH0O/j6QbaC/s0uHmgmknbl60tks71OpV1elCekBjin0JzFyy1/EEzVuRYSwfYEyfzB16/LBLLtCFY7CqhW0Lsd73NQlC5SrwuEFyRTQXr44MEUuwHhJOUlXtG84BURYfASJMvXTjjfEqRGCiARNAJGJieGgAsO0oCUgtY7hBd4KVhOPbODhpVRSpp0xGZ1M8OFSPQSbRTFigTjCUrggsdFT+oFRZFw6d2bzGq48eQuBzsNsQwoJEKCkIGmgoPbDatrNXme0XhLSANmRTKrG6wIjFYLgg34MjBcTcl7GmkduzsHkCr6aUHta6KxKG3wKmW+N2V8p+n6bMiA6Qm8AdkYbhzewpkMtYD9yQ7BOqrDCm0EQkdmezOGqxvEGJiWC7z1xNIzCx6fgfKBJM2JBppYUbeHpDJifYnOVojeI5QB0TUCJQZi9ARn8b4lhhpQ+LpBZwVCRFxbs5wddClJUWGyHkJ11SFRKnQ66FLbQrdtZ1tW1y/wnb/5d3L71nPUBy9Q9a5y7Uu/QFPN2Lv1RdauruPFPiBJ0hU2V78dIU8vwXgmp+Zs/HxviHue3HAysyBOPhhP1IuzAfOJoiCOA/2z2zyjAp2ZaejUHXHPWpymuJ0Z1/HuTxJ8zkgO8Wh8x/sOZ/rA3KtYIeKZBpdn3j/x5L13v0f7OJNqdna0x+M9PuZ7qcDZtLBjo4P7W42e/eC930C39mK+w/bNXybJLUqXzA6fJe9toE3KWYgjNYmz6hNn+xKJe16dVybOGkmcHkcgRsey2mPpD7E4kv4ljFjH+ZZAxWoRGa2kqAhSRIQSRKkYXBzQLpfgIIbAfFyyd+cQaytMdVQPJCOrawMoBEY3rK2mqCzS2JZMaESMNAQEDuIh0nyRTFyG5iGUjCyXNeOFozCBRemYLhz9QeBbvsUiJdzZf4l00DBcKQgmQhBIG5CFgbahqW9S6YJe7yHksWHBuS/y+LydnqizphUCqNwht7Z/iRvPPU1jIYuRtrZoKZEyMDDJOw04vwKU7WZNfyNCBLj0s5rP/+yH2ftW2HqACcAxkuVXDmjagaCeZPzQc7+Pv/nYT/Mu03+9h/uyUELyjx75BV764/+a7/s3f47RlyXCi5Ni6v6dbhIg348EI4gSpo8Lon6H2Px6Qbov6Z8J3gfXYWm/fq54qjpVOrJxpB3KE2tm2XJfoshrhc27iS1dx5clNHCk8L4UsT0BUaIrHrhzESCZQUgh349f8R6oq4hZds8cX3wVPXFiV9MzuP7K95GXHcNX9anXGUJBkgSywtDEiBYRJyMeQbSC5bjC+4htHbYNzOYN1bRh0EvJBwZpEtrQUgwkvYEkEJhVNaaVBOtY1JZk0Cc4ARIGGZTLmu2JIyWysaLYWs8YriQM10aoPKOWjsl0RjtvGPRz8iwh+sByUmPQuOAxWlBVEnSkV2jMKCMIsMGhnMQ3LcJ7wqIkH+awX5EbhVARmQW881TThmq15EDeRgVD1AKBYeXCBvvbd7r+OVWNWjNY3yK0oMGT9HNGztH6GoTmcL9ip65xD8GK7tNPRiT9NaQpCK7tSIy3iOhBSIRQtPUEhKRYuYKtJrTLQ5Ji2M3tmhyhNL6saZsS12rqumTv9h1ilKysrbN66VFkUiBNjtEZrm3ITM6jj30ji8WYw4NnqKZ3id5RLw45vPsZsgs9hBT4tqR2E/J087w6Ie4LpbmXnojTRd3rM8qJoPuOT8ywOPszPRMKH7uePUAtFWdUlvNx4+lojnPgwzEpiae1JeFYbToez5GicaI2HKevift2cG6cZ/Wa05Q3caJUnNFM7vvs/a+7Jf6ERJ1vVnp8Hk9e3atynVFlzo7s+LxYV3PjxU+wmN8iSgsysFg8T29+hZW193SKIee3d36c52gq54wHzp2iM0loRxG8IOJjSeWfBrlLqhXL2YRDcZPN/gq3xtfYX9xkpe/Z212QGcnG+pDWtp36GS1eC5QvcM5zOGuoXIPWkfnCUQRFsqaI0dLEGpEWmNUcLQRlWRJVYGXYJwDeBpb1gthPMEnOeLzNF7/4SZq2JCsUrQ2UPqBTRZSSnYM7DHcH3Dl8gQsXAu6o+shaRy4MQkFaGJz3+LjoSOmxksbpqTpbt3X+99ApaGV7wO29z/H8F5+mqS2hV7CsLSnQMwqVSbx6J+3mHbwyjvvlfLUo9gL6E5qn9CUuP5G+8gfeALzL9HnpB3+Cv/pd7+bv/OxvOzFlEAEGt46C26NlupTY4Tuk5tcDZCPI9+O5ZrZR8hXdtF5PqEqw+vSpG5lqI6vPRg7fJ9Fl99v4WmGqSL0iXpXRiEsFs3eDnkO2Hx+YVuayzrY52xXo+iuPT9lI/2Zk9qj8qhRO1QjWnoqvSZm6F28NUiMExaAg0SnL8QSiQyYJVSvwrSB4QV4YQrD0Rxn9DYNtA7HxGJlS7jfsz0o2HxqweVUSpGMxragXllGRk6aGZdtgq4Y7exWLKiD6A+RijpUe25dkq4bRxU3SYR8bIrZuiU2gKR3LwwlpT9EbpGgtkJ1JGjpTDNczyCV1ZYltQAmw1iOVRuQGJQwXNzbZ3zmkeXqP0AZGQw1CkPYkaU9RVw2ttMgYqLxFCjCJYTBaYT6bEaKkqhY0jSNrPaHxzLDgHYVRtMFT9BMeXhuxUgxYG14l6V9EqAxnLcE7gi1x7QJtUpJ8heBapE7R2QiZ9In1EpkNcd5h2wohJP21q7AKaW+VGDzV7IC6WlLOZ0BkebgNUpMP1pHpECklMTpMkrG6eomiqCkfezdPP/Nl6rahmsxJt1IQCh+WLKtr5OlmRyI4DWrFmZzOupqxnO6zfvHRo7DtSBm4z+3q/Dz/ae+YeN7FLB4HfUck455g/Xil+/86fvs4UDxKNTthWmdqR04UplPaEM/sBQQn9bZHY+vmB49C0RhPC4COBZ1z0f1ZjeRo4QkJOVWt7ussfy5gPdrGCXuL5947dUc+S1/u10c42s/44DY3X3wKLUq88BitqMqb9AbPs7L6GELK00+fYSUPiqHvT4ISJ6TxJK3vjKITY6T1Uyp7E2gJQXDYVGxPniS5cokoHEkSkB5Sk7C6VVA2NYv9OXZ7STEw+NZTZCmLRYMQAZkqpgeWZtkiegmxEmRasUgFi6bizkHNKJGsriTIFUXlLThPWbUopQhqTBS/RkOfcXmT6bLq0k89ICRSRbQJfPwTv8DO7CbDK5JpaZnO9skLQ55nhMxhhMOWDu0GEBWCiJJnSMwxyXnQV3x0hVTtnGdv/SrXv/Q0y1mLzA0iagSRxGiyQiFSgZX+HVLzDr4umL8LNrdm/MPpo3x7/iIfTt8ccvMX1l7gT/4fvshHh/9nNn/BPLB5aToBO+Ar/jZU3dlEHxdTv4O3JoodcV+9l6kibRD3z26+3oidVfO9NSsu6+IQ9SpIyKtFNnl1hMJUkfUvgO11pgAPIhO67urwbB/ivaHCPXC5QNXQrgbia3RrFx7y7fu/n9eKtwSpiSHirGV2cIDIU/prA5TQZC0sFo5WBgarhtWtFYKI1M6hhSa0HqM0e3eXFH3NlYf6ZLkmRI1eN4RRQMiId4G6rNAkXN3I2baBg55iIQVogUhzGIyIWUJbOxQG4wzO1yADWV+ic42NnqKf0Rsk2Ohpg2eyrFgTBblSTJsZKjFoBDpLkFqAVEzKJcvxElxgVlmUTEi8Ih1opFL0h+s0daCnFU56QgyE2pMOB6g8I+8PUAKMD7RRoIwkOMvueMbqqGCU9bBtizGS1rdUrqRpl8QQCM6Ct3i3xLctOukTjoqBs94aPkQWB7eo5vsIEQm2oi4XZHkfY9IufU4bdNpnsHGFfvBUizEChUp6WNviXYWrDiEEpJRk/TVMNsAkGe/74DczHAx49rmnKMuSoXMorUAImnaHEGqUOq6tOcJRRO1cy41nP83ejS/zkd/yI/QGa0dhmjjfZgY4Wzx/TqYhnpvVRnR9PiQc9X6BE1ZxtP69ctFxfN+lcYkuXetYZDm7q3tUh3gywPM/0i7zSpyueDah6p6xnyVI97TfObPdoztNPKUJ53ncmXEdj+fko/eSw9PtnrUPPiYSx7VOZ0lkBPqDdfprWzTlmHbhyHRCMSxoml3aZkzeu3gu8I4nx3b/Tf6MTcQ94z47vu61D57DxXNM3bNIucQgaENHSnDw5M1f487sDlU75dKagLplJTekShOLAt5liC7gxzWzxZTFNDKfefJMkGwomjxBSYVIAtF4onXcvNuS4ImXM7SNiDKibEArSZIqRKoIKjKr59y4s831lw5YzlqcDQgdSVKFkoKPfeQSiybispLV1YI810ihSRMNRLzzxBhRJqVp5+xOvkygYWv0AZTO7hXSzvx9et5a2/L5a59kd/s2B+OSGI8cDqeHZJlh5eqQioByiqpqie/0JXwHXwfIRrD/who/Zb6Vb3/Pi2/qWFZVwRd/x3/P//Ad7+Hv/u3fc99seXYQqTaPDAUePAtDetApAJMn3qnBeSujHQCc1pnUKwLVQL4bsH1Js/bG3ABF6NLeenfvL3pXTVfcn75KIvK6jy121tGvuM5XSGU7RjKPBAXZvqRej6/eTTDC4JokO/jaz/9bgtRILVC5ougPMJkAYVFBgFZkA0EuNUEEmrYrjk90inARISNpprn0aB9hBL2BZnlYUy5bFmVDAHpJTtIH50GowKCX8/BjCdZ77r5wiPSS+WHL08t9Hnm0YX1zHe1ByEBvLSVZ7epIFIqmanHW42oIMUFnHpMokBEvBP21IVFB9AFrA8aDKxsO7h7gdi3DngHtcTrQLgP+hmB6d8F85Sb99TWSUY+00DgCOkiEFOxu77K5ZdhaG+FcxVJYrHQ4ImmeILRmGS3RO/JGMuoLWl8eFT1bpJBIrfFtRKoMkw6QUiCM6RyvfE0IgWywgdIpvl6wcmkNkw8guJP42rcVyhRIY6inO9hqTKtm6GIVna8AghAsAvCu6dy1hCDJcq4++n5W1y5y7fpTuMrhlAMtqNsDZsvnWB1+qKs14kw6VIyMd36NnWufpJwtuP3i53jPh37L6Yz/Mak4phzHnIDTAPh80tpZXeA0VexcM8rzf9z36RiPVYbT2pt7GxzeS3JOx3iyqFtTnA3a79WbHjSW074vZ0d3P4k7Tns7y1vE2VN0j2p0dgzx1Pr3aPlJWfoJAYHYFcWc2D6DoMgLRiuaKZp66djbKUkGF+k/9D6UzpDi3iM7r2LdS/yIdKYVJ2LTyZVxz9qBaXsHl8xwztIuHTPbsj9fMp8GroxWeffWo9zda8BO2LjYw+d0BcFW0suHoCEfNRxc32V+d05TenKlSJSgiRGLxyjJYt4gtefxUcrWYyPWLg1IUkNdVjRLS9sK0qjIlEYIKFvPvGmJWafM6lSQDhR5lnB5vc8jj2yA0TTRIzQcHi6wTcvGIEfnBisDEolWkt1pRXOwAPs8mcxZGz2G1gkST3cbj3gfEAK0NCgl0UowdwsuZjkvTGvKOpLKmuBAFwkiNywqh6ojHk+gazL8Dt7BG43e3UhIJbXTR/eGNxd9mfFnVm7y7X/uv+VHPvUnWP2XvZMZadVGRs8LDj94VmU+QoTirqR/uzMPyvYly6vvqDVvVdhhoNg5/XJMCc1IUOcC8Roctl4zgmBwIzywHuW4YL9zD3t15OGtDOlheC1Q3BVUFyTlpSOiIqD36JRU338SysbAi6OvyQXyGG8JUhMclFNLoiNFz2CyDK0MIUiSuqGOFuu7VDARJJkR+Njlnq9upBQjTSBQB0sdLKVrcTiyLEFkHpUatFCkaQK6K3QaDTPSvmYxbolBsvFoj9H6CkmiKctAU0VkIWhsxFUBWo9JBdYGEh3RRWS4UpClEh8dtXPENtJWll6vwPqW+eGU+rDGzVoa7zEDQa4UvVUDAuw04qxDKUuRRZpQExuFjwHfCvpZzuZjG6QmYRlaFjqiEkNbWfI8Ic8MPgaM0QhtcG1gXM2p79xEB8OVzUcw2SohdD8mk3R1MuiEiEQE16kWKlKMLiJ1BjGidALRE6NHCIlUGqlSgrddmlTSY7l9F5E4hr010jTHO4fzlrYtqdoSqSRp1iPNRpg0oz9a5z1PfITZbIcDu0sVPUEGFtOXGPXfi9adteexAuNdy/aNp1hOJ8QQufP8Z3nkiW8jzQuadk6arpwhKS//BDmXRXUiMMijwPzBCkU8Vm7uEQdOS2DuV01OPnlO4TlWQR7sKnXq6HUmTUycpV7nCczpNs+8c1auOjmmUyXl5NPiWGmKpyQlcm4PnZV0C6ScmC4cOQycZMsJTvrEnKVRSmkuX/0oLmjmu0+yvmoJfpv9nU9gTEKafBNS3duc8IhsnfTOOXMu7uGB54je8bhiJERHrxhw66Bl92CMCIK9SUXtoZ9J5u0eVRSIvMUYg9QKLTQ+OswoIRpJaC2ujjStZjqP+CZw6D29nmJeeZyFrDEEa8l7nkEO1X5kpgSrF4ZoowmpoGktUYJRAqNgfSXjWz/UY7VQfPKX4fbTB8go+eYnLvPhD13G5Alt9PQDTKYld7ZnoCXTJuI85D3NxY2CXu4ZrBqihSYu2Tt8lksrq6wVWxAjMQaWiyUH40OyYoXVjQsUeU4MDXvjGb92/SX2DpeoUULpuz5eaZAkUuKCxfQVUisECqle/rf0Dt7B64Vk3s0QXe5PuajeOkT6m9OET3/s7/I33vdN/JN/8v0Mrx0VcNtTR7SzUI2gdzecBGO97YAddG5S2d7Xr/j8NxJEAOHEAxtHvhKi4sjJq6ujUW2k2Ou2U25J2kYQ0te+3Vcab3ooWF4SJ+T3/ApdGpg34oHpj29X6Cay/GDDb3v/U/zA6hdQIvBb8zmpuL9J8c8s+/zFJ/8I+f7rsN+vfROvA4RgY2uDZMWgshQlE5Tv6jNq4QmhSyFLU0UIsGxacqOQUhB8xDaRICEgGa7kZAND8AGBIE9T2mCZTWoa52lKWBkUXLg64j0fuYSbR7yPhNiytjrEeY92lsp6xvst8/0lrokIk5AlkaasKEc1+dAw6m/hdaCMDUFG2miJMdIsl7RlRTNraOYWdEQnEI7cc8qJxySdocFgLSUf5cTYItDgujz3dHOASCVpMOBhVlXUrkU52c3E6oANgeglqckJwmFFy6JpKPQKIDrFqK0IIRCEQoSI8wEjI4hAdA22nqGToqtrcRXRe2KzIPga15ZInaHTnOBavA+EGFlOdzG9AfnKFjrtIbVBSJAqR2tFI2A53cO3LaCJ3iIIKKUZDbcwi4S5r5g3U5yf0SwP0KMrR9dCF7PW8zu083288xAD5XzCePtFept9yuomm+vfznTvDqjA6sa7EEIdXUpdUBZCIHiH1slpgH68fRGRRIToVLhzqVjxvDJx+tb5sDvenzXFWS2EyJla+3vIReRMutg9+7knhe3BlOg8tblf/zhjSnB2vSMVpiN58ehcH6eXBRq7Q+vu0s8/hBD6qCBdQPAcHj7PYHAFbXonhEgckQshwPmW2XTC9aefRfiKbKiQmWA+3QM+Tpatsrr62LnRngw+nk+aO0f0xDFXO79cHJ3MEAM3bs25cWvKZLnE68Dufo2PhitbFl1EXGip5zV3JzWjYctjjwwYjTJMqjgczxlvHyJrz3h3yWxmcbWnyAVWRiZLz2RiEaJFK4VSMBhb1i6mzBeRm3dLHnpkBe+73k7TWc3OXsMw1TzxSIISkUFP4pYNWmsefWydD33gMq0MLBYLVJD4RCKNYrxUzNuWfhqxIbA61PS1IBMC4RSbA8OFImWgKkS7jWh72LahXNxlvthlf8/R76+xNsgJRvDM9S/ziZe+zMG0wbWK5cLikcQQiGmg18/ojzQkEVcH2oVHvON/9g6+Tlh7MvLSh9a59lDC1mvMv38j0ZcZf3njGb7rx57h//Rrf4jsX6yg2kh6ICkvn78Xpwf39+wQHtJDSe9uxPUFwXSBrU86Yxoip/UGka7p5zvuaq8ashFkB4LllfOKmAjQuyGpLsX7yOcJjs6/Ke+vH5E2kk4E1YXX+buIXT8aqU9mRc/BJx3B+vVCaFwmOHwfPPatN9nSlh9c+xw/UBwXDJ0nNLfcgr9/+G38s5/+XuwFTzxqSfC14BVJjRDiIeAfARfovo6fiDH+dSHEGvDPgEeBa8APxRgPRRdV/nXgfweUwB+LMX72Kw7CCBwLZGWoo6WRKRGBd0cBTRTo4/qXGOmlBtdYoof5YclsonDeU6ynnXpRW5bTmsmkpEhSZKYY7y8oioTpwrOnSgbDgsFKxsZjfW5e32MxAZKIAdIgMEJSLz2lNjRNg7QNG5dWMJcKkkxRDDPmoUTWogsEpEBFhYsW6yw+eOqy5nBS4lpYzj1FTxOERxLACrRRROlpXEVCgvUBoxVN64iqRDQRrRMa75nOKpppy2xa4qrApUf66EJRVRUqQiI1vvTUIXC73mUlT1gbrJMnA+JRqpAQGokgeAsIvGtIsiFSany9JIbuFy+NQegM4TuzX+ca2uUEpCYCOh/gW8tiuouY7pDlBWledARIZySrlyj6a9TVhHY5pi4XKJ2gkxQJKDwjnTJMLnAw36WZvEBvePHE3jkGT7nYZXY4BgIhBLwtefrz/4aHP/owUnum0y1e/PKv0L8EwjSkyRpCaop8C4DJ/i22b3yZJz78/WidnF7PJ9f1Mbm4p4LjTI3JvQrB0f3wlIzcl2Z2/L8uEn/QnLfgWPE5T1aOP3ZWtDmrzpy9F56SmTNk7XTnJ2M9R3COidTxGE7Wibgwx4eaZfM5QlhizJAi6QhIiLCc7/P8l3+OR97zfWxceO+JZHW866ou+exn/z3PfPH/RyItoxVNWTa0lSdJFE26j22nJ0TkhMDEM8d97njvS4rj3GpH7y/rOZ96/pd59vaXWO8JwhLGBw0hSJy13N7dY1wXxOBoZzVGgg8WrVvWlzliHqgWFVF4lg0883yJsI4YArv7gaoOBAJCCkwCFk+wMD+A6SKwseXJVg3bMtJbTxmt5Fxa7bMsLbLpJmAEjlEv4/Lj6xQbcPVCHyUCVWxpfEtOSuMiZQzYRcVi3qAKw2CYg4/sTC0Lu6QwCboSxIVEr66ynLfI+i4gUNowzLdI1mvy3iqp0ezt7jOfJVCmzCcLZrMSkWRoDaOBZjhUTGYVd+548lzSlC0qgG3fOrPmrwVfj+fUO3idEWF62MNGRRPtA2dw30x8Twaf/daf5E9e/M386r/7EL07kerCPYTknsBYBCi2I7rqMkJULcm3uw7u5abEFV0j0+O+KLoUFHe7xoZfIeHgHRyd63Qsj85vwCeSevOMY2MQZONIs94RhfvmzzykB5LhtQeoJUB22Nl461K8foYPEZJDSbHbRQ8PKsR/tUX9bxfoOrL+JXj+yib/9Lt+gm8wEUgeuO7PlY9xYHv8pT/y0/w3P/FDiNehqPPVKDUO+L/GGD8rhBgAnxFC/Czwx4CfjzH+FSHEXwL+EvAXgd8FvOfov98E/O2jf18WIUR0kSF0QggSpSS2jUwmFd46Ll4aYPKE2jmkV3gbEELRK1JUrtAjiUoFmTFUTU3dNIhM0F/PqOYtiYeHHlojyTVXE03dWBaLwJ2blvHBHpfXezzx8BUSFbHO0QZL6wJJrlm/IBjUktAEUi3oDQqKFYNMBR5F03pcZTk4WLC+WZAmgsV4yWK/ZH5QM584lBQkKWSFIMkz0kQgNLQ20DYBf9iidEuaKqIS9JKcYD0eWFQlNyY188OGgREI6cmGAtsG5suG/Z0pm1sek2jaRjCrA5cuap68ewtkwuOXA6NsA6UMgkhwDWgNCIQpEDEQmgrXLIgxYJslJu+hkx62nuO9IxttkfRXibahXhyC0ujEIKJltn+X+W5NMRjSG6137mrZgChAExFJSjXZZz49RGcZJklwdUVa9OitXMAoRRUCBNuRGgEhWA5uP0tb10AkBI8PgfF8l0t+hFGaF1/8OWazfQaPXGQy+wyKFJ0OScz3onXObP8WOy9+huH6Flff9c1nCEA8Cuo5+f89/5ymQp3pJXOMYzJzhiOc2drpjTCeXcY9nOP4U+JUTTk2PI5n1aJ7VJtjInbfZE88HRPnxnWGnJ2oMud1H+9rJvNP09gxiBqMYtleIzNXUCLD+5brz/8ibXXIrWv/G3lvRH946eT0tG3Fpz/7H/jSFz5HFh3rV1N8E5jvW2K0rK4VqKljeniL1dXHydLhEXEUR2fp9GjOjuvcMZyc06N/Y8T6mqXbRyZTrlzpXP7iIWiTEGVE6AhKoSUkRcqwMFzakqytGJaLhpeenbP31AE6BIarCUlfs7WRMBlH9qaexdyRpgKUpGk9rYM0UeSpREpBbQN7U8/VrZQoIrYJLOaWg52G8UHDd3zkSndsyjDIW37rdz/K9Z0GtQwgQRtJCBrfBGZlzdg6QqqhDUxspF14qMAsIpvDiB1ALgwz0TDzFlNPCUvLqL9Glg2o2jkxKsq6YveZT/LS3owvTfa5vn+X5WSBC4JUQmIi++OGnR1HlihSFUmThOF6glIS8RaaMX+NeMOfU+/g9YWIUDyV8seS/5T/5H1f4K9e/NybPaT7oITkHz78i3z+R3+O3//L/znxID0JTIUXmAcUWJ8tuh6+GLp0qQi9nUCU4BPBJOsMBVQlyMYBl0vKy+9Yqn8lrDwjCCpijhq+FjuRdqVLQxMeBtcEygZWnoHl5aNajjMPy8FLkmz8YEJzFmZ+RGq+VkRQrcAs3/51Mq8V0kH2ZM7/ZeOHeWgw4acf+3l8DChxPhMgE5Y71Yi/8bf/AP2votHmg/CKpCbGeBe4e/T3XAjxFHAF+L3A9x6t9j8A/5HuYfF7gX8UuwT9jwshVoQQl46282AIQbOoINYkaY5E0VqL1gKColp4tOumdRvb4lxEIjHC099M0ZkmKI+Xnt4wReUSZz0xwKjfI1GaNDU44RBSkJqM9YFmaHImk4ZRL0HEQPSKthFYGxFR0e8lNLZFEJFGEKKgKTtnpxg8de1ooic4j3Mt8wNLJgP1rMEfBUJbV3qkOUQZIAhs63FeoISiWEnBQTVxzLanDEYeM5AsfaQ3LJBO4o3nwmrBQ/0CmUTqkBEliCBJGslodBFnHUFEtIwkXvLMS3PcdEneDnhs412kKwVa5wihiKElxBZip34gFDJJ0TIy37vOYnrAcP0C0qSYYki/v4nOhgRX087vopVGZQOS3ioER39lo7OM9hYRAkJoqtkuzXKKEAKdFl3AHSKLwzErl66Sr2ygVRccmiRHtC1ifo02WSHqAhdgd+4IJkPGkugDPgaKYYpQgp39ObvP7bC51UMYRVAO4Tytbajq2wzyRznYfoGqXLB97dNsXHyEotg8vthOyMeDE22OwuyjVC04SjXjfJJYlzUV72EXp5qPvGfZCRvheFvnSY84SzlOUtvO05djchJP0rWOl59uo/vY2XHdQ4Hi6fFDZNm8SNXeYlGV9NKUJEtxeAIeJaBcjjncfwHna/x8l+07H+fdgx/sGkAK2Bm/yHMvfhEplgyGgvlBTTX3aC1Y20pRPRDasbPzaaSBy5e/hX5xsUsXFOef4Cek8vhAz5ytUzVMYN2S/fltWl+xP15y5+6UumppWoeTXeAgHDgL9bJGRcPFrYwil7z03JRyvKSdNVx4vE+zcPgmYi3s7Fn29huCg6ynWFlXVGWgqjzOeaqFo04kly4YLl1OmTWRg+2WRSk5nC+QBjIt2dwY0DpoW0sdLUJEVlPJ41f6HNypsD6wnJXEVlCg6UtJg0aSYJynWtY0QSKMwIXIHReZVoFeAQfLwKw55JGhZb0B2wQO98fYqJnOKxrXMJ0vOPAN1XTMfGdGvWxoypqmrJlrjVCS1CguXSpYWdX0BpooQUeJMW9PVvN1eU69g9cdw+sBrmc8dfkifzN7iD+zcvPNHtID8eE05YXv+4f8tfFj/ORL30LdGsIXRgQN981WncG9heEidDPZZi7xWUTX3e26fzvgM0mz/k4Nzn2InRmDWZwnJKqJpGNJdTGilx1hge6c57uRZv20Bqp3S6Lq+IqEptgNVBsSn3Z1UV8LyUxmknTc/d0OxG84YjN6KTCLF/iD/+nPsu+X/MThR/nLG8+cW+d/m76Pz33qcYa5gK+y2ea9eE01NUKIR4GPAJ8ALpx5AGzTyf7QPUjO3pluHS172YdF2wTGE0GxkmGSoyaTMRCdxztBURiECQQRiUkgkxoVBCEE2sYSdIAkELzABUFbORazlsO9iqayrK6lXLqyQt5PEEogggIPa6M+G8MVnG1YVjW2DQTriDaADPjgCSFACGidEHxkZ3fCdF4yGmUUw4y86Hy183xANGCrluGwT7lfs3d7j1o7+hsZTeXZv1uT9SSLcUs7j5AIohFsrqYMhhqHo3IlUhiMKDC5QoZITsRIjckUvo3M50vyNEEp0FqhIyRFQtpLKOuW5vqS6SLh9rV97mzdYWu4iWVBDB7naoRShOCItsbkayiTEY4cy5TQZINNTNLHu5pQzxEmRylDUqyRZKu4egLBIpXBJL0j0uKRKsNbS9OU2NahjaJZTsnyEf2VLebjbXy1YLGcIaVhdVOTFn2CrZDtIZmfsSxneJkTm0NwDXXbdHVORjHa7DNf1Dz30iHD2qN7CSFGpHNEJKIJTOdPMT+YsX/nOWL0VJMdFuMX6RUbZ/rhdM5s5/rS32Nrc9bV7DQN7Z473LkGlWdVlQeQkQcnsnWvH6B0n8b75xt2nov3T4YhjlK54rnw/+x4jrdxd+8WWms21i7gbM3h4kWsc0QVWAbL/GCfoBuUvcXFlSc42LtGY6eUy4pMZUjd9YtSWjFbjPnUZ36BZrnLpQsKYxPKpmK4pTFadqlrO46L71plZXgJa3e4s/dvubz1XQyKdyOFwtkWZdLz4z2XUnd6FND1pNHSsChrvnDjSV64uY1d1jjhMZlkdZiiEjg49DRLh40Ci2J3HjlsAraUbG3mJA8NUEaxGDfcembKeK+hcl1/qaZqKReWttFYG6kbjxCglKANcGfXUTlYu5By4XJB1tOsriXETOOjoMgzVPQkIgGT4HSgsR5CYLhqmO7PaUpLCBHrLCGAi4rN3DDZntE0Fhu6a94YhRMCaxSyLxheGDBe1tjGcT3MuThb4XIyYNDrI0WgaSyzsmHml8zLmtZbqqpGJQaTZyRGkWeR4VCR5hBcoJo7+r0cW9ujFNS3N96o59Q7eGMwf1iyISLfVzwDFG/2cL4i/tzai/y5tRdZhJp/96Et/u9f+L2kP9P7il3WH4R8N+IzSb57NCEVu7S1doXX3N/j1yP0QqBaQbMaUO15M4YTCHBHl8u9Nsk+5aT2U1ddWtrZhpsvB5sLVBVZeTbSDrrGlF+NIQF0dTTCCYrt+IqWyb+eYHPB9AnY+EJkeC3wX/z9P0z5gZrPff/f5DON4pvTLhXtL2x/hE/efYSNz3UK2+uFV01qhBB94J8DPx5jnJ3tGxFjjEK8tvIeIcSPAT8GUPQSWhsw85bxpMJGQZ4nKKUwBsq26/yNAJkafA11HYghUC9L8nVNNJHZYdXlvyuD8xEkCBkpy5adnSnDZU5RpJSNR0hY6QekS7Ctw1tPcAKTKgqd0Sxb8BIZZZcOJCNSQbaiKPoaVCAYSz9J8FFgncFpjxSK9rChnZWsbWis8+xeX9KWAVuBXXqWpSXPFNYF6iXcXECxCoNVwWMX1yn6fXSiEVEhXSA0nhgD7UFDUB7hIjGNBAGVa8FGdKtxrlOPVgeK7JLhm69eopBLysktXFMSQyDrDfDB46yFpiT0ahAKoQ06SdGpIbqGcjlBKIXIHYKASguEMsgk78iBkAghCERcPYfoUMU6Qlsyt4bUGqLHtzVSZ7imYvXSYwglWU52WUwOqecT0rygt3oJ29TEGBn1+oz396jnChEj0XkIkTuHNTfKfRguEW3N1csF2WqGROKkIMaA9pG63mb3xtO0zQKjFUVuaGY38P6b0CZHEDvyJmXXqOZYEbmXnHRSDGeS0c5evUfX8Jm6kHsrPk4a2RxnW8UzxgLnq0bEGWVFck8sfzykc7U+D0hpE/cSo/uZQWtbPvX5XyZNMn7b9/wA+7Nb7M0OSJWlV2TMXEUbLVksqJspTTtlWV8nBNeliGYJm+sfJDEZ1jV86umfY7x/k8QInn12iWw9l68aNi7klIeO/bslwcLaouCRb/wdtPElyvZFZtWXuh5IfsStlz7DI49/jCQtzow23nMcp699CFhvuXV4h1sHd0B6+lsGnWjms5Y7N+dobWibjvSiBK13xEWklwrWL6QURcbhfsnhrZJ6ERC9hMxIMiEZ35iBCEgtKUuHRJImhhADOumMJaIULGuBu9OyWMzYeLhPMcyQ1lP0ElY2MlwMCCkxCnwbmC7nRKsx0eBqR69IQYOrPYnWjLShvevJ+xmtEV39oALvPVJJcmMoveXWeEE/EyT9lP6qJC0C7UIRhSTJMkLZUqWCQxsoswBKYLRBKYPWio21jDSNIBzOBaINGCmRvkbr+wnz2w1v5HMqKVZfz6G+gyMs3tvykZWb3HQj3p/YN3s4rwp9mfH7+zP+56vXeUZ9EPxrC1qTZWTtqfOf0XUXBEf1GycAfhCEh2JbkMwiPhWY+f1mDNCl8RV3I1WU9G+cV2HKS4KQdKl/K890LmevBFsIZo9B/0ZHMtNZJN+VlBchHQuatfiaDB2ijOhK/IYiNNA5uW184fT18HrApxn/5Yc+xrf2X+Sb0ynP2iU/8/Q34eaGtRzU6/izf1WkRghh6B4UPxlj/BdHi3eO5XohxCVg92j5beChMx+/erTsHGKMPwH8BMD6Rh7bsmVRQZ6lXLzQZzDUNLGhqh2z2mIbB/44s0YxWsnIRhKdg0wFbeNJC01beXwMBAeugavvWiNJJYnRRBGpXedQ5kvJYV2itUMGcK2nbSLlMnDz7pzJpOLxR0dc3MoYreQkqe46OdSBLEmpmwbZOJbBU0eHbWxnrewcoi4RJpCvalQlaOaeynqcC2xs5qxfTMgyhfWBqvT4WlKWkcVBYLruMInDxwCtJXpP3VpKF2iWFpMolJZEH46Uh4gTkSAE02mJJyIDrG/0maiKrWIFbxJ6gw2SfAWpjqeBBK6aIJVBJ0OQuquhqWpicNhqTn/9AirJQHiEEAipCa4GqeiiaIFKBwCd8hMtxIA2KTBA6JToWtp6CbZlOd1HpxnGZKxf6NzOXFOhTUKSJjTlghg9/V6f9z9ykRu3l0ymcDCZsrCa2lkyq9gcSGQuWM5LhExopxVFP0OahOg8oa2IeJIsJemlTMY7rCx3GK080h2HiCgREcij4o2zRftnNJmjNDB5pvblPsYhzv95QnCOl58QlnuJ00mO2cm+jrdyjo5EjiyP79npkXLzIHn8uCVMJDKd7tDvryGE4tnnv8jNW9fJ0pTrN5/m1v5nyPue1nl00DgbIEDdlAi7x3R6h+2XvoyQ0OsbXKi5ffMLZL1Vdmd32a9u4QvFjacqQtnQT2F/zxF9JJOK0cBQjDQtt3ny6Z9msFaQj3KCW1C2zzG+OWf35gskacbD7/4OhJDnqaEAoofQAJ4oc2pXc/PgRXbn26wOUswm2KphvN8yuVNRlpbgW1SiQEgubW0gBFTRUleeu7sNN1vLfFLhKocIjiC79EZXBwievNDY1tPUEZwABz5EgvMgIMk0XnW2y03tuf3CnKRoWN3sLNNXcoNONU3b0DhPUIJhv4dODLaVRBNplpbQRBIDOtV4EdhaT7m5rZk3LW3rUEohlUZpRSsCiZIEEaiCYa8OLPYszXDGoyuKMHGs5Busra4iksBkvGA3KrTJkEODkholoWwcNkZC27K2Ykh6qqvliwHrI29noeaNfk711x96G5+dty4u/pzmH5ffxer3LfntxbU3ezivCR8d3uDZH95i8XNbZOPI9D2w+mR8zcoNdGpDvivO9bmRxxNvrzDZUNyRVFuvLeh+KyE5lNhhlzqcHkjyg0DQILwkJByl3N/zoQg+E6QH9zuHJZOu74tZCqR7dSqAKSNrXz5fz9m/HTALQToNVDPJ/FEeeI6jhGiO0t9aSX63M4UQ7mXGfg/KTUlUnSX4643uPPKKqXdvJIbXIv/y6W/ij33sV4Ccn5x8Gz/zsb/NH/zsn0T44eu6r1fjfiaAvw88FWP8a2fe+l+APwr8laN//+czy/+sEOKn6Aovp6+Up+xQ3ClTonM8tiLJVhRza/FW4BtYLj1NHWgaT6LhsQ8WjFYSkp7BR4cMmjzpmscFoK4bylmL9Z5q2SKEoVfkKCUxSUQmXS2Lax2iiUyXLXcnNfXSs79fEq1jUBhc1TCdRC4+PEKoLrkn0Qk6EwxMRgyB1lqkF+Re42uHryrKWc3OzYrlwuFaWF9JKQaG4WqkGAh0ppEKEqPprQvszFPMI0ob0jQSpUJKjUoiZeO6VDgRsDoym81RCDYvjshSTWtLjO769uxMW3pJQm8gESFyd3/GZFqxsJLf9KHvQuuMGANSJyAkSqeotIdUWVcTow3Dqx8gRg8yAd0DmaGyAqFThDQgOtWI6PDBEq1DhEiMAm9rgmtw9Ryhc0y+gm8rEpl0qTbNGO8dJh90xgVSUM33uhntxCCFpa1LkjTlicc22VhJ2Npa8LkvPUfPNIyVJLrIYAWacUW9v4RHBa5pkUaiswRKWO7PgUjdNGzf3iEremTXP8lgcBFtsiPaIBCSk7SzUzeyI2pyrLAcNaSR4uTP+38jR/+evB3PvhLn7iYPrhu5X4U5KXsRp+X0p3s5v1dxbvnpX1U55wuf/ddceniDh6/+Zvan+5S2pXYNX/jMv2HtYkRvboJKqWwFrWPZ1LS+pdVjDvd2aWYViXaoVGAXlpvPf4Koaq5Xlt3DivG0xQh4zwd69HoSv/AsFxa9qRFE0jRB5YrImNl4go0j+qNV2jBBDUvQlru3Ps9w9XJnzX10DpyrcXZCcLdI2EXLiDAfIDcXubpxgVH+PVy/+xL/8TO/yu7OGOsjMtOkRz2rYohEJdi5tccg7eEFlLMldlHTzmuitQTvyROB0BofILpA8IG68bSNJ7huggB5lNonBEIJXOuRAoLSaJVgEk3dROYVJI1gOq3JpcImIFLRNe5tHG0dKKcBVzWIROAzD0FQLmvquWC4kvLQ5QFxT7I3r7vaQSvwbcDJgNWgEodJHYKMzb5h1E8YDTJcE9k/2GfvcMqYJYdthXWetmrxrUNKRyAyK2F9qHn04R7DddM1Dm4ioQ04H2mbt6372Rv+nHoHbwxEhMELir+1+T0cvr/HJTPhP1+5j1++JfHjq9f48dVr3PiGBf9s9k389F/77V8VoTlGsROotk57pWz86h6H7998xRSoejO+PRWeCLIV9G92D9zJ+6B3pzsO6WD1mS7IfxApMFXEVA8+5t5OIJ0IfPZgx7GXw4MC/3R6PJ5IvicoL51ZKUIYeH7oWz7Fj6//EgD/3cHH+Of/6js7w4GiS6887nf0csjGb5xJxOwRSb4fT47jzULy5YLf3fxZXvodf58b1Rr/wH0nzXNDstd5P69GqflO4I8AXxRCfP5o2V+me0j8tBDiTwDXgR86eu9f09lkPk9nlfnHX2kHwXYyYdpLCUgOD1rAI70keolrAuUyYoPAR7h7vaI89IQYsK1nd7dEG8n6Ro9la+mtaDY2M4pe3tVOCCinHi9bVnorFIWhto7WWw5jy2Fb0RBQyvPopZTC9EgTRVXXaCOJAYpRRgBM9ETpcd7B0fhoGw52K0yiiKWjnnsE0NZdwbjOBMpETCLJRwkueKqZJzVdXdBy4tFGoJKAbSp8aRBpRpBJ129HS7SCTEqMzlEo5pOW4FucbzGJJCaSXg+C8+yPI70eVE3FHGi/9DSb6SZPPP44ymRE3yKUAQK+ntE0dxDaoEyBEBHXLFhMdqiXHcHQJiHtjUizAp32EMoQbEsIXYNOW8+ASJL3IQRkkmGKdaJvCO0CqTOSoocyhqau8DGgpUAnPXqrCe3yENtUKBmRQtDOx5gip0g87310k8ceucT+fMaXbt3lxt42ajmnsQ7vI97vIhWoIIkritm4oW27aQnrPFIplFZM97dxtsKYrKuXEYqzbmXn0szO5HV1WWRHxsj31rKc12bOc5nTDd2HGI9Szu5dDojj2p5TdnQPETpVYs5DEEP3m5BSsVge8KUv/Bzbt57Hxx2U7vHizeeIIWCJjGuHaQPVziGDoUGm0B/2oNVMK8vewS7Xn7nLWtpCjGTCoFLw2vLS3ae5tjTs3ByTCsFDj6T46JgfBIQVbFzO6W0aQhuppo44tmQjTdJPkERaW9Eqjc41va0e8ztTtm9/gdHqJSKC6XyH27ufI5N7bPRAJAqlDVp8Ca2nVH6Dp649w8e/9DkW0wVOQEwkIlVICUYoouwUFqc9h26BVAo9VCQxJZYeFwPSKDzgfcRZT1t76sriXSDGrn6HGAguIqQgxkiaGqKLEEAqSd16kILhakGyWiCUwgcoo4WoUcuAC45+ZtBGIIzhYLeiKh1Fz+BKTzmrOZwHXrq7YDpd4rXCNQ5cpG0i3gaSLOnS0aInGWoikb2mZnnoqDcjV4sRO9OGg6bkDnPG9Zxq2WLbruloCNC2jqZyxFZhkkh/dYXFrKVcOFztsY3/CiXPb3m84c+pd/DGId8PmJ/r8dNP/mb+mx/9B2/2cF4zHtZ9/tTKlxn9hYq/8u9/kHxbMnrptc+6Sw/FjmDx8NG9v311eTnBvH1+ucJ1zS9DGkkPJWYGpgpE0RX0n1VWXgshuRe6iejmdRjwEZJ5pLx0+uBVFyv+0Ac+zY+sfJInTA/oA/D/2Poc/gck/+KpD9P/5YJ08soH8bUQ4VfCygtvvvmEdJHsAPofm/E3Jw8xbTM+8z99iI07r+xG91rxatzPfomX55Df/4D1I/BnXssgYgg0hyVuabg5bhiNMlbXEyKB2cIyLS1V5Qixs76dHNakRtBPNWmuSZVBy0iwgVwZYhnZv1XTtAHvQLUBLxRee973Lg2XBugCmtCQCbjQM5AKXOtom8ion2EywZAEaSROOmZL1/WoWNTs7FdgJVsrBboIRyqHIEk1Do1uDGkVGY4iIXb60aCXYFKwtaW1gbr0uBhpyi5AMkMFRKKPlG0gNHOi7JFpwXJpkTqCjSwWDYnWlMuWRCqUEvR7GchI2sspeinzqeVzn9qmKls2L/SYuppffeqzbGwMWV29gFIJyEhoG+rpHs7WmKKPd9sQA1JqsqJH3l8lyfqE4CB6bDkluIqkWEEIgcQTZadxhOiPgvKATvtIpTtFJzjwNUoCJoFqSbU4JOYFGaDTApP1acpx13g1EZSTPYJvGaysdn07dMrDV9/N5uoWv/BLY8oSKhexrafdKVGJpJnv4LOGa4c1xgVc2dDTivV+oGrmfPN3fidZNjhqKAlCCmQ4W8FxTEviOclFxtDVDx2vd6aK/SyRESdV/KdbOhF6Tq90zm3i7NJ4poznzLoPxIN+jREOp3tcv/0c73nsG7i+/UkOJ89SJBFf1zz93OeYLhqWrUMCh/MWcTsy3AqEUBBky3ZdM2sC81Igly25dETbkTC90plOL+aCuer6SgzXcmQbuH1rwfywZKVQrPdS+pUgjxBFJKpA1NA2nmQk8QhMlDTWolWngLW+ZW/3FuGZT3BYHbA3v0VfOy70MuZBQO4RBmy1IPAStj0gWRzy7VtbrD/6GLfmC35l5zpVsEQhu2J3FzFKk4xMZ/aRSJRWyGEkGpD7EmxLbTszEO8D1nb1LVGB9Y66sZ1BgJadMnP05WgjSRJFcJ5qXkNIkUlLGQL2Qp/5omWzl+CCxUeH84FGKaq5RSaGrQsrVLVltr3AeMHaSp/RBsxLy1PPWm7vV4QEVCJQBow3qCCRCJyL6EYgTSQ4SEeCvapEJYLDoWNftkxmJW7WIJYeX1pkT+NC11jTKEWSGZSWLJctOhVkQdOIrsTMv03zz74ez6l38MZBus4K2R0K/j+3v5cfeM+/fbOH9JrRlxk/NrrDj/2Bv8M/Xwz5L//bP0w+fvUBpU8EUUC99vb8Db5amLlAV2AHUNyJJEeuVyJ27mNvVYjQpZM9+qE7/OmH/yMfy+5wSfeB3rn1jFD8Vxc+z4+v/xK/Rf8pfvj9Hwfgn7zwLWT/fAVlf31/vw+CCLC8CoN/ucHfzX8PUUP/7hvzXb8m97M3CsYYBlmGLhLq1jJdWhqpaBtL01ggopXqAr7gUUaRDgRrF3OGK4Yi1zjrCT4ilebgsGE+cwgBQ63QrWO/DUxri/SHPIZkbb1HL/YItFQ2cu1uRVO2GBkRMbCSFl1xdBJZNi0qGg6mDUkMXFkpunz3RKJ7inLWkPdSVAzECpQKDDYUxSihqbpUlnJuSb0m7UuijKS5YjnzTMeOwSCBoHBtJKYtO9tLtEnQukIFT4wRpWOXGrNoSYaK0ajAOw/OEUNkNquwPrK+KSj6CRuP5IS6T2jgzt192uULXChSvvvbvosk6dE1N7VY5/FR4ltPJCF4i5IgVR+V9QlEfAx46wheYLyEpkszi8TOuUooYoiUkzEmyVFFINSTru4jyfD1grYck688RF4M8e2S+eEOrqkYbT6E1AYpFW3TkGYFSTEiuBohFasXrzI9OMTbmqwY8fDlh9jdLziYl1i1RPolLYayHSBZoS8q1keSuJaxsTZA1ju86xs/Rn+zIIQGpfVx78iTvi8nqWUnicynqWOSQDjpq3L6TzxjInBc2yTOrHLsgHa+zP38q/typU8y1e4vlz8Z55ktnawToazn/Opnf4Htg222q5tEcYA0LTqBybRl11aUdSBKgSfSishECdrSk8iKRAtmC0/ZWnKtuwL7LGOyPWEtiSAjLsDC9JnMHK7tUjurgzl+aYlR4n1k97BEqBQSgSBQZIrYh0DAI0j7Q5Isw/uAMIbBxjp3brbcvjvnxdmvIBKF9BlVs8oicyRM0dFjTELTGPbGDXUTWM0SHr+0xorOefiRDUyi+cU7L9AIgXOWNjp8jBivMFIhgkC0AR8dKxf6tDKhPFzAtIQAtg1IAWmucMEjg0aZ7vsySWc/HmLE2e5elPUMIEiPCvrLssSIDGVr2lKgpKafCbzSkEiIAm8dtIG6bLh9+xBBpFekNG2LKwXLZeTS5pBIwnhREyJY36KkYmujYHXVUNeeRImuYXEE5y1laSmtAy+o9h3usEYEQYiBfJRRLVsIXeqcVN1Ey2TSIEQkLwy72w11afHe30PC38FZxJejTO/gdcHx+f3iUw/z05dG/FB/+uYO6GvApp7hf/shC+DSYM7+Tz+ETwTl5cjKN+6ztzPiW594iSf/1/eiarp6nMehfxNC+maP/o2DCNC7G9929sZBwd7vbPh/ftv/wo8MDo6W9r/iZy7pPk9/1z8+ef3n157h2/UPwz9bf0Vi4xOB7XUNQX+9YP1L3bEEDYcfthTbGpcJdPPaUgRfCW8JUnN5c52/9Ed/mOn0kBdeepHWeeqmpawaWh+YVw2ztkGZgE4VaIXSkXoJTWXJpaCaOqRKKKmYETrHIwLDXsqjo4wXX5ohE01uNFu9HtJ1NTqNdVStZ5BJVvopw5WUSKBumy51zUqCU8xby7yxvOtyn5TI5LABr7m80euUCtdinCeaSFCSw8OG0VASELhKYF1g/25FMVLkPUmRKYYDjUkEro5ILXAiZX20yubVBITCxUCMELyjqVqCg9V+gQoCiyfJEpwVRAnDtRxP1xsDL5jNIjKR9BN47JENHtm4yMNX3o0Nkti2CJ0RSBFpgnAWD5ikQIRADA5PxDc13jVwnIqDxtYtykVCCITQImgRCKSU+NYh1JFJQ1tCbBFIyukeUgqU0qjBOspkmMU+47vXiVGysnEJqQzlfI5UGcXqJer5Pk1ZYzJH0S/Y395F5SPe/Z738e73BMqqZm9/l1s3nmewtc74EO6MQQTLcLjJ+991lc1Lm5R2n3zjIoeLL1E1F0mSgtNGnKeqyal6cp50RHmq0pwpwblnSvgBDmnHpTHitB/OPYlqJ14B5wr+z2zo7JDu3W88ij6Px7Q/3uH63Vs4Gl7YXnJJNohlS9sE9qucme9m4YUWSC0RmaTVkaa2uNIRlaRtGwb9FC8VJBFfOS6sKdoYqF0kGa0hsgTvHG1wNHWLLS0yCjY3DZurksVhy83tip1xzYXNlIcezpFSUKxm2HnNrS9e48IjW+TrI8b7h+xvK25PDF5HMnqIZY96IZnOKvb2doi+JcsNRU8BnrIqSZVm41KBtZbZosR5z0cvXSWRkn/33NM03hGcIxlIQoy0rmU175FaxWJquXp5wDRaRGlZ+hLXdnViUgmSQiJsRAmJ1gZEQBuBjwIpI8ELljPLct6CFKh+htGabC2lt9njwsUUO6+4uXfAekhJjWLNjFCJQg07lUoEwUP5Kq6JKKOo2hZnA23bsr9dE9pAP2pUpmiEQmhN0ldEHUkzT1k3rG30WFtJET7QOslyHpjcafAVpGRdjZQP2DqS5ClJpkgzSDRo2anSe3crtLL4IBn0NUXP8FT2jp/sy8GveLY/dn+QkRwqRs/fv1wcK8FSMHkC1r/cvd77qGDj86/vg/zXA4IWzL6l5jsef4nr7Qbw9iU135PB5771JwF41tb86O/5Y3z3pRf5ry7+Ktddy+ffc5kf6k8p/+y/4Qee+gNM/8VlZCMwy4DwAsybfABvBCKYqSSZv70u/Chh/Lsrnvyev0cqvvovRgnJxz/yU3w7P4z4p2sPTDnzpnvC1+uC3/mjv8K//qcfY3DjrXu+ougI2PQJWHmar0jWgu6Ob/KxhuKpDBEDy8uC3h1etjbqq8FbgtRobXjf+z5A8J5v/ui3oJTBO0eks+ptmorD/W2QAust1lpihJt3d9ndO8C2Ad8LRCGoypJSJVTRQxZ497rnUhZ4QqSIIqPXS7FJIPiW2rUQJFmRkOYprW/Ii4TWdfnwyTAhyyVZsCTLugsuY+DuwZJyblkZ9ZndrRhPSkRoyGTLfNqyv9sSm0A7jiyWDuEVq0VCmoJrA7UMFIVGpYJhX5NkhnIaWC7g7qTBTy0RwaULOUp2aTRZL8F7z2Je0VSONE8wiUSnCUlm6PUzbHS01kFUPP7IgE/9ym2e312SZ4b5Fcdaf8RguMZwuIoUhhA7K2sfI97W2LbB+xYISNEVRvvWdqqElIQQkUKjosM2FVJpTFqQ9ldIsj5tOUH4Gu9alDS05QLnW2KUJL0NhDRIlSAKg5SS0JTcfvEFqumY0eZFTDbChYg4cmESKsE7i5aRXk+xKCdk+UVMWpBnOaujAQ9fuYgPC8KjLXvjGU++UDGeT3jpjuHiVo++LliW1wnRsqxuM+pfBdEVsctj1eXkSjwt0j+t8RfnBJXjVyeNN484ytm+NifmZogji+bztTFHb4KIJ2lr53/SZ4jPSUpbPNk7EVyoaNo5vWyTtq348jOf767nAmzTMF6W9GWLj4rWOmIE6zoGJYwk6khVN4Tad+mf0WOMoJpbJpMZhVRQe2oruLtTspJIsgxGjw7xWrEcL8FF8tU+I9OSK0vTeiZzR+sBC20VmE8tOQp/2BXDC2dR4S7mYMr44AK377ZEpVgbXiEPAxASoSvq8gDvIonJEULjvKRuKoKF9VHC6qAgTTOs9YybkmUVWFcDHhVrfGFymyY4cBy5eQn6sU+9X7GcLNmVOY1rmc5meCzx+Fr3kXLWqZdE0ArynibNEmzjqRahq/lqAs4FhIBlWZN4hXQtwXvq3pCN9YLVrYy0pxBRUDlH1trud6Y9WiiqtqZeRpRXWGshkYgk4KXD+4CWmq3BOrHn2VkumM1b2hZGG4q8SJktLNdenOOtY3NlwMP5JkL0cHrOLC4JBqTJCU3L6npKmkkWM8vhtIUQcY2HGOn3PKOBJEiYLn3ngPcOHohMO77xm67dt7wNivI7kvuW39pbJXiBvpUSksjBh7o7wIe+/Xluf/Fxlg8Jlu/rkv4HX0wpdgOzRyXJrEtzeS2pS78eoGzk4r9J+NXve5x//AM/z8u1R3674Lh7+hMm419+4z/gv979LaTC8IQxPGE6wlbIhH/1/v+JT/75jP/sn/xniADFXcH80V8fM/TSCsxUnDQV7d1++x3Xwe+p+Px3/11Scf9v/LVCCckvfeQn+Y7wh0l/avW+iY3xN0BUka1PR37+v/8OildhRf1mwmUdoSF2Y9/83Muve/hewW/6rV/m/7j5Cf40P8LwWvKG1Pu8JUgNHMeQ8cjGVCGkPOnoro1mOFrtHKpOChUETzzRQgxdGpYQhAjBOeq6YTGbIpQmzQVKNrzbKEo/o2xrvG+ZLma00RFFpPEl81nJYtLilg4hJFXj6VeOUnuUVhghGWqDX1oGKiOKSCgbrKxZH0aa0lGXHqMi6ysa33iEkCSJ5mC/Ydo0CEkXYPS6vH8VJL4JlG3LeLftZlv3ZhTrK+SF4eBuIDUp43FJXmiuXOnhvScbpiSJ6tLCEDSLhqp05ElK1Qpu783xXtC/MMTkhnrScDhZ8syNfTbXdnnEFKSZJNglti2J0SGV7BzPQoV3nogmRgkBICDRJGmCkBohNEp3GrlJC6Lv6m1kDCiT4l1FtTykqea4tiEGQCXotE8iDQKBMgXD9SsEH7j1wvOUyzlrl66SDTZwIeKRaCEJzuPaBWmqEMqwnNylv/EIJsnRBIwWNFUEuUbv0atcvrzL+PAWSjQk6T5QoF1CooaUzT7WLdDJCBkfoK4A52zH4Kig/560sbN1N4JzxOaYrBynkj2wpv9eFnRCWk7ePf1DnF0SETGyqHeZLa9Ttweo1W/h5s1rXNu+iRUBlEfZiBJgtMLWgab1eJWgVMRr8Cbig8WFgCNgraWtWmSeIr1gMEhIXcv+9pyRNjy+3mc6L4mJZ5ZIQvAkhcaYiJtZhrlg62JOcJ1K196tGBSKXl9j0q6DfVSSpXPcvd5wuYb+7CplWTCQjjzNcJXEjFLyfkYI3fW4ujKiqS3adO55iRnQywXrfYVSCpRipSiYzGqefOmAnUmFSHps5VtM1ATrHEJFkl7CUtW0ukIkkf3xIdW8pG1s16slgFQCnQiUEiitcLZL91zOPYt5jW27RllSdusao7p/E0U4cxlYG9C5QAhBuewIRKsch63r0taSFElgvu+59uIh/SLBpAIbIirtvDfzXFKVgUld0vpAEyyJluR5ZGujQGqJ84HRSsLOdsP2uGJ3dhfZKsrZEqEURqRUrkFlCW0F5dzhbcTbo/tsIkiMxPrAwUENdMfu/W+sQPr1QCI9SVrdt3zl6tGyR+5ZX3nsHxhzqVfynuEeAJ/eeojZr2zi+pFgBCJCO5Kkh5Fs8tYObF5vbHxc897pn+F///1dLcJ3D57hB3vlmzyqrx5KSK7qPn/j8qce+H4hE743D/x3f+jv8af+v3+CtV/rCujf7pCtYPgimGVg3BOkhwJTvn3uL1HAwQ9WfOq7/w6FzF+37abC8Esf/cd8t/jDmJ86r9hsfu70t35ca/R2wOA6r+iutv7lyFMvfZC/sPENrO91scwbgbcEqQnBE3zLcWjgXeesJYTo3Ie8R5iuRaxUuksFUpLgLFprVJZzOj0u6PX7rG1sQIxd93Nl0GneBfBAUy+QFxRKZwQCs8WYxla0bUVrLSJCRcWSOcE7rLf44LA4Ah7nPIORobUVviqpDluWs5aq7AhQ1UrG2y1pGlhb1eQDQZooEiMRMhCDQAiJSiWJ6WZJL2QSWylEMUJIDdYzPmyZR8gENGVDWyWsrQ8RSuDpHNZUFOAlru2cr55/aU7bOPK0K4xeuTSi1jUPXdjkvQ8/wtbmJoPROkhB1J7gy87tyTd4liA1ymhElLi2petgqkEqIpLgO9MArQ3WtoRYdufeN4jQogjkvUHX/ybtdVbQQtFWJYc71+mvXqQYbR0V6yf0his8/N73Md65w+xgG6FTBquXCK6mnB8QfUJbT1HKMNx4hGBb9q99nnxtk6ToIUKkyIcIqajrmjS9wsZ6xnLxImV1HWMKtHwXwzDASEfwDeJoekQgXoZ0wPlKmGPGwj1E5MyiYwuPe2tkzmzvPtOAc4Tl/rfiOVuQjiEFPAfTJ6nsHiFYXrz5i3zuS3eZti0ilZ2tpwejIt5HgskwaYKrRVcrJANCdTbDOkKrQORgUk1sHNC5kfTXcpJgyctIf5iwEvssU8MiTbFNgwiSal4zNJHeQLBzuyHYLpXyocsZq2udZfd03sBccmO7oXYgfMaVC+9mpXiU9b7k7s4eh5M5w9V1VlZXyBJNuVxQ5AXLxQIhQQqFRLA66DEwns2BZFhk5ElCv5+htQQlGY1rbuzO6FV9vAgcqgmKbvJAGkl6IScOHXa/xocAQnTF8ykI2TncudYjIkjZ1Uq5ox5WIQSEkITQORaaqDqzDR+6Gr9Mo3KJj4HDcc3hYcNq37C11kMqAX1NknX1XOXccmd3QpYqklQhNQQXSRLDylrkYL8lEmikJRK4eNEQ8UgR2d8rqRtJb6TpDzQysQQl8HVDqCO+sRAdznuiliitcapLoQjKY4xCCYGWEI/usUooFBrhIIR3CkfeaNTO8PBoAsCdcgTA5f4MfvvsvnXvLIbsz+8PqNxuzvD5+1MFs4PwhjopfT1gysjWZ+CXP/ObAPi5je/gz1+O2E3H//t7/yn/SW/xJo/wjcFvLyzP/tDf4ke+7bfyxf/1fcSvMjozM4m0nKgjbwoiDF46DXS7Bpivv9PVG4X5Q5Lf+yO/yF/a+BT915HQHKOQCb/y0Z/kY/wI+qdfucbmLY34yoTmGKaMmBtv7LG+JUiNty2L6S5pPkBIzXJ2CNEhtaGtS6QUJGlBW1VkeR8hJT54ltNDpIioNGd2eEB/OGBl/QrH0WTbtOzfepG1i1dI8gLblAgp8NYTg2flwsNIXZCtFJ3VcezUFXHUbDFER4wB521nXywii+qQcrGkcXPqekJdLmirmsliyrheUrnIdG/JJHhGg4TVdcVgVWOSbobXhQBRdD0r5pE8N6hMs7qhuPviAn8wp9E9pAgMBp0ZAW2krTyhammiZLqs2N07RGmJynJ8BK0VSgb2pjVN63j8yognLmUEBPPUsJoa3HLM2soT9Psak/UgFrS9lHpZspjt4nVLMIFIREuFyntoNCImR81Ja7yzeNs1GpVSE6PHZAVgaOs5iYrM9rfJhqvopCC2S4RKyPprtHXFfLpHJJIWI4gBqQ294TqjrUe4/eznme/fpTfcIElyaqWpypIsH+DaiqY8ZO3iw3jbcOuF5xlsrdBbSVFaURRrZInB2hrlU1L9MNbfIQZo/YLcbDIICtVUiDwi6OqEmnaBEJL0qInoeapyb4AXTxbdw11OPnHf+mcWintIzDmt6AzjEef2EU9SzhCRstqltgc43+C959aNfQ6WbRdcx9gReWeZTVpSGQhG4b2nDAaFwtvOvjgEQetbgvSE2Lm85akBKVm4yOFTM0xdEl0kXzjyzRVcIVjOK0LjUS7SLyKFbNm+5ZiMPW3rePxdBVcfSklHCpSkvr5kb9uyWEZ62Sofev+HeOTKo7TWcvPuDrOyRac5q+tr9HsFdVVRVRW2afDWoYRCElkd9ujpSJ5IBnlKv5eTpRolBUrCpbWcRy6ucWV9wLO3Z+zMC3CSqZiABWkk3gX8wlJPK9qqJfrQEXoUvol4504mUoSkU4xjIM0N0QdCgBAiPhyZZ7RdsZOgU2rjuOHW3HELSaKh19dsb1RcuNTHKI3H0k8lJpe87yMXEEGRoLm7d8h8u+Zwv+Zg3KXxFYOcqARpT1IMFfvbNYd7FdZJWhswEoqBgiAxSuJlN4ETCWipcA58bWldTSk6q3fvjhr2Oo/UEikhWI9SkvXeCGzEt2/ziPjXGS73Zx3huReXgG+6f/GXbl3GN/eTnf5TCyrQdQABAABJREFUCek9io/wXZDxVke+H8j3ART/xZM/yu/683/9a6pteCtDCclPves/8Kd/X8l//JmPAl1xfTKRBBNxvVf+vuzgzVdDktn52pl7m2O+lTF/WPJXf+zv8zuLBl73LiqnSIXhkx/9Kb5ddOYBLgdpQdeR/Y8INj/71j9npops/NqbPYrzeEuQmqauefrTn+SRJ54g662wfe0aWkekEkxnC0arI5SS1KXDVRVKK/YPxizLikE/J80ybt/aY3N9xLvf5znY22d9c52qcXz+M1/k/R8sWd3cpClLhJA0ZcliPucxrSgG6zT1gmKwBkikNgipAIGQErwn1QXHOUaFGRKHnAShIXZdyK2tsb7BtQ2uqVku5igtuHX7BXZn19mp7qAyiRYRESVFPeADj3wDo7VVdJbT2DnvvRyxrqZxLZPZmDZ0hgXRw95OoCodBkffGLLLmywWJRZFWVsaB0rB1lrGeNEy9x4/rrETzfpmj2IUyfOE7ckBWa+PSTKUNiTFauf+5AZUSTfLK8XR1K6UuAjRVfjgCRF02iPJQHiHb0uIDUIHpNKkRQ+jDaovuxqbZo5ra4QKaJMilEQEQzWf4OqSJMtRKkGaAqTi8hMf5saTn2A+vk1/ZYM0zahsV0RtipWu6LtZsnH13bi2YjZdUCuBkHcQQpDqHr3BGm01JbQVkg2CVLRNStSSGMEv9nD5CG0Mh3svMVneQZucra33o1V65Ax3mnImjir5zwg0Z9LD4n0L76VE59SWe+5RgtObfjwmPGdXjxHoevdEASE4JvMXaEODDYGqbijHM4LXqBSSQrBoHaYKNNbReoEzgiZqVACZSYrVhIinqhtUI2kmFW3jUFpRlxaxdFhr8aXtmqoSMHVkVNTInqZuHeu5Jk8dO3ct46VlNrYM+orhuqH2gcPDljWdonPJeM8xnXoevniBd1/9RlZXNqmaltt3t0ElrK71KfoD1lZXsW3DcrnA25ZUK2SRI7SmyFIyLQmuQUkNOAQeIRRN02ASTZ6mrKyuc+HSJba2xnzxhV3iTY+yEh+7Y11OK8LMdRbqRuOCAyO6PllEtOkmHoITBB/xrQOpcDYQQkArSZJ1imU8Eu+0ViAEtvWIhWB4IaU/1KxsJKSpoNdPWJQNe7tzpmNHvXAUmaJXGC5dHnaGJ7YlyRVGCSIO4zTtxCFXoK0Vu3cDrYMoNUkmO8OUpHOUK5ct3gtUE8BHgvXUbUNru9+rFAKBB+cZ9TKct1ipSPoZtI7FgUUODEJ36vCDhMN38PbBN1y988Dl7jF5Ykl+jGmTcfeZrZPXyVSw9uT5C6AZCQ4/cP9FMXxe3keSpItvm5n4tzp+dP2X+dnBR8A6hi+ArgO2d1S/QPd4fll8vcXWeJRqfcYRR9VvbO+VNwrzhyR/5cf+wRGheeNx1jzg8IU10kPJ6LnI6JnufL5jJvLa8ZYgNc4F7tyZkPfuMlptmE1mONvQNDWH0wVbm3MEESEN8+kCkyhu7RwAkfkkQWnJzsGCyWRGUzXsjWdsbgyRWnFnZ8xwlJP3C6YHh8xnc8qyZjJbMtxYY9V7muWSaDtLU5NmCJWgjEEIQb2YkBUjkqzHUc4UITgEIKXq0uToekhkKkcUPehL1jbA2YaNzYf4/Gd/gS89/RLFmmH9SsZs35H5q3zzh383w9UNhJC09RxvLcEHnK1YLsZEIfHB4YNjvL9PGyoOF4cUSqETReMaFk3LrFriQ+S5mztYF9nop1x6qM/+geVwUWLngb1rgYcvJLz/kYTgLK5ZQoAYNSH6rnDeJWg1RGFAKEIIXXCuBCF1yFRhkpwYHbaaonDE0IK3EC2SiGssmJwQAknaWR5aWwMKpQXuqNP5sauaSXOyoiDYCmVyHvngx5jtvoRrl5j0iEx6f5SCaLBtjZSSjcsPMVyvmU6m1PMAYQ9vJGlvnf76Kml/jlAJ1lkOd3cJtoKsQASHX4wRq5foDTZpfdkpbdMXybIV1sy7mBxcx+Q9snREdA6TFWecyDqicZbJdGYCXaPVY5nl9OF+Vqp50NV/TGQi1WJMVqx0ZJpIWe1R1mM2Vp7oajTqXeb1Ni4KfPDUs5ppI2g9NMJRt46waOn7ztwhKolXmugUQgRaa2FmMZlGSIFKFGkvJTMGHQXTgwXNrME7RzhqgKYzjUwMvoXUK1RRUDvL7k5DvQyEMpImggtbGSaCFoE8UWAjDsflqxmpGvHed30Lg+EaVdNwd3efIDVXLl8Boch7PbTWxNah8BgJMniInkRKjAKpIE9T1oYpRh1ZvUcBwpMWWUeYtWI0WiPLe9i2Yn93m9u3liSDlGxVI1YKYhlxraNxVXdNKYVKZUcaneiss9WRiuE7VSbG2P0d44kd+LFZRBARqUGpjvk2S0uWQaISLmwVRCQ+WDa3Ui5d7PHSM3PKhWdvXLO9V+NtIM0T8kKhjGa2tCRCorUmjZLaBtqyoS0tzbIlzzWmZ5BGEQiYYSRxkbYqaWZ117QTgRaQpYI8VyghsU4hJNigmc0cblGRat0pU9bTVhXSfY038nfwloUW93cs38yXbH74pZPXT965CE+eT7WZvifyjWfWOcb8gynWn1eEbj23hZmcj7ZVIxg9//ZJO3qr4NszxaWPbIPRzB+FdCwJBgYvCdoh1BuBdCyJEuwgIi34LN4z63YPzr731RKfCHopzilGuhJk+4LFQ9011pkdvP2+8MUVyf/rx/4RP1DUX9f9HpsH/NHV38GkyXnJPEzvQ2Oqn1t/S/fteRBeyfb+63EfeEuQmhAjtXXM5iWDtRFewLysKcuKugk0bWQwKEjSgsWiZTqvQBjKuqGqGoxWRKEobeD5Gzu0LlC1Dq26GdX9/SlruzvM5xXj/SlKSsplxfaN28gIB7v7rKyNaJsGpRRp0SPNCkyWUc5nIO7SGwxJ8gFSJzTllBAiaZrRtg1tVWPrGikEJksxaYbJc1SSIYRksNJjuKIhBiZ3K6pZJOlZ8LarIhICQleIjIDgWvr9o/StEBBScWHzse5ceXdkiuAgdikz0+ku1XLBBy9VNK2lcZbbkwOyvOI935ygIty5MSXYlhsv3sLQ5dUXgz5CZXhvKRczpBqSDnoEH4neI0IAAt5aysWE6B1p1uv6jNgSsKS9HkqZLu0pOnzb0pRTyuk+Os3orW4x6K103e5DJCSW+cENdu/ssHX5KheuvgtXzRFK05ZzemtXWHuoYP/654nBo5P8KKXKYZsSnWa0TUmaZuTpgKQYUZUV0+khzXKMVgnD9Qso3ZFTnfaJa575+C4xeqTMcMt92nxEagxbm48QY8AHUDrHtgteePJX8IlgZXWTfjKgt7KBVCntckZdzVFpQltVkESCjRTDEcF6UjMg762QpD2kUAihXr5e5576mno55cuf+rc8/qHvgsRDkEzKGzR2yqDYIE1GLJo9Gl8ThcABe0vLoetqPKKGBEOWCGTbEJVAJCnB5KjGUzWeUEfCMmBlizYKlUvyYFAKsuBI+yl35y1RCITqgmCAIEAODb5u8DZSlw3SOoYqQl8QRc7unkDHls11ifURA6R5xkZ6hZHewqQ96tYxPpzgouDqQ48wGIxwvqvriN7jvWM+nRKdJTGQJAohQEaPRuA9HM6WHPiGuh2jpGJQGFbHC1aHOUppBsNVlAo8/u4r2Kbm+vWb3LmzTwxryMxSlVPaxnauf65Lu5NS4m2XXhZDQJmu0D92JXpo0/WpEVEQQ0QoiTGSXr9ApRCCBSHIV9YxQSNKyXJXUYnIzgwmC8FKlnBlI+Mj7xkwr2tkCgfTip3dhtYJ5ktPjA0IQStD17S0sWSJJk96lLGinxmEiggl0EIipURoiSJSuwBFgkIwn1dkKXgRuhRVpTA+cDixBCLDVYXREoJgsd+iRGS9UOTo+xrDvoPf2Mjf/YDUN2Bgmvtsh9c+dO2+9dqg2P7WwVFfr1NMr62Qb58nQNlBJJ195ahHNvBLdcb3529DGeA14g8//Al+JvkY4okFKrXMbw/RM0VUHVkcXgv4RODTrs/N5D2SqCDfiagGsmmgGUrqNYEuI9UFQTID2+eElEQBIXn1kaY6Kv6fvVuQTLt9929FpA3U6wKfRXo3Jbp5+wTjQUP4Qwf8ow/8j3w4fXOaBKXC8FPv+g/8+N1v4ZnLF+n/qzWK6etzDstNiVnEE9vkKGFxWdKOOmX1rDo7f0gyuHl+v81QMH3idJ30QCId9603f0iyeG/Lo4/s8ace+Y9kwp57v46Gv/jzfxC1fPUmGKoRrH/xtTGhtwypcc5SVxVNW3NwOGa5KJlO///s/XmwbVt23gX+5pyr281p7333vib7Vl1KKVkSbmTLGDAYu+wyuHADLso2GIqqogIKVUVQjoCKcEBQUCoHYQNhqALZFVgYA4VdSAoBbiRbli1ZXaaUUmY+Zebr7rvNufecs7vVzDlH/THmXGuf1+VLKV+++/KdmXHznbPP3muvNedce49vfN/4xhY/KItQOENdN0j0tF3H5XpD2w4YMRwdzJAQ8SJ4a/A+sOo6TpYLghhWm4EHD1Y4WxIp1H2rahgGYbdpefhwzeXlVguORTD2IXVTUlQVQ6/AY3lwgSsc9WzOo3v3iQiLwxld13P/pUd02xaMYbFoKMqC01snLI9Psc6xurjPwc2aPnh671nWlt2Dc+5/8TPYuMMVBatHdynqJTEI28szBDi69R7azSXN7BBX1FjrCL7HOGVXwtABhsODmyyaA466ViUxVcMnJGJchYja1XbdwGa9xg89g9TcubvBngWapsPEDffOBpqZp/fniAwcLhbMm4bgWwYJmHmDEcFYaC/vsbk4Iww7lsdHzA5u4EMkxkBZ1RTNAlt0hH7g8u4LNAdHLA5PMVZdfZx11HXNdnPJ+vIRh0UNvscVJe36jNnhLQ5vfpAHL3yaYuZxtsQIlPUC4xy+X2Mk0iwbrCs4PH4CA6xXG4a+ZfXoDrP5odYNRYe1wtCusUWBMyCmZH1xRpQvEmMPpqQobxLLBV3XU5U1F8MFbfcI4yPr4QGD7wmbQFEVmN7QXe4whWV1cc7B7WMY4OLOI45v3eTg5CaucjTVIQfz2zhb4lyJtYXKp/Yc0wQhhJ4v/eov8fd+5pc5H3pOnpkjg6c+rBAj3D//LLeOP85294AQHNF2BIE4eAKO0AhlFQmdp8CzOKpwvcXVNdsY8G3A+p6+D5TBsV6vOFgseHp5g3pZsNtsWF90WmcSRWvWBpWkLW4fUB7V2KakXXXEbc/J3GBnDauLgW074FuhpCeawL3LgDGRG7GhqT/IZrUkisFWHmRgtd7yzHs/wNHpCRZD13dYE9lcXrI+f0ToO6wz3LhxzHI+49GjC3a7HsqSi/WOZ8/O8DGy2mpTyqZyVMbz9BOHfPDBhm/ZBg4P5zgb+eD7n+T3/LZv5kf+zqfYeuF7Pv7NDB8848c/9Sz3H66xRhvbGhxVUeB9wAeP71LNVV4oZ6nKkqJ0lEXBfL7ElQ5LSXNYUjrHrOlZLp6idrfAGLa7C9rzjifqhk98cMk3vv+U08OSat6w3WwQM/D5F+7whWbH/d2WbfRECfTeM0RPZgNdZSlLOFrOKI3Fo+dsjdH6GSOAo7ypktkoQh2XCMIQ4t4+g5ObESTifASBfhDM8+p89v7TOU8sav5q/Vh8JVyPr5NR2TCaIlwZn3z0qodeXB3xYH21hiEGx/wfzK6wiH/6V38P3/ENf4kTN/8qn+3jN2RW8T/9xv+Y9xRL/udvcZwFVT889Et+6Dd/gpf+Px+keSQcfGmLDTNiMYHHUBmKVli+pEHhvoueb1LFpoVQG7ZPpZ8bwQRDLOUKm2MiGG9wO4MbIgdfMLherhS4Fxtlq4uvYs+Rt3qE0mD+8H3+zrf9V5Tm7e96+mee+mn+yOnf5Z+9969y8hldv1/vMBG633fOg7MFAPPjHX/+2/8if+7OP8JnHtyGXzqenvsauQIj8Fu/5xf5R09+CYBf2L6XA/dqNut3HnyKH119gqVr+f2Lh5Tm1bV9/8zv+/Nf0bk/Clv+rbvfy0/+2e9k85Sh3MD8XiS+wdfUY/INJrTtwG7X4fueMAQslqYpOfeeF++f0/cDx49WrNZbhhjTq7TLepSItbDd9kQ0iO/DgIRI3wd8GGh3S+YzA9ETBNqu1X+7LcMwEMUxmy24XK0pyxK/jbgusl1vcc5hUAtX7+Hh2RYfB2xVsN30PLps2W46jAjn6xYfIi++/JDF/AWWBzNeXj/gnIHlDcdsUdNuYLvu+Nynf4H7d55lcTin3w2U9QHtrmN9saIoC55YX7I+v2BxdEDdLLC25PzhI7CGh48uaXdrmmZO4Sq22y1d11MWBUXdsGsHTk6fYNt5FssFQ4BdO9AOntVmA1i6Qej7gbIqKeoli2ZDVXYq7zqGWT1Ql7CY1Tz99Ht44bkX6b1APCbOZgzs8KYg2DnWwtCucQKxWxP6gWp+RD1bgASGrgURNg/vYoCn3/8B6oMjurZjs3pIM1tiXUnwA9uLe1TzUw5vfpDN6gwfBlxR4HA4V7Febbi4f4dnPvwx5oen+H5D3TQE3yN0+AE2lw+Zi1CUJYZAM5+zenSPOGxx9Sl3HwSeOIqYYkEMFaV2OcUMkYeXNYuTE3y/RZpI9AEZBGsdztZ0baRoKnwX8DvP5mzFYnmAKy3b1SVD31IeVBj7MneHzxM6z2JxyND2HN24xfHxU8xnx2zXj1jttty7/zI//w9+hpfPW04fXfD8w0fMmsA3fOIZMJbz7Us442iHlk3Y0bcduzW8/FAteUH7jhQDLGYGFwuefvoUsYZHj1ZQdpgGXjzf4qh58uiE7/nER/hN3/mN3Lx1m8vLC/7Gj/0tfvSnfxlnLXHwWGuwYglnA3IRiIWj7TqcCXhfsPPCatXT7bRnVHHSEGJJUZTMlwuODz6K3x2y67Y0i4JuGOjbjlu3n+L05k3qqmCz2TH0HX234cXnvkBTFhwfHREl0FQVi/kcV5Ss1lvu3j/j0cWabdsh1mBtZmfh4a7nwfohv3qv45ee33DrZMnRQU3st2zXlzR1xfHRE9TH7+Ojpx/iu7/12/iJX/gVnr17Sdt5Zs0CMGw2G9bbLRKFqqqZNTOieJp5g3WWwpWAxQgMw0BZlnR+4N6Dl9lcBNrFObPKc3h4gBo915hgGYaSX73T8+K9DUcHc8QaNtuelx4YutZR7ZbMyoKCyIP1OT0D1bJhVtc0ZWDnWs6HjmABcSDJPMJYBhEkghGHjYJYQzARE6GMhmAgpHotYw0uWkzURqzWGY6eXOAG+PAzh5wuCorqnW8lez3emeOZgwueObh49R/e8+qH/q8v/w4+OLt/5TGH8M8dfYof2byfu15d5b6peZHfXD+88rzaFMztr7/nyNd6fLy84D0jQ3XBv3z8It/zT/9TtP/1bcKs4P632bHB65cb+8FyuYUmYcz22OA68AtLfwD9iT7PdlA/MszvRayHyr/6fY6+EGmPzZdl2x6X0R4bqt97n5/85F8BHp+mw99dl3zuj/7H/Kl7n+C/+pHv4Ymf+/XN5+wswg8e0X7SMBwHPnzzjD/64/8Cpz9eM1tfPfbypVezQ9VK+JU/8838Ct88PrY7tZx/61W98sd+xx3+1M1fTr99debzxM35P9/6G/yuW99FtYL6XM/PHQ+v+5rHAtQYDBebjvp8za3LLZtVS1lYCmOYlQWxj5ydbzi/3BFS4bZz2jNiuagpCy3mddYmKVHUpndxwFnDrNYPsPV2R5DIECL94Om6geA9TVNyudqwmFeUpSOKsFmtqUtlOh6dr7FOODicE6NnGHp2bcu9l+8hYuh7/b0qCjofaQeP9yVdH1htOs67jrO2Zbt2LG6UPPu5lpt9zXq1IYae87NHHB0ds9td8ujsAh8im23LZrsDMWy3O6qqJgTHnbtnuNLxxRfv0af3LKsiyXhAguFsIzx/f8Xi4Jh5Jdw6WWKt43Lb83C14+xihStK5nXJrCrwlMyWh9w4OmBWFwzi+PTnBrxXlupgPuN3/UPv46/+9Z9l5Uua2Yz5fIE1lkVTUhQ9lQ2UpaWsPAcNhF2LMxtObz7ByckJpfWUpsNUM2aNxViDxXB4+hSbiwfsNhcQA+X8kGHYEIYd9eKYGAO7zTkgDENLUdbMDk65+9xzPLr7gmbPmyVxSHVCtqAwlkdn9zl/+TmeeOb9lFVJXZfUT72fECKrTc+D85ZnTg4RA/cv7zF78oN0wxrnNrznqciq7fH9QGjWUBTIEKnqkjh4tpcdNu7ofUtRF/hdDwvDbLnk/P4DirZk2RzSrrbU9Yy6mrHtVqwvz+n8motHLxHiwL3n7nJ/KHju7pq7X7rDe5864Obxgk/96hnz91YIQh8HXBh4uHmelgHrA+Fy4Pxunxy7AhLAdUKMnru+Y1mUlI86DuYVRTBU0fDxD97k6ZNTvD/kGz70Pr71Q8ecnNygag64Wc/5nu/+jdx9NPD8gwuMa3CmIGI5WBzhCgcGnn/peVa7Czpv8f2Oxbzk6KgiOBBXUruGGwenvP+9H8Bve5574UVuPvkkQwjEzlOVDbeefIqqLNhsttx9+T5NVXD/7sv07ZZFc4grDPNygQCPLtcIsNnt2O1a/NCzWKhF9f0HK4ZBpXK2cBSuIEa4f7ElupL724Gz+/d5+eW7xOj51sOnaZoDPvfiGR97z5I/8r/4h3n+5Yd8+rm7PHvnHjGULJeHnPqBwhZYaymcQwTq+RxjLRbL+flD1utLNaYoK568/TRP336G84uHbDaXxOA5Pz+jKiuMs/TGsusG/B2PcwXb3Zq+b6GKSKG27P0KCgqOloesznes1itmzQx7eoOj44rbtxZ8ur2nrJLYZEWtRhIxRhBReZwV8IE6GGxQpik4CDGosYG1anpRGKwRahHmHzzAibBYVjgjuGv92fVIQ7fa4xmgvrQ9Gu2w87Am8v7qAf/fe99OTFXrf9d8iB+wVwO1984e8W2L56489uHqHt9ZX01TF2g9WicDFvuameev1firmzn/x//5T/Izv/vP8B8+/E7+t6c/xQ9tPsiLX7zJR/7ICzz6wfdw8svJvKgA6+HhNxkOn4WLj/GmJTyZzSl3wuwBDHcNJoDrtZb0y22HN2vt+1ojd6d/I6e07shw/j0tT/xI/bpGBKv3aX+93W3h9BcVwEVtAYY4fY/Lf3zDD3zXf8531YbHtcnrn771Kf7YH/67/P5v+Bcpf/iY6vLXZ8Rx8+cEsNz/sQ/wZIRfjyvM7GFk9jevztufOv8j/P4/+me/6vfJe4olf/df/X4AvuvP/+ucfPaNZXmPBahxzmoPjihIFNbblqZ0rLcdu64nOdVirDBvKmZNxeV6R11YFnVF6z0hRm2IFw19L9jSajG/syxmNcMQ6HrPclGzKAtW6xbvPcaoE9LgA7tdhxihLEra3UC7GzAGfIxsdju27Y4bR4Fd19K2PWfnK2JqBFoWlqqybDpPiIHdIPQyUIWCIAMnT1a024F7X9jy6I7neDkw9DtMbenantkzT/Hg3iXDoOcUJLDdthDh4nzN4qBGxHK5vqQqK2RoMRIJQ69OUFYtgufNnE23VVnPdsXN+Zwbs0hTF9xclBwUO/rNwP1NR7uzHMwa+mh4dLnm5TuWsiwoypLBB7quJXjPjZNjPjXf8Auf/jSrwTGfLzi9cRPnHLPZjMKV9H2HEAnBU5c1y+WSqqmRL71AYV5iVlecHB2xaCzz2nC6dDx9y9KcHNAc1Wwv7uOlwK8vsWXDsNtSuBYJA1Uz16JuU4575PiJW8xPj9msLlgalQ2W1Yx7LzzP8uSUxcEBIpLOyzA/uo0tS/rtis3uHBFPszjGOrj38ou8+PDzKRsvrFcPoanYPdxwdHBM6AMiHsTidxvK8oTVwwvEBmYHFe1uwIeeoR/o+4Hl0TGxjRgH5axi6Ds9l7Zj82BF0cy4PDuj6zx3w4x21xOi8PH3n9I4S1k5FicNvQg+JNc57+kuOl5+/iEPz3ZcbAMbGm2saYXGe+zgqQ9qThc1YRN4+eGOaITF0Qlib3F4smS37bHO8Aufu8f251/gYF4yqx2LxYJv+tjHmR+e09Rzeu+5e7bCh8Bms6auappqQdUc4jtPKDeIgQ/caKBwvPwQTg8P+OhHPkrf9XzhxS9qnVTfc3BwwMMHFxwd3VRp1nbHZz/7eQ4PD7i4OKPfbbh544TlwQJrDa4ouFytWK9bAsLL98+4vFhxcLDg9lM36PqO5198mc1moJ411HWNAOvNFtfCk0/eYjZreHh2TtcFHl084rPPPkssCuZNw737ht1uy7d97Da3To9YSMfPf/4BfdQP423bEWLg8PCIwhXsNiuw+nkSgyZKqrLGCDw8u08UcJXh5q0bOOfwvdC1LZfrS1ablrqs8VGt0oMPdMOOrt3iKmhmFbGwtN2WsnNIjIQQWK3XrDYbdqslQY6wpkCq7FKgPY/M6M5nMBEsBgu4AoraYggIEXEOsZI+a6Fw2oendIbSWYqoxgaFiNbaXI/rAVx8yPKh4/O3+zS+4hH3rMGiWPpwdU8/u36CZ9dPXHmscp7GXc3+fnB+xvuqM/7W+ceYuYHfe/qzlEyRdGUCv7XxOPPW3zPfOzvDLga+5z/6N/BL4S9/w7dj/v4RT30pcvez70VO4OFv7XjyhyrOvlXtgA9/VcHI4ed/7YmKr9Ty+ysJuqODu98TufEzjvOPC9W5hU9esvz/Hbyu7KpcC8d/u8GG13+jw9/xMh8+esD3v+eH+d6//yfZ3lvwgY/c5cGPPsM3/y9/me97+kf4ZFXg3kaQ+mbHh8slv/Ddf4nPfHLLP/VT/xLN3zhg9vDXV2vzVjmqnX5a+PfOvnmPrfnqjaVNstQ3sZUfD1BjLYtFxWxRUdYVZeHYdQO7biAmoynvI9Ya7SDf97jCIiIEHzmsG9zccbHe0XqtC7CFBSNUlboE+cGz2XbEGFguZnQ7z7bpOb9csd31RIls25Zh8NR1yWbbUThLWRX0g0ciBBH6YWC9aWnbAR8DTVUiAlXpKEvHwlYEiVo/YsBai+8LOvMkbTjni7/6CKo5damBeNsPWAPEqEXK1rLre3o/sF5rv5jtrscVUM5KRDyrdUvlLJW12kQwylg4fDgvsKZhvZtRl44bBzCvhIOFY3XZ8cRBiX36kOremjvnHecbIcTU1FREM9RFQQhq7euHgXa744cf3uW5lx4wiGG+WDAMXguQywrnHG27I0pQS+eioK5qyqpk6AdEImVVcrg8oq5rgu9ZVsJv+7bbfMwK/QBVPeditWa9XiGmwhQlZ2eX9FLQVE77FRnDzRvHeA+FHGHjMSbu2Nxf05SWbgjsOti9fI/b730fVbOgbBbEEFifnzE/vEl9cIu6hRgfcLFbMzuqeOYD38SD1R0etC+xOtuyuXeOPZ0zdBtuuYrtwzPEGVxdEQzMFx7cKX27pt9uWd48pJiX2MZyyDFBhIu7j6iPS8REXv7Sy4Te06+3WOcYLjfI4AmmwAdh6HpmtX4xVhY+cGvJ859/xMsvrfjGj9zAliXeeBpjOJSCVfA8uuyxpcP0Pc4ZjuYl87kjlAt2Q0XrDVSBpnEIR1ycw+LUsvE9P/2ZL9CuOppZw9HRoRoNyLmudxBC3NG2LX3X0fkOgxCbOe12R3M4pz6wtDuIoeCgKnhw3rO72HLj/R/AYLl77x6CYbaYM5s1hEFpah8GVpeXvPDC8yr59DUXZw84Omg4uXWMwdLvBrbtjm3bcblZc7ne0HUDdV3irLBdrbnYrrm8vFBQ0/dUVUlROG3SaeH84gJrHWApyoJ5VVEVjrt3XuLwaMnR0RE/9+wZDx9teO8TDR9+6jZPnZ7yM599gc++8JCyVmZmtd7gvWfXbphVNVVVYYwQY6BtAzsReu+RKIQ4cPrkAVSR0GkTTlcZ3OC4XK3UBwSDtQYfhL6PBNfSDi1VVWBdQet3+OAxGHwIhAgXm57wwiWLpxZ0ldpsOwETNdNjEbCpuSaCKQUpLLEQCitUhaWpLJU1NEZwhaWsDWVpKAqLCmsN/tzTRkN5LT97146jgx33v2PO8jnD7IGajxTvEk/ZPhT04Wo49PP9e/j5pH27ZMZ/+uL3Xvl7YQN/uVnrPfiK8aHZfb53MQV3DuHpwvO8L/l4Gacg7U2OIzvjp3/7n+PPfdt38Bd+6B+m/h8Pxz4wy5ciy+d2PHw4B4Tbf19r5vLVlI9hjUuoDA++Xfhbv/v7+dzvPOIJt+EP/KV/jZt/ZckbMQg2fHk2aPjB23zX9/0DbroFx4sdf+Gf+M/5XH+bn/pDH+T/8dTPAO886eE3VnM+81v+Iv/+N36Y/+y//52cfvrxs0+3Hn70zje+JaAmj+HjW+4vZsx/rn/d5zwWoEZSU0OVUMBTT55w//4FndeC2W7wiBF6H3hwvuX0aM5yUdL1ns2uJwahtE6zjmVF33ssaihmxLBtBwia9T7feC63LT4G2l4ByjAoOPFDZL3p6H1IdTqO4CO7tmcxH5gvGubzhrIs2O46BV1RaJqCIULolS1y1lI4BRy7tsdZw1PHNzjbFjx1aGijsKgdZeFwRt3Pdus1/TAoAPOewUe89FTOEY3gCoc1Bj8EJAizpsRZSwiRrvfaJbxwLGc1Zen4gHjCoJIwY1Bnqc0OZy03DhsMcDQvWXWRO496+uBVJhQjZVFqUBU8IoL3nu265WK9wVhLlMh8NtcAfRiw1jJ4bVDqC23m17XqJBeCT/bOFe2uxbkCP/TEMLC690W+8LnPUTTHPHXrhO1uh4+Rup5hXcGdexdEV1O4gtXqkicOS8TvuPeo5c55R+Au86bGIOzW5xwen1C4Jaa/ZPHojJtHGz7xTR+ibpYYW7BrW4KpiKZhkMiaMx5t14TWweAZfMujyy0nixNu3rrF9uYFpvRUyxqfGLTZ8ZLgempTUpUH7ExDUUaIhl3veelsYL1dE71w69ByYIWHqx3rsw03FiWusviNAoXeGbrWs1m1vP/2ISenC0pnuREsz97b8sWHG24Vhidu38AagzWWW7eewLqKO+d3qJ1g5gscntNZjYjjIpbsCkOcR1y0yDDDzRpW/QPMFjabNUYM9WxGXddEVSxxcXnBdrslRjDovtL9qckDZUsDrt5BYXAhMJeKzzx3iRXLhz74YW7dfpqzs/s8fPSI2XxOVZQUtuCLX3we5wowlsuLNavLLcuDJWcPz+m84bINrF+8SE1xhcNlw+pyxcVqzWI+ZzGfM2sqwtCxXm9oVy1EbZDb9z1d21M4BTBVVXDnzstI0B5PPniKwrFYzGn7lkdnHbvNhur9NQ/aBc9/5j619Nw6XfCxp29y2hi6Ab70YMP5dqAwjqaY0XcdQxioyooQgiY/qhrnCi5W5yqnjDXn9x+w3mwgGMq5wTUG62F30RElMD+cs2DJrJ7Rhg1StjjroHNEJxhj2bYd3mtG2Nclu77gFEsrPdYLFJZQAMZoQkTU2MAaMIXBOLCFUBSGunDUlaNwhioKlYBpDdZbqC3BRsRY2pMGa+Ha/uzdOz56cp9/+Q/8Zf743/1jyE/OHosmjl/p+JFHn/iavZeP7lUSuDxe2B7zY2cfHX+3JnKj3nK/XfK+xUOW7moflJNywx84+Pkrj73Yn1x9jpvzp27+Mt/3Rz/Fd/79f57wN49Z3NU1MlFoziOxMBSbqG5kN9+eBqW7G5b+COqHGnV3p4buW7Yc/40Zl//Iho/cfsDvvPVL/B+Of5UveviBe7+Fn/rhb+Hml5EVvdmRjfY6GYhimBvPHzp4xB86eLU5xSCBF/zuDY/3UpjzP1x88lWP/9GTn+Qbq6+tWcX3nT7Ln/znv58/9/CT/Ndf+Hb6v3fK4iX5soYC1WWgubPl8uMHmAizez3bJyuKVvdMdAY3CKFSA4hQ/dq+Bx7+9acI3xLfMvby87/9vwDgu//i9nWf81iAGu8Dl6sdFrh9c4WISrhmdYlE6PqAK5O/qoe+8+BgtWmJXuj6AWe0TqOoLEMIGAz9EBhCwFpD4xyFtRji2DgvhAAiDH7gYNFgZwXrTct61aqczTlCjAxDZL1RA4BFUyOirJG1RjuLiwKL6IUy6fB779XCWITZrOYbDk44/K73Eb8t8Fd/9O/jbFQ5S4yIRB4+uMRbp55HhcUZo9dTaoNB6wzOOAyG0AuxiDhnqMpCu6KL0A+eXd8xm9VUpSM6taJ11iSHuUi0QjRgHDSVZfBCZSNtL3ivoMZYO4IRUJvby80OHwJWhGEY6IeBUo2XCCEQYgrCQlBmTQI2OES0kH0YfAqYe2IMBO/5pYfn3Hu04vhkyxMvn9OUlqNlzclhwBpDU3isBe+3LO2OJw8tlxdnvPzSBV+4v2OIQlGUiETO7t/j5hO3UvAsVIXjqaVmM55+6iaLgyXBD/R3H/GZLz3iUWe5cRaoDwMP1hu2bUdVeigtUhueWJ5QLd7D+fklWMui8dx84gO0w5b7l3cJPmCisOsMD57rqI7g7vmWB48GVg+3LG7MKTaRJ8VRHxzSnu+0x5GP2CQfCh5qSp44fZrT05pAiURDUUY+8OSc0xnMKRgutly2QowNRg5YdYe893ZkFw3zWqgxnF8YLrYl0cBAz6wuYQBvI4/6+1D0rC96/CDMm0PqmSOGgHMNZVVxsVpjTEHf6Qd8CBFXLOhaT11VGArquuZkfsAwWJZNQbftOdu13D5d4r3w2c99kV27Y9tCN3TEhxv6/mXatqMqC+6fXRC9YJ3jueeeJ8SAtZa+UwZV+8IEPvCeJzg4mHNweEBTK2idz2dsLvXejSHSVCVF1bBrW7brLTE6omgTzYvzC2ZVRTcMbDcbTg4WPPnkE7x452XOLy55cP8hBOHgWxpmy2PuP7jPc5+9w7yuOD2oqRwcVAWVsfRi2XbCwyGy2/VsNjvqoqQqS5yxWuOHoywbfOsww4zYb2mqGc7Cbrdi2BmwgaYu8a6lW7V0q4HFoiLEiKtKFosloR247LbEVCMzrwtisrLuW8/7n6mgsHQIPggxwhCF4AXpI/SajPHR0A3CGoM1gZz5tBicAZIpmrXJujpL2Qysd9fNat6tY+sr/swL/5g28PwDb/fZfOUjiuV+u3y7T+M1x/65Pbc5fc3n/N2HH7ry+4Pdkhf+2CH/xfl38r8+/mlObcHSNtSm5FP/0H/Jj30b/Ev/xb/CrZ/x+HnJMLep9uXVIxNur9u0U2B2f2B369cHhO78togR4Sd/7/fzQ5sP8u/87O/is9/7A3Qy8K3uT/Bnf8Nf4nfOVea3jj3/xA9+H0/8rHDCrw3QDHPzqmvqTg2nxZqXfMd3PfEcP7z+Fn74dV6/Cg0/f/HMl32f+BoTd3H09rilHdkZ/+bNX+HfvPkr8F3wp+59gs+ub/FTn/owx58uqM/jq+qNrBfcxQbkAERw2wGoWH7ugv6JBbsnSuYvbFl9aMHi+S2XH1qMzpn7+8JEaM4Gdk/o77P7A+2NcmwU+uWI3Xthw9y4r5ip/ErGYwFqQlC6NITIZr3j/HLDo4s1zhpKV1A6yyDof0OkcI6+9Qy9FsCGELXXiwE7KNDogspC6lItnEPQfhQGGHxgGAKxLtjsOi43O2IUjpdLvA+EEAlBWG06YoxEgX7wlKVjtdqw2uy0a65LtohC6nOhwIEEmpzTG6Fte5797Jdo6ppdN/D55x/wze89RFA76xgis7pi3akEbd5UrFZbgo+YKLTdwMPzFcfLBS6ZzXb9wGbX60YyuvskvVddlypb6zqVZLUDpSu5e75l2wd2vWfdeTZtoB2EdtBsrcRUeIxKxrQIWY9sjCWKqEQuClGi/h707okJ1JgYscYQJWpzwhhT4KSNRfVnrRu43PUMQ48vlqzaQFXAjYOGbvDM61LrlBoLViibgllTcLbqtYfRriUAblAAvN3t2Gy3FKmhYIfwoaOS5597gc3lOU1VAJGzy8Avvbgiupq4OeS7v/UZnikKPnv5gHW14elbNf1uw5cefoGT/gYnzVP43cCymXHj9D20uw13X3yI9wOXqy0PVxXrvsCvtuy2Pd2up9vsCKGnu3Q8s6xZzI6IiwvK0jEMkWW1pB12FD6y3UYiA/cfVgw+8vTtE0x/l02rtS937q1BSlq3wBZCWaygFOojx8wWxF3F6tzo/izUAVD7M2k70BgDtWtwzDjvz/C9IxQBXwPRsWsjPqyxpqGqHCEUqV+TxQ8WkZrtLvLo/BF937Ndo+yOHwgh0vcDn//SHYryDND3HfyAMQbvPSEE+r4HhLKqMJgk19J+S6S9lIveu7bl4qhmebQkxEDft5TO0e122Og5mtUMXcNd0furqks260DfDUgs1bLYGS5XK6wx7HY7nrr1BFWzYL48YtsObLc76qbm/r07HJ6ccnJ8Alju3LnDs8/tiJLuKWOoqpKD5YzT4yOiGQgiOArKYgYYtt3A8rDk/FxtvxeHS9rQclDfULfEzYZZc8SweoihZLtZ4fuAiMUVxzy4f05VeoY5lK5is94SQ+DkYEEYetbbLbdmM3brHcfFAjsHaoctHdaAC2D6wMVZZNM5Zsse7yNtjOysofeBzkd6Hxg6h7cCTogBTTikL2sTAW+STO56vFvHawVv1+NrM14596fNltNPfoGffvR+fuHyGU6qLb/l8HMAfHP9Er+pdvzUn/x+/oUv/ZP81E99jOqZNYd/dYkUBhFLvzBcflj7kDSPAraLbG+XY12CGDNaMofa4FpPqKoRGNXnAT+3b5i1P/uWyRp68c2P+A++8Yf4x+f3WNoF/5vDe3zpm35Kj2VKPv09/zmp0pkgkX/n/ndz9Dle1573/GOG4eANGAgDtz5+j6P61fbC/83d7+C/t58kinldEPn1Mv70rU/BLeg++CNsf8/AP/PZP8iD9YLup09ZPidvWH+0/cAhxfaNP/TLVX8F7BarHhKoKTYDnBaAoVwFytUbMzx/+Ff+MP/Ek7/I950++7rP+b/c/SR/4vTv8LFy8Zp/DxKJbyBRfCxAjQiUhWVWl1yuW9bbjm3wlNHhg1fpSxRCKnbt+kF15GJSdpaRNbFRTQeCaAAdo3b87gavUiUxDEMYu4K3nafvA2f9hs26pxu0I3cIkcqqE5qI0HcBS4/vA7vdQFMXxLRZfB9ATAJAoi5saB1QqmFnte7Y7Aa2bZ9A1DKxNEYzz03Bdhh4+GBN3ai0zvvINgjRCoMPnF9stC5IhBj0OogaGwpq0/rg0ZZ7D7esdwMP1y2XO62TGCKstj0+qvFBUNMkrGpOUEW+Xo94tenNvTIU1kjqYaIz533AMCRAlZ4jug7eey2KJmIwGKNzKDF73wsx1QQcNAWlCfTDQNdr4bO1wrIpOZhpU88QBUdku15x/6zn7HJHN2jDw2gVfAWJDMOQbL71fB6uIq7oOTtfs5zXFBbunG1pu4Hd0PJ83HJaB8qy4gsvXbIdBp759md48uYHKWaWXb9CGihrx8ubu+yeB2LNYn5E7Rf0fcvTs4ptt2Vo11SzDe0Qsc9YLtaBxSJyUBwRF4b6mRmnteczn3uB9733ae6vWjbnD6lroShm3DxaMKst3/zBW8xnz/CTP1vwwt0tu76idA1lbalqoXTCegi0/YzGLhjaQJAB6xzdZoezJSEG1ruOfmi1vsxu6AdlRfzQcXZ3RVlWSFQAsttuaZpZYtwiXbvDOXUAi1HdBNvdDu8Huq5LcjT9F0Nks1nTzLT5pQbKTH8XoW13uMK9Yq9kSdsEnGMUBu+5d/+MtmtpmprjgyUHiwWDNTgJFM7x6GKFMRZrHbVV4LHpN2w2LWVZUNcVu13F8dERN2+eslwuaTtPUTXU8yVzH1kcndAsFoTocK7k5ES/+L70ped4eH6BtZaqabCxpA2O2JZgDE0doRS82SjTVFS4YDBO972hwBmtM+t2HU5q5s0hXdtR2xKKYy7NBZuuw5gK3wmh7wh95ODgGAn6+TEEw8W6wzrLfL4AB599bosrgcqpaYCFIgh1FGWIGssQhdIIs8Yxnzmg0Hs9Ct3Fgmo24CpP7yOD14ajIUR8F+nXJgUd1+N6XI/HafSh4O7ukP929xsA+KHiW6ms5588/RR//PaP8zNPvoe/9J3/Gf/dx76DH/zl30C/qvid3/pz/I9/71t5+M2Ww88XWA+XHzIMhxHXai+aZ/5mZFhYft+/8df5gb/2O/jXfv9f5f/+P/0eZnccz/xYy4NPzF/VZHF/zD/xiN/6zLP8qdt/k1tuwb2w4Y9/8ffyvaef5X93/Dz/pxs/w49uD9Kzp8D4x9bfwC9cPEPzB+6+7rE/VLdUr2dx9mXGaxlEfLXHZ/vb/MbmwVv6Hl/JqE1J7Ur+x2/8awC88O1rLqLj/332W/iRv/Ib+cDnST3yMqpVYHtlfIV1Ouv3zpAUEw4H6pL6I7s5v3v+aqAJ8F99/C/x7977rW94zP/ml76d3/Ldn+Vj5WtLzP7a9pBf3t543dc/FqAmxMi2G+Byi48BHyOVKxh6T1naFPBoFC4CnRcKp93GSUxFjIIPkdKZlAswI7DAQ3TC4dJSlhWbbY9BA/OmLpg3Fbt2GLubKziJDJ4kZQMwbHcDIgM+RHzo1PXIWixCEG3VZ7PdKuBDHJkUHw3OWqAkRGV+vPfpMajmDfWg0prL1Y4YJAWdATHC5brFRlBfAA0WVV4nrHcDuz6w7jw+Wg1YQqQbPH0QfExgRUggY9q76ipnMChA1OajdmzYZ0z6AZOC1DgClBiTzaNJx5QENKNosGrM+H7GWl2s9MYSBYmeeV1z2BRgtCllXRYU1kAKpredJ/iAJfLwUeCFhwPrLmKsrr8xNjFi2rukqiowBgmRly565gthtqiJUrCYO566WTOYLXcvdoitWLeByg/anHTb8sJzd9lc7GhmNWUz4+FmRVk4lm5J7AaijSwPn6SQmqVb4fsd7tZTSNSGmLacI8DglY3qBk/0Lf3uPrsoPPP+A6Qq6NpLtnaHcz2/6RMf5BPf+DFefvCAddtSNUtu3/oodx69jA09gqPbCf1OMBJZ7wZCDMSww6d9FEJg8F5BYAhJbuixqSbG+yGBDmG72TCbi6558MQkw7RWQUeMgaIoKAqHiMPFwNBbqmpOXTfpPpSx3qrrCmbNDOecAmMxe38f2O22NHVDVSnlnAFy2pDjcwc/wFZrfKw1LJYzjDNsdzti8NS13tXbtiWKUIhKN5fLBUPfEoLakJeVJeKhiJzcOubGMzfxTqgPGhppKGYFZlYSG5W+he0lQ/R04nnqfbeZ36xZ9xuauqau5xSlpXQWJwe40uAqrR+rJeKosXLIyekpRixV2XBydMqsWeD9gIiwmC+5fes2hSsZho5du2O93nByfIPTkxt6zxmYzxfsdhtCiGx3LUcnN/FDj7UVs1kDtqacqTthNBk0BgYUGEdvWF+i/WqIRGsQB1lv1sQZQ7QUrcUZqCpD2RisjZhDTzwuKcvH3xHoelyPd/tofUlLyQ++/N0AfMvTd/jzD74Xi/CJp1/iF19+ik//+9/KR5/f0T7R8OJvtyy/aHnqJ3rKtceEiAmCOEP90PA//Ol/mOMa/oOf+8conmjpbli6T1V835/4y/zow2/hV//Db0CMyr2qjdZcbJ4y3Jy1/PEbf5uXfMF/u3qGv/jcP8S2q3jUzfnM5mkGsdzdHb7mNRQmcnO2+VpO21d1/J3Lj/LPHtz7mrjffSXj/3b/m7jbX53z7cc6uvedsv5DF8SfPOHwlwcWL3XYIWCGwNwLWMPipY5YOYruKpAt2lS7Fa7+rmNCQss78L//W/8c/8O3fpouFNTu1XLmH/+vv4N/5X81mTX8huUX+RNHL7/p69vEmhhfP/lmRN5+C4VbJ0v5p3/rt2CAWVNgnWUY5ErQHxNocM4m5zPGWhJjFDCEJBULUYucS2eRqOCirh03bywJXjg/34CBsnKcHi0JIXCx1qy2QRkfH2JiEzToLwuHtSqd6VLtSeFcYgV0WYskN7Ops3eXistLV3BwdEw9m3Pn/kN+4uc/x2/+2A0++t4TnLU4Z/jAR97Ho4uWL33pjCEE7aMzePohybqsVQ190ONuu8Bq17PpPNs+0g6RICYxLyT5mBBHTKJgyxmDc+rAFEVSxlv/haAb0LwCvYsIbdty/uihBkfNjJOTGxRlkYC/waQb25jUGDExZVkWqI/bUZoXRTh/cJf336i4/eQzLBdLlk3FfFawaKoEmGA3BFZbT9vuKGXNy9uazjQjw5QD8Qdn92jqGcfHx+P1z1zgqZM5T944pigrbt9oKJsl5xvPejcwaxrmTcngI4+2A+0QOZnXNKWCOS8WYwuauuJgUTKbN1hgNj8k+ohf76DvaHG0YollSVMX455Ytdrnp+0C56sVhYnUdUNRBHwIdN2KR+cDpwcL3vf0DV56sGa92VCVBYOHXecVaKOSvWEYFDjESFEUKeOickRdW0A84nuqwhKCsjNCahZZFCDCbrdjsZhjjNFeLyK4Qu2yfYT1eoUt6vGjygDbzYqirJIM0SB759SnRpSZuRFjCD4kl7CO9WZNUVQE8bRthx9iYikTA5hkjdvdlu1mw/JgwQc/9gR1Y+l9QAw0TUUzq/Ahcr7aqDQzG2egFspD78HA8sacsixZVEsqV9PUCyw6X5FAYSoKWyDOY42jsKVeZXTKKjrtc1XaBmeLEZhbXNq/ZgRvUSRVpup1GLLtcp47M2qT8yNCHBMCIpkNHe82lXYmqWYIeo7WOSBinaWqGkJUMCrI+NkoIkTiCDrz55KIsrAWm853al4sRIIM9HGHxfH/+o9+gJdefOmarnmNcfwNt+S3/af/zNt9Gm/p+NL5CW1fYozwoZtn7xr3s7d7tKHgS2e/fplUrhceBsfR35wxvx/Z3dTvXddrz5blc5oBz6AGgCi0t2acf7Rg/R077EsNzQPD+qMDsy+VPP0TVzPvoXasn/7a5cRNQBNgv0b8MPuDL9P6gstN81XzQpk3Hf/ih/8O9i20Ift3f+x3s/z8V1DnJHDrZzuVhb3Nw/g4/jc2BUStcR73XBq72w2PPjbtpeULumfD65TdFFv4/H/5/WzOnn/NlXwsmBpEWZMhaCFwUxcjO9B7bSppjTaOi1EoMQwhjICmKGxiB1SaFkWonNaI9F7vhhhhs+kRA2VVag1IFGIf2abXaJwiY4G/xiMmFfTr40WRmAFLalSnFEWUSVIVZIpiNNg3fPjjH+c97/8gf/snf5rwM78ysoCS5FWX55dstoHWD3gfaLtAPwR6H1m3A+tOWZkQIyFK+llw1tCUjs4LISTGyCQmZG+KjQhN6XjisKYuHXcvWtadFhErq2Jf4Xyk15ABjgZyjAFTWZbUTaPMlLFXwIuzbnzN+Hqrz7PpsRgj7W7LF+89QGY7bpVL6qbAuRrrSiKRXR8433rO1p5tK5ydbRjChhu3nhxBkrH63jdOb1IUBQcHhxSFAotbN0+4ebykrkqWixm2qrBlyc1DyxPWKhBORdJPF4WaP6SF0bogIQI+JLCLMERhc9EpqI6OYGbjdHkf2fYdOU+Q91EUmDVzmrqmqUvC0FG6iLMLZjMFIw/XQlMvmM+WGAP9EFhEPZci0WBBBGsMhdN/akgho0iwLAyl03N3zijjBfgoKjUSwUJ6vZ0YO8ks3N6OSQe1xlA3DV3bUhQFfd+ltQVnzSvCcb2HiqIcwRKicsfBK5Pkvcoqo0iqXVPJW4yRru8ZfMS6gqqpIbGtE3h7jY+OfM6iQFmSEYjaHTv2AcMEss0eC7+3v2W6hvGgef+Os7x3bxmwCZghBsz+a8cZGc9gAolWwRNay2bSNeZrsVhtyCxojVjeYKlLsx+GxG7p9YzcijG4BFUkfXZl0KhzlQ4jMoIdXf6GxqhExL4Dejdcj7duuL92wnt/ccuDT84Z/sA5RXENar4aYzXUbPopO73tS+Rvn4wF3W4nvPfnX9/R6fWGSfe28REpLCYIsbDop80WI8L8zmu/9kpwaQ3Ng5YnH4D8pMFIYlB+HKB71WvdznN6/urH3/BcfVSpkv3q5UxMKgF4ZaD8yiH/9iEzEU6iIO6NkZHtPVib5vEN3lsa/lvzj35lJ/wVjo9Jx2vN/zthSJq//F+Tvpc1kBds54mzktndltldtFg37Y3DL7zxsb/Qvf7n0mMBaqzVQKN0lrLQwDeiAXtyNtUeNaXD+zgaCxijTS+NsyqhMagNbTpeEMGL9n4xwK4dmM9KvAi9V/vlYCJFYSmKmvW2I6ZjI6k2wxis1bmOKXByzmC1MQQxqhOaETUOkGAS2LJEkzKoRMqqolkeErD4EJI7WtTgEsPqYsW6N3QxsNoNnF90hCi0PnC5HeiDEEUzxgdNya2jiro0VM4hIty7HLhzMbDpB4xzhMRyWaOBbl0W3D6suHFQs2o957tINJI8RwzOaTCjkrME5YTU1BO1rr04x/sBHzxRIlVV45ybnq+HSpltDahsBn5mCipzkHZ4eMz5o4e8ePchFEv6YNh0A7OqoPcKanaDGhsYY5kdnlLHyMHygLquODk5oa4byrKiKAqqssQWhe4Bp/Ip5wrEGtbBYFqgDZjMoaYzUSfbXp3inKGqK8pCa51CCISge9FZk1gtBQ5lYahLsxesptqQxBZqzYKCTxFDiAO7XapDkmQkkYqufFCwKj5n0RMwFmFIASxoryQfBTPsS2MVjA1B66qMMbhgqAq9n5w12ox2WqJUK5YYUCMMyRzDGGgHPXdDAi5bT9cHoB3XzxgZryMmtoCsKDP9lWA+r7cxJcZVOCcK1BLbY5M1sXNm7GjvoySwM31OhBiTxHHv2hPQMynhYazOadcP471pTTpemGp58l7fXzeZbn32n2H2fhXAuL1jZFYkASQx+TWZQUszIShDIom5sYBY/aBPQGNCP2nt94DJ+IYYJDHS++ek53JVEpDXJ5+byYAmHz5JE9NbvSZovB7vsiEaKO9uGWbF25/tfaeMNhTjZ3QfHS/+g6ex3RRoH3xJOH52YjsOIthh/et6TxPS50IQpE7f386MQOfXfNy3SL0jb0Fj3y8HZvIYr8l++fmRJMH9cs8zPsKbvCYzBAWclfuqgrp30tC1StduDXG2x0BFwfYBKewEgjqN0/LefrPjsQA1IkLhLNZAVRaQNPdqa1pqXUv6Qi6cBuCFm2yTLRqMWQFSwJkLnJ3RQCkE/XnXqmtTSKyLLQwH84btdkjOZ3qsIk2sBon6sxstUDMrY0bwYwszZlxJazeBInWh8kPPSy+9zK73XG4GhiFSFQ4fAm0r+FBgXYOXiNhCZT42UtYlNkJTFdw4qDhdVsyqzIYAYjk8FE6Oes42PX00tP1AU1jqXA+QAvLLQbjoIhQzxr2yx07IXl54Cv4EZx113dB1LQwDm82axWKZJGUyFpxNQVh6bQ6orMHKBAA04LQcHB6pxXNUAGP7Am8LirLi+PiAk9QMtKlrmqamcBZXFFhbpP+6xNZokGasUY2rzQDK7AXAJhNr6VxTxOcMVaNZfWsd29YTfNaC7oe+05iCVnMlwNY1MRnHjcfIMqQI42uMAVc4irLEhkjXtVg7BZgqO9PzjSlY1tIyBaMaw8qY/JD9081748qNxpXzyizaVQmqGc0xLOANYBScKXjQfigZ2LnUZFaiEBKYy2zSxOxpQsDk/bBXc2Os3u9BhGEQbAZLCCJW5VRptrMDn0+GHBPgidOaWjWa8CHbkU/APZ2OHjszkei+Ibn1jTVnCTmZ8R5It7akVR/XnDGYGeVn6e2MpHsh/W5xV1gTyehCTHpvRgYoL+SVYzKdl0v7WBBMBkp7QFjIgCu/2f42yPvUjh9Xeb9dj+sBvPLj7nrsjZfWhzx4dk8qJoYnf0J7gYBmpD9wudUGuV/lYYagn0vJvRVnvzZR3F5m/e0cZghg7ZsGM1/1909Acj/4fjNDnNX6xjcJaEwQTO+Rqvjy1xoFM8SvOPh/rIY1KlHbG1K+en5t60fQ+XrjMQE1GjBYqyBj6LWmJWeF7Z4cSBtbgrEW7zVwtYUh9KlIPzk2QfrSJj+u75XrZCxGQYxEFoua89VOAzKngfAkkwpjdjPzEcbY5BUmOKfyJ2PNGDvk5k829Z2xxiIhsl6t+YVf+hy9V/ah6zzOGlbbjrouefKpU8qdoSgr5nVH12vB/xCFunAczkuaqqAs8rml7Gw0WCfcMNqAcztELncGHyJ9NGz7oK5nMknrJDFdLt1kmYXKGd4pFppy18vlAavVOTEEttstbauNAzOoyAGjxlVTBtsYQ11XkOp3qqpieXBA4Rwf+chHmc9nzGZaB1FWJWWhHeKLokw1R9rMtEz/damORoNoBQoqs5mCTZORJfvxnGo6c/xXlQVFZamqAu8Du22f5nT/GICZJDzTkaaR90UOJBXAjCn4N978nc/IdHyq7j/ZY7XS44q/kAQuDLmmaA+AikwBag7OMxexl/DfD8rNeIzJLCCbQeT/Gav7wwfB80ogNE3KGPxfmZ90f++BPZP2hZUUCKAgymJwTuuBnDNItOmzwVCVJcbAZtslpkHPw0eZriedc7RuZKR80Lu1dIZoBYlmmiMEiGBBZWHTWU8AaCJSMhDR+zoBwPT+gt6TGJNYpQmQZBiV1yIDX0mAZvzQGJHp1XOUBHTyvtY5nI7K3iEyws33X76v2Xv/V9wV6QyvuZp3+zj7np7D5ytm33H2dp/K2zY+e/8JdqupB8nJ36+YPZhY0FkrfPT+Gzds/GoOEwRiHCVmYg3ytQYXr8ysv13D2r3Pua/9yHHga40ccL8mCPkK2RlxX8EaW/PmGKM3CUxzLcxbwax9ReM15uyVwOe1xmMBarRBpDobDYNPGWA7BiWaeJ/ct/pBMGi2diw+SlFO2ItKTT62syPzkNVQQAI3SaoSRIuvyRnlxM64XJAN1lkK5zRT4qbC4Cyfi1eCxswSaPDy4MEZv/yFF3n+7plme5Oz2flae+YczGtunB7QP9jRxxIHDF1ImVt9D2cM1uX6IQV+rQ94L3RDZL3zbAbPqg10Q8THKYs/ZmMT+jBAYQ11YeiDynwiOSgfp2f8SUSYz+fUTequ3vds1isAikKBTQaCB8sDmtmMwjnKqmLWzDg5OaEsC5wrKMtylK45Z7HO6XqbVHdjcyCrx8wNRK0xiCEZIiTjA5fLDyagdmUkadP4qzXMZg1F5Yji2ax7dlvtoTOGfZnBGLPlr9yxeyxNft5e5nyauKvBY954+wBQQPew2X+ZEHLwv78KezhpBAUmO+7JHnuS/pZ+tyatbcoc5qaL+aDW7tVzWJNYU8P+VMoIVCfwlqV1IUm7QoxJNiajaUeWuEkC4K+UfpHZhlfMFEyAzJDBcZ8en7iX/Dqb5Y7Tilw5bwVVCTDa6Rl5fxXp/korPuLMiTUizY8CLzJIy9DDZJORBEhyggAzgkbItXnaS0dwoyFICKT5jOM+Eq7Oe5RJfpf/tr85XzWHObkyAtw8KftAOANqc2WvXY9355gddNz5jYd89Oji7T6Vt2REDL96dmN0T+rakpO/1bDf+/H2i57qSr3I2yPDM0HAazNLcUaZmXepdCmPt4uhGYd9/U/JNxNwv1XjTc3LVxmYmi5gYvzyIOlN1j19tcZjAWpA9fQxqLzGJEmLgVFjn2GKALawRJ8jvCTJSWglB3OCBnGuUOcg58z4Ja51BPr83hsGbynKGQdFwxC0s3kOp3JQYo3BupxrNZo5GcPaFJilNHUOxlximALCgwcP+Mlf/CJt5ymdYdcPDD5wsKg4OWhYzCosgeWi4Xzb46xRpGwSAxTV9cxHYdcHrXsIgXbQn7UhorDpA33IxdI6l03haEpLXaQapDRnzkIQeLgJdFGD+tGOOUdBZgrCrbO8973vT+yJYzabsVguuXHjJvPZjLLS2pb5fEFVaq8OrUFxWDeBnvwvgxddN0aGaF/Sld/fWlJtkKN0ClSLBHpyNjqDmpGtMdN+cM5SVpayLOk6z67t2ew8hUymEILZD4fHE9DYdUKGE2SeHs7yqmm3Tq5kUwAf01xeBU3sA5q9N4ljwJ8AirNJdhXGjP5rgYEp1E7nkuc4PWr354cJpIxXZaZg3xiDRUZwZAwUziUZqM7ra33P7teuqCmAsjxDiFoXlx6LwtjgNsvexrkzk5RRmSOVXozAcZyqPRYiF7+/CmCOZ3b1x5x5e40i/wxoxjnde88xUZARhsk7N80fWaI3yVYzW5XrnwzKUjWlxVR66gZHUnQSEqsaokr+QkyNg732mcrX6ZPL4X4foLx/QJRVlsSGWe0lEILaYeul5+u/FqC928etwzUPvyNg36EA98FuQRDDg1+4xezuq3ezCfDUz+zGbDTEqSj+cRgpmw4g1kJhiW93IP+VjCy5e5eDr3fyeLMMjdQO4U1I3nLG3L3xc98sSJoKSl97PB6gxoArCv3yT6xNCDH1fklOTdaM8iLrLJgIThIb4Oh6bZqJ7MtcpoxqlocBOHIdAPQ9tLuIc45+CBijtq5XM7U5hjRj1LfPgIzB4Zj01L/bnE0Hgh/wQ48g9F64v+rwITKri2QFLTx6eM786CahV/YmO7oNQdj1nrYPbPvA4IOCvyRD0hqhZGJghbnVInFroCosJ4uKw0aL30EDpcFHHly23LtsWe2G0aULY2maRvuUOMfy4ICT4xPKsqQoCmbzOXVVYVKtS1mWlGWJtW4yDUhgzibHs1c6To2OaOzHkWbv/3P0qPPok9Nb7xXQWWtoSsu8LpnVBVWp9t2ZvTHp/6yFZlZgnW5z33uGIVBZKJuSg7oYC/oHL6NLWB8i3RAmpmu/FmcPIEyWBzLuhbHOI9dOTIlw8qVl5mB/jD5ZGVDmx5L00RYlhweHlGXJbrulbbfabDRl62WEP3tJxwzeJTt06VEnedyU8Z+kUhloGcb6qOmyQVQmNoJ3yUyrMn8jq5aZtMT8OGuoSkNTFeN9ASm4Ttc++Mi29cmMQ4vYuyGogQIGiRN4zesRx6ke4dnVHbU3z/k6pxVknJN96eT4mnR9mQUcn8s+g7P3WpPfI7//9PpxM+yv+4jF9s75yvnKtDZ7EsXxvCecrWu8x7LG6eISwMngMOZUkK5D6lE11YNxPd7F47jecVx/7aRVX8mIGDp/NWT5/KfeQ3mZNq0Ynvx7A7ON52B4a2pa3qphujAWpou179j6iNz/BlIc9A69juvx1RtfrgZmfN6bAUnJUOA15DPjeDxADRbramwJzjmqytK1EVLzwKypHwOR9GVs0zd7DCojM8aOAUSWM40Z/DgFciYFXGL1y3/T9hTOaWY0RpVryFTMnT8bYwr8hDj2XMGAJ47Buvbf0CDBGkfpUhwTDe9/4oRf+sLLdIPn/kXLy482PHljgRQKNLq24/YzFYWF1bbDR+h7lakFifQ+4mNkXjpmdUFTFkQRdp2nHTxDCBSuoCkshTP4GDBE6sJjojD0MIilDYZ1F7jo4Ojmk9yqG5qqpKprmmbGLBkAWOcoXDkyLmaUiGUGROVj+w5oGkjKCGJAw+hslZyH2fu/K3HUlV/2A1iNGANAUPe6TRcp3MCiKZhXBXVpaSoFufWsSv1yArtNR8hOMa8YLkkKZ/UYwxKTtC9ElfX1g9Y2+fS+Q+qdMmXmzd6xZe9tZNxH2ov0Kg80QaIpUp2gxjQfBmHoOx4+OqMqK5pmxvHJDdq2pes6+q6bmtNO8CjN23SsHPRqYj69k1wFLAnJkzP8e1hMe6emNcgshWAwMa15AhVXljodzqTZsnaPBcqAyeztG7TfU1MpK1U4wxAiZaH3xWbXKZh26iLY9mGsrTHG6L2yJ7Oz6bryNAw+3c8p6VG45JqW9liQqYosQ8vBw8i6yV4SI/fr2QMPeTuAjEYBI/AwMc33NDmjvCzP6bRaZFOSqeCfvWFGgDy+9T4wu7KmezsrRPKnmAFiDkDSa+Nr3CPX43q8HWM11HzhM0+N+7m8sDz1E1eb+X1o1WJ9fI1XP/4jy8ts75HCfl3Iy6R0SMnIONmVJ1YFFG9fcf/1+Doa2VDgDbJvjwmoYdTwC+pqpC5Qk2xj/DkFAs5axMgov7BMzR8RRve0MUbLEYMhOTlN2WmJBm8mOVkUQXtYJsFOTgSloFD7fezXHCRwJXtBaXofPa4GtTePFxzOa+6de9ad50v3V3z0mWNOqhlGIA6Riwdn3Did8dL9Fd7HVEcTiRKwEokmUBqhQPB9r4AvBlwcaMqC44N5mhsQV/DEzZtY4+hjQSsV0dUM4riRyrKruqIoHHXpErAzY9Bnx/oWlcG9kmXZBzhZ+qIvnZiGSaB3dS1iDu728MA+K7YfW2VAkKVq43OSDfHgA9vKs1xUhNoi3UD7aIcfIgahdJML3MQkqM2YEbRFT15okWTX7KiAWTUFllGg7Tyr3cBuUOnfGGzuRaWSgskJ66TcuFzNrE/MyD4CYPwSn3ZXqqnwkda3atBQFMyaOYdHR3S7lsvLi72ANAXJksAgrw6aJ9biFXKutE688lX7cbvwir0uoxNbHvughrQnchPI/b/vr/N0fnJFRigiOKvMgnWWg/kcL8Jmt1HGksyQxbGpbOV03Xyc6sdAExpFWovSGZpK+1lVpR2b5wrasNcaxn5Arxwi6f4O2vi29zE5rUlKjujejkHd2kgA8CpkukK1TPMp+R7Yl9LtTb4o5LyyZnne0qbeZ6Vkfz1H8LK/XulA4xtdj+vx1o/nL494dHYw/j7/TM3RFyaAYr3wkTvtW2Yx/LaM5FRlu0EZmaYgzquvv4A/1W9ktzCzG9Rspinf8cDtyw0zBMwQEOeQ2o1GD2+na9u7aTwWoMaQQApCDNCHMDEtMbmgjZshNZTLjkeSe6HkbK1+L2cnNQlTsKzf9xrsBBGMNZNVbQrUosQEbNBOsZILsRW0hPTeGD0vUg2QpOacmP2ALeJ9DkoF6wwfePKE+xcbQgjcedRy/2LHydFMgwwRLs9XxKpmGHZY0fs/hIglUllDUVqchao0lNWMw6MjrCtwZcXR0THLg0PtUxMNfbR00bHtI7GPuKh1PgeVo3SOzke82LF2QozBOSgyeJG9uUsgLrtj5XWTvCY522xSrj4F88ZOgWJeo6zdlxHR5KBKDzAGtvmdTfocNPlI+nxnLU1TMF/WlIXD+4H7D9a0rYIdfa1m64vEDhSpDiRL5IzRgLcoDKVzr6p/yKxeLrqfNSWzpiCEyLYbWO0Gtl0gE0G6NxMrI7ln0b6bXArwx1mZgM2+ee8Ypo4sQ5IIJaTkB89quGS9WaeMfdxbjTSPaW73+Z+RjMnHzz/JK95zfDD/Pde5jIvMfmf6MUi/QhNMPVYkgdIMsUY74zwvr4pbpmsFCGGy2N7tunQtuQFrAo0hYp0jSmA7pARE1D48GXDvA4i2F1bt9B17xVAisxlGP5tyvzZr9wwYrH5uNKVRi3VhrBEi7S8RrSUyRu2ufdhjZ2Sqhwnp8yN/VuQ5GlmkvIqjTfQENjPoHdcmX+He3/I+nJISE7AxTADoelyPr9b40vkJ3aAhhoih/rEDiu20z+YPIzfv7Evdvn774hgfMW36DCusApm3213qazBybxJZVl/2uV8vQ9mqPRnVKz5bTRBMp43m4qwcza4ATYh+nYO+1xumC5iQetMkQHjl7+HNfUc9FqBmzF6mqMsYdTErUmF0jpNijMSQvpz3Fl5SULcXJ2kdS8hf2Cn7Y8wIWsaX7/WeGZsJRiGry8iHTJ8/MjqK6V+jCCZmBimda35uuh5BRuvX990+5jPP3WfbDWwH4c55x+0bnqNlgRhDGAJNZagszBdLmqYBq/bGpzduMJsvKKqKoigp6xllVYOxhGhoh8imC3Re2HaRPuTzd5jCUFkN3OvSEoHSCS7mSNuMUa1NwERyJhmTAkP9mfEG1AnP0rIsFctyIBFtFMgYSDEFyQZUJT3p+XPJQY7N8nFysGgxGAtl6VgsG5q6VqZmGDg/3+ETc3JV3qM1KcEYrTUxVlk4MXQJQPskyckgJxd379eHOAPOWIzV7L2zWvNROYuUGiAOQQgR7aPyiqaRo8RKQPVapHNNfVhMBkJpAsSO5542cXpNBnUpio1hlDtlKdl+QDvdJHnSZXwu+d5Izl1ZWpWHSaBT742MPMwecN8LoF/xXhqYT5MwMmF7T5Ko15fLRcYNmK93BInCPkO4LzaJMSRZnM6jxJgaYO5lF0xiGyWqbNU6QvD6ORO0dgr261auAg+1+hgXb2IU01pc/QqaWKapUamhclp3lD+TCpdMO8yeA5vTWkKtI1L5ow/JRY7puy47zvkwNXeN4/mGCfKk/9u/l2Sc17xn9voJjTN8Pa4H3N8tiG/SP/fBowNmPz2/8tjNT/cUqwmoGPn1NZt8x42s/49RM/d1+a5uvvhuHa8Er+IMMp9AnhEgSShNoUUVtvX6mZz71OzXh32d7p8vW1OzLzN9A3zzWIAa0GLwHDREJj35fvYxD43hcs57qrO5GhNp8fwocUqPaXCQsvH5+Kl6IMaYXIEEjMWlnjchgkuMhgpMIAZlfZTdmWRpGDAxhXlBNHtsoR0827an94Hv/OQnmM9nPHk0431PHnN6OKMuHepd7aiaOd9x4yPMl4cUZYVJvWA0oLIYqwsfBHaDsGkDlztPO+TgXGuTFlV+ngbb2jHd0HnRpqQwgpnMrghT0DjinD3plyDJPheEOLIQWV6zF39PQfp+4JcbL46AaT9cFKbbf3KR02w5NE3F8qCmKAr84Lk439B2gRAC0y6fWJCkPiRIanqZAEc3xDHwFJm6s0diWkej85UD/739tr8Xc7Bo89yIXp8Zmaj9A4w5cc2+5wMkgJynYrIr3pPbZRYsHzETGFk+loNvk/ow5ccmnJqxSA7Lp3NLga8kkJTZpgw29W32MklIkoPovTBG0MZOc8ResJ/ONea/7f83z7uYEZBdvbb9vcDYHHNa6nyM/L77DmrpnC0QIRJG4GPMoMexDiRbWivrE6LHFSXB+wSE9B6e9tYEHvO2kD1zh7zueYbyI7v8qOz1qxnBqFAkcw9Q0OJjVAYxW86l41qrbmlloaYLpVM2Z/AKhlY7z7YLiKjssiqyyUq23Q7JeCOBo5HdTp+kZn/er8e7dWx8hftPbjJ/9ObYk2UEO7zLQMvrDDMEZWZ6rxnnJDG7HtfjtYY48ypnsFfaQ+fieLEWKa3+nl77Zgvx3+njCnPzBrjusQE1mSmJovZvOdtunU31FBmxaOdyRNREACaiQaafs3OYZuX1pd4HlRMlStSmsENVYxpsaDY128xq0CZRCCZoJjXu9ccxGiRvu24s5q+dozCGsiyp60a7JVrLjaNj3rdcUpYVN27dpq4b7STvHMa4FAYmC2djaeZ6Rj1a8yOR1GfEECSy7SK7xMqEKEiSu5SFZdk4lrOSulCXAu8jnY+0vc5JVRiq0rLrI5tuUACc5SkwBrgQtdHjtEr6/6/I0ucscBSZ7GHzq0TXMjNkujb5depiNyYexoBaj2+soWkKDg5qTm8UbDaW1arl/NGWvvd77JpMQXs+hkWZJBlPYgRYV2PmCQTkgHk/GM3EiD49s065zitJzcZJmQAaeU+m3yXmed2T1UkOdHM/Jjs208wzXCZ7c32OJiviKPuapEgK2K+ulKSeJwo800HMxLqYvfkR0o2QJybp/fYz+yNcNEbtlROo1cndy6KMYDafCCNLMAHlvE+YziG/fZoXk9m/fLV7AfdYDze+KO/cfJ3JNCROECMfRyWtQNTGp3rqZkxoeBn0EOkzp6wrvM8OA/lfWqF9YDm+S5YbJnA14rA9uZ6itHFeYnL3m65W6HN6YdzDMS2NMjzakFbve/1s0mNE9POvLmE5L5hXKqvMpzsMgdVu4HI7IChwMkbt80v39S+JuR5XhxfLL/7yezHD9Plx8Kzj9r3NO8pB7G0diZXJsiKpCsJB83WbVb8eX9vxSpATq1dIs5IdMvB1YTjx6xmPB6iRKQCQpLXIrLcRDZyyzALRgHV8jWEKbkiuXJAEIzmQ2gv2YkSMWsxqzw/Nzmf2IcZIl6x/sw5eJKqOnik4K8pSgwcBXMXR0ZECFecwtqReHDCfLZK8zWKLUrPZxnHWW6TPwVcYgxW9MLtfSpCGZmunsGwKonLwlQP6EIVdF/FhwDmV2Lg929Ysp2r7qL1yxqaT2anJksv7p0L2PYvYBFJGJzkgjj9bJiCQs9e5BilnnCdp374Vcv4HUNeOxbLk+EQbdG7WkTsvtazXPd6r99bEB8SRSdDsu0lANLMP6fEMKuAKAJlqRqY5F7MXwMvENo2rkTvAZyDElcViYk8y06ivF0wCfUzrlwELaKO1kUHSP3rCSIS43PfEGGJiL2IG2WmR9mFVbvyqi5SlR9P7WnIiYC9IH+fEKlDSrplkW27Zk6OI2PF1eYqihDEhMdlJ7x1d9PiZxRvdvaKC3JGZfdWcT8Awv84kgGj2nzfe87rncp3KlSomk6R9GSlC+hJIMq4Q03H13ghJ55uuWtcxg1ozndvIHps85ROAnsBOrvXJk7+HmvezMolpy/tMp0PPMSSw0/u4N0WTjFbZqshlK6y7oM1Yx3nMn3t6rUWSNtgEMq9j2K+/8bCd88LLJ1ceO/3xmvoyf+AJH32pw4T4Gq++Hm80zBCwu8RmGUNsKqS07+qg8np8DcYr9teb7hnzLhiPB6hB6yWydEYzvRMYyUFMjKohd0zuVfvB435RdgY0IWh9Q5SYGIKIc1AFh4jQeY8f5Uva0Tv4mHgcQxBomoaj42MwjoDFFDXLg2NwJREFLEVZK+uCSeDF0iX+JwrEHnVecu4VjQ33A7/MGNgUvKVHrUAcwxKMmbrHZ0c27YoOVZFsllO/H5uCmCGoPfEQNSAPOdgbU+eZUdnLLKdgOAe5OfKPe6hTRMZiejJX8AoJi0m1KLl+hLw+2BTHRcqqoK4dy2XD0UmFc4H1Zc+jhz3bbV7DvWA9swSSs/k5YMxgJS9piihH+93I9HFgEvslo9Qo59uNlfG44//nqUrnnK+DPamkvmY/OMggKyoTk54rcTrbfS4MMSmOzYxAkgWJEKLN0bOuh8mF5MnIgknilO8qkTxPE0gbHQJT4J/PT6/PprkMI6AZV3ZEfTIyYpJ80af9m5MNJoGOPYODvByZLcpzGcc7dkxWXGFpEnhLiz8CgUzQ7O+2LDdVi+sEQTJulQzg7XQuae5jTqbkc8ir+DpB/rQ1TJqnvFMmeZqCnb3529uh4zqNrNS0Zcc3TvUwyiZNxx3h2fgaRVUZkIz3gxh8FHzgFYzWdBWDz1ejMM5fB7bvuPHS+pBNO8mbdquG0789/V5uhI9+YfuKV3mux69hpKJu0w2jq1WWmL0bCv+vx/V43MdjA2pgysLmnxHB+xT8K02iQXWcQE9ORIukglmvoV3wgWHw9EPAey289TFQlU6tf9E+F9HArGmYz+aa/TYFdbPg8OgmQ4SIJZoSU+hrrLXUZcGiqWjqksIZigQkCpusj7EMUWg7z6aXVMMBy8ZxOK+oy9wo0hJE6AbPELTwtxuEKNqbI5Lc2MSOCdzSGqrSqfQtCD6qfORg5jheVMyaUsPSFPuFIMmlayo+1iamObCbAh2VtWhWOiZJmzGZPZNkzrAPLKY3ihhs6sNix4BTxuL7MZBO7ykI1kRcAYtlw/HxnINDS7sLPLi3ZbtttVcRdgyglV3IGfWoTnb7RInJQaJNhM3efjL7TEUKukcQNu4+JkbMTOcscQR7Wn+RNGc2O0Kk16e5jHsypX33OIs66hkDrkhSMxG10UbxYwheex3tgakxto9hrK2aiDB9XhC1/QaT2wRhbVZMBQXaZGe3BOCiKJhJUM6aHCLHtH57QHrcK3ECGQYyuBwBdg7CRdeO8TDJHTDfxvmq0vvoDirGwHuCyYIWv0uK49P/jEX2ZHgj+MwAIL1R3gPZmjyzgxMTmt4v202nxMpoGkC+ngkojhBF5BVrPyGgVxVY542WgZSZQJRB9B6fcOy4/pPttpnWQ8Lenk8s7AhwpjXKcs98/6Ysxd5Z7gGlV8gXr8fjMx7sFlew9Z1nn2DxhSkre/J5z/Hdbu8ZHiNfv05ib8vYs2LGBygcsS6vm0tej+vxmI3HAtQI4GOYgsEkhRh81r/r13U/eAYf1YnK5eykpIaXIbEGGr9Fr0Gbs5bDxQxXlIix1FXJ6Y1TlgeHRDFECop6Dq4giiWKwxaF/i1VmBfOspxVLGclB7OSOlkiawFuLuxFM8SpQWM7RDYDdEEoCsuiVtCxnGlxr4KZSOiVfYpR8F5S00e1HHbGaigsWvRel45lU+KsYdcHuqiZ8KqARe2Y1w5r0aLhXguGd73W3uzXYpik31OZ3h4Tsa/5z5TEGCrJ+Lz9gM/mgGoECVMAFWMAU+i7mORYJ5GidCwWFSenlvnCMQwV243ni8+2tN1ADBr8hagslU1yobGQeYoJ02Mj1aQ8TIx6dWPAOV7gFAAaSfbe7F3fxAKYMYjUwN8kxzN9TqphCQkQJGOA6SUaIEqKNG0CRz4Bb2MEF7V+wRlLU5qxXqsbLEEUsMaYWZtxVfaCazJC1GsWMLi0dpltS8BD7Mh0KBgIjIG5geyAJQLG2ZHRGJVRmeHIQGdkffbZl7x/8iSk+zMl/rMVssQ4MhWjdM+QzBWEbE09XlOWvcXEWiRGShnExFImtkTNEbI0c79GzIwNOUnyVPLeye5f49pnMKVNdDMrNaEgdYubwLRNICrdDyb1P2IyEMkAa7rP9Pext9MrlnQ0bpAJgIyYKNnh5fWYmm/uh73TusA0TyCpzkzSfGWAOYH3K4e5Hm/5iBj6MAXGIoZnf+49uF36XA6Gp36ix3UTg/aR4Voq9rUa2X7XdMpsSV0g12DmelyPx3Y8HqAmRjbbVkMZq1/QIUa6dqDtfGrEmYICUVcfZ7MjElRVRVU3ypYUJTdu3KAoS8qipKobFssDsCU+Gnw0BLFEU1A4N7Is1lpiFDqvTEnpDIelZdGU2qW+cGPdjQ/Crh/Gpns+MNqqajF3CmqTbt4ZLehFhF0XOB88uz53rdfi7yxBKUvLzFokqma+DzHV5WhA3vbqXjSIsinOaNA/+MDDy5Y+QtdH+iH1TsHgrxQgp4DeBJXBpahLSIIqkwNkkDHTn6MfM/59P4u9F/0m4sCmYCu7NKic6/BQODktuHWrpG4sXRd48MBz9+6OdjNl8nOUrESIjO5m2bRgUi5lS+iItZrpTmZXY6+QfamSNSSHq1RxZSZAZ7PcyWigKFG0T1EOS2McZXe5LmIKJfdrHlIvH+OQoAzDaO+cAZOBaJLDGhHTi8opUT5H2Qa1qzNY5CodpZn6HAyPcsVsH5zrbNLRjNmTboGIT8/XJ2f8MYo2Y0RiuMIU5IAaa6esv3F7ABcgIjGDwDC5kJlcr6YgUwyjFC/LLDOCCsEzzm56U13COMmzJEvaDJlREZK1s1E5Y0bl6s63N/djrYqZbMvTnh2vK90LWfq1DwIyYMlgV+cr5JcBqb4pz+se1Eh3gV5dejCvywTCbLrsJPszMjnNvRL45KNnQCm5TilO77V3n2ZwmBsZ5ls21yDpc2Tv6NfjrRgPdgte+vwT4+/1Pcftn77Kqnzoor0GLW/zMF3Atj2p8GwCM9fNE6/H9Xisx2MBakIMbDeXgCb2x3qSAMvK4YqCLL+YNTNu3jxNoKVgNp9zdHSUCvEdgkWsI4qhDzB4YWetghdrWaS6FlcU+Aidj/RekKBFs4cLy6wutUdOhCFE1rtI71UiNoRA76PKS4wdM7a5SHeMPowGp6VVa+jeR7q+I6LHDGK0Z4UxGKugp0g1OW3vR8vVXPQcDOx6SXUlFqw6tWENrRfaYUh1MmaUZul5mLF+YZSy5MDQZCka5ADMSJZXJde1dE0GnSNJTnRjIz8BaxwxyXe0KH+qEygKy2JZceu2YXlQE6Njtep5/vmWh2eBfjDJQUwYrZ4x6rqTa6tIeEEcIfUQslZGyZPKl3QhIiEF6WaUVulvJvUKilfmxJipfslkTVeKKcN+ITc5oI/JUlvfT89BQQYGYgha32QEXJ5vBRb5bMb3NcqgWNShLgeh1sges5IK4kcsmWqCLMnkwiRmxhJF62AyVJMYSfAnyZASeLaaHBh1ajkqF923MdV0jLUwJu8LDZqdcePe0rmbMvxZEmbNfo8pUdCRrjsbYuyD2MyUZdlixjoxjPZyuq9NNtJIYJWMynTfhjy3MZJlWHnPI6J1b6KWxsaojbcuzH4NT7pWy8j25GvNwrhccD/iL2SUBCoo1rOz+c5KICqtRgJUMUkQE8s0JgcyYMlue5pysHtJAjHT2mcN2TifwJV+NeO55dfnz6h9UMS03tfj1zy+8OiU1eVs/P3gZxsWL00AxfXCR680nLwej8WIgomCab02AAxRJWbLCnHXhf/X43q8U8ZjAWqsMVRVCdZxeHiAcw5rHXVZcXJywnw5xzmHK0rKqqFp5mAMQ9CO3D5Cm9gSAIelsIb5zFIXDucKrLX4KOw6z2Xn8a1HxFAXlmVTUBZaD9P7yMN1oB0G+qBGAzomiY4G1goG7F6FrwY7bowLUskE3SC0XnvgRMkuRVP22cRIH4V+mCKMMXsKKRhR8KdMVkw2tNqsz+z1ixlrScbcfQ4X9fosyR0pBeoabCaWQAzYvfeVqWbZpmL/HMWFJCMyYiicSQ0CbWJDDAeLObNFwWJRUVYl1va8+MKOy4tA3w2j5C434DRj0MfI0ORMfA7EREKSosUx8I5J+mVNRBJssMaOlQNmJJdkdGHL2W+VbnlSFdCev8Hkp2VQ0CkxAw2bXi9q4JDAg0WNJ2JiEPqoVtWFsxSFshKj61ScZGiZAdp/xyhm7KEyZvHRfiMxMwoxBfnWQYjjKmdWJQNTPX5i+pJNcyRJ6vYA7XS1AW2NMjmd6b5PTJnROrDR1CNJ3LI0jMQCTRzY3n+zPCyqhAvY6wGTAEJud/MKWdVkoKFPMinQVxZvMouYHNcm2aLsMVUxBIxxI/gYg3nJ+82SHfVU4jYdQ5m9kGSIaV5iqlIZ2Y6r9UC6XHtNZiVfY2BcrHFPh1TXRJK2GiYpWpaP5mSFHecMGPfndL/ofZqdtjXRESbgIvnmYGQGJc/F9Xjd8YVHp2rYAQyDY/63lrhhmrPjlwNP3m/3XnHdu+VxHiaI9pXpBgUyzmrDw8K+a/p/XI/r8fU0HgtQs1gu+Y2/+Xsoyor5rMHmTLgxSJLp+Kisy9oLF5cqjxFjtVdDYVnMLGWhtS5FoVKkfghsO89uM9B5leQUFprSMatKrIHOC+fbgW4IDGIT28EYHNj0816chXUuRQspyM2ZzjHIU7bCj4Ffyo6OAZfKXwwpo5xqDTIDICngs9aNMhKJqS4ldUbXACmmYMSM5xVkH4Rla1pLduvKrlIiGtzHFFznzLG+X0hSmxRgGYuM/r/6HK2PIGXIQUzUdVjMmM0aZvMa5wx913FxvmK93tH3PdYWSJyK2pFs5WvHjH+MMl63tTZDmhT/GS2qzgB2lASlzLWINk7Mc5lqIiQBSefcBGBS7UvOxEfJ2fH0nkG0MD/Zek9GCTkY1mNoeKkBp016riy/CuKxUUG2sySWyWBTjZOYHLiLwgHJgbWMf5MYEBMgOs3Yp31kQNdwZJMM1rpUt6IsQMxBKwmUpTUXA0SbjAvyBo4EEb3/UjCuTn25TiThqSvAWKGQsha5hieZOOS9AxNgTA6GmLAHuaMCBWPHoHq06jZqqDHRDjHJ+lI8v9eHRkHiJFOMGcQmEMPeOes8hMkOO92zCjYmcDSiggRWJF/7Huuph9t3foOcWkgThIhq8q1xI+OVncFHu3QzigAnRjHt0CyVG9kbye+d2cKYHAZlrFva04+SWTmT4bPJ0j4YWaoJI12P1xjdec3N/3CO203OYUauQcs7buyzMr32lVGJWan9P65ZmetxPd6x47EANUVRcvLEk0QM3kf6VE/S+YCPWncClqpwNJWjKAxV4ajKQgO3CD5ofcum9fRe6Hxk8AEjMKsdy1rrYlRyJqxXrTIxQmJjDNZOgMakwDUHuAogJHU1z4AjBTFRI74YvQaAYSoCzllwDdrTBaeMNTmgNGCcIxfqO+u0bwcyMjpiZWJxUhAcYg6kYcqNT7SRhoM5oDXjORn2LK5FUtI3alCKTUFz1AA5BVJGDBLUfUuydAlwheP0BpzesCyXh7RtzXYrdP2Gy/OW3dYrq2NIEVzAjueFggbJdt05g6+9dcizZ0hsiMGINlBVPKHBsUb3JqlwrhZZjwwWYGzBXnSc6jqmwDTLeSRJ6YIILqKgM++HlGFXiVN+P9Ia67pofUeed722YHKfmVwfZTGicDMgiFJwUxI9QWSsISbpW5CgQNW60TktEsBaMgejJ5LduWKSriWgFpWpIMkPM6M4NsU0WpEkee0TWBnZlFHalgBYAr6jBC25qRmrrFTu9zPWhaR9m5nKmFzkDBYfg7rnZde0sSA+mURk0DvGGwms5sQCuXYo6v2TnmNMTlAw7gsSMDEWHAp6Yoip/8seK2PSeo23lyRZ5+RqN7Eber9OhgTprex0XxpRt8VsQDAFTzHthQnm6XTvmyqwxyi5vUdz6oURCOn8RXK3LmuzBDLNPbmXUG5gEzGS3A2v47nXHeU6UmyvXcXeqcMMAeMjpk1rKAJlQWyKa1bmelyPr5PxWICaPsALDwe8DxhjtYDfQVmULOclTem0SVwKsnofaIfI5a6l98KQQFBMev+mLJhXltkygR4xtENg1Xr6JFPzSQqmzlVJqsHUhDMXxceoAUDu9h5jSPUJuYA/PT9mpXx2XzKjlERlIRqIKK6we8/T7LIdO7hnGRXEMGCNxbpUVJ0yqlpuYkfWRFJQH4KknjFmzGCHbPNrUhZ/DN0i1jhlTtAASDPKCgEUrO31OBntf8E4S1lW1HXJweEBh4cFTdPj7JbLiy137wS894SgBfwxATObiufDGLZZjEtAYsyq21HKNNUZaIwmVtdOs9FproMCOElZfGsczlUpgM1Bck66xyShyi/I5FkOFtE1SgyZcwLiQQxOi720uWQKyiWadDyACDEbFkyZ/CxHUuZgYowQT7YY1rnR980AIUYhJkbCpb1nJDNqkpqLmhxrJ2YDJAZAgUVGSAmi6eUlxiLL8jLYUE+LtM4pUB/ZnXR/mHEik7wr24hJIBeUWKNzF/O7hjDORQbldgQouteypC5auQLs8sJNbmxyRS5njcFZpwYdQfevTfU0+flaZxfGg2q/q3ysnHQYyBLMfJp6X6ocZaxjy6AjAX1lXZQ1NtaOTNiUYEi1bTnBYYQYPJjEIsYEONM8S7r4cf8IWJfOO90vMQaVPUrac5Du6L3XZXZOzLgvRkOHzMhYM97PMd8b09Rej+vxdTFMEPDJijmk+zNLzKriuvD/elyPr7PxWIAaQEHIQUVVlimo1ODAh8iuj7RDoO2DMjBBppoOo6xNUxqWTcO8qXBWgzsfoB0CvTd03qcaHMZu2hpERkjMiCRGYXQKIjEJ+b8SksQjBSlZn54jAZOLgDXACajzmUiWNqXgSJTxsUaz3cYWKXgTcv8YyI5YBsSlrHRypVI9lQZoyF4BMaNahpwFzxazRgPfmIMXUsCDSrzy8Wx6nrO5b4YGf1EizbxmuZyxPChxRTMyRI8ebVk9t8MPQyp4V5DmCt1eJupjMRcvj8Ftzjc7ctFyBi052z7WHtlUTyFBAV1ifnLAZiFl121iKrJcx4yyMREZzQ5y8Di1mjE53kdSjUrhHMY6YgyEJB/SuVDg5VwKMo0G8WPNBxYje13orU0uWjEV9+u8xRQA2xRNukIbywqaY88F72GvJsNZZfSMmVi5mCR2OrlJOieMjVc1itU9YDHEBKozOLnSFDQF21hDCIO+b0znkr//jUm9ogJGUj1VYh+MSWylyXUuMrEcxo4GAhkEJLiX9n0Ci5L2vk2yyZj2PKmGymROI8sqRa2oo4wW79bm5EQcj2tMMd4bZs/IIJteOGOV+UoJA9mbY9mrZ8nmHlkap3tAkw8yrrGdnk92Z2O6f/MdG1LiwEwyN/17kqMK02dCZlPIoIXx+Pq55dIeyDRRhLQ+o3QyyfFisnS2mZ0zuX7relyPd/jI8rLeY4ZU9J8kZnFW6mfTNZi5Htfj63I8FqCmcoYbByVDENre03tPF2Dbe7ohaL8O0heuCM4KVeGY1wWzqqAqUrE66hzWDQHvYciytKC2q8YmcCAxyWVCChyyhCgHyQBTj42cSc2hr2aps/wk17eAc2V+9hgkhhiS1j8H4skDS9TRzADWWS14TsGcyvuT0xNGpfFJmjVK/dGMfM56G3IxcHKXyllrsoxtksFkoKI6e0GiWulmW2QNZBO7Y4Rm7jg5XXJwWDFraqIE1uvA+fmW7aZn1w7kPjKqgNkLKI1VViGGJGdLQMZAtCpNisnoIELKYjMW0gukY4pmvo3OaX4/vR6b3NfUjtg5l1iVBBJjDvosmJgC64jgMRSMRehZ+pQYKpEsrZrkhLknCiS3MUb/rZFBUoamGPdHTOAgjyiCK1yqhzGEtL/iIGMQnuunrLPjcUxyJvN+0Foiq+fjCquCpKjgIiSJVAweGfe27hmX2KC8F/Q+sITogWkvJ6wBZItqSdtWA3aXGS4jCQBnEwPdO3qMfM+S7l+v7KC+eervElLdVBJTmVy0rtcWo5oJ5EJ65xy5/w/GoKZqicGxJj0XnYN04W6U5+nchwQsjSXVdtl0PhCiT4ymAsUQ9GRDDMn2PeIScxqiHwFK8P04p2qt7NP86jurxNPsgZ1kDjFKvkzGMtNzRjfDMAJ8Ef28yK5qui/MVGqTinQkAaAsF43BpzkeKToUWOfcjCM7Al6P6/FOHFdYGZ+SSs4iVYk0Wvx/Pa7H9fj6Ho8FqOmD8KUHLZ2HLsTRmjgzF85oX5rCQuksVanyNIyhHTyrXcSL2uL6EAkhZUSNSeBD9upD9D2NUXYmaIdHEDNmWkXUaQxITQFz1lTG4DgmFiDLPqwx2mdjzOCqZj9GucIUEC1GCoIMGrBaNyVVsQxBHbP2C5GF5PoF5CJjyVl5rfhOkhoN+l0CLDbHdXuBorMlqZMLkB3aJB2LdN5CVcGt25a6XrBYHmGMIYTAetNyebni/FFP6BU05qAyijaONMZopiydQIzaqDJGGeV0GkyblPWfWCV12couUEavO9svp+snMVgSs2FARExMgFAfj9HvXVNQ0GJTkJjmxNkymRKkGpBIslPWdcylJC43jsyMSLJZntLaY4iZAkvdU9liWbKE0RSjOikzdyJeE+jOEtO+zWDaTc7JRFFGRxJA9TFgxBGNwfocG0ec4jacs6kPTq7zsECh4DEBL2WfElMiEGMyOAAKm6RkRpmIzPC5LK8jM25Z2kgK9DVIVplVMjFI4FzZLRjBk9G5T5s0rbNgi8moQOV5koJzdTuzNrn+magWzSY3es2fGQrcLY4Q1fwgm4WFxIz4EFMRfQrwvVepVzY2GO8bdJ1iRIzF2gxWFZRNrWtsXiiVCYr6+omoM17em9Y5fNA1n5jKlChx+pkUQ0gMIem9YgLoeq56v1iy1XdOUEhiiCQZeihL6dJzLTEOTIhVPxNUGpvqBq95muvxThtRsL1KMMzgM0JX2WhTXTfJvB7X4102HgtQMwThbJOtddFsrwFnDM5AYadGiL2HbhjG4EswSYqWAmCZQEZ2uoohTvUJzo0SjpikIq7QTKo1uS7Bj8GpMQ5ryzFzr8yDJ8uajLPpPC0+dCpbyfIorL4+dXE3xmAcKcidQIqGowpWrHUju2MwBBHwA84ViKSsds60pjoZdZ+KgD7HJB1+7miex1jEDIioNW0M2WUJILBYFNy4Oef4tGG5tLStww8dD85azh/1bDfKyljniD6kAu8pqDMmBfEGiBpUWWMwriCXsuR6ihygk1mNJOWaJFFuz90qc04WQ6GgIiW0VWpkCT4Htj5JGHV+o4iubSQF2BqQ2uxYxQTMjLEURaUASGTMYAdJa5aCZ5tBKrm5qcGaiLFJ7hQDIkEBS6qryLI7Yy1+yH1bNCiN2l9UATZBa0RyAXiWHxl9RJkHNwbxMbGFIQrWBJwVJDoKY3V/OAO5psY5glfmIUQ7Wg7jDEXq75RleQpkh8RqJWaHxG6k4EFiZi61Fk4NDEIC/hEnChitS6AnARXSvav70icwXYwOZCrTykxK6k3k3GTPDCN7qvJJEtsmyU0spnnTa5UQkxQ07RskAdvMDOr9on+aanJ0STLAUxAq0SRG0WLE6ron0K91MUImRCwTQIsGLOrW6P2gQMwq8yQhjOA9ojVC1uRqLIdz+nPwXj+3MlNpE4OTJXyJcYqg5hp7uE1xdDqx0d45s75pn8r0GXE9rsfjOoyP+i/XyqQhTXndJPN6XI938fiyoMYY0wA/BtTp+X9FRP4tY8wHgR8EbgD/APijItIbY2rgLwC/ATgD/qCIfPGN3iMHZogWOGthPClwNfRKvUw1JnpiybVMxhCJlDmOMWhQGlSzH1O21ViVcrgsOcpSr6iSpJCKzm2SbYQAPgjOCA6LSOrrIrmA3kLwiC0I+BRwpay9AEaDO4mThj/GHIAUY11CkCHVIeR5SFdlNQC0Y31JZgKEEAesLSFleXMjTA1o4phRx9gUNJLYqpZcx2CtxVpL3Thu3Cw5PS1ZLiuauWAkcu9uz0sv9azXPUOvUpzc4C+EVP9gBKFMjIxmu/dBjkhUuY+xWLFE78EYiiKvFajmJlKMmeqI9x5rCwUnJteqRH0PSMFbZkgyKLNjVl3BkSWGxD6YmKyKldXJRNHEBmmgF0XdxLR/j8Elu2tiMglAg0VJYFK72AeyC9dotZstfG0BbmLYjDWpz0lUqVQkzWHA2FIdwEKeYxIYSsAu9d9R4C8ULtdvhRTI28SS6DG9hdIKhY1YI7jCUJcOCoPkHk9Bjb99VFDh+45ogsrLUvG6dYUG2lqQpuyKyawRYFwK0lPtTwzJsCLXR5kr8qmYpGTWlVp75dSVLiYmZlRHJY88k2yq9Zg5EaCfFbrNZGRrsuzKYhHxBEHXJAqmVAtwSQX9EsEnEw8R3UshO4Flt8LkDJgNBqbaH5UahmSbTgIWNte6GMYKqzACHU1khL7X+ZO0yEawthid8oy1FDazxkl+m0COfmCZJBcEl3oNZdgvqeFozHVYI9jJhhYy3keZpSFJHdX97J0ZDH4tvqeux9s8omCGqC5mwyT9pHCItcjsGsxcj+vxbh9vhqnpgN8hImtjTAn8bWPMDwP/OvD/FJEfNMb8J8CfAP7j9N9HIvIRY8wfAv494A++0RuoHF5ZD21qqUGMBn1xDGQkaIbSpupu7d6umdYs25FUn5F7n5gktXKFTVlmIfR9qlXQoMyiTI1xqZ7CFiprSnIkoieakIIVzdJGQEKgSAFwVskbo71iokTNdifJmgZhBZGQGINBY3ljMUWBqFYouWBdLdIPQaVUmpU1BK/OW8bmxpVmBE44iwSPpIaSUOBMwdTEEawNLJeWo+OS09OGg6OC+dzjHHRdz907PeePAvfuDfSdJAmXU3CUAIY6ccUpiDSafbbRJMvlJNkRteS2+TGUfcuBsTFxDCBjWvOUpNdstFJnhFT8rWBXZUEhOV4ZJMmnQuoDkzgAEUSGtDa5gNyl4DLtJWNTK4/JQYoELK2zEMLUl8SQ5E6kPZfqfEhSssxnmNyI0ydmR8+xcFU+k4mpQllFddeLBB8mkGZkfK8YPCHta2cLvPhEviTWJDFHehVaJxZixCM4kwLloJKzuigoraF0AVPpeoUYwTj6ssCHZJyBQYzFBxTwVwUxejI76r1PgCK7DGZwlfofkfoMRUMMgnU5sE61JUlqmq211UggNdS02apceUz9XLBEGxLTmdYgGrz4dM8mGWNOjliHcQJiGLyCjuAHbeSbWk0F8Xp8k9zL8r5D5ZImM7KJbc0NY5GAy2BP3xYRtaYWicrgFk5rn7xXZ8JUy6fALn/yJYmb1c8IUsF+ZpattRgbEB/IjXv1828P6CaApcmNZBYglphrZAafAKG9whaOCkpJXPE7m6l5y7+nrsfbM4yP2N2gN1pmZXLhf10ipb3uLXM9rsf1AN4EqBFNi+YOY2X6J8DvAP5IevwHgH8b/bL4felngL8C/FljjBF5o2/LVCcSBYNaDIfYT0XFSbASYrJRTWyMtRbjkswodbOPYa9JokzF9ep4FsA4jFG3sRzMGKsghaDFvSY3rLOSLI9VJhVDQEykKMrEKmmgG6MHCem5WsDvbArgTAYFyc0pguBxBmzpVHJjCrCi4AUNZBT8RGWDDIj0GsQaNUWwRYUplL1QMy+DTxno3G8i99RAIjF4irKgbipu3a55z3trZnOYzVusvaDrIvfv1Tz/JcP5+UBI9S4GldUYC7aoiGFQeZdTKY01ao6gDEou3M9Sl8R2ZJc5wDkDMWpdwVg3k5kMEFyysU11KMCoGEJBoA8+OXLp3olBwYnWXmjNkAGVjNkEHFMx+mjH61QaSOqTY6IZaxfGkDFmB7OpEF2dr5IkLQxJnmhSPYpKxkzOisf02rRfvQwwSn4yxxgBl0C4wdiQXpOkZ4nVyyyhJObIWotzBcEPyj7aZPedepikIi1C5kt8IERDNwScG7AIdWmZVY66clqnZi3zpiGD/eCj9nGKKWiWyDAIYgxDLOm7iA+BgLIJ2pRWWYRcW2VtoaC2kBTDi0qiiopsrT34jlxPZa3BJpknaQ95CThX4saAPu0nYxGvMrPovUo0Ubc4CQaT7sUsw4whgWGStMs6nBi9zzGMfZqyucIo20rgy5gEtkqIXgF9ciSMIhS2HJ8nIgxDYIiDJlvSZ4orlIl26TNJa9+cMrhJnqYAX8EY6R6wdnI7YwRHkpz8LLYoRhbZjmYKLkkLE58rI+zG2BozyhyTRPMdHBh+bb6nrsfXapiQ3Mu06/b0B2eR0l1LzK7H9bgerzneVE2N0SYr/wD4CPDngGeBc8ltsuEF4Jn08zPA8wAi4o0xFyj1/+AVx/yTwJ8EODw8REyBiXFkAzAaHFlTEpOTkX4ZayG3xKD1JqkttzVWtfPk52loazBYV0H02h3duZQx1eyxtnY3qOi/SHG2ggE1JAtTXw1Lkr11OOs0I05y2LKFBv7WQEjF2Ol1gqSaGIdQaJCZAiWix2nSmjDkzLfT0gp1GsA6Q+FKZQOS1EZiIHpSQFsk2U9M2XBH8IN+pVuoCsPxyYzD4wUnJzUnp4GqChTFhvVqywvPF5zdL7hcRfwwIMZp4st4DKk/DxC8x6XaAms0mxykJxs65HkaErDUrvI29Vkh1UvEiTHC7cnpItaWuKIkikcDfa01ilGD0OgHYpqXbIPrkntdFMG5UgGE+JSlNikwzS5UuT+K1kOE4DEh5Hw5BoMfBow1qT7EkSWRcSx6QcGOzSAoHVusBsYJD8ckSVMXOa318imAHOuFUMlkVGSMwRGTXbkxgsuAOnoFdgl8xyyviz2TI1xMBeaJ2QRCKlIXUyQWU13XhqBsyK6HXV9SV6CqtIGqLJnNKiqnUi3nmOSPYcB77fs0hEicNfQ+MnitixuigDh8cHR+UEwXoxao2wqb9qVilgx+U9G7TpoCqCQhxAhFkQp9rVPQL5OzlyscoQDjvUoKRyZFP9liTA0+xWhLnL09oAxFZmMsnl7v3aj7PABiBGfLsd+UFoQFYmKOSDI7l5Ipwe8SW5bdzkjubEYljSimLbBIGMbeNIVTCGtNoeeMsoRGNDmCFEQEHwaVH8ZIjCONNd7/JGAyGQqkj+e0H6NRswiVz6r5RBCb6gllvAveqeOt/p5qqqO3+hLe9UOlZQHT7cnLYLRjvm6SeT2ux/V4o/GmQI1oyv2Txphj4L8DvuHX+8Yi8ueBPw/w1FNPpbIFUfcmo8GFFtzHlIXWoNWHPjEHbiySRQxeUseWZAmcEusakELqC5P055KkQ9YqyElBm/c91tWE0CcmoCTGQetEbGZMUpG8BGL0WrsCBJ8KzW2uMzAU1mJiZiM0cBPfJXJA3Zectak7OxSVZpqN1aAv5maaxiC5i3iISc6mcq4ohjho7YKYSAyGwgBimM1Ljo6XHB0vOTmFxWLFbL4jhh1nD4QXXrBcnNcMg0r5YvCEGHBlqcxGVKmUcxYrmpV3TgN0g+CKgqEfVPpWmNR/xIxMmfbTlOm8JeJcpQ66NjuUCdrX3SW2xgPJXloLEjSYdW6UqRkshcuyMV3D0Hd4huQSpYGqoGxVTBLEoizVQUw8iKNIhfAYm4wADEVRYK3Ta4aUEc/BXnpPE9O6JoeqzIgZSayNT7bBk6zOjFJEldTFOCQgVgEpkDZqlFAUMwUySGoqqXUtGXzp6utvjFK+VMskjOdqRBS/SWYVLBJy3ZYCqiEKsYeNaKNXZ7dUu46DpqFylrIQqsbhrOCqAlV7GurE3kSxdH3Ah15rdKIhBMO2t3ivTW5NlnZJcgkUwYhP0tFkjx0GGKWjmZlVkFKWdQJAKidV6WByDcwzklk/qw5zuRmnsYXubaNGIERJyQyhdAq4owhD8IjVfklxdNELqZanorCCj3qOSMTainTX6Wy7AlNoDUuujVHjD0mMidbmIZEwxJFpwlgt/te7BOsKwKWkzYAqSpWxrl29JzkL+KEjVxTGGAjBI1Fld+oGJ3v1NrpnVJpqUOOS5OynpKxCmncupnnLv6cOl89cszhvwTBBRjBzhZUxBqkLZWauwcz1uB7X402Mr8j9TETOjTF/A/hNwLExpkhZsPcAL6anvQi8F3jBaLOOI7QQ8w2OCxKybGJsjoHJhbOobj9EAVNQFKlFYY7rUoO5KBGsSp7EWM3i50LuKESTG2HmHiwxqVwCqRE7IXbqvLYnmbLGaSBrCg0mfHK2ihFXVqlOI1kK2yQrMhrEiBWCj+oSZsEVKeAksSsE/aep+AQmPNHHydksBHxQIVFhC6xVsBFCIAYtitZo1lLXJUdHNTdultRNRQg1xpT4YWCzNvzq5wNnZ46+FbqAgkhE5U1Bi7cTTsS6Eu+7VFtkMSZby9rEQqg8rkgsldZzoKAKQavNVYcVJBIkAF5rmFK9kDXFWHciEvEhF8YntzExOFukniVJJlPoWkuEYLLErSSI1j1JVEbJpqBRo7qI+AFbpCJyci2PGe2KjVF3vNwpPpAz2iGxbgEf1YQhsyXgCLEHhMIp2+hSlDj0kiRlpGy5rr33A9YpeFJGIoH2ZOMrJiJpf1pniUEDcXXytSrPS7IqnXQFN9bkgnqV1DlxxKBsli1VNiYpe1+WZSo4DwyhRawkB7/AEA3t0FEmqWPpthSFYdZUVM5ROpekhSr9LApLVVaaXIgqV5xVal3cexiiYxg83g/0IST5uyQHODMCCGM1cSEYRP2r0Sa6Kjd0liTVdMTQY8K0PjHNr0t225IcEUnOas7kGi6jex3wYnDoHBgsRWJoxWqiIyQ3QhE/mo1gk5th2jMhRNQQT2sCE6Wc2KQisScqrQuJBXRFgfeD7ltjkKStjImlconJEq9mKCrvU0e/wpba9yjdO+pEl0wKnMX9/9n7kx1ZsiRdF/tE1lqqau6+947IjMzIru7lZTfnhG/ANyABzvgyfI07IDghOCPBMTnkkAAJEODF4bk8TVV20ezG3UxV1xIRDmS5R56qrKyscyqrIitdgERV7Ma3mZqamciS//9+acA8kJA0+3iA0uYgPPLvK4iU/Iz0IMxeKHp/7vWn+p56rX/aksMyU+aZA/9cLTNlfK2vXpnXeq3X+kfVH0M/+xHQ5xfFBfhfkKbK/xvwvyTJMv8b4P80/8r/ef73/33+/v/1H9Ypx4scq8zTZvOZSQFoTa/KC871Gd08ZTrP6doReeqj0xRrZoTMgcYgzfo2tf+kwZmS3ojIBPl49nfg+LO0h4FScD/miTEwT8dj5mzkqfLzz54cIpk5ORMjnNczscsxhwmlMiamNSwpVYSjtaGyMMYtm/OX8JI84e3DcmOihaUpl0vjzdsLD2/u2Dbl889PRAYfPsBXvz34+OGR8zD2/ZbbKdJ3Ed0Zzwf3GukTwnIY8aR5DUvp3tQgUWqFKaF73hBlZzZJUlOSl6Z3KKWm4d+d0XeqVtCWaFxNOU9CB7KBR4JSZPoQjDYHwVIEiSMN/JLytuGGx3jZkhUEoswBNXCS5AUzr8WyictXt1MiCXeIIm2CAoQ8XXdwyY2CjylrRDB79uaMlyBGD0tMcgQqFVBE+xw40nMTkbS90PRQFMkcFZ8I74RZPPscjJi0P/dBLS3fI/3ATKi1UEud6GlStjaHOvUclkttRJ9kNo95Yu9TymgTI54QApWFboaY0RmECFUKreWgVVRpTydbU7bmE7HsXFqdm5X0p7UC61IglO7psvKonPvJfgrXfhIo57AJBZCUXj4/bgHiOzKXz8cnURjj+TrlsC9SU/aIEqQZ3n2OWtODlDK3BAXkzDJ9dCVfs3NuxLQkZTHVp0KVPHJYNDd45mS4Z0RKv563T+7UWnNonT8rB5gD0fJCeFNRKPFynyRvIN9nz/TCooUww+gwCWgehpnPrd3ITR+5YbQ5WJdS8r4rSUPMz4pJmNOa2+QJXPF5OPIiF50SuFRO/vmehv/zfE+91n9pyXBkH4j7dwGZz9VqSsxeQzJf67Ve6z+z/phNzU+B/93UKyvwf4yI/4uI/L+B/4OI/G+B/wfw384//98C/3sR+TfAN8D/+h/6B55JZTFzG2zSf0ScUhdSnmJTBz+zUMhwSQtHo6BaJ+9rvGxKfEpuRBX8TDkIBkZKzkQwLy/SNqEw/EhDsmT2jFkOGyYTx1tmYyolT73FKXVDtTLswGdQpsgz3tdTNud5MuvjzMZnCD7/bqiSawefuR+FMHA7XiAGqvNUfQwWWWhloZTKdln40RcPbBcFqZgFY8DXXysf3xsfPjzy9Hhkloo2bCKqVYJSVuaZf8pchLmFqdP/kWSoHNpO2vIsleq02maoYUmJ0ySXSXmWn825KCZGlwUnqBMlbRYvA2WUyIwUBEokqMF9bkgcG4ponQPiJGdN6dFSG8P2iYNODLRFwWVuBGa2j+pzhlFOzbW0mV+SA9EziprwTIefSF33gAL4yF+DzD8Rnb1j5paUujLGnkODJzxBycEsFGqZfonp7XAfuTHUDHRMT1gORM/NKzE3Ae4gPU/qS4Pf8S8lpAIiEibwfEDAbIJf5JaWA3cgjPG83bMXieazVEnLlITVFTud6BnQOcwYo7DfnLYmgKGVwq3trK2wFIHIDcK6pKm/acEQxJ37rbA22CwHHvPg7J1zOPtpDNb0jHikl64USl2R0aefqGIjDxVs+BxqjSL+4ncScVwC05rXyBPmoNrQCn0Gd6ooNlI+N2zk8BffZez4GJzEy+YkPShBCaUUZa1BaxVzIagghX4a3TrDIz+TyvSp67Nba8oeeZajZrZU5iDlPTn6yfyQIzy9cs/ywvyMnLJZIj035VlqK6jmIDOGzfvn+V+yiUBPGebLVshGDs/x3XaplPrix/kzrD/599Rr/eeVWMBw9Bw5yPzu7Fj0xfT/KjF7rdd6rf/S+mPoZ/9P4H/2e3793wL/89/z6zvwv/pHPYoIfORJ67OP4/m0PDtmQUpQJiXInyllpSDPxuKpEX/xvkwCVoYkPv9eI7y/bHqYDaNKmXjaBBBIqZngLhlymFuibBDN0gNStUBjBubl79eSaMlMDy/088yGy7O7l5INpFl6AuC7bQQORZfpETIiBqXkf5s5tSi1VkopvHl7x9u377i722YzI0QcjOF88/UTx37w+HTFPX08HoZKRXBKEXQ2vaMf8znm0Hg++wMkB4oM0nRqqS/IWRuO4dAzV0PVkmblz8SuMvNcPKVc8/eQYFs2fOw5/Ahz8JQpfUkIRJFMRE+6Ws1BdJ5md0upHl4JHxiWcjzJTCEzKJNI9zz4hA1ozxsPxyxobSEiqDOzxc4OZd4vM81etdDnCuvZn/EcxuozR0a05XMtU7o3769naZI870ZMJykvG2SPoOiSTW3YDFNMLwTP3g3xHG7ne0GfYRAx5nP/3bePvWwrPZyq5cVX4lPOlEG0PmWMipSWG0PvQEo9n71dMvN+VGN6lkCocyAH75mzcoTyRNCqsCzKWkBwHlTZWkXc5jYSWiv5s7VRgT7GlDU6D5eVwyqjC2fPUNBzGNZPNCKvrycKuUh95jxQBKyfhNjLhhBShqdV8DHliIx8HmgeFqjM16hQas0sIT9xYnqwcgsnSg73UpKcRm4sqxaq9cRiq7M1uL8k5a3biUvFqexnZ5ijDGx6i/J1ciwGuU3xl88jtykv1DxqGJZDUAIrbA7FQVu23PL4zG2anhvzA6Sipc7tU8n7n5R0+jh4Js4hEy4ggnufw0z62f4c65/le+q1/vjyPJySfSBn/09/T4RoFariS3mVmL3Wa73WP1n9ozw1f6pKYz2ZXUjSrtxTI9/7mQbmktjjYUaQGOYxOm2eVhKRJ5fPX9puiXp1JxgUTYLQM973+cv7O2yw8ez5zsyYNJzE1Pzr86moPKOjrzPapMztzGxALabUJ/M0lJL5Om653RHJUNA6PR9mc+iYH+4SE8U8MzRCqEV58+6B7bLy9s0d928eEgMbj9TaOfbKh48HH94/8vHDp0leq5SSfgOZuF1/kZokre0FD0yhUhl25qUTSbmV28xxEbyPBByI4B1GmQ1xWdKUH4k3NvMJAnBkZr8M6xncaRWRpEkN6zlETl+KeyRRlzzpRp3Lck8EjJ7DTMoKk2SX+SOzqasLPqVgdj7R1ruUmhEvfhYbhptTmxJ0oNKPY4IejOiCaMXwmS3ScxMXDlSEgo1BFP/uvp1hk8wwSZm5JUoSqcznY36WGEWesrfSiAiW+Zq4jxfJmU2jfJGC2Ykj02zOzGkSJArmew71mpQ2j6A0pcWKauXsV3LFJIQdjAhewkHFGGPkgPKcyWJJ6GtlPs/REy8tAA2zHYt5v/hzFkrCLE6H3YOmOYA+HQdL2SnFuSyFy3afXpgQUllitFZoERRXWlM2CdwbEZXbvnMeMFzoUefnwEBEGP1kRurke3JK+Zgo7ny+A3OZ9K8ZvKm83I8pVvMXnPckDhDzcCXffplVpZrS0VI0s6dKylrH2TmnH6XpSElcBK3AUgvrIrzbVvo0PjuNboahnKdxENiY2TeRHipZagIWgVpWvOYhQpC+QJGJKn8eLt3m8Do/r2RKXedJeExpY8JOvgOdxHwdcwMEEYWwmfP15znTvNb3pTzQ05Cj52HW37qhYmnEVl8lZq/1Wq/1J6nvxVAj+nySzPTK2PxiT/wxczAxn2hkD8yOKZlqPBOHMgPGp+SMJEh5oOqI5sAhkt6MTNSGUhaescIyJS14yqjSxA+gc+vhFDpS6mwYglrTdGxxgiRmFpgm9eeAyGweMCdkpPnbD1Cl1EaJJCmZ93kan03Uugr3d4WHNxv39z/gzdsHxuiY31i3zrAnvvrtyTdfO9djTI9NPs5nbw4BIc6w6zwFnonqlobl8MzeSdLTkbQoN5SkmyEFH5kpkyCEMqlgA4qwNmUMwyTpYgyfPWKeFKfROv07z8kroc5SN7wPhp9IXSGC0ffc1qmyaG6Zek+/kZSJcfY+82Jy1EDju/BM8emJsjm4CjG3JNaTBvUsYXQ/SKyzEzZywxeBd6doYzxLz0SzH8eoazbmdu7ZEEs2nenRyNNwwWi65Am4zJvb4TnLJCZaHMlMmW49JXpaKZOcpiq0tlDC6DFyW2gpX8zt1nhpaluplLlZsKGMGDRNmIHZSOJX8Zf3xnP4qI/57yxbetcsUlpZ8kMhzHFVVJeUfoaz1OUlC8Um0esFBxzG8ILGwn7eQAZrW7k+ddblA9tWeXO3sraaxnVVWhG0NsxPnnN5aoF6t9KXSu/pt7IIjhNOg73k4yk1CM+UmJjNfHi+FuM88HCmdS63EjG3qvNzQuc2t7QG1udnjmKS8r0MkdUpMc3spBLTDycg0jBPGdfZB9qTNPIsyys3oShcWmFthbUGd2uhtYp7ZdjCfh6cozAMjt45PTOLwgbeLb2EEhznjTLf1yIK2JR2GkVabtiesdsxkFLzeYpTavqnysy+sukHjIl1FjI3KDfg8ee6qHmtf+GSbug+0s9l/p/+Zi3EMilmr9kyr/Var/UnrO/FUANJ+Zkrk5RgTT+EhL6EUaoIKpGhlRaTljWymdE82U6qlE9/gOI6TfvMNPacdia2Nw3d/TymPl0zewJHQjMzpyS5yP2k1QzKTFhLauWHBZQ8iX+hHHmGBUqthA1KeUYW8yKRKbPZj6nzr3VDzSnFWLeVd59v/OIXhW119uOCm/Pw5gOfPjnf/OaJv/kPO0+PnbPndimHFeMZ9ZuQhQoi1LYSMbBxTDFQNoBVCqd3Yow0z4tQa6OWRFkzm09qbqc0FKUARrf0NRz7DH9c24QlkDowT5pTqTNnZ5qekTKJapkhUrSkxEgq1DZhBUIpC+cxGGNHa5uDbZ4y68zuYKKaReemK9KkPtzRUieu92TYYCAUqTn7TOM8ajPbKAMcVZzWVvwYL0GaaA5touQmxk9kAiVye5gDR9E6s3mCMc6XU/FaF0RsDpttwgvyPgj3lH2JTwzvi4Bq0s6egQF5fVQLFoZbBjqqKDECr4Vh59wkJBY8PTRLDuajgykjOlaEVhpLXXKwsv5iYlcBHxmCm4cEgtOxMTLoNaD3HJ7XVjEZc9CdWToCHmea6S0IOorQT+X0YD9vrGtjrVDLJaWJ0rOxriVheX7mQC3pryqt4Q6XJe/p2+FYFLoFwwuuHbVOjp05yD776zxGAiH8fMmoqlpzEzVze0Yckzy3Avncn7capTRM5tBsKWENn1uzsNzM1JqblGd/vha6O0euJnlCaK1S1KkabOvKtjSWIlyq8mYj77kxuPV0ne37wX52Tg9MNXN0LGVqeRCR904phSKZpTR6x83xAlUarW74uPFdDlBNkMGzVJckRI55L8nEWcfrVPNaf2TJ8O9QzH+bYDYlZrFVQuVVYvZar/Va/yz1vRhqMrDOpn8hG04t6zR1Oz79DDYSs6ulZpMYzxIjIVcSOQSJ1DS9Ypz9fCbepnSk95kbUtAyGGaTYtSppc0skUREg6S0SmYA4URHi0rmpnhM1DApr/Fp/p/+jZStVOqUGdk4gDLDLedpfQwwY7us/OjH97z7rHB3X9g2ePtWWBbnOA4eHz/xN3+98+vfKB/eH3mdKNnsloaEkwfRUzJWJA3Z5kTPTJ6Qlv/+9IiM0ZO+FvtEOC/pOxhTMqM9r6kIY5w0nXImAYs0ypf5PBopZWqtIovODJOk2BGDqguBTsned000ZpkRo2kel+gUFrp1bBxISRN0SokqEcLwzDkRcWopKeeSNIX3MRBthA9GPyddLD1B4YYJPOe2VG3Tw1VQbbn9M8Ow+e8qEUqdA7P5MQlmFSEYfUw0ruO2U2Wh1MLoNoMwGz19/Kj3VHLNPBVg+inyPWD2PJgFLtPor06hYGaYgodOA3lLSRoZNCqRgasZBpsNcAA1hLBgDKOUirpOzLC9+EdsZJPrOqZRfL48zPec57YuQujjRFSo0pCSXbxohsUaSUizkVk8dWmJHA8nVDiPDjdjvZG+lPqBdYFFnbU2FjFqVUQlr6soRWD0JKsFztM+kLImbEIOSgRUpRyF3vP6qq7UtREoZ7+haL5XRAiHET3b9hn+qc8Uw4lFLnVBpo+t+4lQJsJ7hq+WkkMxz8SwkUOfLIhumQPkZx7OSPp3ThfCJO/n66BppaqyLoXLCmvbWVoeR6xNudvuCRscPeWL170xzDjHoIfSTTn7yK1L5IBd20qn52fAODktr0fRgptxGwdFG+Hps0opZ3rskjQ4Q2Bf67X+QIklxEX38Z9myjxX0dzILK8Ss9d6rdf656/vxVBDBIXZ0OHzRDxPqWurkGeh2BwokmZVoJTZ7E7zMzI1747Pk+tug1oqNcAisGGg+pKVUVVx4WVTlMjlGYqpuSGQlsZbJmZWdJK2akECuqURUp7hBr8znKVMLTNfkgob1JKytboI794tvHl7x+efv+XNW2Vdd0oJIu4Y4+BXv+z86lfG11/tHPuzCb9R18roJ+Kg7pimidiH5RZgEpMyaC/DL210XGxKhtIsXesKuswNmeYQSFDbCjN8VKZfobQ0xmfTKuDZDE1aM9OZj0gSyZKkoCjPhmaZAY8tzdieXqfhTsSB4IRBD6cuC0T++z4GtSyIK1qVKEmkE89hwD0xz0oBN86+IwJLWyi6UKRy7B+QVtBlSenQGNOwnRKr9A5VxHMIRW0Sy6Z3prbpvUjjtkr6u5wxqXoxww8T3+yh4ILoQCLT7kttee8hnOeUvKkTlnZ6F5BS0KL52gaESkrAntPrWyNOy32ZRIZAhs2sFiN6ENIQqQyfG5RgEt1m1gtz46CB1KD39F2FCkL6c2KA+0FbYL0k1KD3HAxEZrZLJN6aMrdCrkneirxmOt+V3k+0LYgURsz7sEM7ClWMpQ4uF6fVStUclHWiELoL+xmodIY7921QcZZtw+Y9PFrjdsLex8ycARBa21JmqpJwi/m4zzMzX7LhH3OLCFEqVSWv+9w41VYoKCaZF1NqeQFQJH48D0sigjGOPAzRIF9lcpCYm0ipF8xPhjvdnNswPu2CFmi1slSh6SfWVtjazG8i83Lu7y78sAbnMNCFp+tOxekO1z44h3CVhrtgPnDvc1BLQEXmJeXnFR5p/fOTVmoeZMh3HsPXeq3/pHzuj/eOHOPvGq8yxRVfG7G+Esxe67Ve61+uvhdDTZCyF0pJOa4YrS280AMyxp2lrRmIqM8n3TaTyDOJvtZG0YU+9heTb5GFMOG0gUiZid1pHBcVWrvg1ikl4QI9BqCItCk1CdRmSGcE7iPt15L/vpnRLe3238mInj/386Q15SwZylhb8Pat8eMfKz/+8sLDm89QKZjtBCdmzvUq/OY3X/PLX175+H5Q5A73HLY8It0pvVOfMyhEGX3kY53SMdU8OR99z2FPFaowekp73JyITkjK39wT1Rwh0/OTor1S2gyBDMw9t1XP8jpN6teYpnwkzdDSD8JO0CSCic4sIM0AzwwjddYlgwKLQB9H0t68cvSD8E5b72Dm/jCeoQdpti8qoBtnP4AMcKtlYfigtQ3IDJtWCtYHFkIh0+PFCz4yVb2WlpS3UCLgGHtu0DxN36L5Yutz7kkt07Q9QwvJfKVzQK0VlcCj080RMapn5pBowUXp/aCUBoyU3ElFw6YvzJG6MOZwXyiM4VM2lYOnenB65Em8VqpmFknMZtwmwaoWQycIIubrhGSe0ugDjQyLlBJ5rZc7CKH3vAdCoNZGdydGnuyXZ8+J+JQAyksAbKnpCQscbYq4491yyypz6o1gxDN62BkTGNANbo8ntThLUZoMWnFqWyhNnxd7/OCyIFqR6PO9JpkFtVbWtXB04/HaU5JKurhElCbKOaOXiBwgZAZUtmXh/v6eUiv7cbzI6HR+/pgNjmN/8dwlRARq3TjjxGxMUuBENwtIxARAwPCTopr3qEi+P81etr/mg9GdPmAHIjptaRTtFIFaBDNl7098dr/m4YIMPntoCUMJ+KJc2Hvn60+dVpU+4OlIeV13J0wnVODIDy4VrHcSZ5LBwBIlUeWv9VqzxCLlZef4u/IyyA3nWhPJLLxKzF7rtf5EJYe9AGB+X7361b6r78VQQ0CfGvVSMgtCJ3Z12El4ppaL6CSD1elJyABKJs8IEfromRFRfCasJ2DADapWIkBkTEzsYNhJrmiYqN6JP50GYUE5+pk5KDbD9Uj8UrjgJi85J0KmqEtkrkytZYaIntxdlJ/81R0/+Znzgx8Otq1i4y0i8PjpA9fre643eP+t8P5beHpS+giIij6jViWQWtHw3DL0gWsltHCe/cXo3cqS5m0Cl5QUpVW9sLRGbWDes0meVK0+fTWqFa0NJ5sxsQwVHc/ilEiPgJmldKUWog/O/YpondscB22JlFVIC3XB+pHbCkmDv5GNKyPQSAoZmmZqVSWsP7uhZt7HdKN4Gt8zHHVKbBwkZJ46O1UrfsLACTGWbaW0MrcpTG9RkBK+SE/KdBRkaOGap/dTYiFhudnAsTB6dNzHBAQkfAJxLDy3BUVZWkUsEeRtyW3LmLkrRWZII3NYEnBxoh+Jb470d4gkjUxKyiDj7Nmgkpjn9JWd6ZEwT19ECN1zA1FKRem05cI5Elm+ruvc3OWmzjTxwrVVVITjPHIY8vSomBnDQGfY6vCEf5sZFc0hbTb9pQZmJzLlaqhSl2VKpWY4Zqlojdz+uDOC9H4BhxlmO0utLGfnsqbkTmvmusTYgcynai03O2cIIcJSg3f3S265VDOvCOfoMHbHvMzHarOhh1ILl7t7fvDDH1BrzSHFg+eAn7N3vvrqa27XG7fblfO2J9ihGE4OgBJCSL5HA53eOacuiT0/R6doYWkZ0vm8DEl5ZM/wTgmGJclseGYSCUl8W1oeFuznQSuNrVbWBlWVSkDL4edHbxeKJOXu6Ck1fLqlN+4YjkuS5Q6HXhL5nYCB3NLK84fxa/3llgfSHTH7/VsZgFYzV2bmy7zWa73Wn7iqwtFT/vl7ZJ/yfMDQCjGjRf5S6/sx1Ewqk2pDGGREIAwUovBdfF1Se7JpWfAokwYUSMAYnnIfJnXrJb8kszgSexoMS6nWPFalloIZnP2czWmA5qURmX4UFK0LZiPhADAFJkFVZqo5M88lA0KXVbh/EH785cYPf3jHm7cL67oDhdFTe399cv79f3jiN7/auV4BFkpZXgIZxzhmowqlgninSE06l6SMTCRoLeVRITKp0ik7a+2Cx2Cce5qL2+/S2XKY8cjnIiJ50l8X1Mts5DWzTRxEGyOE8wR1KMNYmuYAIQMphSqBritjpAdBtTCsU0qlHwql4nEC+Tr6mDkpMU3eLYMJJWb6udaU8VTNHB/g7MckqtlL019qmSZ5pXfHxRFt2Dhy8AomYrlN71MGXJoEo+e2b6T+MD0j89QdSUlerSvDThTNAMw5GA1PWdm6NNycozvuSqtKnQhvs07vU64ouSGIkvKnvPg1N0hSwWGcgUd6voqSjcaSfqJSocpGH3kIYGPgjKRzVc3TVUn/jUhFRBneUc930TPKN+ltJ2fv+edCMhdGhbZUuiV1TEPws+Oar8G2LkhXzvOcMlHwEXgcjCjp7XGhBLRlQzSHpWHpmatVyfydmPlQ+4vXanCjzsFzjMGplcdPV7QubJeNVQdN8wM8NxKe/9fSC6My85HqkqREyffmZVnwEVgo3cHpFAnWtdHHzodvf8vTx0/c3194+/k73rx5y7KuqCpjDJaaUI99P/j48QPv33/gPE+8P396lRepV3neDLojbRIEIw9jxjDMBrUuiTQIn4Ng5lF5DELrSx7VyAUkt3lKF2EJsyidVoWtCUtVSs/HuNTK6UGVmgcOCm9XxcJ5+9AIWTiOwmm5dT1scNsP9j19ZRbGy8T1Wn9RJSPpoHr0DMj821XSe+aX9hqS+Vqv9c9cUYS4W7IXsIre8lD6hTQYgewd2TvUgq8tAVZ/gb6278VQI6IUzcwNH0Z/bsDmlz7IxLcqPvLXWlGKJNpZ24LGQu97ooa1MiyI8Zy4nsF5EqDSaPUufQMERM9GTxtBZ8CUKUlSvQCta3p4PNHHWgqllOkfKYTP03kVVI3LXePHP77nyy8Ln/2g5YCiDRspLevd6Sd89dsbf/PLk6cnx/1uInILGjVzVSIQCbRm6KdP871LnuJn3sRJaCFUqWQiuE/8tYa+bGSE1NTn+0Cn1ycHwpTHZFOVzISEDgw0kdeAjz5lPgvj6DxzcQPNvxfQJFHXojlAegT9uKXsKc0YtKaMkfIuIv//qJdJnDupIzHBMb1L6Z9K83kfiXoTaXOYBesdkWxax/M1CwNxWltwT5iCP6OQbYZjRoeSwYvDBja3X0u9oGFYH2hrFF1Z1y3vBU050vDpmRKjtBxSbBL7Sq3Ymc3hs7xou2zs50FEeRneEmFsqMA5esqkljdYnHQ6pVzQcqS/xwW8UVQ57UYp0JYLNjrDE3m91rwmYxreEcFi4H3KvuTEJYEC8CxjnBTACVbAnTECqQtNBXumscmgTsP9vh/z3qv4EGpJ6htjUEPxufGRiU9HjD4y6V7cWJYFnulsWtNnM84cdCIQKwgV1fTAjQgw4fY0UJxahCbG0gpLbSwl3xNlnCkjdKOE5MymwlIXmsAP3jT6GBync0oQWvEo+f5WcHvi668+8NU3v+XNm7f88IdfcHd/D5Jo57Ut1Fp5+/aBn/3sp3z88IHHT498++1Hjj6QujKsE9HzQIXCOByTk1IUJIl2Eem9clFCC2u7UOuC24E2SZVP7y/XvhbFrdMnLVeXRrBw7p29B7UZWxO0G/dLQVFuPpJbMoQmlVZPSgQqwVKCVizfe1F5exGO3ehncLXCqwLtL6j+UEDmcxVN0/9SX7cyr/Va/9KlQmjBJgFYzvGdPPS5hqHzYOIlF+oviED4vRhqIBuQRNXmpkVIc3sgUFPaZeNEilC1JYnqGbNqgyGK1sysGZayDffOc7K9xDO1qKdXoI9JAEpZ2RgnWgKVmrSuekGiZSie68RFQ9s23J0+TsKMUitLbdQW/PCL4Bd/pbx9e09b1um5uXAelT6cp6fg/YeTj98Obk/O2ZMaJZJEskwV79h58Jw0LjK1zSKZWl+m2RfFxRkRxDkoKFErFpYNXUTakTwHFCTQuqEU+ugMO9CWw1mdhCR3m5uBNLGbQe83IkDLBTMjYsfDaUtjjB2LdW7ZKv080LrhIyVRtS7ECAorKoLrweg7pawIC24dkQDbabViHvTzpLUVSiEkN3Y2JomqrDlIqpIxhYka9jHAUnYGsJQ7fOwc+zVJTxbUpFtjIyVraOb0tEkbs0iAQ8QtKWOkX0FUWRSejk/UeodaSS9HjLSyuzCip6JOC1pWliZodEY/MMkwUxOhHyflOZFeKuH9O+yzFgRD6NSSgyyRBnZBsfNImppb+qDcsfOcUseCu3CeJ6W0F5KXolg/uKz3hAjX/THpXbEm5MFmCn2p0xMyje8hE0pQIQrH7ROuY34oPg8MCeSwcaAFain08wYO5km6Q2zS0aaZRYQRQZGGec/Xv7QXmlhtbZrjE73tkbK61kpuwY4bVlZYKuetUzTv1zqDcYvmJhc/WVuhNBKgUQwfSQPbFri7bHOwdiwaEbDfOk0MM3j68IHr0yeWtrFuFx7ePsDdPR5QpfLZu8/40Y9+hLtzuz7x7Tdf8+HDJ759/55xDobCCLCen2Gl5uFBtzMh5BEsdSNsYVjmL/XznBQ2wchrsGiliCAalDU/g0KNWgWVRFMfR2ARFHH2Y6eWSciThKhoEVqBtRa6PXG/LmxTAbrWhkVhfVCiH7w5D9pfyBffX3LJ8GyGnlHMf+cPSGbLtIIv5S+mGXqt1/pzqihCXBqsNQNvu+WW9Xcko3L2PLD4C6ISfi+GmojAemrSi0wZF5Kp9xYwnFEytDJzMRylZsJ5KMPbS1PoHkhoYlMvU9ZhkQNOAYtECGsRmM2U1pQ7KY0wo9bEuA7Lk3+Lkc03itgMlzRnWRoPDxs/+cnClz+DH/xw57INVB9Bruz7He+/hU8fgl/+6spXv/2W695RlKWueDg+DoSKFE3ZjDloejjSyC0UyUBSJKjU+VyUVtbMr/CRw51Y5vCI5MCmkpQ2hTGM3q8s68Pk9XbKpLu5B3bmc9RSwfI0WaRlA+9OxJ4n6FJJUF36fWIETuaA1GXh7B2o1LoR1qkotQjaEryQjyON8eu6ITYYo085YKK6DfBxQ7VxWswtmeB2UJpQJDLTJDwT20MyNLJVJCp935PIVnJzADKbx5EoaS1UXfEouCsaC6moyIDQUgo0MBvZfEeinc1O2rrRSmMcRhFyu4jQbyemjnqnqXLaIFyRUmgzCFRF50l4el/GsMl7Jv/bd0Q1R3rbX+ST4YNuJ8hBUaWSeU0iPgNV04O0bnPQODpRhLom/c0xMDIHqS4Jr9CUXGpZcU4kStLCrOPRwTPFXlXQlpk5rT3Ma3KiQh48BHiPxH+/4KB1+ooEZohp/v3tBXYhNMx2xDtLS1lhBpDPja0ner2UgoigRViWDdWWj0+FY6TUjvOcuGxNwpsII4wlFvoQHseN3julKZe1sGhujKToBAMIIgt6K/Rj0Ce90Ljx/vrIh2+/4e7+DfdvH7i7f2DfVqRUtCjb5Z6f/9UDP/9F8M1Xv+Wbr77m+vjE0/UjN3G65/tQRQkW0Ilzd0OK4y4cx5lywqJUEcYYlHKXskRPeMgMWGJdGmKWW2nJTY7168xhUsaQdIrJCSFUAyvBpxuYKT4UvSi1laQalsZt39mK06q80PFe619Zefy9jc9LPTc+83+v9Vqv9WdQKvhWYasvuVF/58DCHDFPn9y/8gOL78VQAzMjQVKukwn22Rz7xMKGdUZ4PuBYABh90E+jVqctFwJDi9HqmgGIM2PC4iREKGUF6xTRhAFEJOWMpBW1pVGWC24HZn0Sj7IxVnGapn+jFuHhB/d8+dMf8O6zhbs7IeLkP/77NJe/eePU6nzzzc5f/8ff8OF9Z78duBvreqHUbcpQDvo4WFejtJSg5PYibzQFsLwJM9hRU0alwTp1/iqGy9zyjDRGI4Wi6U0Z1nO7M9GtTiSlynLSV63z+me2hsQMbKQDHa0XfFjKY+Y2R0ulnzfMRoZnal4j8Tw1XiYWO9dMNXNXwsCFoo195LWN2zWDK5clr3M/qG1udZDZDHvm64SCnaALWlPyNA6jBPRzR5c1h4A48JLXQFTAZJLhCrU4iCMlcrODc85N1OkZzrg0wcZJWRquueWqZWFd3zD8liSvKDhQa+bCCJGnJVoZ/WCEUbe7+Zoc+Bj4eUBLkIIMSZO4dUrLe8ZOnc175iRpIwf8LgxzJCdp3IJxOtSaBny3l21aW1seCLSCxGD0G60snMeRYaGXdQY9OuYHWpylLPQpRxzjxM4pxyzrS0CslpXgZPQbWhaKbpOmNQEHYYguiec+b3PoThS7jYO2XHBpjNMTuR4HIJlP5AHkFsWA4ePFT5ag98bok0hWJ6zDc4M7zCesIcELJRoSBbRwjE7vnVpSOukEa73jw9OJWGddlW0tVHWqGI2CbulLOYbT59aqzdwpO3e++ZtPfFoLH755x89+8QvevH2LiHB2S+ni3QM//MnCD2xw3D5xuz1yvd04rlfO0Rmlso+R2yld58FBAh1UG5SUwxUVKAMfJ8Ond2/i5s+zp5Q08mBBSqGS/sEES6T70CUwGZhUqj/fp51jnLy/BXUkobCud4QpI4S1tN/b677Wn29Jt5fNzO/dysCLxMzX+q+yyXmt1/pLqZcDCQ/0GOmV+12wQCRoQPqgHPoC+/jXdIjx/RhqsvdMmROK1MhjWzGWItRSOI5OmGGRTbLWBrqw3j37Yk6KVkIaOaQWZBjBQakrTRTvnaBw9BMVnfnjzjluFF1Yygaiab6euGbotFq4W1e2y8a7dw+8eXvhctGUxQQchyMs9G70Pvj4Hj5+GHzzfmc/TpjeoLrcp4Son1iMbEJq+mF67/gwallxl0wKt0FdExpgI1PrQx0N4Rw7hZIn5vI84KS0RclwShxUajZ64URkwKK2BdPMIzF6bsNmA9vtRlsqhZKkOQlak2w7wwiFogu6bdlY9jOpdO6EnSxto5YyqXLZiI3jBB+EWGYLSVLW4rTclHj+rJgDpESdJLrM+8AdlUaPY3oDdG53Ug6YSUVg48BisNSNdbmjn1cAvKZULY+hK2N0RDyRuAShDfGZ6yMZ5qoUzn7O0/IkfLkf2NiR6rlFk4V+Ht/dxnPbtI+dFgdr3RDJYcdloQ/nsE5TZ2ajYjKzj6yjvxvMOv0ZIoV1rWivqG50DHPDJ5a5lBXVlOQdx5lm8pqUrTBPUpk8AzUk9bZIXueX/JZC0PP+qDWXRyWwvqOROOkIxfxE1CnSGN6xiaKuS/p0AqesGzbOKR2ruMHonVoqWkELEBkoKlPGVupC+KBpoUR6dyQUj6kLBiIUn0b7sJGEwzGDdOs6PVngZ8cU0Hz/j9JzoCsLw4N+eEoGcW5nMOygNWFblMuinH6jtNyCqsB59gQt6DK3gE98uO48Pn7iBz/4IZ/94HPevH2bIbttybBXEd784Me840f0Y+f6+IGnp4/crgcfPnyitAUteW32PQOAl3V9gaB4SIIofL6GwfTE5eejhUwYCpzW0TDcd1pr9BCKNFpZEDnQIlTdiPPkDGNIS7/dAVVXxg3COyrGkyrdX6eaP/cSC+To2dD8PtM/pNSx1b84vf1rvdZfRGlCPQBktAQL/O0NrTlyPVLlUAtR9V8F0fD7MdQgaWiWjk6/xRkH4Wf6A6KCrGjNxlpbYd0uWN8JNw4beJzcXTbEe5qeYzAMWl2JbpxxgmeTGDMpHhUiOmXm27hf8bCkXbU8tdUCn3++8bOffs7d3QPLCqWkUd8jyU/X68F+O/jm20cer8YYSnSwIRQqFKW2RtWUfCTyFghHS80EdZRSc9tQa0UDeu+cfU80sns2yC8heVNtI4lXDknjvkolYqKn3SGUmHS4kI55pbZ7UMfHFfxk9EAlgQAhg/A87dbSGJJUp+etRURhP3e0VFQKkANIjiAp84tRZ9hjQcTzVN+M5f6eWivHcTDORDBLqbN5HWirKTn0JIHZDFb1GEAjVNFSGH1wO3eQmmBeKfnaquUNbYPj+inzh7ZLWvLPM69DWXAW8DFpeJIAsgLLoqgk0rcEtFLYe2aRtNIyuyeEoSeZT6OYC0RHxBIhLJlXEzEY/ojqAgR1KXg/cZzeDa8buUmsmHW0KFVbEtz6gfUTaSnd6+fBGB0tULY175Ve6OMTwUC1UUqjlYrbmeCD4RMBTg5woRS9ZEYK88yAYPSDEMGJ6ceY2OzwF4/ZsDOHVAnGGLSSfq6QRE4jlXGeII7WSlvu6f0KnKzbQj+dww9EA3WlTNqaaKWuG4Qw7AAziraUrnmS7zwUG2dmKrnN0MwlhxkpaORJVNlaHgSIMYYnyIEpVZzvO48cnIOO+aB7hlkeI5HH+znBHHbQVPEBZQ6grRj9HJgPWlQ4H/nq1ze+/u2v2JaFu4e3PHz2A7QUWmuZ9aNK3e5YKdT1gfuHnWVZOfads99YqrDerRznIJN1OgeGeUuMNk5VGGOkiDKeqXVJL6v1kr43L1jAOI1SCsuS1MYSBe8dWqXWBqKZlaUl/TkRnHak9G36KOZ++LX+3OoZxdwN6X8PihkyJHNb/mLJSK/1Wn9pFVWxN+t3hMP9/Ltb22HISIx7tImGbn+eaOjvyVATlBaMAfuxZ7MvRq0VKQuEUKbhOEQSEdt3Rs90+7IsFII+PiVfX3OVZuZ4f2K9XFhLpZ9zWLVBWQQpjfM4IaBGQDFsnGzbwtt3Kz/56crbN0kn0uJs2xNtTRTtea7crsb7b09++csPPH664jFY1jvUYdiOz2Y1wwMjZUiWZCM0qW8Z5pfSuxFprMaVYQeOzcFBkuJGYD0xzgAjOqqBRce802rj7nLBaIxxpBF82KS76TT/G6pHEq1K0B1Ug/R5VJQp12qJcA4bGco3m0zrfYZWVsIyM6WPgyqNUlckyHySAI3ctpVFCS/E2HHuGD2dLstSEdJvMexAoyftTMo0QnfAWS/ppehnEp3cOuJCrUH0nVrbJGVNIO0cxFiWzIVBc7iQZ++NclwNNzITx51SlDqpcuO4YTqo6z1LLQmFCJCSzbiKJ2zBH6n1Ln0l4ahIkq7cGXvQI0MXlzWBDzg5xIjmEK8pjcINimCSWUsoGEKlYMMoZWGRfPxhmbsjRWjkrw3vHP2JVjOLp0TgGKVseOQ2I0Ya6N0MJ0lvtSyIDTxyoLQxMPPMLnIoFEIGLsGwfGwyf15tC225MPpJjGz43Y3SgtKm50YLrRWCwXF23AFdcjhJZxDqJfOm3F9koCLpm3M/gZo+JE9Joorg0XOLqIrW9J3lBOIp6dMFdWV45OZDwbpwFpvEw0GbBv1SKo7jBoefqBSExnUcRFRUhXVxgo6PzrZWLAQbRi2Jlxa78u1vP/Lp00e2yz3rZaPUxrJufPb5Z9y/eZOyTYTPfvgjzv3G11/9ho8f3rO0HECGO/frhe7w8QZunfCeG+r2PKAVcMMnDOQ4ryTcUBLvXgph8HRLUEpBQSp9HKjsFCI3e7Ug7lCVpS20PpIGGZZSytf6s6k/eiuzVlBN7f1rvdZr/cVVVIUKtl7QPXGafyeLKuI7uMCf6fbme/EJFxH0I5smLWk0LnWbRnfDPTcPoo3aEo1smQY4CWZJZWplATXcKxagOggZjKMTUhmRjX1rdxxijBC03eHD8XDutuCzz3/AF1+85XInLG1Qa8NduO3Tg7NX+tn59puD3/zqPfupOBmyp1LTrzBuuPXZoCZZ7LRbSoLmqfhSViJK+lti4H6jSaFQs7moKcOJcIooWhbMQGqdJ82Oe0fPkafl4aCGnTdCJX0XIoSCRIIFVPPxdd8JOqJCrQ2pd5gZ1o/n9Q9SJD0kkdkupRZKK8iyEDbIEMpBadAuD4zDqe2SnpLjmhsVm7jhywMiQT8H57mncb0VpCyZjzJuWGLg0ldlI3M5kBzEXOYguBDWkQpNMjvI3HOLIZWmJf0yc5sVUhinE8PQttL7jkLmIXnKdPDA8/bhNnZqvUcWx8fgPB8JFFFNac/tMfHVl4XSFqRDRQhtnJ4YcfVBkXzcw8htkqeDXpd7LFLCFSPv+2c09BgnRdIjFKUSS6P7SXEQMUpJfNvZD0Ibo0x/U61ISVR09x0fNQdgzbBKjwAKzsiNjQYSSZVz60gY4YMqFX82sUcgVcA1/66dSE24AAZ9v+F9JHo7bA4vCigjMnumqKARnDOfpczMnFIFt0BrS6pbP9ITJMay3c8PWEuJYYDFoLULlcp5XPO1DSYFsNFHxcOxczD8pNsAMdZ1SaqfZzCthCBLvgeWcmGMW96/JQ8JInK4NklvlVQhZKH3E7rTLT1x9+sDiziP56AVqCKEBMu2YBiPTx+x27egjcv9G97ebwxvPF0zNLS1ClK5f/dDLvfvOG5PyNMjclxTgjkOKsa6FdZSOFrQo+Cl0S04T8Wj0kdgVKzmoKYkkCHv/IqZ5PanKIJQpSMUzqtQbk80BrWtrJty2RYCn8Pm61Dz51By2B8OyJwVW/uza0pe67Ve609bz4cbsjbk1n8/0v13tzdrJUoh1u+/9+Z7MdQAUx6RDU3RmvhdOzmPE1WltEopKYHq54FURchcFB+DttzPTcRJiLG2BaWx3x7zZLMOimQ6fQjozOXY1sabtys//6+Cn/0Mrtd3nOeFiJ5bHSr74Xz6NNivV85DuT6eHKdhdkvJlC9Ja5ICdqbEo14wHy/NkkgmjaMxqUsQo7/k0KCNbD4z5DDQXJ5IYVimryf5zeZGxbIBrUmoKr5lirt1StkoS33GAiC6pR8n0i8iAqU+TO9KpsODJ+FNglrWlDL5SURJ34jkkFFUcjPhmR8yXCAqbpnw41YJLZS20sdBaRtGeiQkJyxEUsNfdWX4oGhHW30ZlkpJk7xoxbwz7AqRgaqQwaGlpSxKcMJLGtHtQOb2BbfEDWtj0ZUY6TkKS2nVsABxai05DE/Ygji5Gaw1T8tHvoYdR1shXPBohGdSu3nm+yB5Cl5ZU05WG0sF62dKkcJRDLwndlifTdlCREqqcON2/YQsG6bOog0taUR3g1aVpd0xRmfst2xESzajmVkE3jsac1jVSn8+vO3pU5M58KluOaDYI1Jk3pMpcSxFGdYZMZJMZoZAbgoqjFagFJSC02F6PdQVDadLYVnuUj5KgiVQZSmXvKbaKRoUqRTSJG/RM0RVK+a5jdq2B879ET+SLJecZ0d1BWMCMjLPRrQh0SglZZaBE2Ggjbat2HnmwGidEWdCJCIlkzYOynKZwazHC6RkKQdOQg32M6lvcjSKtMSnawEG4bCtd9i+o2Rmkd1u+Hnjb/ZHlvs3DF1oS/rjak2qYGkrixRoKxf/HO8nul8ZT+9BhG4H9w8L4sI+QBfjXBa0NPqAp6dH9jO3nufoGdpLRQJETqJMP5LD8AAZyeuwndIK1QfbcLYlr5vEmKG2r/V9LBmemTL296CYn+s5fK/q6zDzWq/1Wn9vRRHiYUGswfDfH777HOxJh11zuNm+v2jo78lQE5RqUz6RGGKzwMNYtpWUoChSCz5GytLCM2xvauU1HBsdkcG6bISkF6Eu61yYbJznI9igrJWHS+UnXxa+/MnGZ5+lzOTYH7CRKenDCjaU4xg8Pp18+81Hjt0ZPdJzgmXDFpm5gQRKyqeKrKANkUTeVklELeIZOKjpQ5GmFFWKlPS1UPCanhUYVAExY8RIs7cWEmYtOQy1NeUz3jMPQxe69WykcQaOaKGWhVJWzvNG+EmrNQP/jtxyjLilmbptuJ34cI6xI+LUZWVdL5hbeo8A1yC6ZYAly9T0Ddz2zLgJmUNEzUHG8yxZ6sw+IellHietLlAa53ElRGhtnaGVk5DmpCla1tziyJRWoRRd0SAxtpJABhfBzKmlsh9PLEunLODeWUoOiz2d5C8ZPSqCe25cunWIwVJzqNL6nGcSMwMmqWUEVGcirwOKUzVQ0hMUk2K3bEkKG/1GLcGyrIByjpEp83YSJEVujAGl5j07bkg4KguVlDudkkCAPg5UF2q50HvHRsIKUiK34HjKyCK9Uu57mtNJaZVHJxi56VxyA+ReKJKAAT+dMMUEdrHEnVuCGEJnTlQIUhcKhdNvUIx1fYf1IwNqydvCrKeMsOUhhIQQVM5+oHRq21jKyrmfiEDvj5gby3qfgaYO3gehg9IatWwMd5ZlS4KhBbfrNaEKWolIMIZP7LrMTdIz8jw8g2xFG1IaYGi5QGm5zbWDEukFU3JxmbuQynOApgF9FMZSqNUZ5qgodBjuaBNKLXR3+uNH9PqJIY03b9+wLhvUlVILZyhSW76HxVnWjfX+Dev9W8Y4OG4fOfzA7eA8DpatsG0Ll1Y5D6PGArJTtHAcjdOVVnJYO84EQBhJQBzuLG2lIIzn93BbGVQ+XW+Y5+ZtvA413696RjE/08v+gFfmJYfi1fj/Wq/1Wv+IiiJQCtY0A3n/vhyrZzR0H99RE79naOjvyVAjhDeGGaP3lJqlVgtNrjE+TopnE4JGmnDrwhgjTdkjJVZ4UIqjVWltg5Ea/UFw93Dh88+UL79c+OEXhfs7OM97jvPC7ea5r4jBbXceH5/4+PGJ/eaYNW63AyWNtlGS/KSx5BRLUOoFJcCN7kYVQaQlTCAG5jkEVYyiia0VGnaeWCS9S4rAeVJUE71rBwjEOAkJtFaUwhg3RJyiCpYNc1vW9BX5DDCdOSLi0CSQOInYc9uDgB+M6HS7ouKs2x2tXNj3SvcrESfLdsdpBhjrck/Rxjh3zvMRl9TyFwEVn3jfM4EFRYiSiFkfN2rdUJ1UNjHMnCI1gwhH4JbmfC3k4FdWYMrQNIc964Z1I4qyaEVGZYwdj05tK6KFbnmtg+B2G8CCBAwLwsckqkGwJH3MB30IXsrcNOTjsRFcr3ma3ZaNtt5h10/sxydCDfee4azlARt5t6LMRPlgqQvuEG4MO1+8JCNkbsD6BGAUkAVBOfsASWDFuO04HWtpiMcsf1bvmcNSV6q2lIC5pRFeFMIpreIxOPcrUTraVpQp94qWj4sp2dMMEsUHR3+kFGVZVkKg95NQcstCAwJVqG3BA/rxyOE9pYlLQwncB+4+wQxPuHXWywU7lH3cGHqjorn50UIpits1c4noLHVF9ZKbGjO83yiL0tobbrcbx3Hgi2DesRjU5Z4qjaVt9HPPoYWU4+iUUfoYmfFUJuGPQKPBMEz6HCoKYsZhe2K1Qxm9s48DCrRWKEtlKxsKeFSKBkEHC2I/eBqPLAq3PWWWywq7ObUU3qxK3w8eP1zZZeVSN968fcf65h1RlHVNalog7PtBWTbaunF3/4bzPDhuV0a857Yf7LfOUY1WC+7B53cFN4ERuN+4b4VlvePTp4oLWDinaOKajekhqhzd815mTCAL4JWI78+X019seWRj8cdsZWZjEUt93cq81mu91n9ZqRAqRF3Sr3eO34+Dj3iRp5Xjd7Y334MDle/FUCMimHUcJaIQks1pkzS+ZjaIc8SR0g1phBSOYbgfmZPiA5lbs6MfxJmY5WVZeXuvvP3M+MlP77m7K7S1IMBtL5nIbYOz79hIr8Pf/Psb799/oLtlg0qSl0I8gyTLkgnuxxXEuSwrWgZ9ZA5HjAFFKGVJr8zWMMvsHNUMBh0W3M4r67omMnfsKA70RNyGJzigpH+jlYkGHpZZOa1gfU9fwLohLBzjzCbNlOGZnaEyOMc1/64PIqAUYZyRxKTRqSqIO8f5CCh1KYhcKGUjhkFoPt79I+M8qVUnm3dk822OljazSZIGhgwEQ0qwbQvjPNFS8rT77Azfk3R1OsMG62WhFM1t1WkTUa2gK/3YGeeBSpmDVWdAfqFLoqpbuYNxoOEs28IRhqA5VPZBWVs2/i4UrVCDvl9TpiVAGDYMG55ZOa0S3jmPKzrOHMpUEW24V+rMQhIkCWwWRARj3FBxSm10T+9Xk5YStn4j7EQ17x19hmDUDVHlPK9ECXz6RkrkYOR2MvqJtkKRwlY2zmOnHzt12xBtaEnvlo9BFKcuuUUhgloWIiyHfzO0LYgZ6/qA25FY5ZKIb1SRFsgAMYdxsC4pXzzHnjIn1RfvhUiG0UptKWV0SS+YkhsjH0gt4JXaHigoY7wnzDJDSWYEro8clN0pZQIkzDhuByo3RApLTaqYqlJqRUXox46bMdBJNjOG77Sy5fZQPGWLZco/Zc1NnwRqs5mXyrCnJIot7+jdOM7rzIBZOfcpXW0ny7aAOcVPbHxE6kY4fLxeudsurM0RnGsXtBZag30IIRfi7Oxxclbjdu7Ihw9I2/jyyx9x//DAMKcoiMMwZ90WPnt4w7Is3D594sM3X/Pxw3tu+41r7/R+8GYTLm2BNeWOdVXKUvjp5XNut5PhJ6N3nrohrVHVEyhxGufYudmgaJshva9bmn/Res6W2Psf9MkwSXW+1X9V+RKv9Vqv9f2pKEJcGlwaclhK037ftvh5e3Omjzy29i+aefX9GGqA+uwx0E5dFkIWvGe4Xi2CUKf/4hnFfKbp+6Uh7agUWqs4yvbwOT/8wVu++FHl3Vtju5yMsbAuzm1fcAMpN87j5PFx4cP7nW+/OTmOzIwRaajec8ZITw4bJsGnESwGrS64JlHqGEaJkijlsJRWudPPoEifAY4FpTHcufXO0lbu7z/DfHD2kxFQ6kBLZe9pGhcJSonMI3Ho48AVSlsJmEb8IE4nNLDe0SKZ4XNG+hPY6WYspVHqRt93bv1GaQ0tjbo0iOA8bXqXlNGD4XAcV4qmh0VlQwM0POU5OLotCDWHgTNT3pfW6H0QMfNOpKVPJDRlafSJE16RqKgY67aiRbMhx2cekWez3S5oqZR6EgIWln6AWhmeVLUxDsI/oiUlWTZ8giUCkLltCJDGuqxICLfzilJy42GWmz5VaIq2lKSFZ3imjcw6aevGUjeE+foeT5N4VvLxh1PmVlFVqWWlkvk9oo7HScSGWQ4t4ZE0NSVJZd45+iOyrJS6oc7UlD2nxBeW0hh2RVXQtU2sMjlkjzSLS+4UiZL5L/uZVL9SU5rkI+l35/E+yWd1RSg0bdgwPDrrmtfFPFHhiGZQbRjX40oGvCYu3IdnFk1t6RnRhXPsOeiyYBGoNLyfBDo9RvmcQoLaNkJLyvYCzNPEbvuR4A0N1m2jtMJ5npg54Z3QgVITHBIAnVIK67LMSNR0i5USSFWCmuGiYYCwru8YfuN2+0i4UNuFPqECSpsQC0Mi5XnDoGPUarg2hleKF0KDdVPwE63w6TiJllLNT3uhaaeKcN4cjx1bKrVUmjt+feTp01e8++wL7u4u3N/fc3e5QFkIhOM4IGC7v6dtG9vDG4jg44dveXp6pPeDY9/BBsu6YCP49HTlbjM+f/PAsQcD2NZl+qKM6wHVU4Z764JLZVghpkzvtf55S7pljsQfkpfB96JheK3Xeq2/vIq1YGv5hw9eIpDbSdn7v9jBy/diqMkT7hPzg1KEEg2fBmzRkh4UMVyMYVearHmKTFB14zRHG1zuVi53K+/evePu/i1v7iuqnduuPN0UpXGrgZbC/f0nzuPX/PKXytdfr+y7pY9nGFom7vl2EDFAB6oLGo2iio8bPTpIecHMVr2k2ZyeUqkRlDZSjjURxRIkNtrJHJFm2VC7ITUok/SFLrgbrWSmR1jH7GBdHjCB0ZMzrrXhIzNerBtFnKUuWBitKeIC/pxGLow9typlSaO3uYMshDjDOzUqJeJl+yBiLO2BcV7p51Ma6UUwjKVWamjim10RCmHGbQxidMpMtQ1pGV6pmdNSly0zSYojNTN5al0Y554Ibs8cFa2KtIJK0DlxHXn67ooKmfmDM6JjNc3ZYPTRybk38jEghFd8DEorjD0T78MHhcA7OAVouI/MJ9l3vFZ0qagstKVynCe348BsBpiyUDSpUemxOF/u1QiwPgDHxo77QV0XypobiIi8v7wrIvnne3+CAotsuZn0k6CgpVLLipaGmXNagKZ0TCgv95eN3IwVZco2G+O84gTuoFoyQHR4+n205mmCN9blHf14zMEuhO5XvBRa3SjrA8qSmVAYqjUHFJnIuOlTUSkZ4lrIjWZNHLV4Et3S+xWZqyPgRPq4dKGQA6yH46REbJw71ByKRTKo8ogj5XghhBR6HyAHJsGyLBSt9OOklAXCc2iKlBOKp9RKlBxCFcw7PhTrhnuBSO+bks9JhmLhLJfMBsrHdaWfg/X+M2gPDO+c45xAEOccC7UpbVHWurCfIN4Z7GgrVNm4TY9WxXi4U24HfP3+kU8fv6GU4P7Nj3j79gcs65LvxJ7vyGEJXbi/v+eLL79k9JNvvv6a999+w7e/+TXe8/VoTbEIbsfBtgitCiOUsMRur2uD+sBDE277kSGwEfRhKaF9rT95/UFpx9+ulqbcV4nZa73Wa/2L1gz1lKXm59fInLi/UxHQB/o73pt/rs+v78dQM9Oyi0jmKtj0EcRJmRkkWpWmd4jp1Mwn7tjcuL/b+OyH7/jyy8a7d3ccR+F2M45TWFbQ4oybUoqw34KPn97z9Lhze1Is1jydPtP/UBeBECQqtXW63RI9O4x1cZQCVRAV9uMTboOiG0LPk2YHN0ebEgzcCn04fTyhpSJiuQnSziKDS32ASJO7eiCq1HLP6FfMguqFEQPROjcEwvBIbf9EFSuDUGPEmihnBloLWgtFLmhZCQss9myutWVzLfkzKE5bNyTIIE/Ax2DYnkQqUaSUDP6rZWaxpNn96D1zMtCUbSnUraKi+fqcR/o5RLHDCdL7gCaKN3rn2K9JsrNJrKoZPS9UxAsxjFJaXvP9YASsIbRWCVHElVI2FMF8TxTxkJRj6Y4ujfWyIpHobin5M5+HEPUMjxQVytqwW8fPg1IqbXnDsT/iNrJxj5iGfEFWoZ870BiS92+TipLUqXHe8uRbZqhhpA8pTBAabakoSoxgHAe1JgzCMErbsqGdEIDSNlxn6OuZgTw+3SjL5Q4tsB+5waltRSQ3LqVoDkkzykVCMe9UrUkbFGO/fp1yt5oDRZFGdBgEGp1hB9Y7Hg7SprwyNy6FYCsbxzhfBtLuOfwUzTBVs8yoyaykFfUVHwN8x3FODyIGtRREF8aYeUFu1FZZlwtKotR3+0CrW/qsBAShuMzPiyQBSi6kOMaR4BE8EdWar0VxWLRQNa+FecGj4N1zu9eMtW14D7A+s48yzHacRj9PzvEeXRYqJaV4RXFvnL0QceJx0lVZa4PIgNencdI0N8+K0twJW6jq9AHnUalx5Zvrr3n/1Xse3rzls7cXLm8/IxTGviNaOc+5CWyNz3/4BW/evePdu894/803fLw+MsbBeevs586bZcWcpCZOL9e2Ndal8rAJa8ntr8vC7XDKa9P8Jyux+I4wlCvJv/8Plwxa9Uv73lKGXuu1Xusvs16kaYCMlptm99//mWaO3M48wJEcitA/HZnxezHUyEz9di9pVNVCyEnowEUpXrAjM2PShL1T6smPf7Lx9t077u7uktK13LhcdsZYWBZh3YJ37wzixq9u8Df/8Yn33+5cryO3CzGgdjyMWjbWbSMUzrPjcZtBkBWRlGWUUjA5U4rjK0XvKXrQmhB2YkPokYGbmcTuBI2lKFspuGW2y1KFUuEczqfxSF0agidiuFSWtXKc4FaxPpIIJo2z74w4UNJ3YDaIsWAS4Ip5oMVY15UiSvgAUcY4GWOw1s8YzCBJVYoowz9gw7LJaivHuWczKYVS83pMrRRNFtCki5195NZCaxrUa+R1ODMY03CGdUSnDK7fZoBoYb28TYmWG8MHrd0ToqgZLpWQAgK9d279xhidVlpisCVodYMIbk8fE4UcI4217Q4Czn5FJfN+gtR7HrcdHx2VlRBBysqyXPK03jsqDkVzw1YaqkrvV8wNPIlaWtqEQThRQKmsy1uO/kQhCXxS0p8Qc3hyTwmchxBmlJJ0P+YQKAjHvnOcVygrtWxIFKwnYW2cO21p2NinjyVR392O9DWpcBzXpPCFYVFT5hVGrY1AaLVgYyeUadLPMNZAaG2bg1Peq0UNiaCuhf3snOdBKS03MK60ckk505YEwvPoeDsRNcxGcjzakvCCFKdlvs44wJV1a2jAUgtnVyI6pTbE9QV2YGf616QuMDeeykDqio+FcdiUrrUcUGMwzKd/xhNfHenzKbXho9Nt0LQhkRte847IMkNcK4c7xI26FJqshOW9o8DCwtPTlTMS1OC1oAgaZOaQKAUINVDHJLOQAqfbwOZnzdkPujr3dUPD+dSdu1KILvj5Eevw9l2hLTD8oPgH3n/9kW/ff2C5v+fd2zu2daEUOPcbjx97UvlqYb27560Ulrt7Rt+5Pl059p1PtxvhnXefvyO8gTgjADNuo+DRUJylFdayUfXVo/FPWh55dnDrSQz6h+hyJcPuvm9Eodd6rdd6rd9XURV7s35Hanz23vztmr+mnyyltK0Sl0YI/6Sfdd+LoeZZRx/hLDXJP8dpEAulbpgNagu2mv6YhzfwxRc/5M3bd3kCSWffO+YbYxgigz5Ojo/CN984X39rfPXNLU3ushGi9JjI3GicpyFy4/6yIR4UzeYxLHG2bb1LgpI6a1np5ySMxUBqsGxvuD7e8MjwyEXuQFOWFuOkFofIE/NVL2CDIYFGISKNu/vxaVoXgu4plaqtZoZGBMMHEZ1WBbfM6lHN5jsohCrhN2KcUCshF/bbjtkNyoJqYben3AJoZtKYS1LXQjiPPYlsAU0VyAa8tgXxmJCBnsGEUljbmpIkM47RWfUeOYEQjM6wgRRNiZYP2rpw6kBKUsokFqxnMypqOCemQinKfv0EUTHypF+KEMMxGfM1O4kxCXmc1Lpwefvj3HadwS43goN62RiHZCo7QkQ+HqmaoYmxELajEoRGZgkNkFbZLm+43T5wnFfUtwysdMfjyI0FlSKZu9O04uPE7cTqQEpDy8pagz6SCCaRWx6tjQwQSUBFCJSlsNW3RATnudOWLUli5iCwXO4Zw+jjmgNfW4hScK+JHJbEQtfLPXYG3fZs9k+jD0syntaZp5PbjWOcVF0R0aTN+U6rFRnObknwC4T1co935xw7bbmjRqEuC6qG26A1YURCKe6WC91yo3Pc5jaxpLxSFbTCdrfRb4+YdaR4Ipr7SXiwlCXvw1ZwS7JbbSv77WSMa6K9WfHTcHGsnEkgNKNHIsejd3z0DL2tsEhQquIjUATv6VOzYUTpKddaKmspMCEHbjlg2bgxxsCiQxQkbkidmVoOrSwc+xWVTIQ6sfTixYKdwaIr/bzR/WAURxXEg/fXoGqllgJPyrE/sTXQuNLljqe98nQLvvw8EL3He+f4+A2/fPwNRVa++OIL3rz7nPtLy5DhoowRyGXjctkYvfPuXYazhhsfvvkmw2T7TpQkwjUJPk7JZ22FNw5NIyWpr/VfXv/QF/zv1vyCp+rrMPNar/Vaf56lkqGeS0FPS/Lw33eQE4GcM/Tzn/gg5/sx1Lgz+k5ZG67B2W8QwbreUQrc3Stf/mTwi58bn3+uBCtw5XL3W5YlUHXMgvP4AV9//Tm/+pXwq18efPvNjd4Hl/WCeFDlDuuJEK4oLoVuBUpmXhxnpxKzmS/U9ZKafBtIdFSFbnCMwO2kNQCld6e0JU3hvePlxvCgIUgrfHz6BAiXyxtAuI3OODJnZ70smJ+olMzkGE74AQwGxnk65krVhsjKfj6BrxMt+8QiCt0ZfqPUgo3Cbd9ZHxba3YXj04FEJFlMA+kV1aS0KUIdgdkJpXB2Y5zGulSkxJR2FZZaGJZG6+Pc8RHc3d1BaTzumYQ+uqGXDLS0ns3zVh8wg3N8SkmeVkLW3ESMPRvFunHtN9DcApy9I3VjiTsIp9tJUQjNEFNE0gSvgvlBSL6O5kbYCZysteKRfivXK2WpdNrMRrlxX96hDtFHbk5EGWNQulGkJaxh/4BHykR8+mCKZAZMaM+h+XREnbrkcEPNLeOwoMRBqeTrOEZuiDyI2KmlJGSgNpa7h8z2EVCvdOuM48ZpAEItC8ftlnKucnmhucWxgwkuDVmd0BvLckddL1g0rHcERfzARkATGEkOc0uoBjHoxxPL/R1lueCWVDBRTSP8YfjTE3VRLtuKqBC2Y/1EUc5xvBDhjqcru+yU0ljrhlbn6fEDsdQX+WHTxnn9xLHfUtJYBRvBcTgeQCQuOtQICoyaeTlmjA51EUKMsmaYaSi0kqQ/BgyEtS20KnNTprmV88ZCZjhFFMRgDAfprGtFIIdWIKQwInOfFt3QZgw/MPJ9WFwThrHvPF0/UWPBAlwFEyCcta1o6QwfjCEcbohUWlFCK+iaBzlHcAqYKxSlrG/4eBuIBJfaUBcsnhgujCGsS6H7ya9++R/49tNHvvzJX/Hu3Wds24IP4/Sg98GYMAXz4P7+wk9/9gseHz/x+PE9v/yb/8B+dGJZWGtl2JXhjl9zqMnN4mv9Z9UcZP7gl/nvVi3feWVeJWav9Vqv9a+hnocbQEb9+zNvnsscuR6U2z/N4c73YqgRgdaWlNvYDRXhfm38+MeP/A/+R87Pfg4Pbzq1ZrhmxDKT0ftLAOfoCx8/fsN/9/8J/t2/hf0wPK60ZZ1BnoGWbLrdd9q2UBCKdWotmeC9n9kMrytLy81K9MwM6P1kjEbVBfUTLcHStsxYOTu1XaAYhx24n3m6bUlxWusDYGhMQ35dMXY0NLdCwxDPoSOsc+wntQmg1KKIOmVV9tsnoneUCpmTiOjKsjWqXWdIpKA182vstEyBlxPxDlZzWxCNGplq3uWW26Z1Y99vdDsQ4K4+IEUY+wEuDAeL3MyIgEWnDwFpuBgmB0iDAOsFD7gxaOsdpdyxFEXm87eRJ++lNNQqNdvvzPBp4CeE5CC5tIbUCyGdcQQhA8PYLvesco/5zBc6b3MASbM74fT+SK1LDrD7zmURWl1YIgg7cHNqbXQ7cysSyVVgOFoc84r4Ar1jISxLA048FEFhFURq0q2D9F65pbysbDgrcFAr1LpBCPv1A66Zp1LKgp17eo/spEbm21DXmaOTpK5xGuhBW+4okqjgiJF+JTFKucNsoXdHdUc1/UYmQdOMW9SiiZgG2nqhSODHEyGOjQypjSC3aJLPWWIQLhMEodgxc5MkwCuL3iMove8Jl/DAccZ+UNRZ7hYshVo5SPiZGGdNKd+wg1qUyyLcjgPhU4bqomi7Z8RgDMtw3VpSzmczdFVBxo6fB7WsOcRoZy1rblhsEL0xfLDVlbVd8OOKy6AujeVy4Tg6Z+/ECLwob+5+SNx2qgQWg+4nhOI4ssBS7rndHolrzBDRwItlgKtXxmloq4zzCa3Btq7UTYmD/Fm+ESMw+0DIHcRBWYJyubALtJ5hu67K5a5yO40+Ctd+sm6Vh1q4U2UMeP/Nt3z45pGHu5Uf/fgH/PDHP+Vy/4a7bcsQV004h2TQF/dvHvjixz/my5/9nN/86td89dVvuH74wBgB/UQXiMjDgNf6x5V0S+P/H7OVgaQCrY1o+rqVea3Xeq1/tRVVibr8pyHCw/6eP5zbG04y+2Zt6d35R9LTvh9DzczJaIvw0586P/1Z8MUXJ1/+5JF1M6Dk/2QnBXg7qYsP9tvCr/7mLf/23yz8x7829usNEGrTTAoPydNv3ykorTakbCyXe2KkxMVtcPogqrCub1m0MfaD7qmhlxhJVRJjuSQZzKNgFoSXTGrvjofN5/EGwhj9CZGcOPtonGdubnyc6X9hcJqyrZf0pohzvX7CJAiFRYW1TMrVSJNpnVSqEZ7m+NDM2AjwM5PcayuEd4YIsa4UN7o5EvFCfTKMVgpta9w+HiAnRSvbdiF0Ibzkc/AFV0XrApa+mCoCkaf6l7s7EOf2tBMuqOgLvnjYII4b6+UCAbf9hkdBooI+YHHiWhFOUCNE2JY7ul0xjsy98UA1/Ui1BD36RGafVCkc+y2pTVFAHKnOtm5J9/I0uSsF8Z1lXSkM+v412moOvD5ACrXepWypXDg9tzaEIx7sR4aW4k9ocXBHFs0Gxg2GUOuF43olilMKKEGRYFnfcZ6PnLfH9NRs91hcU/JVV2KcaXonA2VFFgwHm8a7RZFaKVoAn+GZStSgLhtbfYOPwTHSxxU+OK3TlgX3k2W9J0K47U9ILSxtobUNiUEpb1gQHm+P3D58y7qsXNZ3SWI7nVCnLOnd2j/caJoDnEsaBVULEgWRlaVO/PqyUda3nLdvEowRsB8nqvdIUUwXrucn1kXAMryz6T13dw+YHziC+UBlRzVYl41w4TwMO8CjoFVSGre+ATs4zoGNTmuJSh5DGcNgu0ej4MB1/whtwYZTKLklXZXjWFCpHOdHdj4i0QgKrtDqHd0a6GPKHmVwqYpEgGZoZ21LHqqcBxLjJSdITbheT2pJ6AUWHH2wygVc6CpAZRi0GmjMk/phIMGnsxITuGCsnEfnya/AgbQLGs65X/n66hy39/z6V3/N3f0dv/jFf8OPfvIzalvztEjmpst8Is8L9/cP/Py/+ivef/Mt337zFR+/fc+np4/4sAzmfa1/sMQigTW3/vvpP3/nL0wN+fckoO61Xuu1XuufrX5HmvYSLPyHttlzeyMArSZcQOSPggt8L4YaVeHn//UD/9P/ifFX/9V7ttUyHdwL57Fxvb5hv63cP9wopaPlPR8/Vv77/+8D/+7/t7LfVvbTuB0GYbQ6T1e90eqKu73kcCx1SVrXyKBCt0SxRqRZPrqzj095Gq1KlYU+Buvlju3ygDGws2ewoB1UKUR0gooUUE0PkBTQuiDesFOodUUqnOMpSW8WeL9xWqByY7t/i1vQjw6iFG24B4bR948IbwiPF+pR+nUGx/mEtEZplaVeOPuNpyPpZ225wPUjeFDalhsRNeqmifcNYfTEKJud1LvPU8I1MkTRYAZq7ogJaytYXREvuK9pZh/O8B2AKCvr3U8I+YAcX2MilEUJd85zB1JGZybpF4qCU/BuEJFhnNZS5tMqrd5xe3rkeHyPeoZs1u0uvS2nsGMMS5xwVcE9aLJR2OjPbxYR+nFQtHC/fcZ+vWFacRrj3HFNIph4odV3lHLPfn6g9yulBlGM5WFDozLipGijlQWzThFl3d5y7o+c4yCKIyK4BWf/wFje8HB3l+hvT5Sy2pVWv4MOmAjn2HPLpJ2ytAza1DqzdjbMTobtLMtKrWsisiWb6+dsJG1pwj+HchxOv54sNT1bEZHyxViQyJ+/tgUzBy2sdYPe8WHsPBHjzH9bhDJlMV4NygICdamUthA26MeNMwatSN4rKoxx4KJYVxBDNKjFiSFs21tagNFhbqr28yNelLZU6nrPKhfOp5Pz/MRoj2yXd3iZkrpQOjvFwaXSli3zj3znlAxsrds9NeB0KHVJ6MNxo5SNJi1DeiXQVliX3N6iF9yCCIcCHRA6DcvthRQEY71cuB5XStMcOEwIKr0fjNGJotzdv6HWCzLgPB4ZdmXd3iDiOTgk052Bs7aKysZxBtf+xEqj1MqYn/fqgyqF0+CrpxsajsonSivcLStbc0rdGCZcP33kP/yb/xd//e//LV98+XN++KMf8fbdO8IztUckUem9G1WFzz7/jC9+/GPMnN9+9Vt+8ze/AnmVQf2h+kehmOFlK0ORV4nZa73Wa/1llwqhQjwsyKhgkTTIv297A78XDf2H6nsx1Kxr5YefveHsT/Re6OeFTx+Fb98/QDzQz4aWK5e7wqePN779+hd89ZXz6dPIsMECdgb6THaipY+kvkFbpcqNGks2o/2GR+JiIxK1KzWNyYbAMFQCrZW23GNnR1vDI+jHQaC4LCmZqw2ZxtohUFjox43QQY2Wie6mmB8oPY3KfqLcIcVwzzyeah27PbKfNzx2yrKyti/Yr9/S+xXqhaU6TRq6rgwpnPsj4wykCHdVKWGUsjKsssUAF6o1yvYjIp64XT/SZaWUYO1gY0Ao47jR1CmLU4tTJfG2x3ml1JXl4Z6+Z+O9oiiVo9/AlHM/cDnQ6rx5eJfJ9fsjfruBXNi2C+ftPbfjCTy4vLlHGzTdUF24nTeqn9SS0AGTAykFkYrtA+QR269IcYxO2x5AjfP4SGtvKMvGVgrj8AzIDAecYTe6nNRaqHVj+MC98/TpE6c5lMJSF8ZphI2EKxQoRTnHR1SdtlzSLM5JoWajbuD7SZQcmrU2zHqCGebg7AEjClIu9DH49OkbluWC1pUogpSCxSCsE+R2Y1lXWnuLW6ctG9tySZlaVGpVuheClDcNnii1UooiZG6QlIZ64/r0hFblUhdO7xAL4wRzw8OpCsuS+TQ2clunc2N42RrnSD+UakVah6qc5viZcqa6VCob5/EpQQ21EO6IKacY6/qA+cDGTqkrrIW+fyJIuV1IShn9uBGtMvxkqQJNoTSkvqHvT3QXRj8StkHjtl/RdoeuSrXB7ldMG9UcOwdtu+d+/THH/omxOxSjtcoSmlufKR2MGMj6QNSFMW6M48ROw6WzbCuLbvTre+zcaetCEGi9IBj4SOxygNQ7QhZOPwCjsExEeCMMjk+PjOWRy/aOu+2e4zo49iOzriSRz+N8IlB6nNRS2GrDZCWGcZw3mm+00rAYDB8TtLByHHvKDl2JqmyyMEYHN6QJj9crst/49qtv+O8CfvSTn/L2x7/g8x/8kPv7u0RpIoQbx74TCJ999o63bx/4+c9+xsObN/+SXwXf6xJz9MP1j/iDkojvtRHrK03utV7rtV7rb1dUhQq2FuSwHG7+UADxMxr6ds6cyt9f34uhRtX50Zc7b988cuyVX/36Hb/+teRpdTg2rnx6/MBXX52ct54SrHWllBUx6PtI07gGS1WW5qi2lGBg9PMJlQyVdC3YeaKyTOBsyn6UC/120gVaLRRXrB+I1gwD7Z1TBmVJP0LTSj92oFO3JQeYmI21FcyFHo5Lpywph3NdWJY7iudGRuQB0UGRhT7g6IkBxqFfv0ajE1IQGwx3Sm20EM7zkThOmgpt0fRMSCM4qc2hbJgXht0opeB+QhHqZaVEKvh63wlPMhRecIJF84r0dmHc3lNmI1hr5CByFG7HJ052RA6WrbG++YLwE3HlPD9lIKZmOOK+f0u44AIene4Hq5UcYDQ3PkRgAucIqgfoDRGhj04MpW4bdQH3M/NxgFgW2CqFyvXpA2GZo6MUzoDalELCCHxEkudcuB4HXRKxqkiS7pw8AaiSeN4Z+Ho8fUx50XKXMisXVBrX2xNbLXkt68rt+ITiWD+o7YLKwqIrghFyUKvS1gVtwjiEuq6Mntk23k9UKsUaNg5chMKZIZoS3G6fcO7RekkcuMPRO2Xs1NrQFypd5bZfiTi4f/uOAgmyWDeWes/+eHIcO7FkEKdHSp/cJ1ZahVDw4yllkfWCksNnH1CWFYuB784xCXoSQa2aOGZdieMxje3oJLMZMR4Bo6oiEtRl5RwHt7FTygMeK6cJl/sNc6OVFbcBZrgIXurcrgT7nn4ck0DnVqvjVCuc+wdKa6gby9o49xshA1SQCNpyT90+m9fzRtOCY0QpUI1xOvu5s20FWqXKwwQXBGEnI05CoK33NK15IDCeMuepJJ79cteoR4eonOTW5np+5M39j2n39/jxkVKCcZwpk1wgIqMur0/fQlWWslIczHe8G8EbSlT28xGLyGBXLGWyZeUYleMpGH4FBpd1owIWg1pWvJ/IV7/ml1//mro98POf/Jz/8f/wv+Hucoe0ipYLTkE9M5q2taLldZvw99Y/ZDcSIdaKb5nf8Coxe63Xeq3X+ocr1oI1Tfz90ZHjHwCt/IHf+l4MNdt28rOf/htqc4LKug3W5S1//R9X/vqXV779eNL7QBwWXZBWs8mXAG6UGizrgtmgH1d6h2VdWZYHAmWMPBFvFmzrhpbK6B0HUDivjxAVtwyh3JYtsyDOE+8JI1iWhR5O9wOJE5/0NNELag1cEgtcWpqrKSgHVTN/5thPllJQzUT6WAoqDRudWx+4Hyx1I3Tq6NUp+sAWitnAGCDBGLc8laVTBGq0lDzRCUslTWlpED72G8cYGJ7fr3YwiIQH1IIb2NixcFpUDjkY1ilSeLNtE6V8w8eB9DUJaKvSyspaL6whmJ2cI83z7oGHJQFsHPR+si6V7W5BzoXzPDiIRCF7UKVg/UYvjlVlvVTuHh44Pn1N1cpQOM4b127UZaN6ys3wilrJQEQtlCosOPtuhFZanKlbF6V6w2uGLLZW0Bhzy2FJtKIidlLCGbETUljLAyHvMe9c2l1eOw/cjCo2fR8HLRoNn9aFllsLNdZFGMeeWGap9P0pAytDiTPzfno3zusjWhdGJzcVrVBkRaLRyoXLmrCKKplyX2q+1uGVphciRjbnkhugIndEuaN7z/swJipbOiwLSjD6YFk3xti5PX5g1I22rUnfqgtK5RwH65Zhpk0HdgbDH4nS2O3g9M62vWEd6TlaN+U8gn79wFBjWe9RCXY7yZkxAQitbIBhMbgsGaAZLnAbNOlE+ZYRziBlcW2p8+RGKW2juzGCzB7SO7a6YMcV6ASFslxQaUkG1EJd7ol+crs+UsuN4cayLYh8YmklD0i00u4a+3FLOSKBeM2NUwyaD9yNDhzjE5eyEiOSZFdyQC61EaWjzcCF5jk0MgZn/5jvFS2Ml0wkTWlfCda20E84zoGuAxVFTTDbOQVaeYBnxHVOUbAo5e6eKoX9+sjomR117Bm+OgjaorxpytPpaBjXT7/m+uEbfvPX/z1/9fOf8fbzH7G9+QF3m1IYeHeuhxOvSOd/fLWaevE/YaDca73Wa73Wv+rSDOmIuwVZG7ij+/jjPIu/U9+LoUZksGwnva/85tcbv/4b49/9u2/4+LRx9EYJQ4uhFVTSpzL6I15OqgqiNaU/5xUtWwZiyML/n71/ebF13dY9oV9r7+W79B4RY8x12+ciSYL/gWDFiljURCuKooiFhKwKIkrWLGjBUqYgCAlZUCsJWtE/QBIUrJhYTAQzOeLZl7X2mnOMiOi9f997a83CG3ubgmefvTlnnz1Xnngqc8QYMWLGiOjR+9ve9jy/5zjLDC/HiFmk14NKAAYmg5h3uhnYQl532uNgtMERG9FW6qOjAVJSXGb/hbCQQkY1YkNgGGaVPgYxJ9qYTfW9NUw+oAKtoV1perDmlRwzcVs4zhlA35ZAbYExhARgA40LOX/FywNV6D7tLa0dM0ORPzIXOD46JtBKRzBS2oG/aFJPRObWCQPxQRsHEmd4P4bMGlZGKfRecZ0UsDFg9AchreR05TwLZoM1ZWLcqMf77DMZs00dZoYo2YoPoXOQJBC6QS8gMzOxr18ZNui9zayQCJFK2i8seaG+vVFuD9J6nUWK5h9FqXC2k4VIQLl9e0VygCxYGxRzUk4fPSwB98G67PgwBGGLz5g0Ru24J1oQYn4iCgQuqBjDTlo1znJgokw4RSfny9wu2UFKjiRFhoDMLUQb52yql4gwsPY2ARNErHXGOBENDINaywwYi5DySojQRkdVsDoHBrqQQwad0IPWCmZGl5lxCjoIOrCP0towOiE5iiH2joeM6kJvN0Z/Q5bEGi6EY+aXGnWistOCaKaclbQsaNgQXbCWP8opK6CzE6YZITn7885iMBA0ZMr9DQ2BaoNCJy5XRlVEnRQ3artjBmKGeEHNuaiQeqPZHRPn0efnYh44agEiiuCPO2vIhJFIeeN6WYkSuT0OlrQTdfDuYCMQ3RBp+LKj5UofFSxio9LbHEzisjN8oGPQemPYoPU7koSQMuYd1UDgw1YXJs0vRiWJ0nqntYabEUjkdJm9Ra1OApxEhtdJnQuJFDd6GZRaCB7QCDEvjNYJA6p1LGWipo8+p0YfdVoKDYI7ww5iXshxY/ST3gde4Bw3fN0/6GYVXPBqeAxAp2G8dQGvRIEkwnk2bm8/8uO336Mp8+Xrb/ij3/xDfv3Lr7w8X9hSROTzUP7XUtC/bMf+m9J5PvWpT33qU/9keRAIgZEC0tMkTP41c4w/i6FmDOX/8R9e+Y//o8Cf/kngOBoigsY6G85lEELGTfDu9H7H+UDDsoDqRPJqRmJC40oMGfoDBYSFs7xOapaMaWMaRu+VoIFl21EiosZIiaEJLychKpoDbZyoJZJuBNNZstg7kCAq3SvLdafb7MAJkmFA/Aghh7B8kIzG7D5hwMgEz8R4gPW5UbKTFJe5Q2idVm8Mq6DQ64HHjsZBiM6yJGwMjl7/ssTRxvgoxRxEhZAymlaQATFhZ0VECXFjWa7YKB+5kU71B1Rnvz59WMY6QTNqSjmcOhIxDGwAEjlLp1XHw+wGYZRJdRuz6T2Ksl6u1CoQIr38iNeT019BhTEGAwg6w+x2TiR1vb2RlidGCICQNJNtYJqJQcCMo01CHEPY/AoEjIr5QFXngVsT23blKO+M1mj1ALf5fVinlSyMgvUHI8ZJIhsKIxDy5aNo8+Rx3jEbaIjk7ZlhdRaYumCj063Mx1S6ku2FPt5o/oAYURTrDfWAhh1PwhiNXh+oN7brV3R0Rr1zHO/ky04KER+d4g/MGn4apZw0g7gEoijWO6RAPzvb/ozHwf1RWPY58NwfJ2c3NA5EnD3MWw9zY4xGbScEgSHoEli2FRTax/fQJU2rZIpEm/Yky0KtjWBlFrK643Yi2nFtbE9XpNxJMTB8UNoHwIFA7w/i8gTWCDItVIPGkEHrTlh2lmXDGAiG+AR2oE8IHZNG7SfRBNM5iEeHJJksHU8dFcNaYZw3Rj9o1lAM9YyNBZPOOAsiQg/TxpaWjehK90a3Bua4GEvMxCgMwnzsWiPmlTQix/cfcR0szy8kCZhBbYU2HNEOLiigSQhpFp0+bjeGB/J6RekT+W7GMOPhjW29QBqMNotKY97n4ykq5kKrQhsV+sHwguhHduv+RowJs0EPYG6ItdlppBlDYECLMJF8AR+Fe62oFW5//Fv+7E9febmu/Kv/yt/nV7/+Jf6JdP4nS/jLsKot8dNe9qlPfepTf8uaWGhFcvz/Qlr+iqfen8VQ8/6W+L/8n79yL9C9klIkqcybZwfROLMAZjgDzYEQL4jL7MXoN8SE3jqRTkyZUd7opeIeGNaATowZUGSkiV6VQsh5HmYRUtrJ646NB6NXlu2KhJV2KuCkmGnWMAuobrNzIwjP6YqEyKM+CGbYWRAbqBohKTkpJjoPHfJxEB6N1k+iO2EI7h0NFRcBD9hoVG9ImK30DnOLMhqRQEqCOKz5QikPhsvM2Hiklk73G6R9ggfU8DYHlbitiCtnuc/SzDq3CCJCSisaAjFFHvc6sxq1TGtPmrfMpUOpd1wzsspfbpEWCeRlpZbOMGO0ShkO8Upk0FFOE1BlTQnrr4BRzQm6seSVXgshJ4jOGNOmk+OG9RP1SPDAsE4ICzkqo33HasFGR8UJeWO9bPQ2SWjH+eA8Z3aou4DCkhb2/Yl+3GnjjpkB60QpSyWnhXq8Y6pIghCv9P6YPTqSKGcBdTRE3EH8CdHKsEYd3zFxOok1bgSU5bLQ+0lOcW6A7EH42DjaR4jdxgyfx7RNhHUKmDlRImG5Ejq0/kB7RVXpdVBuB2MYh7+zvryw719xn1mSJWWCZYoMqndCU1KA6jckCkETqpnROq4TMWuj05vR+4EHJYyMDaV5Y4wZuO8dRpe/BF5IDgQW6r0goRBCQKwQxZFlR2RFEwQ7cXfyun/87BXSElASoc3HNm0g3riG+W83MVyMs1dsOEGd7nNztyxKHye1zqwLKoQAVipiiaBg9WQEIDialeGGxjDLPuuEHAxvRJsZIPnI6oQPLLYjWCsT+x5WRjHc3pHoiAnn+U6LASRirBh9UutcCYBUw8KYRLc0bXrC4Cw3HAjrxnV5YmarjmkfjQnv8/PMCFYKzQc2HEKeWySLDB8Ysy8ohbnFpE6AhM6wDtEazqT3iUR6MxRotYErKV/AItUqj9t3fvdnv+dyCdxvt3/hz/9/KHIVxsv2d/1pfOpTn/rUv3TyIPiWYEszXvBP0M9iqOkdjmNmDpa84qMxRofgs3gy7rTqGILmgFuntTJL+kKCEfAxiDGQ8zLJZyqT3tQa7gUfg+6dtCrNJwBACeAbvSlGBAXOO8Igpg3XRC/vuDUMoVtDNLHtP9DLg6CG1ZOzz8B0NyemnWZ3Ygysl98QifT2imnFxUhBGDIHlpAE88C9HBNysF2ozBtXcwc3AgpByMsCAtYc9Ux5v7GtgZBWnECrH8WKT18I3hj1wK3S3TissBBYt52cn+ljhrC8NYAJDEiBJQlqg3YUsi4QErU0ghb265UlXnncH3RTSBeG3xEqbThLvqLW2JdAd+X2XrEgZDVKeaOFyLY8oyLYOFiersjpUB5sqqwRZIm4C++3G6JpkqLqnVGddAm0xzviQkwLQ9q0VW0bx/3GMKPWzmob3iKileN8JWBze2MTq604t++/w3ywXBfEHKeR8xOmCqfR+skQnfSp0XEbjD44zhsPCmFd8RBREUIIDPOZR8kJhpGGUcp9fm09gBuDc2KAyZg3NC2EmKnv76jOvqAUPg7rpREls+Qn6uNGzokk+7Qn9TtBr7RwQjT66BNAEBZKrahBkEaMiZg2ip2U2xumAYkXxhioTI9qyhkP8Lg/JoJ8uWC9EGXavEY/6aMhElgvFzYR1IUgwv1WqecDhjCqIRuEnGjd8GaExRmt0fsVDQs2HlS7sawvcyvUDyAyDHp/YA5Pz38fsU5rd3KOjF7R0JCgqOy4tw8L1xM5/5J6+5Gzv0EwJAbEFt5aYRFhhMT9vKFaCfmCyZUhA6iYZcIAQ2hmRM3YqMRwxdqDnAwPynCllpmrW9cn0EzYElkCt/KG9cYWM0kDeUkz72NC8Ii1Qr2f2JIJ6iRVhANN+mGPVYadiA4kOnSnmxDChV4d1TumRo4bKURsNIbB+IBeRBZaK5zlZFkuZGfa6DQwquHWMZ85shSM2ju1VZoVcn4iiFLGbYImgNYd2oX6N/Qv/0ulT2vepz71qU/93euveC7+WQw17g5e2bcV1Gg+Js2rFzoDt1lEGHXaUkQmUcutznxCULoNsESrkRCdMC9RyXGhV8VGI6eFoJGzPIh53gj3UhnnQNQgGHGd3Ta1daw/UCI+YPhJFCGmgHgl5kCSC72t9HEiMbGnbfa95Mskt9VO8UZxn1uaMbcaQ2ffTG8NfODLTlw2xALe7iRdEIm0cUDprMvKkldEA9UfjDI3Ax0BN7oHrDeWdWNZA7V12jkm/UlkdpqIId4o5UdKL6RlZVt22plp/UQFrAdMA49yEvL0iQ/x+XfPwQg/TUBBUFqvaDhJeSENwbzQR2Hff4UaxHtCdaHWgi8LKQSk3lBNIM55HohkUk4MAm9HxeTDmhciy7rjVii1zc4Zm8WW1menTlcD72SLVDrr/pVQ4P42A/pL7qzRGS4gmet2QbyTdeW1NCQpIa+Ms1Lf78gxaKPgEkk5EXxSqHQ8wBPDBtUGI0aCyNzUtJOhDawhplg1hnU8RsRmUF8YiASO0ok6C/tEVpSFFDfu9TvmiT0IVo/ZQ6QTuxx1o4+Tzo19+UorJ/dRaFZwaWz7M0n56DL6jimEfMV6p3vBTxihQ1QGgxiMHPMsGZV5QLZ6MM6DkOYt/yIJ6XP76TrI+4aPQW23D3R0wGrA2Ik5QigkE/pxYtU++piEWs45QMVMa5WokfYoHLd/TMwBDRMeoCwoE+NYHu9saQdzSruT8sp1+QGXSDcITHxzOx/U4/skoNRArZ0jzeeFYTozaRLQ5QujzAsNUYGYiHkl08CNrC80e8POad+ULOCJ2gdeGnU0JDpryoQUGHXileOmrCkyBtAa53hHlImB10hpdwZ9Zp7SDjbpdY6j6QPGUA6KGd3uhKSsuhDHIAXm4110Fnd6p8v8HocgBAIqEZWFgFPLSbm9QowsOX90GlU0JAbOqGVudeLCsFlsevrA/AGpM0bDUUQTZz3+SuDMpz71qU996lM/Z/08hhoAGTgJJSNu1PIAB40BZ3wclA6CQt4viAe8pxkCxlAW5C9y5aPS7IGNhsRE2i7kdKHXRjkKIa44Ct5n2HuXub1QB82UckclkmLAXTFmq/2wStKDGHZGM3o/SSmT04YN4fb2e3wYpIWUhCAnEhekda75ifa403thWZbZj2JCyIn1+mV2T0ifmFk32nhw9DeWmAlppZZjQgcYWHTGcEpzmg0YCuq4NqxUrHR8wBKXiWhGqL1RRmVZNpa0c5x3LDijNnJcyGHBgdJOyhjsYgRLbGHDLFNKIy6Q45U6HshwUvrCEiLDz2mJ6R+Zp7PTTidisxQyJWwY5+jz39LuhJiIYcWjctTG6IbYRkiVZVt4HG/0UlDdZ3bouBO8M8wZPnHOGjNenVUXlubgC00OCI1moGRCjGDGOB8MOxl6knJmXSYc4TgftGG4rvRxYKFNGMF1JQ9nyYHjMdHM8SkRxkkMgdhnJkJwRAPeCvdWJkluyXgTep+llykqUTPIBDlApjxO+nkS4stHQSy08iOdebAM4crDfvrol7lytIPiByaBFCNBNyBRe8cxkMDcPTg5bKCDR33DTBg5sZjgo3GW2ZGj8STEC0t6QVbFGNTymMM0D0KOIGnau0SwkAiyMVrlLAeExPJRROieoMLohZpOtu2KpshogoQ8v9e6UNp3GnOQXySiDKCgWdA+e0BGbtPm0wwbD3SLpEUJXWjlZNDJYeV2+wmrHTel9gMn8+X5K2qVdp4IEQ0rdcxiV+9GL+/ItrNuK6W9EVMj5Y3j/kptnW+3H9niwmV7oZUT8Ubz2YWV7UHtZZb1jkYIRtCEOJglQHDPDFPsA6DR+5hbzrRzf7wyxIgxs0QniHNZFo76AS2IAAmpMBwIgRR3FHjcXxFdSMsFodPaAakhwYhBYQxGB2+w5B2TSepz9zlk90jQhmomqlPah6VvQIyZkCP1PDnqOb4nhw4AALQvSURBVOmFn/rUpz71qU/9AepnMdSIQMo7NoxWp61Dw0qIAfeTdV0xi5TuuEApg6ArYyjdZgmhysCxeZtuB5GKKqQlsmxfZjC3D5orYzh2npidPF83lvXK2dMsfhx92lySIBH6eZs0IgYaBJXM7fVGayealD0ovXbOWjAfmA7GaOTlaYaNrRAwvHWsD5YQEVF6EAiJGCPl8TqDvSJUKwRJWBJ+cfkNUZ1uJ90Omjc0ZFyEMmCYsYR5SI0BWldu58m6LmzxBRHnPO64ZXo/JwWuGMc5O32cmfspNhjudNpsbW+DcVSWp43z/uDs72zXZ0QXzvtB7SdBLjxuD0pxQp7N8cMG79+/YybovpOXKzbeqI+Jy5UgjCbzANYbHk/cAgxjC/mjNShA76gpozRkOdnyDxNjLUrOGeIC40HWweiKt07LHZFODAaWONs7IUToFbEGGlBdmfsto5dKrQ9GNNLTExqv+K0i1uli+DAW4vz84oKUPjG+xux1scawaYEUVsycMjr7/sS2XznfX3EbuAm9DYwH67IQEGp7xbqjy0pen+jlTrFOG0KIaVqvmjGG4UAvjlFYtwuqHW+GdyOoUMug9oOwQl4vtKNQ+n1mX8JCTleaV2BMNHkM1Dp/vlQU1TvkTg5Xyu1Gbx2JCy4QVWerrMeJaD7foUKMgqeFpkqwJxIBz8KdG9UVP++s+5W0ZGLYUXN6bQxmVSXDGe8nW56DXkgXYKBmtONOSBGLs4Dzcb6y2pWggdYLt/s7IS5IiMRtZbRK0Eh1p7cDGccEUIgABeKEQrRHQ4EwOs1vSFKKPYjMnztSQkwpA1YXQswk2QgeOcbBkIIzNzW1N1JM5JDgw+Y1RiAEJa2JPS2sbfA479Rbx+MdPOK9cbYbtmaWoKhDt0axjnqeAI1ScB/ElKnnMfN3NLIu9LPMfKANHscNloCmgGgkmeG9crQT04iJEkQQV+hKHQdwIENQq2hifm+5gjthOEuahbOf+tSnPvWpT/0h6mcx1OA+ez080r0jAaLOxvNhg9gbqsxiRIu4OBIjSSZhSaTjOoPMjMq2RqIkXAMx7tjjwF0Yo0wPuzesF3JSkiZG67MHolQQx3QGs4MFcr7OvML5Sj3bLNwMCdF5iDFXzjqQEFnXRGuFMAa9V1RXXCHESHncCQEIwjkKQRNug0dv0yfnj2nHkY7HgAKlPejBUZ39OqFF+CgQDWtmSRv1fGCUeTMdM2mNrOuVfnbe3/+EPkCjE1OkHDeqC66N6/5CcGOEQAwLa1rptTLqySk3NAkpRYo466qEMMP7no20LoSg1LNjFgk94LERQ+I4D1ifkBhprSKqbE8/UO8/zhb3eps35wlSjmhfaHZD7IC8zwFiHGwx4csCRLzeiGlnoLRxoBQkdFw+LF7ScebXqJaGYB+H8G+IC0qcQ4sNRAfgPEToEojxirpDfycEn6TWKESJ1KORFsPdOO6vM4i9zuyVpsQqv5xt8z5BE+ggCmSJ7D/8muP+ylFmFsJxYo5INdbrlXK706wiPBixgjkpXonJGeMdJxL3r9y//Tk+DO0FHULYMyZGWq5E2fBRUL0QYsL8hqmQ141VrzweByIBLCAMckrEsEw89TgZQ5ARyEtA3WnmmN1hRFSfOY8HKTshZXo3Usrz56M/yPEvHreDQJubG7sirRA1QZ+WT493JC1oVp6vX3ncvmNp/nzUXlFxcjnZri+c93faecxtbYigjeFGHwNXxZOitjCa4aPR89x4pBS4bF/o5xu9zd4gC/3DEqa4QlzjHBysEFOgNKOOWb5q1RhB6WYozvv9hrpPwpsMEEU1sCyJnEBtwlfEDUuZMUDM6ePOWSIpRbb1GafzGAXvzmBS81orDHW6zo6jRPzoH1JCDCzpQj8LvVRMnZBmfkbUUDFaOeYWZ8mEJaOaJsq5dkwGpdRpP8TQ/Zm4XrFaETMIkZwinBWRDmtEY4UBOa/zue3TfvapT33qU5/6A9XPYqgxhHNERIUUjHXdCWGllAM3o5/zMBpklhsGXQg+7R1CJ8SAyoWAIeEkxYipzq6V46SPkxEDIStbesZqIQchxki3wfA2b9+lT8pVzIhE3GZovI86b81lvo/g5JRRgdEeeDswD4SUwWx+frpgQxGbwxgJGpE6FG8NGwcjBFyVGBUfHyjYoIj3eYBOkRDmbauVE9pJjAvpcqWWB1ln2zv7Tu0F1U4vndf7g9E7pZ+zT8EN0UiIC9EixuA8GjXDuqxkcY7v32nHQJLNz7UPXn/6EbwTdcFqR9KgMwiaCRpJY+foBfYEfaCtonHhcvmB89Ho50/ELbPGTIsTb6uu8+sdIOJUv9P8Dpqmda8e5CBYGGh0HCbClsQYAzRidhBDptdADBP3Z73jvRPTSkpPhPbO4/YjBsiSKEMmXW3i9DAx1n0npUhGqPWOaMbtMYefMXA/GT0Sg1JyR3Nk36/gA007/Ryct1fykknLSnfDTAnHSfMxs19WEM0ImX40Qj3Iyw/I+kRwR+LGAHwcBObhWXWh10ZvA3QjyKDWAc2I5Z2cV3QRyvkjMSmJiGrC0lcQIdNJPujnfW4+dXDNF1prtFogfDxWdQ7lMVyox41mHXNHaNAbole6HaDCtn6ZFkCM8TG42GikfZsZstIZzchhJwZQiZwqmCv1cWekj14eGVhv5KTkD/y6qDLaMXNdDMQNiKinuYGg4DkS40Zvd4odJE3Y8aAnmTmf8W1i4CWw5IyL0wKUUoiuLHLBdVLwbAh9zALe6g0V8PKYK2MN0I3uH4W1okjMOJkkissgBDgfd4ZBSAkU9vXKaIVhHXGn9RttHKScafX8KM500rJDCLgEahtIG3MDqI2SHmzbigbFK5T7iWtEF0jBOI8b5p24beiI0BRinzk9gdGEzgVNiUzDS8M+Wpp1CEmVlDJhfeZeX3FmBizmZSK/ozFRap/61Kc+9alP/eHpZzHUABNlbAOzyPmoiBRiCPNWNARiTmCJehSq34lhkHOmjpNyCmEExIy0zVyMt47VEzBiDEgIpLxAbx8v5k7vnbxu0Aa93olJCXHHCIzzpJcTRp8I6Zynfan26fEPkT2vs51+uXLUg+P2NvMMzF6JgeCm9A8bTEgRP29wHki6oCESBLYc6GI82oF+NHrHoIwyeJzztjqnSGAh68qonTYq1WbLuFZhmOM5EvRC54FpZLn+ktE+rF84tEF1Q5ZIWoQlP2GPwbfzjWaNddnIS8C7ICGRY6aUud0JQVi3SLsL93NAP+jHwfq8ki3Rjndgoms5fiJ1pdO4vd1wqaRlR8Yg5RVRQXshyixsDNsV2kL1jPAjxBVcQIWXrxdkZO6vhT0PEOfx6HRTkr5w+hvuBYZw9kGTOykXAhshfcX7G+aDMd7m8BBXrvGK2CBEJcUNLwXvgjblrAd2faaVxih3cluofqBbmiWU5Zio3FYYPdAlcKs3xBqZTG0OraM+D+feDQmVvLxQzxuJNrtx2gAiMkBEse50eaefA5MDDRHr34kx4N0hBMx92g8JSEhIUKIOyvEgSGJJV1Ch1MI5oHmb0I2U0HWhnI3hM2sRdSHqLBe9n3fa2TEiolfMH+TsJBPK0TncKHpDWsPMCLpTSyfmDY0XhnXMJjq8dacWI0XFc+K930nVkcPpy4O4Z3JXWjkxrzAGFhdqHzAG6+WChkztHckb/pF1O95vbPsTW14ZZdDawGubpZZLxgaMMVi2zBBh9E6SjIcLl3zlvP/E2Y/ZgYTP7Vp3hndGCug1sZAI1WmtMiSjW2YN0HqjnJVKpx0PVHXS7kLmOAf4wNqdJWVSiJznjQPoH7k5MYhhJ8aEBgUHk0xYhGZviHUg0EvnXu9oCqz7zp4S91uhNkOYIALvYCmSw4qVxv3+BkmRsKJbJhfjvL0hUcnL7PMZdXb3mAVqOUAhhAXDkDSHKBtt9lp92s8+9alPfepTf6D6WQw14k6od1QTaVmIe/6gnQV6LLNPo6+MPksBBydEwW1gDbxVivd5O1sStTo4uBVEldIKMSVCCFjrmE8S0hwUAnUMVCMqUFrBLM5G+ssFTGb+RJ1RBVVBTWi3d8buSF4JMlu847qx5mfK/aS2E1NY1pUUF7JsSHPuvVMlEkVQBjllnAHJkXLSayXuG10M2kTkEh3/KE68+aDRIWUcJTPIQZEQ5mF71Jk5MEdqxe5zk6BROGolLRcuX3YE4Tw+QskpsKaMeOcoJxoC2Trto+G+1gM7I09jJVmYByUGl+cVdaPWGx532nlHpBHSikQjpGe2cRBDpD1uE9NNJseFoMoYBRUhxpUhK6G8gTijntR+J15Xui/Y2fB+Yt3wAL7EaW/ihrVG7w2JKzntRFFGP0hxZiV6NeAkxEDennCHUu4sltDWGZZoY+Ze4hA8hllcCnjesSrTjlUCjuBpZcQxqbwSZqh/7PhQvFZUjKEPxhCiJzQkNGUAli8/sGdwNx7hxJEJyDhOynmQFuF6uWCeKO2OpsLCE2V0wmVFl5VlSZTjG+14nxkpM8hKbSfn/cHl5YmwrtxeD3owfInksNBqxYYRk9Jao1uB4TQvkFZSvtA/EOCqF4YPVCuqhvRGXK8f27HXuZHSj69BULwbRIUhUGFdf01rD/p5EKLTM8QzcL7dGPJOWldwp94N5ESzEwVEjNYG0jtB0/z8emPJmUU3ynGwboEUnDIM1gXNQlpWVBK9N8yd+znT9tIq7o2hRogQZMdUMJycI9oT1gajV1BnuT6zbReOtz/jbIVxnNwZSFRCXKc9dFmJYUIXCJDWSHlMC2q1g1msO2ijYykygJxWwBHm1i5IBofRGyFnUEfGQEVxmaXJrVcul5U9LpQqjN4m+CTNy59z3PHRsdahO74w4SNHp9vJGp8QhDoaromQ5/DonvFaiaosIVB7pUubOa6zzG3opz71qU996lN/gPpZDDWIYDIYVllTYM0rozq1PjAbjO6MccNkoEsgSCD2SK+dgbNdn3kcJ2e903BSMHJKDBfMB1HjLJK8d3q/EYOw7i+YGcXuSHBiyB+2KGHJEZUNB0Y7CBKnJYg7XZ28JvrReCsn0pnoZBQZk1o2pBBi55o38hIRcdp5p7bOyIAEYogowhiVHAIBCOuOsxHiSvc4KWHZWLdnrA6Kg/Gf6K6ohbwIyzqRsa0Zrd8B4Xn9Nbfy54w1otuOj07YE+u64N1pxSn9NgeYvLLvXzjf3pDhs509GsSN6M8c9v5RCLlA2KF9J0fjul/RkXi/vUFYGcnp/Xd8e/8d634lBGX0zuP9Rm8V18QWt3nY6pUoRlKhPt5RPQleiGumj0FKT6zLC/4dtCh6Bm6jsn3d2OLCt/sb169X8rhwlp8QVc76jTUstLFxbycHFV0zTxoJeWHbnokWuT/+hOGNR00o33GZ9kYfjg8IKPv1mVEOKifY7AjCV/oAtztisC+/5LKuvN9/T4yCRae2wpKfaL1gbjQasTspnyzbC5qutPNg0YC7YdLJl+XDjvROEIXm+DGQNXG0N0ZeIAZycKqddG+TXpWUdb3QR6MH5bLuLOuKph+IvIN/4ay3eUoeQu82v9/LhmlidaXfC1hnyB1n5pFyvpDTV2wMQjKWXvD6imv6ODwHNAjdO2+v34nqpDAImlgSYN8wOzArM0myRJ5fXljtQquVlJ9IMXG8vVF6RUaYxbLq1N4ZdnLJO0vcOZtR28GWM07jHELYdvZUPwAhjtjAxYlpIZI47Q2CgCnd4MfzwWW7QuuU+8npD7a8s4izpUhtfZb89jqfC+LgsiRq65RaGLpMPLNmokQibWZ1HAQnrCCaGSEwRqH3Rgw7edmprUxy4jgRV9QUkcGMthQcQddMcNDGHIbUEBUepaBuhCCoRIxAs0KwwJouINBGmJ+7gORIGxHxSPfIsGlldReCJHJUUviw3DZ41D4BAr3jedoJ/6qm5k996lOf+tSnfs76eQw1OKLzRjPETDsGrRTOWhliWHJiCoQB0g0rg6EdXTJY4Dwr5sZ2vRBCAo/UdrKkhTVv9CKYCUhjv7ywXZ4RXXl//e2kJwXFRVjzQh/Qz4aESLcyaUAhMDwQ1x+wx43H6wOTQtLAJWaSK6U0ztJIObBsCz6U97c3Uj7Z952QVr48vXCWk9FBrTD8ToyJ0QqaAsuaZ+mmBurRGONgzZElCbZ9YRGdB1RTjm9/OoshfaGWY8IDBNrZycuVHgbb08oWdo5WGB36yLS+gCiln0jYcOl0lLM0QtqQYEhwaqv4vYC0SWxzoR53YnZCcBzncTxwC7RwIEsnbpHju2BnIUuYG6LtwtGNtETSdWeRRChGqQ9OCmm5cP36a9px0mqh2+zbOe93+vHGqk9YNBqF7geldBachM8W9WXlh/yMGBzjwAa4zgD1IkIArFUkR7CT3hoeK1E2SnlHt0xQmXTv7MSQ0JQ+BkRnuNOGgRqqB93veC/sy8uHDfCk9HeqB1K8Ir5gpaHaSMvOFlb6m1LLK4FA6EqpjVof9FHpYoS4suhOzjvH440+KpKENgYSFxaNiGzEuNLON5J9YbTGt3InxpMUIm6D1p1tJESEpDvl/JHgs6tnDGdUx72yXzdUQFHEI3V0RhCW5QvxNLjdqfnPSTGTUCxl7v2BeEc0EMNK0IjHjbQo7fg9R3mQ08q2PZPCTn1r0yo1KqMdjC2zPD3hjwNrlbM/0EW5Xp847oMyKjkFvlx/QanMXpol8SWvvL6+03qeKOiYePny96nHG7e33zPccW8s64LYQR0F653RZvZLwiCjuEc0bXA+kFYpo0IUlmVlDSvilfL+TkVmvq430AnESPDxb/tCL51+HrjfWHLGamXkQUwwRqPS8DgLbb1VImUi4dedffsNS3yi3n7ieP9zWncaENocytwdNSH6wrLs5DwY7cFQpZTBqIqGJyDS+gc0JGZcdH5P3EnLzBSe9wfNJu5bNYBkylHosYAbJo5bJ6SApHVi8fPyd/oq8KlPfepTn/rUP4t+FkONiPDl5de4O632iTL1MXMVVtnzE6s+U+uD1g882KR/LYHjXjAZrDmwrxeMRB2d0I0gQj1PRDISOhoNCYleCn3cGaPRbcz+FzNqGQwzMKh6sqwLAcXdyLJQ60CLMjwT4yC4wZio2j6ctGxs20KMmcIJqRJjAhMkZXoreHlHzechBudsJ+IDLxU/H4hGIitWO3mbyNYQNq75B3p5xyVQRqH3gsRMb46oImvEeiWtX4n5wrB3Ek7UnUcraF/IZFJ4wRyEBR0nGis5fSGFFfoBUqjtgfWBo0RtJDoaEmKRVu9YKIgEwrpCMNyEJQjbkomXZ477HcOJ+Zk+BjnuDOlk3WiPytE76EQhIxlhwcqgl0D3B73O3Mp1+4rVzgiN7RcvjNc+B7rjBiL0JgjGuqyTmDUcHwPqnZRg3SO1NUyUiEOrjFIJklCNpLSwpIQgfD/e0WjEZSOkBT8LACEuaIiIOikvjDE4zzeaObW80XvBo7BsG9FnGL2ebwSmJcurM0RYtq/0aoz+yhiVMTpBN2LKc6NRvxFCRuJGDs+zZV4dZVDud0Q7Xt7ZLheO8s7j/hOSEsMTW3zGRqWfhYc8CHJHZJtdRDjWwYbQovLlywu1vtN7JWnmMQ4sJta0kNxIopxnobnhGgndwSrXS6aMwVkHQStqwDjQZUNkIS6zI8VbwF2IcZZYxq7IyAQyW7zQOCmPB8vlhV4PzCt5gzUt0Duhd1aJbNsXjvKdRiXEitnAFWo9ePv+p3gwRnB0BJDAo9kkFroiHhh9UP2EpKSsSL8Tw8LLNWP1lzzOEztmN0sIEKTSR2PoQrLEkheWy/PM8JV3SnlD1Qmkj8d8otQO7rRH5y4diZFeCuJOTJ1hH4Wb4ng9IB4EyawIslxZ0uBoD0p/IKIzJ5VnzqqXjo2IDyFmIWuic0dGRHGiJIxlAg/swHVumVO+TsBGDmgvCIXhjUGhd6OacV0W4ggcGKgSJZG9U0dF/oqm5k996lOf+tSnfs76aw81IhKA/xvwx+7+r4nIvwr8e8AvgP8A+O+6exWRBfjfAP854Efgv+nu/+iv+tjucDvuAASEfVuI8cL99korg/p+o6c6SUk54lbprc3OBVlY4yBFoZU7aZn0pSI228VDZDAwcaIZ2p24LfQPhK07BE+4Z1pzhjbWVVnSDJG3+0Etd2qcoWthEJiFfhAodfr/c0os1ydGa9zv3/Ew2PZMYqF3ox0PBEd9oCo0UYhXxvlAfKAxwJgWKIIj+pEr8Mx4nLzf/hEhTjpWt5OwKjEujGqEqAQJNOsM3gm903vj8SikAOof9imc8/X3DEmkHBj1HeuDsxZ6WhAPhGWCEYRZIriuCylN7PPbW0EiqM4/Ox/fkRjIX35NHJVeDHNI605YFtCdev6W2iqan6iHYa1Pmx+gBNrReHv8nlpfObtjXghrZ9+eKcfBeX9ndENjBllxOuQ87VQt0jlpYXBNO0LAhiC6EdINdPD1yxO1D8o4sGZQodWTdqns+xXV9FF2mFEP1PvJuN1IcWFdf6B4Q9zptbCvV6IoJQbMYV+/chzfKDJofSB+w3zgUZBwwavTa8WXTFhf6OcbZ3llMFASvYGMB8YgpcDT9YX30riVO+3eUIdFB9u2E/MX6v2Nen+n1wMJmXWJiAZ6PQmWGREGsOaXSRyzSLo8MUojGIzxoLSDa165nxXRxLY9EfanOaS83hjdsQyWYORl0tgexvHWIc7gvs8CKNzh+/efqL2z7Cs5Zuwo3Nt3PBlD5uNabCGnCxogeqeiWDdGa7SuhGuE1kiyMppNG2k1+EC1p3XDHWJaOB/vnOcdUmSyCp3AAm6k5YV9uXDcvzOGE0XRsNKHcTse7Bfj+rQwOJDzjdKMNpRlCUjvEJQQnRgCvTXa95/I68Z+eeZ+fOM4b8SUgQkiGL0x3BECISrrvtFSngCCVhHt88LBhH4U7vVPKNuPRMmMMWZBphj7fiWmOK22wzlrm9Y/nUjzx1EmBEUTwybUYrjj3FAb6DgQzTQR3AsqTu0Hw42gAYIgUdjCDqWjChKEi2zgkXLeuPWKCTOj9Qesv83XqU996lOf+tTPW38T1M1/H/gP/xNv/8+Bf8vd/7PAN+Bf//j9fx349vH7/9bH+/2Vcje8FbxDH8bZO2+Pd1qIjDVjl40qnTrecQ80yxwlcDuE+9knlQiHtFINjsdjhtI1IiNCAR07ZjoDzikirgQCOT7hutPI80C4rfzih18BgZ++/cS3e+V0p0th2Y39qxKvkbDuiOzT1mXGUONxfqNxEJZAWnZsOK+P7/x0f+fsdzQ0YjbQhvTOMoxtSayXK+6BQcAVxmqM5DQzzlr4/vg9XRtEKP0B5rPFfEwAgGrECqhHokAIfGxWHOsHoo2YBhIOiIW8dbrf6NEp0hnReIwHtb+xJeU5vRB9I8UFJ1JH5vujcx+V6hV3Ybl8JW4Ly34hmWJNSHL9CChnRm8Uf4OcGKNg7U453yheKEHonmkFhkf8ovRlZaSEbxt5/8qy/ZoxAs0Dpw8OCi0rsmfysrGtP7Bfv+Ax0jXzfn/lHBXLAd8Kshn5eiHHhRiEbfuC5JUenZGEkK+U4RSPlBEQEu4BmtMlU8h8O+/cR+fR4f0sHPc37m+/n7YiF2zccK3EZWW9/hJTICl5u7DtP2BjoKrQC+U8+FYbb61ybx0J8zF1dMPkB0SfuR3vtH4n6mBJ027lRO73Sr39Od7v1AJBX9jzE731CcRwKN1oR8P6gdvBkIBJory9YecD2kG0gfugtMHj/uD99iN9HKzj4CnDdbsSTD+Q5k60ymW/sF2f6GelHo02OrU0WnnnUV4hbOz7L8A2zkN52OAQo9WOdFjSzppWyvnO99tvseQ0h2KOXL7g+87pgbNGSh0cZ+VsB7deOH2lNqV15/G4zeJTSVQbtPOOdnDP9DIYZeBt0P1AcoCkhLwQY0TGYJC5n8pRnREicV9Ie6aNgVnDRYg5sG8RjYYHZzg87je+ffstpRXqGHTzWfy5LuTLBYmR4k5HYBQiHXrFu2HVyGEj5oxEpbvRcXpwqhy02CneuR3vPMqNEALiPpHWrnib/826QTPqYyLu057R1fFwoLGR0yA/wXIJtHFgYRIjiQlDcA/Us3GUioY4B+oesZ4YrWESkHRFmACRP3D9rb1OfepTn/rUp37e+mttakTkHwL/FeB/BvwPZHoU/kvAf/vjXf7XwP8E+F8B/7WPXwP874H/pYiIu/+VBQi1TURt3mazPN5p5cCtkZdAkNnmbmchyY67obEToiE4wzoqSisVJc5ekx5m30Ywgjw+RrgwOybqgVmnic/iSoGYldELb99/4jgLo3dEK8v2TAiQUmAJkahOa1BrRdSJuhLDClbYwzpzGL1jzQiaeNoDUYzSCmXAaA0VofcTi5H18kJcMtQHMUaCZgh1WsDqjSVdib5z3B40GqPOr9mQB86Y5K6c2K8vxDj7Xpp/Z/tyIaQrtZx4N9T5uN0fczBiJ2jgbAeRBBK5PYwQOqefYJ1t7DhPdDeaO3E8cO1E6bgm7HSO9nt6b5x5kHWFMabdj4T44Pr0FRuJ1k58VDIbZxc0JF6eL7gE7t3mAJBnd0ods08lL1/I8WRZFu6PB6NXNAZyjCCQxFjCRvWTuiZCElYx4siU+4MWC9KV4IOnpx+o45VvfYDtnO0n6Ad7/gXiSq3fZsdR3InpCuc7itN0dqwcw+nnA190WorS09wWjAajYG1gf9E8fzHQzHn/zhAnh8GSp0Xrkp8ZrbKskV4PUopY2Hn7fhBcyGlFFZ72KzYqR6mE5UI7jOEGBCwYpygiAUWpUma5bAnc7BvvfeAhsTDLUqNc8OOgD+GuSl+E3g5WSxytUW3mXzwby3Xjunzl/ds3HuUbZoMWweSBBp0ZpKHkGGj+hvrK6IO3s5LyjoaV2h9Yq4QFUlrp7YF6oHmZmRNdEGfSvUahnI0WjMAgayAGx+uDUQoWFrDAffyOly9f2LYro3V6g+5O58DMkH7hfDfwgnon7i8ISmoP8EHBuD3m11g84Jzk3AkxEWTBzLk9KildEYwlDWJU2lgn6SxewSNWpyUvCOwSp3WtnNz7zP7hxpCOffzMqzFzLA5jBJ6efonXmQXK24XWKjYq5WzQnSwLw4xhBz4E0YSJ0+ior8iI5DWQciAS0TEtmvv+TLopbTRiiLNzKAilDpRIG857n5scXHAiEiKqk3xobvjf6J7r56V/Ea9Tn/rUpz71qZ+v/rr2s38b+B8BTx9v/wL47u794+1/DPyDj1//A+D/DeDuXUReP97/9/+kD+4uDDPWNDtY0BPVQA4fxZWtI5KgVdxOCE5Ig+vTlTUvnOVgaGA0ISK4QjkqIk5YlGVbUVvp53dGOzBvaIisl18wrBKQ+THoBBeO0kACmtNHH0gkSCehqCj7Ghkxc+t3ynnS2kErb+SYeIyOeUMSaFJaN7pV0rLwtP4KyuDQdyoFcyfmlRCg94OszpI3znowygMhkcKF4crZ24Rw6ROtv9LqjWSBJX+ZhXpx0Modscu05gXIlx+gTw/+7fzG8MJHugRxyHkSlYQdDCQGdLlSa+EshaiZIoJkI6cVXw6s3mcp6XEwOgyb9pvhig1Duc9yy2IMP8jbhTF2GIMUjIZiS8KDoa1g5ZU+jCAGOtCY+eGHfwU77zzev2Gjk+TDDufCsj0h487Z7lhtH9SzV1QTGUG7gRmuSt4mrawVQ6Nyf/sdvU24glNZl3WSo8yBwZBBaSdijg4n1pMhnedf/QZBub3+fuagTPCeiSo4mVAflPYd8QVQLHRaO3m6/j3E4a284m7QKpLzLKdkQVjp9YGNbzN0XwyLndH6pFnFBJ4IDHozXBNdBq2+4mO2zW/bhsokodVj4qwbxsv+Qh+ze7VbpZ3f8DZv/4c6eUmslx9YdCFqYkk7r8dvJ8nPA/1sjHPQ5UTTisaI2Ml1/YGzzuEmRiGuX5Ce6f0ntji7TzwE0rahvjB6R1nxEecWRYycDZMTc6EcDSMR8z4D7V7o/UbCaP02nyBUUe1AZdQbl/2ZE8OlE/OVrpk2GmtUzuPkrAeiSrI5fIgExBrRKyFElrTPTYg3UhBElRg36jFR3CIK7gwczYEUAqqTMlbrwXk/aNUQDJODvGyzQFcFic4YDpLmYytn9uUJPwpneaO1g7f3H+djtBViHsQc2ZZfYOfJ+/l7TBOq0xpmKeKieFgIOVJqoT86bSxkFXo/CBrQpNzeXvEBY1l5en7i/P5O7ZXmD9waKUZCAGIAYFQnhLnN6vXOgxvwB32m/7f5W3yd+tSnPvWpT/289U8dakTkXwN+5+7/gYj8F/95/Y9F5N8A/g1gtrSrcLQbeCUlJy4rpg45sVxeyDga4CwdeiHmjY5RrbKsTzwejxmel4C5oVmBQQ6J5JF6vlGO7xCEGBaQANVm1iQm9uvOaDrx0QyMgoaFqIK60WrD+szDoI61iHVHouPSSHkePoYqQZwUI0giyKBbm5uA2yvNCzU4Qp6EsBChn0TppKCMeqOWEzNImjE3ug0sFrbtSkxfKKUSccJoROuEAflpQxzKWajmbMsP4E/U40GzQAtKCitOI+cMNjtStvUJ64nH8SMaCklXct7xo9BK5W7v9Pady/ZE2h3VhdAzZkqXTtBAawfdC2E8qBKRGkkR1jVhwP39FXMgL5CMvK5sQyFCjmD1jSiNZbuSPZPulXKcuGYk7vTzlX4+iGmZWQyHsH5FzzdkhDk8pTzb7nsjrRsIHLd3Sm24XukUOncgU8tAUmfLiSWt2EiQF/brr2it40UYrfLw+yShPV4RJjb3+Vd/n30s1HZQaydrhnJgQF6uuA0UsLvz7fzHLHllzzvDBmMYITjtOFBd5qB2CJbrJKNFwcMcaIYJuv6SKIF++0avA8sL+vSM3xtWfoIxeH/7xugn+34lh0RpgkvEutHuD6o5RAgaCcsVdxj9R3REtE67lueDLm+U40YImbB9mfCH7Y8o5537/YaEWUxL3NDRIQaWxdE0s2tdMqfdwITROuuyo2Pe+1tr1FoY9qCNOxqcJbdpM3z+DffHg94dxmD0kyYC/lGOumQsBELaeVp/g7cD4k4cc8gjLYQAm26U8wFxAhBGN+p5Y1l2RDM5yESol++U+gaacHWi2rSoKaz7M8MGyEptle5wJ5DdicWo53d6K2hQ8iViI9DP2Xm1bivncWM0CCmTA4gLbo3j8SMpJMbHNqR/5KpyTIS0zt6r40CkzwGDwRg3xAWxleCZbkbKStpWnJWoG+N4o7WO9MZyDR9W1IQ148aDHBOX9YmlXfl+/B776ISKDNz77JSSk4WVPu6otnnb8QeofxGvU2t++ef1YT/1qU996lN/C/rrbGr+C8B/VUT+y8AKPAP/C+CLiMSPW7B/CPzxx/v/MfCfAf6xiETghRnE/P+Ru/87wL8D8Mtf/tr3yyxK7AY5b2jYGVJZYmDVwBqEsHyl2EEfN0YvZOm00ukYEhNhBLbthaAb9/c/B4xleaK2k0e/o9uFGAUNAqL0YaS4IzFiYyBmRDVEDBEhmGK1gwrDBcTQkBjDEBmsa6RZnYejrNgQsIbkC8a8RY15wSoc5cRwRCMUI2glrBsxzD6MWh6c3iEkTFZcIkLG6g3XO24B2oXogY2V0u8IjosR8gIdRpjErYsofrxTxGlhUM6TLE+YdUr/hnklxYBgtPaOFUGLse1KGAdmJ2mpHPWdEmDLmT0b1ttHnscpBSwMuoDHTtQFsYLRkGysz79CU+J8v9PKHUuK2OApBaTeOY5GLYUhFURZtw3ps1vkVn7Ho72i6wWtAa+dHiCEGbFvEvghJe7vB6YJSS8co0P/TlqfZ89PfxC2K4ETTGn1zqBPK9ZToI+Tx+MgXPrsHwmd3g60B0wqxQojDZ73XxFP5Szv6JpZ1p0XfaaeCm702rmHhLsRYkXJtOOOekLCShuJx/ETrsKSVqLsxPUX+PHg/fYnND+RNtBeMXEqkURj3xPiD2oxJAZcBiEy81gp0/sLulS6diQ9Uyzyq+e/R9Ibb7dX3n98MLShObCGSMo7tZzUAemjeLa70PpGPb7BIqR9Y1lW8r5zvN057n+KsLLFyyQREjiPA/NCzhspPeH992hsXPavhAqnvZFUyV44y4FKJAaDCH0E4vKVy/7MEhzVCBhrhpHDfAzbM2F0GG8IH48viQRdqSNiI3F7e+eyLqScqZb59u2VGBt5YZbjhsi2RXLe2PIPnK/fKL2wLF+wsVH7nS5CN2PRhGOYlY9CTYEo5Lih1fFecf/oL/rIeFUSUQIeHlx/uMzLgmFzC0YBzRAiDMEdUn6mjZOhnZwWdBgmG8M6pUIohWaVsEbW/ZnQOsXfPgpOBReQnvHTiMko44bFQdAIITOsUE9DwswLZk30flBjJDHAG4tmPEbUhD5ALFPLN4b8SFtXXGENF1T+YO1nf+uvU8/Xf/CHOfF96lOf+tS/JPqnDjXu/m8C/ybAxw3Y/9Dd/zsi8r8D/utMssx/D/g/fPyV/+PH2//Xjz//P/1Tfco+8KPDgKiBfhrV3wlBKVpYn1aqJ9r9G26Cy/lhTYscx511EcQEeud8f8f1wHCwweP4hhAgKBJnJ4d6R0wIKRJSIvSF0TrV32d5nhnuARefwVpV4qLs60KUlfM8aePgaAchJdZ9/YjrZMyV0Yw67miCkDfWuOC84qOhFjAqGhIxb6TlCXMFG0AjLDvtcMY5UB2YFjwrCPTyYNiNJUR0v0AEN5k0MTfqMSjFaaIYJ8qDoBNf3Os3RjLWvLPlhNOgK5SNenZqbZhUcjqIKRMibJcLTzmz5RUbg/dHQWNAk9BqJ2qgeUWGESQjGhlWeLp+IRKxoxJE5qMsDJZlkPKGNZudQK1Rh7LuO0tY8eoUbwyvpKcnbAx6qbgqNQopBK7XL5zlxuP1d3Ortj4Tw5Xu74TlK6Jx3pj3wrY9oQSMznVfaJ5IMaOaedwP+lAe9xMbt2klU2Nopg8FXVmC4m3w/f4jboMUOsdbQJZAb+eka6ki64qPA9eBIB+t9YMkQgyBpAmzNul3GuntxNqJhxVlpdpPiDS6LnQUb40cHA2N7/cDwkBCJLnyvAXSkrgBzQbJHZeAExjWSJdIGtDqIMcV4mBZF677ykidZkqtTreTlJ+wds6yyJxJ6UIMmff331OPgsvArOICHgbmg9EKEoRsnXI/OEdBkxLsRhpKt0RMTzAOJDhInLas1tjiSlwCa95wM/pZGfXPMHdaq+TrEy9f/ohxdG7vB907rT2gGuN+50DwELHROO53ni87GjLLvmMyc2WmBcyQNijtnXYeiPvH8DhR6sMbYsoSF8SglTtVBJfE6JVlLFySEGJkPJzaGk07hECXheqd1iddrbdGphJHJG0v6LjjDNwVJaBhEHNDe8TZCUTMGzGtiBponD02VfGzMWhI2LhsGQuCSZyPzd5p1LkJqtDu37AkSAyQB8vlB1Z5oteD0m9zCNPE2W/oaIzSaKfgKKqVoAkJEwcfNNKHseSM/oFyAv6FvE596lOf+tSnftb6Z+mp+R8D/56I/E+B/zvw7378/r8L/G9F5P8J/AT8t/46H+xsIHYiSZEecRE0LaS8c4yI10rWwb585agFbye9z54Ic6c/7hPPHJRuZVpKQqK1OgEBMXIOJ4iSWZDuJA3U14YPR7MzInQylo2kiiCUepDTL3nadrI2UnQgMZox+h2JinUh5Iz1jlXHWkXVSCFjY0ArLBZBAs3v0/I2+iSn9UFOF+w8GTboreJl5hpaeBByYlk3YsyscqU+3iB0rk/PtNK5317pNrMAtTvFFUvCmhLdCr0fLNsFgpM1smpEXTnPx5yjfKOZ04JNspM57SxE3Ygkljhb0ksx8EQbQusVTRGLQhqzuDDHGUwO4Yq1wa2+AlBqQ2QQcaLAur2gKLfjFZGNlHb2kIjVOeuDro2wRNZ9J8SVc+00m3mbSCOL0mOghQQp0XonLgNNiSABPx608w4hcTwepDwthJKUYIPH+WCMOxAJlwvn92/0crBuAX3eQVdinF8nMeN+/5Gj3eY2TyJ23hl9Di9BFEc5z0AIOr+e+MxhxUwt7zBOUthwzbh1xii04xWrnbh8JcedROQc31CENa2klHh7+91EaecnVIXzPLHWeLOG+OMDOLByvx+M0RAKDze2l439ZSGFRKsnBIjRaOcrVk80XUgB+ojEvFLrjwQTkiR6PxlWGecgkAk5Ei87x/1AJDLcqM3JIRGXnX47OYsRLsJTSnAccFQe/beEHEFXzAN2HnjvnPcDiU7ZDpZ8IQdBvKKuJE20+41v4/9FihckLWgK9Ps3rD1YQ5h4Yo2YJ0Y9eHv9Tl4W9l/+A87jnfefviHiLDmxhszoTm2z0BWEqBPssaQL3iGIYu5YyDxfvnK0QqmD4Z123qkdxJTeHE0JQpx5KB3Tjhec0cvsxUobQRb2yxMuDxBjFKE8Ko/X+8yuRSUkJYyIHw3nRJKzLBdiUGgTHOF2p4UGqrjuSEqE1un9QfPOcrmQz8zZBi0GQqhIcEJW1BOlNGQNpKCoXmiPO4NKUqdaow2B0NA1E+0Zb4VWHhSbRaH/KdM/19epT33qU5/61M9Xf6Ohxt3/feDf//j1fwz85///vM8J/Df+Jh9XEAQnRSPExNA8izL9znl7RyVy2TJjGEf7iVYH8RLJa8b7yeXyTD2nn9/jwp4XYsiM4dzuf4475Cak5khwYoCYFHDqaMS0kGMjCKQlgMo8FNVOjol1yQgPNEYwGKfitiDJCMuGD6HdGqN3utQZLpbIqJ36+IZYQjRxqFHbg6RKUsGOwXn/zrK84M2x7tA76ELcAHVEA24Nq433/orjrBo576+0lrDlSnEl2AxSp5RRoNQ+b2ljQggs+Zl+FB4a0BA5mzP6HfwgL1cueeXxeON+OmYXni6BP/rVQu+Vt/ugmRDXDUVYwk5UZ/SB1QG6EXRFMZaUaWdhJJ2ABVa83lArhGrY+ys/PR708dERRGOwMqSSLgujNlJURnugIbEukRe9YP0EeycH6NXQHAjrhrz/SHZh1A+qU1a29My2fOH17bdoaKyXL3y73+lHYQkXUhiY3Hh++SMePGhnJecNkUAtd9b9K3t+4fe//Y94r2/ounPdXliWjXo7uJ2GW2ENgRgXYqgE37nX98nTNsFLmcN1d5aXF7pXztLw+40AhJCmhTAbKT8h3efwheK3Vy7Pfx/rndhOtm1hSMVTAgmIBFLoRK3EtFBbR83o46BIY/vyC8Iz+K0gIiSLfH//Pn+uemVZlOGF7/c/YXgn50RcMt2doaBxnSjhYERAcwIPSK00DDWnVeHs0GumtXf00tjTC1amrXOMRloyi+80KRgnMRpVldpOygA1wcXJi/Hy/AMbke/3B49zIGHaRMN6BW/EdeWyJ1J+ItiF929/Qh8FRaivfzrRxeNkjE7WALrO8ssRcMsQI+vLC9EK6or32eXiMRE9su4LF1+oZeM83ujngZ0DzYHlspGj0HqhdSNqnNAQh5NOVIhasHrQWHEVPBh5ycQm0FesCaV2ulcu+5VQod4bdTyotA/ims4y1zbQuFGyctodHp09BgJOHx01J0aBdpBqIFjA7cGbf5v2O4VeK2cv4DYx0EkRdtQ7PS00j6gfZIHWjSYT0tLH+Js8df8s9bf1OvWpT33qU5/6eeufZVPzz02uyvrk5O2P6KVT7m/Y/SDGMW9nZfZYdAfCQlqMHAxwNG+0etD6oLXGGgZRA0v+yvv371gdEycrTlpWYki4DPjIxlh8MLTQPJDySs6Z4E7IV279R4IKGmx2ggyjn4Ozdkw7aw4skij2oIyDkBM5fZmUpOMboxdi/gF5eaYB9f2dFDa27Yr1uV1RiZzHO44g3XAviLyD5Q9CU5z2OYzulT2v9FI47q/I9kJcvvK8/grKSfMHJpFuheYHGncu13/Alp6pj2+U+iDtz3gvWK+gkZiXmV0o72zrFcLO/ftJbZ0//6kS1Wj+0XsRhDgqGSVK5uiVPiqqF8rjG32c3JuxPV15+cXf43g/CcuFSiME5zgPHrVScZawk+OK+bRJ9Q5WHDeltQdRnziON2JXWr/jUknroD4eiGXUjafrhrVEt+9EjUhYJ6a7NM73P6NLhQBaC9dtYxDpZ6H2G6aF2/c/w4cR8w4O5XYyzJB9Q7wzWiWnlX19wr2jPtiXC7dvDddElU5cvhCtYb0iBqIbeMe4k5eEDKGNE4/Kuj1hpbHlHXFFR0GSgjSi9IkQ77PY1FqdfTHV+en7G+mSkawEWbHSOPw2gQ8EbDR6vaEMLF6x240lPSEkan+jlIF1Ja0vH/a3b8QUCHGnloIgPB43uikuGZqxrpnSCr0JDnS/YzRSWMEDfwHhQMGG0mrnkQ+2l2fkDJT2IF0Cy7KR48Z5h8oNFE4X8roQLeFtw+XG2W4s8YktR6gF64a1E02BkAMikT6U/nhjz4ktPXEfzmChjQOSsv7ih4lDfj94e/0Rjc66faE257RGeKssUfHxDjhh2RGNlMcbrZ0fW72FQIB9JS55gjbGgcRMtwPTQdq+YL1hIpj5xIyT2fdfEFURDZznd94e3wHh8uU35LNDueO9U+9vqIMFx0em1kqTk5frb1hC5PX9Tyi80+2Z7eWXMAw/7oxWCfkJQmDERGKl1O/TTlcyzTqaBhoirQ1CChPtbEZQJS0V9YDUB83BiaQ1sYadWB1NF4Kkv6uXgU996lOf+tSn/pn0sxhqEGeJC7t+5Xv5LdIr6x7wsNAtoiMxeiOnDU2NEBoWFkQyhjLKyeM8CVHp3RjNuZVvlPNANKBrZvjAteMyWMIFkYTvzjKU0JUwEomFUQYmHdeTff81SSIpLJy8cdx/xHsjeAMTrCaOVujhxAMEj4xycIwH3ZR1/QUhR7Iaer8TGSzbCyEKTZ/pTLTwqHdwwaKjMeGmHKMR48TBRp2FgCEsWGv89O2P6aOweSaXgBedhZjrF4YZrRc0Rl6235D8BW6F9vgJ1ZPQ4/T1h4yENMsbRwMznr7+QLBAj++cJdCbsqRp4teQGceDNe8kc3wM3D5uystBMaN8UKsW7UgrbB4Z9qDyxjxEbrRSeVq/kJdnej0QW+j3k3YrSFBkh2Fj2r2aUQ+n2UDXThvGOE5kPAgx8v79twQ1lrTQHWJ+ppaTQkNCZDRwubDEK+oNV+VdTyw0+gA7DpQLMt5BFFhxu/D48Y7FnxAZbHEhqVH6ndYKu30lD6iSeYyEjMR1vdLlz5FiZE044L5w2QLigxEW1ARxp8qETLy9/8hQYSXgon8Zmn/54Y+wPvj+0z+e9saQ6SmSBLDCdrlSW2eMhft5YnYQU4S4cdqdMxj5rJTzHTgAxzwgYSNK4ny80jm5PGf2vBHZsdEIMgsaRRd6cHw0BDCZFL/aOxoTOQSCdZIbEjPIoDv4WCjD0bWzXy/IeyX0QdoLPQzyusw8zqYTztGMTKer02zi2KudqMCijRx2zjrovSE5o8vO8Thpjzun3tnXJ6IKZ/1OXy+E6th4Iz19Ydmf6ceJ+0GIDRud99q5hgvl7EiMoIMxCsrAk5LzFVrn9vYjpVbitrE97ThKP96pOghpwcZJYyAqeOts24WjC7pEtHf6ozC80rROGmNQ0vbEulwIP/0pPRzT4iYD1IjDwa+MAqf9HiFgLJg38Eq7vZHDBj7YLzvtrOgwJB7owiyRRXFgdWVYp5siWiE4ulxxu+MxE9YX9hC5duN2/x3nWahvd2IGSRGVhPynz372qU996lOf+pdEP4uhRgzaT41v8R8xdEB0jrNNKlYWkgxanICA0WeLuoaAD6OOwVEOVCHpho+d91vg0d7x8UaMKyPtaAxEexCCMNq8SV2eE2kEvA+aVlor5OWZvDyhCJSBtwdjEdb9Qi2JctwQBBXBwkk3Ydw/DoD5JISEj4D67Mhwa5SzoFGJSVE6vT6oKPGirPELzRTTiI830rIxLHGWd5aUWeKKUBm9cd4HWKBbxpaIh0hrjaM8MBkseR5OkzfyurJGh/ITxMjl8gP380d6OXDNhHTB8wL1QVgDvXWO88bTOm11UabNBgWNG2CogNEZkjAJaNoZCJIDQRorkdgXbHR+92d/SpDAUKWlRHKlPk5Eha4dxmM23Q+fRYPZaLHwtF1RFup54yV+5Wgw1BH9CzjBBfOKR3iMwrIsDHNSfmGUjrTO06bU3jjbHfXAaMajPLhuX1ANRMvEFMjLD4wx6GUOBr0LMQk5CpK/svRKZqJvn66/pLbOeb7jyZB8JcUX1CM8Ksf5oJwPQujk7YoEp7/9SHCDvBJjYM9zgDiLQ1Dcjcfjnf35iSWtlHbD6p3zfWZQhjSQwpIzvVTEB3f5TtALqgHtjW27wjBqPdmWH8iXL7Nv5X4HH6zXZ9LlGetOrw9yMpJsPO7G+/1tHoaXzMse8XLQ2gOXgLjSxkBCRqLTVPEww/MXzXh3bHRCVlwCTZUl7hNvHYXr9Ze0dvL++tO0loYFZKcW4xp3UoRafiItkT39Alwpt3dsFJZ9wRm0WvCwsYQry7qw5JXDoR/fqaOw7Fe2AMOdlHfuj8pPx5+w5pnHGQ/h/bWQ1pVf5JWjveFjIMNJi7KOnVIPQCntRjQ4HncG4HXhkBs5JpzIUUB8ksGsBogL+Ik8Hqga41a51YN23ufbW0Tjilulljv78jQH3FpY0jMhdkY/qdLYUuK8n9TjpIaOonBA2DvkinXHz4ObnwQJ0ApDhbRd2dNKqonz/k4LjbxvLGOd3yuHBJwyN9nWndE7wzuBQF4d7xvv7w9MKmF9x9z+zl4HPvWpT33qU5/6Z9HPYqgBQS4bkgz3xuiKtU6WgjPoXHCH0w21BtY4RyPrRg5Xyii4O6+1Qyis65WgGfWNaNBrIeCoCP0URv3GCCftvtA0EJYrQmLNT0R0WpwEarkzxjur7jyxYx54bQ7upHgnhAXxBckLmtaZ/x+PWWrphqxXNO/s+Rn7yNfc2p2uhbw/sf5/2PuzHU2yJb0SXLJHVf0HM/PwEyczySoWiUK//9t0owk0kmTmGcIHs39Q1T1LX2iwHqD7ouKAtgC/8QuH2+BuKiqfrK9Z9PkNJ5Y+MmMkaAveBC5/+i/szx9s2zesWNoO21aOzhpvWOKZmjfaeMI0YWVChtLKHRGow5H2hDOO5fU/4aqwpRtGLMY4VBxaG2UknEaIJ4Yzx4XLMuG7I6VB70rwlhg9by8vhzWsWlQtY0CM58OYND4ww+JaYvRGR8CHI7pmJnpOOOfw04yLJ9q+kdPHEXm5vqCj0uo7Qwwt79Sa2NqDMa50W7Ei9NLw8YKOwVbW30sDC2MMjHbavnEKlpp39v1Jb4neLB/PBxZLcYXRB9oEFyLGCqWvqKnE+cRLOPP4ead0BbW8vvwZtp2U/obxMIcT+7biXyZ0NKhPVGBb77/fkHxljEZnIKPSS4eeyTUTlwXvAtZZaqtMy4V9vVEH7I+NFHeMNZThyGllUBhuUFvHqFByZ3bQtGKN4N2JeV7I+2HV+/r1T6TSCfMr2UbGtLDfb+R1RbtgrcNiSTWDVXptVPWoCq11EFjOZ3RfkQG5JjoTZhjoGecsc5yxk+U6nUn3H6TxQI3HWI/2zLp/0NuN83zGeYcOSGUH9QxRmr0QTcOWAc6jYpliRESpraPW0vbjGB+vKAPVQXmu9LwyXy9AQbwlnr9gxUAbxyCYfjJw1BoQKQQXMJMDLFN8Y+6G3b6TjRJCxJZMLRuqg6GGNMwxOFuLjIaPFmciac+seae7gFSL8RNuTPgikKD3iomGXB+YEXDmzJDf5Q19R0V5Pr8jzVHyyt5WonWMx0bud4ZYrvOJ6TSxfuyk5rB0JBRUJvwYRA/ICzgQDlNh7QH0DO4XggR4DlpaSTSMywTrGVuh1np0/ohhpAfJeNQ7/PwF35+YqdPbxHovtP3JGP/4NzWffPLJJ5/8r8kfYqgRUbreCQSimdkoVBfBdLJOjNGxwR7FgGIw4QuMhT0nPnKjmIiMQbDxiKh1B73i3YL2J5J3nLmAm+k2406CD2es8YwmmGFhNFL6wWiNZgy1NYYmXLDUTXnmn6xlp3cQ47D2hBVHdAtdjvuEnHfamPEdHJ15LPgUaesKxoBY1HbidMERqfkdE4+DZrTi5gs17wQHpnsmD6NFtudOThtmDjhjmeZXgp/IoxPsjFahrDt5FIzPiLMMI7SeAXi8/78Z4unOcZmvXOOZx/bg3gpFPbF0TnHQMhQ9Yc2Vx/YdhsFxpqSMM/C8J9KeETmj1qLGYs0MWrFwbM5qo+nAOoORysVY0EbzDieCJbJ/fGerG00yU5iZPIRWmUwkuIXbQ+kdsI3CD4wOZnfBxAnVQZyvTLJQ0o5sCemJ+/Z3AHo/BBBDDc6e2Jpioodckf5AVbEWen1iFgNLZEqdfftglEZrO21UJjkx2Mg9UXqH9qS2G0wGgsXWylx2xvpAS8W2gZt+QZxD62+clkhyjWomXK9Im3n/uWFbxl4ck50wVujdIy4yyji2fjZhFodVwdtAiIYtFcIkzJMlzBEzImaY4y7KGmoqbOsNxVBWx0DY1xvaCzkVUn2yuIlgrtgxk+0TY5XzdGbUSutPYpgR7+j3Qjz9gjVCWZ8Ina5P4jSAFVuhpZ94cdjTmX3d2fdEqonhhbAshNMJI409r9jTjO8Lzx8V6wp+nshrwsSMGE+rJ0p+UMeGjxeYHGl4JjcxnZVeCzVlWjMkuTPMwM0zp2liu/9ge7zjzxcu5xeaCjZdSenjuCMRwYill41GwTnB9sHITwTQDkYdXY8uqmFAo8US6bWQwo6fXjnLmWyVLtB751ELi49cTl/p5YrEgHOJ9nint4K1AWMM+ENM4k2n5++U7eO4DxudsmZGOAyPP//6d9R1hkwEMyHBIHoh743aKy40DAVx1+Pv65TRhfz+5L4Xop0IAifzhaKKtkFKP8HDMr1hqqEHQXNjtCcmnvEhQraUUYmLOzZj1SPyD+p0/uSTTz755H95/hBDTR+d2nZs7zQyuVXUCFiHNQapO35YvHE4ZkyZKTbgpwntDa8rJxMxu0eIDNPAGnq+U9MNRFC/Yn1DFVQXJA9y2aijg1GcC3gbifN0PKTOFvFvjKGcrl9IG8haiQjWTQRvESK1FIZsjFbwYyL6K6NmyD9o4zfMNFF6o/VMODlO84yTSFNLt+1oYG+VGCesKNV07vfvrOs7YTkd0R46nM+40xuTCbjesdqRGNmfT/KWUDMTTheM+YGZTth4pddBzXcSmVIyOnaidfx2/8HedljesBJp+8rPdENCxMoJawXB482EEYsn0PPGWiq9JFycAcGYEyn/pI0fhHghvv6ZJI7t9oEzEI3FmCMe1suGqiX1jTY61gbO5wtxnhg9QcsoSsuVKQSsC1gDP+83xlBqbocZbChjFAxgVVAD6hYa8dAlj5VoI2F+YfREazvahTlOjNxQGTAG1ghxbMwYkKPQcwxwLjJao7fMrf8dFz1hOlMb5PJkPp8PcYNpqBwaXT+fWZ9Pnvu/MnQQraJrQOwRP7IIVj17WrEOorWH1U719wZ3xdmZohO1b6BPrLW4UkHh1b+AWNrIrO8PRj1ulOLZ4+x8yBVKx50D++NJ60LKO70UrIv4+UqpmT39FdWOKozosXZALlyvX3AobXvgvSdMnvPlC99HoaeK7REqpL5SpCEnZVn8oY32G2IbYRiGc3RxNHX4cUg05EjaUa2Q8kYZBX+90MRgZae0J711amvgduzsOc+/MLbCUAveQVfKulFKx5w88eVPiBjK2FE/jp6rVDFOOQXP5L6S052RKyU9Md2wvL1ihrKuTwoNMRZpA28dRoToBhihdYMzFlMH1KM0NpoJ2xrFDEQ8Yz7ibdF78s/KSIozM+ILtX9jmJ3WO8Z4jAbKYyeNTmemy86enjQzMN0wR09YFpBBmGZGUzKV+XTh7A05bbS0Ix4YhS5nvHSc7CiJkjaGf8VKRMeTdf1ArT9KReuOuhtGDLpmyhSI01csHh1CWht734lzBNPomvjH7d785JNPPvnkf3X+EEONiCDWHiYzBJNBMHgRektEfxiXrJ/p6cbQB+H8Z7xzuHojoJRnpRSD8Yo/K35q7DaxvL3RN6HmJ3kv1G6wXlCT6eKwwXOaPKIGlUbneLsaTgEfIn19IPmG647LVLF+Ip5eyI8HPf8kRIvS0D6w3WDF8dSdinIKnWUWcsp02SgjQhPi9IZvgWZ+v2XZHqz5BtKQPhCxuGAY2gEhhhOlZ0z6YDpf2R43VBVjPKVDO19w/orKjg5DMJGeMm0oDWHYV4wU6ErTCH5nCgZnwdsLuXSqdEK1DL1hTxdO8yutDgyKHb932aQnyoTthpZ+IPaJhoDRgO1CFEvtBhdnpsmyzF/ordLLE2sv5JyQMfBqGL0yuYClYE1g2Im1FaTdkdGhR5SJ6E/UbafdG93uWDORe0NsZDJnaixUd6JzppWfMCqTj8zOMnSi5YT1lmA8YgO5bdgYMThKGQiW2jI2zHgzUdoDK5FeKxIEOwWW+VfW94QZnb5vtNJYXq5waozcaRVyfKXUvwPKMk8Y4xABbCT6M1M446STjFK7UNrARc9ligyFUQdSHoxRkFlZoqVnoZTM2t9pKDo4DuLlKKA008CoQ1uk1YBrLzh5MLTgg8FPr9QxqChdHMVHjFkwDkxIDO1YaYdhsBdMG7y+vlF7Yvv4V6Lv2DDT1pnH40aSHTd5JnvBxKM8dQqBdjbQAq0mOo7ChBlCXx+YBmMIbijYTGKDvWHPZ6y/MOoRl7TdUbcdOQ+m09H5VD4SrRRa60hw2HCitcT2+EnaH4g0wnRhtMrz4zttdCTCvLwQBux1Ba9YaxktE2LALgtUGL2jklGBuMxYeww501iZfWT0AsaCKrX9YOTCdLkwnTxlP7ZMoz0xSyZ0Q9qPWyK5vuB8JVolD2EKL8jIpHtCR6YPUOswCF2FvRfiOXC2Z9K2kdIKRiiizATsVHlqRVEcFrErL/FMuSW2UXGzwfJANdFl0JVD7NAFEIIxMAYDofdGc4lFApoLRsD3QLolKpW9K2N8igI++eSTTz75x+QPMdQAGLGAMI9IDJ5aMymvyFC8E84vrxQsWT2oICYdERxrwE5Y59D6OA6B3ZXSdqK3XJY/8f78G7UWqliss6hW4hSY/HS82X6CkrFWaGoQB60JvRegsxhwAXIdBLVQ7jg/EOMQVXQoLTe6NIxZUW24aLmcL4ibsGqw1cMoeBUoK9v2jVIypTXUWNqAOM9cz1/opWHcYRgrqTL6QHpFa2Orjdod2hWpT5wzxPMF1UKvld4tW9+o0iC84dyMH4oYsHbCkuimMroeb3KtwcjA9w4j0zHMduby8sb9dmN7/MSEr6iLWCrBTaTtRtIMDCYT8PZE2R6sjx1jFpZwxtLI+5NWVqyLGOeZ3Ax1Y9Q7xgqNjpeJ3pU8Gm664vtO3W/k/UbHM8wFsR1nPMaEY2vlZqw/0XvCyEK0V6JWwumKmDe2/YNbS4DSjKN3xapDa8bYCWvPyBBy2zAIYzTKc6M4ewgghmFoRfrE/kjsH/8daZbWEqk0SiqkWo7hQPzvsoQTrgZcMEQ3Y8TQRsEEzxDYPn6i/ZAtIMpan6CHTtlNx+aLsWJHY/FnTjFwrzuNwjARtY6XeIWc0RiPnqJSMG5jvi7U3lER8BNDN8bvtsBehbQ9cCJc4+XYaAloXrHWHDGpUWgpkdOOMcp8jhjJjG4wfqCyMzQxxRl/CjxrpX1vWB/oe6FikTDhFKKfkQ4OOf7scByoq1M8A8bxfVafmZY9zh8P+OosfVRGGfz48f/BDE+lgjfUXMB4luWVaUDtT3ovWHHHbdMA4yOhGUp+kvVBiCdwHePAzTNCBJ1YpsgcPaMoRR94ge15Q04L0U/Y/UljR1Cs8XiJlHKjjUTPYCZD8JG0fTCMAeMghMMaJnC5/kdYC708uHqh1/8pXFDm04RLQiEzOIo/VY5NbaqV58dKbplwPSMN9lawdDBylLcCMVhG3vEKXix73gmngEOoVJx6WskYG+lcyfshKVEbCM4jtbH2d2rNDO3Mc0CzZTTH5I8OpE8++eSTTz75R+QPMdSICMGeKPtOtYlhOLofTMBNBkV4Pu9UGfSSiPEEJqA4ZjfRtwfoOyEMGpZ8/xt17FyXX9kfd9xseL3+Z9b1xv74wLkGeyPVSnz5Z7yZUB60dSNtKz54ZvcLwYOM5Tj2ziu571SjzPaK4BlqqHmH2vF+xnpDbwnDEa8qaRzH5Fbpw9F7wUmj5QciCx2D9iezc0xeuZ5e8CaQNNH3etifujK0Ukch1Y6UgbEW08E6x3T2eD9IW0c1gp9+H1oKF6uMtKK148KCkUTnQS07oyvOCm4+U2uiS0Emh7GCYWW9Z3odGANdjjfMYgy5bjzGSg+wTB5nAy03nvsG5sLkAy54xvODok/m64LxM2omSt14bHeExinOjA6pHKpmI3CZJqSBqEX12E7MJ48lkLcEYjDMgIV6g99LECcXfo/xFUQU4848ewI1+PCGEcHHF/a//Ffscqbvnby9o9azTPDLL2881o1iZkQM7faNQUPqgPHK2N4xtjBdXtiHIjah47DlmeBQ7xHdjgHPObyZjgNtF1nmP0MdlPoNOwwMRekM//uR+RSRENAxuPzH/0S+/aRr5ZEaGEuYT6idUFFe3/5Me/yk68awSnZCk0TTjqKIeuiNy/xnnts3Wk8YnZisR3SnpW+HPnp6ga5o62BncloRDt359+83frUz1sC+N3ofYA3TyfH25yvny8Jff36nbSDJM6pHzoeBTWrB6MBgGaUeN11BabZRtWKc4W25ogNKaXRr0QE1DyQsiDfE4Cl5R8SiYcY6T1Qhp8T73/4702UhLBNmWEYb1JxRA6fLKy/nX7m9/501PXgUQewJYxNhPmHrRK8brSTy+DvOLjiJ9JZoqbOnD7ZomF2k9UYMC61X1HREAs43RlC0D9q+YYdl2I4Yy7o/8SHga2PUG+fLV3QNlPLOvv6k24FFqfuTOpQQJkxYGFTC+Yok5fbxP2iiuPkwl7m3V65yJa/vaFpZW6bWDrLxtnyBocTeSLmQSqK432O0U6BqYpjCKU60vTIQDIOaHlgf8GamZqWjPPLKAFwILGoP6+Mnn3zyySef/APyhxhqVIXcd0wwTNOXo3ivV7wF8YYtbcTJEtVS6MynK9Ys5PvOXj6obcMvmdGg1kK3FhdfWHXHlQeXl6+0Zmmj4+cr3g7s4piXMxMXttsHdSQkLMxxwrVEaA9MhV07wzqqVNrsYACpEp1lmiZ6yeAcbgY0o/XQSxugbO2IuthONxPeG7xdyHtFGJSSSS5TrOIw9I8nRhPWdow0unSqhU5Eh8U4A73T1YKvKJm1NaYdjFmwPmCxjG7xpkIq9K1jZIZ4IfNO6so0XbC140wg2BOrHkPLZZ5BwAWPamSJF57rymMv1FHwJnGaTpwkEOZAdDM6PMU0bAiHsra9k25H24a6gQ2RKV6ppXFLHxT6ccfT3WF1a4M5nsAU0vM3pumfMBIZstNaZX8e9qacd4KdcFaw04xYYdSNpju9OGQYattRNSzhC7M5keoNsQZrHF6VJIOeHqgYcutIb8j0Qm8OawKv5z8hYtmGZ28PJnemlk5Vd8RyxDB5Q4yRvL/TrMf7C9Igpe8scYbRSfsDKw5PINaBjsaYjmiP4QIiJPnByBbrPE6hj0E0lunlV+73v+BD4PXLfyTdV95v/34UYG7vOH9sh05mgl5oKL10ejOkfTC2Jz4YMJHWCqo70zmALnQ1tJYQEjhDqo1pfsGaQCkfLOdX6reNn/ejQ2UM5SQOCTMuDIYI23bEl+xieP7YEDMTxNL3B6Nk1vpALNjhEY5hrWNAPBXYUsN5g/iJmQVtO4/yk14q3l/IrZLSijGH6c66hWmGaY7cfv5gLxs9WqxYjFhaEUQCa8vk9RuqjtI8WRRvA3Yo+8dPFj/TciK1Q2jQekOaxdSOcTOTf2HPT55jxRgoY8XLhMpxKyQyIzpQMcdRPQE/LyzeonthzwlLQ/nOrp0YzozS0NGhekZwxHmit5WiG6MJLl4Y243r8sZpfmG1FQkRsZW+bpQIwQfaKMztKIN1upDyhtYdUYjGkRVaU/pITLNhPl3Q1pgnT66OtewQA3KaaGPwbCu4TkdRdZgijNopUuCzp+aTTz755JN/UP4QQ42IkPeCkwAITWHbMtSCSMe7djwoOcM0TVA2bo93Spajf2YOhBh45g9GWLDiWYJn9CPOsj0epFIIpjO5gJ8nnIvUj43cVnrfmJbANHn2NbNtOzlkRBydgbWZOHleTn9i2xJtWxm6gybm6xnHRG1KqXd0DoR4pjwHvT3wAYZYei44A7lsbOVBHQU7eZb5FTBId9SqxLDgotDayjYEcZFoAo4GzvHY7xi/oC1j+0BVSTWxXM+c4iv18YEzAxte6bvHhYhqZ+uDHmdCNMxWeG4/sdazrp37A6Y409fCkEEWQ66dMnZK9dQ6cCFzmR1LCNiesW2Qnj8YCnTDZCNiPNYHSt8YphFPE8446vpgrzshLqjzaIMYXqFXSn7Q/MA4h7EBLwtr+8GojpYbRQvTMmGMYHXGNGHsd4Y5FMhdj96VnDZqzURzwffBnn5D+UC9RV2khithutB6Y4wGDFJu5LLBQ0AKo/0bA+gmYI2jtht9JM6nN2oWcknEKRC8p+6CHYfNjXInjIGlYacJYSI/jxjix/u/oSg+QDhPiFj2utH7Ef3LrZLXghODGd/wdsIYQy4794+/MYoe/S+t8Hz/y6FPJjBQ7CJM0bOVTGsVKEjvpLRjrgErE9AZQ1HRo7vETNghNLNxmif2dEPoTHHChsDrdeK238HCPHnGGLSu2OWVUp4M21ku/5H6/g3rVxgNGUdMShFEHaVlLtcTfQ+0WhgCznhK3XlKxdTBNC0Ec8GNiSCeVAupFVJW2lCsy4iPjPs7RjP8T623doYR5rDQnxW/XBilMxjsLQOWqsJoliHt+FzmSnr+QFVRc8TKnDXsaYU6QBQ73jHW07EgHjc6LlhcrZhuqF4xeCScjk3c+zvr/UYRz+Px5JEaguB9ZX50/LIzOc9yjrRcua+Z2i0+BGKcaTlTy4PqDknC7APoYHiL9Eq7vfMYP5lPkdkFMpUihfb8gGBRD8Ge6PdKa4nhGs6eSHvFxEMIMkThdHxde694b5jsQn80trFhxo7EI77KXnnu7+jnUPPJJ5988sk/KH+IoWb0QVWltJ3+/b/RW0C6w3qPnc/484lGRcpK7Tv3tTGcx50dYgetrqRq8PaEHY4xNlIqOGfAw/32gWpjiZ4uytgrW1+PuwkUcR7kSktK70/i9UKpCWscMTrM+P0GZz5hOXPPg23/gVfFmk7uh05XpsbL9QtGJh72QXGd3hpGI148Vj0pJaoBEcvJRaIT4nym5YbMQq+dlAepVebpFyY7H4Wd/UFJBaOdSYRaDL3s+JMjLm9EmWmP77S6UVNDh2CNx3bB2CtODVPIjG3nse/UkqimI6MzLZb57Ggp4YJh3wo1FVCLHx7nwGji+VRWjm2ImuOWyA6HKYX4eqYr5PqktSfn08wyn+h5p+aMjQvYDt2SWifgSG2l1Q3ZE4EFcQt7+kktD0rZEG0EGcwm0n9/6NNeqfVJfLkyhQlNG70/KW1n9IaanUKh8oNuYT5/wTfDuv1gaMeEM6OD1UjA0rRAE8xopNFQY5iXVxyOWizaPXVU3HSm5h1n3BGtKgmxgl8GmYbxM7UXStpYLl9Q+6BLpjkBEXpJdKfM1xOjPxml0+0J5ydkdLRWiJ5eKzqUvT7QXrFyROuuly+YdmXdnmyp0UrBd5hMRHJn7IVmO9JXTHhwOf+faBdayWif2PPfKeNGiDPRv9L2FWzBVkNtmVw9j/dvBJ3p4jF9MEZCrMUbg+kOkYm8fUPknXm6QL9BaViz4l4c+70eFjSdyKngRuckC63CXj8w0jHecDpd8cYw+jsiFuGw0Q0qRRLzeULph6kOpdQVEY+JE5N1iHrG40lbN8QJwUfqyIgTonsl7kJu9dAThxk9Q8+Zlu7UsdL3gnfCFAN9QNWM6s4YiWg9roO2TlrfwQrBL4i1VATWlSmAlYa2wl53bBDOk6c0g6RBfVSoDfPygjiHDRVXH+S60VoAEwhLwDYP+5NmMwyLI5ByolMRD+ueud8zwXnc77c1Xhw1W1priPvAypnov4JLmFhwMpHqxnwKaHsiWpmXGWe/Uted7f3Bvj5oteCMxyahtp9M08yZozPok08++eSTT/4R+UMMNcYIL5dXcu2kxwNPxbjj6Dp4cGRq3Xn0HWFg5ol4nrFd0OYwwSAK2+2dJgW1jt7BB6EOpbdBCIY8jigX7ow1ls6KdkP0bwwvlPLOcjkdx7tdcUGRvoExNLHs74/j13o/1Ls+MqQwbKMbZfYn6rYiNnF5u6J3w/5xw+IZmml9EMLM2b1S0gNDPz5GM1PGO20IQ07U8YBWKB9/Y9MjEhLcAsNjjVLyHSoEP/jy+gvWLow2wHRKTvTWaT4wRiIMR9A7OipdxxFToYArGOdwMjj9eWb2rzx/Cnn7oOZGzStiFOc8PnhyE6p6xHiMnRCJWONwI2HMk9P5Si6VZ90ZvfC8JUrZUFGMcZyWF6x6nts7vSo/62+o6Rig7TfoieELvWYUi0jjPC3QOvV5p1uDWH885JvDlmeN0LXRdSf1OzBodiDOI+cFtDNaw/ZILY0xhePB2givX/4Z5yL7+oPeEzXvyIBhOqWs+Ph6dJWUD1xcGG4QQqTuCVUlbxt+cuy3v4AE/OkXCpVRN3LN2OUXVHccg94qYyiFTnSdECdqLiiB6C4E2+macC6QtxtDG1Oc8D4eRraU6F2R8T+7awTrDWV/8rcf/44OZTp9OYYnWbGTYGfBpE7PD3oRZAjBGpwMgu8w3ig5k/YPnAlYPK4Z9tYYIeKG0GrFTR1com9/p43G0ELd/kY5TQwzCHEmpycuOFwMsFcWb2lj4GeLy4ORBgGPnSZaz5THjW79oVF3Af192PXxhPEO5xtGHVZmrAuoZkww+OWEHxNtXY+hUgQo4Ca8ObHt32gi2HDGKYzeiP5M14KZFXFnAhN7SWj73X63LEhzaF05hQU3BNsGFU+zyugd2o7rER8dpiop3yg94bywLIE4f8HUxj0/0LNFckGNpW7fWfUJxiFjwUgltZ3xnjAvDhcmrHeINjhdMG1BPv6NZ1nZR8fYGVQZpRPFY22DqEcsUyfELrxMZ1qxwAVrdsQNFl7o+8owjTwa6I43FTUeWSbCGL/3E2XUDvpWyeWJCx4+b2o++eSTTz75B+UPMdSAHpEuDBJ/bxIfjVohrYn+7BhrWJaEmyfmlzccF6QoGixlfeeZPsgWEIdXg6dj2mBSxV9miJGcFLUzy+mM4KnZ41FOU6TVJ007exmI97jLG9YvRxkejsf3/0Hd/0KvhRY5Ng9qIRxlnDRLx/LYnvhpRpMSRiRZIWlGtOGnGW/NoVk9RYZUahG22502NoydGTwZWwLj2eWJWkewZ7Cv0B94q+ypM2RjmhfWtNLqHe8sxnlk8hgMjIpzV4zz7OM7KooMh7iO6sCIxy+R0TuBE9KOh9jSBxojWIuKI5tMJyNqWdwFaxaqVnTsBBcxfmBtZJo8RpR9UzrQjND6oOvgvExMPrKtT4wIp2liWIfOM7Y+aY/CXjOjHNsxQyTEM3E68Xz+pGjCqscOT/cJpWFQXFjIz3dq7qg9YZyh+oD4mWgGs7Pszw9+lBsjTITTn6Gu9JKgKa3vaM1EOx03Sqp0LKlZ+lhBMtYHprjgpzMxvpL0A8Qg+wfNWowRogzs2HFuoTuh1RvRvx1RNxEUi/URbxw8d/q+cQ1n0jDU/EEpA8rgZlacVZb5DYwyWiPXyrZv1GEwFsQIai1DDDKfj6N8BiMK1geMXhm+cVt/MjOT2v77wHR02hhrGIzf/90NjPOMalEjGDvRa4LWqNbS3QXLjtQjombtOIolNVJ7xQ5Lbuuhnf5thaZHwaW6Q+JgTywvM7V0zLgwTAHv0JaJ5ze8CZTypFuh24EBvHtFy0/Qgj81vFkY5cqgIKbRyhNvHWosY7KIn9mzEMZC7YZSN87XM+d5oa4Z+oNDbnwMs9eXX4nDULbC7ec7e31ivKN1jm2PmTFYrBR66EzhClti7DvSoOoLwwmDQG9Kb3e8XzHd0GulTMrrL/8BUqaVv/GsKz1Y4hLx44V++0bJDdVGCMpy8czXX3ASyc5wuv7vyPo3XH9HxWI5On+GJsS43wUqhjgNjJ0YpWIpFH8o731XHDBKJvcn26hI+IXmHdbD6Z/+d2wyhB/f2be/gBaKGKrluLsxn/azTz755JNP/jH5Qww1Q5UaI+78yoSlbE96eVLGA6zgiXgH8xxx04wrgheLts5W/06lEKbIgsUaxyiDkp9AQg0YnZBiWbQz+gOfLI5Iyz9pvfLxHCTTETOjeiVK5zJ94eJfkQr3+1+hDYZVdmM5Xa+8zF/Zfn6Q+h2nkdoHXevxoJZAtx+o7ZhlQnZFWjusXtbTpGCM4/mx0+tKrgNnBi+vM6fzK7dhGFKI9gVNlWW5oK2T26AnoYvDxAv3UrBamaylB08Wj5oFpOEC2Hgl1w9uZTAU5tH4Ms84F0npSa+NYI6G9+YUdRPtomgzNCo4h9GEqCLAqBsSC9M5spzeqLcba/nAupn3+7+jGGyInOOfDiFCrjzyjdENt/s3UloZI2HDC44JLYoZSlj+mXv5gfcBbwMjFTCOR3o/Ilv+C6YppWWwsCxnVBvPxw+6CeSqh63MeDoB0y3l+UH7ve9j0050E04dxr0xePDx/e+08SQ6aC4g0wmMxWhEhwCZMDlGyxgBJ5ZlfoG9saYPLr/+n2AN7f2/4UZC+47DofuTLvvRmWIdhgkXJygCOSPqkTrobae3iirU3ztFSu9YHzHRE8yZtfxGbQWxgXXfCNeF19dfCbrw/u032qi40yvGWTqJJo1eK7Ypfd0wk2NIwPjB69ufqDmxp5332zu1HEOJ8yc6Ho2RIQ5NlVoa1lWGWoSOOIsxBhPhdPnKL+f/wuPjN2pO1L5RRyGXQeuVeVqYgyP4BXpHbaZLopoI4lBtdBWMPyNmorX+f/0vZPCYZuhVKNuKUAhXjzWO/ZZJ2414mrAitJyhGuS0MMrO2jutGSTMNDsxnGMKC84Z1nQ7bntao+0PnEYkJ7wet0xruuO8JS4zczxjd2HfMsadcNNXvBHe27/SNCFdGCNA8IzeKXsht7/gw0QandItEzd+Wb7i259pQHfK65cTU/yV1+nK9vw7Se8MdaRUGN/+HR+OLijDC0tYMC3T6eACtVWkgp8mgrvQtk5bMyJ3alfAEZzStFLU0qyhtI2t7xSBMe5oDoRpJv34jUv4yhxPxHphbU/iSOy9s+2ZoZ/xs08++eSTT/4x+UMMNc5Zvs4nrJxoI2Oio46Z4RvGOwyADBIRtxtMeyfGFbERHyJmOKyxWNew6lmf7YiUuIAOC21Q5YaaRjCOlp5svFNGO9TQNoIsOHNBtGH2lXL/dx7mr2TTWdsG0plOE9fuONkr9eN4yFJTwA1mGxATMWNQu7L2o/PDZ4+tE0MjTQvaKlvOjKqse8ZLPGJVs8Ng2B/fGDIYOTPPJ16+/h+kVLk9//UY0IxhiSd62xnaOfkZcQOVwdVfePYfVH1i56+HjazvTGoIJqA0ns8nPjZCONGKomam6cLtuR5N61bxUsAWZLJom/H+lb51tJQjcjMtzMNSasJZy2l+Ie07KgFnA8E6LBP38he8FWKYSami7gzDgF/Q1tG0UrQhxhDscbxtjGX5039k3+6U7UGwM603WutEf8HazlCwxtBax0og+sPeJGPHWM+og1oS3kf2siEoMVikJkou1L3TO6jtNA6rl0kry+VPNAL9/ncaifPbr3QjjK7kdSU9/5/Umqm98MvXf8E4z/v6F9RZcB5vI6NvjG7oUrAN0Mx8eUGNUmpGtTNUyLUweme6fgEDaXtgh2KGUNcnZnF0rcT5xKxy1Ls4SxgQDTg8Wx3UfifqgrF6tNzHE/RGGw0fHKYsjDEo205JD0pvWPdKGztow3qDmqMPxgeDb471uWOmgNGKsxaxx7B1mhY8lm39hhWDu7zwev4X/v7v/y+yaajxqHqsOdFSpZRElUzJlT5HTssbNe3s/cEjVSYPIVpGrcf2qO+0bhEq7hyROVCdQZxFR6XmzjCJOhLaO4ELWiLYioudkC5UBR6JcXJgPdomXBXc+Rf2x4P9/U4VaKWio+PNsWGsJZF6wc+CGFA/mOOMbU+sPzGfXmjBYtTx+PGTlnfcacH7N9b+Th4OxgxbYq3vWLviTeCyvFDak0nhZAbZFUyc8Ebxy5X9uZG2ByMXmmn46EgUei/EGBBR1A/C6QuLuUAt9HmnW9i2DdFBA0YxtNHZWHHB4r3D+BMzhi6C0rABPI6+V1Le6WWntR0ZDm8CzrYjbvfJJ5988skn/4D8IYaaMcZhYTKJVmFbE6KdeQYdig/HG10zDNZAM4ZuOl4FSYLRio0Z7YPH9iT3SLWOpIJ1SneNDjhjUTMzwkyMV3xPWBux/Q3pgVJu1O07vaWjMdwOineIcURrOdszbayUj99orTO/LigzQw1mVHorlNZRM0N4PbYH9o15uZDz7SiYVKjD0sqDcFpwumBkxxnDlp500zBdiA5mOrJ9sD1vYAdzjHgiJSea7JgQWVNmkHmZXnBrgjKQ+YKWQk5P4oh4e4F4Io87DsWoQXeD9IlcDW1sVB04U5gvhfN8IhfDfL2wfTzQNKA2RAZjV27rv/GhHVBMPPO870gb9PbEuTNPhKJ32uhMDsiV/lyxcWKaL7iu1JIZuaAY1HbcSJQ2aAa8FaQN7PC0lrlpwdgzFk9Kd7CdZfmC2Bk3BtfTK2U3DArOGqoO+nyhj84yL0cxYrnTzQOGA/FYr8jJU3tiiRNmh5E2uu5Y57E2MrpSqmKsQ3tnlI2hmU7j/uO/YoxDrMVMkSlGTIGkFR9PYB3BBKbhybd3tu12RCqtQ0xADFAHRhwqgy4FZwNmQN93sgqDY+g5mTN1vZHrk/zxF3bx3NbMtidOpwXTK6ID7wxFGzlXlhAwrVG7wcuJbX0n9ydNDb1XrH9F2oYLkV7vGNnQsjJEWa4ewwCxLNev1PxgtMz28U6Mjjq+oeIQazj5P2Hxx8bNn0BhXxOijVEHxVtkXqA/aGoR6wnx7ZAwlE61D4woaCZ8uWKNR3rHqqW0G0ML05evnNho8sL2WEllRfyFYb8gRIaLiL9jqsd0xdkz+8/f2PuGdwujNELaOV8v3O4/qWags6XtBfWCCS98jQvl8cF6/6BrRwLMWmkNVO6IPdG3yvwaiF++8v22/m75E8awhBCZpy+kx4NUdkwUztHgm6Bj4+NjpbR0SA7ChdENz33DeiH4mfHoyFB0JIbdGNppYpDuKR1qeYJkyprAVawz2NDobSBjUNVTZGaMyNDjJccYhzHOOYeLF4L1GDakV4RI1ReKdMrI+OEIAubTfvbJJ5988sk/KH+IoUYRclJca2x7JkvhcnYMbZhoWC4LHx87+/OJ6xUjStvBmoSoQWzBmDO1tmOoYMNp5ewCEj1qI+I8XgVbAtKUoRnbLUY9Od9oo9DliFnZIMjUEeNxtcBo1ObYRqNhQSunUyTaF1Lt+BlqVx6tIt6ixVIbiBhqd1STIDbCEKQJfSheOifnER9pO8hwzLOnSaWOjm2ZVDM/b99ROi+vr5zOkfut8dh/YoIQxaLMtB7YhyVrIpmCFKFvRxzLLH86zF31NyZNnKcT+Vao64olMNwEIoe9bd6hKymtWO9Y3/9Oek8YtYf6dZnJ243SdowPWDMhZmHNlbFtuBBw1wsjJZwzGOMZZOx0QVKl5QfODiSeqXjUO6RnrO+0YUk1001nTxujghKQuBC1gDZS+8GoCecdzl4I9kR7fEd14OLCnjK9bMTpgldHrjvaOyLH2+rGUabY/I4YIUwTrtsjgjd2no9vuHjBqGDtRK4JsfHQKEugtZ2cN6xx5HzjevlnelfKmqhbxYswRicYDwp5uxHjG8FO3NsPtv3jEEWcTwiWahPr+gPrLHE64ecLuq7EeSHlJ0UT6+M76jNt/UC1gjTMdOLycsKws4QzxmbauNN6p6iCMeTcMFLoHYYcnSRJQXVgbSc4Q6t6RMhaIQRP65UuhjmeyY+f5JrJvWOMEuNErTv79mAghOkVT2BvD4r5/ettoU6BrgqlYaZI95FwesXcb+zbhpoZrRbDYBhPIxAmPdTYXVmsYy9PhjhGgaYPwvzG+fVPlFqY3Yn0/mTVQtMnRhtOHNZMYB0t7WhfMTagtmLGStdGuT9I+Uk1hmFOxHnm60m4ffxEq2HvA9ci4oTOoJeN1jawkVyexGlHxsxvPypBDPiCtYbRwaillUYaP3AGeghs3WLHwGCotfHIOx8pE5ZfuMgrUs+gcpTeymA+OfwmPNcn3RlCEMq24e2EE8i9so1M75mhBSeR1js6BBPA60B6Z1CxLePFMMzvfTzBH8KFddByJvV3jHgcM4YZOwlG5binkU9RwCeffPLJJ/+Y/CGGGunKWBtbzagR5mhpuTLcwBtPHxB9oFVHM4U+wInHekfqHSsDSRtoYYkBROm1Y00luEi3gb4nnCpQ2J8ZTMS7X5BzxpqC04G0hPMRMy3Ml1/hUfnI/8omndkGjLXMyxtmgfR8Z98Ky2K4zr/y4+83rAQqlVTf8SHgikX1AbFyPp3xfSJvGescurwgZUXSoWfdzQ2flF+//hO9dvb7hgwFAesE9cqPXLjXgZ0nzvEFw5k+Ao4H88mT1x0plVYH2g3LeSF0wSUwuZPbepSTjo5M0IeQ5SiF1KnhTieCFazpnE5nnu1BN+V4u/525tcvf+bjY+a5fWBMID87qZdjcxYjEo+HcS0rPXVyL7z++gtWz4y44U4LajvDWvSx0hH6smBtxwWHeRpmG9hzZyuFabqyhCtz/TjuKNJMKwZjB2X9SdYnA0PPhZp2WjukBq5mvLWAUvPOGMJ0OmPNCcNhGLtMVxYsZTwxbiLZQR0JLzOUJ9XccJPjfHllVMfoQoxnZGSUAcaADEreeDx+ImJYphkdCubQMud95ee2IcaAV0aF7gUN5lAMu3yk8TQwjYGmG8YIximax/FnbB+ozYy0goD3DS9nvnz5F2T9jbrdsC8X5vgV7TdEoPWECDgxeA9DC10rDAsNVDcQh4xGLjsqR8vM0CPqZVCEmV6U3hrVZd5CxE8T2h3SLT4seImMlplfLrgw2PrAB0vwAvUF7ELqFa0DJUIzmHACJ1gPLjpGu5LaB04KNSXW3LDi+Ni+0RCs/Er/ccf2hLSVeT5xPZ+Ym8csC4/vv1F3YfnisdNOWTN7qqh5EE4GxOAnoVVlGysjXDDOs5VGdO5QRadCNkpaN6rs1AD+/AplMATCcuZZv2HGDU/A6ITzx+2ab4neGn2+QHCc1NDSSpOGzRENBj+94cpMH4O8bTj5gXsK2jNZP1CXsKczZnH41dPKIFVDl8aq2/Hv4zoj1zd8BfaN7gqYSLllQh2IbbSeGb0eMVUM0Tsme9jSWHdaN5T2OAySZpDbyuiC48TwniGHav6TTz755JNP/hH5Qww1XeGBQd1EdBXjBKYz8XwhqGOUHb9cmDTw/vEXRh9I6Gw1gTiaGqIZvJ5emK8vrNtgXxWRzKDR0we2K6NDKp2CRcwEmpnqhkd5pCfiGr4rJ/mKe058//igGk/oDust5/iKVcv951/QmpDwJD0nPm4C5oPX+Y1WDCsVMwpmFhgzOoRYHNv2AAentxfWvfFtf1DrD5xWjGtcwwu276zlSQrgcDh3QaXQwxnhhTjuWDvh7AtmAFoJs0HbyrolNChuPtHryrr/nSx3vH+F/pNSGiZY/OkLdYdSj0iLmRbi4nlbztT0DkMhNdLHnW4bnC9YM3g+vjN6xhjL8/lOHmCcx53/iclMzNNE+3inFaVbh3Ew9sGzfXCafsGKo/bfIBeaVnpc8FGQAad5prZOrY3UD/10yn/H2Yo2gb7jbSS+nCis1D4QGTRtLOYVGQXU0FF6zVgmtLdDpVw3yI1l+QUjBm8cL/MrqpnWHfNyJtWBq8dxP60gEayNpPUO6uktczm9oX2l9wrWHNFIN6EoRyXKiVErcGistQ8qHesM8bRQ+okQT2itxNMVpxPb9oEZxz1E743z6UqYAn3MlEei5YwNHqUzegEjuJZxfWX0Jzn9RMyKOU0ox8c7esYZSy3gvGeeTrALxnr2lMi2kVURzmAUWqLUHbWCVmBYSq6EOEHuaKnstw9cUJbrC6+v/8L+uB1lnDpwboFwRXLGaobHQJ1hijO1ZZxMmBhZy4Beebm8EL2htDtMC7V/pdwT+HD0T6llNspP32kmQD/T28D2nVp2fK44mbnowuv5C9+/v/P4/mS6An6gRRimHyWczhMuvyDbRi4V8ZE5nnBqSfn3r6MYYoskLTR7JY9EzRvX5QRpMPogmIU0MrSKmxJOIlQL1WGGQOmEeGUJC5aF5+0v1HFH2hFN9HFGpkh6PCn5OxrPmOqhWJp2biURpzPNB0orhzVPAl3A4hhJjjLRxfPLl39ibA9aMFzcL+zv33k8b2AqJljUTjRrkK7MNrAsx73g87EifsGYgdWOxgISaSVR9ifJv6H6uan55JNPPvnkH5M/xFCDAQkBq47pxbEsJ6zxmFIxbcXPC2lvaL7xdl1QDZRSGJKJ8cToEEnMYSaXQdeA98qgYvwrQQa5Pcl1Q+yF8/krdiRG/WDbOx9pYGwmDktOlXr7C8KNisWOiTE2bM08y99oOo4D64tlWd5o90bWldGV8XFYpXpL2BeDsRPRBWqvfNv+hkSHt56fHw9SKuSiyGi0aBD/Jx4D8uM7cYpMbcZUT5eOeOVNFtaPgkkDs3iCDB7tG2M0Wo60lNAw6MEzRUN8vvJxv2FOiRYGQ94QHxAH1p3wi9D5RrMGHw1fpsjbNfBjV2qufP/5G8MHzLQQLi/EHrjf/4Z4BecJX/4Jm0AkcZ6u9PKEfeAIGD8fD8h2p/YVjGMQaOU3ar9TigUTkWEgK6qW++MGYWKYiG8BHXeYPN0ZpuXCeH9S6sfxNp3K6XwlWstolZqe5OeTwhO3nJm14Gpl64GBpetKR1Hp5HLHSOf7418RPxCEeutYFSY5HlqXt1cUJacHwUdgICrU8kGI0KqDZuhbwS9fuF7/hIijlJ36/I6RCT+/MnRQtUC39G3jFF745Z/+H8TWKXllWk483ImcH0eJ7LoS/YwrkdGejDawcsHqBZkcqW6sbac+V/bHb+R+x0wOtUI3IOpwWhEM3lpaF/YtHWKC3g6t99QIPmLEMEpGO+iAVgUcSBgYmZnOgfnlC+X2gW4rqhkthpELYjgO5p9/w3qH9YOSCmIm1DqGc8haSPXB0BVjG1qUy3Rmb4Xbj3/lcgqE2VNbYY7/gTYW6v2d5eUrlI5t8BY4+nYeO6kNel/QBq02WvRofjBN8Pa/LeyPwtZWTDAsKI2FeT6jtXKKE3++/jM/fvsbdzI2bywyA8KzT9RRmEZFQsXNJ74Yz+P5wf3xG3Z6I3hLrBdqVawxeG9wo6L7g1x2LJ6pXLG3nXv/H2hNtNZo0hjOQp1wZsE05eV6Zk8DJsvCFf/w3PoJxkBwzL7D3kimcTlfoHmGswyx2G1j1M56HbycF8b9Hec7p7cT013JIxFPFvVn0tYYeyJXGGll+IphBRmIPYG8ICOg00w8L9j7z2NT/jnUfPLJJ5988g/KH2KoMcDbJSI+sATH7C6k9UEv7+jgUA77yrxEajbk3GEUjGa63DF+ItfCt9s7amYmf0XrHRsXRvaMDLUp4gZBL7itMPRvVGmImYiLxxKgFmq2aK+0sf5fCtr5LLgYSLUgvmC9w7kT0kBlUMbGGJmsESL0KVBEMVV58pPCsT2ZXMDJieYcr4slvn+wbt/xy3/E+gtFf9ClMJ5CKw+W6ZXz9Y3H+195/7dvjKoMU6hd0Ham1YwTQzATTZ7HkW/asX0w9ok5GHS+omIwZOLyhlGPGQHrC+cvX5jnM45Ivb/z23+/sW8rIXgQR5y/kvs7LsO2ryR1uAYuwvl8oWqht8HYv9G7Es2/UFuimCeEgtjGGIKqhfHEmYqTK6XCGAbPDJwYZLr+YNQNVwOuKwpMpxdciIRwYr15VFesh94V4ywuBMbo1LyxpzvDVubmUDHk0VAT0NFRhBBmTpcrdS+01tjKDwThPL2xvz9RHXhnGX1wvr5R9sZeP0jlHWcuzPFPeHtnnh37NqjtMGapvaO045tYDHY6M53/GdGA2W8wwPiI9WeiP6G10PqgrHfKfmc4JfoTva2I9dTnSpPKVp4MOmYM1ud3ZBp0Y0lN4NArHEWVNh6RI8DGmQFH51NvtDYYYukKNgQGneE9zi9Y9TSntF4ZHUQEi6eTaa3joifEQHz9QiVTeqDHSDWBH9++IQrL+StSO2W7M6TjnNCbwVhzbKpyxXih1ELdHoRTpQOpr8hDeXGGUp/kCvPbL7jHRCuDPjrdCro9cO2B2BNTt7SyogyGO2PjFaaJalaMfWKvMyHP2GnGlc7j+YOSKl0F+fiB/aIEKr9GBSNs93f2+kDmX7gOR37sDBvxBkTBmys6lNE2mvOcllcu9gW7ZfKP74zzmfOXX2ltI5cE0nH2ScmZtReaUbAO0c65DYZm0rrx4XZCnLBbYTXfaDqIIRI0kvc7OzvD6CHT2FaMcZA7wTn6qEj16B4owWJPV7w5YVMl2IxqZqwNDTeCtaifKXtm4053SjeKOIMvUPqOkRl93GjmA28gSD+kGp988sknn3zyD8gfY6ixhi+vv9D2Rn/sJHMjtye9dUTG7xn8E3mDNna6HaS+M7ThXSBop+aKMzNiV1K74ZyH5Olj0MzMmIA2WIvi+jtoQpaZKZ7RCr02tAvWCbtM7B18qLy9XXh9+0K6faAUMIPaoOw3HtwRHN5H4ATOowKlrVQ6QRw1H3EoVxJuNvgozHFhqoHWf3CaF87Lr/SaKTowLSK94aaJ7pSSCi0HqjpYHN18YNzAtI7USlfDo32jtBWHYbJnZAicCqMeXSRGvuMJBBGohq38hflqcFaIxrJ/3FnvT8pe6FrY2476BbP9FSvCur/TooDxjLQfdyN9JYwXup2xthDwSC2k9kGzj8P8FV6OG5Q2yPl+tKznilXB+RnpO04chRXpildL1IBIxVjQfGeYF+L5BC//zON9R4zFjoAh0HPl+f7j0Habo3Ol2UCX3w+encG5BasG64+BUoHaM2hEmmNkBVWWKTJNJ7Ytc//5HcFiu0FFiP6MUaEXeOZKnF9x04Rwo7Qnra30sePnC/PrmZe3P+PGC9I3bunfMN4zzWeMufC4/cSKYfRKL5lGxVqPN47eDNqF4Rvqf8GzomroZcOo4CVQjWM6v7G0wNg7pTY0NLQrcfrKl7f/xONv/51tf6KSENNwvz+od4ElvuEIx0bqdCU7y2Nb2WsCjliXOlCrrO8/0bIjLWOkMV3eOLk36jP/PsBN+MmQUySVH3jvf78FyhTfoVQaOz4udBq13jm9fmG2F7Zb4X6/I9ZT1r+S5BvOnbAtYJ3HLV+w/YU9/0CNHBvNXoHC0ILZIJp/xriFlN+RmDn5K46AOsvafmJtP3TU4Svr95W+3XB9EC9X5DITV2jliQkBGzcaEe9fME2JfsPoEf30vRO3O6E1ulZEBF88fSuIF6bpwqg71guX6U/YXChloNqxxtNKBangBmItqtArrGPFWo/sg9YVbzpmWsjSsWk/ynmdwY3IaBsmdJwPeGfZ7x/E+UShYJowhiM3oY0GI2DnwnSaWXzkcTeIheV0oqVEqYd1EKk4sWjKNNMwThDzqXT+5JNPPvnkH5M/xFCjqvz47YN931D5iVrFmEh0kVNYkK6UWpDFco4vpD3Re8f6E84Ees7IMHTJOA/GRuwIlAHVWEbciUDOQuKJIWObZ8kOq5aqma4VYxqtb4yuxKCcryd+/XpFt8IjbdAKbQy6ATXHUa1zZ6J7YeQHdReqHYQpYtuKHZaxCtTC/KfA5RSQttG3RiEirhDDK33daS0BhZKPqI/vE9Z5CpXhJoY3lPogTo6X+CtshZvf2BWaRkI0UArZXWAqvF4W0u1ByXdElNYTDdBSye0ON8/5ly94/8rHqDQJmLDwlB/I7FEFOzqLf6P3DFumlow4QbIjWUs1BRctv7ycsFQ+7u8Mjn6Y2Z44G4+bJ563D3KHMcAayygJ5/0hQNj+ftiX6kBaZV5mJESeW6U1i6rFlMMolsdAxfPnr38mf9zY7zd6LdhpxlqLmEGn4+JCcGda/gGqGJHjAHpYLDOjPQh8ha7cb39hnh1z9ATvkMmybpCKgBqsUUr+Tu7HRkXjBMMx0oM0bog6rC6MsVJzwhilrL/hvedy+YXuVpydqa3wfNzQoSyXF1SVPX3QdQCVGGbEBDCCkYCzr5jRj/jd+U+0/E6tG6cwcXYz0TiaQP74gXGD6XLB5oz3jcVf6KUzxsAFjzNylIGOQs03Wh5cz7/S+506bowwEBMREc6nE7Up5Ezvg1qfYIQ4OWJ9gg622xOjgXA54V6/8hL+C+P7YPv4RpyvzNOVZJ/AxPbxTi2J3gYqBmk719OCrrCWhJ0MozSa2VFfqMPQ3gu+nojLnxF+QZ+ZZ/0BOrBAxzDqd/oOeRikrtjk2PTfMKczi39DZGG0hA+KkY14fiPXncf2kyfKfPkX/vTr/0768ReGzbAsBBSzTMS2oLeOSoVqCLXTa2N93mhknPeAx+2BUjZ0CjgRmhrcCJwkMttCISHB4+YZ9idpK9QCJg6oFWsDfgRwSikbHof3V8QNmnp6eVJto1pPHK9AoRohl0JvDV8r3jvGaL9HEE+kBrXvBDto/QezPzHFE9rAaUBng5NGt0dnjVHDsEJ6JLR2xvgcaj755JNPPvnH5A8x1IwBP9Y7Kk+uZ48znrJVyqqYpNjYUQcyQPeBXy1RHa5DS4U2GkkdrXvkWRGBOCnHOcQPRmqUarDDMDOxV0cfGdPBsIOtTCfPKXwlPVdcWzHB4zC8/+W/0XIni8HPJ3x7QxhkfWJGQUZna5XahVIz1B2zpyMq4gc6WeYvF8LLC7l3kpbj97dESRbfDLv9YH6d+XL63/j4279TSiJ4h5tmStuQlln0hVM8YzyUZskYkr0wtkxwAecGiBD9jdflzGURRlZyVVZgWMPsJ0rOWBeoqqw/Nnz5DpODtpDiE2MDLy+/wj1T8xNB0egx1aM544eHYchGGH0nasBJxMnpKB8l48Wjz43VPZBgqa3RSsdZjsN0tTgdzNaSjAFVhnqsVEbbWZ93mmwYmSHdeJRMLit9FKI7M3JmXx/oGPg4wfnMsBN+dExNiBa0ld83JG/0slHyk9/yf2U2L7Se6eWJiMM6wXnPula2vWCwqHrEOpydQNvvYa/DhEUp5P07lR1jzVEE6i40CkMaOVXu4webfaAcLe8MT+8K4rDOEU+vmNbZ1m9Ib9SekSaEaDGmIkOQsR2fl/ST5hqt7Kx54+16JmijrSu9FZRK3xvZbVgcj/vfuT8/6H3gjGWMQu0FFUFEqSNhjeX5/I1SV6rtiPcsPh6iggh57Nw+bsexfdsRf2E+v2IVPj6+U1rDaYf9B8IHTU+U509yWZEhxC70/GCYoxDU2Yncdmpv3LftaK0PoI9O6TfKGOgUsd4SlhPiMznvWPsg6gvbWhBjicuZnj+o7Kj1VJPp9eh48tbBKCQKv3z5ytfrmfv7g7U+qPsHxdzotqLF83hU8ngwmVe8mXh8/J0snY5B5SfhPBPPV56lY2mM+8awhxpZ26CbwG4DUge2eiwDlUbtFZWN3hqWCWaPXwzTsGy7Hlay8AYyQb2Rc6WpJUwOd3YwGq1PBH8F/52iiaGNafaY1vFmplmPBAtlxfmAdIPmG90V/KI4c2JLMHJnmEYhY50l5Y75OciScNZgo8VEg90t7Bbpx8ulz/TZJ5988skn/6j8IYYaUWUyG8YMpERqU3KBbjNZErNYbHXYItSutJFpJMYwWLOAsZgRiC7i/JloI4aGtowqjDaoo6DGkRuMYVHjqLNHLy+YdMOMnX3byGYwna64Ybk9btSyM80e6yLSK1kfVOPp1UAy5LhhwwMr8SgRbInhAmH+D0z2hLd3zpeCnyI/fv6kpsLiLX0DSYnkbvhzYOZK3hKNgnMCUo6jerPgQmSZzyyvX9m/fZC6UuoHRjteV2xQujEMvWKoDOk89sw2oMcTswZazSw4NA6ifeP9twd5NPzlhuNPqEw4uxHkzNgH697RcuJxP974BxdZXv8zOgrr7d+RkYmnCbXKXhK1dhKGVhMlraSq+LPjbM44Nbxd/okxCs/yHScwChQH1XWcv/B2/TOP739je/ykUCFGrFRaL6z9KKac7QkfHZnB1pRRO9M8YXtAxQMWlYauG/FlYnl94ZflP/Pz+1+5lU6TynAeb8+IfTLUMJkLzgQeH+/ElxPeTYxesXZlulzZHj8RGTjvGH1Q952SH2iE2Z5JUoDMMIr1MzLGcffSOWJxJWONJcSvx+d2FNLHcfMAEyX/BJThhO4sDYFWMGVDtaFa0PyDVhpaMskO8uxIWilpo1vFusC+r7jzgp+/oulOKitGhOn8BXHC6E8Ws/B8vNNGoTIgmN+jdxMyPMNYjI+4PphermhJ1F7I5cH9MXh5+YK1Dnu2BPXIeNDLg5TfKW1graOWxL1nsIfCOpwm5uXP1P0bvWUea6GJwU0T8ctXJD3w+iS1irET58sLwU6s33+S33fUf8eandlyFO8Gw7T8M34EZCS67WQRujEY3lBzpu+Nsn+jPr8x2TNj/hNoZTUFuzjmR6ZuGw++YYfQu0NoSBUe5SftufIlnpjEMvAMjqJQ5yImHNFGrZWh7pBd4KhqGHknRMWGQ93e7yuijqGG3CrNVIZmzFjo/kzhJ7YmzJ7x9hdEBC3piCHWjFphnk84EUxN9L5CODGNM4aAiwFnZpSZOt5pRg7joHS6DKwG+prwC4RZaa2ju3DfVwJCjyeMVUyrIJ3h2v+tPwc++eSTTz755P8f/hBDjbEWHwMlgbaGCZ6Xr29YH3k8Pih5O4oNZaIxsFGx9gzaGaJIHizRYqeI5g1fKwUFO47iRWOR5QVTO6PuEAbn84nXywv6TGxp5cGdOL3i7EzZCntLDOPxrxH1nrJ1aikIMEtkjIV6MiyvlsldacmRxwcSB2F6w6qg6a9Yt9Obw/XINXzh/vgr+/MnrYOJE/4UsCbwvD8gHsNa7/k4vHcnXuJXTNuxI7H+9je2+zvVFeZpRirUyTJNFtsX9j1TpLFq4Ty9MPUZQ8FFh5HA4/5X8sik3o5Y0ylgTi9YnZG4smdF1HJuHl8afU+E4cCemU5fwRtS/klujuXFcH37Z0wVGjtpZKp29jrovbK8nJjjAgprXTGuo9Yi54WgnvLYqM870/IfuIQ/QfPoCKTa2KPBodCV8+mKDqAfN0Dz2XM6/UpZB7f370fPCBFJGzUahgn4UQiTpzxWPtb/Tu8Zaw1iz1xe/oVeE/de6CUdhrD1J60VxvaDYifk9/4VkcZoHWMhnk/kPJBmKXtBVNmbUq1HHfismDYwISDThfrMKIHR3BEBswu9ZHL6d7Yt49xC9CdkfmGYjrEWRSmtYXHHrVF70n1ErQOn+OgpeeN+e+DnK7pXtBeGQFyuhOVC2j8OcYEWJJ4wznFaXsg1skikPyvP/gOJltPlF/LjcWicpR8xPRUMliV6xC5YHTjbEOdIDMQtTOKYzETbOmMOyKiYsWGdo9aNYireOMRc6MORnk9MV2Yswpk5zrjTldIKoV+RWugu0HllbQk/BKuVvm7cxob/ErHLgp8CLi80hVNcaM/G7gfn6URkRtXyKlfax09urbG2FX2+Y0vAn06Y3ZF1w1rLHCPBNFJ6YsOEUUdJK7RGIXB7/mSaAmIFNxnqM6Gp4qPBRkehE08nqEIrG2E5YcbE/vxGNyvGeiQIiEVVUBeY1DMkY/uDqXjCODNMQntjK9/wly84FVK9k8aNyobvjdw8jIE1HkomiyJZkNtPwgRTPHG6vtJ7I7Wd03yijImqjVGVOgx+cvjTiThZuH+jlScBx9uf/pnqN35+/IViCyrm/+afBp988sknn3zy/xt/iKFGFXq3qAxO15nl9IIOT9530Hy8PZZfYExY++Dyy5kylH2taHcsk8OMSi0bWjPVeWSySG2kx5MRJi5pIrVCnJTTciFiqT/+TteO2kqwZ6bwBbMX1CgSZ8QHrJ/QnJF9hwJGDHaK+MVxOsMSL2hbyPs7xu9MUZCe2PKGjsSoCqaj+Z20Vra8U0ZGoud0nZhPr5TVoHpDUYadQAveCdFGxnpj8KDsnS0nhm2MMdDcoTW6ZurjMDr11sl1kPdEnzohRjAVm4Q6LFkG4k5IOLGcXzCy4ZhZ5jPP7QOpwi/hgsuG+/gJHkItWCo97zSp9CrERbicrjj1lJaprZI6aLwgbcPHzvXtlZGF0ioaX1DOuDhj7Y7UxFBFFaRn2vqdIQtFEmNZCJPFS8aq0h4fuPmCU8uwg+gM6XEjGscpBOw0YdzM0BvkhA6hD+Hxs2OMp9jfmKYLAoz6pJUb6XHDycR0eoO0oeyIN/RRGOIJrmP9sZ1TafSaeHx80PfDZBaXE+KOmwjblZYrrgun5YVSVtp2P3pzumJMw7qZ1la0PjB9BVHUJrI0ujUYY2m94GpgwiEYRDoyzTjn8dOCGcK+3egKrQ7iLAwd9NbpZcVPHuMC3Q9GhiF6xLG2d3p/ME1nHs8nwwrx9HIUsbaM92fW20+GNtBBWp+YMOPEI6NDsMyXM2G+Iv/f9u4lxrZtPez6/xuv+VqrqvbrnHt9r2M7JCRygzhWBLaIEASBTBTRSoMIiTQipZNGkJBQIiQkmnRIgoQiEK8OAkR4RW4QgpO2g0OcxLGx4xDr3ut7ztm1d1Wtx3yN10dj1TVHFiL2ja/3rmL+pKVac661zxlfrVHrW2ONOb6RB9J4IsxAiVRjafrXXPUd07vPeDd/QVXF6WWzUmleIQo132JCJa2JNlxhkkHHO0otZN9BvmxEy3qgNh1+6FnjjDcDOheM94jdU8qKcYKuC2O8pcRCoSB1Zi0zVL0UCpnPLGIJzacgK9P6ObM50tQdDoM4RdPEso6UJOALzl3KR7skSBkppTJNidRUnBFMB6UYcsq4XDGhu5R33jtqquRlZF1Wal1YKtTiabTStND4S7nvohZRi/EtSedLUYhsUApiDdkWvBGCKhINJQsUQ+N32KC01WFy4pxWkjUogXQayToxvHrJrrvCKKxrhofKcjqR/EJoejQJXiIm7Ng3LeOyMj+ckfJtGhwWQVdF2dbUbDabzeZp+igGNbUm4noieCGOK+fTLdEUMEpje/xisLKgMoJkltwS3DW29KRlIer5sg/J0EOIBI24Yok1Y5qWUCKm3rHrDWINazxwTJFu8FyFHRoNTf+SZYJUFbGBIgW3ZsK0EJeVKc1Eragmot7SScDEnsPD59guEL2hppnlWOhsh2UgS8uqMzGeiWlm0Q7pXhLjW6xVWoE0ZbQJ2PZTjG1w8/FSkvg8sTwcCYOl21nmVahiMblQoyI7jzEGXVf6/Q2me8nxm3esuWKtx1koRojTRJCV1beI79jJNbV7SSwraRqh67F5pdEC44osR8bWoXuhpSMd7lCfkKCIcRjruLm+oUrhYXpLmgy5JNQY+htD8ANGLC9uvsL4xQkbFPSK5bjSdnskZabpSCWjwXKSmVUnqPcUCvthwFhDTAVXEzUVip6oxbO7bilr5nw8kaZCaC5rX7wNnJueGCtGHMt0Jo4TTegwtrLqDNkgxlCWE+l8putavBq0JKRrWEvCOE8T9jijhKtPMLZlmW5Z9Z55HqEExFSatgELfhgIOnA4foFrOnZ+x2ldkJxxoWNaDhQjrOs9oglnFIJFKJSQwFugo84RcZbOd7SmIcfEIZ+wV7vL4ConyIKJGRCohfV8IteVVVdctsRx4n35Jjdvvp+mvmBdI0PfUlRI64zJSjzPlK4luAZNE2KFm5uvEM8T83hATUcJAacCaSHqQiIix5WXfscVV8waSfVAiYXsI+b4ll37gs4G5nwZBFnXk9cjOX8D9S1N8Jhr6Eug845sIMaI0YoES9d+lfr+xDLdkmRloYFdy/6T30G+fcuiB0qaSSyYMIB44lJZ15m+69mHK8bDe5KMRM3Y4HHOY2qiDddYPzDGB0wdKVUoySCSqKbi2gFJlRpnxET2r18gtcFMD6S6XvaIcT3OOKxW1mWlLEqVhG0cJhWKRMLgWZcVjMX2DsUzrZDfr5Sh4q3HJMcqmawFjCPZE9IEGANWIsVUsq5IiRgFXzyuOK57Q8oVQ4Ey4+oCYpiN4kKDqS3vv/mrON/hgyPFlVhXCiuaKst0oA43DGWHW2fSeqSUBaVwHgsnbakoKcFl4dhms9lsNk/PRzGoUTFUdZQaybZSRJAqDNpCrBQdUZcR45E6U94vjGUkO0f1BSGhGAZryDGypIRdDI1pEFtp94790BNjZhwXvFfa4PHRUJcTGMMx37LOC9UonX9Fmx1rOnHIhYcMYpWQK21v8K3SS4NPnqmMFF9Q70kPnqZcygYvYaE6j2jGmkBV0GSxxtJ317QeGruHLLR4XAqM8cBN06HV8l5Hko0k26K1oYYX5PRAkYKGM74kTNNhi6NiyHdHcjqBV9QbWtOTzpUpe7S12JzxumLsiuhK63oWVqTcMycFAkYsWSa87PEFSjxhry222VFSpDpBnGGOR9xwzc5fc0i/SmMq1js+eXVFnQZOd99iev8ezYY4T6RSSLHAKdE2Cy/ffMrdF8KpOErNpFCRInhj8QhNo/S7G/KcmecDlYKaRGFgOa6sc6ZYx9Bdo+pJKmBasCtiA7iMmAHTtBiZLgv0xSJUclyhVmrKjNNIYz3h+hUlBvLyQIr3qDG4tENKpmuvEbXMy4p4R04J4ytGFFMVAxgEJ4aSI7UUYp7Iask1Ie4FyB6tC0XO5CCX/u0HQnuDl4ZGRs7jO6bpTMpn1riwsBBaR9j3+MWzLgdEFU0zsusww0A3eWS2FDKu34M6Ht59cSmA4DuMWEpN1Kqczie0ZvbXNxjxj/uSeM7vv41qhmox7oaigbmOZD2RKcSqxHnC3n1O33tcyRwloxb80KDZcno4kXWh94EkmW7XUQ3o6Y6VBOHr4AzSrARTcFLwzSdw8JzvPyObb1CKUptCXR2fp1ts2/BJuOJmf8PDNJO9o5YG63vyfGLUFRMGfDYYX6gpMtaV3Ap7ExiSxdSFFCPGdrS5YGykhB6WgdH2+C4QTAQ9XEo1a6LOB168/DrWfZW702d0QTAuoEslLSPBWMQEtCoqmd1Xfojl/j3H0zeREDCpwXhP4y+zZuWsnE6F1k8YaxA86o94WrzdE7qGhGecHyCtDC9esGsC95/9KkahrDCVA6Fz2OaKbFqWZcZ4w767onEDveyIhy+YYqWIxWfQOWNtg7cNlAwpI2bBFkdWTzSRaupl5tmFy9+/uUbko0gJm81ms9n8pn0cGUwNKpYaBBRMUaw2xFRIFGzj6foeNGKKZS6ZKBnvPI0JOGvxtqVmSEVJaUGzIE0GLwh7xrGwlggYzFrRXDibFWM9aKaulSgrrm3xBKoYJtNw0gnfG3yqiC/cfOWGeoyc398iriLBcN18ldf9a24PyuJXslxK6HpZuXnxVYb2hvn9iQf9HG1nPELIFbsqeZ1Z1zsSAVzDsiaSWXBhTymF45zx1eEwpLUFb7A5E9cjzgYkWdaHSM4r6jOdHXAVaiyU5rKmSPFAJupCEcUUjyuJq92OEsHlhFlXSttCcBhdOa0nEMcn16/IxbKkFVOFXTswnUZkWVnWW0o9odbiwhX5ODEdjiznCSkJLYZcyqUYQwmkfIdowtQCeSWYTDZKXgJ+MVSjrKGAGHZhoEbF+pbzdIejcryfkbKgocFfXWNjg1ZHWo8YOzM0lq55ybRYGt8Tdj3rdIvmiJpKygvrNIIVqsmIq1RNGO0Qo6goURJrzYyHX8LgaP0bcsoIMFwNnB8OxJhxFQQh6ZGaE7GcWOdCLT3ql8usljaIKGImjPeQHC5lmv01lhtMdDgt5OUEZUXEsmokmYXQOBxCms5osdRiCf4VmCNNCLzY3XBOD6RlpNRCMJbWdExxAQa8seTpPdlkXnzlBwhz4PDuGxBnnHd49SzLZR8cd31DF1ZyGpn0llKFJIL11+zCS0pK5HXlkN7iQ8YEQdJl08fGCYpF644Xvcd1SkoFdZ7sA20XQCfM2VBDovQ9VpVkF0w3IGfLOd5jmkC18VKxTS5rQR6+9fOsfSA7i/grnOk43r0jTQvqDI3sKVEYgdC94Sq/4S7ec/JCzke0FuKseGtxoWBNpNqKXu/x9JR8IAu0/Y6SLevsYK48PHzOTXuFxIo4h8cynhdmqXgRjAeSIx8m5vCOm/2LS/W3+oBtdmTzkjWdaNUw9A3HFJkqYBy1CnU50wm8bH4HLgnRRny3oy5Hzm9vUdOS68wYJ7CGNUJQT0eD5ExrWrpuwFhLcC1lOmO6Didnkl4q2hHA6QRNoepALJY6Aq7QdIFpcrSmAAktCR+FUgLCNlOz2Ww2m6fp4xjUUHBDJksDyQCWiqHYSHbKftjRd1dIvVTp0ajUJSHjylzONI3HBkeuBVCCBwwUV2hkR4oCXaVtXjLdPjCmCe1b9jcvkaSk8UgKQn/9KTIW8umEWjDrgU4FWy0xT/QvWtoYuL87sK4VpdB5KPcjpwdYykp2PWQlGOXG9byy18jZkOYJ24EMV7gY6VoPs+N8fkeOC16ay67jodINVwQ6ap0oFZYyYdKBzjWXfTrihGhCkiC7K/I0M8mEMY6WimsUe9XQdTvqYcTljDctMYEVj0mGdieE2nA6zUxyizhIu6/h7Y7z+ZcZRdm5wHGaWG1L370ijfec59tLIYO1UJyQvcG3nuHqmng4cl7OeAfrdKbUjPEB9HwZWGkhJ3gY3yG+Is6y726Yj8L5vJC941QLL53FlUhNl+IBKTms4TKjIAEsDOEKmTOn4xeUeqYZHN627EzA+QZIBBGWObOmEzq4y6VmtmCDo7+6whbL8eELlvVAFUWtwXYvOc1vqWWmNYEY82V9SCrU4z3GOkoWUi4Yd+l3ViJxPKLGIVxhjKVWhazgVko+0/pPsc0V83qPywUX7y7rK6zHiFy+UZfLWi40I17BRYwOVDXYpqc115RZWdeF97f3lDySSsIaT5nWy+J150gyYotjnheizFAzIezpww2n+S3n9R1rWtGi+GGgf/EJJgXGd/+AGt+D7TBuwNPRFs+ue8MaRur5C0pekaZBXSYtGe0qud0h80CIFdNcBjqn8xmtjnZ/Q6iBeb6jjIljWjE1YfyO0L1mGL6PIN9H9Moxf44xlyqGqYyUZeJhOrP/9FNa94pyfEDmdKnShpDdhBluMHaHrDOtMVwVOJMoVwPOVa7VMb99YE4rPnQkDYgWLDNlnYi54vDshxe4OhPjSl4qb8dbJFe6taG7uaHbX3Oc31NdxA4tu/Y14+0tp88/Y7bfppZ42ZS2zrg8o1qZdcHlgi0R9cLQXBOLch/j5ZK4MiGpsOYZsS1NfUWaHzjkM9YamqsOdYHG7rClktNM43p0LszvJ2wwlF29zLIpDMM1OZ55f7wjiaAlQIn4PtDqjroUkmSCM3S+UJKj7yziHVhhPM3otk/NZrPZbJ6oj2NQY4XW7MkVCgVMQs1MNcreXnMln1Cjo+pISgtlTUhcyVUxzoMYkkkUFTLdpQKVLTg8FU+RSCM94+GONZ2wztM5T1c8MxnTtXRSCWNkOZwuVdZKgMVBGSkBnGbMYeC4JHKzw7g94mE3rGRjOKkBdpji8Mz4PJPPM29Ph8sAaecYdld0OjDOK6lMnM9nJlbAE2wgeFjmSMkrrr9cCta0HY00pDjiZaKScY3F+AHxnoWZRQu2ZG5uOnrTM81H8nLEDw2fvnxJPB7om2vu3k5Indjd7BCB98d3WLen+A5MR9CBND9w1swQXsJUuCszfRcJ9mtMziH+BWZNlOkBP3S4bKjzTEkr3bCnmc9UowgNJQpxSQR7xOEIbYstLe+tBVMYiMhUWcbMhCBa6UKmaweW44l5GZHisGlGux2lrIjJKJb54TNsDFgniBP8zuIEJM20wTGnEUrC2cCKZX/1ijSNLPlE2+x4vX/DcjgyOUcRwHdoPEBNtL7H+GuseqZkwXhUViqVtunI4sl1AmfwXbjM7KXMWkaMuVwKaaqnlozzAc0ry/qAw0NV8jJh/EDT3pDHI+t4oFhorj+hzTvG+E1WJkwtWFVEKynfs+pE1EwtkItCBbGG0PZYWqRmqiYKKzHNTGWiVMvDZ99g8V+gqRJzAmfQohibqGlind8ytL+Lrv1+blSpYklSGExLvn/L3J5p+haxlnlWsl1w/gWW12BHxA640lDjkWM+gFN4XOuU4xnfvELcnrIckFpY6ozMKwCda9jrq8cP7z2lBFwKrHFCsyVnSA8PXL2+oglXZHdEZKF6j+qK9RUdR0qesf0eo4a+GlwjtKGlw3L15lMexhtcvyMYy3FeiHm87HulkZor5MRVFxhrZK2Cs9ckzqxpptx/m337hsF7xngCW5DQMfQNpvTEFEl5RinYpNjyOVhDksSiKy4aYpxZS2TffQ0bXjBKJlvDPB2oGkljwRdL3/ZYvyAFgglY1+EkYESYj2cWe8BpS5xXypTwy4y72nF19QluVbRWemfIYqn2inmZiOlIuwPvwqUdc6XtW252O8bDiBHDcLVH9VKuerPZbDabp+ijGNSYqgzGkUzgPr0nlhlXHY3rCAUmvUedRapS54IJgZs3X0dzgbIQxF+qTpEwtlLypRqVDQYxlev+hlKF98sXWOfZ7a9JS2auJyIrhYhmz1pbNLcY2yGNwXmLkx0hBMo0UnPGhEpnXlBsj2Gl8fckf8XVaknnd6Q6U+pINJVUCzEWmtbzqr2G0nF49wUpLtR1Ya4rw/CGumZ8B8WCpcWEQJTLuo/BW6ZzZC2XjfRM2NMPX6FoJmmiqR4piWSUXA3nHMlSaE1DWwSzzhgxzOd71jSzGxravmFcE0lWbl78EFZaxvk9pHvG+J5OhN3kWH1lt7vhsoF65KV7SVgDU3lgtpdvy9UAXtAM03rCXve0/iXj/S1LVqQWZD5gzGXNRtTI/rqjMwPx7sicHELLvgEjM0LkfDgTq8eZHT0r1lv2+z2nQ8QMHXbXYrWjjpG6RK5fv6akRJxnYCXXM2u6Z5GGiqNqQtcFK44gLVLg4eGWOEcy0ITAq5eveRtn4vxwWfe021GLRauQ04gLga7t8NIituHh/A1ivkfkFQKUzpNOE6onmrrHisO4RC0JilBMxmhDzYJ1FRMUZy4VzqbYc8oPnKcv2NeRbC1qX5DWmVrONG2HH3YcTkdKMdhc8eEKlT2FI7koYg9c7Xps8KRxpVhwV3vKubIuoEYvBTnMhLUttWkpZIgrerqlkY7GDbwyb1g1s6RbQjmR14m1HjAmsOMG6XfknSfTMfhXxLPgSXhnyarMubCQ8abguxawrCFgrnfsTQPLHZiONRXG6YHFZVq9w5ev4sMVrhwZz2+x+0sZclcq1RgeHj5jMAG/K9QUiOtKXEfmOJFjg1XHq9Cxs4VzPsH7BRlappSppuX1134Pnbtiefc5xlpmaVF1aDVIkzAGpvlMDhViRdVg1KMlck4T79ZvgjR4WTFz5VgWetvQD4ZQlPnsiCmBemRZcN2lmuNcFpqmZVkD65QQ/xmGy+Wfy5pw4ml8g2plOo1UfYNr9miaqWsgjw/MvEMahwEkZXITMDdXiESIC+l45LRMXDU70lpIsVJqREzFYcjFs8wrjQdnGnI8keKBfJVpW1Aj5HHFlYjItvvmZrPZbJ6mj2JQIwBJibJAhSY30PjHmQihmkprBV0KVSvBB8o0saQTrXMoGaOREAoxLQgOTQXrEtYa5vmBh+OZlCtdaJnnlTWfkazQtHzylX+SeDbcvv0CXKZpVpyP7EJDUEs1iampLLpSkqVpXlBVqWmiUtGysJ6PJD1RSkR8i5GOkhcSlQY4v59RjUzTSs0TKpG26zExoqFCcwW5oGZkrRGdlVIqd+9OrPmy6LgJLbZ9iTFX1PNb6ulI0oCWQm0Dxe+pccbiISmn97cUGrQ0TOXIEspl7cipcIoTTTPgcmROZ0oeqbkQa8KcKtpk+ldvMEODrRMhn5E5sZzeY6qlaQa6bo9tdszrHcH0zGak71/iFphdx/WrG+LxFuqKMYbKpZSuHy+zDOWsOKns1RIpVDMj1lKyx0ggpEqyI0YKS3qPbzzd1RW+G1DtmOdbJl2YZ4MWyBQwkVJWslZKnikKMUfe33+bbveG0PWkkojHA7VmbDNQq+Hu3RcscSXnSNOEyx4l9OTlATUWSSOQyOVEkRaVdCmnnUZcM+D7G9J5oaqh8y/JLiC02FKwTi8llnNAUyJqJq0noo7swifsu1ecp5kxzYDiTYctgikdUUd0nalUqlaiJnppkBqxMpBLQy7j5W/IgfctWi+XT+67G/baUNfEvNwSjULToEBob8jJoeVMTZXx/TdItkfyjiQLglDrgm0txjpyXTnVO0LXct3fkJcARLrhDdP4Odbfk6uy73dITRxPB1zJuLal9Qd24Q39MPDAPY10aO2Zp4l5iZyrZ8dK130FzRPJKlkTTQusDUttoPZoTQj3NMNruu4Txvu3xBpJTSJF5e72QNMKOWRKhTzPuMZT88Tp7hcp3SdINcSUENfigqPMmZwjk4tUlKxgnUWyYLueNBZyKsziiXjaEGgaj/MticyYFGehaxTvHZiB9XhmmSJpNyCukoIj7DxBHWuNUA2hDOT4nto6ck5gCr5vicsR6DFtixShrIklzXjnCe0Okw3iZqR/iZQBsZGm7kjLPe/Xe6p4shqMtAgttc5oXjES0LIAFZGFEpXjO8E1PeIzvpkIRrcVNZvNZrN5sj6KQY2qsqaEpELQFfFy2fSuGDKCyyv5fLneu6pyOpww5rK+RHtDNh2rRnhcw3FZwL1SDORsWONKUo+VDl0M1hVoBG9aXoQX9Gfl/nAgyUxrBUPElkrjA8EX7s8njmUh+Z69f4OxSk6fU5bMqUB1Z6rPNPaaVAuEl/icSLrSdhbjepZ5IQSL2opIwNqAilCays2LV3S84LQcqJKAgPUQp4qUldAnzL7FtQM5rcynb2CmiXUeCXaPdYadREJKaPHgC9UK41qRcMNQBrQGGp8peeTutBDNgul6jmZFG0+cM+Ijr9s3xDqidqXOb2mtxxVlmh5grUgVhAHKgksKUrnqX3M6vKNiGG/v0XFB24hDGbobpuWMGsEET3Aty/EeTSOXimuFpmsJjWNKlS506DFTE2TjyM6iRMQJnenRHCF5al6I+QEsTPOEbxts9ymmdEiG2OwotVLDDtd9HSMWcQHKEamGqgbTtPTXb4jrSNGID93lAyYAGYNyc/MGoeHwxS9RFYxmst4jNmG0oOsRUNruBbZ5yZIOiFSsyfhSMGRKrmgtlw+MWtGaocBaMq484KSjcQ50oLUtpip5OuIZMDhyLixmJgw7msHS6xuYZtbz54ivuBowSyGliCEhOIbhJXEaqfGAx4FxuODo9zuW8wmPcnX1mjV2tK7ldHjHXCdeXl1hoiHmiFaDufKYRUEdSx2J5xExkVIDc7H0coWtMMVbao1I09C0Pa/cwHQ+YaqhHEdms5KxTPWMakaoWGmo6im5Xop7pAMqCXY9VZWcF8QMWLcjuGtkjaTlSJnfce1esWt3TBmyu6PdBTq5oozxUi2vWSkRjNuz3+05v/82D+f/C60twb1GcsFqvRQ0KMI6T4ip9Fffd9lnZzoRJHA4HiE7ejtAUdQYam3omz07Y5nPB2oR4nqZrQrWYrxgaIi1x4uhLZbUgvMVU3dAIHQN5kFZlxNFFrSx+Bc7uthTz/fM02doaCnNpfR0MVBCQFxDmR4Q8xnWv0KSIdaZNa+suaC2oTplP7zE18BaLSqZxEjJFqoBLjOFaVk5nYRgG0xQbFhRtpmazWaz2TxNH8egBmFOSq0rWI/GiplWmk7pBs9Cw4olx5mqCrjLInkjlKVi+4K4ioowZ1imSHFyqT6VA0kdalZKXWjaPUYc3giiluPxzHu5XDYyVIOpC0YKQ9ghVZmmyJwM3fAVuuio84ESjvRiiHJZH5HLBFYx0mKaNxQqsR4othKsvWxUaCOxgm9vMMWj9oxpFO88dVVO84mUI2ILQiQrGG8wnaHZ7+mH1xRNhNazxjtmmzENiFuwfYtWQ1pOGDE4Z5FqabLFl8uH06Z7DelMrQHtzkiaYD3T9Du60vI+KUomE/H9FWU5onVhfVDGPCGupZqZXGdqTWhS4rjSJscVifb6JS4NrOdv0XUdsynEcsaEBvfiNTKvSAZKxdiKabiUPLaW/mWHsYZ0r6xLwrjHymJAFk8XAmYVkjGEbmDffYV3b7+B31/ThWtIlZoXnL7ElYlzzjjrqcHguh1SLC5mlmVkWiNN5wn9juA8L/sdDzXTNy85lgcmTpRqmKaIxDu+9uYHSXNi6Sy1uYbq8Hkk2IhSUCv04TXL8Y60zGiNZA6QBNtY/HBFRbG5PG5guiAepNujIkQbiDUT2oHBNdiYKSWxiCHX+8vruL/GOcfQ7TG2Q6eGbBKnOpEXaBS0rhwPFbEZzYZPdp6SLOuiLHrCGEdPwIwHvGacCntr2PeBGCt5reScmMwdzlokVLzvmKeVugriBprgkXom60rUDGbgOL8FHMXuafIZu0QQwyAtimdeZmgb5ppZpaKmYZkTuS40ruVqZ4lxYbEe33h2dLjOk9OedJ45nW6hSfgXLf1uYLrvWKYD99MtViL4lr5x1LiymPdI67DaktTRXPdY65BaGbqe5XRgNYqXM2l9TypgJONtRl1lEkXP93zt5gewg4UUia4hmhVpCm1xjEtFl5WYjsShR8cDUWbWqOTiEPUUSdRG6cw1pgYwJxojrEmxKWHzke76hv7mJdPZcoh3FCwsZ5pW8EOPWxdiUMT1DG0LvcHQUs0ObE9d77HdzP71K+rJUbEUp6Q849Siebps+mvzpZqaQs4JMYKx+0sxlTZhl0peRyyVRE/BfNBcsNlsNpvNd+ujGNSIBJo2sM6FtEbQeNkcz1pSyWQMKVUkO6yaS3L2FsikWliWmaQFY/eXylTG0+9uCOGK8XTCsdI4f9mI0zeQ7xB1xFhYa8USCWlGiRSTYFJOZ2VsA3Zo8a6BtVLzittdZgKW+fZyOVrOGCqNeIy/Zq2BtR5wVvFdIJeEF4dZHHUeCVpphmuyAdM4cC+IacYzY+xCu++AhikXbKtoLpc1Q8c7bCPUVSl6JruKsYLvLEM/sE4LWhJaC2m2iAqSLFNaadqKmSOZhW7XgyaSKrlm0ulMGc/ASMkgLl0+kHuPcQ1lXVlqwWmlBItrbsjTSDUFqS1xjazdmavhn2A9FDQ4ipw554VswVvLVWgxpiPontP7X6FYJSH0ww7nHIQGK5ZgE6U3eDrG4z0xrYRikCSU2pBCQQ4LerjnPB6xIRL2DseemhXPiWk+UOpK1iPqLI16GttR4gFjLrMv4gTrLOuSuP3sLavM1FqZ04TvrjClQrakdeTd7Tcux0ERA0YaRBOYShd61Ho6OzDHb1PyTCURS0bEY4zHNi1NhFUi1IJrLLQeFWj9QBB32VcHQTVT8krwLa77hLvzP4S64uuOhh3xMIOekaKQlN6+IK/lsgGtq9jqL//WGJbjRB7PeAm47isYUWTNxDghAYx1pHUhpcg4zuSU0CzM40izu2xUKhKBDLaiGEp5ifOerEeqNRgF6xR2LaUOROkI+Y4SC0vNUAvFVNqrT+jtgBhHyWDlM9Z4oAuWoevwAepacXFB65k1TQR5wGMpHmh2xPkOozO262jdNXm2LKdfIc13NDLQuo4lLbh+x67Z4w8jc125aq8ISTjEBwyVnYPGC6e4YKxj3+yZT+9YqeQucMqF2/NIUyGt9yR3me3Jc0SJtBRyhHh/YJYdXi8DiWIEaTy18xD3lHJEzQnVF6QYqGVFPLRNh02G4+efkZvuUiCkCUQMWgrH0zsAnApOLNoYQuohrVhZcMag4QWuecW03BHlSN+3LMld+rY4Gu/IccJ3l7VocUmE6sgmU3JhFYN4y83VNXZ1PNzdEssZlQXZCgVsNpvN5on6KAY11ATTgqpS3USVhBpHEqWUSNFLAYCuu2YdM0kr1VdWqRR11ApX9NgoSGjYux29tkzxjC9HZJoZmmuCC0zLe5QKGIgrLmUwldJZqg1oNJBWsonU2mFpsVNCdEf/cmBnAw/vv8XiMtk4jLdYLRQglpUqGXO9Y+gcV/aK8eFzKBMzmdoK19c7unbgPJ6RtqcxA6ZZsK0wjgaSQYlYEiORapWUHkALde6wuqIObP+KvMwkXZjWSwlZrCP7CgqShWoTxVfERKJWfAgYt7COK9VYrHOIaVnsPdUbnL/G5MIa37HrW5zzqBVKeYn3O7wkmnUlpcu+K2IdLgDriLy/hZiodeYQ74hiQQJ1jaR84urVD9AcFk5tIiWPnjPBB6qFKRfyrNT5gdZbchmJElldxVtBBIpVlgw1WpZy4phPdHXBeAhLJMeZQ51ZirJrerzNRFNob16xb77KYUwY7pESqeqYY0HEQ/a0raH1L5iYLt/cNy2lFpY0EeNIExw2eEw6sS7viDkhwGKgM4Ek7zCxYMU+Xv5T8f0OZxuOt18Qp4hpdlS4lKY2DhWhzhNRI67tSONMigvGOESEMSbGkghU7MM71GWyvUbFUfMtJiVcs8ep5byMnNXQxIjv9nTSQ7yU7jXegTcYyUxjZdFCf7PHFs/dwzsKhbjWS+GI2XFllCZnoGWtE9U21Bwul0GaL9CyR+sLSpjI/hU2RYKZ8XkkYy6zWQWqtKhNaPkmeTlirIXG0Q2fYLLBZY/EhZkF23iGRpCxcprOZD0TXMVwmZUN1VJcwzwd8BScNHTsMP6rTFpI4wm6Bet7as5kDpikxPHI+4d7rnyLSCXYPZozyR7wNwN6EvI8YqulqgETqL7jISktLc5/Cu5Iv2tY382M51vQhGtvqO5MNGdM22PrAKpYqdiQafwb4uJwDqiCkTc8nN5RWPD7iZbKfI6UJXJ1PdA0Dmcsxl2R5pVZZ1LToeulgp8JN/h5YKnviOY9nhHnX9OblsPdHfcukQSqNFQKYxJYLXG54/r6hqA9Fk8Nl724SiqU5GHfMbQdy9kTpxbxHbqNaTabzWbzRInqh7+GWkROwC9+6HZ8D70G3n3oRnyPPOfY4HnH95xjg+cd3/cqth9Q1Tffg//uk7flqSftOccGzzu+5xwbPO/4ftvz1McxUwO/qKp/4EM34ntFRH7mucb3nGOD5x3fc44Nnnd8zzm2j9iWp56o5xwbPO/4nnNs8Lzj+xCxbatCN5vNZrPZbDabzZO2DWo2m81ms9lsNpvNk/axDGr+kw/dgO+x5xzfc44Nnnd8zzk2eN7xPefYPlbP/Xf+nON7zrHB847vOccGzzu+3/bYPopCAZvNZrPZbDabzWbz3fpYZmo2m81ms9lsNpvN5ruyDWo2m81ms9lsNpvNk/bBBzUi8hMi8osi8ssi8mc+dHu+GyLyn4vIWxH5uS+deykif1VE/v7jzxeP50VE/sPHeP+OiPzoh2v5P5qIfL+I/HUR+XkR+Xsi8qcfzz/5+ESkFZG/ISJ/+zG2f+/x/A+JyE8/xvDfikh4PN88Hv/y4+M/+EED+A0QESsif0tEfvLx+DnF9isi8ndF5GdF5Gcezz35fvkdInIjIn9JRP5PEfkFEfnx5xTfU7LlqY+7P2156sm/l295iqfVL7/jY8tTH3RQIyIW+I+AfwX4YeCPicgPf8g2fZf+S+Anft25PwP8lKr+buCnHo/hEuvvfrz9SeAv/ja18buVgX9LVX8Y+DHgTz2+Rs8hvhX4Q6r6+4AfAX5CRH4M+PeBP6eqvwu4B/7E4/P/BHD/eP7PPT7vY/engV/40vFzig3gX1DVH/lSLfzn0C+/4y8A/4uq/l7g93F5HZ9TfE/ClqeeRH/a8tTTfi/f8tTFU+qX3/Fx5SlV/WA34MeBv/Kl4z8L/NkP2aZ/jFh+EPi5Lx3/IvDVx/tf5bJxG8B/DPyx/7fnPYUb8D8D/9Jziw/ogf8D+Ge47IDrHs//Wh8F/grw44/33ePz5EO3/f8jpq9zeUP5Q8BPAvJcYnts568Ar3/duWfRL4Fr4B/++tfgucT3lG5bnnp6/WnLU0/nvXzLU0+3X36MeepDX372NeCbXzr+1uO55+BTVf3s8f7nwKeP959szI9Tvb8f+GmeSXyP094/C7wF/irwD4AHVc2PT/ly+38ttsfHD8Cr39YG/+b8eeDfBurj8SueT2wACvyvIvI3ReRPPp57Fv0S+CHgFvgvHi/L+E9FZOD5xPeUPOff7bPrT1ueenLv5X+eLU89yX7JR5inPvSg5v8X9DIkfdK1s0VkB/z3wL+pqscvP/aU41PVoqo/wuXbon8a+L0ftkW/NUTkjwBvVfVvfui2fA/9QVX9US5T2n9KRP65Lz/4lPsll28hfxT4i6r6+4GR/2cKH3jy8W0+Ms+hP2156mnZ8tTT7pd8hHnqQw9qfhX4/i8df/3x3HPwhYh8FeDx59vH808uZhHxXBLFf6Wq/8Pj6WcTH4CqPgB/nctU942IuMeHvtz+X4vt8fFr4P1vb0t/w/5Z4F8VkV8B/hsuU/t/gecRGwCq+quPP98C/yOXZP9c+uW3gG+p6k8/Hv8lLsnjucT3lDzn3+2z6U9bnnqS7+Vbnnra/fKjy1MfelDzvwO/+7HSRQD+NeAvf+A2/Vb5y8Aff7z/x7lc4/ud8//GYxWIHwMOX5qm++iIiAD/GfALqvoffOmhJx+fiLwRkZvH+x2Xa7B/gUvS+KOPT/v1sX0n5j8K/LXHbyE+Oqr6Z1X166r6g1z+rv6aqv7rPIPYAERkEJH9d+4D/zLwczyDfgmgqp8D3xSR3/N46l8Efp5nEt8Ts+Wpj7w/bXnqab6Xb3kKeKL9Ej7SPPVbvXDoN3sD/jDwS1yuEf13PnR7vssY/mvgMyBxGbn+CS7Xef4U8PeB/w14+fhc4VJJ5x8Afxf4Ax+6/f+I2P4gl6nDvwP87OPtDz+H+IB/Cvhbj7H9HPDvPp7/ncDfAH4Z+O+A5vF8+3j8y4+P/84PHcNvMM5/HvjJ5xTbYxx/+/H2977z3vEc+uWXYvwR4Gce++f/BLx4TvE9pduWpz7u/rTlqaf7Xv6lOLc89YT65Zdi/KjylDz+jzabzWaz2Ww2m83mSfrQl59tNpvNZrPZbDabzT+WbVCz2Ww2m81ms9lsnrRtULPZbDabzWaz2WyetG1Qs9lsNpvNZrPZbJ60bVCz2Ww2m81ms9lsnrRtULPZbDabzWaz2WyetG1Qs9lsNpvNZrPZbJ60/xvH0T8mRG7rRAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "N = 2\n", + "img = imageio.imread(image_list[N])\n", + "mask = imageio.imread(mask_list[N])\n", + "#mask = np.array([max(mask[i, j]) for i in range(mask.shape[0]) for j in range(mask.shape[1])]).reshape(img.shape[0], img.shape[1])\n", + "\n", + "fig, arr = plt.subplots(1, 2, figsize=(14, 10))\n", + "arr[0].imshow(img)\n", + "arr[0].set_title('Image')\n", + "arr[1].imshow(mask[:, :, 0])\n", + "arr[1].set_title('Segmentation')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.1 - Split Your Dataset into Unmasked and Masked Images" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "FlzMS0mhmkb1", + "outputId": "e2ad8c66-c380-400f-aed0-9f4b1f53ecad" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(, )\n", + "(, )\n", + "(, )\n" + ] + } + ], + "source": [ + "image_list_ds = tf.data.Dataset.list_files(image_list, shuffle=False)\n", + "mask_list_ds = tf.data.Dataset.list_files(mask_list, shuffle=False)\n", + "\n", + "for path in zip(image_list_ds.take(3), mask_list_ds.take(3)):\n", + " print(path)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "aNF2Ztii8-Jx", + "outputId": "7e91a651-a54c-4838-e1db-41ef4915680e" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tf.Tensor(b'./data/CameraRGB/002128.png', shape=(), dtype=string)\n", + "tf.Tensor(b'./data/CameraMask/002128.png', shape=(), dtype=string)\n" + ] + } + ], + "source": [ + "image_filenames = tf.constant(image_list)\n", + "masks_filenames = tf.constant(mask_list)\n", + "\n", + "dataset = tf.data.Dataset.from_tensor_slices((image_filenames, masks_filenames))\n", + "\n", + "for image, mask in dataset.take(1):\n", + " print(image)\n", + " print(mask)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 2.2 - Preprocess Your Data\n", + "\n", + "Normally, you normalize your image values by dividing them by `255`. This sets them between `0` and `1`. However, using `tf.image.convert_image_dtype` with `tf.float32` sets them between `0` and `1` for you, so there's no need to further divide them by `255`." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "NUjQfI1wmkkn" + }, + "outputs": [], + "source": [ + "def process_path(image_path, mask_path):\n", + " img = tf.io.read_file(image_path)\n", + " img = tf.image.decode_png(img, channels=3)\n", + " img = tf.image.convert_image_dtype(img, tf.float32)\n", + "\n", + " mask = tf.io.read_file(mask_path)\n", + " mask = tf.image.decode_png(mask, channels=3)\n", + " mask = tf.math.reduce_max(mask, axis=-1, keepdims=True)\n", + " return img, mask\n", + "\n", + "def preprocess(image, mask):\n", + " input_image = tf.image.resize(image, (96, 128), method='nearest')\n", + " input_mask = tf.image.resize(mask, (96, 128), method='nearest')\n", + "\n", + " return input_image, input_mask\n", + "\n", + "image_ds = dataset.map(process_path)\n", + "processed_image_ds = image_ds.map(preprocess)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - U-Net \n", + "\n", + "U-Net, named for its U-shape, was originally created in 2015 for tumor detection, but in the years since has become a very popular choice for other semantic segmentation tasks. \n", + "\n", + "U-Net builds on a previous architecture called the Fully Convolutional Network, or FCN, which replaces the dense layers found in a typical CNN with a transposed convolution layer that upsamples the feature map back to the size of the original input image, while preserving the spatial information. This is necessary because the dense layers destroy spatial information (the \"where\" of the image), which is an essential part of image segmentation tasks. An added bonus of using transpose convolutions is that the input size no longer needs to be fixed, as it does when dense layers are used. \n", + "\n", + "Unfortunately, the final feature layer of the FCN suffers from information loss due to downsampling too much. It then becomes difficult to upsample after so much information has been lost, causing an output that looks rough. \n", + "\n", + "U-Net improves on the FCN, using a somewhat similar design, but differing in some important ways. Instead of one transposed convolution at the end of the network, it uses a matching number of convolutions for downsampling the input image to a feature map, and transposed convolutions for upsampling those maps back up to the original input image size. It also adds skip connections, to retain information that would otherwise become lost during encoding. Skip connections send information to every upsampling layer in the decoder from the corresponding downsampling layer in the encoder, capturing finer information while also keeping computation low. These help prevent information loss, as well as model overfitting. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.1 - Model Details\n", + "\n", + "\n", + "
Figure 2 : U-Net Architecture
\n", + "\n", + "**Contracting path** (Encoder containing downsampling steps):\n", + "\n", + "Images are first fed through several convolutional layers which reduce height and width, while growing the number of channels.\n", + "\n", + "The contracting path follows a regular CNN architecture, with convolutional layers, their activations, and pooling layers to downsample the image and extract its features. In detail, it consists of the repeated application of two 3 x 3 valid padding convolutions, each followed by a rectified linear unit (ReLU) and a 2 x 2 max pooling operation with stride 2 for downsampling. At each downsampling step, the number of feature channels is doubled.\n", + "\n", + "**Crop function**: This step crops the image from the contracting path and concatenates it to the current image on the expanding path to create a skip connection. \n", + "\n", + "**Expanding path** (Decoder containing upsampling steps):\n", + "\n", + "The expanding path performs the opposite operation of the contracting path, growing the image back to its original size, while shrinking the channels gradually.\n", + "\n", + "In detail, each step in the expanding path upsamples the feature map, followed by a 2 x 2 convolution (the transposed convolution). This transposed convolution halves the number of feature channels, while growing the height and width of the image.\n", + "\n", + "Next is a concatenation with the correspondingly cropped feature map from the contracting path, and two 3 x 3 convolutions, each followed by a ReLU. You need to perform cropping to handle the loss of border pixels in every convolution.\n", + "\n", + "**Final Feature Mapping Block**: In the final layer, a 1x1 convolution is used to map each 64-component feature vector to the desired number of classes. The channel dimensions from the previous layer correspond to the number of filters used, so when you use 1x1 convolutions, you can transform that dimension by choosing an appropriate number of 1x1 filters. When this idea is applied to the last layer, you can reduce the channel dimensions to have one layer per class. \n", + "\n", + "The U-Net network has 23 convolutional layers in total.\n", + "\n", + "#### Important Note: \n", + "The figures shown in the assignment for the U-Net architecture depict the layer dimensions and filter sizes as per the original paper on U-Net with smaller images. However, due to computational constraints for this assignment, you will code only half of those filters. The purpose of showing you the original dimensions is to give you the flavour of the original U-Net architecture. The important takeaway is that you multiply by 2 the number of filters used in the previous step. The notebook includes all of the necessary instructions and hints to help you code the U-Net architecture needed for this assignment." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ETPr2Kx7CpqG" + }, + "source": [ + "\n", + "### 3.2 - Encoder (Downsampling Block) \n", + "\n", + "\n", + "
Figure 3: The U-Net Encoder up close
\n", + "\n", + "The encoder is a stack of various conv_blocks:\n", + "\n", + "Each `conv_block()` is composed of 2 **Conv2D** layers with ReLU activations. We will apply **Dropout**, and **MaxPooling2D** to some conv_blocks, as you will verify in the following sections, specifically to the last two blocks of the downsampling. \n", + "\n", + "The function will return two tensors: \n", + "- `next_layer`: That will go into the next block. \n", + "- `skip_connection`: That will go into the corresponding decoding block.\n", + "\n", + "**Note**: If `max_pooling=True`, the `next_layer` will be the output of the MaxPooling2D layer, but the `skip_connection` will be the output of the previously applied layer(Conv2D or Dropout, depending on the case). Else, both results will be identical. \n", + "\n", + "\n", + "### Exercise 1 - conv_block\n", + "\n", + "Implement `conv_block(...)`. Here are the instructions for each step in the `conv_block`, or contracting block: \n", + "\n", + "* Add 2 **Conv2D** layers with `n_filters` filters with `kernel_size` set to 3, `kernel_initializer` set to ['he_normal'](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/HeNormal), `padding` set to 'same' and 'relu' activation.\n", + "* if `dropout_prob` > 0, then add a Dropout layer with parameter `dropout_prob`\n", + "* If `max_pooling` is set to True, then add a MaxPooling2D layer with 2x2 pool size" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "id": "_jREFwsA5w6j", + "nbgrader": { + "grade": false, + "grade_id": "cell-5bc67a8f4f19dea5", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1\n", + "# GRADED FUNCTION: conv_block\n", + "def conv_block(inputs=None, n_filters=32, dropout_prob=0, max_pooling=True):\n", + " \"\"\"\n", + " Convolutional downsampling block\n", + " \n", + " Arguments:\n", + " inputs -- Input tensor\n", + " n_filters -- Number of filters for the convolutional layers\n", + " dropout_prob -- Dropout probability\n", + " max_pooling -- Use MaxPooling2D to reduce the spatial dimensions of the output volume\n", + " Returns: \n", + " next_layer, skip_connection -- Next layer and skip connection outputs\n", + " \"\"\"\n", + "\n", + " ### START CODE HERE\n", + " conv = Conv2D(n_filters, # Number of filters\n", + " 3,# Kernel size \n", + " activation='relu',\n", + " padding='same',\n", + " kernel_initializer= 'he_normal')(inputs)\n", + " conv = Conv2D(n_filters, # Number of filters\n", + " 3,# Kernel size \n", + " activation='relu',\n", + " padding='same',\n", + " kernel_initializer= 'he_normal')(conv)\n", + " ### END CODE HERE\n", + " \n", + " # if dropout_prob > 0 add a dropout layer, with the variable dropout_prob as parameter\n", + " if dropout_prob > 0:\n", + " ### START CODE HERE\n", + " conv = Dropout(dropout_prob)(conv)\n", + " ### END CODE HERE\n", + " \n", + " \n", + " # if max_pooling is True add a MaxPooling2D with 2x2 pool_size\n", + " if max_pooling:\n", + " ### START CODE HERE\n", + " next_layer = MaxPooling2D(2,strides=2)(conv)\n", + " ### END CODE HERE\n", + " \n", + " else:\n", + " next_layer = conv\n", + " \n", + " skip_connection = conv\n", + " \n", + " return next_layer, skip_connection" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-41849354bc5921b4", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Block 1:\n", + "['InputLayer', [(None, 96, 128, 3)], 0]\n", + "['Conv2D', (None, 96, 128, 32), 896, 'same', 'relu', 'HeNormal']\n", + "['Conv2D', (None, 96, 128, 32), 9248, 'same', 'relu', 'HeNormal']\n", + "['MaxPooling2D', (None, 48, 64, 32), 0, (2, 2)]\n", + "\u001b[32mAll tests passed!\u001b[0m\n", + "\n", + "Block 2:\n", + "['InputLayer', [(None, 96, 128, 3)], 0]\n", + "['Conv2D', (None, 96, 128, 1024), 28672, 'same', 'relu', 'HeNormal']\n", + "['Conv2D', (None, 96, 128, 1024), 9438208, 'same', 'relu', 'HeNormal']\n", + "['Dropout', (None, 96, 128, 1024), 0, 0.1]\n", + "['MaxPooling2D', (None, 48, 64, 1024), 0, (2, 2)]\n", + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "input_size=(96, 128, 3)\n", + "n_filters = 32\n", + "inputs = Input(input_size)\n", + "cblock1 = conv_block(inputs, n_filters * 1)\n", + "model1 = tf.keras.Model(inputs=inputs, outputs=cblock1)\n", + "\n", + "output1 = [['InputLayer', [(None, 96, 128, 3)], 0],\n", + " ['Conv2D', (None, 96, 128, 32), 896, 'same', 'relu', 'HeNormal'],\n", + " ['Conv2D', (None, 96, 128, 32), 9248, 'same', 'relu', 'HeNormal'],\n", + " ['MaxPooling2D', (None, 48, 64, 32), 0, (2, 2)]]\n", + "\n", + "print('Block 1:')\n", + "for layer in summary(model1):\n", + " print(layer)\n", + "\n", + "comparator(summary(model1), output1)\n", + "\n", + "inputs = Input(input_size)\n", + "cblock1 = conv_block(inputs, n_filters * 32, dropout_prob=0.1, max_pooling=True)\n", + "model2 = tf.keras.Model(inputs=inputs, outputs=cblock1)\n", + "\n", + "output2 = [['InputLayer', [(None, 96, 128, 3)], 0],\n", + " ['Conv2D', (None, 96, 128, 1024), 28672, 'same', 'relu', 'HeNormal'],\n", + " ['Conv2D', (None, 96, 128, 1024), 9438208, 'same', 'relu', 'HeNormal'],\n", + " ['Dropout', (None, 96, 128, 1024), 0, 0.1],\n", + " ['MaxPooling2D', (None, 48, 64, 1024), 0, (2, 2)]]\n", + " \n", + "print('\\nBlock 2:') \n", + "for layer in summary(model2):\n", + " print(layer)\n", + " \n", + "comparator(summary(model2), output2)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8n-9c0keCtbf" + }, + "source": [ + "\n", + "### 3.3 - Decoder (Upsampling Block)\n", + "\n", + "The decoder, or upsampling block, upsamples the features back to the original image size. At each upsampling level, you'll take the output of the corresponding encoder block and concatenate it before feeding to the next decoder block.\n", + "\n", + "\n", + "
Figure 4: The U-Net Decoder up close
\n", + "\n", + "There are two new components in the decoder: `up` and `merge`. These are the transpose convolution and the skip connections. In addition, there are two more convolutional layers set to the same parameters as in the encoder. \n", + "\n", + "Here you'll encounter the `Conv2DTranspose` layer, which performs the inverse of the `Conv2D` layer. You can read more about it [here.](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2DTranspose)\n", + "\n", + "\n", + "\n", + "### Exercise 2 - upsampling_block\n", + "\n", + "Implement `upsampling_block(...)`.\n", + "\n", + "For the function `upsampling_block`: \n", + "* Takes the arguments `expansive_input` (which is the input tensor from the previous layer) and `contractive_input` (the input tensor from the previous skip layer)\n", + "* The number of filters here is the same as in the downsampling block you completed previously\n", + "* Your `Conv2DTranspose` layer will take `n_filters` with shape (3,3) and a stride of (2,2), with padding set to `same`. It's applied to `expansive_input`, or the input tensor from the previous layer. \n", + "\n", + "This block is also where you'll concatenate the outputs from the encoder blocks, creating skip connections. \n", + "\n", + "* Concatenate your Conv2DTranspose layer output to the contractive input, with an `axis` of 3. In general, you can concatenate the tensors in the order that you prefer. But for the grader, it is important that you use `[up, contractive_input]`\n", + "\n", + "For the final component, set the parameters for two Conv2D layers to the same values that you set for the two Conv2D layers in the encoder (ReLU activation, He normal initializer, `same` padding). \n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "id": "9lzEn-mu6nHa", + "nbgrader": { + "grade": false, + "grade_id": "cell-4a6bea191d41d977", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2\n", + "# GRADED FUNCTION: upsampling_block\n", + "def upsampling_block(expansive_input, contractive_input, n_filters=32):\n", + " \"\"\"\n", + " Convolutional upsampling block\n", + " \n", + " Arguments:\n", + " expansive_input -- Input tensor from previous layer\n", + " contractive_input -- Input tensor from previous skip layer\n", + " n_filters -- Number of filters for the convolutional layers\n", + " Returns: \n", + " conv -- Tensor output\n", + " \"\"\"\n", + " \n", + " ### START CODE HERE\n", + " up = Conv2DTranspose(\n", + " n_filters, # number of filters\n", + " 3,# Kernel size\n", + " strides=2,\n", + " padding='same')(expansive_input)\n", + " \n", + " # Merge the previous output and the contractive_input\n", + " merge = concatenate([up, contractive_input], axis=3)\n", + " \n", + " conv = Conv2D(n_filters, # Number of filters\n", + " 3,# Kernel size \n", + " activation='relu',\n", + " padding='same',\n", + " kernel_initializer= 'he_normal')(merge)\n", + " conv = Conv2D(n_filters, # Number of filters\n", + " 3,# Kernel size \n", + " activation='relu',\n", + " padding='same',\n", + " kernel_initializer= 'he_normal')(conv)\n", + " ### END CODE HERE\n", + " \n", + " return conv" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-10e351ce736f2727", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Block 1:\n", + "['InputLayer', [(None, 12, 16, 256)], 0]\n", + "['Conv2DTranspose', (None, 24, 32, 32), 73760]\n", + "['InputLayer', [(None, 24, 32, 128)], 0]\n", + "['Concatenate', (None, 24, 32, 160), 0]\n", + "['Conv2D', (None, 24, 32, 32), 46112, 'same', 'relu', 'HeNormal']\n", + "['Conv2D', (None, 24, 32, 32), 9248, 'same', 'relu', 'HeNormal']\n", + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "input_size1=(12, 16, 256)\n", + "input_size2 = (24, 32, 128)\n", + "n_filters = 32\n", + "expansive_inputs = Input(input_size1)\n", + "contractive_inputs = Input(input_size2)\n", + "cblock1 = upsampling_block(expansive_inputs, contractive_inputs, n_filters * 1)\n", + "model1 = tf.keras.Model(inputs=[expansive_inputs, contractive_inputs], outputs=cblock1)\n", + "\n", + "output1 = [['InputLayer', [(None, 12, 16, 256)], 0],\n", + " ['Conv2DTranspose', (None, 24, 32, 32), 73760],\n", + " ['InputLayer', [(None, 24, 32, 128)], 0],\n", + " ['Concatenate', (None, 24, 32, 160), 0],\n", + " ['Conv2D', (None, 24, 32, 32), 46112, 'same', 'relu', 'HeNormal'],\n", + " ['Conv2D', (None, 24, 32, 32), 9248, 'same', 'relu', 'HeNormal']]\n", + "\n", + "print('Block 1:')\n", + "for layer in summary(model1):\n", + " print(layer)\n", + "\n", + "comparator(summary(model1), output1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.4 - Build the Model\n", + "\n", + "This is where you'll put it all together, by chaining the encoder, bottleneck, and decoder! You'll need to specify the number of output channels, which for this particular set would be 23. That's because there are 23 possible labels for each pixel in this self-driving car dataset. \n", + "\n", + "\n", + "### Exercise 3 - unet_model\n", + "\n", + "For the function `unet_model`, specify the input shape, number of filters, and number of classes (23 in this case).\n", + "\n", + "For the first half of the model:\n", + "\n", + "* Begin with a conv block that takes the inputs of the model and the number of filters\n", + "* Then, chain the first output element of each block to the input of the next convolutional block\n", + "* Next, double the number of filters at each step\n", + "* Beginning with `conv_block4`, add `dropout_prob` of 0.3\n", + "* For the final conv_block, set `dropout_prob` to 0.3 again, and turn off max pooling \n", + "\n", + "For the second half:\n", + "\n", + "* Use cblock5 as expansive_input and cblock4 as contractive_input, with `n_filters` * 8. This is your bottleneck layer. \n", + "* Chain the output of the previous block as expansive_input and the corresponding contractive block output.\n", + "* Note that you must use the second element of the contractive block before the max pooling layer. \n", + "* At each step, use half the number of filters of the previous block\n", + "* `conv9` is a Conv2D layer with ReLU activation, He normal initializer, `same` padding\n", + "* Finally, `conv10` is a Conv2D that takes the number of classes as the filter, a kernel size of 1, and \"same\" padding. The output of `conv10` is the output of your model. " + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "id": "Sv2UCFehHZsh", + "nbgrader": { + "grade": false, + "grade_id": "cell-e43cf8104499fbd9", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C3\n", + "# GRADED FUNCTION: unet_model\n", + "def unet_model(input_size=(96, 128, 3), n_filters=32, n_classes=23):\n", + " \"\"\"\n", + " Unet model\n", + " \n", + " Arguments:\n", + " input_size -- Input shape \n", + " n_filters -- Number of filters for the convolutional layers\n", + " n_classes -- Number of output classes\n", + " Returns: \n", + " model -- tf.keras.Model\n", + " \"\"\"\n", + " inputs = Input(input_size)\n", + " # Contracting Path (encoding)\n", + " # Add a conv_block with the inputs of the unet_ model and n_filters\n", + " ### START CODE HERE\n", + " cblock1 = conv_block(inputs=inputs, n_filters=n_filters*1)\n", + " # Chain the first element of the output of each block to be the input of the next conv_block. \n", + " # Double the number of filters at each new step\n", + " cblock2 = conv_block(inputs=cblock1[0], n_filters=n_filters*2)\n", + " cblock3 = conv_block(inputs=cblock2[0], n_filters=n_filters*4)\n", + " # Include a dropout of 0.3 for this layer\n", + " cblock4 = conv_block(inputs=cblock3[0], n_filters=n_filters*8,dropout_prob=0.3)\n", + " # Include a dropout of 0.3 for this layer, and avoid the max_pooling layer\n", + " cblock5 = conv_block(inputs=cblock4[0], n_filters=n_filters*16,dropout_prob=0.3, max_pooling=False) \n", + " ### END CODE HERE\n", + " \n", + " # Expanding Path (decoding)\n", + " # Add the first upsampling_block.\n", + " # From here,at each step, use half the number of filters of the previous block \n", + " # Use the cblock5[0] as expansive_input and cblock4[1] as contractive_input and n_filters * 8\n", + " ### START CODE HERE\n", + " ublock6 = upsampling_block(cblock5[0], cblock4[1], n_filters*8)\n", + " # Chain the output of the previous block as expansive_input and the corresponding contractive block output.\n", + " # Note that you must use the second element of the contractive block i.e before the maxpooling layer. \n", + " \n", + " ublock7 = upsampling_block(ublock6, cblock3[1], n_filters*4)\n", + " ublock8 = upsampling_block(ublock7, cblock2[1], n_filters*2)\n", + " ublock9 = upsampling_block(ublock8, cblock1[1], n_filters*1)\n", + " ### END CODE HERE\n", + "\n", + " conv9 = Conv2D(n_filters,\n", + " 3,\n", + " activation='relu',\n", + " padding='same',\n", + " kernel_initializer='he_normal')(ublock9)\n", + "\n", + " # Add a Conv2D layer with n_classes filter, kernel size of 1 and a 'same' padding\n", + " ### START CODE HERE\n", + " conv10 = Conv2D(n_classes, 1, padding='same')(conv9)\n", + " ### END CODE HERE\n", + " \n", + " model = tf.keras.Model(inputs=inputs, outputs=conv10)\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-16d8e2fe99b33552", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "import outputs\n", + "img_height = 96\n", + "img_width = 128\n", + "num_channels = 3\n", + "\n", + "unet = unet_model((img_height, img_width, num_channels))\n", + "comparator(summary(unet), outputs.unet_model_output)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.5 - Set Model Dimensions" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "id": "jCQIwZlnsDTQ" + }, + "outputs": [], + "source": [ + "img_height = 96\n", + "img_width = 128\n", + "num_channels = 3\n", + "\n", + "unet = unet_model((img_height, img_width, num_channels))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Check out the model summary below! " + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"functional_9\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "input_8 (InputLayer) [(None, 96, 128, 3)] 0 \n", + "__________________________________________________________________________________________________\n", + "conv2d_28 (Conv2D) (None, 96, 128, 32) 896 input_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_29 (Conv2D) (None, 96, 128, 32) 9248 conv2d_28[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_6 (MaxPooling2D) (None, 48, 64, 32) 0 conv2d_29[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_30 (Conv2D) (None, 48, 64, 64) 18496 max_pooling2d_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_31 (Conv2D) (None, 48, 64, 64) 36928 conv2d_30[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_7 (MaxPooling2D) (None, 24, 32, 64) 0 conv2d_31[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_32 (Conv2D) (None, 24, 32, 128) 73856 max_pooling2d_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_33 (Conv2D) (None, 24, 32, 128) 147584 conv2d_32[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_8 (MaxPooling2D) (None, 12, 16, 128) 0 conv2d_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_34 (Conv2D) (None, 12, 16, 256) 295168 max_pooling2d_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_35 (Conv2D) (None, 12, 16, 256) 590080 conv2d_34[0][0] \n", + "__________________________________________________________________________________________________\n", + "dropout_3 (Dropout) (None, 12, 16, 256) 0 conv2d_35[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_9 (MaxPooling2D) (None, 6, 8, 256) 0 dropout_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_36 (Conv2D) (None, 6, 8, 512) 1180160 max_pooling2d_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_37 (Conv2D) (None, 6, 8, 512) 2359808 conv2d_36[0][0] \n", + "__________________________________________________________________________________________________\n", + "dropout_4 (Dropout) (None, 6, 8, 512) 0 conv2d_37[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_transpose_5 (Conv2DTrans (None, 12, 16, 256) 1179904 dropout_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "concatenate_5 (Concatenate) (None, 12, 16, 512) 0 conv2d_transpose_5[0][0] \n", + " dropout_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_38 (Conv2D) (None, 12, 16, 256) 1179904 concatenate_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_39 (Conv2D) (None, 12, 16, 256) 590080 conv2d_38[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_transpose_6 (Conv2DTrans (None, 24, 32, 128) 295040 conv2d_39[0][0] \n", + "__________________________________________________________________________________________________\n", + "concatenate_6 (Concatenate) (None, 24, 32, 256) 0 conv2d_transpose_6[0][0] \n", + " conv2d_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_40 (Conv2D) (None, 24, 32, 128) 295040 concatenate_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_41 (Conv2D) (None, 24, 32, 128) 147584 conv2d_40[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_transpose_7 (Conv2DTrans (None, 48, 64, 64) 73792 conv2d_41[0][0] \n", + "__________________________________________________________________________________________________\n", + "concatenate_7 (Concatenate) (None, 48, 64, 128) 0 conv2d_transpose_7[0][0] \n", + " conv2d_31[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_42 (Conv2D) (None, 48, 64, 64) 73792 concatenate_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_43 (Conv2D) (None, 48, 64, 64) 36928 conv2d_42[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_transpose_8 (Conv2DTrans (None, 96, 128, 32) 18464 conv2d_43[0][0] \n", + "__________________________________________________________________________________________________\n", + "concatenate_8 (Concatenate) (None, 96, 128, 64) 0 conv2d_transpose_8[0][0] \n", + " conv2d_29[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_44 (Conv2D) (None, 96, 128, 32) 18464 concatenate_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_45 (Conv2D) (None, 96, 128, 32) 9248 conv2d_44[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_46 (Conv2D) (None, 96, 128, 32) 9248 conv2d_45[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_47 (Conv2D) (None, 96, 128, 23) 759 conv2d_46[0][0] \n", + "==================================================================================================\n", + "Total params: 8,640,471\n", + "Trainable params: 8,640,471\n", + "Non-trainable params: 0\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "unet.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "A02eTdbXDDVv" + }, + "source": [ + "\n", + "### 3.6 - Loss Function\n", + "\n", + "In semantic segmentation, you need as many masks as you have object classes. In the dataset you're using, each pixel in every mask has been assigned a single integer probability that it belongs to a certain class, from 0 to num_classes-1. The correct class is the layer with the higher probability. \n", + "\n", + "This is different from categorical crossentropy, where the labels should be one-hot encoded (just 0s and 1s). Here, you'll use sparse categorical crossentropy as your loss function, to perform pixel-wise multiclass prediction. Sparse categorical crossentropy is more efficient than other loss functions when you're dealing with lots of classes." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "id": "AGfA5_7NtH9i" + }, + "outputs": [], + "source": [ + "unet.compile(optimizer='adam',\n", + " loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n", + " metrics=['accuracy'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Cz5Z8XdbC6Hg" + }, + "source": [ + "\n", + "### 3.7 - Dataset Handling\n", + "\n", + "Below, define a function that allows you to display both an input image, and its ground truth: the true mask. The true mask is what your trained model output is aiming to get as close to as possible. " + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "id": "mSuxeWlSgU5f" + }, + "outputs": [], + "source": [ + "def display(display_list):\n", + " plt.figure(figsize=(15, 15))\n", + "\n", + " title = ['Input Image', 'True Mask', 'Predicted Mask']\n", + "\n", + " for i in range(len(display_list)):\n", + " plt.subplot(1, len(display_list), i+1)\n", + " plt.title(title[i])\n", + " plt.imshow(tf.keras.preprocessing.image.array_to_img(display_list[i]))\n", + " plt.axis('off')\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 350 + }, + "id": "xpFmVX5vgXRj", + "outputId": "676f40ec-2c76-4fbe-8491-fd04c96c51d9" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(480, 640, 1)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for image, mask in image_ds.take(1):\n", + " sample_image, sample_mask = image, mask\n", + " print(mask.shape)\n", + "display([sample_image, sample_mask])" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 350 + }, + "id": "cqON4c2UGgC4", + "outputId": "43f3503e-2b8c-4f42-cda0-76c46ada9c13" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(96, 128, 1)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for image, mask in processed_image_ds.take(1):\n", + " sample_image, sample_mask = image, mask\n", + " print(mask.shape)\n", + "display([sample_image, sample_mask])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Sco-8XdVC-gN" + }, + "source": [ + "\n", + "## 4 - Train the Model" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "1Ne0IowRgcom", + "outputId": "0e68b994-2a09-4cd8-b0d7-c0d042d81144" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(TensorSpec(shape=(96, 128, 3), dtype=tf.float32, name=None), TensorSpec(shape=(96, 128, 1), dtype=tf.uint8, name=None))\n", + "Epoch 1/40\n", + "13/34 [==========>...................] - ETA: 22s - loss: 3.2405 - accuracy: 0.2856" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mtrain_dataset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprocessed_image_ds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshuffle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBUFFER_SIZE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBATCH_SIZE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m 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\u001b[0;32mexcept\u001b[0m \u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "EPOCHS = 40\n", + "VAL_SUBSPLITS = 5\n", + "BUFFER_SIZE = 500\n", + "BATCH_SIZE = 32\n", + "processed_image_ds.batch(BATCH_SIZE)\n", + "train_dataset = processed_image_ds.cache().shuffle(BUFFER_SIZE).batch(BATCH_SIZE)\n", + "print(processed_image_ds.element_spec)\n", + "model_history = unet.fit(train_dataset, epochs=EPOCHS)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.1 - Create Predicted Masks \n", + "\n", + "Now, define a function that uses `tf.argmax` in the axis of the number of classes to return the index with the largest value and merge the prediction into a single image:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "AvFEnJrHhmJo" + }, + "outputs": [], + "source": [ + "def create_mask(pred_mask):\n", + " pred_mask = tf.argmax(pred_mask, axis=-1)\n", + " pred_mask = pred_mask[..., tf.newaxis]\n", + " return pred_mask[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.2 - Plot Model Accuracy\n", + "\n", + "Let's see how your model did! " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 282 + }, + "id": "PqCzmTmnl1lI", + "outputId": "f79baa53-3c7b-4161-e680-2279a3b4d7fb" + }, + "outputs": [], + "source": [ + "plt.plot(model_history.history[\"accuracy\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 4.3 - Show Predictions \n", + "\n", + "Next, check your predicted masks against the true mask and the original input image:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "BX4uCaP2glMo" + }, + "outputs": [], + "source": [ + "def show_predictions(dataset=None, num=1):\n", + " \"\"\"\n", + " Displays the first image of each of the num batches\n", + " \"\"\"\n", + " if dataset:\n", + " for image, mask in dataset.take(num):\n", + " pred_mask = unet.predict(image)\n", + " display([image[0], mask[0], create_mask(pred_mask)])\n", + " else:\n", + " display([sample_image, sample_mask,\n", + " create_mask(unet.predict(sample_image[tf.newaxis, ...]))])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 446 + }, + "id": "5qODM_hRhfR5", + "outputId": "78a90e2a-d5aa-4c39-e591-9d78e9526404" + }, + "outputs": [], + "source": [ + "show_predictions(train_dataset, 6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With 40 epochs you get amazing results!\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Free Up Resources for Other Learners\n", + "\n", + "In order to provide our learners a smooth learning experience, please free up the resources used by your assignment by running the cell below so that the other learners can take advantage of those resources just as much as you did. Thank you!\n", + "\n", + "**Note**: \n", + "- Run the cell below when you are done with the assignment and are ready to submit it for grading.\n", + "- When you'll run it, a pop up will open, click `Ok`.\n", + "- Running the cell will `restart the kernel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%javascript\n", + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Conclusion \n", + "\n", + "You've come to the end of this assignment. Awesome work creating a state-of-the art model for semantic image segmentation! This is a very important task for self-driving cars to get right. Elon Musk will surely be knocking down your door at any moment. ;) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + " \n", + "**What you should remember**: \n", + "\n", + "* Semantic image segmentation predicts a label for every single pixel in an image\n", + "* U-Net uses an equal number of convolutional blocks and transposed convolutions for downsampling and upsampling\n", + "* Skip connections are used to prevent border pixel information loss and overfitting in U-Net" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Residual_Networks.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Residual_Networks.ipynb new file mode 100644 index 00000000000..3e764c72b68 --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Residual_Networks.ipynb @@ -0,0 +1,2034 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Residual Networks\n", + "\n", + "Welcome to the first assignment of this week! You'll be building a very deep convolutional network, using Residual Networks (ResNets). In theory, very deep networks can represent very complex functions; but in practice, they are hard to train. Residual Networks, introduced by [He et al.](https://arxiv.org/pdf/1512.03385.pdf), allow you to train much deeper networks than were previously feasible.\n", + "\n", + "**By the end of this assignment, you'll be able to:**\n", + "\n", + "- Implement the basic building blocks of ResNets in a deep neural network using Keras\n", + "- Put together these building blocks to implement and train a state-of-the-art neural network for image classification\n", + "- Implement a skip connection in your network\n", + "\n", + "For this assignment, you'll use Keras. \n", + "\n", + "Before jumping into the problem, run the cell below to load the required packages.\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Content\n", + "\n", + "- [1 - Packages](#1)\n", + "- [2 - The Problem of Very Deep Neural Networks](#2)\n", + "- [3 - Building a Residual Network](#3)\n", + " - [3.1 - The Identity Block](#3-1)\n", + " - [Exercise 1 - identity_block](#ex-1)\n", + " - [3.2 - The Convolutional Block](#3-2)\n", + " - [Exercise 2 - convolutional_block](#ex-2)\n", + "- [4 - Building Your First ResNet Model (50 layers)](#4)\n", + " - [Exercise 3 - ResNet50](#ex-3)\n", + "- [5 - Test on Your Own Image (Optional/Ungraded)](#5)\n", + "- [6 - Bibliography](#6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import tensorflow as tf\n", + "import numpy as np\n", + "import scipy.misc\n", + "from tensorflow.keras.applications.resnet_v2 import ResNet50V2\n", + "from tensorflow.keras.preprocessing import image\n", + "from tensorflow.keras.applications.resnet_v2 import preprocess_input, decode_predictions\n", + "from tensorflow.keras import layers\n", + "from tensorflow.keras.layers import Input, Add, Dense, Activation, ZeroPadding2D, BatchNormalization, Flatten, Conv2D, AveragePooling2D, MaxPooling2D, GlobalMaxPooling2D\n", + "from tensorflow.keras.models import Model, load_model\n", + "from resnets_utils import *\n", + "from tensorflow.keras.initializers import random_uniform, glorot_uniform, constant, identity\n", + "from tensorflow.python.framework.ops import EagerTensor\n", + "from matplotlib.pyplot import imshow\n", + "\n", + "from test_utils import summary, comparator\n", + "import public_tests\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - The Problem of Very Deep Neural Networks\n", + "\n", + "Last week, you built your first convolutional neural networks: first manually with numpy, then using Tensorflow and Keras. \n", + "\n", + "In recent years, neural networks have become much deeper, with state-of-the-art networks evolving from having just a few layers (e.g., AlexNet) to over a hundred layers.\n", + "\n", + "* The main benefit of a very deep network is that it can represent very complex functions. It can also learn features at many different levels of abstraction, from edges (at the shallower layers, closer to the input) to very complex features (at the deeper layers, closer to the output). \n", + "\n", + "* However, using a deeper network doesn't always help. A huge barrier to training them is vanishing gradients: very deep networks often have a gradient signal that goes to zero quickly, thus making gradient descent prohibitively slow.\n", + "\n", + "* More specifically, during gradient descent, as you backpropagate from the final layer back to the first layer, you are multiplying by the weight matrix on each step, and thus the gradient can decrease exponentially quickly to zero (or, in rare cases, grow exponentially quickly and \"explode,\" from gaining very large values). \n", + "\n", + "* During training, you might therefore see the magnitude (or norm) of the gradient for the shallower layers decrease to zero very rapidly as training proceeds, as shown below: " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "
Figure 1 : Vanishing gradient
The speed of learning decreases very rapidly for the shallower layers as the network trains
\n", + "\n", + "Not to worry! You are now going to solve this problem by building a Residual Network!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Building a Residual Network\n", + "\n", + "In ResNets, a \"shortcut\" or a \"skip connection\" allows the model to skip layers: \n", + "\n", + "\n", + "
Figure 2 : A ResNet block showing a skip-connection
\n", + "\n", + "The image on the left shows the \"main path\" through the network. The image on the right adds a shortcut to the main path. By stacking these ResNet blocks on top of each other, you can form a very deep network. \n", + "\n", + "The lecture mentioned that having ResNet blocks with the shortcut also makes it very easy for one of the blocks to learn an identity function. This means that you can stack on additional ResNet blocks with little risk of harming training set performance. \n", + " \n", + "On that note, there is also some evidence that the ease of learning an identity function accounts for ResNets' remarkable performance even more than skip connections help with vanishing gradients.\n", + "\n", + "Two main types of blocks are used in a ResNet, depending mainly on whether the input/output dimensions are the same or different. You are going to implement both of them: the \"identity block\" and the \"convolutional block.\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.1 - The Identity Block\n", + "\n", + "The identity block is the standard block used in ResNets, and corresponds to the case where the input activation (say $a^{[l]}$) has the same dimension as the output activation (say $a^{[l+2]}$). To flesh out the different steps of what happens in a ResNet's identity block, here is an alternative diagram showing the individual steps:\n", + "\n", + "\n", + "
Figure 3 : Identity block. Skip connection \"skips over\" 2 layers.
\n", + "\n", + "The upper path is the \"shortcut path.\" The lower path is the \"main path.\" In this diagram, notice the CONV2D and ReLU steps in each layer. To speed up training, a BatchNorm step has been added. Don't worry about this being complicated to implement--you'll see that BatchNorm is just one line of code in Keras! \n", + "\n", + "In this exercise, you'll actually implement a slightly more powerful version of this identity block, in which the skip connection \"skips over\" 3 hidden layers rather than 2 layers. It looks like this: \n", + "\n", + "\n", + "
Figure 4 : Identity block. Skip connection \"skips over\" 3 layers.
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These are the individual steps:\n", + "\n", + "First component of main path: \n", + "- The first CONV2D has $F_1$ filters of shape (1,1) and a stride of (1,1). Its padding is \"valid\". Use 0 as the seed for the random uniform initialization: `kernel_initializer = initializer(seed=0)`. \n", + "- The first BatchNorm is normalizing the 'channels' axis.\n", + "- Then apply the ReLU activation function. This has no hyperparameters. \n", + "\n", + "Second component of main path:\n", + "- The second CONV2D has $F_2$ filters of shape $(f,f)$ and a stride of (1,1). Its padding is \"same\". Use 0 as the seed for the random uniform initialization: `kernel_initializer = initializer(seed=0)`.\n", + "- The second BatchNorm is normalizing the 'channels' axis.\n", + "- Then apply the ReLU activation function. This has no hyperparameters.\n", + "\n", + "Third component of main path:\n", + "- The third CONV2D has $F_3$ filters of shape (1,1) and a stride of (1,1). Its padding is \"valid\". Use 0 as the seed for the random uniform initialization: `kernel_initializer = initializer(seed=0)`. \n", + "- The third BatchNorm is normalizing the 'channels' axis.\n", + "- Note that there is **no** ReLU activation function in this component. \n", + "\n", + "Final step: \n", + "- The `X_shortcut` and the output from the 3rd layer `X` are added together.\n", + "- **Hint**: The syntax will look something like `Add()([var1,var2])`\n", + "- Then apply the ReLU activation function. This has no hyperparameters. \n", + "\n", + "\n", + "### Exercise 1 - identity_block\n", + "\n", + "Implement the ResNet identity block. The first component of the main path has been implemented for you already! First, you should read these docs carefully to make sure you understand what's happening. Then, implement the rest. \n", + "- To implement the Conv2D step: [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D)\n", + "- To implement BatchNorm: [BatchNormalization](https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization) `BatchNormalization(axis = 3)(X, training = training)`. If training is set to False, its weights are not updated with the new examples. I.e when the model is used in prediction mode.\n", + "- For the activation, use: `Activation('relu')(X)`\n", + "- To add the value passed forward by the shortcut: [Add](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Add)\n", + "\n", + "We have added the initializer argument to our functions. This parameter receives an initializer function like the ones included in the package [tensorflow.keras.initializers](https://www.tensorflow.org/api_docs/python/tf/keras/initializers) or any other custom initializer. By default it will be set to [random_uniform](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/RandomUniform)\n", + "\n", + "Remember that these functions accept a `seed` argument that can be any value you want, but that in this notebook must set to 0 for **grading purposes**." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " Here is where you're actually using the power of the Functional API to create a shortcut path: " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-0017b68317ffa974", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1\n", + "# GRADED FUNCTION: identity_block\n", + "\n", + "def identity_block(X, f, filters, training=True, initializer=random_uniform):\n", + " \"\"\"\n", + " Implementation of the identity block as defined in Figure 4\n", + " \n", + " Arguments:\n", + " X -- input tensor of shape (m, n_H_prev, n_W_prev, n_C_prev)\n", + " f -- integer, specifying the shape of the middle CONV's window for the main path\n", + " filters -- python list of integers, defining the number of filters in the CONV layers of the main path\n", + " training -- True: Behave in training mode\n", + " False: Behave in inference mode\n", + " initializer -- to set up the initial weights of a layer. Equals to random uniform initializer\n", + " \n", + " Returns:\n", + " X -- output of the identity block, tensor of shape (m, n_H, n_W, n_C)\n", + " \"\"\"\n", + " \n", + " # Retrieve Filters\n", + " F1, F2, F3 = filters\n", + " \n", + " # Save the input value. You'll need this later to add back to the main path. \n", + " X_shortcut = X\n", + " \n", + " # First component of main path\n", + " X = Conv2D(filters = F1, kernel_size = 1, strides = (1,1), padding = 'valid', kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training = training) # Default axis\n", + " X = Activation('relu')(X)\n", + " \n", + " ### START CODE HERE\n", + " ## Second component of main path (β‰ˆ3 lines)\n", + " ## Set the padding = 'same'\n", + " X = Conv2D(filters = F2, kernel_size = f,strides = (1, 1),padding='same',kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training=training)\n", + " X = Activation('relu')(X) \n", + "\n", + " ## Third component of main path (β‰ˆ2 lines)\n", + " ## Set the padding = 'valid'\n", + " X = Conv2D(filters = F3, kernel_size = 1, strides = (1, 1), padding='valid', kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training=training)\n", + " \n", + " ## Final step: Add shortcut value to main path, and pass it through a RELU activation (β‰ˆ2 lines)\n", + " X = Add()([X_shortcut,X])\n", + " X = Activation('relu')(X)\n", + " ### END CODE HERE\n", + "\n", + " return X" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-e73a8466b807e261", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1mWith training=False\u001b[0m\n", + "\n", + "[[[ 0. 0. 0. 0. ]\n", + " [ 0. 0. 0. 0. ]]\n", + "\n", + " [[192.71234 192.71234 192.71234 96.85617]\n", + " [ 96.85617 96.85617 96.85617 48.92808]]\n", + "\n", + " [[578.1371 578.1371 578.1371 290.5685 ]\n", + " [290.5685 290.5685 290.5685 146.78426]]]\n", + "96.85617\n", + "\n", + "\u001b[1mWith training=True\u001b[0m\n", + "\n", + "[[[0. 0. 0. 0. ]\n", + " [0. 0. 0. 0. ]]\n", + "\n", + " [[0.40739 0.40739 0.40739 0.40739]\n", + " [0.40739 0.40739 0.40739 0.40739]]\n", + "\n", + " [[4.99991 4.99991 4.99991 3.25948]\n", + " [3.25948 3.25948 3.25948 2.40739]]]\n", + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "np.random.seed(1)\n", + "X1 = np.ones((1, 4, 4, 3)) * -1\n", + "X2 = np.ones((1, 4, 4, 3)) * 1\n", + "X3 = np.ones((1, 4, 4, 3)) * 3\n", + "\n", + "X = np.concatenate((X1, X2, X3), axis = 0).astype(np.float32)\n", + "\n", + "A3 = identity_block(X, f=2, filters=[4, 4, 3],\n", + " initializer=lambda seed=0:constant(value=1),\n", + " training=False)\n", + "print('\\033[1mWith training=False\\033[0m\\n')\n", + "A3np = A3.numpy()\n", + "print(np.around(A3.numpy()[:,(0,-1),:,:].mean(axis = 3), 5))\n", + "resume = A3np[:,(0,-1),:,:].mean(axis = 3)\n", + "print(resume[1, 1, 0])\n", + "\n", + "print('\\n\\033[1mWith training=True\\033[0m\\n')\n", + "np.random.seed(1)\n", + "A4 = identity_block(X, f=2, filters=[3, 3, 3],\n", + " initializer=lambda seed=0:constant(value=1),\n", + " training=True)\n", + "print(np.around(A4.numpy()[:,(0,-1),:,:].mean(axis = 3), 5))\n", + "\n", + "public_tests.identity_block_test(identity_block)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected value**\n", + "\n", + "```\n", + "With training=False\n", + "\n", + "[[[ 0. 0. 0. 0. ]\n", + " [ 0. 0. 0. 0. ]]\n", + "\n", + " [[192.71234 192.71234 192.71234 96.85617]\n", + " [ 96.85617 96.85617 96.85617 48.92808]]\n", + "\n", + " [[578.1371 578.1371 578.1371 290.5685 ]\n", + " [290.5685 290.5685 290.5685 146.78426]]]\n", + "96.85617\n", + "\n", + "With training=True\n", + "\n", + "[[[0. 0. 0. 0. ]\n", + " [0. 0. 0. 0. ]]\n", + "\n", + " [[0.40739 0.40739 0.40739 0.40739]\n", + " [0.40739 0.40739 0.40739 0.40739]]\n", + "\n", + " [[4.99991 4.99991 4.99991 3.25948]\n", + " [3.25948 3.25948 3.25948 2.40739]]]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - The Convolutional Block\n", + "\n", + "The ResNet \"convolutional block\" is the second block type. You can use this type of block when the input and output dimensions don't match up. The difference with the identity block is that there is a CONV2D layer in the shortcut path: \n", + "\n", + "\n", + "
Figure 4 : Convolutional block
\n", + "\n", + "* The CONV2D layer in the shortcut path is used to resize the input $x$ to a different dimension, so that the dimensions match up in the final addition needed to add the shortcut value back to the main path. (This plays a similar role as the matrix $W_s$ discussed in lecture.) \n", + "* For example, to reduce the activation dimensions's height and width by a factor of 2, you can use a 1x1 convolution with a stride of 2. \n", + "* The CONV2D layer on the shortcut path does not use any non-linear activation function. Its main role is to just apply a (learned) linear function that reduces the dimension of the input, so that the dimensions match up for the later addition step. \n", + "* As for the previous exercise, the additional `initializer` argument is required for grading purposes, and it has been set by default to [glorot_uniform](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/GlorotUniform)\n", + "\n", + "The details of the convolutional block are as follows. \n", + "\n", + "First component of main path:\n", + "- The first CONV2D has $F_1$ filters of shape (1,1) and a stride of (s,s). Its padding is \"valid\". Use 0 as the `glorot_uniform` seed `kernel_initializer = initializer(seed=0)`.\n", + "- The first BatchNorm is normalizing the 'channels' axis.\n", + "- Then apply the ReLU activation function. This has no hyperparameters. \n", + "\n", + "Second component of main path:\n", + "- The second CONV2D has $F_2$ filters of shape (f,f) and a stride of (1,1). Its padding is \"same\". Use 0 as the `glorot_uniform` seed `kernel_initializer = initializer(seed=0)`.\n", + "- The second BatchNorm is normalizing the 'channels' axis.\n", + "- Then apply the ReLU activation function. This has no hyperparameters. \n", + "\n", + "Third component of main path:\n", + "- The third CONV2D has $F_3$ filters of shape (1,1) and a stride of (1,1). Its padding is \"valid\". Use 0 as the `glorot_uniform` seed `kernel_initializer = initializer(seed=0)`.\n", + "- The third BatchNorm is normalizing the 'channels' axis. Note that there is no ReLU activation function in this component. \n", + "\n", + "Shortcut path:\n", + "- The CONV2D has $F_3$ filters of shape (1,1) and a stride of (s,s). Its padding is \"valid\". Use 0 as the `glorot_uniform` seed `kernel_initializer = initializer(seed=0)`.\n", + "- The BatchNorm is normalizing the 'channels' axis. \n", + "\n", + "Final step: \n", + "- The shortcut and the main path values are added together.\n", + "- Then apply the ReLU activation function. This has no hyperparameters. \n", + " \n", + " \n", + "### Exercise 2 - convolutional_block\n", + " \n", + "Implement the convolutional block. The first component of the main path is already implemented; then it's your turn to implement the rest! As before, always use 0 as the seed for the random initialization, to ensure consistency with the grader.\n", + "- [Conv2D](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D)\n", + "- [BatchNormalization](https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization) (axis: Integer, the axis that should be normalized (typically the features axis)) `BatchNormalization(axis = 3)(X, training = training)`. If training is set to False, its weights are not updated with the new examples. I.e when the model is used in prediction mode.\n", + "- For the activation, use: `Activation('relu')(X)`\n", + "- [Add](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Add)\n", + " \n", + "We have added the initializer argument to our functions. This parameter receives an initializer function like the ones included in the package [tensorflow.keras.initializers](https://www.tensorflow.org/api_docs/python/tf/keras/initializers) or any other custom initializer. By default it will be set to [glorot_uniform](https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/initializers/GlorotUniform)\n", + "\n", + "Remember that these functions accept a `seed` argument that can be any value you want, but that in this notebook must set to 0 for **grading purposes**." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-df47af4847e5335f", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2\n", + "# GRADED FUNCTION: convolutional_block\n", + "\n", + "def convolutional_block(X, f, filters, s = 2, training=True, initializer=glorot_uniform):\n", + " \"\"\"\n", + " Implementation of the convolutional block as defined in Figure 4\n", + " \n", + " Arguments:\n", + " X -- input tensor of shape (m, n_H_prev, n_W_prev, n_C_prev)\n", + " f -- integer, specifying the shape of the middle CONV's window for the main path\n", + " filters -- python list of integers, defining the number of filters in the CONV layers of the main path\n", + " s -- Integer, specifying the stride to be used\n", + " training -- True: Behave in training mode\n", + " False: Behave in inference mode\n", + " initializer -- to set up the initial weights of a layer. Equals to Glorot uniform initializer, \n", + " also called Xavier uniform initializer.\n", + " \n", + " Returns:\n", + " X -- output of the convolutional block, tensor of shape (m, n_H, n_W, n_C)\n", + " \"\"\"\n", + " \n", + " # Retrieve Filters\n", + " F1, F2, F3 = filters\n", + " \n", + " # Save the input value\n", + " X_shortcut = X\n", + "\n", + "\n", + " ##### MAIN PATH #####\n", + " \n", + " # First component of main path glorot_uniform(seed=0)\n", + " X = Conv2D(filters = F1, kernel_size = 1, strides = (s, s), padding='valid', kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training=training)\n", + " X = Activation('relu')(X)\n", + "\n", + " ### START CODE HERE\n", + " \n", + " ## Second component of main path (β‰ˆ3 lines)\n", + " X = Conv2D(filters = F2, kernel_size = f,strides = (1, 1),padding='same',kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training=training)\n", + " X = Activation('relu')(X)\n", + "\n", + " ## Third component of main path (β‰ˆ2 lines)\n", + " X = Conv2D(filters = F3, kernel_size = 1, strides = (1, 1), padding='valid', kernel_initializer = initializer(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X, training=training)\n", + " \n", + " ##### SHORTCUT PATH ##### (β‰ˆ2 lines)\n", + " X_shortcut = Conv2D(filters = F3, kernel_size = 1, strides = (s, s), padding='valid', kernel_initializer = initializer(seed=0))(X_shortcut)\n", + " X_shortcut = BatchNormalization(axis = 3)(X_shortcut, training=training)\n", + " \n", + " ### END CODE HERE\n", + "\n", + " # Final step: Add shortcut value to main path (Use this order [X, X_shortcut]), and pass it through a RELU activation\n", + " X = Add()([X, X_shortcut])\n", + " X = Activation('relu')(X)\n", + " \n", + " return X" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-95c291eb244218fe", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tf.Tensor(\n", + "[[[0. 0.66683817 0. 0. 0.88853896 0.5274254 ]\n", + " [0. 0.65053666 0. 0. 0.89592844 0.49965227]]\n", + "\n", + " [[0. 0.6312079 0. 0. 0.8636247 0.47643146]\n", + " [0. 0.5688321 0. 0. 0.85534114 0.41709304]]], shape=(2, 2, 6), dtype=float32)\n", + "\u001b[92mAll tests passed!\n" + ] + } + ], + "source": [ + "from outputs import convolutional_block_output1, convolutional_block_output2\n", + "np.random.seed(1)\n", + "#X = np.random.randn(3, 4, 4, 6).astype(np.float32)\n", + "X1 = np.ones((1, 4, 4, 3)) * -1\n", + "X2 = np.ones((1, 4, 4, 3)) * 1\n", + "X3 = np.ones((1, 4, 4, 3)) * 3\n", + "\n", + "X = np.concatenate((X1, X2, X3), axis = 0).astype(np.float32)\n", + "\n", + "A = convolutional_block(X, f = 2, filters = [2, 4, 6], training=False)\n", + "\n", + "assert type(A) == EagerTensor, \"Use only tensorflow and keras functions\"\n", + "assert tuple(tf.shape(A).numpy()) == (3, 2, 2, 6), \"Wrong shape.\"\n", + "assert np.allclose(A.numpy(), convolutional_block_output1), \"Wrong values when training=False.\"\n", + "print(A[0])\n", + "\n", + "B = convolutional_block(X, f = 2, filters = [2, 4, 6], training=True)\n", + "assert np.allclose(B.numpy(), convolutional_block_output2), \"Wrong values when training=True.\"\n", + "\n", + "print('\\033[92mAll tests passed!')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected value**\n", + "\n", + "```\n", + "tf.Tensor(\n", + "[[[0. 0.66683817 0. 0. 0.88853896 0.5274254 ]\n", + " [0. 0.65053666 0. 0. 0.89592844 0.49965227]]\n", + "\n", + " [[0. 0.6312079 0. 0. 0.8636247 0.47643146]\n", + " [0. 0.5688321 0. 0. 0.85534114 0.41709304]]], shape=(2, 2, 6), dtype=float32)\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " \n", + "## 4 - Building Your First ResNet Model (50 layers)\n", + "\n", + "You now have the necessary blocks to build a very deep ResNet. The following figure describes in detail the architecture of this neural network. \"ID BLOCK\" in the diagram stands for \"Identity block,\" and \"ID BLOCK x3\" means you should stack 3 identity blocks together.\n", + "\n", + "\n", + "
Figure 5 : ResNet-50 model
\n", + "\n", + "The details of this ResNet-50 model are:\n", + "- Zero-padding pads the input with a pad of (3,3)\n", + "- Stage 1:\n", + " - The 2D Convolution has 64 filters of shape (7,7) and uses a stride of (2,2). \n", + " - BatchNorm is applied to the 'channels' axis of the input.\n", + " - ReLU activation is applied.\n", + " - MaxPooling uses a (3,3) window and a (2,2) stride.\n", + "- Stage 2:\n", + " - The convolutional block uses three sets of filters of size [64,64,256], \"f\" is 3, and \"s\" is 1.\n", + " - The 2 identity blocks use three sets of filters of size [64,64,256], and \"f\" is 3.\n", + "- Stage 3:\n", + " - The convolutional block uses three sets of filters of size [128,128,512], \"f\" is 3 and \"s\" is 2.\n", + " - The 3 identity blocks use three sets of filters of size [128,128,512] and \"f\" is 3.\n", + "- Stage 4:\n", + " - The convolutional block uses three sets of filters of size [256, 256, 1024], \"f\" is 3 and \"s\" is 2.\n", + " - The 5 identity blocks use three sets of filters of size [256, 256, 1024] and \"f\" is 3.\n", + "- Stage 5:\n", + " - The convolutional block uses three sets of filters of size [512, 512, 2048], \"f\" is 3 and \"s\" is 2.\n", + " - The 2 identity blocks use three sets of filters of size [512, 512, 2048] and \"f\" is 3.\n", + "- The 2D Average Pooling uses a window of shape (2,2).\n", + "- The 'flatten' layer doesn't have any hyperparameters.\n", + "- The Fully Connected (Dense) layer reduces its input to the number of classes using a softmax activation.\n", + "\n", + " \n", + " \n", + "### Exercise 3 - ResNet50 \n", + " \n", + "Implement the ResNet with 50 layers described in the figure above. We have implemented Stages 1 and 2. Please implement the rest. (The syntax for implementing Stages 3-5 should be quite similar to that of Stage 2) Make sure you follow the naming convention in the text above. \n", + "\n", + "You'll need to use this function: \n", + "- Average pooling [see reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/AveragePooling2D)\n", + "\n", + "Here are some other functions we used in the code below:\n", + "- Conv2D: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D)\n", + "- BatchNorm: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/BatchNormalization) (axis: Integer, the axis that should be normalized (typically the features axis))\n", + "- Zero padding: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ZeroPadding2D)\n", + "- Max pooling: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool2D)\n", + "- Fully connected layer: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense)\n", + "- Addition: [See reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Add)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-10dc95a4cf6275b9", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C3\n", + "# GRADED FUNCTION: ResNet50\n", + "\n", + "def ResNet50(input_shape = (64, 64, 3), classes = 6):\n", + " \"\"\"\n", + " Stage-wise implementation of the architecture of the popular ResNet50:\n", + " CONV2D -> BATCHNORM -> RELU -> MAXPOOL -> CONVBLOCK -> IDBLOCK*2 -> CONVBLOCK -> IDBLOCK*3\n", + " -> CONVBLOCK -> IDBLOCK*5 -> CONVBLOCK -> IDBLOCK*2 -> AVGPOOL -> FLATTEN -> DENSE \n", + "\n", + " Arguments:\n", + " input_shape -- shape of the images of the dataset\n", + " classes -- integer, number of classes\n", + "\n", + " Returns:\n", + " model -- a Model() instance in Keras\n", + " \"\"\"\n", + " \n", + " # Define the input as a tensor with shape input_shape\n", + " X_input = Input(input_shape)\n", + "\n", + " \n", + " # Zero-Padding\n", + " X = ZeroPadding2D((3, 3))(X_input)\n", + " \n", + " # Stage 1\n", + " X = Conv2D(64, (7, 7), strides = (2, 2), kernel_initializer = glorot_uniform(seed=0))(X)\n", + " X = BatchNormalization(axis = 3)(X)\n", + " X = Activation('relu')(X)\n", + " X = MaxPooling2D((3, 3), strides=(2, 2))(X)\n", + "\n", + " # Stage 2\n", + " X = convolutional_block(X, f = 3, filters = [64, 64, 256], s = 1)\n", + " X = identity_block(X, 3, [64, 64, 256])\n", + " X = identity_block(X, 3, [64, 64, 256])\n", + "\n", + " ### START CODE HERE\n", + " \n", + " ## Stage 3 (β‰ˆ4 lines)\n", + " X = convolutional_block(X, f = 3, filters = [128,128,512], s = 2)\n", + " X = identity_block(X, 3, [128,128,512])\n", + " X = identity_block(X, 3, [128,128,512])\n", + " X = identity_block(X, 3, [128,128,512])\n", + " \n", + " ## Stage 4 (β‰ˆ6 lines)\n", + " X = convolutional_block(X, f = 3, filters = [256, 256, 1024], s = 2)\n", + " X = identity_block(X, 3, [256, 256, 1024])\n", + " X = identity_block(X, 3, [256, 256, 1024])\n", + " X = identity_block(X, 3, [256, 256, 1024])\n", + " X = identity_block(X, 3, [256, 256, 1024])\n", + " X = identity_block(X, 3, [256, 256, 1024])\n", + "\n", + " ## Stage 5 (β‰ˆ3 lines)\n", + " X = convolutional_block(X, f = 3, filters = [512, 512, 2048], s = 2)\n", + " X = identity_block(X, 3, [512, 512, 2048])\n", + " X = identity_block(X, 3, [512, 512, 2048])\n", + "\n", + " ## AVGPOOL (β‰ˆ1 line). Use \"X = AveragePooling2D(...)(X)\"\n", + " X = AveragePooling2D((2, 2))(X)\n", + " \n", + " ### END CODE HERE\n", + "\n", + " # output layer\n", + " X = Flatten()(X)\n", + " X = Dense(classes, activation='softmax', kernel_initializer = glorot_uniform(seed=0))(X)\n", + " \n", + " \n", + " # Create model\n", + " model = Model(inputs = X_input, outputs = X)\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run the following code to build the model's graph. If your implementation is incorrect, you'll know it by checking your accuracy when running `model.fit(...)` below." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"functional_7\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "input_4 (InputLayer) [(None, 64, 64, 3)] 0 \n", + "__________________________________________________________________________________________________\n", + "zero_padding2d_3 (ZeroPadding2D (None, 70, 70, 3) 0 input_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_199 (Conv2D) (None, 32, 32, 64) 9472 zero_padding2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_199 (BatchN (None, 32, 32, 64) 256 conv2d_199[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_183 (Activation) (None, 32, 32, 64) 0 batch_normalization_199[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d_3 (MaxPooling2D) (None, 15, 15, 64) 0 activation_183[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_200 (Conv2D) (None, 15, 15, 64) 4160 max_pooling2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_200 (BatchN (None, 15, 15, 64) 256 conv2d_200[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_184 (Activation) (None, 15, 15, 64) 0 batch_normalization_200[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_201 (Conv2D) (None, 15, 15, 64) 36928 activation_184[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_201 (BatchN (None, 15, 15, 64) 256 conv2d_201[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_185 (Activation) (None, 15, 15, 64) 0 batch_normalization_201[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_202 (Conv2D) (None, 15, 15, 256) 16640 activation_185[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_203 (Conv2D) (None, 15, 15, 256) 16640 max_pooling2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_202 (BatchN (None, 15, 15, 256) 1024 conv2d_202[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_203 (BatchN (None, 15, 15, 256) 1024 conv2d_203[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_60 (Add) (None, 15, 15, 256) 0 batch_normalization_202[0][0] \n", + " batch_normalization_203[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_186 (Activation) (None, 15, 15, 256) 0 add_60[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_204 (Conv2D) (None, 15, 15, 64) 16448 activation_186[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_204 (BatchN (None, 15, 15, 64) 256 conv2d_204[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_187 (Activation) (None, 15, 15, 64) 0 batch_normalization_204[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_205 (Conv2D) (None, 15, 15, 64) 36928 activation_187[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_205 (BatchN (None, 15, 15, 64) 256 conv2d_205[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_188 (Activation) (None, 15, 15, 64) 0 batch_normalization_205[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_206 (Conv2D) (None, 15, 15, 256) 16640 activation_188[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_206 (BatchN (None, 15, 15, 256) 1024 conv2d_206[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_61 (Add) (None, 15, 15, 256) 0 activation_186[0][0] \n", + " batch_normalization_206[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_189 (Activation) (None, 15, 15, 256) 0 add_61[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_207 (Conv2D) (None, 15, 15, 64) 16448 activation_189[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_207 (BatchN (None, 15, 15, 64) 256 conv2d_207[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_190 (Activation) (None, 15, 15, 64) 0 batch_normalization_207[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_208 (Conv2D) (None, 15, 15, 64) 36928 activation_190[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_208 (BatchN (None, 15, 15, 64) 256 conv2d_208[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_191 (Activation) (None, 15, 15, 64) 0 batch_normalization_208[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_209 (Conv2D) (None, 15, 15, 256) 16640 activation_191[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_209 (BatchN (None, 15, 15, 256) 1024 conv2d_209[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_62 (Add) (None, 15, 15, 256) 0 activation_189[0][0] \n", + " batch_normalization_209[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_192 (Activation) (None, 15, 15, 256) 0 add_62[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_210 (Conv2D) (None, 8, 8, 128) 32896 activation_192[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_210 (BatchN (None, 8, 8, 128) 512 conv2d_210[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_193 (Activation) (None, 8, 8, 128) 0 batch_normalization_210[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_211 (Conv2D) (None, 8, 8, 128) 147584 activation_193[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_211 (BatchN (None, 8, 8, 128) 512 conv2d_211[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_194 (Activation) (None, 8, 8, 128) 0 batch_normalization_211[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_212 (Conv2D) (None, 8, 8, 512) 66048 activation_194[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_213 (Conv2D) (None, 8, 8, 512) 131584 activation_192[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_212 (BatchN (None, 8, 8, 512) 2048 conv2d_212[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_213 (BatchN (None, 8, 8, 512) 2048 conv2d_213[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_63 (Add) (None, 8, 8, 512) 0 batch_normalization_212[0][0] \n", + " batch_normalization_213[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_195 (Activation) (None, 8, 8, 512) 0 add_63[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_214 (Conv2D) (None, 8, 8, 128) 65664 activation_195[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_214 (BatchN (None, 8, 8, 128) 512 conv2d_214[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_196 (Activation) (None, 8, 8, 128) 0 batch_normalization_214[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_215 (Conv2D) (None, 8, 8, 128) 147584 activation_196[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_215 (BatchN (None, 8, 8, 128) 512 conv2d_215[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_197 (Activation) (None, 8, 8, 128) 0 batch_normalization_215[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_216 (Conv2D) (None, 8, 8, 512) 66048 activation_197[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_216 (BatchN (None, 8, 8, 512) 2048 conv2d_216[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_64 (Add) (None, 8, 8, 512) 0 activation_195[0][0] \n", + " batch_normalization_216[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_198 (Activation) (None, 8, 8, 512) 0 add_64[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_217 (Conv2D) (None, 8, 8, 128) 65664 activation_198[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_217 (BatchN (None, 8, 8, 128) 512 conv2d_217[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_199 (Activation) (None, 8, 8, 128) 0 batch_normalization_217[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_218 (Conv2D) (None, 8, 8, 128) 147584 activation_199[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_218 (BatchN (None, 8, 8, 128) 512 conv2d_218[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_200 (Activation) (None, 8, 8, 128) 0 batch_normalization_218[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_219 (Conv2D) (None, 8, 8, 512) 66048 activation_200[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_219 (BatchN (None, 8, 8, 512) 2048 conv2d_219[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_65 (Add) (None, 8, 8, 512) 0 activation_198[0][0] \n", + " batch_normalization_219[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_201 (Activation) (None, 8, 8, 512) 0 add_65[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_220 (Conv2D) (None, 8, 8, 128) 65664 activation_201[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_220 (BatchN (None, 8, 8, 128) 512 conv2d_220[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_202 (Activation) (None, 8, 8, 128) 0 batch_normalization_220[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_221 (Conv2D) (None, 8, 8, 128) 147584 activation_202[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_221 (BatchN (None, 8, 8, 128) 512 conv2d_221[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_203 (Activation) (None, 8, 8, 128) 0 batch_normalization_221[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_222 (Conv2D) (None, 8, 8, 512) 66048 activation_203[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_222 (BatchN (None, 8, 8, 512) 2048 conv2d_222[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_66 (Add) (None, 8, 8, 512) 0 activation_201[0][0] \n", + " batch_normalization_222[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_204 (Activation) (None, 8, 8, 512) 0 add_66[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_223 (Conv2D) (None, 4, 4, 256) 131328 activation_204[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_223 (BatchN (None, 4, 4, 256) 1024 conv2d_223[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_205 (Activation) (None, 4, 4, 256) 0 batch_normalization_223[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_224 (Conv2D) (None, 4, 4, 256) 590080 activation_205[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_224 (BatchN (None, 4, 4, 256) 1024 conv2d_224[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_206 (Activation) (None, 4, 4, 256) 0 batch_normalization_224[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_225 (Conv2D) (None, 4, 4, 1024) 263168 activation_206[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_226 (Conv2D) (None, 4, 4, 1024) 525312 activation_204[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_225 (BatchN (None, 4, 4, 1024) 4096 conv2d_225[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_226 (BatchN (None, 4, 4, 1024) 4096 conv2d_226[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_67 (Add) (None, 4, 4, 1024) 0 batch_normalization_225[0][0] \n", + " batch_normalization_226[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_207 (Activation) (None, 4, 4, 1024) 0 add_67[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_227 (Conv2D) (None, 4, 4, 256) 262400 activation_207[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_227 (BatchN (None, 4, 4, 256) 1024 conv2d_227[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_208 (Activation) (None, 4, 4, 256) 0 batch_normalization_227[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_228 (Conv2D) (None, 4, 4, 256) 590080 activation_208[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_228 (BatchN (None, 4, 4, 256) 1024 conv2d_228[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_209 (Activation) (None, 4, 4, 256) 0 batch_normalization_228[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_229 (Conv2D) (None, 4, 4, 1024) 263168 activation_209[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_229 (BatchN (None, 4, 4, 1024) 4096 conv2d_229[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_68 (Add) (None, 4, 4, 1024) 0 activation_207[0][0] \n", + " batch_normalization_229[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_210 (Activation) (None, 4, 4, 1024) 0 add_68[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_230 (Conv2D) (None, 4, 4, 256) 262400 activation_210[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_230 (BatchN (None, 4, 4, 256) 1024 conv2d_230[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_211 (Activation) (None, 4, 4, 256) 0 batch_normalization_230[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_231 (Conv2D) (None, 4, 4, 256) 590080 activation_211[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_231 (BatchN (None, 4, 4, 256) 1024 conv2d_231[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_212 (Activation) (None, 4, 4, 256) 0 batch_normalization_231[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_232 (Conv2D) (None, 4, 4, 1024) 263168 activation_212[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_232 (BatchN (None, 4, 4, 1024) 4096 conv2d_232[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_69 (Add) (None, 4, 4, 1024) 0 activation_210[0][0] \n", + " batch_normalization_232[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_213 (Activation) (None, 4, 4, 1024) 0 add_69[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_233 (Conv2D) (None, 4, 4, 256) 262400 activation_213[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_233 (BatchN (None, 4, 4, 256) 1024 conv2d_233[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_214 (Activation) (None, 4, 4, 256) 0 batch_normalization_233[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_234 (Conv2D) (None, 4, 4, 256) 590080 activation_214[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_234 (BatchN (None, 4, 4, 256) 1024 conv2d_234[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_215 (Activation) (None, 4, 4, 256) 0 batch_normalization_234[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_235 (Conv2D) (None, 4, 4, 1024) 263168 activation_215[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_235 (BatchN (None, 4, 4, 1024) 4096 conv2d_235[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_70 (Add) (None, 4, 4, 1024) 0 activation_213[0][0] \n", + " batch_normalization_235[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_216 (Activation) (None, 4, 4, 1024) 0 add_70[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_236 (Conv2D) (None, 4, 4, 256) 262400 activation_216[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_236 (BatchN (None, 4, 4, 256) 1024 conv2d_236[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_217 (Activation) (None, 4, 4, 256) 0 batch_normalization_236[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_237 (Conv2D) (None, 4, 4, 256) 590080 activation_217[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_237 (BatchN (None, 4, 4, 256) 1024 conv2d_237[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_218 (Activation) (None, 4, 4, 256) 0 batch_normalization_237[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_238 (Conv2D) (None, 4, 4, 1024) 263168 activation_218[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_238 (BatchN (None, 4, 4, 1024) 4096 conv2d_238[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_71 (Add) (None, 4, 4, 1024) 0 activation_216[0][0] \n", + " batch_normalization_238[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_219 (Activation) (None, 4, 4, 1024) 0 add_71[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_239 (Conv2D) (None, 4, 4, 256) 262400 activation_219[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_239 (BatchN (None, 4, 4, 256) 1024 conv2d_239[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_220 (Activation) (None, 4, 4, 256) 0 batch_normalization_239[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_240 (Conv2D) (None, 4, 4, 256) 590080 activation_220[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_240 (BatchN (None, 4, 4, 256) 1024 conv2d_240[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_221 (Activation) (None, 4, 4, 256) 0 batch_normalization_240[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_241 (Conv2D) (None, 4, 4, 1024) 263168 activation_221[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_241 (BatchN (None, 4, 4, 1024) 4096 conv2d_241[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_72 (Add) (None, 4, 4, 1024) 0 activation_219[0][0] \n", + " batch_normalization_241[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_222 (Activation) (None, 4, 4, 1024) 0 add_72[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_242 (Conv2D) (None, 2, 2, 512) 524800 activation_222[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_242 (BatchN (None, 2, 2, 512) 2048 conv2d_242[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_223 (Activation) (None, 2, 2, 512) 0 batch_normalization_242[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_243 (Conv2D) (None, 2, 2, 512) 2359808 activation_223[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_243 (BatchN (None, 2, 2, 512) 2048 conv2d_243[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_224 (Activation) (None, 2, 2, 512) 0 batch_normalization_243[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_244 (Conv2D) (None, 2, 2, 2048) 1050624 activation_224[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_245 (Conv2D) (None, 2, 2, 2048) 2099200 activation_222[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_244 (BatchN (None, 2, 2, 2048) 8192 conv2d_244[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_245 (BatchN (None, 2, 2, 2048) 8192 conv2d_245[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_73 (Add) (None, 2, 2, 2048) 0 batch_normalization_244[0][0] \n", + " batch_normalization_245[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_225 (Activation) (None, 2, 2, 2048) 0 add_73[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_246 (Conv2D) (None, 2, 2, 512) 1049088 activation_225[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_246 (BatchN (None, 2, 2, 512) 2048 conv2d_246[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_226 (Activation) (None, 2, 2, 512) 0 batch_normalization_246[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_247 (Conv2D) (None, 2, 2, 512) 2359808 activation_226[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_247 (BatchN (None, 2, 2, 512) 2048 conv2d_247[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_227 (Activation) (None, 2, 2, 512) 0 batch_normalization_247[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_248 (Conv2D) (None, 2, 2, 2048) 1050624 activation_227[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_248 (BatchN (None, 2, 2, 2048) 8192 conv2d_248[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_74 (Add) (None, 2, 2, 2048) 0 activation_225[0][0] \n", + " batch_normalization_248[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_228 (Activation) (None, 2, 2, 2048) 0 add_74[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_249 (Conv2D) (None, 2, 2, 512) 1049088 activation_228[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_249 (BatchN (None, 2, 2, 512) 2048 conv2d_249[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_229 (Activation) (None, 2, 2, 512) 0 batch_normalization_249[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_250 (Conv2D) (None, 2, 2, 512) 2359808 activation_229[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_250 (BatchN (None, 2, 2, 512) 2048 conv2d_250[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_230 (Activation) (None, 2, 2, 512) 0 batch_normalization_250[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_251 (Conv2D) (None, 2, 2, 2048) 1050624 activation_230[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_251 (BatchN (None, 2, 2, 2048) 8192 conv2d_251[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_75 (Add) (None, 2, 2, 2048) 0 activation_228[0][0] \n", + " batch_normalization_251[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_231 (Activation) (None, 2, 2, 2048) 0 add_75[0][0] \n", + "__________________________________________________________________________________________________\n", + "average_pooling2d_3 (AveragePoo (None, 1, 1, 2048) 0 activation_231[0][0] \n", + "__________________________________________________________________________________________________\n", + "flatten_3 (Flatten) (None, 2048) 0 average_pooling2d_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "dense_3 (Dense) (None, 6) 12294 flatten_3[0][0] \n", + "==================================================================================================\n", + "Total params: 23,600,006\n", + "Trainable params: 23,546,886\n", + "Non-trainable params: 53,120\n", + "__________________________________________________________________________________________________\n", + "None\n" + ] + } + ], + "source": [ + "model = ResNet50(input_shape = (64, 64, 3), classes = 6)\n", + "print(model.summary())" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-866b891ec47ccb7b", + "locked": true, + "points": 10, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mAll tests passed!\u001b[0m\n" + ] + } + ], + "source": [ + "from outputs import ResNet50_summary\n", + "\n", + "model = ResNet50(input_shape = (64, 64, 3), classes = 6)\n", + "\n", + "comparator(summary(model), ResNet50_summary)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As shown in the Keras Tutorial Notebook, prior to training a model, you need to configure the learning process by compiling the model." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model is now ready to be trained. The only thing you need now is a dataset!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's load your old friend, the SIGNS dataset.\n", + "\n", + "\n", + "
Figure 6 : SIGNS dataset
\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of training examples = 1080\n", + "number of test examples = 120\n", + "X_train shape: (1080, 64, 64, 3)\n", + "Y_train shape: (1080, 6)\n", + "X_test shape: (120, 64, 64, 3)\n", + "Y_test shape: (120, 6)\n" + ] + } + ], + "source": [ + "X_train_orig, Y_train_orig, X_test_orig, Y_test_orig, classes = load_dataset()\n", + "\n", + "# Normalize image vectors\n", + "X_train = X_train_orig / 255.\n", + "X_test = X_test_orig / 255.\n", + "\n", + "# Convert training and test labels to one hot matrices\n", + "Y_train = convert_to_one_hot(Y_train_orig, 6).T\n", + "Y_test = convert_to_one_hot(Y_test_orig, 6).T\n", + "\n", + "print (\"number of training examples = \" + str(X_train.shape[0]))\n", + "print (\"number of test examples = \" + str(X_test.shape[0]))\n", + "print (\"X_train shape: \" + str(X_train.shape))\n", + "print (\"Y_train shape: \" + str(Y_train.shape))\n", + "print (\"X_test shape: \" + str(X_test.shape))\n", + "print (\"Y_test shape: \" + str(Y_test.shape))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run the following cell to train your model on 10 epochs with a batch size of 32. On a GPU, it should take less than 2 minutes. " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/10\n", + "34/34 [==============================] - 1s 24ms/step - loss: 1.9635 - accuracy: 0.5111\n", + "Epoch 2/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 1.0252 - accuracy: 0.7204\n", + "Epoch 3/10\n", + "34/34 [==============================] - 1s 24ms/step - loss: 0.9123 - accuracy: 0.7667\n", + "Epoch 4/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.5948 - accuracy: 0.8130\n", + "Epoch 5/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.3253 - accuracy: 0.9176\n", + "Epoch 6/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.2047 - accuracy: 0.9241\n", + "Epoch 7/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.0961 - accuracy: 0.9639\n", + "Epoch 8/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.2262 - accuracy: 0.9463\n", + "Epoch 9/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.5787 - accuracy: 0.8259\n", + "Epoch 10/10\n", + "34/34 [==============================] - 1s 23ms/step - loss: 0.2785 - accuracy: 0.9037\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(X_train, Y_train, epochs = 10, batch_size = 32)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "```\n", + "Epoch 1/10\n", + "34/34 [==============================] - 1s 34ms/step - loss: 1.9241 - accuracy: 0.4620\n", + "Epoch 2/10\n", + "34/34 [==============================] - 2s 57ms/step - loss: 0.6403 - accuracy: 0.7898\n", + "Epoch 3/10\n", + "34/34 [==============================] - 1s 24ms/step - loss: 0.3744 - accuracy: 0.8731\n", + "Epoch 4/10\n", + "34/34 [==============================] - 2s 44ms/step - loss: 0.2220 - accuracy: 0.9231\n", + "Epoch 5/10\n", + "34/34 [==============================] - 2s 57ms/step - loss: 0.1333 - accuracy: 0.9583\n", + "Epoch 6/10\n", + "34/34 [==============================] - 2s 52ms/step - loss: 0.2243 - accuracy: 0.9444\n", + "Epoch 7/10\n", + "34/34 [==============================] - 2s 48ms/step - loss: 0.2913 - accuracy: 0.9102\n", + "Epoch 8/10\n", + "34/34 [==============================] - 1s 30ms/step - loss: 0.2269 - accuracy: 0.9306\n", + "Epoch 9/10\n", + "34/34 [==============================] - 2s 46ms/step - loss: 0.1113 - accuracy: 0.9630\n", + "Epoch 10/10\n", + "34/34 [==============================] - 2s 57ms/step - loss: 0.0709 - accuracy: 0.9778\n", + "```\n", + "\n", + "The exact values could not match, but don't worry about that. The important thing that you must see is that the loss value decreases, and the accuracy increases for the firsts 5 epochs." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's see how this model (trained on only two epochs) performs on the test set." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4/4 [==============================] - 0s 7ms/step - loss: 0.3467 - accuracy: 0.8917\n", + "Loss = 0.3466799855232239\n", + "Test Accuracy = 0.8916666507720947\n" + ] + } + ], + "source": [ + "preds = model.evaluate(X_test, Y_test)\n", + "print (\"Loss = \" + str(preds[0]))\n", + "print (\"Test Accuracy = \" + str(preds[1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Expected Output**:\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "
\n", + " Test Accuracy\n", + " \n", + " >0.80\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the purposes of this assignment, you've been asked to train the model for ten epochs. You can see that it performs well. The online grader will only run your code for a small number of epochs as well. Please go ahead and submit your assignment. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After you have finished this official (graded) part of this assignment, you can also optionally train the ResNet for more iterations, if you want. It tends to get much better performance when trained for ~20 epochs, but this does take more than an hour when training on a CPU. \n", + "\n", + "Using a GPU, this ResNet50 model's weights were trained on the SIGNS dataset. You can load and run the trained model on the test set in the cells below. It may take β‰ˆ1min to load the model. Have fun! " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "pre_trained_model = tf.keras.models.load_model('resnet50.h5')" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4/4 [==============================] - 0s 25ms/step - loss: 0.1596 - accuracy: 0.9500\n", + "Loss = 0.15958674252033234\n", + "Test Accuracy = 0.949999988079071\n" + ] + } + ], + "source": [ + "preds = pre_trained_model.evaluate(X_test, Y_test)\n", + "print (\"Loss = \" + str(preds[0]))\n", + "print (\"Test Accuracy = \" + str(preds[1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Congratulations** on finishing this assignment! You've now implemented a state-of-the-art image classification system! Woo hoo! \n", + "\n", + "ResNet50 is a powerful model for image classification when it's trained for an adequate number of iterations. Hopefully, from this point, you can use what you've learned and apply it to your own classification problem to perform state-of-the-art accuracy." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "**What you should remember**:\n", + "\n", + "- Very deep \"plain\" networks don't work in practice because vanishing gradients make them hard to train. \n", + "- Skip connections help address the Vanishing Gradient problem. They also make it easy for a ResNet block to learn an identity function. \n", + "- There are two main types of blocks: The **identity block** and the **convolutional block**. \n", + "- Very deep Residual Networks are built by stacking these blocks together." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Free Up Resources for Other Learners\n", + "\n", + "If you don't plan on continuing to the next `Optional` section, help us to provide our learners a smooth learning experience, by freeing up the resources used by your assignment by running the cell below so that the other learners can take advantage of those resources just as much as you did. Thank you!\n", + "\n", + "**Note**: \n", + "- Run the cell below when you are done with the assignment and are ready to submit it for grading.\n", + "- When you'll run it, a pop up will open, click `Ok`.\n", + "- Running the cell will `restart the kernel`." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%javascript\n", + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " \n", + "## 5 - Test on Your Own Image (Optional/Ungraded)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you wish, you can also take a picture of your own hand and see the output of the model. To do this:\n", + " 1. Click on \"File\" in the upper bar of this notebook, then click \"Open\" to go on your Coursera Hub.\n", + " 2. Add your image to this Jupyter Notebook's directory, in the \"images\" folder\n", + " 3. Write your image's name in the following code\n", + " 4. Run the code and check if the algorithm is right! " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Input image shape: (1, 64, 64, 3)\n", + "Class prediction vector [p(0), p(1), p(2), p(3), p(4), p(5)] = [[9.2633512e-05 4.2629417e-02 9.2548847e-01 4.1606426e-04 3.1337839e-02\n", + " 3.5633519e-05]]\n", + "Class: 2\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "img_path = 'images/my_image.jpg'\n", + "img = image.load_img(img_path, target_size=(64, 64))\n", + "x = image.img_to_array(img)\n", + "x = np.expand_dims(x, axis=0)\n", + "x = x/255.0\n", + "print('Input image shape:', x.shape)\n", + "imshow(img)\n", + "prediction = pre_trained_model.predict(x)\n", + "print(\"Class prediction vector [p(0), p(1), p(2), p(3), p(4), p(5)] = \", prediction)\n", + "print(\"Class:\", np.argmax(prediction))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Even though the model has high accuracy, it might be performing poorly on your own set of images. Notice that, the shape of the pictures, the lighting where the photos were taken, and all of the preprocessing steps can have an impact on the performance of the model. Considering everything you have learned in this specialization so far, what do you think might be the cause here?\n", + "\n", + "*Hint*: It might be related to some distributions. Can you come up with a potential solution ?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can also print a summary of your model by running the following code." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"ResNet50\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "input_1 (InputLayer) [(None, 64, 64, 3)] 0 \n", + "__________________________________________________________________________________________________\n", + "zero_padding2d (ZeroPadding2D) (None, 70, 70, 3) 0 input_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_7 (Conv2D) (None, 32, 32, 64) 9472 zero_padding2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "bn_conv1 (BatchNormalization) (None, 32, 32, 64) 256 conv2d_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_6 (Activation) (None, 32, 32, 64) 0 bn_conv1[0][0] \n", + "__________________________________________________________________________________________________\n", + "max_pooling2d (MaxPooling2D) (None, 15, 15, 64) 0 activation_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_8 (Conv2D) (None, 15, 15, 64) 4160 max_pooling2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_7 (BatchNor (None, 15, 15, 64) 256 conv2d_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_7 (Activation) (None, 15, 15, 64) 0 batch_normalization_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_9 (Conv2D) (None, 15, 15, 64) 36928 activation_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_8 (BatchNor (None, 15, 15, 64) 256 conv2d_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_8 (Activation) (None, 15, 15, 64) 0 batch_normalization_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_10 (Conv2D) (None, 15, 15, 256) 16640 activation_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_11 (Conv2D) (None, 15, 15, 256) 16640 max_pooling2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_9 (BatchNor (None, 15, 15, 256) 1024 conv2d_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_10 (BatchNo (None, 15, 15, 256) 1024 conv2d_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_2 (Add) (None, 15, 15, 256) 0 batch_normalization_9[0][0] \n", + " batch_normalization_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_9 (Activation) (None, 15, 15, 256) 0 add_2[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_12 (Conv2D) (None, 15, 15, 64) 16448 activation_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_11 (BatchNo (None, 15, 15, 64) 256 conv2d_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_10 (Activation) (None, 15, 15, 64) 0 batch_normalization_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_13 (Conv2D) (None, 15, 15, 64) 36928 activation_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_12 (BatchNo (None, 15, 15, 64) 256 conv2d_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_11 (Activation) (None, 15, 15, 64) 0 batch_normalization_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_14 (Conv2D) (None, 15, 15, 256) 16640 activation_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_13 (BatchNo (None, 15, 15, 256) 1024 conv2d_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_3 (Add) (None, 15, 15, 256) 0 batch_normalization_13[0][0] \n", + " activation_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_12 (Activation) (None, 15, 15, 256) 0 add_3[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_15 (Conv2D) (None, 15, 15, 64) 16448 activation_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_14 (BatchNo (None, 15, 15, 64) 256 conv2d_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_13 (Activation) (None, 15, 15, 64) 0 batch_normalization_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_16 (Conv2D) (None, 15, 15, 64) 36928 activation_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_15 (BatchNo (None, 15, 15, 64) 256 conv2d_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_14 (Activation) (None, 15, 15, 64) 0 batch_normalization_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_17 (Conv2D) (None, 15, 15, 256) 16640 activation_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_16 (BatchNo (None, 15, 15, 256) 1024 conv2d_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_4 (Add) (None, 15, 15, 256) 0 batch_normalization_16[0][0] \n", + " activation_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_15 (Activation) (None, 15, 15, 256) 0 add_4[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_18 (Conv2D) (None, 8, 8, 128) 32896 activation_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_17 (BatchNo (None, 8, 8, 128) 512 conv2d_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_16 (Activation) (None, 8, 8, 128) 0 batch_normalization_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_19 (Conv2D) (None, 8, 8, 128) 147584 activation_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_18 (BatchNo (None, 8, 8, 128) 512 conv2d_19[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_17 (Activation) (None, 8, 8, 128) 0 batch_normalization_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_20 (Conv2D) (None, 8, 8, 512) 66048 activation_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_21 (Conv2D) (None, 8, 8, 512) 131584 activation_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_19 (BatchNo (None, 8, 8, 512) 2048 conv2d_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_20 (BatchNo (None, 8, 8, 512) 2048 conv2d_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_5 (Add) (None, 8, 8, 512) 0 batch_normalization_19[0][0] \n", + " batch_normalization_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_18 (Activation) (None, 8, 8, 512) 0 add_5[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_22 (Conv2D) (None, 8, 8, 128) 65664 activation_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_21 (BatchNo (None, 8, 8, 128) 512 conv2d_22[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_19 (Activation) (None, 8, 8, 128) 0 batch_normalization_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_23 (Conv2D) (None, 8, 8, 128) 147584 activation_19[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_22 (BatchNo (None, 8, 8, 128) 512 conv2d_23[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_20 (Activation) (None, 8, 8, 128) 0 batch_normalization_22[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_24 (Conv2D) (None, 8, 8, 512) 66048 activation_20[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_23 (BatchNo (None, 8, 8, 512) 2048 conv2d_24[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_6 (Add) (None, 8, 8, 512) 0 batch_normalization_23[0][0] \n", + " activation_18[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_21 (Activation) (None, 8, 8, 512) 0 add_6[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_25 (Conv2D) (None, 8, 8, 128) 65664 activation_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_24 (BatchNo (None, 8, 8, 128) 512 conv2d_25[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_22 (Activation) (None, 8, 8, 128) 0 batch_normalization_24[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_26 (Conv2D) (None, 8, 8, 128) 147584 activation_22[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_25 (BatchNo (None, 8, 8, 128) 512 conv2d_26[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_23 (Activation) (None, 8, 8, 128) 0 batch_normalization_25[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_27 (Conv2D) (None, 8, 8, 512) 66048 activation_23[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_26 (BatchNo (None, 8, 8, 512) 2048 conv2d_27[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_7 (Add) (None, 8, 8, 512) 0 batch_normalization_26[0][0] \n", + " activation_21[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_24 (Activation) (None, 8, 8, 512) 0 add_7[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_28 (Conv2D) (None, 8, 8, 128) 65664 activation_24[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_27 (BatchNo (None, 8, 8, 128) 512 conv2d_28[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_25 (Activation) (None, 8, 8, 128) 0 batch_normalization_27[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_29 (Conv2D) (None, 8, 8, 128) 147584 activation_25[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_28 (BatchNo (None, 8, 8, 128) 512 conv2d_29[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_26 (Activation) (None, 8, 8, 128) 0 batch_normalization_28[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_30 (Conv2D) (None, 8, 8, 512) 66048 activation_26[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_29 (BatchNo (None, 8, 8, 512) 2048 conv2d_30[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_8 (Add) (None, 8, 8, 512) 0 batch_normalization_29[0][0] \n", + " activation_24[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_27 (Activation) (None, 8, 8, 512) 0 add_8[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_31 (Conv2D) (None, 4, 4, 256) 131328 activation_27[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_30 (BatchNo (None, 4, 4, 256) 1024 conv2d_31[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_28 (Activation) (None, 4, 4, 256) 0 batch_normalization_30[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_32 (Conv2D) (None, 4, 4, 256) 590080 activation_28[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_31 (BatchNo (None, 4, 4, 256) 1024 conv2d_32[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_29 (Activation) (None, 4, 4, 256) 0 batch_normalization_31[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_33 (Conv2D) (None, 4, 4, 1024) 263168 activation_29[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_34 (Conv2D) (None, 4, 4, 1024) 525312 activation_27[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_32 (BatchNo (None, 4, 4, 1024) 4096 conv2d_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_33 (BatchNo (None, 4, 4, 1024) 4096 conv2d_34[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_9 (Add) (None, 4, 4, 1024) 0 batch_normalization_32[0][0] \n", + " batch_normalization_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_30 (Activation) (None, 4, 4, 1024) 0 add_9[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_35 (Conv2D) (None, 4, 4, 256) 262400 activation_30[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_34 (BatchNo (None, 4, 4, 256) 1024 conv2d_35[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_31 (Activation) (None, 4, 4, 256) 0 batch_normalization_34[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_36 (Conv2D) (None, 4, 4, 256) 590080 activation_31[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_35 (BatchNo (None, 4, 4, 256) 1024 conv2d_36[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_32 (Activation) (None, 4, 4, 256) 0 batch_normalization_35[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_37 (Conv2D) (None, 4, 4, 1024) 263168 activation_32[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_36 (BatchNo (None, 4, 4, 1024) 4096 conv2d_37[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_10 (Add) (None, 4, 4, 1024) 0 batch_normalization_36[0][0] \n", + " activation_30[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_33 (Activation) (None, 4, 4, 1024) 0 add_10[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_38 (Conv2D) (None, 4, 4, 256) 262400 activation_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_37 (BatchNo (None, 4, 4, 256) 1024 conv2d_38[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_34 (Activation) (None, 4, 4, 256) 0 batch_normalization_37[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_39 (Conv2D) (None, 4, 4, 256) 590080 activation_34[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_38 (BatchNo (None, 4, 4, 256) 1024 conv2d_39[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_35 (Activation) (None, 4, 4, 256) 0 batch_normalization_38[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_40 (Conv2D) (None, 4, 4, 1024) 263168 activation_35[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_39 (BatchNo (None, 4, 4, 1024) 4096 conv2d_40[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_11 (Add) (None, 4, 4, 1024) 0 batch_normalization_39[0][0] \n", + " activation_33[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_36 (Activation) (None, 4, 4, 1024) 0 add_11[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_41 (Conv2D) (None, 4, 4, 256) 262400 activation_36[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_40 (BatchNo (None, 4, 4, 256) 1024 conv2d_41[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_37 (Activation) (None, 4, 4, 256) 0 batch_normalization_40[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_42 (Conv2D) (None, 4, 4, 256) 590080 activation_37[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_41 (BatchNo (None, 4, 4, 256) 1024 conv2d_42[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_38 (Activation) (None, 4, 4, 256) 0 batch_normalization_41[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_43 (Conv2D) (None, 4, 4, 1024) 263168 activation_38[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_42 (BatchNo (None, 4, 4, 1024) 4096 conv2d_43[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_12 (Add) (None, 4, 4, 1024) 0 batch_normalization_42[0][0] \n", + " activation_36[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_39 (Activation) (None, 4, 4, 1024) 0 add_12[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_44 (Conv2D) (None, 4, 4, 256) 262400 activation_39[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_43 (BatchNo (None, 4, 4, 256) 1024 conv2d_44[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_40 (Activation) (None, 4, 4, 256) 0 batch_normalization_43[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_45 (Conv2D) (None, 4, 4, 256) 590080 activation_40[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_44 (BatchNo (None, 4, 4, 256) 1024 conv2d_45[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_41 (Activation) (None, 4, 4, 256) 0 batch_normalization_44[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_46 (Conv2D) (None, 4, 4, 1024) 263168 activation_41[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_45 (BatchNo (None, 4, 4, 1024) 4096 conv2d_46[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_13 (Add) (None, 4, 4, 1024) 0 batch_normalization_45[0][0] \n", + " activation_39[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_42 (Activation) (None, 4, 4, 1024) 0 add_13[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_47 (Conv2D) (None, 4, 4, 256) 262400 activation_42[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_46 (BatchNo (None, 4, 4, 256) 1024 conv2d_47[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_43 (Activation) (None, 4, 4, 256) 0 batch_normalization_46[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_48 (Conv2D) (None, 4, 4, 256) 590080 activation_43[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_47 (BatchNo (None, 4, 4, 256) 1024 conv2d_48[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_44 (Activation) (None, 4, 4, 256) 0 batch_normalization_47[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_49 (Conv2D) (None, 4, 4, 1024) 263168 activation_44[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_48 (BatchNo (None, 4, 4, 1024) 4096 conv2d_49[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_14 (Add) (None, 4, 4, 1024) 0 batch_normalization_48[0][0] \n", + " activation_42[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_45 (Activation) (None, 4, 4, 1024) 0 add_14[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_50 (Conv2D) (None, 2, 2, 512) 524800 activation_45[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_49 (BatchNo (None, 2, 2, 512) 2048 conv2d_50[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_46 (Activation) (None, 2, 2, 512) 0 batch_normalization_49[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_51 (Conv2D) (None, 2, 2, 512) 2359808 activation_46[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_50 (BatchNo (None, 2, 2, 512) 2048 conv2d_51[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_47 (Activation) (None, 2, 2, 512) 0 batch_normalization_50[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_52 (Conv2D) (None, 2, 2, 2048) 1050624 activation_47[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_53 (Conv2D) (None, 2, 2, 2048) 2099200 activation_45[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_51 (BatchNo (None, 2, 2, 2048) 8192 conv2d_52[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_52 (BatchNo (None, 2, 2, 2048) 8192 conv2d_53[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_15 (Add) (None, 2, 2, 2048) 0 batch_normalization_51[0][0] \n", + " batch_normalization_52[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_48 (Activation) (None, 2, 2, 2048) 0 add_15[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_54 (Conv2D) (None, 2, 2, 512) 1049088 activation_48[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_53 (BatchNo (None, 2, 2, 512) 2048 conv2d_54[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_49 (Activation) (None, 2, 2, 512) 0 batch_normalization_53[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_55 (Conv2D) (None, 2, 2, 512) 2359808 activation_49[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_54 (BatchNo (None, 2, 2, 512) 2048 conv2d_55[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_50 (Activation) (None, 2, 2, 512) 0 batch_normalization_54[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_56 (Conv2D) (None, 2, 2, 2048) 1050624 activation_50[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_55 (BatchNo (None, 2, 2, 2048) 8192 conv2d_56[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_16 (Add) (None, 2, 2, 2048) 0 batch_normalization_55[0][0] \n", + " activation_48[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_51 (Activation) (None, 2, 2, 2048) 0 add_16[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_57 (Conv2D) (None, 2, 2, 512) 1049088 activation_51[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_56 (BatchNo (None, 2, 2, 512) 2048 conv2d_57[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_52 (Activation) (None, 2, 2, 512) 0 batch_normalization_56[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_58 (Conv2D) (None, 2, 2, 512) 2359808 activation_52[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_57 (BatchNo (None, 2, 2, 512) 2048 conv2d_58[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_53 (Activation) (None, 2, 2, 512) 0 batch_normalization_57[0][0] \n", + "__________________________________________________________________________________________________\n", + "conv2d_59 (Conv2D) (None, 2, 2, 2048) 1050624 activation_53[0][0] \n", + "__________________________________________________________________________________________________\n", + "batch_normalization_58 (BatchNo (None, 2, 2, 2048) 8192 conv2d_59[0][0] \n", + "__________________________________________________________________________________________________\n", + "add_17 (Add) (None, 2, 2, 2048) 0 batch_normalization_58[0][0] \n", + " activation_51[0][0] \n", + "__________________________________________________________________________________________________\n", + "activation_54 (Activation) (None, 2, 2, 2048) 0 add_17[0][0] \n", + "__________________________________________________________________________________________________\n", + "average_pooling2d (AveragePooli (None, 1, 1, 2048) 0 activation_54[0][0] \n", + "__________________________________________________________________________________________________\n", + "flatten (Flatten) (None, 2048) 0 average_pooling2d[0][0] \n", + "__________________________________________________________________________________________________\n", + "fc6 (Dense) (None, 6) 12294 flatten[0][0] \n", + "==================================================================================================\n", + "Total params: 23,600,006\n", + "Trainable params: 23,546,886\n", + "Non-trainable params: 53,120\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "pre_trained_model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Free Up Resources for Other Learners\n", + "\n", + "In order to provide our learners a smooth learning experience, please free up the resources used by your assignment by running the cell below so that the other learners can take advantage of those resources just as much as you did. Thank you!\n", + "\n", + "**Note**: \n", + "- Run the cell below when you are done with the assignment and are ready to submit it for grading.\n", + "- When you'll run it, a pop up will open, click `Ok`.\n", + "- Running the cell will `restart the kernel`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%javascript\n", + "IPython.notebook.save_checkpoint();\n", + "if (confirm(\"Clear memory?\") == true)\n", + "{\n", + " IPython.notebook.kernel.restart();\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " \n", + "## 6 - Bibliography\n", + "\n", + "This notebook presents the ResNet algorithm from He et al. (2015). The implementation here also took significant inspiration and follows the structure given in the GitHub repository of Francois Chollet: \n", + "\n", + "- Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun - [Deep Residual Learning for Image Recognition (2015)](https://arxiv.org/abs/1512.03385)\n", + "- Francois Chollet's GitHub repository: https://github.com/fchollet/deep-learning-models/blob/master/resnet50.py\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Raw Cell Format", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/courses/Coursera_Convolutional_Neural_Networks/Transfer_learning_with_MobileNet_v1.ipynb b/courses/Coursera_Convolutional_Neural_Networks/Transfer_learning_with_MobileNet_v1.ipynb new file mode 100644 index 00000000000..28dd63016bd --- /dev/null +++ b/courses/Coursera_Convolutional_Neural_Networks/Transfer_learning_with_MobileNet_v1.ipynb @@ -0,0 +1,1508 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Transfer Learning with MobileNetV2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Welcome to this week's assignment, where you'll be using transfer learning on a pre-trained CNN to build an Alpaca/Not Alpaca classifier!\n", + "\n", + "\n", + "\n", + "A pre-trained model is a network that's already been trained on a large dataset and saved, which allows you to use it to customize your own model cheaply and efficiently. The one you'll be using, MobileNetV2, was designed to provide fast and computationally efficient performance. It's been pre-trained on ImageNet, a dataset containing over 14 million images and 1000 classes.\n", + "\n", + "By the end of this assignment, you will be able to:\n", + "\n", + "- Create a dataset from a directory\n", + "- Preprocess and augment data using the Sequential API\n", + "- Adapt a pretrained model to new data and train a classifier using the Functional API and MobileNet\n", + "- Fine-tune a classifier's final layers to improve accuracy\n", + "\n", + "## Important Note on Submission to the AutoGrader\n", + "\n", + "Before submitting your assignment to the AutoGrader, please make sure you are not doing the following:\n", + "\n", + "1. You have not added any _extra_ `print` statement(s) in the assignment.\n", + "2. You have not added any _extra_ code cell(s) in the assignment.\n", + "3. You have not changed any of the function parameters.\n", + "4. You are not using any global variables inside your graded exercises. Unless specifically instructed to do so, please refrain from it and use the local variables instead.\n", + "5. You are not changing the assignment code where it is not required, like creating _extra_ variables.\n", + "\n", + "If you do any of the following, you will get something like, `Grader not found` (or similarly unexpected) error upon submitting your assignment. Before asking for help/debugging the errors in your assignment, check for these first. If this is the case, and you don't remember the changes you have made, you can get a fresh copy of the assignment by following these [instructions](https://www.coursera.org/learn/convolutional-neural-networks/supplement/DS4yP/h-ow-to-refresh-your-workspace)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Content\n", + "\n", + "- [1 - Packages](#1)\n", + " - [1.1 Create the Dataset and Split it into Training and Validation Sets](#1-1)\n", + "- [2 - Preprocess and Augment Training Data](#2)\n", + " - [Exercise 1 - data_augmenter](#ex-1)\n", + "- [3 - Using MobileNetV2 for Transfer Learning](#3)\n", + " - [3.1 - Inside a MobileNetV2 Convolutional Building Block](#3-1)\n", + " - [3.2 - Layer Freezing with the Functional API](#3-2)\n", + " - [Exercise 2 - alpaca_model](#ex-2)\n", + " - [3.3 - Fine-tuning the Model](#3-3)\n", + " - [Exercise 3](#ex-3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 1 - Packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os\n", + "import tensorflow as tf\n", + "import tensorflow.keras.layers as tfl\n", + "\n", + "from tensorflow.keras.preprocessing import image_dataset_from_directory\n", + "from tensorflow.keras.layers.experimental.preprocessing import RandomFlip, RandomRotation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 1.1 Create the Dataset and Split it into Training and Validation Sets\n", + "\n", + "When training and evaluating deep learning models in Keras, generating a dataset from image files stored on disk is simple and fast. Call `image_data_set_from_directory()` to read from the directory and create both training and validation datasets. \n", + "\n", + "If you're specifying a validation split, you'll also need to specify the subset for each portion. Just set the training set to `subset='training'` and the validation set to `subset='validation'`.\n", + "\n", + "You'll also set your seeds to match each other, so your training and validation sets don't overlap. :) " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 327 files belonging to 2 classes.\n", + "Using 262 files for training.\n", + "Found 327 files belonging to 2 classes.\n", + "Using 65 files for validation.\n" + ] + } + ], + "source": [ + "BATCH_SIZE = 32\n", + "IMG_SIZE = (160, 160)\n", + "directory = \"dataset/\"\n", + "train_dataset = image_dataset_from_directory(directory,\n", + " shuffle=True,\n", + " batch_size=BATCH_SIZE,\n", + " image_size=IMG_SIZE,\n", + " validation_split=0.2,\n", + " subset='training',\n", + " seed=42)\n", + "validation_dataset = image_dataset_from_directory(directory,\n", + " shuffle=True,\n", + " batch_size=BATCH_SIZE,\n", + " image_size=IMG_SIZE,\n", + " validation_split=0.2,\n", + " subset='validation',\n", + " seed=42)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now let's take a look at some of the images from the training set: \n", + "\n", + "**Note:** The original dataset has some mislabelled images in it as well." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "class_names = train_dataset.class_names\n", + "\n", + "plt.figure(figsize=(10, 10))\n", + "for images, labels in train_dataset.take(1):\n", + " for i in range(9):\n", + " ax = plt.subplot(3, 3, i + 1)\n", + " plt.imshow(images[i].numpy().astype(\"uint8\"))\n", + " plt.title(class_names[labels[i]])\n", + " plt.axis(\"off\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 2 - Preprocess and Augment Training Data\n", + "\n", + "You may have encountered `dataset.prefetch` in a previous TensorFlow assignment, as an important extra step in data preprocessing. \n", + "\n", + "Using `prefetch()` prevents a memory bottleneck that can occur when reading from disk. It sets aside some data and keeps it ready for when it's needed, by creating a source dataset from your input data, applying a transformation to preprocess it, then iterating over the dataset one element at a time. Because the iteration is streaming, the data doesn't need to fit into memory.\n", + "\n", + "You can set the number of elements to prefetch manually, or you can use `tf.data.experimental.AUTOTUNE` to choose the parameters automatically. Autotune prompts `tf.data` to tune that value dynamically at runtime, by tracking the time spent in each operation and feeding those times into an optimization algorithm. The optimization algorithm tries to find the best allocation of its CPU budget across all tunable operations. \n", + "\n", + "To increase diversity in the training set and help your model learn the data better, it's standard practice to augment the images by transforming them, i.e., randomly flipping and rotating them. Keras' Sequential API offers a straightforward method for these kinds of data augmentations, with built-in, customizable preprocessing layers. These layers are saved with the rest of your model and can be re-used later. Ahh, so convenient! \n", + "\n", + "As always, you're invited to read the official docs, which you can find for data augmentation [here](https://www.tensorflow.org/tutorials/images/data_augmentation).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "AUTOTUNE = tf.data.experimental.AUTOTUNE\n", + "train_dataset = train_dataset.prefetch(buffer_size=AUTOTUNE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 1 - data_augmenter\n", + "\n", + "Implement a function for data augmentation. Use a `Sequential` keras model composed of 2 layers:\n", + "* `RandomFlip('horizontal')`\n", + "* `RandomRotation(0.2)`" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-cd6b3e9f32b1bf37", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C1\n", + "# GRADED FUNCTION: data_augmenter\n", + "def data_augmenter():\n", + " '''\n", + " Create a Sequential model composed of 2 layers\n", + " Returns:\n", + " tf.keras.Sequential\n", + " '''\n", + " ### START CODE HERE\n", + " data_augmentation = tf.keras.Sequential()\n", + " data_augmentation.add(RandomFlip(\"horizontal\"))\n", + " data_augmentation.add(RandomRotation(0.2))\n", + " ### END CODE HERE\n", + " \n", + " return data_augmentation" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-f3afa9106c3fad56", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[92mAll tests passed!\n" + ] + } + ], + "source": [ + "augmenter = data_augmenter()\n", + "\n", + "assert(augmenter.layers[0].name.startswith('random_flip')), \"First layer must be RandomFlip\"\n", + "assert augmenter.layers[0].mode == 'horizontal', \"RadomFlip parameter must be horizontal\"\n", + "assert(augmenter.layers[1].name.startswith('random_rotation')), \"Second layer must be RandomRotation\"\n", + "assert augmenter.layers[1].factor == 0.2, \"Rotation factor must be 0.2\"\n", + "assert len(augmenter.layers) == 2, \"The model must have only 2 layers\"\n", + "\n", + "print('\\033[92mAll tests passed!')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Take a look at how an image from the training set has been augmented with simple transformations:\n", + "\n", + "From one cute animal, to 9 variations of that cute animal, in three lines of code. Now your model has a lot more to learn from." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "data_augmentation = data_augmenter()\n", + "\n", + "for image, _ in train_dataset.take(1):\n", + " plt.figure(figsize=(10, 10))\n", + " first_image = image[0]\n", + " for i in range(9):\n", + " ax = plt.subplot(3, 3, i + 1)\n", + " augmented_image = data_augmentation(tf.expand_dims(first_image, 0))\n", + " plt.imshow(augmented_image[0] / 255)\n", + " plt.axis('off')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, you'll apply your first tool from the MobileNet application in TensorFlow, to normalize your input. Since you're using a pre-trained model that was trained on the normalization values [-1,1], it's best practice to reuse that standard with tf.keras.applications.mobilenet_v2.preprocess_input." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "**What you should remember:**\n", + "\n", + "* When calling image_data_set_from_directory(), specify the train/val subsets and match the seeds to prevent overlap\n", + "* Use prefetch() to prevent memory bottlenecks when reading from disk\n", + "* Give your model more to learn from with simple data augmentations like rotation and flipping.\n", + "* When using a pretrained model, it's best to reuse the weights it was trained on." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "preprocess_input = tf.keras.applications.mobilenet_v2.preprocess_input" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## 3 - Using MobileNetV2 for Transfer Learning \n", + "\n", + "MobileNetV2 was trained on ImageNet and is optimized to run on mobile and other low-power applications. It's 155 layers deep (just in case you felt the urge to plot the model yourself, prepare for a long journey!) and very efficient for object detection and image segmentation tasks, as well as classification tasks like this one. The architecture has three defining characteristics:\n", + "\n", + "* Depthwise separable convolutions\n", + "* Thin input and output bottlenecks between layers\n", + "* Shortcut connections between bottleneck layers\n", + "\n", + "\n", + "### 3.1 - Inside a MobileNetV2 Convolutional Building Block\n", + "\n", + "MobileNetV2 uses depthwise separable convolutions as efficient building blocks. Traditional convolutions are often very resource-intensive, and depthwise separable convolutions are able to reduce the number of trainable parameters and operations and also speed up convolutions in two steps: \n", + "\n", + "1. The first step calculates an intermediate result by convolving on each of the channels independently. This is the depthwise convolution.\n", + "\n", + "2. In the second step, another convolution merges the outputs of the previous step into one. This gets a single result from a single feature at a time, and then is applied to all the filters in the output layer. This is the pointwise convolution, or: **Shape of the depthwise convolution X Number of filters.**\n", + "\n", + "\n", + "
Figure 1 : MobileNetV2 Architecture
This diagram was inspired by the original seen here.
\n", + "\n", + "Each block consists of an inverted residual structure with a bottleneck at each end. These bottlenecks encode the intermediate inputs and outputs in a low dimensional space, and prevent non-linearities from destroying important information. \n", + "\n", + "The shortcut connections, which are similar to the ones in traditional residual networks, serve the same purpose of speeding up training and improving predictions. These connections skip over the intermediate convolutions and connect the bottleneck layers. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's try to train your base model using all the layers from the pretrained model. \n", + "\n", + "Similarly to how you reused the pretrained normalization values MobileNetV2 was trained on, you'll also load the pretrained weights from ImageNet by specifying `weights='imagenet'`. " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v2/mobilenet_v2_weights_tf_dim_ordering_tf_kernels_1.0_160.h5\n", + "14540800/14536120 [==============================] - 0s 0us/step\n" + ] + } + ], + "source": [ + "IMG_SHAPE = IMG_SIZE + (3,)\n", + "base_model = tf.keras.applications.MobileNetV2(input_shape=IMG_SHAPE,\n", + " include_top=True,\n", + " weights='imagenet')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Print the model summary below to see all the model's layers, the shapes of their outputs, and the total number of parameters, trainable and non-trainable. " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"mobilenetv2_1.00_160\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "input_1 (InputLayer) [(None, 160, 160, 3) 0 \n", + "__________________________________________________________________________________________________\n", + "Conv1_pad (ZeroPadding2D) (None, 161, 161, 3) 0 input_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "Conv1 (Conv2D) (None, 80, 80, 32) 864 Conv1_pad[0][0] \n", + "__________________________________________________________________________________________________\n", + "bn_Conv1 (BatchNormalization) (None, 80, 80, 32) 128 Conv1[0][0] \n", + "__________________________________________________________________________________________________\n", + "Conv1_relu (ReLU) (None, 80, 80, 32) 0 bn_Conv1[0][0] \n", + "__________________________________________________________________________________________________\n", + "expanded_conv_depthwise (Depthw (None, 80, 80, 32) 288 Conv1_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "expanded_conv_depthwise_BN (Bat (None, 80, 80, 32) 128 expanded_conv_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "expanded_conv_depthwise_relu (R (None, 80, 80, 32) 0 expanded_conv_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "expanded_conv_project (Conv2D) (None, 80, 80, 16) 512 expanded_conv_depthwise_relu[0][0\n", + "__________________________________________________________________________________________________\n", + "expanded_conv_project_BN (Batch (None, 80, 80, 16) 64 expanded_conv_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_expand (Conv2D) (None, 80, 80, 96) 1536 expanded_conv_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_expand_BN (BatchNormali (None, 80, 80, 96) 384 block_1_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_expand_relu (ReLU) (None, 80, 80, 96) 0 block_1_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_pad (ZeroPadding2D) (None, 81, 81, 96) 0 block_1_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_depthwise (DepthwiseCon (None, 40, 40, 96) 864 block_1_pad[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_depthwise_BN (BatchNorm (None, 40, 40, 96) 384 block_1_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_depthwise_relu (ReLU) (None, 40, 40, 96) 0 block_1_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_project (Conv2D) (None, 40, 40, 24) 2304 block_1_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_1_project_BN (BatchNormal (None, 40, 40, 24) 96 block_1_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_expand (Conv2D) (None, 40, 40, 144) 3456 block_1_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_expand_BN (BatchNormali (None, 40, 40, 144) 576 block_2_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_expand_relu (ReLU) (None, 40, 40, 144) 0 block_2_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_depthwise (DepthwiseCon (None, 40, 40, 144) 1296 block_2_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_depthwise_BN (BatchNorm (None, 40, 40, 144) 576 block_2_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_depthwise_relu (ReLU) (None, 40, 40, 144) 0 block_2_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_project (Conv2D) (None, 40, 40, 24) 3456 block_2_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_project_BN (BatchNormal (None, 40, 40, 24) 96 block_2_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_2_add (Add) (None, 40, 40, 24) 0 block_1_project_BN[0][0] \n", + " block_2_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_expand (Conv2D) (None, 40, 40, 144) 3456 block_2_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_expand_BN (BatchNormali (None, 40, 40, 144) 576 block_3_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_expand_relu (ReLU) (None, 40, 40, 144) 0 block_3_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_pad (ZeroPadding2D) (None, 41, 41, 144) 0 block_3_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_depthwise (DepthwiseCon (None, 20, 20, 144) 1296 block_3_pad[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_depthwise_BN (BatchNorm (None, 20, 20, 144) 576 block_3_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_depthwise_relu (ReLU) (None, 20, 20, 144) 0 block_3_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_project (Conv2D) (None, 20, 20, 32) 4608 block_3_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_3_project_BN (BatchNormal (None, 20, 20, 32) 128 block_3_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_expand (Conv2D) (None, 20, 20, 192) 6144 block_3_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_expand_BN (BatchNormali (None, 20, 20, 192) 768 block_4_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_expand_relu (ReLU) (None, 20, 20, 192) 0 block_4_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_depthwise (DepthwiseCon (None, 20, 20, 192) 1728 block_4_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_depthwise_BN (BatchNorm (None, 20, 20, 192) 768 block_4_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_depthwise_relu (ReLU) (None, 20, 20, 192) 0 block_4_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_project (Conv2D) (None, 20, 20, 32) 6144 block_4_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_project_BN (BatchNormal (None, 20, 20, 32) 128 block_4_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_4_add (Add) (None, 20, 20, 32) 0 block_3_project_BN[0][0] \n", + " block_4_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_expand (Conv2D) (None, 20, 20, 192) 6144 block_4_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_expand_BN (BatchNormali (None, 20, 20, 192) 768 block_5_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_expand_relu (ReLU) (None, 20, 20, 192) 0 block_5_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_depthwise (DepthwiseCon (None, 20, 20, 192) 1728 block_5_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_depthwise_BN (BatchNorm (None, 20, 20, 192) 768 block_5_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_depthwise_relu (ReLU) (None, 20, 20, 192) 0 block_5_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_project (Conv2D) (None, 20, 20, 32) 6144 block_5_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_project_BN (BatchNormal (None, 20, 20, 32) 128 block_5_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_5_add (Add) (None, 20, 20, 32) 0 block_4_add[0][0] \n", + " block_5_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_expand (Conv2D) (None, 20, 20, 192) 6144 block_5_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_expand_BN (BatchNormali (None, 20, 20, 192) 768 block_6_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_expand_relu (ReLU) (None, 20, 20, 192) 0 block_6_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_pad (ZeroPadding2D) (None, 21, 21, 192) 0 block_6_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_depthwise (DepthwiseCon (None, 10, 10, 192) 1728 block_6_pad[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_depthwise_BN (BatchNorm (None, 10, 10, 192) 768 block_6_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_depthwise_relu (ReLU) (None, 10, 10, 192) 0 block_6_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_project (Conv2D) (None, 10, 10, 64) 12288 block_6_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_6_project_BN (BatchNormal (None, 10, 10, 64) 256 block_6_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_expand (Conv2D) (None, 10, 10, 384) 24576 block_6_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_expand_BN (BatchNormali (None, 10, 10, 384) 1536 block_7_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_expand_relu (ReLU) (None, 10, 10, 384) 0 block_7_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_depthwise (DepthwiseCon (None, 10, 10, 384) 3456 block_7_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_depthwise_BN (BatchNorm (None, 10, 10, 384) 1536 block_7_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_depthwise_relu (ReLU) (None, 10, 10, 384) 0 block_7_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_project (Conv2D) (None, 10, 10, 64) 24576 block_7_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_project_BN (BatchNormal (None, 10, 10, 64) 256 block_7_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_7_add (Add) (None, 10, 10, 64) 0 block_6_project_BN[0][0] \n", + " block_7_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_expand (Conv2D) (None, 10, 10, 384) 24576 block_7_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_expand_BN (BatchNormali (None, 10, 10, 384) 1536 block_8_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_expand_relu (ReLU) (None, 10, 10, 384) 0 block_8_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_depthwise (DepthwiseCon (None, 10, 10, 384) 3456 block_8_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_depthwise_BN (BatchNorm (None, 10, 10, 384) 1536 block_8_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_depthwise_relu (ReLU) (None, 10, 10, 384) 0 block_8_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_project (Conv2D) (None, 10, 10, 64) 24576 block_8_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_project_BN (BatchNormal (None, 10, 10, 64) 256 block_8_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_8_add (Add) (None, 10, 10, 64) 0 block_7_add[0][0] \n", + " block_8_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_expand (Conv2D) (None, 10, 10, 384) 24576 block_8_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_expand_BN (BatchNormali (None, 10, 10, 384) 1536 block_9_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_expand_relu (ReLU) (None, 10, 10, 384) 0 block_9_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_depthwise (DepthwiseCon (None, 10, 10, 384) 3456 block_9_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_depthwise_BN (BatchNorm (None, 10, 10, 384) 1536 block_9_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_depthwise_relu (ReLU) (None, 10, 10, 384) 0 block_9_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_project (Conv2D) (None, 10, 10, 64) 24576 block_9_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_project_BN (BatchNormal (None, 10, 10, 64) 256 block_9_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_9_add (Add) (None, 10, 10, 64) 0 block_8_add[0][0] \n", + " block_9_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_expand (Conv2D) (None, 10, 10, 384) 24576 block_9_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_expand_BN (BatchNormal (None, 10, 10, 384) 1536 block_10_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_expand_relu (ReLU) (None, 10, 10, 384) 0 block_10_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_depthwise (DepthwiseCo (None, 10, 10, 384) 3456 block_10_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_depthwise_BN (BatchNor (None, 10, 10, 384) 1536 block_10_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_depthwise_relu (ReLU) (None, 10, 10, 384) 0 block_10_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_project (Conv2D) (None, 10, 10, 96) 36864 block_10_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_10_project_BN (BatchNorma (None, 10, 10, 96) 384 block_10_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_expand (Conv2D) (None, 10, 10, 576) 55296 block_10_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_expand_BN (BatchNormal (None, 10, 10, 576) 2304 block_11_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_expand_relu (ReLU) (None, 10, 10, 576) 0 block_11_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_depthwise (DepthwiseCo (None, 10, 10, 576) 5184 block_11_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_depthwise_BN (BatchNor (None, 10, 10, 576) 2304 block_11_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_depthwise_relu (ReLU) (None, 10, 10, 576) 0 block_11_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_project (Conv2D) (None, 10, 10, 96) 55296 block_11_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_project_BN (BatchNorma (None, 10, 10, 96) 384 block_11_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_11_add (Add) (None, 10, 10, 96) 0 block_10_project_BN[0][0] \n", + " block_11_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_expand (Conv2D) (None, 10, 10, 576) 55296 block_11_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_expand_BN (BatchNormal (None, 10, 10, 576) 2304 block_12_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_expand_relu (ReLU) (None, 10, 10, 576) 0 block_12_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_depthwise (DepthwiseCo (None, 10, 10, 576) 5184 block_12_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_depthwise_BN (BatchNor (None, 10, 10, 576) 2304 block_12_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_depthwise_relu (ReLU) (None, 10, 10, 576) 0 block_12_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_project (Conv2D) (None, 10, 10, 96) 55296 block_12_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_project_BN (BatchNorma (None, 10, 10, 96) 384 block_12_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_12_add (Add) (None, 10, 10, 96) 0 block_11_add[0][0] \n", + " block_12_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_expand (Conv2D) (None, 10, 10, 576) 55296 block_12_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_expand_BN (BatchNormal (None, 10, 10, 576) 2304 block_13_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_expand_relu (ReLU) (None, 10, 10, 576) 0 block_13_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_pad (ZeroPadding2D) (None, 11, 11, 576) 0 block_13_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_depthwise (DepthwiseCo (None, 5, 5, 576) 5184 block_13_pad[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_depthwise_BN (BatchNor (None, 5, 5, 576) 2304 block_13_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_depthwise_relu (ReLU) (None, 5, 5, 576) 0 block_13_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_project (Conv2D) (None, 5, 5, 160) 92160 block_13_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_13_project_BN (BatchNorma (None, 5, 5, 160) 640 block_13_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_expand (Conv2D) (None, 5, 5, 960) 153600 block_13_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_expand_BN (BatchNormal (None, 5, 5, 960) 3840 block_14_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_expand_relu (ReLU) (None, 5, 5, 960) 0 block_14_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_depthwise (DepthwiseCo (None, 5, 5, 960) 8640 block_14_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_depthwise_BN (BatchNor (None, 5, 5, 960) 3840 block_14_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_depthwise_relu (ReLU) (None, 5, 5, 960) 0 block_14_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_project (Conv2D) (None, 5, 5, 160) 153600 block_14_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_project_BN (BatchNorma (None, 5, 5, 160) 640 block_14_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_14_add (Add) (None, 5, 5, 160) 0 block_13_project_BN[0][0] \n", + " block_14_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_expand (Conv2D) (None, 5, 5, 960) 153600 block_14_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_expand_BN (BatchNormal (None, 5, 5, 960) 3840 block_15_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_expand_relu (ReLU) (None, 5, 5, 960) 0 block_15_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_depthwise (DepthwiseCo (None, 5, 5, 960) 8640 block_15_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_depthwise_BN (BatchNor (None, 5, 5, 960) 3840 block_15_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_depthwise_relu (ReLU) (None, 5, 5, 960) 0 block_15_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_project (Conv2D) (None, 5, 5, 160) 153600 block_15_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_project_BN (BatchNorma (None, 5, 5, 160) 640 block_15_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_15_add (Add) (None, 5, 5, 160) 0 block_14_add[0][0] \n", + " block_15_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_expand (Conv2D) (None, 5, 5, 960) 153600 block_15_add[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_expand_BN (BatchNormal (None, 5, 5, 960) 3840 block_16_expand[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_expand_relu (ReLU) (None, 5, 5, 960) 0 block_16_expand_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_depthwise (DepthwiseCo (None, 5, 5, 960) 8640 block_16_expand_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_depthwise_BN (BatchNor (None, 5, 5, 960) 3840 block_16_depthwise[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_depthwise_relu (ReLU) (None, 5, 5, 960) 0 block_16_depthwise_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_project (Conv2D) (None, 5, 5, 320) 307200 block_16_depthwise_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "block_16_project_BN (BatchNorma (None, 5, 5, 320) 1280 block_16_project[0][0] \n", + "__________________________________________________________________________________________________\n", + "Conv_1 (Conv2D) (None, 5, 5, 1280) 409600 block_16_project_BN[0][0] \n", + "__________________________________________________________________________________________________\n", + "Conv_1_bn (BatchNormalization) (None, 5, 5, 1280) 5120 Conv_1[0][0] \n", + "__________________________________________________________________________________________________\n", + "out_relu (ReLU) (None, 5, 5, 1280) 0 Conv_1_bn[0][0] \n", + "__________________________________________________________________________________________________\n", + "global_average_pooling2d (Globa (None, 1280) 0 out_relu[0][0] \n", + "__________________________________________________________________________________________________\n", + "predictions (Dense) (None, 1000) 1281000 global_average_pooling2d[0][0] \n", + "==================================================================================================\n", + "Total params: 3,538,984\n", + "Trainable params: 3,504,872\n", + "Non-trainable params: 34,112\n", + "__________________________________________________________________________________________________\n" + ] + } + ], + "source": [ + "base_model.summary()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note the last 2 layers here. They are the so called top layers, and they are responsible of the classification in the model" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "global_average_pooling2d\n", + "predictions\n" + ] + } + ], + "source": [ + "nb_layers = len(base_model.layers)\n", + "print(base_model.layers[nb_layers - 2].name)\n", + "print(base_model.layers[nb_layers - 1].name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Notice some of the layers in the summary like `Conv2D` and `DepthwiseConv2D` and how they follow the progression of expansion to depthwise convolution to projection. In combination with BatchNormalization and ReLU, these make up the bottleneck layers mentioned earlier." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "**What you should remember**:\n", + "\n", + "* MobileNetV2's unique features are: \n", + " * Depthwise separable convolutions that provide lightweight feature filtering and creation\n", + " * Input and output bottlenecks that preserve important information on either end of the block\n", + "* Depthwise separable convolutions deal with both spatial and depth (number of channels) dimensions" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, choose the first batch from the tensorflow dataset to use the images, and run it through the MobileNetV2 base model to test out the predictions on some of your images. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(32, 1000)\n" + ] + } + ], + "source": [ + "image_batch, label_batch = next(iter(train_dataset))\n", + "feature_batch = base_model(image_batch)\n", + "print(feature_batch.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Shows the different label probabilities in one tensor \n", + "label_batch" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now decode the predictions made by the model. Earlier, when you printed the shape of the batch, it would have returned (32, 1000). The number 32 refers to the batch size and 1000 refers to the 1000 classes the model was pretrained on. The predictions returned by the base model below follow this format:\n", + "\n", + "First the class number, then a human-readable label, and last the probability of the image belonging to that class. You'll notice that there are two of these returned for each image in the batch - these the top two probabilities returned for that image." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data from https://storage.googleapis.com/download.tensorflow.org/data/imagenet_class_index.json\n", + "40960/35363 [==================================] - 0s 0us/step\n" + ] + }, + { + "data": { + "text/plain": [ + "[[('n02489166', 'proboscis_monkey', 0.10329965),\n", + " ('n02102177', 'Welsh_springer_spaniel', 0.07883611)],\n", + " [('n02125311', 'cougar', 0.1654676), ('n02389026', 'sorrel', 0.10764261)],\n", + " [('n02437312', 'Arabian_camel', 0.2923283),\n", + " ('n02437616', 'llama', 0.27713484)],\n", + " [('n03944341', 'pinwheel', 0.31154886), ('n03047690', 'clog', 0.052500293)],\n", + " [('n02454379', 'armadillo', 0.73107153),\n", + " ('n01990800', 'isopod', 0.038719974)],\n", + " [('n02437312', 'Arabian_camel', 0.25663644),\n", + " ('n02422106', 'hartebeest', 0.12122728)],\n", + " [('n02437616', 'llama', 0.6612557),\n", + " ('n02090721', 'Irish_wolfhound', 0.23782855)],\n", + " [('n02133161', 'American_black_bear', 0.82735676),\n", + " ('n02134418', 'sloth_bear', 0.02925945)],\n", + " [('n01518878', 'ostrich', 0.9267562),\n", + " ('n02002724', 'black_stork', 0.0017766367)],\n", + " [('n01518878', 'ostrich', 0.94954586),\n", + " ('n02018795', 'bustard', 0.0028661634)],\n", + " [('n02437616', 'llama', 0.8699833), ('n02412080', 'ram', 0.076757126)],\n", + " [('n02415577', 'bighorn', 0.2429446), ('n02412080', 'ram', 0.160565)],\n", + " [('n02437616', 'llama', 0.9473245), ('n02480495', 'orangutan', 0.0076571796)],\n", + " [('n09428293', 'seashore', 0.48092392), ('n09421951', 'sandbar', 0.26179993)],\n", + " [('n02437312', 'Arabian_camel', 0.95963204),\n", + " ('n02504458', 'African_elephant', 0.0009881927)],\n", + " [('n02509815', 'lesser_panda', 0.9096807),\n", + " ('n02443114', 'polecat', 0.014759211)],\n", + " [('n01518878', 'ostrich', 0.74165), ('n02002724', 'black_stork', 0.07205889)],\n", + " [('n02437312', 'Arabian_camel', 0.49920738),\n", + " ('n02412080', 'ram', 0.11842591)],\n", + " [('n01518878', 'ostrich', 0.87967354),\n", + " ('n02018795', 'bustard', 0.0077298395)],\n", + " [('n02437616', 'llama', 0.82569915),\n", + " ('n02437312', 'Arabian_camel', 0.010480011)],\n", + " [('n01518878', 'ostrich', 0.9612779), ('n02410509', 'bison', 0.0013086519)],\n", + " [('n02437616', 'llama', 0.636178), ('n02412080', 'ram', 0.058401026)],\n", + " [('n02437616', 'llama', 0.5928003), ('n02417914', 'ibex', 0.039721698)],\n", + " [('n02437616', 'llama', 0.83541703), ('n02104029', 'kuvasz', 0.048998024)],\n", + " [('n03042490', 'cliff_dwelling', 0.3091509),\n", + " ('n04208210', 'shovel', 0.06726616)],\n", + " [('n02093647', 'Bedlington_terrier', 0.4338772),\n", + " ('n02113799', 'standard_poodle', 0.4069308)],\n", + " [('n02133161', 'American_black_bear', 0.97880507),\n", + " ('n02132136', 'brown_bear', 0.0055297976)],\n", + " [('n01518878', 'ostrich', 0.83605814), ('n02018795', 'bustard', 0.004823002)],\n", + " [('n02133161', 'American_black_bear', 0.9362426),\n", + " ('n02134418', 'sloth_bear', 0.007733786)],\n", + " [('n03240683', 'drilling_platform', 0.04555222),\n", + " ('n04146614', 'school_bus', 0.033719867)],\n", + " [('n02437616', 'llama', 0.9278842),\n", + " ('n02098286', 'West_Highland_white_terrier', 0.0057286685)],\n", + " [('n02437616', 'llama', 0.94477594), ('n02423022', 'gazelle', 0.0054335156)]]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "base_model.trainable = False\n", + "image_var = tf.Variable(preprocess_input(image_batch))\n", + "pred = base_model(image_var)\n", + "\n", + "tf.keras.applications.mobilenet_v2.decode_predictions(pred.numpy(), top=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Uh-oh. There's a whole lot of labels here, some of them hilariously wrong, but none of them say \"alpaca.\"\n", + "\n", + "This is because MobileNet pretrained over ImageNet doesn't have the correct labels for alpacas, so when you use the full model, all you get is a bunch of incorrectly classified images.\n", + "\n", + "Fortunately, you can delete the top layer, which contains all the classification labels, and create a new classification layer." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.2 - Layer Freezing with the Functional API\n", + "\n", + "\n", + "\n", + "In the next sections, you'll see how you can use a pretrained model to modify the classifier task so that it's able to recognize alpacas. You can achieve this in three steps: \n", + "\n", + "1. Delete the top layer (the classification layer)\n", + " * Set `include_top` in `base_model` as False\n", + "2. Add a new classifier layer\n", + " * Train only one layer by freezing the rest of the network\n", + " * As mentioned before, a single neuron is enough to solve a binary classification problem.\n", + "3. Freeze the base model and train the newly-created classifier layer\n", + " * Set `base model.trainable=False` to avoid changing the weights and train *only* the new layer\n", + " * Set training in `base_model` to False to avoid keeping track of statistics in the batch norm layer" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 2 - alpaca_model" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-106ac76f39286ee3", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [], + "source": [ + "# UNQ_C2\n", + "# GRADED FUNCTION\n", + "def alpaca_model(image_shape=IMG_SIZE, data_augmentation=data_augmenter()):\n", + " ''' Define a tf.keras model for binary classification out of the MobileNetV2 model\n", + " Arguments:\n", + " image_shape -- Image width and height\n", + " data_augmentation -- data augmentation function\n", + " Returns:\n", + " Returns:\n", + " tf.keras.model\n", + " '''\n", + " \n", + " \n", + " input_shape = image_shape + (3,)\n", + " \n", + " ###Β START CODE HERE\n", + " \n", + " base_model = tf.keras.applications.MobileNetV2(input_shape=input_shape,\n", + " include_top=False, # <== Important!!!!\n", + " weights='imagenet') # From imageNet\n", + " \n", + " # freeze the base model by making it non trainable\n", + " base_model.trainable = False\n", + "\n", + " # create the input layer (Same as the imageNetv2 input size)\n", + " inputs = tf.keras.Input(shape=input_shape) \n", + " \n", + " # apply data augmentation to the inputs\n", + " x = data_augmentation(inputs)\n", + " \n", + " # data preprocessing using the same weights the model was trained on\n", + " # Already Done -> preprocess_input = tf.keras.applications.mobilenet_v2.preprocess_input\n", + " x = preprocess_input(x) \n", + " \n", + " # set training to False to avoid keeping track of statistics in the batch norm layer\n", + " x = base_model(x, training=False) \n", + " \n", + " # add the new Binary classification layers\n", + " # use global avg pooling to summarize the info in each channel\n", + " x = tfl.GlobalAveragePooling2D()(x) \n", + " #include dropout with probability of 0.2 to avoid overfitting\n", + " x = tfl.Dropout(0.2)(x)\n", + " \n", + " # use a prediction layer with one neuron (as a binary classifier only needs one)\n", + " prediction_layer = tfl.Dense(1)\n", + " \n", + " \n", + " ###Β END CODE HERE\n", + " outputs = prediction_layer(x) \n", + " model = tf.keras.Model(inputs, outputs)\n", + " \n", + " return model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Create your new model using the data_augmentation function defined earlier." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "model2 = alpaca_model(IMG_SIZE, data_augmentation)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-f668c813eff7f3d1", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mAll tests passed!\u001b[0m\n", + "['InputLayer', [(None, 160, 160, 3)], 0]\n", + "['Sequential', (None, 160, 160, 3), 0]\n", + "['TensorFlowOpLayer', [(None, 160, 160, 3)], 0]\n", + "['TensorFlowOpLayer', [(None, 160, 160, 3)], 0]\n", + "['Functional', (None, 5, 5, 1280), 2257984]\n", + "['GlobalAveragePooling2D', (None, 1280), 0]\n", + "['Dropout', (None, 1280), 0, 0.2]\n", + "['Dense', (None, 1), 1281, 'linear']\n" + ] + } + ], + "source": [ + "from test_utils import summary, comparator\n", + "\n", + "alpaca_summary = [['InputLayer', [(None, 160, 160, 3)], 0],\n", + " ['Sequential', (None, 160, 160, 3), 0],\n", + " ['TensorFlowOpLayer', [(None, 160, 160, 3)], 0],\n", + " ['TensorFlowOpLayer', [(None, 160, 160, 3)], 0],\n", + " ['Functional', (None, 5, 5, 1280), 2257984],\n", + " ['GlobalAveragePooling2D', (None, 1280), 0],\n", + " ['Dropout', (None, 1280), 0, 0.2],\n", + " ['Dense', (None, 1), 1281, 'linear']] #linear is the default activation\n", + "\n", + "comparator(summary(model2), alpaca_summary)\n", + "\n", + "for layer in summary(model2):\n", + " print(layer)\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The base learning rate has been set for you, so you can go ahead and compile the new model and run it for 5 epochs:" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "base_learning_rate = 0.001\n", + "model2.compile(optimizer=tf.keras.optimizers.Adam(lr=base_learning_rate),\n", + " loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n", + " metrics=['accuracy'])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/5\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.7665 - accuracy: 0.5611 - val_loss: 0.6658 - val_accuracy: 0.5538\n", + "Epoch 2/5\n", + "9/9 [==============================] - 8s 836ms/step - loss: 0.6257 - accuracy: 0.6603 - val_loss: 0.5015 - val_accuracy: 0.7077\n", + "Epoch 3/5\n", + "9/9 [==============================] - 8s 857ms/step - loss: 0.5199 - accuracy: 0.7137 - val_loss: 0.4585 - val_accuracy: 0.7077\n", + "Epoch 4/5\n", + "9/9 [==============================] - 8s 845ms/step - loss: 0.4364 - accuracy: 0.7481 - val_loss: 0.4357 - val_accuracy: 0.7077\n", + "Epoch 5/5\n", + "9/9 [==============================] - 8s 845ms/step - loss: 0.3981 - accuracy: 0.7748 - val_loss: 0.3436 - val_accuracy: 0.8154\n" + ] + } + ], + "source": [ + "initial_epochs = 5\n", + "history = model2.fit(train_dataset, validation_data=validation_dataset, epochs=initial_epochs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plot the training and validation accuracy:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "acc = [0.] + history.history['accuracy']\n", + "val_acc = [0.] + history.history['val_accuracy']\n", + "\n", + "loss = history.history['loss']\n", + "val_loss = history.history['val_loss']\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.subplot(2, 1, 1)\n", + "plt.plot(acc, label='Training Accuracy')\n", + "plt.plot(val_acc, label='Validation Accuracy')\n", + "plt.legend(loc='lower right')\n", + "plt.ylabel('Accuracy')\n", + "plt.ylim([min(plt.ylim()),1])\n", + "plt.title('Training and Validation Accuracy')\n", + "\n", + "plt.subplot(2, 1, 2)\n", + "plt.plot(loss, label='Training Loss')\n", + "plt.plot(val_loss, label='Validation Loss')\n", + "plt.legend(loc='upper right')\n", + "plt.ylabel('Cross Entropy')\n", + "plt.ylim([0,1.0])\n", + "plt.title('Training and Validation Loss')\n", + "plt.xlabel('epoch')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['alpaca', 'not alpaca']" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "class_names" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The results are ok, but could be better. Next, try some fine-tuning." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### 3.3 - Fine-tuning the Model\n", + "\n", + "You could try fine-tuning the model by re-running the optimizer in the last layers to improve accuracy. When you use a smaller learning rate, you take smaller steps to adapt it a little more closely to the new data. In transfer learning, the way you achieve this is by unfreezing the layers at the end of the network, and then re-training your model on the final layers with a very low learning rate. Adapting your learning rate to go over these layers in smaller steps can yield more fine details - and higher accuracy.\n", + "\n", + "The intuition for what's happening: when the network is in its earlier stages, it trains on low-level features, like edges. In the later layers, more complex, high-level features like wispy hair or pointy ears begin to emerge. For transfer learning, the low-level features can be kept the same, as they have common features for most images. When you add new data, you generally want the high-level features to adapt to it, which is rather like letting the network learn to detect features more related to your data, such as soft fur or big teeth. \n", + "\n", + "To achieve this, just unfreeze the final layers and re-run the optimizer with a smaller learning rate, while keeping all the other layers frozen.\n", + "\n", + "Where the final layers actually begin is a bit arbitrary, so feel free to play around with this number a bit. The important takeaway is that the later layers are the part of your network that contain the fine details (pointy ears, hairy tails) that are more specific to your problem.\n", + "\n", + "First, unfreeze the base model by setting `base_model.trainable=True`, set a layer to fine-tune from, then re-freeze all the layers before it. Run it again for another few epochs, and see if your accuracy improved!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Exercise 3" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "nbgrader": { + "grade": false, + "grade_id": "cell-5c3d1b52347cc066", + "locked": false, + "schema_version": 3, + "solution": true, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of layers in the base model: 155\n" + ] + } + ], + "source": [ + "# UNQ_C3\n", + "base_model = model2.layers[4]\n", + "base_model.trainable = True\n", + "# Let's take a look to see how many layers are in the base model\n", + "print(\"Number of layers in the base model: \", len(base_model.layers))\n", + "\n", + "# Fine-tune from this layer onwards\n", + "fine_tune_at = 120\n", + "\n", + "###Β START CODE HERE\n", + "\n", + "# Freeze all the layers before the `fine_tune_at` layer\n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = None\n", + " \n", + "# Define a BinaryCrossentropy loss function. Use from_logits=True\n", + "loss_function= tf.keras.losses.BinaryCrossentropy(from_logits=True)\n", + "# Define an Adam optimizer with a learning rate of 0.1 * base_learning_rate\n", + "optimizer = tf.keras.optimizers.Adam(learning_rate=base_learning_rate*0.1)# 0.001\n", + "# Use accuracy as evaluation metric\n", + "metrics=['accuracy']\n", + "\n", + "###Β END CODE HERE\n", + "\n", + "model2.compile(loss=loss_function,\n", + " optimizer = optimizer,\n", + " metrics=metrics)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "nbgrader": { + "grade": true, + "grade_id": "cell-6f11678f0b1d5adb", + "locked": true, + "points": 1, + "schema_version": 3, + "solution": false, + "task": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[92mAll tests passed!\n" + ] + } + ], + "source": [ + "assert type(loss_function) == tf.python.keras.losses.BinaryCrossentropy, \"Not the correct layer\"\n", + "assert loss_function.from_logits, \"Use from_logits=True\"\n", + "assert type(optimizer) == tf.keras.optimizers.Adam, \"This is not an Adam optimizer\"\n", + "assert optimizer.lr == base_learning_rate / 10, \"Wrong learning rate\"\n", + "assert metrics[0] == 'accuracy', \"Wrong metric\"\n", + "\n", + "print('\\033[92mAll tests passed!')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 5/10\n", + "9/9 [==============================] - 10s 1s/step - loss: 0.5834 - accuracy: 0.7786 - val_loss: 0.4219 - val_accuracy: 0.7385\n", + "Epoch 6/10\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.3629 - accuracy: 0.8244 - val_loss: 0.2373 - val_accuracy: 0.9231\n", + "Epoch 7/10\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.2718 - accuracy: 0.8817 - val_loss: 0.1708 - val_accuracy: 0.9231\n", + "Epoch 8/10\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.1920 - accuracy: 0.9237 - val_loss: 0.1331 - val_accuracy: 0.9538\n", + "Epoch 9/10\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.1848 - accuracy: 0.9008 - val_loss: 0.0881 - val_accuracy: 0.9692\n", + "Epoch 10/10\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.1802 - accuracy: 0.9122 - val_loss: 0.0882 - val_accuracy: 0.9538\n" + ] + } + ], + "source": [ + "fine_tune_epochs = 5\n", + "total_epochs = initial_epochs + fine_tune_epochs\n", + "\n", + "history_fine = model2.fit(train_dataset,\n", + " epochs=total_epochs,\n", + " initial_epoch=history.epoch[-1],\n", + " validation_data=validation_dataset)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahhh, quite an improvement! A little fine-tuning can really go a long way." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "acc += history_fine.history['accuracy']\n", + "val_acc += history_fine.history['val_accuracy']\n", + "\n", + "loss += history_fine.history['loss']\n", + "val_loss += history_fine.history['val_loss']" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 8))\n", + "plt.subplot(2, 1, 1)\n", + "plt.plot(acc, label='Training Accuracy')\n", + "plt.plot(val_acc, label='Validation Accuracy')\n", + "plt.ylim([0, 1])\n", + "plt.plot([initial_epochs-1,initial_epochs-1],\n", + " plt.ylim(), label='Start Fine Tuning')\n", + "plt.legend(loc='lower right')\n", + "plt.title('Training and Validation Accuracy')\n", + "\n", + "plt.subplot(2, 1, 2)\n", + "plt.plot(loss, label='Training Loss')\n", + "plt.plot(val_loss, label='Validation Loss')\n", + "plt.ylim([0, 1.0])\n", + "plt.plot([initial_epochs-1,initial_epochs-1],\n", + " plt.ylim(), label='Start Fine Tuning')\n", + "plt.legend(loc='upper right')\n", + "plt.title('Training and Validation Loss')\n", + "plt.xlabel('epoch')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "**What you should remember**:\n", + "\n", + "* To adapt the classifier to new data: Delete the top layer, add a new classification layer, and train only on that layer\n", + "* When freezing layers, avoid keeping track of statistics (like in the batch normalization layer)\n", + "* Fine-tune the final layers of your model to capture high-level details near the end of the network and potentially improve accuracy " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Congratulations!\n", + "\n", + "You've completed this assignment on transfer learning and fine-tuning. Here's a quick recap of all you just accomplished:\n", + "\n", + "* Created a dataset from a directory\n", + "* Augmented data with the Sequential API\n", + "* Adapted a pretrained model to new data with the Functional API and MobileNetV2\n", + "* Fine-tuned the classifier's final layers and boosted the model's accuracy\n", + "\n", + "That's awesome! " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 378ccdfb244c7e347918c6dab8fcf7ccd6ca5200 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:25:26 +0530 Subject: [PATCH 03/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index caa8585143c..94fc946fd2d 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples - +1


From 4dd4d5c58f8641ef07886d50b28cbdaac025cec7 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:25:37 +0530 Subject: [PATCH 04/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 94fc946fd2d..2e8d29f3c7f 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -1 +12


From d9be84ec988daa72fccf30be8c2c79d84aa75acf Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:25:48 +0530 Subject: [PATCH 05/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2e8d29f3c7f..2b597c84e0d 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -12 +123


From e770fb4fc608abc1c2d9c36f6a55bbf3e5e68c00 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:25:59 +0530 Subject: [PATCH 06/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2b597c84e0d..9940e01f63f 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -123 +1234


From 0dc7c2f6efa144de7e540fc74137230004a9647b Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:26:12 +0530 Subject: [PATCH 07/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9940e01f63f..68391fb95f9 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -1234 +12345


From 4793934dab95e8c4e1f361b8f2c6e2bd47f47e94 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:26:24 +0530 Subject: [PATCH 08/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 68391fb95f9..d0f1eb05d4d 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -12345 +123456


From dfc81ad210ff6c7bf47984e036f231966251fb4f Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:26:39 +0530 Subject: [PATCH 09/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d0f1eb05d4d..524c84de465 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -123456 +1234567


From 3209160283eb2d7b3df5295562363b131b2d99c5 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:26:56 +0530 Subject: [PATCH 10/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 524c84de465..4b238581d94 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -1234567 +12345678


From 3d015abf9b09266878db06cd2e390576f839fb42 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:27:11 +0530 Subject: [PATCH 11/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 4b238581d94..fec6799d0c0 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -12345678 +123456789


From 34910e03d5bb5be48fcffd0c46f100803f9eeaa2 Mon Sep 17 00:00:00 2001 From: Durgesh Rao <77789927+DURGESH716@users.noreply.github.com> Date: Wed, 1 Feb 2023 01:27:26 +0530 Subject: [PATCH 12/12] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index fec6799d0c0..caa8585143c 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # TensorFlow Examples -123456789 +