ML_project.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ML_project.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "Jfv_jLxgxpDX",
        "Obu6Nq8YvMOb",
        "28TzrBhMyu6E",
        "Y5l9q3Ut2M0b",
        "NrIH3xmvihpa",
        "3UuFoU7Pih77",
        "qDRKRKYDpalU",
        "e-VO9GGt5wQ4"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "rsZ32DvkRjXD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "53c45463-f867-45cc-f7a4-e63ddd9ee44b"
      },
      "source": [
        "!pip3 install gdown\n",
        "!gdown https://drive.google.com/file/d/1Y25en48feU-AAa19Zidpxw-1jfez88Vc/view?usp=sharing\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: gdown in /usr/local/lib/python3.7/dist-packages (3.6.4)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from gdown) (2.23.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from gdown) (4.62.3)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from gdown) (1.15.0)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->gdown) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->gdown) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->gdown) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->gdown) (2021.10.8)\n",
            "/usr/local/lib/python2.7/dist-packages/gdown/parse_url.py:31: UserWarning: You specified Google Drive Link but it is not the correct link to download the file. Maybe you should try: https://drive.google.com/uc?id=1Y25en48feU-AAa19Zidpxw-1jfez88Vc\n",
            "  .format(url='https://drive.google.com/uc?id={}'.format(file_id))\n",
            "Downloading...\n",
            "From: https://drive.google.com/file/d/1Y25en48feU-AAa19Zidpxw-1jfez88Vc/view?usp=sharing\n",
            "To: /content/view?usp=sharing\n",
            "66.6kB [00:00, 9.70MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wap5ygq-daJ1"
      },
      "source": [
        "# Import Statements"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ApjSUAmkfOuU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bbbee239-73ff-4891-da36-15331e25c228"
      },
      "source": [
        "!gdown --id 1Y25en48feU-AAa19Zidpxw-1jfez88Vc\n",
        "!gdown --id 1AsbRTEmoamy3KZ-8TW8DldeKHEVoUZSb\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from tqdm import tqdm\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import classification_report\n",
        "import seaborn as sns\n",
        "from sklearn.metrics import classification_report\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1Y25en48feU-AAa19Zidpxw-1jfez88Vc\n",
            "To: /content/sign_mnist_train.csv\n",
            "100% 83.3M/83.3M [00:00<00:00, 179MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1AsbRTEmoamy3KZ-8TW8DldeKHEVoUZSb\n",
            "To: /content/sign_mnist_test.csv\n",
            "100% 21.8M/21.8M [00:00<00:00, 133MB/s] \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xBHCh3esfZLj"
      },
      "source": [
        "df = pd.read_csv('sign_mnist_train.csv')\n",
        "df_test=pd.read_csv('sign_mnist_test.csv')"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jfv_jLxgxpDX"
      },
      "source": [
        "# Understanding the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yat6N7eXyinE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "20d6600e-daf8-419f-e2b2-7258ba2a5ad5"
      },
      "source": [
        "print(df_test.shape)   \n",
        "df.info()      "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(7172, 785)\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 27455 entries, 0 to 27454\n",
            "Columns: 785 entries, label to pixel784\n",
            "dtypes: int64(785)\n",
            "memory usage: 164.4 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0sEoEgEKfd4B",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bbf043ed-03ee-4793-d7b0-a54429a359bb"
      },
      "source": [
        "image = df.values[19, 1:].reshape((28, 28))\n",
        "plt.imshow(image,cmap='gray')\n",
        "plt.show()\n",
        "image = df.values[130, 1:].reshape((28, 28))\n",
        "plt.imshow(image,cmap='gray')\n",
        "plt.show()\n",
        "image = df.values[3, 1:].reshape((28, 28))\n",
        "plt.imshow(image,cmap='gray')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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N7M2qOprKW18diMdGX758ufS+oxr/vHnz3PjExIQb92rC3vroAHD27Fk3Hs0TsGDBAjfu1YxTxroD1Y5Xj/ZdZ9/LmslFNRMAfmxm75BcAGA3yR1F7Gdm9q/VdU9EmmUm67MPARgqbo+RPATgrqo7JiLN9bnes5P8KoBvANhVbHqW5Hskt5Jc0qDNJpL9JPvPnTuX1FkRKW/GyU7yKwB+D+BHZjYK4BcAVgBYjcln/p9O187MtphZn5n1dXZ2NqHLIlLGjJKd5GxMJvpvzOwPAGBmw2Z23cxuAPglgDXVdVNEUoXJzslhNK8AOGRmm6ds75nya98B4A/NEpFazeTT+HUAvgdgH8k9xbbnAWwguRqT5bhjAPy1ezFZrvBKMSlT6EalkPHxcTeeUt6KSmvRkstHjx514xcuXHDjnmj536hvUWkuKht65y26z+pcVjm1b1X23du31++ZfBr/ZwDTZWHb1tRF5LN0BZ1IJpTsIplQsotkQskukgklu0gmlOwimWj5ks1VSa1rRrVybwhsNMwzdQhrNBzTW3Y5mpY4Eh07Ghqccvzo2NF5q1LqEFmvfXTOyj7W9cwukgklu0gmlOwimVCyi2RCyS6SCSW7SCaU7CKZYOqUuJ/rYOQZAFPXF+4C4A+Yrk+79q1d+wWob2U1s2/3mNnfTBdoabJ/5uBkv5n11dYBR7v2rV37BahvZbWqb3oZL5IJJbtIJupO9i01H9/Trn1r134B6ltZLelbre/ZRaR16n5mF5EWUbKLZKKWZCf5GMn/JXmY5HN19KERksdI7iO5h2R/zX3ZSnKE5P4p2zpI7iA5UHyfdo29mvr2IsnB4tztIfl4TX1bTvJPJA+SPEDyh8X2Ws+d06+WnLeWv2cnOQvA/wH4RwAnAbwNYIOZHWxpRxogeQxAn5nVfgEGyYcBXAbwazO7v9j2LwDOm9lLxT/KJWb2z23StxcBXK57Ge9itaKeqcuMA3gCwPdR47lz+vUkWnDe6nhmXwPgsJkdMbOrAH4LYH0N/Wh7ZvYWgPOf2rwewLbi9jZMPlharkHf2oKZDZnZO8XtMQA3lxmv9dw5/WqJOpL9LgAnpvx8Eu213rsB+CPJ3SQ31d2ZaXSb2VBx+zSA7jo7M41wGe9W+tQy421z7sosf55KH9B91oNm9ncAvg3gB8XL1bZkk+/B2ql2OqNlvFtlmmXG/6rOc1d2+fNUdST7IIDlU35eVmxrC2Y2WHwfAfAa2m8p6uGbK+gW30dq7s9ftdMy3tMtM442OHd1Ln9eR7K/DWAlya+RnAPguwC219CPzyA5v/jgBCTnA/gW2m8p6u0ANha3NwJ4vca+fEK7LOPdaJlx1Hzual/+3Mxa/gXgcUx+Iv8XAC/U0YcG/fo6gL3F14G6+wbgVUy+rLuGyc82ngbQCWAngAEA/wOgo4369h8A9gF4D5OJ1VNT3x7E5Ev09wDsKb4er/vcOf1qyXnT5bIimdAHdCKZULKLZELJLpIJJbtIJpTsIplQsotkQskukon/Bzf1Dts2kVu1AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I_M6IltB8GiG",
        "outputId": "5bbcb89e-e427-49d4-c985-3aff30d3d31f"
      },
      "source": [
        "df.iloc[:, 0:1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27450</th>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27451</th>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27452</th>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27453</th>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27454</th>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>27455 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       label\n",
              "0          3\n",
              "1          6\n",
              "2          2\n",
              "3          2\n",
              "4         13\n",
              "...      ...\n",
              "27450     13\n",
              "27451     23\n",
              "27452     18\n",
              "27453     17\n",
              "27454     23\n",
              "\n",
              "[27455 rows x 1 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xKawrAdi7nN3",
        "outputId": "3f953c4a-c132-49a3-d8f6-a305057a8a24"
      },
      "source": [
        "a = df[df.iloc[:, 0] == 19]\n",
        "a"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>pixel1</th>\n",
              "      <th>pixel2</th>\n",
              "      <th>pixel3</th>\n",
              "      <th>pixel4</th>\n",
              "      <th>pixel5</th>\n",
              "      <th>pixel6</th>\n",
              "      <th>pixel7</th>\n",
              "      <th>pixel8</th>\n",
              "      <th>pixel9</th>\n",
              "      <th>pixel10</th>\n",
              "      <th>pixel11</th>\n",
              "      <th>pixel12</th>\n",
              "      <th>pixel13</th>\n",
              "      <th>pixel14</th>\n",
              "      <th>pixel15</th>\n",
              "      <th>pixel16</th>\n",
              "      <th>pixel17</th>\n",
              "      <th>pixel18</th>\n",
              "      <th>pixel19</th>\n",
              "      <th>pixel20</th>\n",
              "      <th>pixel21</th>\n",
              "      <th>pixel22</th>\n",
              "      <th>pixel23</th>\n",
              "      <th>pixel24</th>\n",
              "      <th>pixel25</th>\n",
              "      <th>pixel26</th>\n",
              "      <th>pixel27</th>\n",
              "      <th>pixel28</th>\n",
              "      <th>pixel29</th>\n",
              "      <th>pixel30</th>\n",
              "      <th>pixel31</th>\n",
              "      <th>pixel32</th>\n",
              "      <th>pixel33</th>\n",
              "      <th>pixel34</th>\n",
              "      <th>pixel35</th>\n",
              "      <th>pixel36</th>\n",
              "      <th>pixel37</th>\n",
              "      <th>pixel38</th>\n",
              "      <th>pixel39</th>\n",
              "      <th>...</th>\n",
              "      <th>pixel745</th>\n",
              "      <th>pixel746</th>\n",
              "      <th>pixel747</th>\n",
              "      <th>pixel748</th>\n",
              "      <th>pixel749</th>\n",
              "      <th>pixel750</th>\n",
              "      <th>pixel751</th>\n",
              "      <th>pixel752</th>\n",
              "      <th>pixel753</th>\n",
              "      <th>pixel754</th>\n",
              "      <th>pixel755</th>\n",
              "      <th>pixel756</th>\n",
              "      <th>pixel757</th>\n",
              "      <th>pixel758</th>\n",
              "      <th>pixel759</th>\n",
              "      <th>pixel760</th>\n",
              "      <th>pixel761</th>\n",
              "      <th>pixel762</th>\n",
              "      <th>pixel763</th>\n",
              "      <th>pixel764</th>\n",
              "      <th>pixel765</th>\n",
              "      <th>pixel766</th>\n",
              "      <th>pixel767</th>\n",
              "      <th>pixel768</th>\n",
              "      <th>pixel769</th>\n",
              "      <th>pixel770</th>\n",
              "      <th>pixel771</th>\n",
              "      <th>pixel772</th>\n",
              "      <th>pixel773</th>\n",
              "      <th>pixel774</th>\n",
              "      <th>pixel775</th>\n",
              "      <th>pixel776</th>\n",
              "      <th>pixel777</th>\n",
              "      <th>pixel778</th>\n",
              "      <th>pixel779</th>\n",
              "      <th>pixel780</th>\n",
              "      <th>pixel781</th>\n",
              "      <th>pixel782</th>\n",
              "      <th>pixel783</th>\n",
              "      <th>pixel784</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>19</td>\n",
              "      <td>173</td>\n",
              "      <td>174</td>\n",
              "      <td>176</td>\n",
              "      <td>177</td>\n",
              "      <td>176</td>\n",
              "      <td>177</td>\n",
              "      <td>177</td>\n",
              "      <td>177</td>\n",
              "      <td>177</td>\n",
              "      <td>177</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>174</td>\n",
              "      <td>173</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>169</td>\n",
              "      <td>168</td>\n",
              "      <td>168</td>\n",
              "      <td>167</td>\n",
              "      <td>167</td>\n",
              "      <td>166</td>\n",
              "      <td>174</td>\n",
              "      <td>174</td>\n",
              "      <td>176</td>\n",
              "      <td>178</td>\n",
              "      <td>178</td>\n",
              "      <td>179</td>\n",
              "      <td>180</td>\n",
              "      <td>179</td>\n",
              "      <td>178</td>\n",
              "      <td>178</td>\n",
              "      <td>177</td>\n",
              "      <td>...</td>\n",
              "      <td>203</td>\n",
              "      <td>202</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>199</td>\n",
              "      <td>196</td>\n",
              "      <td>195</td>\n",
              "      <td>194</td>\n",
              "      <td>193</td>\n",
              "      <td>191</td>\n",
              "      <td>204</td>\n",
              "      <td>206</td>\n",
              "      <td>207</td>\n",
              "      <td>196</td>\n",
              "      <td>184</td>\n",
              "      <td>176</td>\n",
              "      <td>175</td>\n",
              "      <td>157</td>\n",
              "      <td>134</td>\n",
              "      <td>105</td>\n",
              "      <td>88</td>\n",
              "      <td>81</td>\n",
              "      <td>76</td>\n",
              "      <td>82</td>\n",
              "      <td>186</td>\n",
              "      <td>205</td>\n",
              "      <td>204</td>\n",
              "      <td>203</td>\n",
              "      <td>202</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>199</td>\n",
              "      <td>197</td>\n",
              "      <td>195</td>\n",
              "      <td>195</td>\n",
              "      <td>193</td>\n",
              "      <td>190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>19</td>\n",
              "      <td>188</td>\n",
              "      <td>189</td>\n",
              "      <td>192</td>\n",
              "      <td>195</td>\n",
              "      <td>196</td>\n",
              "      <td>195</td>\n",
              "      <td>197</td>\n",
              "      <td>199</td>\n",
              "      <td>200</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>200</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>199</td>\n",
              "      <td>200</td>\n",
              "      <td>199</td>\n",
              "      <td>197</td>\n",
              "      <td>196</td>\n",
              "      <td>197</td>\n",
              "      <td>196</td>\n",
              "      <td>195</td>\n",
              "      <td>194</td>\n",
              "      <td>193</td>\n",
              "      <td>193</td>\n",
              "      <td>189</td>\n",
              "      <td>191</td>\n",
              "      <td>193</td>\n",
              "      <td>196</td>\n",
              "      <td>197</td>\n",
              "      <td>198</td>\n",
              "      <td>200</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>201</td>\n",
              "      <td>...</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>222</td>\n",
              "      <td>221</td>\n",
              "      <td>222</td>\n",
              "      <td>221</td>\n",
              "      <td>221</td>\n",
              "      <td>220</td>\n",
              "      <td>218</td>\n",
              "      <td>217</td>\n",
              "      <td>217</td>\n",
              "      <td>216</td>\n",
              "      <td>64</td>\n",
              "      <td>64</td>\n",
              "      <td>67</td>\n",
              "      <td>41</td>\n",
              "      <td>28</td>\n",
              "      <td>32</td>\n",
              "      <td>27</td>\n",
              "      <td>51</td>\n",
              "      <td>224</td>\n",
              "      <td>226</td>\n",
              "      <td>225</td>\n",
              "      <td>226</td>\n",
              "      <td>226</td>\n",
              "      <td>226</td>\n",
              "      <td>225</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>223</td>\n",
              "      <td>222</td>\n",
              "      <td>223</td>\n",
              "      <td>222</td>\n",
              "      <td>220</td>\n",
              "      <td>219</td>\n",
              "      <td>217</td>\n",
              "      <td>217</td>\n",
              "      <td>217</td>\n",
              "      <td>217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>19</td>\n",
              "      <td>121</td>\n",
              "      <td>129</td>\n",
              "      <td>138</td>\n",
              "      <td>143</td>\n",
              "      <td>148</td>\n",
              "      <td>149</td>\n",
              "      <td>152</td>\n",
              "      <td>156</td>\n",
              "      <td>161</td>\n",
              "      <td>164</td>\n",
              "      <td>168</td>\n",
              "      <td>174</td>\n",
              "      <td>175</td>\n",
              "      <td>177</td>\n",
              "      <td>181</td>\n",
              "      <td>182</td>\n",
              "      <td>185</td>\n",
              "      <td>184</td>\n",
              "      <td>188</td>\n",
              "      <td>190</td>\n",
              "      <td>191</td>\n",
              "      <td>193</td>\n",
              "      <td>193</td>\n",
              "      <td>193</td>\n",
              "      <td>195</td>\n",
              "      <td>195</td>\n",
              "      <td>195</td>\n",
              "      <td>196</td>\n",
              "      <td>122</td>\n",
              "      <td>131</td>\n",
              "      <td>139</td>\n",
              "      <td>146</td>\n",
              "      <td>149</td>\n",
              "      <td>152</td>\n",
              "      <td>157</td>\n",
              "      <td>160</td>\n",
              "      <td>165</td>\n",
              "      <td>169</td>\n",
              "      <td>174</td>\n",
              "      <td>...</td>\n",
              "      <td>228</td>\n",
              "      <td>229</td>\n",
              "      <td>231</td>\n",
              "      <td>232</td>\n",
              "      <td>233</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>237</td>\n",
              "      <td>237</td>\n",
              "      <td>157</td>\n",
              "      <td>157</td>\n",
              "      <td>207</td>\n",
              "      <td>209</td>\n",
              "      <td>179</td>\n",
              "      <td>157</td>\n",
              "      <td>130</td>\n",
              "      <td>126</td>\n",
              "      <td>111</td>\n",
              "      <td>86</td>\n",
              "      <td>88</td>\n",
              "      <td>80</td>\n",
              "      <td>176</td>\n",
              "      <td>225</td>\n",
              "      <td>220</td>\n",
              "      <td>224</td>\n",
              "      <td>227</td>\n",
              "      <td>229</td>\n",
              "      <td>231</td>\n",
              "      <td>232</td>\n",
              "      <td>233</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>236</td>\n",
              "      <td>237</td>\n",
              "      <td>237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>19</td>\n",
              "      <td>169</td>\n",
              "      <td>175</td>\n",
              "      <td>179</td>\n",
              "      <td>183</td>\n",
              "      <td>186</td>\n",
              "      <td>188</td>\n",
              "      <td>192</td>\n",
              "      <td>193</td>\n",
              "      <td>195</td>\n",
              "      <td>197</td>\n",
              "      <td>198</td>\n",
              "      <td>199</td>\n",
              "      <td>199</td>\n",
              "      <td>201</td>\n",
              "      <td>202</td>\n",
              "      <td>202</td>\n",
              "      <td>202</td>\n",
              "      <td>201</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>201</td>\n",
              "      <td>200</td>\n",
              "      <td>200</td>\n",
              "      <td>199</td>\n",
              "      <td>197</td>\n",
              "      <td>196</td>\n",
              "      <td>195</td>\n",
              "      <td>194</td>\n",
              "      <td>171</td>\n",
              "      <td>177</td>\n",
              "      <td>181</td>\n",
              "      <td>184</td>\n",
              "      <td>188</td>\n",
              "      <td>190</td>\n",
              "      <td>192</td>\n",
              "      <td>193</td>\n",
              "      <td>197</td>\n",
              "      <td>199</td>\n",
              "      <td>199</td>\n",
              "      <td>...</td>\n",
              "      <td>228</td>\n",
              "      <td>228</td>\n",
              "      <td>227</td>\n",
              "      <td>225</td>\n",
              "      <td>225</td>\n",
              "      <td>225</td>\n",
              "      <td>224</td>\n",
              "      <td>222</td>\n",
              "      <td>221</td>\n",
              "      <td>220</td>\n",
              "      <td>220</td>\n",
              "      <td>217</td>\n",
              "      <td>35</td>\n",
              "      <td>27</td>\n",
              "      <td>21</td>\n",
              "      <td>16</td>\n",
              "      <td>18</td>\n",
              "      <td>4</td>\n",
              "      <td>92</td>\n",
              "      <td>233</td>\n",
              "      <td>217</td>\n",
              "      <td>223</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>226</td>\n",
              "      <td>228</td>\n",
              "      <td>228</td>\n",
              "      <td>229</td>\n",
              "      <td>229</td>\n",
              "      <td>227</td>\n",
              "      <td>226</td>\n",
              "      <td>225</td>\n",
              "      <td>225</td>\n",
              "      <td>225</td>\n",
              "      <td>224</td>\n",
              "      <td>223</td>\n",
              "      <td>221</td>\n",
              "      <td>220</td>\n",
              "      <td>218</td>\n",
              "      <td>217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>19</td>\n",
              "      <td>145</td>\n",
              "      <td>146</td>\n",
              "      <td>148</td>\n",
              "      <td>150</td>\n",
              "      <td>152</td>\n",
              "      <td>154</td>\n",
              "      <td>155</td>\n",
              "      <td>155</td>\n",
              "      <td>156</td>\n",
              "      <td>157</td>\n",
              "      <td>157</td>\n",
              "      <td>159</td>\n",
              "      <td>159</td>\n",
              "      <td>159</td>\n",
              "      <td>159</td>\n",
              "      <td>160</td>\n",
              "      <td>161</td>\n",
              "      <td>163</td>\n",
              "      <td>163</td>\n",
              "      <td>162</td>\n",
              "      <td>161</td>\n",
              "      <td>160</td>\n",
              "      <td>161</td>\n",
              "      <td>161</td>\n",
              "      <td>161</td>\n",
              "      <td>162</td>\n",
              "      <td>163</td>\n",
              "      <td>163</td>\n",
              "      <td>147</td>\n",
              "      <td>149</td>\n",
              "      <td>152</td>\n",
              "      <td>154</td>\n",
              "      <td>155</td>\n",
              "      <td>157</td>\n",
              "      <td>158</td>\n",
              "      <td>158</td>\n",
              "      <td>159</td>\n",
              "      <td>159</td>\n",
              "      <td>160</td>\n",
              "      <td>...</td>\n",
              "      <td>207</td>\n",
              "      <td>208</td>\n",
              "      <td>208</td>\n",
              "      <td>208</td>\n",
              "      <td>208</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "      <td>209</td>\n",
              "      <td>194</td>\n",
              "      <td>197</td>\n",
              "      <td>200</td>\n",
              "      <td>201</td>\n",
              "      <td>194</td>\n",
              "      <td>179</td>\n",
              "      <td>188</td>\n",
              "      <td>190</td>\n",
              "      <td>171</td>\n",
              "      <td>145</td>\n",
              "      <td>120</td>\n",
              "      <td>96</td>\n",
              "      <td>80</td>\n",
              "      <td>74</td>\n",
              "      <td>92</td>\n",
              "      <td>176</td>\n",
              "      <td>209</td>\n",
              "      <td>209</td>\n",
              "      <td>209</td>\n",
              "      <td>209</td>\n",
              "      <td>209</td>\n",
              "      <td>209</td>\n",
              "      <td>210</td>\n",
              "      <td>211</td>\n",
              "      <td>211</td>\n",
              "      <td>211</td>\n",
              "      <td>210</td>\n",
              "      <td>210</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27389</th>\n",
              "      <td>19</td>\n",
              "      <td>138</td>\n",
              "      <td>139</td>\n",
              "      <td>141</td>\n",
              "      <td>143</td>\n",
              "      <td>145</td>\n",
              "      <td>145</td>\n",
              "      <td>146</td>\n",
              "      <td>146</td>\n",
              "      <td>147</td>\n",
              "      <td>148</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>148</td>\n",
              "      <td>148</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>149</td>\n",
              "      <td>148</td>\n",
              "      <td>139</td>\n",
              "      <td>141</td>\n",
              "      <td>144</td>\n",
              "      <td>145</td>\n",
              "      <td>147</td>\n",
              "      <td>147</td>\n",
              "      <td>148</td>\n",
              "      <td>148</td>\n",
              "      <td>149</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>...</td>\n",
              "      <td>89</td>\n",
              "      <td>148</td>\n",
              "      <td>135</td>\n",
              "      <td>141</td>\n",
              "      <td>145</td>\n",
              "      <td>154</td>\n",
              "      <td>141</td>\n",
              "      <td>124</td>\n",
              "      <td>132</td>\n",
              "      <td>141</td>\n",
              "      <td>153</td>\n",
              "      <td>109</td>\n",
              "      <td>83</td>\n",
              "      <td>84</td>\n",
              "      <td>84</td>\n",
              "      <td>85</td>\n",
              "      <td>83</td>\n",
              "      <td>83</td>\n",
              "      <td>85</td>\n",
              "      <td>134</td>\n",
              "      <td>143</td>\n",
              "      <td>124</td>\n",
              "      <td>104</td>\n",
              "      <td>91</td>\n",
              "      <td>70</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>56</td>\n",
              "      <td>133</td>\n",
              "      <td>173</td>\n",
              "      <td>169</td>\n",
              "      <td>125</td>\n",
              "      <td>137</td>\n",
              "      <td>135</td>\n",
              "      <td>149</td>\n",
              "      <td>115</td>\n",
              "      <td>125</td>\n",
              "      <td>146</td>\n",
              "      <td>143</td>\n",
              "      <td>96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27405</th>\n",
              "      <td>19</td>\n",
              "      <td>183</td>\n",
              "      <td>184</td>\n",
              "      <td>183</td>\n",
              "      <td>183</td>\n",
              "      <td>184</td>\n",
              "      <td>184</td>\n",
              "      <td>184</td>\n",
              "      <td>183</td>\n",
              "      <td>184</td>\n",
              "      <td>184</td>\n",
              "      <td>184</td>\n",
              "      <td>184</td>\n",
              "      <td>182</td>\n",
              "      <td>181</td>\n",
              "      <td>181</td>\n",
              "      <td>181</td>\n",
              "      <td>179</td>\n",
              "      <td>179</td>\n",
              "      <td>178</td>\n",
              "      <td>177</td>\n",
              "      <td>176</td>\n",
              "      <td>176</td>\n",
              "      <td>174</td>\n",
              "      <td>172</td>\n",
              "      <td>170</td>\n",
              "      <td>169</td>\n",
              "      <td>168</td>\n",
              "      <td>167</td>\n",
              "      <td>185</td>\n",
              "      <td>185</td>\n",
              "      <td>186</td>\n",
              "      <td>187</td>\n",
              "      <td>186</td>\n",
              "      <td>186</td>\n",
              "      <td>185</td>\n",
              "      <td>186</td>\n",
              "      <td>187</td>\n",
              "      <td>185</td>\n",
              "      <td>184</td>\n",
              "      <td>...</td>\n",
              "      <td>61</td>\n",
              "      <td>149</td>\n",
              "      <td>255</td>\n",
              "      <td>243</td>\n",
              "      <td>246</td>\n",
              "      <td>244</td>\n",
              "      <td>242</td>\n",
              "      <td>241</td>\n",
              "      <td>239</td>\n",
              "      <td>238</td>\n",
              "      <td>234</td>\n",
              "      <td>234</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>242</td>\n",
              "      <td>185</td>\n",
              "      <td>190</td>\n",
              "      <td>197</td>\n",
              "      <td>196</td>\n",
              "      <td>183</td>\n",
              "      <td>152</td>\n",
              "      <td>122</td>\n",
              "      <td>99</td>\n",
              "      <td>79</td>\n",
              "      <td>73</td>\n",
              "      <td>234</td>\n",
              "      <td>251</td>\n",
              "      <td>245</td>\n",
              "      <td>246</td>\n",
              "      <td>244</td>\n",
              "      <td>244</td>\n",
              "      <td>241</td>\n",
              "      <td>239</td>\n",
              "      <td>238</td>\n",
              "      <td>236</td>\n",
              "      <td>232</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27431</th>\n",
              "      <td>19</td>\n",
              "      <td>234</td>\n",
              "      <td>233</td>\n",
              "      <td>233</td>\n",
              "      <td>234</td>\n",
              "      <td>234</td>\n",
              "      <td>235</td>\n",
              "      <td>236</td>\n",
              "      <td>237</td>\n",
              "      <td>238</td>\n",
              "      <td>238</td>\n",
              "      <td>237</td>\n",
              "      <td>234</td>\n",
              "      <td>237</td>\n",
              "      <td>235</td>\n",
              "      <td>233</td>\n",
              "      <td>233</td>\n",
              "      <td>233</td>\n",
              "      <td>234</td>\n",
              "      <td>235</td>\n",
              "      <td>234</td>\n",
              "      <td>235</td>\n",
              "      <td>233</td>\n",
              "      <td>232</td>\n",
              "      <td>230</td>\n",
              "      <td>229</td>\n",
              "      <td>229</td>\n",
              "      <td>227</td>\n",
              "      <td>225</td>\n",
              "      <td>236</td>\n",
              "      <td>235</td>\n",
              "      <td>237</td>\n",
              "      <td>236</td>\n",
              "      <td>239</td>\n",
              "      <td>239</td>\n",
              "      <td>237</td>\n",
              "      <td>239</td>\n",
              "      <td>239</td>\n",
              "      <td>238</td>\n",
              "      <td>238</td>\n",
              "      <td>...</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>246</td>\n",
              "      <td>210</td>\n",
              "      <td>168</td>\n",
              "      <td>184</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>255</td>\n",
              "      <td>234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27436</th>\n",
              "      <td>19</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>170</td>\n",
              "      <td>171</td>\n",
              "      <td>170</td>\n",
              "      <td>169</td>\n",
              "      <td>169</td>\n",
              "      <td>169</td>\n",
              "      <td>167</td>\n",
              "      <td>167</td>\n",
              "      <td>166</td>\n",
              "      <td>166</td>\n",
              "      <td>166</td>\n",
              "      <td>164</td>\n",
              "      <td>164</td>\n",
              "      <td>162</td>\n",
              "      <td>161</td>\n",
              "      <td>160</td>\n",
              "      <td>159</td>\n",
              "      <td>157</td>\n",
              "      <td>156</td>\n",
              "      <td>171</td>\n",
              "      <td>171</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>171</td>\n",
              "      <td>172</td>\n",
              "      <td>172</td>\n",
              "      <td>171</td>\n",
              "      <td>171</td>\n",
              "      <td>...</td>\n",
              "      <td>77</td>\n",
              "      <td>138</td>\n",
              "      <td>229</td>\n",
              "      <td>214</td>\n",
              "      <td>217</td>\n",
              "      <td>216</td>\n",
              "      <td>214</td>\n",
              "      <td>213</td>\n",
              "      <td>211</td>\n",
              "      <td>210</td>\n",
              "      <td>209</td>\n",
              "      <td>211</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>224</td>\n",
              "      <td>228</td>\n",
              "      <td>204</td>\n",
              "      <td>164</td>\n",
              "      <td>176</td>\n",
              "      <td>180</td>\n",
              "      <td>178</td>\n",
              "      <td>167</td>\n",
              "      <td>147</td>\n",
              "      <td>123</td>\n",
              "      <td>105</td>\n",
              "      <td>91</td>\n",
              "      <td>88</td>\n",
              "      <td>208</td>\n",
              "      <td>222</td>\n",
              "      <td>216</td>\n",
              "      <td>217</td>\n",
              "      <td>216</td>\n",
              "      <td>215</td>\n",
              "      <td>214</td>\n",
              "      <td>212</td>\n",
              "      <td>212</td>\n",
              "      <td>208</td>\n",
              "      <td>174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27446</th>\n",
              "      <td>19</td>\n",
              "      <td>133</td>\n",
              "      <td>135</td>\n",
              "      <td>138</td>\n",
              "      <td>141</td>\n",
              "      <td>143</td>\n",
              "      <td>144</td>\n",
              "      <td>144</td>\n",
              "      <td>145</td>\n",
              "      <td>145</td>\n",
              "      <td>145</td>\n",
              "      <td>144</td>\n",
              "      <td>143</td>\n",
              "      <td>145</td>\n",
              "      <td>144</td>\n",
              "      <td>143</td>\n",
              "      <td>143</td>\n",
              "      <td>143</td>\n",
              "      <td>142</td>\n",
              "      <td>141</td>\n",
              "      <td>140</td>\n",
              "      <td>137</td>\n",
              "      <td>151</td>\n",
              "      <td>113</td>\n",
              "      <td>102</td>\n",
              "      <td>166</td>\n",
              "      <td>160</td>\n",
              "      <td>175</td>\n",
              "      <td>175</td>\n",
              "      <td>137</td>\n",
              "      <td>139</td>\n",
              "      <td>142</td>\n",
              "      <td>144</td>\n",
              "      <td>146</td>\n",
              "      <td>147</td>\n",
              "      <td>148</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>151</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>176</td>\n",
              "      <td>167</td>\n",
              "      <td>156</td>\n",
              "      <td>138</td>\n",
              "      <td>139</td>\n",
              "      <td>140</td>\n",
              "      <td>116</td>\n",
              "      <td>82</td>\n",
              "      <td>55</td>\n",
              "      <td>4</td>\n",
              "      <td>21</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1186 rows × 785 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       label  pixel1  pixel2  pixel3  ...  pixel781  pixel782  pixel783  pixel784\n",
              "19        19     173     174     176  ...       195       195       193       190\n",
              "47        19     188     189     192  ...       217       217       217       217\n",
              "55        19     121     129     138  ...       236       236       237       237\n",
              "65        19     169     175     179  ...       221       220       218       217\n",
              "101       19     145     146     148  ...       211       211       210       210\n",
              "...      ...     ...     ...     ...  ...       ...       ...       ...       ...\n",
              "27389     19     138     139     141  ...       125       146       143        96\n",
              "27405     19     183     184     183  ...       239       238       236       232\n",
              "27431     19     234     233     233  ...       255       255       255       234\n",
              "27436     19     170     170     170  ...       212       212       208       174\n",
              "27446     19     133     135     138  ...         0         0         0         0\n",
              "\n",
              "[1186 rows x 785 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nF-Kxryh63s2",
        "outputId": "b8511436-508d-4b85-c1bb-bdeccfda0376"
      },
      "source": [
        "print(\"Unique values in Train data \",np.unique(df.values[:,0]))\n",
        "print(\"Unique values in Test data \",np.unique(df_test.values[:,0]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unique values in Train data  [ 0  1  2  3  4  5  6  7  8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24]\n",
            "Unique values in Test data  [ 0  1  2  3  4  5  6  7  8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Obu6Nq8YvMOb"
      },
      "source": [
        "# Preprocessing the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wITYHirSvRSU",
        "outputId": "82baa20d-bb1a-495a-d0bd-7754a15069f1"
      },
      "source": [
        "\n",
        "X_train = df.values[:, 1:]\n",
        "Y_train = df.values[:, 0]\n",
        "X_test = df_test.values[:, 1:]\n",
        "Y_test = df_test.values[:, 0]\n",
        "print(X_train.shape, Y_train.shape, X_test.shape, Y_test.shape)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(27455, 784) (27455,) (7172, 784) (7172,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MMdjlTdZwB7L"
      },
      "source": [
        "####    Normalising all values between -1 to 1 , using Standard Scaler"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q1ZeBVc-vjhz",
        "outputId": "293e4539-c9a1-4d38-ff83-323ae70d4264"
      },
      "source": [
        "from sklearn import preprocessing\n",
        "\n",
        "scaler = preprocessing.StandardScaler().fit(X_train)\n",
        "X_train=scaler.transform(X_train)\n",
        "X_test=scaler.transform(X_test)\n",
        "\n",
        "print(X_train.shape)\n",
        "print(X_train[:2])"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(27455, 784)\n",
            "[[-0.92895113 -0.76362507 -0.62085156 ...  0.66406257  0.65811336\n",
            "   0.65493948]\n",
            " [ 0.23165213  0.2128048   0.12168008 ... -0.93157535 -0.41091344\n",
            "  -0.16809718]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tzQZCWo3VL0B"
      },
      "source": [
        "# Trying different models"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "28TzrBhMyu6E"
      },
      "source": [
        "## Applying Logistic Regression on the model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bl4zKZvyvF2l"
      },
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "\n",
        "log_model = LogisticRegression(random_state=0,max_iter=400,penalty='none').fit(X_train,Y_train)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f06Bc42qtWkJ"
      },
      "source": [
        "Y_test_pred = log_model.predict(X_test)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "oWgqgXG0uuze",
        "outputId": "741766fa-82c5-4500-d948-8172f861d099"
      },
      "source": [
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for Simple Logistic Regression\",fontsize=20)\n",
        "\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.6529559397657557\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.77      1.00      0.87       331\n",
            "           1       0.94      0.80      0.86       432\n",
            "           2       0.99      0.80      0.88       310\n",
            "           3       0.83      0.78      0.80       245\n",
            "           4       0.76      0.89      0.82       498\n",
            "           5       0.66      0.89      0.76       247\n",
            "           6       0.78      0.70      0.74       348\n",
            "           7       0.81      0.67      0.73       436\n",
            "           8       0.70      0.51      0.59       288\n",
            "          10       0.56      0.49      0.52       331\n",
            "          11       0.55      0.80      0.65       209\n",
            "          12       0.63      0.63      0.63       394\n",
            "          13       0.43      0.30      0.36       291\n",
            "          14       0.95      0.63      0.76       246\n",
            "          15       0.87      0.99      0.93       347\n",
            "          16       0.69      0.74      0.72       164\n",
            "          17       0.16      0.30      0.21       144\n",
            "          18       0.25      0.34      0.29       246\n",
            "          19       0.38      0.37      0.38       248\n",
            "          20       0.40      0.39      0.40       266\n",
            "          21       0.72      0.48      0.58       346\n",
            "          22       0.44      0.70      0.54       206\n",
            "          23       0.55      0.46      0.50       267\n",
            "          24       0.60      0.55      0.58       332\n",
            "\n",
            "    accuracy                           0.65      7172\n",
            "   macro avg       0.64      0.63      0.63      7172\n",
            "weighted avg       0.67      0.65      0.65      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "62unJ1Kg19on"
      },
      "source": [
        "#### Logisitic Regression with L2 regularisation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1v7Lf28b1836",
        "outputId": "3d74f532-b5d7-496e-b140-22ee8d8f8573"
      },
      "source": [
        "log_model_l2 = LogisticRegression(random_state=0,max_iter=400,penalty='l2',C=0.01).fit(X_train,Y_train)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_logistic.py:818: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG,\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gVPnE5J523f0",
        "outputId": "ef7af550-4c99-42fe-9289-d6d4061a34d7"
      },
      "source": [
        "Y_test_pred = log_model_l2.predict(X_test)\n",
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for Ridge Logistic Regression\",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.7064974902398216\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.86      1.00      0.92       331\n",
            "           1       1.00      0.88      0.93       432\n",
            "           2       0.94      0.92      0.93       310\n",
            "           3       0.87      0.93      0.90       245\n",
            "           4       0.88      0.87      0.88       498\n",
            "           5       0.71      0.91      0.80       247\n",
            "           6       0.82      0.73      0.77       348\n",
            "           7       0.81      0.72      0.76       436\n",
            "           8       0.64      0.65      0.65       288\n",
            "          10       0.71      0.50      0.58       331\n",
            "          11       0.63      0.89      0.74       209\n",
            "          12       0.71      0.63      0.66       394\n",
            "          13       0.69      0.57      0.63       291\n",
            "          14       0.99      0.69      0.82       246\n",
            "          15       0.96      0.95      0.96       347\n",
            "          16       0.62      0.74      0.68       164\n",
            "          17       0.17      0.43      0.24       144\n",
            "          18       0.36      0.48      0.41       246\n",
            "          19       0.39      0.41      0.40       248\n",
            "          20       0.49      0.47      0.48       266\n",
            "          21       0.81      0.53      0.65       346\n",
            "          22       0.45      0.69      0.54       206\n",
            "          23       0.58      0.45      0.51       267\n",
            "          24       0.73      0.57      0.64       332\n",
            "\n",
            "    accuracy                           0.71      7172\n",
            "   macro avg       0.70      0.69      0.69      7172\n",
            "weighted avg       0.74      0.71      0.71      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rlugwgiv2u9b"
      },
      "source": [
        "#### Logisitic Regression with L1 regularisation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YfZDBM7v2zSC"
      },
      "source": [
        "log_model_l1 = LogisticRegression(random_state=0,max_iter=400,penalty='l1',solver='liblinear').fit(X_train,Y_train)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rw3vZTxX24CV",
        "outputId": "afb002f3-61e7-4e67-cbdb-81547e59c7c5"
      },
      "source": [
        "Y_test_pred = log_model_l1.predict(X_test)\n",
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for Lasso Logistic Regression\",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.6330172894590073\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.80      0.95      0.87       331\n",
            "           1       0.95      0.87      0.91       432\n",
            "           2       0.92      0.86      0.89       310\n",
            "           3       0.83      0.91      0.87       245\n",
            "           4       0.87      0.94      0.91       498\n",
            "           5       0.58      0.87      0.70       247\n",
            "           6       0.78      0.76      0.77       348\n",
            "           7       0.81      0.70      0.75       436\n",
            "           8       0.48      0.56      0.52       288\n",
            "          10       0.45      0.30      0.36       331\n",
            "          11       0.58      0.55      0.56       209\n",
            "          12       0.64      0.52      0.58       394\n",
            "          13       0.47      0.36      0.40       291\n",
            "          14       0.78      0.50      0.61       246\n",
            "          15       0.67      0.67      0.67       347\n",
            "          16       0.68      0.62      0.65       164\n",
            "          17       0.18      0.43      0.26       144\n",
            "          18       0.36      0.50      0.42       246\n",
            "          19       0.42      0.56      0.48       248\n",
            "          20       0.34      0.45      0.39       266\n",
            "          21       0.72      0.40      0.51       346\n",
            "          22       0.38      0.51      0.44       206\n",
            "          23       0.73      0.31      0.44       267\n",
            "          24       0.63      0.58      0.60       332\n",
            "\n",
            "    accuracy                           0.63      7172\n",
            "   macro avg       0.63      0.61      0.61      7172\n",
            "weighted avg       0.66      0.63      0.63      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y5l9q3Ut2M0b"
      },
      "source": [
        "##  Decision Tree  model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "19TdB_VX2Q2G"
      },
      "source": [
        "from sklearn import tree\n",
        "tree_model = tree.DecisionTreeClassifier()\n",
        "tree_model = tree_model.fit(X_train, Y_train)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5iArNFuU3pEr",
        "outputId": "eb87d211-04f2-4790-f725-64294fc947f4"
      },
      "source": [
        "Y_test_pred = tree_model.predict(X_test)\n",
        "print(tree_model.score(X_test,Y_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.4347462353597323\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Fsxhfea63uCN",
        "outputId": "82d3ad86-fd9d-4b69-c5de-24bc4b8a768b"
      },
      "source": [
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for Decision Tree\",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.4347462353597323\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.70      0.71      0.71       331\n",
            "           1       0.72      0.53      0.61       432\n",
            "           2       0.63      0.73      0.67       310\n",
            "           3       0.41      0.42      0.42       245\n",
            "           4       0.67      0.50      0.57       498\n",
            "           5       0.45      0.55      0.49       247\n",
            "           6       0.50      0.45      0.47       348\n",
            "           7       0.71      0.57      0.63       436\n",
            "           8       0.20      0.20      0.20       288\n",
            "          10       0.32      0.26      0.29       331\n",
            "          11       0.51      0.58      0.55       209\n",
            "          12       0.38      0.34      0.36       394\n",
            "          13       0.21      0.16      0.18       291\n",
            "          14       0.47      0.35      0.40       246\n",
            "          15       0.67      0.59      0.63       347\n",
            "          16       0.53      0.79      0.63       164\n",
            "          17       0.07      0.14      0.10       144\n",
            "          18       0.22      0.32      0.26       246\n",
            "          19       0.33      0.35      0.34       248\n",
            "          20       0.30      0.40      0.35       266\n",
            "          21       0.26      0.23      0.25       346\n",
            "          22       0.22      0.38      0.28       206\n",
            "          23       0.36      0.39      0.37       267\n",
            "          24       0.45      0.36      0.40       332\n",
            "\n",
            "    accuracy                           0.43      7172\n",
            "   macro avg       0.43      0.43      0.42      7172\n",
            "weighted avg       0.46      0.43      0.44      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NrIH3xmvihpa"
      },
      "source": [
        "## Ensembling On Decision Tree model (Random Forest Classifier)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3hP8Xc6-IKWv"
      },
      "source": [
        "from sklearn.ensemble import  RandomForestClassifier"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OyILkA8OHR3u",
        "outputId": "9bcf4aa8-f6b1-47e2-c8de-5e193f44a621"
      },
      "source": [
        "from sklearn.model_selection import GridSearchCV\n",
        "clf = GridSearchCV(RandomForestClassifier(), {\n",
        "        'n_estimators': [80, 100, 120, 200, 300],\n",
        "        'criterion': ['entropy','gini'],\n",
        "           'max_depth': [2, 4, 10, 18, 30]\n",
        "}, cv=5, return_train_score=False)\n",
        "clf.fit(X_train, Y_train)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/plain": [
              "GridSearchCV(cv=5, estimator=RandomForestClassifier(),\n",
              "             param_grid={'criterion': ['entropy', 'gini'],\n",
              "                         'max_depth': [2, 4, 10, 18, 30],\n",
              "                         'n_estimators': [80, 100, 120, 200, 300]})"
            ]
          },
          "execution_count": 63,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y71P9sNtHR3u",
        "outputId": "b1543743-717f-4475-b474-e88754ec929a"
      },
      "source": [
        "clf.best_params_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'criterion': 'entropy', 'max_depth': 30, 'n_estimators': 300}"
            ]
          },
          "execution_count": 65,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zpAgRzHGHR3u"
      },
      "source": [
        "rf_model_tuned = RandomForestClassifier(n_estimators=300, criterion='entropy',max_depth=30, random_state=0)\n",
        "rf_model_tuned.fit(X_train, Y_train)\n",
        "Y_pred_rf_tuned = rf_model_tuned.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "mIfXOg3rAEWJ",
        "outputId": "106b9156-7d1b-4de0-fb11-34a8e65b30c2"
      },
      "source": [
        "cf_matrix=confusion_matrix(Y_test, Y_pred_rf_tuned)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_pred_rf_tuned))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for RF \",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_pred_rf_tuned))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.8149749023982152\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.93      1.00      0.97       331\n",
            "           1       0.97      0.95      0.96       432\n",
            "           2       0.95      1.00      0.97       310\n",
            "           3       0.87      0.97      0.92       245\n",
            "           4       0.88      0.98      0.92       498\n",
            "           5       0.90      0.91      0.90       247\n",
            "           6       0.94      0.83      0.88       348\n",
            "           7       1.00      0.92      0.96       436\n",
            "           8       0.87      0.80      0.84       288\n",
            "          10       0.76      0.65      0.70       331\n",
            "          11       0.79      1.00      0.88       209\n",
            "          12       0.92      0.65      0.76       394\n",
            "          13       0.79      0.58      0.67       291\n",
            "          14       1.00      0.83      0.91       246\n",
            "          15       0.91      1.00      0.95       347\n",
            "          16       0.94      1.00      0.97       164\n",
            "          17       0.30      0.62      0.41       144\n",
            "          18       0.54      0.81      0.65       246\n",
            "          19       0.55      0.79      0.65       248\n",
            "          20       0.66      0.61      0.64       266\n",
            "          21       0.83      0.54      0.65       346\n",
            "          22       0.47      0.65      0.54       206\n",
            "          23       0.85      0.76      0.80       267\n",
            "          24       0.93      0.57      0.71       332\n",
            "\n",
            "    accuracy                           0.81      7172\n",
            "   macro avg       0.81      0.81      0.80      7172\n",
            "weighted avg       0.84      0.81      0.82      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c92EywL1hvr2",
        "outputId": "42dac450-6f8e-4ff6-94b0-175ec6f4dd0e"
      },
      "source": [
        "print(\"\\nCLASSIFICATION REPORT for RF classifier\\n\")\n",
        "print(classification_report(Y_test, Y_pred_rf))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT for RF classifier\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.91      1.00      0.95       331\n",
            "           1       0.96      0.92      0.94       432\n",
            "           2       0.94      0.99      0.97       310\n",
            "           3       0.87      0.98      0.92       245\n",
            "           4       0.91      0.97      0.94       498\n",
            "           5       0.90      0.91      0.91       247\n",
            "           6       0.91      0.85      0.88       348\n",
            "           7       0.99      0.92      0.95       436\n",
            "           8       0.74      0.76      0.75       288\n",
            "          10       0.73      0.72      0.72       331\n",
            "          11       0.80      1.00      0.89       209\n",
            "          12       0.85      0.64      0.73       394\n",
            "          13       0.69      0.58      0.63       291\n",
            "          14       0.99      0.85      0.91       246\n",
            "          15       0.92      1.00      0.96       347\n",
            "          16       0.93      0.99      0.96       164\n",
            "          17       0.37      0.67      0.48       144\n",
            "          18       0.56      0.73      0.64       246\n",
            "          19       0.58      0.79      0.67       248\n",
            "          20       0.71      0.59      0.64       266\n",
            "          21       0.81      0.61      0.70       346\n",
            "          22       0.56      0.65      0.60       206\n",
            "          23       0.85      0.75      0.80       267\n",
            "          24       0.91      0.60      0.72       332\n",
            "\n",
            "    accuracy                           0.82      7172\n",
            "   macro avg       0.81      0.81      0.80      7172\n",
            "weighted avg       0.83      0.82      0.82      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pGEpHLCrH3S1"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3UuFoU7Pih77"
      },
      "source": [
        "## SVM\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Zq-OaoiijNY"
      },
      "source": [
        "from sklearn import svm"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f1B3gF23jPWA",
        "outputId": "7c4fda32-dce3-4404-c56a-315ef5d45b99"
      },
      "source": [
        "svm_model = svm.SVC()\n",
        "svm_model.fit(X_train, Y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC()"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8gmPgv3ejogb",
        "outputId": "2d28bcf1-bfd0-43f4-98b7-4af52eb13468"
      },
      "source": [
        "Y_test_pred = svm_model.predict(X_test)\n",
        "print(svm_model.score(X_test,Y_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.848856664807585\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ChN-SKocj7_X",
        "outputId": "f8c6c06b-b8a0-4a4f-d432-00347983ec58"
      },
      "source": [
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for SVM \",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.848856664807585\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.92      1.00      0.96       331\n",
            "           1       1.00      0.99      0.99       432\n",
            "           2       0.95      1.00      0.97       310\n",
            "           3       0.96      1.00      0.98       245\n",
            "           4       0.95      0.99      0.97       498\n",
            "           5       0.82      0.86      0.84       247\n",
            "           6       0.93      0.94      0.94       348\n",
            "           7       1.00      0.95      0.98       436\n",
            "           8       0.81      0.88      0.85       288\n",
            "          10       0.81      0.63      0.71       331\n",
            "          11       0.88      1.00      0.94       209\n",
            "          12       0.82      0.78      0.80       394\n",
            "          13       0.90      0.66      0.76       291\n",
            "          14       0.92      0.93      0.93       246\n",
            "          15       1.00      1.00      1.00       347\n",
            "          16       0.99      1.00      1.00       164\n",
            "          17       0.26      0.47      0.33       144\n",
            "          18       0.70      0.74      0.72       246\n",
            "          19       0.80      0.70      0.75       248\n",
            "          20       0.56      0.67      0.61       266\n",
            "          21       0.83      0.59      0.69       346\n",
            "          22       0.62      0.78      0.69       206\n",
            "          23       0.78      0.75      0.77       267\n",
            "          24       0.87      0.75      0.81       332\n",
            "\n",
            "    accuracy                           0.85      7172\n",
            "   macro avg       0.84      0.84      0.83      7172\n",
            "weighted avg       0.86      0.85      0.85      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qDRKRKYDpalU"
      },
      "source": [
        "## Applying MLP classifier"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W9qLLzxOksbK"
      },
      "source": [
        "from sklearn.neural_network import MLPClassifier\n",
        "from sklearn.model_selection import GridSearchCV"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cp3zsFw3pfVr",
        "outputId": "108257a0-522d-4647-d873-406e78bbe42b"
      },
      "source": [
        "mlpc = MLPClassifier(hidden_layer_sizes=(600,650,700),activation='relu').fit(X_train,Y_train)\n",
        "print(mlpc.score(X_test,Y_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.8565253764640268\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xCkpn5raO_SU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "e6240627-fc7a-4083-a79f-249ec72e452d"
      },
      "source": [
        "Y_test_pred=mlpc.predict(X_test)\n",
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for MLP \",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.8565253764640268\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dMWQfvXVNX+3Wprn+MvXzhhzyOysrK1dBQZuq6/n5eSorK8+4Bi8dHhq8dHho8NLhocFLh4cGLx0eGrx0eGjw0uGhwUuHhwYvHR4avHTQgO1FbJNkM7tO0qOSTNKb0cUk/cPMrm+ocTYG6fj7p+iwO1/Sfh1aq1u7FpKka574QIf85kXNWbRKJ+zdvqGGAwAAAIDtipm5uXgQ55HkCyUdFEL4VQjh4ejyK0kHR/fVycxGmtk0M5u2YvrT33mw5Ws36PXPlujI3b/5zdHGIP33gy91bJpO0lVbfn6eSksXV10vKytXfn5exjV46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClgwZsL+KcJG+UtHMdt7eP7qtTCKEohNArhNCr5YHHb3aAnZo1UqsmyU+5apyTpSN2y9PcxavUeadmVdv036OdPl28qj7926xHj0KVlCzU/PmlWr++QsXFk9Wv38EZ1+Clw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cOGrC9iPNzkq+QNMnMZkuaH922i6TdJV3aEAO0a9lYvz15X2WZKcuk4g9L9cLsRXr8gkPUonGOTNLHZSv08wkfSpL23bmV/nj6AWrdNEdH79FWV/bdXcfc+1pDpNQpJydbo0eP0ogRY5RIbNTQof1VWNg5ZeN5bfDS4aHBS4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGrx0eGjw0uGhwUsHDZ75OGGWFxbSdSrnugZPnr7sYEkdopsWSHorhJDY9KO+seuYifHFR0pu6hp3AgAAAIBYdPPxJtpt1KrriNjnVZWWzx0f+z6N80iyQggbJb0RZwMAAAAAAJVinSQDAAAAAOLl5fOJvWBvAAAAAAAQYZIMAAAAAECE5dYAAAAAkMFYbl0TewMAAAAAgAhHkgEAAAAggxnHTmtgbwAAAAAAEGGSDAAAAABAhOXWAAAAAJDBOHFXTdv1JLnkpq5xJ6jbQc/FnSBJmvXWgLgTAAAAAGC7x68MAAAAAACIbNdHkgEAAAAA24bl1jWxNwAAAAAAiDBJBgAAAAAgwnJrAAAAAMhgLLeuib0BAAAAAECESTIAAAAAABGWWwMAAABABjNZ3AmucCQZAAAAAIBIxk6SJ0+eroEDR2nAgJEqKno85eNlZZmeePg0/fHOQZKkW37eV0/9fbieemS47vnVQDVr2kiSdP4Z++npx36opx4Zrof+cJJ2LmiZ8rZ07wvPHR4avHR4aPDS4aHBS4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGrx00OCTWZabiwc+KtIskUho3Lj7NX78WBUX36sJEyZrzpx5KR3z3NP31aefLa26futdr+rEMx/TiWc8pi9LV+qs03pIkj76ZLFOOedxnXjGY5o4aY6uveywlHbFsS+8dnho8NLhocFLh4cGLx0eGrx0eGjw0uGhwUuHhwYvHR4avHR4aPDSQQO2Fxk5SZ4xY7Y6d26vTp0KlJvbSIMG9dGkSVNTNl5+u+Y66ohd9fiTH1XdtmpVRdXXjRvnKIQgSZo6fYHWrtsgSXr3/TLlt2uRsi4p/fvCc4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGrx0eGjw0uGhwUuHhwYvHTRge5GRk+SysnIVFLSpup6fn6eysvKUjfezq47Q7fdM0caNocbtt43upykTz1fXXXfQ3x57/1uPG3bSXpo85fOUdUnp3xeeOzw0eOnw0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjpoMGvuJdYs9w6wxx1RGeVL12jD2cu+tZ9N4x7QUcc/xd9WrJUxx+ze437Tjyum/bZq53G/+2ddKUCAAAAQMZzOUk2s/M3c99IM5tmZtOKih6r1/Pn5+eptHRx1fWysnLl5+fV67m25MD92uvoH3TRC0+erbtuHahDD+qgO8b1r7p/48ag4v/N1sC+u1Xd1vvgjrr4/AM16uqnVVGxMSVdldK5L7x3eGjw0uGhwUuHhwYvHR4avHR4aPDS4aHBS4eHBi8dHhq8dHho8NJBA7YXLifJkm7a1B0hhKIQQq8QQq+RI4fX68l79ChUSclCzZ9fqvXrK1RcPFn9+h1c79jN+e29b6jP4IfU76S/6cobn9Ubby3QNaOf1y4dW1dtc3SfLpr7efKkXnt1a6NxNxylUVc/rSVL16Skqbp07gvvHR4avHR4aPDS4aHBS4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGrx00OBX3EusvS23zolrYDObsam7JOWncuycnGyNHj1KI0aMUSKxUUOH9ldhYedUDlmDmfTrsUerRfNcmUkzZ5drzK9ekiRdd3lvNWvaSPf86lhJ0sLSFbr46qdT1hL3vvDU4aHBS4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGrx0eGjw0uGhwUsHDdheWOVZldM+sFmZpIGSlta+S9KUEMLOW36WWfHEV9PtoOfiTpAkzXprQNwJAAAAQIbpZnEXNISC7tfFPq+qVPrRr2Pfp7EdSZY0QVKLEMK7te8ws5fSnwMAAAAAmcjHMmcvYpskhxAu3Mx9Z6SzBQAAAAAAKd4jyQAAAACAmHk5YZYX7A0AAAAAACJMkgEAAAAAiLDcGgAAAAAyGMuta2JvAAAAAAAQYZIMAAAAAECE5dYAAAAAkMGMY6c1sDcAAAAAAIgwSQYAAAAAIMJy6200660BcSdIkna5+8u4EzTv8vZxJwAAAADYSpzduib2BgAAAAAAEY4kAwAAAEAGM7O4E1zhSDIAAAAAABEmyQAAAAAARFhuDQAAAAAZjBN31cTeAAAAAAAgwiQZAAAAAIAIy60BAAAAIIMZx05rYG8AAAAAABDJ2Eny5MnTNXDgKA0YMFJFRY9/7zsaZ5ueGt5TE884UM+f1UtXHdpZknTuvjtr8rkHa97lR2rHJjUXFtx05G6afO7BevbMA7VP2xYpa6vk4TXx0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpYMGbA8ycpKcSCQ0btz9Gj9+rIqL79WECZM1Z86873XHukTQ6f95T8c+Ml3HPjJdR3beST0LWmral8t1xn/e0/zla2ts33fXnbTrDs3U56E3df2kWbqlX2FKuip5eE08NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClw0ODlw4PDV46PDR46aDBL7MsNxcPfFSk2YwZs9W5c3t16lSg3NxGGjSojyZNmvq971hdsVGSlJNlyskyhSB9uGilvlix7lvbHtM1T//+uFSS9E7pCrVqnKN2zXJT1ubhNfHQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClgwZsL2KdJJvZnmZ2tJm1qHX7sakct6ysXAUFbaqu5+fnqaysPJVDuujIMumZMw7UOxf11qvzlurdshWb3LagRWN9ufKbyXPpynUqaJG6SbKH18RDg5cODw1eOjw0eOnw0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDhr8ivvoMUeSI2Z2maQnJf1E0gdmdlK1u2+Np+r7bWOQjntkug558HXtl99K3fKaxZ0EAAAAAK7EOVW/SNKBIYQhko6S9Aszuzy6zzb1IDMbaWbTzGxaUdFj9Ro4Pz9PpaWLq66XlZUrPz+vXs+1LeLqWL4+ode/WKajOu+0yW1KV65T+xaNq64XtGis0pXrU9bk4TXx0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpYMGbC/inCRnhRBWSlIIoUTJifJxZnanNjNJDiEUhRB6hRB6jRw5vF4D9+hRqJKShZo/v1Tr11eouHiy+vU7uF7PtS3S2bFT00ZqlZstSWqcnaUf7LKjPl26epPbPze3XEP3KpAk9SxoqRXrNuir1ambJHt4TTw0eOnw0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjpoMEvU5abiwc5W94kZcrMbP8QwruSFEJYaWaDJf1JUo9UDpyTk63Ro0dpxIgxSiQ2aujQ/ios7JzKIWPvaNc8V3cO2EPZWckfvwmzF2nSZ0t0/n4dNOrATmrbPFf/O7OXXihZousmzdILJUvUd9ed9Mq5B2vNhoR++twnKemq5OE18dDgpcNDg5cODw1eOjw0eOnw0OClw0ODlw4PDV46PDR46fDQ4KWDBmwvLIQQz8BmHSVtCCGU1nHf4SGE17b8LLPiiXdol7u/jDtB8y5vH3cCAAAAkEbdNrkCdnvStedv3Myr5r7z09j3aWxHkkMIX2zmvu8wQQYAAAAAbDMnZ5X2gr0BAAAAAECESTIAAAAAAJE4T9wFAAAAAIiZsdy6BvYGAAAAAAARjiQDAAAAQAYzi/2E0q5wJBkAAAAAgAiTZAAAAAAAIiy3BgAAAIAMZhw7rYG9AQAAAABAhCPJ3xPzLm8fd4IGTFwUd4Ik6blj28adAAAAAGA7xSQZAAAAADIYn5NcE3sDAAAAAIAIk2QAAAAAACIstwYAAACATGYWd4ErHEkGAAAAACDCkWQAAAAAyGQcOq2B3QEAAAAAQIRJMgAAAAAAEZZbAwAAAEAm48RdNWTskeTJk6dr4MBRGjBgpIqKHs/ojnQ2tG2SqzsO2kfjj+ipBw7vqZM7t69x/6m77qznjj1crRrV/P1Nt1YtNPGY3vpBfl5K+zy8Hl46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cODw0eOm644W4ddthZGjz4krSPXV3c+wH+ZeQkOZFIaNy4+zV+/FgVF9+rCRMma86ceRnZke6GRAj64yefacSr7+iyN2boxF3aa5fmTSUlJ9AHttlBZWvW1nhMlqQRe3TW9PKlKeuSfLweXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClw0ODlw4PDV46TjnlaI0fPzatY9bmYT/Av4ycJM+YMVudO7dXp04Fys1tpEGD+mjSpKkZ2ZHuhiXrKjRn+SpJ0ppEQvNWrlabJrmSpFF7dtEDn5Qo1HrMSZ3b69Wyci1bX5GyLsnH6+Glw0ODlw4PDV46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpeOgg/ZR69Yt0zpmbR72g0tmfi4OxDpJNrODzeyg6OvuZnaVmR2f6nHLyspVUNCm6np+fp7KyspTPazLjjgb8ps21u6tWmjmspU6rN1OKl+7XnNXrK6xTV7jXB2Rn6f/zitNeY+H18NLh4cGLx0eGrx0eGjw0uGhwUuHhwYvHR4avHR4aPDS4aHBU0fc2A/4LmI7cZeZjZF0nKQcM3tO0iGSXpR0vZn1DCHcElcbUq9JdpZG77+n7ps5V4kQ9MOuHXX9tA+/td2P9+qi8XUcXQYAAACAVIjz7NanStpfUmNJpZI6hhCWm9lvJE2VVOck2cxGShopSX/84ziNHDl8qwfOz89TaeniqutlZeXKT/EJobx2xNGQbaYxPffUC18u0qtlS7Rri2YqaNpYfzx8f0lS28aNdV/v/XXp6++psFUL3bj/HpKk1o0a6aA2OyoRgqZ8taTBuzy8Hl46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cODw2eOuLGftiEjHwT7qbFuTs2hBASIYTVkj4NISyXpBDCGkkbN/WgEEJRCKFXCKFXfSbIktSjR6FKShZq/vxSrV9foeLiyerX7+B6Pde28NARR8PV++yueSvX6N8lCyVJJStX67QX39LZL0/X2S9P16J163TxlHe1dH2Fzpk8ver2V8oW6/cfzU3JBFny8Xp46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cODw1eOjw0eOqIG/sB30WcR5LXm1mzaJJ8YOWNZtZam5kkN4ScnGyNHj1KI0aMUSKxUUOH9ldhYedUDum2I90Ne+/QUgM6tNPcFat0f+/9JEl/mjVPby5O7ZmrvwsPr4eXDg8NXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClw0ODl46rrrpDb775vpYuXa4+fc7TT35yhoYNOyatDR72A/yzEOJ5t6eZNQ4hrKvj9jaS2ocQ3t/ys8ziraqODKMcJOQAACAASURBVJi4KO4ESdJzx7aNOwEAAAAZoZuP0zFvo8If/NHNvGr2Kz+KfZ/GdiS5rglydPtiSYvrug8AAAAAgFSKc7k1AAAAACBusR+79YXzmAEAAAAAEGGSDAAAAABAhOXWAAAAAJDJslhvXR1HkgEAAAAAiDBJBgAAAAAgwnJrAAAAAMhkxnLr6jiSDAAAAABAhEkyAAAAAAARllujwTx3bNu4EyRJTXcZE3eC1sy7Ke4EAMB2LCjEnSATyy+BjMFf9xo4kgwAAAAAQIQjyQAAAACQyfic5Bo4kgwAAAAAQIRJMgAAAAAAEZZbAwAAAEAm43OSa+BIMgAAAAAAESbJAAAAAABEWG4NAAAAAJmM1dY1cCQZAAAAAIAIk2QAAAAAACIZO0mePHm6Bg4cpQEDRqqo6PGM7vDQEEdHVpbp9adv07//fI0k6cjee2tK8a2a9tzteuDOi5Wdnfzr8YND91LpBw/qjWdu0xvP3KYbLj8l5W0eXhMPDV46PDR46fDQ4KXDQ4OXDg8NXjo8NKxbt17DTr1aJ514mQYPukT33PNILB0e9oWXDg8NXjpocCrL/FwcyMhJciKR0Lhx92v8+LEqLr5XEyZM1pw58zKyw0NDXB2XXnCcPpmzQJJkZhp/58U659J71GvAtZr3xSKddWqfqm1fe2umDj3uBh163A267e7/pLTLw2viocFLh4cGLx0eGrx0eGjw0uGhwUuHhwZJys1tpL88dLOefOoe/b8n7tarr7ytd9+dmdYGL/vCQ4eHBi8dNGB7kZGT5BkzZqtz5/bq1KlAubmNNGhQH02aNDUjOzw0xNHRoWAnHXt0T/350RclSXk7ttD6ig2a81mpJOmFV9/XkOMOTtn4m+PhNfHQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5T8xW/z5k0lSRs2JLRhwwZZmj8D1cu+8NDhocFLBw2OmaOLA64myWb213SMU1ZWroKCNlXX8/PzVFZWno6h3XV4aIij446x5+hntz6ijRs3SpIWL1mhnOwsHbBvV0nSyccfoo4751Vtf8gBhZo68Vd64qHrtFe3jinrkny8Jh4avHR4aPDS4aHBS4eHBi8dHhq8dHhoqJRIJDTkpMt1eO+z1bv3/tpvvz3SOr6XfeGhw0ODlw4asL2I7SOgzOyp2jdJ6mtmO0hSCOHE9FchExx3dE99tXi53nn/M/3g0L2qbj/n0t/r9tFnq3Fujp6f/L4SieQE+t0PSrTHYT/RqtXrNLDv/vrnA1epx5FXxZUPAMAWZWdn64kn79by5St16SW3adasz9WtW+e4swCgwZhZtqRpkhaEEAabWRdJj0rKkzRd0tkhhPVm1ljSXyUdKKlc0vAQQsnmnjvOI8kdJS2XdKek30aXFdW+rpOZjTSzaWY2rajosXoNnJ+fp9LSxVXXy8rKlZ+ft5lHpIaHDg8N6e44rNceGjzgAM187R799f8u01G999affneJpr49W/1PvUk/OPEXenXqx1VLr1esXKNVq9dJkp598V01yslR3o4tU9Im+XhNPDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NBQW6tWLXTIIT30yitvp3VcL/vCQ4eHBi8dNPgVzNxctsLlkj6udv3Xku4KIewuaamkC6PbL5S0NLr9rmi7zYpzktxLyRn+zyR9HUJ4SdKaEMLLIYSXN/WgEEJRCKFXCKHXyJHD6zVwjx6FKilZqPnzS7V+fYWKiyerX7/0v//UQ4eHhnR3jP71o9r9kEu15+GX6ZxL79FLUz7UBVfcq7Z5rSRJubk5uvrHJ+qBh5+XJOW3bV312F777aasLFP50hUpaZN8vCYeGrx0eGjw0uGhwUuHhwYvHR4avHR4aJCkJUu+1vLlKyVJa9eu05Qp76pr19S+Vag2L/vCQ4eHBi8dNKChmFlHSYMkjY+um6R+kv4VbfKQpCHR1ydF1xXdf7Rt4UQNsS23DiFslHSXmT0e/VmWrp6cnGyNHj1KI0aMUSKxUUOH9ldhYfqXIHno8NDgpePKHw3WcUcfoKws0wMPP6+Xp3woKfn+5IvOHqANGxJau3a9zrn0npR2eNgXHhq8dHho8NLhocFLh4cGLx0eGrx0eGiQpEVfLdH11/9OicRGhRB07LFHqG/fg9La4GVfeOjw0OClgwY0oN9JulZS5fLOPEnLQggboutfSOoQfd1B0nxJCiFsMLOvo+2/WVJQi4UQUhG91cxskKTDQwg3fvdHzfIRD1ea7jIm7gStmXdT3AkAgO1YUPz/i2NeTjMLuNbte/EXZffBf4n/PzqRT4vP/5GkkdVuKgohFFVeMbPBko4PIfzYzI6S9FNJ50l6I1pSLTPrJOmZEMI+ZvaBpGNDCF9E930q6ZAQwiYnybEdSa4thFAsqTjuDgAAAABAPKIJcdFmNjlc0olmdrykJpJaSbpb0g5mlhMdTe4oaUG0/QJJnSR9YWY5kloreQKvTXL1EVAAAAAAAGxKCOGGEELHEMKukk6X9EII4UxJL0o6NdrsXElPRl8/FV1XdP8LYQvLqZkkAwAAAEAmM0eX+rtO0lVmNkfJ9xw/GN3+oKS86ParJF2/pSdys9waAAAAAIDvKvqEpJeir+dK+tapykMIayUN25rnZZIMAAAAAJls6z6f+HuP5dYAAAAAAESYJAMAAAAAEGG5NQAAAABksiyWW1fHkWQAAAAAACJMkgEAAAAAiLDc+nti/cYVcScoN6tl3AmSpDXzboo7Qae/WBp3giTp0b4FcScAAOrBtvHDQgFgq/CfnBo4kgwAAAAAQIRJMgAAAAAAEZZbAwAAAEAmM9ZbV8eRZAAAAAAAIhxJBgAAAIBMxpHkGjiSDAAAAABAhEkyAAAAAAARllsDAAAAQCbj0GkN7A4AAAAAACIZO0mePHm6Bg4cpQEDRqqo6PGM6ij9slwXnHuzThp8jYYMvkYP//UZSdKzE9/QkMHXaN/uZ+rDD+ampaU6D69JOhvWL1mi2Xf+Rh+PHa2PbxqtryY9L0la8O/H9dGYX+jjX47V3Pvu1YbVq6ses+aLL/TJr2/TxzeN1sfjxmpjRUXK+jy8Hl46PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NDgpcNDg5cOGrA9yMhJciKR0Lhx92v8+LEqLr5XEyZM1pw58zKmIzs7Sz+99kw9OeEO/f2xcXr0kef06ZwvVFjYSXf9/kod2GvPlDfU5uE1SXeDZWepw6nDtNfYcep23Y1a/PKLWrNwoVru1V17jR6rvX4xVo3z81U28WlJUkgkVPLn8ep05lnaa8w4FV71U1l2dkraPLweXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClw0ODlw4aHDPzc3EgIyfJM2bMVufO7dWpU4Fycxtp0KA+mjRpasZ0tG23o7rv3UWS1Lx5U3XZrYPKypaq624d1KXLzikfvy4eXpN0NzRqvYOa7dJZkpTdpImaFLRXxbJlatV976rJb/MuXVWxdKkkaflHH6lph45q1rGTJCmnRQtZVmr+Cnt4Pbx0eGjw0uGhwUuHhwYvHR4avHR4aPDS4aHBS4eHBi8dNGB74WaSbGZHmNlVZnZMqscqKytXQUGbquv5+XkqKytP9bAuOxYsWKSZH5do3/12S+u4tXnYF3E2rFu8WKvnz1fzLl1q3F4+5TW12qdHcpuvyiQzzbnnLs285Zcqe3Ziyno8vB5eOjw0eOnw0OClw0ODlw4PDV46PDR46fDQ4KXDQ4OXDhqwvYhtkmxmb1b7+iJJ/yeppaQxZnZ9XF2ZZPWqtbrysrt03fVnq0WLZnHnZKzE2rX6rOg+dTxtuLKbNq26vfTpYllWlnY8+BBJyeXWq+bM1q4XjFC3a67Vsnff0YqZH8eVDQAAgO8Lc3RxIM4jyY2qfT1S0oAQwk2SjpF05qYeZGYjzWyamU0rKnqsXgPn5+eptHRx1fWysnLl5+fV67m2RZwdFRUbdOXld2nQCYer/zEHp2XMzfHwmsTREBIb9FnRfdrp4EO0Q88Dqm4vn/Kavn5/hna9cIQsem9G7o47qkVhN+W0aKms3MZqvU8PrZ6XmvfQeHg9vHR4aPDS4aHBS4eHBi8dHhq8dHho8NLhocFLh4cGLx00YHsR5yQ5y8x2NLM8SRZCWCRJIYRVkjZs6kEhhKIQQq8QQq+RI4fXa+AePQpVUrJQ8+eXav36ChUXT1a/fumfKMbVEULQmJ8XqWvXDjr3vEEpH++78PCapLshhKDP//qQmhS0V7v+37zLYPmHH+ir/z2rrj++VFm5jatub9l9b61ZsEAb169TSCS0YvYsNWnfPiVtHl4PLx0eGrx0eGjw0uGhwUuHhwYvHR4avHR4aPDS4aHBSwcNfoUsc3PxICfGsVtLmq7kQfVgZu1DCF+aWQul+EB7Tk62Ro8epREjxiiR2KihQ/ursLBzKod01fHO25/ov0+9qsJunXTqyTdIki674jRVrN+gW295SEuXLNePR92uPffsrD+OvyHlPZKP1yTdDas+naOlU99Qkw4dNPPmmyRJ7U86RV/88x8KGzbo07vvlCQ169JVu5x5tnKaN1e7/gP0yW23SGZqtXcPte6xb0raPLweXjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0OClw0ODlw4asL2wEELcDTWYWTNJ+SGEz7a89Sxf8TFav3FF3AnKzWoZd4Ibp79YGneCJOnRvgVxJwAAAHyPdfNx6HMb7fbDR9zMqz79xxmx79M4jyTXKYSwWtJ3mCADAAAAALaZk88n9sLNR0ABAAAAABA3JskAAAAAAETcLbcGAAAAAKQRq61r4EgyAAAAAAARJskAAAAAAERYbg0AAAAAmSyL9dbVcSQZAAAAAIAIk2QAAAAAACIstwYAAACATGYst66OSfL3RG5Wy7gTUM2jfQviTpAk7X5/adwJ+vCipnEnSJIaZ7eOOwHAFlRsXB13ghplNYs7wY2NoSLuBElSljWKOwFAhmGSDAAAAACZjAPJNfCeZAAAAAAAIkySAQAAAACIsNwaAAAAADIZn5NcA0eSAQAAAACIMEkGAAAAACDCcmsAAAAAyGQst66BI8kAAAAAAESYJAMAAAAAEGG5NQAAAABksMBq6xoy9kjy5MnTNXDgKA0YMFJFRY9ndIeHBi8dHhrS2dG+eWM9fMK+mnjagXrmtAN1bo+dJUl75jXX40P2V/GwA1V07N5q0ShbkpSTZbq97x4qHnagJg7vpVE9OzV4U+mX5brwvFs0ZPC1OvmE6/Tw3yZKkv7wf/9W/6N+omEn36hhJ9+oV15+t8HH3pRM+7nw3uClw0ODl464Gn7+s/vU5/CLNOSEq2vc/veHn9EJx1+pkwZfrd/e8XDaeiQfr4eXjr/+dYJOOOFyDR58uR566L+xNEg+9oWHBi8dNGB7kJFHkhOJhMaNu19//vMvlZ+fp1NPvUr9+h2i3XffJeM6PDR46fDQkO6ODSHottfn6sPFK9W8UbaeGNpTr32xTLce2U2/en2u3vzya526R75G7N9Rv3vrcx3XtY1ys02DHp+uJjlZmji8l/475ystWLGuwZqyc7J09bVnqHv3Llq1ao1OP/UXOuywHpKks845VuddMKjBxvouMvHnwnODlw4PDV464mwYMuRInXHGQN14/b1Vt7059QO9OGma/v3E7crNbaTy8q9T3lHJw+vhpWPWrM/1+OPP6Z//vF2NGuXooot+qaOO6qXOndunrUHysS88NHjpoMExTtxVQ0YeSZ4xY7Y6d26vTp0KlJvbSIMG9dGkSVMzssNDg5cODw3p7li0er0+XLxSkrSqIqFPl65WfvNcdWndVG9+mfwfy9e+WKZju7SRJAVJzXKylW1Sk+wsVSQ2auX6RIM2tW27o7p37yJJat68qbp03VlffbWkQcfYGpn4c+G5wUuHhwYvHXE29Dqou1rv0KLGbY89+pwuvOgk5eY2kiTl5bVOS4vk4/Xw0jF37gLtu283NW3aWDk52TrooO567rk30tog+dgXHhq8dNCA7UVsk2QzO8TMWkVfNzWzm8zsv2b2azNL6b9oZWXlKihoU3U9Pz9PZWXlqRzSbYeHBi8dHhri7OjQsrG6t2mh98pWaPbSVeq/a54k6bjd2qigRWNJ0sS5i7V6Q0Kvn3OoJp91iMa/94W+XrchZU0LFizSzI8/V499d5MkPfrIcxo65AaN/lmRln+9KmXjVpfpPxfeGrx0eGjw0uGhobqSki81ffpM/XD4z3Te2WP1/vtz0ja2l33hoaOwcBdNn/aRli5doTVr1mnyy2+r9MvFaW2QfOwLDw1eOmjA9iLOI8l/krQ6+vpuSa0l/Tq67c9xRQGZqFlOlu49prtunvKpVlYkdP1Ls3TW3jvriaE91bxRtio2BknSvu1aKhGk3n+bqqP+/qYu3K+jOrVskpKm1avW6qrL79a1N5ylFi2aafjp/VX87J16/D+3qE3bHfSb2/+eknEBbN8SGxJa/vVKPfLozbr6mrP00yt/pxBC3FkZZ7fdOmrERSdrxIU36aKLfqk99+qirOyMXMAIbB/M/FwciPO/VlkhhMpDUL1CCFeEEF4NIdwkqeumHmRmI81smplNKyp6rF4D5+fnqbT0m99mlpWVKz8/r17PtS08dHho8NLhoSGOjpws070Du+up2V/pf58lf5M6d9kanVf8vob8+x39d84izVu+RpJ04u7t9Mq8JdqwMWjJ2gpNL12uHu1abO7p66WiYoOuuuJuDRrcW/0HHCRJymvTWtnZWcrKytLQYX31/vtzG3zcumTqz4XXBi8dHhq8dHhoqNFTkKf+Aw6WmanHvrvLsrK0dOmK9IztZF946Tj11P76939+o4cfvlmtWzXXrrvunPYGD/vCQ4OXDhqwvYhzkvyBmZ0fff2emfWSJDPrJqliUw8KIRSFEHqFEHqNHDm8XgP36FGokpKFmj+/VOvXV6i4eLL69Tu4Xs+1LTx0eGjw0uGhIY6O247spjlLV+tPMxZU3bZTk+R7+UzSJQfson98+KUkaeHKtTq0ww6SpKY5WerZrqU+XbqmQXtCCBrzi/Hq0nVnnXPe8VW3L1q0tOrrF56fpsLCjg067qZk6s+F1wYvHR4avHR4aKiu39EH6c2pH0mSSj5bqIqKDdpxx5ZpGdvLvvDSUV6+TJK0cOEiPffcVA0e3CftDR72hYcGLx00YHsR59mtR0i628x+LmmxpNfNbL6k+dF9KZOTk63Ro0dpxIgxSiQ2aujQ/ios7JzKId12eGjw0uGhId0dBxa00sl75Gtm+Uo9deoBkqTfvvmZdm3dVGftnfyN//8+W6x/fVImSXr4g4X6dd899MxpB8ok/euTMn2ypGHfG/zO27M04alXVditk4adfKMk6bIrTtMzT7+umTM/l5lp5w5tNHrsBQ067qZk4s+F5wYvHR4avHTE2XDN1XfrrTc/0rJlK3T0URfrx5cO0ymn9NXPf36fhpxwtRo1ytGtt/1Ylqblex5eD08dl192h5YtW6GcnGz9YvRFatWqedobPOwLDw1eOmhwjLNb12Bxv08nOnlXFyUn7F+EEMq++6Nn8SYjYDN2v7807gR9eFHTuBMkSY2z03eGWwD1U7Fx9ZY3SrFGWc3iTnBjY9jkwr60yrJGcScAm9HtezG77Hrxf9zMq+bed0rs+zT2z0kOISyX9F7cHQAAAAAAxD5JBgAAAADEiJPP18DuAAAAAAAgwpFkAAAAAMhkTj6f2AuOJAMAAAAAEGGSDAAAAABAhOXWAAAAAJDJ+JzkGjiSDAAAAABAhEkyAAAAAAARllsDAAAAQAYLnN26BibJwPfYhxc1jTtB+wx8L+4ESdLs5/vEnQBgCxplNYs7AdVkWaO4EwAgFiy3BgAAAAAgwpFkAAAAAMhkHDqtgd0BAAAAAECEI8kAAAAAkMn4nOQaOJIMAAAAAECESTIAAAAAABGWWwMAAABAJuNzkmvgSDIAAAAAABEmyQAAAAAARDJ2kjx58nQNHDhKAwaMVFHR4xnd4aHBS4eHhrg6Sr8s14Xn3aIhg6/VySdcp4f/NrHG/Q/9+Wnt2/0sLV26IiXjZ2WZnrx/iIpuPkaSdNZJ3fX8Q8M0+/kR2rFV46rtunZqrX/ec4I+fPp8XTisR0paasvknwuPDV46PDR46fDQ4KXDQ4OXDg8NN9xwtw477CwNHnxJLONX8rAvvHTQ4FSW+bk4kJGT5EQioXHj7tf48WNVXHyvJkyYrDlz5mVkh4cGLx0eGuLsyM7J0tXXnqEnJtyuhx8dq8ceeV6fzlkgKTmBfn3K+2rfPi9l45978t76dN6yqutvf1imc699Rl+U1pyUL1uxTr+893WNf/z9lLVUl+k/F94avHR4aPDS4aHBS4eHBi8dHhok6ZRTjtb48WPTPm51XvaFhw4asL3IyEnyjBmz1blze3XqVKDc3EYaNKiPJk2ampEdHhq8dHhoiLOjbdsd1b17F0lS8+ZN1aXrzvrqqyWSpNt//bCuvPp0WYpO6lDQppmOOqST/vn0J1W3fTSnXAvKVn5r2yXL1ur9TxZrQ2JjSlpqy/SfC28NXjo8NHjp8NDgpcNDg5cODw2SdNBB+6h165ZpH7c6L/vCQwcN2F7ENkk2s8vMrFMcY5eVlaugoE3V9fz8PJWVlWdkh4cGLx0eGrx0LFiwSDM//lw99t1NL06arnbtdtQee3ZO2Xg/+/Fhuv2BN7UxpGyIevPwenjp8NDgpcNDg5cODw1eOjw0eOnw0OCFl33hoYMGx8zRxYE4jyT/UtJUM3vFzH5sZm1jbAEQWb1qra66/G5de8NZys7O1gNFT+mSn5yasvH6HtJJ5cvW6MPZ/AMFAACA+MU5SZ4rqaOSk+UDJX1kZhPN7Fwz2+S6GDMbaWbTzGxaUdFj9Ro4Pz9PpaWLq66XlZUrPz9177X03OGhwUuHh4a4OyoqNuiqK+7WoMG91X/AQZo//ystWLBIw06+Ucf2v0JlZUs0fOjPtXjRsi0/2Xd0wD75Ovqwznrx4eH63c/66tD9d9Zvrj+qwZ5/W/Fz4avBS4eHBi8dHhq8dHho8NLhocELL/vCQwcNfoUsc3PxIM5JcgghbAwh/C+EcKGknSX9QdKxSk6gN/WgohBCrxBCr5Ejh9dr4B49ClVSslDz55dq/foKFRdPVr9+B9frubaFhw4PDV46PDTE2RFC0JhfjFeXrjvrnPOOlyR169ZJL7/6B018/nea+PzvlJ+/kx77981q03aHBhv3tw9O0w9++A/1PesxXXHLi3rj3YX66a9earDn31aZ/nPhrcFLh4cGLx0eGrx0eGjw0uGhwQsv+8JDBw3YXuTEOHaNXxOEECokPSXpKTNrlsqBc3KyNXr0KI0YMUaJxEYNHdpfhYWpe7+l5w4PDV46PDTE2fHO27M04alXVditk4adfKMk6bIrTtMPjtw/5WPX5Zwhe+ui4fuqzU5N9d+iU/Tym1/oZ3e+ojY7NtX/+8MQtWjWSBtD0Hmn7KPjLvyXVq6uSElHpv9ceGvw0uGhwUuHhwYvHR4avHR4aJCkq666Q2+++b6WLl2uPn3O009+coaGDTsmrQ1e9oWHDhqwvbAQ4jlTjpl1CyHM2rZnmeXwND+AH+sSX8edoH0Gvhd3giRp9vN94k4AAADfO918rA/eRrv+7Gk386qSW46PfZ/Gttx62yfIAAAAAAA0rIz8nGQAAAAAAOoS53uSAQAAAABxs9hXOLvCkWQAAAAAACJMkgEAAAAAiLDcGgAAAAAyGYdOa2B3AAAAAAAQ4UgyAAAAAGQyTtxVA0eSAQAAAACIMEkGAAAAACDCcmsgBYIScSdIkhpnt447QbOf7xN3giRp4LNfxZ2gZwe2izsBwBas37gi7gRJUm5Wy7gTANf8/F2Nu6CBZLHcurrvy8sKAAAAAMA2Y5IMAAAAAECE5dYAAAAAkMlYbl0DR5IBAAAAAIgwSQYAAAAAIMJyawAAAADIYMFYbl0dR5IBAAAAAIgwSQYAAAAAIMJyawAAAADIZBw6rSFjd8fkydM1cOAoDRgwUkVFj2d0h4cGLx0eGiolEgmdPORK/ehHN8cyvpd9ka6Otk1ydftB+6jo8ANUdHhPDdll5xr3D+3cQc8OPEKtGiV/t9i3fVvd17un7u/dU3cdvK+6tmyesrZKHl4TDw1eOjw0eOnw0BBXR+mX5brg3Jt10uBrNGTwNXr4r89Ikp6d+IaGDL5G+3Y/Ux9+MDctLdV5eE1uuOFuHXbYWRo8+JJYxq/kYV94aPDS4env6dfLVuqiC27VoIFX6qILbtXXX69MSw/8y8hJciKR0Lhx92v8+LEqLr5XEyZM1pw58zKyw0ODlw4PDdX99a8T1HW3jrGM7WVfpLMjsTGoaOZnGvna27r8jRk6YZf22qV5U0nJCfQBbXZQ2Zq1VduXrVmra96coVFT3tHf587X5d13T0lXVZ+D18RDg5cODw1eOjw0xNmRnZ2ln157pp6ccIf+/tg4PfrIc/p0zhcqLOyku35/pQ7stWfKG2rz8pqccsrRGj9+bNrHrc7DvvDQ4KXD29/TBx94Soccto+Kn71Lhxy2jx584L8pb3HLzM/FgYycJM+YMVudO7dXp04Fys1tpEGD+mjSpKkZ2eGhwUuHh4ZKpaWL9fJL0zTs1AGxjO9lX6SzY8n6Cs1ZsUqStCaR0PxVq9WmSWNJ0o/26KoHZ5UoVNv+o2UrtHJDQpI0c9lytWmSm5KuSh5eEw8NXjo8NHjp8NAQZ0fbdjuq+95dJEnNmzdVl906qKxsqbru1kFduuy8hUenhpfX5KCD9lHr1i3TPm51HvaFhwYvHd7+nr74wnSddNIPJEknnfQDvThpWspbsH3IyElyWVm5CgraVF3Pz89TWVl5RnZ4aPDS4aGh0q23PqifXnOuLCue36Z52RdxdeQ3SLg9gwAAIABJREFUaazdWjbXzGUrdFjbnbR43XrNjSbQdTm2Y4HeWrw0pU0eXhMPDV46PDR46fDQ4KVjwYJFmvlxifbdb7e0jlubh33hhYd94aHBS4eHhup/T8vLv1bbdjtKktq03UHl5V+ntQV+xTZJNrNcMzvHzPpH188ws/8zs0vMrFFcXUDcXnzxLeXt1Fr77JPa5buoW5PsLP1i/710/8zPlAhBp3ftpL/O+XyT2++3U2sN7JCvB2eVpC8SgDurV63VlZfdpeuuP1stWjSLOwdAHTb399TMJB8rfeORZX4uDsR5JPnPkgZJutzM/iZpmKSpkg6SNH5TDzKzkWY2zcymFRU9Vq+B8/PzVFq6uOp6WVm58vPz6vVc28JDh4cGLx0eGiTp7bdn6oUX3lK/fhfp6qt+q6lvzNA1P70rrQ1e9kW6O7LN9Iv999ILX36l174qV/tmTVTQtLHu691TD/XppbaNG+vew/bXjrnJ3+N1adFMV+y9u8a+85FWVGxIWZfk4zXx0OClw0ODlw4PDXF3VFRs0JWX36VBJxyu/sccnJYxN8fLa+KBh33hocFLh7e/p3l5rbXoq+RKsEVfLVXeTq3T0gL/4pwk9wghDJd0sqRjJJ0aQvibpPMl9dzUg0IIRSGEXiGEXiNHDq/fwD0KVVKyUPPnl2r9+goVF09Wv37p/0fNQ4eHBi8dHhok6eqrz9bLkx/UCy88oN/eebUOOXRf3fGbK9Pa4GVfpLvjqr0LNX/Vav3n84WSpJKVqzX8pTd17uRpOnfyNC1at06XvP6ulq6vUNsmjTW651664/1ZWrB67Raeedt5eE08NHjp8NDgpcNDQ5wdIQSN+XmRunbtoHPPG5Ty8b4LL6+JBx72hYcGLx3e/p4e1e8APfnkK5KkJ598RX37HZjyFmwf4vyc5Cwzy5XUXFIzSa0lLZHUWFJKl1vn5GRr9OhRGjFijBKJjRo6tL8KCzuncki3HR4avHR4aPDCy75IZ8feO7RS/w7tNHfF/2fvzsOjKs8+jn/vBILsS4AEY0SWIKKAtrgvKIJUEUHBpVq1KFK1FQW1btQFBXdptW4Ra/W11qVVUXCpIgjUBcEFF1RQUWSJEFbZsj3vH5mkCRKSkMycG/P7XNdcZuZM5vl6zpDJk3PmzAbuO3hfAB5Z8G2F7zU+o1MmTevX5w97Fb/3sDAELnrno7i0gY9t4qHBS4eHBi8dHhqi7Pjg/S948YVZZHXJZOiJVwEw8pJTyM8rYPy4R1m9ah0Xnn8bXbu258GJV8W9B/xsk9Gjb2f27I9ZvXodRxzxWy666HROPvmYhDZ4WBceGrx0ePt3eu7wE7hs9N08969ptNu1NXdOuDjuLW45OczZCwshVH6veAxsNgq4CEgG7gQGAV8DBwH/CiHcUPmjfBlNvEglAoVRJwBgJEed4Eb/V3+IOoFX+7eNOkFEKpFXtD7qBABSkqI9K7SId37+rf7yZzG7bH/7G27mVd9e3ifydRrZnuQQwgQzeyr29VIzewzoCzwUQpgdVZeIiIiIiIjUXVEebk0IYWmZr9cA/4owR0REREREpO6JfN+tL3Xyc5JFREREREREtiXSPckiIiIiIiISraATd5WjPckiIiIiIiIiMZoki4iIiIiIiMTocGsREREREZG6zHS4dVnakywiIiIiIiISo0myiIiIiIiISIwOtxYREREREanLdHbrcrQnWURERERERCRGe5JF4iCEEHUCoHMwlPViv4ZRJ3D4Cz9EnQDAzBPaRp0g4lay1Y86QbaysSAn6gQa1UuLOkG2kpLUNOoE+RnTJFlERERERKQu046VcnS4tYiIiIiIiEiM9iSLiIiIiIjUYUnadVqOVoeIiIiIiIhIjCbJIiIiIiIiIjE63FpERERERKQO0yeilKc9ySIiIiIiIiIxmiSLiIiIiIiIxOhwaxERERERkTpMh1uXV2f3JM+YMZf+/c+nX78RZGc/U6c7PDR46fDQALBu3QYuHnkbxx37BwYc9wc++ODzhDd4WRdRdCxflss5Z9/EoOMvZ/Dxl/P4Yy8D8Oor7zD4+Mvp0e0MPv3k61oft+0uKfzlkH34v6N+wWNH7sfQDrsCMGzP3Xm23/78rfe+/K33vhzUtiUA/TLalN72t9778ubAQ+ncrHGtd5VVl58XHhu8dHhoiKrjmqvv47BDzuWEgaNLb7v9tscYcOzFDD7hUi76w22sW7chIS1ledgmUTRs2ZLPb069iVNOvJ4hJ1zL/X+dBMC1V/+NAcdcyakn3cCpJ93AF/O/S0hPCQ/bw0uHGqSmzGwXM5ttZh+Z2admdkPs9g5m9q6ZLTSzp8wsJXZ7g9j1hbHle1Q2Rp3ck1xYWMjYsQ/wyCM3kpaWytCho+nT50A6d969znV4aPDS4aGhxPhxEzns8P34y91/JC8vn82b8xI6vpd1EVVHcnISl/3xDLrt3YENGzZx6pBrOPiQ7mRlZTLhnlGMve7huIxbGAL3fvoNX67dQMPkZB7uvS9zVqwG4Omvl/LkV0vK3f+1JSt4bckKADo2bcT4A/ZiYRx/Ga/rzwtvDV46PDRE2XHiiUdyxhm/4sor/1p62yGH9GTU6DOoVy+ZO+94nIeyn+PSy34T146yPGyTqBpSUuqR/bfLaNR4F/LzCzjnzFs59PB9ALjk0qH0698rruNvi4ft4aVDDVJLtgB9Qgg/mll9YJaZvQyMBiaEEJ40sweAc4H7Y/9dHULobGanAbcCp25vgMj2JJtZczO7xcw+N7NVZpZrZvNjt7WI59jz5i2gfft2ZGamk5JSnwEDjmDq1HfjOaTbDg8NXjo8NACsX7+BOXM+Y+jQvgCkpNSnWZz3Dm7Ny7qIqqNN25Z027sDAI0bN6RDpwxyclbTsVMGHWJ7d+Mhd0s+X64tnuRuKixk0fqNtG7YoErf2zejDVOXrIxbG+h54a3BS4eHhig7eu3fjebNm5S77dDDelKvXjIAPXtmsXx5btw7yvKwTaJqMDMaNd4FgIKCQgoKCrGIjyP1sD28dKjBLzNzc6lMKPZj7Gr92CUAfYB/xW5/FBgc+3pQ7Dqx5UdbJQNFebj108Bq4MgQQqsQQipwVOy2p+M5cE5OLunprUuvp6WlkpOT2BcwLx0eGrx0eGgA+P77H2jVqhlXX3UPJ504mjFj7mXjxs0JbfCyLjx0LFmygs/nL6JHz04JHTe9YQO6NG/MZ6vXA3BSh3b8/cj9uHLfLJrUT/7J/ftktOb12F7lePGwPbx0eGjw0uGhwVPH1p799zQOP2K/hI7pYV1E2VBYWMSpJ93A0YeP5qCDu9G9R0cA7r37OU458TruuOVJ8vLyE9ICPraHlw41SG0xs2Qz+xD4AXgN+ApYE0IoiN3leyAj9nUGsBggtnwtkLq9x49ykrxHCOHWEMLykhtCCMtDCLcC7SPsEolUYUEhn332Naf9+lc8+9xdNGrYgIceejbqrDpp44bNjBo5gSuuPJMmTRolbNyGyUnctP9e3P3pN2wsKOT5Rcs47fU5DJv+Abmb8/jD3h3L3b9biyZsLizim/UbE9YoIpV74IF/k1wviYEDD486pU5JTk7iqWev49U3bueTj79h4YIlXDTqJJ6bfBOPPzWGtWs38MjEV6LOFHHFzNPFRpjZnDKXEVv3hhAKQwj7ArsBBwBda3N9RDlJ/tbM/mhmaSU3mFmamV1BbKa/LWVXWnb2Uzs0cFpaKsuX/++wxJycXNLStvvHhLjw0OGhwUuHhwaAtPRU0tJS6dmzCwDH9D+Ezz6r/ZNEbbfBy7qIsCM/v4BRF09gwMBD6XvMAQkZEyDZjJv234vXvv+BGcuK/7K9eks+RRQfR/Tit8vZq0X5QzuPzmjD1DjvRQY9L7w1eOnw0OCpo8Rzz07jzWlzue32ixN+uK+HdeGhoWmzRvQ6oCtvzfqENm1aYGakpNRn0ImH8ukn3ySsw8O68NKhBqmKEEJ2CKFXmUv2du67BpgGHAy0MLOSc27tBpSczGUJkAkQW94c2O7hA1FOkk+leDf3m7H3JK8CpgOtgJMr+qayK23EiO2+37pC3btnsWjRUhYvXk5eXj5TpsygT5/E/RLsqcNDg5cODw0Abdq0pF271nzzdfG/63fenkfnTrsltMHLuoiqI4TAdWOy6dgxg7N/OyDu45V15b5ZLFq/kae+Xlp6W2qD+qVfH9EutdweYwOO2jX+h1qDnhfeGrx0eGjw1AEwc+YHPPzwJO69/woaVvG8ArXJw7qIqmHVqvWsX1f8M3Lz5jzeffsz9uiQzooVa4Din+/Tpn5Ip87xO7/E1jxsDy8dapDaYGZtSs5hZWYNgX7AfIony0NjdzsbmBT7+oXYdWLL3wghhO2NEdnZrUMIq4ErYpdyzGwY8Ei8xq5XL5lrrz2f4cOvo7CwiCFD+pKVlfgjvD10eGjw0uGhocQ1Y87j8ssnkJ9fQGZmGuPGX5TQ8b2si6g6Pnj/C158YRZZXTIZeuJVAIy85BTy8woYP+5RVq9ax4Xn30bXru15cOJVtTZu91bN+FVmW75at4G/9d4XgOz539I3ow2dmxefvG3Zxs3c8dHC0u/pmdqcHzZtYdnGLbXWUZG6/rzw1uClw0NDlB2Xjf4zs9/7lDWr13NU79/xh4tOITv7OfLzCjj3nBsB6NmzC9ff8JOjBePGwzaJqmHlijVce/XfKCoqoqgo0K///hxxZE9GDLuD1avXE0Jgz66ZXHPtmXFvKeFhe3jpUINfO9nnJLcDHjWzZIp3+j4dQphsZp8BT5rZTcAHQMnHkTwM/J+ZLQRWAadVNoBVMomOhJl9F0KownnYv/QXLwIUlZ4zIFpJVic/5W2b8orWR53A0ZM3RZ0AwMwT2kadIOJWYUjsiRIrkmy7RJ3gxsaCnKgTaFQvrfI7SR3VZeeaXlYg68EZbuZVC353ROTrNLLfoM1sXkWLAP0kEhERERERkYSLcjdTGtCf4o98KsuAtxKfIyIiIiIiUvdYlGeqcijKSfJkoEkI4cOtF5jZ9MTniIiIiIiISF0X5Ym7zt3OstMT2SIiIiIiIiIC0e5JFhERERERkYjtZGe3jjsdfS4iIiIiIiISoz3JIiIiIiIidViS9iSXoz3JIiIiIiIiIjGaJIuIiIiIiIjE6HBrERERERGROkwn7ipPk2SROEgy/dPyJiWpadQJzDwh+gaA8/+7JOoEHjg0I+oEkW1Ktl2iTpCtNKqXFnWCiNQxOtxaREREREREJEa7u0REREREROowHW5dnvYki4iIiIiIiMRUeZJsZi3NrJuZNdjq9mFmNsnMnjCzA2o/UURERERERCQxqnO49XjgN0DbkhvM7CLgz0DJDvrBZtYrhPBZ7SWKiIiIiIhIvJiOty6nOodbHwpMDSFsKnPbZcAS4AjglNhto2upTURERERERCShqrMnOQOYWnLFzLoBmcAVIYRZsdtOpnjCLCIiIiIiIrLTqc4kuSGwucz1Q4EAvF7mtq+A42uhS0RERERERBLAdDrncqqzOpYAXctc7w+sAz4qc1tLoOzh2CIiIiIiIiI7jepMkqcBx5nZH8xsOHAC8EoIoajMfToBi2szMF5mzJhL//7n06/fCLKzn6nTHR4avHR4aPDS4aHBS4eHhkR2bF61ig9uu4t3r7med8fcwOLXit9pk//jBj6848+8c+Wf+PCOP5O/YUPx7Rs28PE99zP72huZc+PN/Pj9kri1lfCwTTw0eOnw0OClw0ODlw4PDV46PDR46VCDT2Z+Lh5UZ5J8M/Aj8Bcgm+JDr68vWWhmzYDDgLdqsS8uCgsLGTv2ASZOvJ4pU+5l8uQZLFz4XZ3s8NDgpcNDg5cODw1eOjw0JLrDkpLpfOpQDhx3Pb+85gqWvPEmG5Ys5duXXqHlXl056JYbablXV7576VUAvp3yCk12z+SAsX9ir+HDWPDPp+PSVcLDNvHQ4KXDQ4OXDg8NXjo8NHjp8NDgpUMNsrOo8iQ5hPANsDdwMTAS2CeE8EWZu3QGHgT+XpuB8TBv3gLat29HZmY6KSn1GTDgCKZOfbdOdnho8NLhocFLh4cGLx0eGhLd0aBFc5q23x2Aeg13oXG7dLasWcPKD+aRfujBAKQfejAr3i9+t82GpctoudeeADRul87mlbnkrV0XlzbwsU08NHjp8NDgpcNDg5cODw1eOjw0eOlQg+wsqvUW7RDC8hDCX2OX77Za9n4IYVQI4b2aRpnZyzV9jO3JycklPb116fW0tFRycnLjOaTbDg8NXjo8NHjp8NDgpcNDQ5Qdm1auZP13i2nWsQP569bRoEVzAFKaNyN/XfFEuEnmbqyY+wEA677+hi25q9iyenXcmjxsEw8NXjo8NHjp8NDgpcNDg5cODw1eOtTgV9SHWHs73Lo6Z7euVWb2i4oWAfsmskVERH6qYPNmPrk3m6xfn0K9hg3LLbMyr2Ttj+vPgiee5r3rbqLxbhk02T0TknSaTBEREdk5VThJNrNrd/AxQwjhxirc7z3gTYonxVtrsZ2uEcAIgAcfHMuIEadWOzAtLZXly1eWXs/JySUtLbXaj1NTHjo8NHjp8NDgpcNDg5cODw1RdBQVFPLJvdmkHXQAbX65HwD1mzVjy5q1NGjRnC1r1lK/aVMA6jVsyF7nng1ACIF3/ngNDdu0rvCxa8rDNvHQ4KXDQ4OXDg8NXjo8NHjp8NDgpUMNsrPY3p/6r6/BpSrmA78LIRy19QVYWdE3hRCyQwi9Qgi9dmSCDNC9exaLFi1l8eLl5OXlM2XKDPr0OWCHHqsmPHR4aPDS4aHBS4eHBi8dHhoS3RFC4PNHHqNxu3R279+39PbW+/Vg+X/fBmD5f9+m9X49AMjfuJGiggIAls2YRfMuWT/Z81ybPGwTDw1eOjw0eOnw0OClw0ODlw4PDV461OBX1IdY70yHWx8V57Gvp+JJ+kXxHLhevWSuvfZ8hg+/jsLCIoYM6UtWVvt4Dum2w0ODlw4PDV46PDR46fDQkOiOtQu+Iuftd2m8WwbvXXcTAB2HDKL9cf355P6HWDbzv+ySmsreF5wHwMaly5n/8N8Bo3FGO7oOOzMuXSU8bBMPDV46PDR46fDQ4KXDQ4OXDg8NXjrUIDsLCyFE3fATZjYshPBI5ff80l+8iIhz5/83/p9jXJkHDs2IOkFERKQWdHGy77Nm9v3HTDfzqg/PODzydRrZibsqcQNQhUmyiIiIiIiI1ERS5NNSX6o9STazHsDpwF5A4xBC39jtewAHAK+FECr97A8zm1fRIiCtul0iIiIiIiIiNVWtSbKZjQWu5n/vJS67Wz4J+CdwCXBPFR4uDegPbD2hNuCt6nSJiIiIiIjIjvFywiwvqvxBlmZ2GjAGeI3izzG+uezyEMLXwBzghCo+5GSgSQjh260ui4DpVe0SERERERERqS1VniQDI4GFwKAQwjwgbxv3mQ9kVeXBQgjnhhBmVbDs9Gp0iYiIiIiIiNSK6hxu3R34ewhhW5PjEkvR+4lFRERERER2Gjrcurzq7Ek2oKiS+6QBm3c8R0RERERERCQ61ZkkLwAOqWihmSUBhwGf1jRKREREREREJArVmSQ/DfzCzC6tYPnVQGfgiRpXiYiIiIiISEJYkrm5eFCd9yT/GTgZuM3MTiH28U9mdgdwONALeAfIru1IERERERERkUSo8iQ5hLDJzI4C/gKcASTHFo2m+L3KjwN/CCEU1HqliIiIiIiISAJUZ08yIYS1wG/NbDSwP5AKrAVmhxBWxKFvu/KK1id6yJ9ISWoadYJspcjB32mSrFr/tEQS6oFDM6JOoP34b6NOYMGVraJOAPQ6Itum33FEJJF0duvydug3+RDCKuDVWm4RERERERERidQOTZLNLBPYD2hO8Z7kD0IIi2szTEREREREROJPe5LLq9Yk2cyygPuAPttY9gbw+xDCl7XUJiIiIiIiIpJQVZ4km1ln4C2K34f8FTALWA6kU/z5yEcDs8zskBDCwji0ioiIiIiIiMRVdfYk30zxBPli4N4QQlHJAjNLAi4CJgDjgVNqM1JERERERETiQ4dbl1edSfLRwEshhHu2XhCbMP/FzPoDfWsrTkRERERERCSRkqpx3xTgw0ru8wFQf8dzRERERERERKJTnT3JHwGdK7lPZ2DejueIiIiIiIhIIiXpcOtyqrMneTxwkpkdu62FZjYAOBEYVxthIiIiIiIiIolW4STZzM4qe6H4pF0vA5PN7D9mNsbMzov99zXgBeAloHVi0qtn+bJczjn7JgYdfzmDj7+cxx97GYBXX3mHwcdfTo9uZ/DpJ18nvGvGjLn0738+/fqNIDv7mYSP76XBQ8c3Xy/hxMGjSi+9fnk6jz76YsI7IPp14aXBS4eHBi8diWxokJzEpN8ewMvnHsRr5x3MqMM7AvCXE/bhjd8dwn/OO5jbB3SjXuzP3/2y2vDK8IN46dyDeHHYgfTarUWt9uh1xHfDVVf9hYMP/g3HH//7SMYvEcW60HPTf4eHBi8dapCdwfYOt/47ELa6rWRHfF+2fYKuE4CBwGM1LqtlyclJXPbHM+i2dwc2bNjEqUOu4eBDupOVlcmEe0Yx9rqHE95UWFjI2LEP8MgjN5KWlsrQoaPp0+dAOnfevU41eOno0DGD556fUNpzZO/h9O17YMLGL+FhXXho8NLhocFLR6IbthQW8et/zGVjfiH1kox/nbk/07/K5flPl3PxC58AcPeg7py2bwaPv/89/120itcWrACga5sm3HtSD45+8K1a69HriN8GgJNOOprf/GYAV1wxIaHjlhXVutBz03eHhwYvHWrwS2e3Lm97h1sPA87Z6jKsCpdzqjKwmTUzs5vN7P/M7PStlt1Xzf+PSrVp25Jue3cAoHHjhnTolEFOzmo6dsqgQ4dda3u4Kpk3bwHt27cjMzOdlJT6DBhwBFOnvlvnGjx1lHjn7Y/JzEwnI6Ntwsf2sC48NHjp8NDgpSOKho35hQDUSzLqJxuBwLSvVpYu/2jpWto1bVDuvgCNUpIhbP133prR64jfBoD999+H5s2bJnzcsqJaF3pu+u7w0OClQw2ys6hwT3II4dE4j/0IsAD4N3COmQ0BTg8hbAEOiufAS5as4PP5i+jRs1M8h6lUTk4u6en/Ozo9LS2VefO+rHMNnjpKvPTSTAYMODySsT2sCw8NXjo8NHjpiKIhyWDyOQexR8uGPDZ3MR8uXVe6rF6ScVL3dlz/2helt/Xv0oY/HpVF60YpDHv6g7h16XXEV4MXHtaFnpv+Ojw0eOlQg19WnTNV1QFRro5OIYQrQwjPhxBOAN4H3jCz1HgOunHDZkaNnMAVV55JkyaN4jmU7KTy8vJ544336P+rQ6JOEanzigIc9/A7HHTPTPbdtTld2jQuXXZT/668+91q3lu8pvS2V79cwdEPvsV5//qQS4+IzyRBryPilZ6bIiK1I8pJcgOz//3NIoQwDngImEHxScK2ycxGmNkcM5szMfvZag2Yn1/AqIsnMGDgofQ95oAd7a41aWmpLF/+v8MGc3JySUuL698IXDZ46gCYOfN9unXrSOvWtXvSn6rysC48NHjp8NDgpSPKhnVbCnjr29Uc2bH4r/8XH9aRVo1SuPH1bf/1f/biNezeoiEtG9av1Q69jvhs8CLKdaHnpt8ODw1eOtQgO4tqTZLNrLGZXW5mr5vZfDP7ehuXr6r4cC8CfcreEEL4O3ApkFfRN4UQskMIvUIIvYaPOKnK7SEErhuTTceOGZz92wFV/r546t49i0WLlrJ48XLy8vKZMmUGffok9oXNQ4OnDoApU2ZFdqg1+FgXHhq8dHho8NKR6IZWjerTrEHxu4Ia1Evi8A6tWJi7gdN6ZtC7YyoXTfq43Nkl27dsWPr1PmlNSamXxOpN+bXWo9cRvw1eRLUu9Nz03eGhwUuHGvwy83PxwEIVT2xiZi2AWUA3YB3QDFgLpAAlv5ksBfJDCB1qFGU2LITwSGX3yyuaW+Wzsrw/93PO/s1YsrpkkpRU/LeBkZecQn5eAePHPcrqVeto2qwRXbu258GJV1W5NSWpZicJefPNOYwf/xCFhUUMGdKXCy44tUaPt7M21GZHUSjY4YaNGzfT56jzeO31B2jatHHl31CBJNveieMr52GbeGjw0uGhwUtHbTW0H/9tpffp2qYJdw3cm6QkI8mMyfNzuHvW13x15dEsWbuZH/OKT9T1yhc/cPesrzn/oD0Y0r0d+UWBLfmFjHtjAXO+X1Ph4y+4slW1mvU64rth9OjbmT37Y1avXkdqagsuuuh0Tj75mIR31Na6yCtaX+X76rnpv8NDg5eOn19DFyfTupo5/IVZtXu2yxqYecJhka/T6kyS7wBGA+dS/PFQhcD1wI3AgcBfgQ1A/xDC5hpFmX0XQqj0POzVmSTHS01fQKT21WSSXFtqOkkW+bmryiQ53qo7SY4XvY7ItlRnkhwvem6KVIUmybXNwyS5Or/JnwDMKNnDa7F94aF4lv2OmR0HfAxcA/ypsgczs3kVLQLSqtElIiIiIiIiO8i8HOfsRHUmyZkUv4+4RBHQoORKCOEHM3sZOI0qTJIpngj3B1ZvdbsBb1WjS0RERERERKRWVGeSvJHiiXGJtUD6VvfJATKq+HiTgSYhhA+3XmBm06vRJSIiIiIiIlIrqjNJXkzx3uQSnwFHmFlSCKFk8nwYsLwqDxZCOHc7y06vRpeIiIiIiIjsIB1tXV51PgLqTaC3/e+A9aeATsBLZvZ7M3sGOAh4qZYbRURERERERBKiOnuSH6X44552o3iv8gMUf87xYKDkMxb+C4ypzUARERERERGJH+1JLq/Kk+QQwvvABWWuFwAnmdkvgc7AIuC9Modei4iIiIiIiOxUavxhriGEucBcADPb18x2DyG8UOMyERERERERkQSr8SR5KxcDZwHJtfy4IiIiIiIiEgc63Lq86pwEzUfhAAAgAElEQVS4S0RERERERORnrbb3JItELsn0tBbxbsGVLaNO4JJ31kWdAMB9hzSNOsGNvKL1USeQkuRje3jo8LA9wMe6EJG6RbMJERERERGROixJh1uXo8OtRURERERERGI0SRYRERERERGJ2e7h1mZ2RDUfL70GLSIiIiIiIpJgOty6vMrekzwdCNV4PKvm/UVERERERETcqGySPANNekVERERERH62kkxTvrK2O0kOIRyZoA4RERERERGRyOnEXSIiIiIiIiIx+pxkERERERGROkwn7iqvzkySly/L5eor7yc3dy0GDD2lD78561jWrvmRy0bfzdIlK9g1ow13TBhJ8+ZNEtY1Y8Zcxo17iKKiIk4+uR8jRpycsLFLXHXVX5g+/T1SU5szefK9CR+/hId14aHBS4eHBi8dHhq8dETVUP5nuMV+hv+KO29/gunT3qd+/XpkZqZx4/gRNGvWuNbG3Zy7ik8n/p28deswjF17H8buxxxN/o8b+OT+h9i0MpeGrVPZ58LzqN+4Md++/B+Wvz0bgFBUxIalyzji7juo36T2mram58VPX9tffeUd7v/rv/n666X88+kb2XufjgnpAR/bI6oO/a7lu8FLhxpkZ1BnDrdOTk7isj+ewaTJt/OPp8by5BOv8dXC73n4oRc48OB9mPLqBA48eB8efujFhDUVFhYyduwDTJx4PVOm3MvkyTNYuPC7hI1f4qSTjmbixOsTPm5ZHtaFhwYvHR4avHR4aPDSEWVD+Z/hN5T+DD/4kH147oVbeXbSLbTfI52J2S/U6riWnEzWqUM5eNz19BpzBd+/8SY/LlnKopdeoWW3rhxy64207NaVb6e8CkD7Y4/hwLFjOHDsGDoNHUzLPbvEdYKs58W2X9uzsjKZcM8oftmra0I6SnjYHlF26Hctvw1eOtQgO4s6M0lu07Yl3fbuAEDjxg3p0CmDnJzVTHtjLoMGHQ7AoEGHM23qnIQ1zZu3gPbt25GZmU5KSn0GDDiCqVPfTdj4Jfbffx+aN2+a8HHL8rAuPDR46fDQ4KXDQ4OXjigbfvozfFdyclZzyKE9qFcvGYCePTuTk7OqVsdt0KI5zfbYHYB6DXehcbt0tqxZw8oP5tHu0IMBaHfowaz44KOffG/OO++RdlCvWu3Zmp4X235t79gpgw4ddk1IQ1ketkeUHfpdy2+Dlw41+JXk6OJBZB1mlm5m95vZvWaWambXm9nHZva0mbWL59hLlqzg8/mL6NGzE7m5a2nTtiUArdu0IDd3bTyHLicnJ5f09Nal19PSUsnJyU3Y+J54WBceGrx0eGjw0uGhwUuHhwYo+Rn+LT16dip3+3PPvslhh/eM27ibVq5k/XeLad6xA3lr19GgRXMAUpo3I2/tunL3LdySR+4nn9L2l7+IWw/42CYeGqD8a3tUvKwLDx36XctXg5cONcjOIsrJ+t+Bz4DFwDRgE3AcMBN4IF6DbtywmVEjJ3DFlWfSpEmjcsvMDPSmdRERt4p/hv/5Jz/Dsx94nuTkZI4feGhcxi3YvJmP/5pNl1+fQr2GDcstK37tKP/isfLDebTo3Cmuh1rL/2zvtV0ST79ricjOLspJcloI4Z4Qwi1AixDCrSGExSGEe4D2FX2TmY0wszlmNmdi9rPVGjA/v4BRF09gwMBD6XvMAQCkpjZnxQ+rAVjxw2pSWzXf4f+h6kpLS2X58pWl13NycklLS03Y+J54WBceGrx0eGjw0uGhwUtH1A3FP8P/HPsZvn/p7c8/9yZvTv+AW26/sPgX8FpWVFDIx3/NJv3gA2jbaz+geO/xljXFe8O2rFlLSrPyb1nJmf0eaQfu/5PHqm1RbxMPDdt6bY9K1OvCQ4d+1/LZ4KVDDX4lWXBz8aDak2Qz62Fmt5jZJDN7vczte5jZKWbWcgfGfmyrZckVfVMIITuE0CuE0Gv4iJOq3B1C4Lox2XTsmMHZvx1QevuRfX7BpEkzAZg0aSZH9flllR+zprp3z2LRoqUsXrycvLx8pkyZQZ8+0b7AR8XDuvDQ4KXDQ4OXDg8NXjqibCj+Gf5Q7Gf4caW3z5r5EY88PJl77ruUhg0bxGXc+Y88RuNd09m9f9/S21vv24Nl/30bgGX/fZvW+/UoXVawcROrv1hAm1/E79DvEnpebPu1PSoetkeUHfpdy2+Dlw41yM7CQqj6bN3MxgJX878JbgghJMeWdQQWAJfE9gZX5bFuCyH8uNXtnYFbQghDK3uMvKK5VY5/f+7nnP2bsWR1ySQpqTh/5CWn0KNHZy4bfTfLlq6k3a6tuXPCxTRvUfWPJUhJqtkJr958cw7jxz9EYWERQ4b05YILTq3R4+2I0aNvZ/bsj1m9eh2pqS246KLTOfnkYxLe4WFdeGjw0uGhwUuHhwYvHbXVkFe0rvI7lfH+3C/K/Awv3ls88pJTuWX8Y+Tl5dMi9nO7R8/OXHv9uVV6zEveWV/pfdZ8uZC5N99Bk90ySg+p7jRkEM07deDj+x5ic+4qdmmdSvcLzis9tHrprLfI/fgzul8wvEod9x2SUaX7VeTn9byofJuUVdFre35eAePHPcrqVeto2qwRXbu258GJV1XpMX8Or+u11VFb20O/a/lo8NLx82vo8rN4A8HA12b62IULvNjv8MjXaZUnyWZ2GvAE8CpwBXAqcGXJJDl2n3eBdSGEfjWKMhsWQniksvtVZ5IcLzX9wS0iUhdVd5IcD1WZJCdCTSfJPyfVnZTFg17X/8fD9gBtE/Hu5zFJHvS6n0nypL7RT5Krc7j1SGAhMCiEMA/I28Z95gNZtdB1Qy08hoiIiIiIiEi11KvGfbsDfw8hbGtyXGIpkFaVBzOzeRUtqupjiIiIiIiISM14+XxiL6ozSTagqJL7pAGbq/h4aUB/YPU2xnmrGl0iIiIiIiIitaI6k+QFwCEVLTSzJOAw4NMqPt5koEkI4cNtPNb0anSJiIiIiIiI1Irq7Fl/GviFmV1awfKrgc4Un9yrUiGEc0MIsypYdno1ukRERERERGQHJZmfiwfV2ZP8Z+Bk4DYzOwUIAGZ2B3A40At4B8iu7UgRERERERGRRKjyJDmEsMnMjgL+ApwBlHz002iK36v8OPCHEEJBrVeKiIiIiIiIJEB19iQTQlgL/NbMRgP7A6nAWmB2CGFFHPpEREREREQkjszcfEyyC9WaJJcIIawCXq3lFhEREREREZFI6SOxRERERERERGKqvCfZzP5WxbuGEMK5O9hTLSlJTRMxzE4hEP0hEoaT09E5UOTkrflmyZXfKd4Nel7INqQkNYs6gfsOib4BYNDrOVEnMKlvWtQJgF7XvdH2EKk7vJxV2ovqHG7920qWB8Bi/03IJFlERERERESkNlVnktyhgttbUHwSrz8BbwFX1jRKREREREREEkPvwS2vOh8B9W0Fi74FPjKzV4F5wOvAw7XQJiIiIiIiIpJQtfZHgxDCYuBF4OLaekwRERERERGRRNqhj4Dajhwgq5YfU0REREREROIkSZ+TXE6t7Um24tPo9gHW1tZjioiIiIiIiCRSdT4C6ojtPEYmMAzYF5hYC10iIiIiIiIiCVedw62nw3Y/jNeAGcDlNQkSERERERGRxNHnJJdXnUnyWLY9SS4CVgOzQwiza6VKREREREREJALV+Qio6+PYISIiIiIiIhK5Kp+4y8z+Zmaj4hmTSDNmzKV///Pp128E2dnP1NmOZctWcNaZ1zDguN9z/IDf89ijLyS8oUTU68JLwzdfL+HEwaNKL71+eTqPPvpiQhv0vPDX4KXDQ4OXjkQ15K9exXd/vp2vb/wTX994LaumvQ7Aihef55tx1/HN+Bv47p67yF+zBoANX37Ol5dexDfjb+Cb8Tew8qX4//zwsD28dHho8NLhocFLh4cGLx1q8CnJ0cWD6hxufTowIV4hAGbWNoTwQzzHACgsLGTs2Ad45JEbSUtLZejQ0fTpcyCdO+8e76HddSQnJ3PFleew996d+PHHjQwZMppDDt23Tq4LDw0AHTpm8NzzE0qbjuw9nL59D0xog54Xvhq8dHho8NKRyAZLSqLtSaewy+7tKdy8mUW33kjjrt1o1bc/bQYOBmDVtNfJfflF0n99JgANO2eRecHIWm/ZFg/bw0uHhwYvHR4avHR4aPDSoQbZWVRnsr4IaFtbA5tZq60uqcBsM2tpZq1qa5xtmTdvAe3btyMzM52UlPoMGHAEU6e+G88h3Xa0bduKvffuBECTJo3o1HE3cnJyE9oAPtaFh4atvfP2x2RmppORUWv/9KpEzwtfDV46PDR46UhkQ73mLdhl9/YAJO+yCw3S2lGwZjXJDRuW3ifk5cVl7KrwsD28dHho8NLhocFLh4cGLx1q8CvJ/Fw8qM4k+QngWDNrWUtjrwTmlrnMATKA92Nfx01OTi7p6a1Lr6elpUYyAfDSUeL773OYP/9revbcM+Fje1gXHhq29tJLMxkw4PBIG/S8iL7BS4eHBi8dUTXk5a5k8/ffscseHQFY8cKzLLzmcta+9w6tjx9cer9N33zFN+OvZ/G9f2bL0iVxbfKwPbx0eGjw0uGhwUuHhwYvHWqQnUV1Jsk3Uzx5nWZmx5tZWg3Hvhz4AjghhNAhhNAB+D72dccaPrZU04YNmxg58hauuno4TZo0ijpHgLy8fN544z36/+qQyBr0vBDxo2jzZpY8dB9pQ08t3Yvc5oST6DzudprvfxCr33wDgF0y29N57K10uPp6Wvbuw/fZ90aZLSIistPZ7iTZzM4ysx6xq5uBAUAPYBKw1MwKt3EpqMrAIYQ7geHAtWZ2l5k1Zfufw1zSNMLM5pjZnOzsp6oy1E+kpaWyfPnK0us5ObmkpaXu0GPVhJeO/PwCRo68hYEDe3PMMdFMyDysCw8NZc2c+T7dunWkdesWkYyv54WfBi8dHhq8dCS6IRQWsGTi/TTf/yCa7vvLnyxvtv+BrP9wLgDJDRuStMsuADTZpwehsJCCH9fHrc3D9vDS4aHBS4eHBi8dHhq8dKjBryQLbi4eVLYn+e/AoNjXM4EZwJux/1Z0mVnVwUMI34cQTgamA68Ble6qCiFkhxB6hRB6jRhxalWHKqd79ywWLVrK4sXLycvLZ8qUGfTpc8AOPVZNeOgIITDmmnvo1HE3hg0bXPk3xImHdeGhoawpU2ZFdqi1nhe+Grx0eGjw0pHIhhACyx5/lJT0drQ6+pjS2/N+yCn9ev28D2mQ1g6AgrVrCaH4l4xNi76GEEhu3CQubeBje3jp8NDgpcNDg5cODw1eOtQgO4uqnN3aAEIIR8YrIoTwgpm9BnQCMLNhIYRH4jVevXrJXHvt+Qwffh2FhUUMGdKXrKz28RrOdcf7c+czadI0unRpz+BBFwMwavSZ9O7dK6EdHtaFh4YSGzdu5q3/fsgNN5wfyfh6Xvhq8NLhocFLRyIbNn21kHWz36bBrhl8M/4GANqccCJr3p5FXs5yzIx6rVJLz2y9/oO5rJ45HUtOwuqnsOs5IzCL35lQPGwPLx0eGrx0eGjw0uGhwUuHGmRnYSV/bd7mQrMi4PoQwtjEJYGZfRdCqMJ52L/0sT/egVD5kepxZzg5HZ0DRaFK7zqIO7PkqBP0vBCpxKDXcyq/U5xN6lvT04yIiNRVXX4Wv+gMnzU9+slEzMTDjox8nVbnc5JrlZnNq2gRoFdrERERERERSbiqTJJbmFm1Pl07hPBdFe6WBvQHVm91uwFvVWc8ERERERERkdpQlUnyxbFLVYUqPu5koEkI4cOtF5jZ9GqMJyIiIiIiIjuoOp8LXBdUZTK7DlhT2wOHEM7dzrLTa3s8ERERERERkcpUZZI8IdEn7hIREREREZHE8PL5xF5oz7qIiIiIiIhIjCbJIiIiIiIiIjGRfQSUiIiIiIiIRC8p8k8m9kV7kkVERERERERitrsnOYSgSbSIiIiIiIjUGTrc+mfC0DESniSZ/mmJSNVM6psWdQIdLv086gQAvrmza9QJIiJ1kg63Lk97ikVERERERERiNEkWERERERERidExoSIiIiIiInWY9pyWp/UhIiIiIiIiEqNJsoiIiIiISB2WZMHNpTJmlmlm08zsMzP71Mwujt3eysxeM7MFsf+2jN1uZna3mS00s3lm9otK10eN16iIiIiIiIhIYhQAl4YQugEHAb83s27AlcDUEEIWMDV2HeBYICt2GQHcX9kAmiSLiIiIiIjITiGEsCyE8H7s6/XAfCADGAQ8Grvbo8Dg2NeDgMdCsXeAFmbWbntj6MRdIiIiIiIiddjO+jnJZrYHsB/wLpAWQlgWW7QcSIt9nQEsLvNt38duW0YFtCdZREREREREXDCzEWY2p8xlRAX3awL8G7gkhLCu7LIQQgAqf4NzBersJHnGjLn0738+/fqNIDv7mTrd4aHBS4eHBi8dHhq8dHho8NLhocFLh4eGRHak1Evi+YsP56VLe/Pq5UdySf89yy2/bvA+fDL+uNLrY07YmymjezNldG/euLIPH910bNzaSnjYJh4avHR4aPDS4aHBS4capDIhhOwQQq8yl+yt72Nm9SmeIP8jhPBs7OacksOoY//9IXb7EiCzzLfvFrutQnVyklxYWMjYsQ8wceL1TJlyL5Mnz2Dhwu/qZIeHBi8dHhq8dHho8NLhocFLh4cGLx0eGhLdkVdQxOn3v8Vxd77JgDvfpPeebdl395YAdN+tOc0b1i93/5te+JQBd73JgLve5NFZ3/DKxxUe1VYrPGwTDw1eOjw0eOnw0OClQw1+JTm6VMbMDHgYmB9CuKvMoheAs2Nfnw1MKnP7WbGzXB8ErC1zWHaF66POmTdvAe3btyMzM52UlPoMGHAEU6e+Wyc7PDR46fDQ4KXDQ4OXDg8NXjo8NHjp8NAQRcfGvEIA6iUnUS/ZgECSwVUD9+bmyZ9V+H0D98vgxQ+2+0f7GvOwTTw0eOnw0OClw0ODlw41SC05FDgT6GNmH8YuxwG3AP3MbAHQN3Yd4CXga2Ah8BBwYWUDRDZJNrNflfm6uZk9HPvcqifMLG1731tTOTm5pKe3Lr2elpZKTk5uPId02+GhwUuHhwYvHR4avHR4aPDS4aHBS4eHhig6kgymjO7NnBv6M+vLFXz43RrOOqwDr3+6nBXrt2zzezJaNiSzVSPeWrAibl3gY5t4aPDS4aHBS4eHBi8dapDaEEKYFUKwEEKPEMK+sctLIYTcEMLRIYSsEELfEMKq2P1DCOH3IYROIYTuIYQ5lY0R5Z7k8WW+vpPis4sNBN4DHoykSERERCpUFGDAXW9y8Nj/0HP3lhzQsRXH9dyVR2d9U+H3HL9vBi/PW0rRDp8+RURE4i3J/Fw88HK4da8QwpgQwrchhAnAHhXdsezZzrKzn9qhwdLSUlm+fGXp9ZycXNLSUnfosWrCQ4eHBi8dHhq8dHho8NLhocFLh4cGLx0eGqLsWL+5gLcXruSgzq3ZI7Ux0686mpnX9KVh/WSmXXV0ufsO3C+DF+J8qDX42CYeGrx0eGjw0uGhwUuHGmRnEeUkua2ZjTazS4FmsTdgl6iwq+zZzkaMOHWHBu7ePYtFi5ayePFy8vLymTJlBn36HLBDj1UTHjo8NHjp8NDgpcNDg5cODw1eOjw0eOnw0JDojlaNU2i6Sz0AGtRL4vAubfhk8VoOuOE/HD7udQ4f9zqb8gs56uappd/TsW0Tmjesz/uLVselqSwP28RDg5cODw1eOjw0eOlQg19mwc3Fg3oRjv0Q0DT29aNAa2CFmaUDH8Zz4Hr1krn22vMZPvw6CguLGDKkL1lZ7eM5pNsODw1eOjw0eOnw0OClw0ODlw4PDV46PDQkuqNts12449f7kWyGGUz5aClvzM/Z7vcM3DeDFz+M/15k8LFNPDR46fDQ4KXDQ4OXDjXIzsKKP2fZFzMbFkJ4pPJ7fukvXkREZCfT4dLPo04A4Js7u0adICJSTV2cvIu2Zq54b6qbedWt+x8d+TqNck/y9twAVGGSLCIiIiIiIjXh5YRZXkQ2STazeRUtAuL6EVAiIiIiIiIi2xLlnuQ0oD+w9dk8DHgr8TkiIiIiIiJS10U5SZ4MNAkh/OQkXWY2PfE5IiIiIiIidY+XzwX2IrJJcgjh3O0sOz2RLSIiIiIiIiKgPxqIiIiIiIiIlPJ6dmsRERERERFJgCRz8wlQLmhPsoiIiIiIiEiMJskiIiIiIiIiMTrcWkREREREpA5LsqgLfNEkWUREEi6vaH3UCaQkNY06wY1v7uwadQIAL373VdQJDNy9U9QJIiISMU2SRURERERE6jDtSS5P70kWERERERERidEkWURERERERCRGh1uLiIiIiIjUYclRBzijPckiIiIiIiIiMZoki4iIiIiIiMTocGsREREREZE6LMlC1AmuaE+yiIiIiIiISIwmySIiIiIiIiIxOtxaRERERESkDkuyqAt8qbN7kmfMmEv//ufTr98IsrOfqdMdHhq8dHho8NLhocFLh4cGLx1RNSxflss5Z9/EoOMvZ/Dxl/P4Yy8D8Oor7zD4+Mvp0e0MPv3k64T1gI/t4aUjkQ1P3fEE1508htvPu+Uny6Y/M43L+l3ChrU/AvDJWx9z54hbuet3t/HnC+/kmwQ8RzxsDy8dHhq8dHho8NKhBtkZuJokm1lqIsYpLCxk7NgHmDjxeqZMuZfJk2ewcOF3iRjaXYeHBi8dHhq8dHho8NLhocFLR5QNyclJXPbHM5g0+Xb+8dRYnnziNb5a+D1ZWZlMuGcUv+zVNSEdJTxsDy8diW7odcyBnDf+dz+5fc0Pq/ly7ue0aNuy9Las/bow+sE/MvrBP3LKZb/m6buejFsX+NgeXjo8NHjp8NDgpUMNfiWZn4sHkU2SzewWM2sd+7qXmX0NvGtm35pZ73iOPW/eAtq3b0dmZjopKfUZMOAIpk59N55Duu3w0OClw0ODlw4PDV46PDR46YiyoU3blnTbuwMAjRs3pEOnDHJyVtOxUwYdOuyakIayPGwPLx2JbujUoxONmjb6ye2THnie4887ASvzC1aDhg2w2A15m7cQ79+9PGwPLx0eGrx0eGjw0qEG2VlEuSd5QAhhZezr24FTQwidgX7AnfEcOCcnl/T01qXX09JSycnJjeeQbjs8NHjp8NDgpcNDg5cODw1eOjw0ACxZsoLP5y+iR89OCR+7hJd14aHDQ8Mnb31M89Tm7Nop4yfLPp41j1vPGc/DYx7ilMt+HdcOD+vCS4eHBi8dHhq8dKhBdhZRnrirnpnVCyEUAA1DCO8BhBC+NLMGEXaJiIhTGzdsZtTICVxx5Zk0afLTvYlS9+RtzmPqP19jxC0XbHN598N60P2wHnw17yte/fvL/O62CxNcKCLiX7KTw5y9iHJP8n3AS2bWB3jFzP5iZr3N7Abgw4q+ycxGmNkcM5uTnf3UDg2clpbK8uUrS6/n5OSSlpaQt0O76/DQ4KXDQ4OXDg8NXjo8NHjpiLohP7+AURdPYMDAQ+l7zAEJG3dbol4XnjqibshdtpJVy1dx1+9uY9xvbmDtirVMuOAO1q1aV+5+nXp0IndZbulJveIh6nXhqcNDg5cODw1eOtQgO4vIJskhhHuA8cDvgEFAH+AKYAkwbDvflx1C6BVC6DVixKk7NHb37lksWrSUxYuXk5eXz5QpM+jTJ/G/cHno8NDgpcNDg5cODw1eOjw0eOmIsiGEwHVjsunYMYOzfzsgIWNuj4ft4aUj6oZ2HXblhmdu4prHr+Oax6+jeZvmjLr/Mpq1asbKJSsIIQDw/YLFFOQX0KhZ47i1RL0uPHV4aPDS4aHBS4caZGcR6eckhxCmA9O3vt3MhgGPxGvcevWSufba8xk+/DoKC4sYMqQvWVnt4zWc6w4PDV46PDR46fDQ4KXDQ4OXjigbPnj/C158YRZZXTIZeuJVAIy85BTy8woYP+5RVq9ax4Xn30bXru15cOJVce/xsD28dCS64fFxj/LVvK/YsPZHbvz1dRxz1rEceOxB27zvvJkfMff1OSQnJ1G/QX3OHHN26Ym84sHD9vDS4aHBS4eHBi8davDLy1mlvbCSv7B6YmbfhRB2r/yeX/qLFxGRSuUVrY86gZSkplEnyFZe/O6rqBMYuHt0J4QTkZ1Rl5/F9HLCJ6+5mVeN2qdf5Os0sj3JZjavokVAWiJbRERERERERCDaw63TgP7A6q1uN+CtxOeIiIiIiIjUPUnmZkeyC1FOkicDTUIIPzmTtZlNT3yOiIiIiIiI1HWRTZJDCOduZ9npiWwRERERERGpq3TirvKi/JxkEREREREREVc0SRYRERERERGJifRzkkVERERERCRayVEHOKM9ySIiIiIiIiIxmiSLiIiIiIiIxOhwaxERERERkTpMZ7cuT5NkEZE6Jr9oQ9QJpCQ1jTpBHBq4e6eoE1i84YuoEwDIbLxn1Alu/Jj/fdQJNK6fEXUCAIZmMiKJoMOtRURERERERGK0J1lERERERKQOS7IQdYIr2pMsIiIiIiIiEqM9ySIiIiIiInVYst7uXo72JIuIiIiIiIjEaJIsIiIiIiIiEqPDrUVEREREROowfU5yedqTLCIiIiIiIhKjSbKIiIiIiIhITJ2dJM+YMZf+/c+nX78RZGc/U6c7PDR46fDQ4KXDQ4OXDg8NUXWMueYBjjh0BIMHXlZ62+eff8sZp/2JE0+4nN9fcBs//rgxIS1ledgmHhq8dHhoiLLjX4/P4NyhtzP85NsZd9Xj5G3JZ9mSXP5w1l8464SbufGK/yM/vyBhPeBjm0TZUFhYxOlDx3HxhfcCMPZP/8dpJ93EqSfexB9HZbNx4+aEtSxbtoKzzryGAcf9nuMH/J7HHn0hYWNvra4/Lzw1eJNkfi4e1MlJcmFhIWPHPsDEidczZcq9TJ48g4ULv6uTHR4avHR4aPDS4aHBS4eHhig7Bg/uzQPZV5W77bo/Pcglo3/Ncy/czkcneI4AACAASURBVNF99+eRh1+Me0dZHraJhwYvHR4aouxY+cNann9yJvc9fgkTn7mcwqIipr36IQ/dPYUhZxzBYy9cRdNmDXn5+dlxbynhYZtE3fDPx99gj47ppddHXzGUJ58dw1PPjSG9XSueeuLNhLUkJydzxZXnMOWle3nyqdv5xxMv1al/I2qQnVFkk2Qze9/MxphZp0SPPW/eAtq3b0dmZjopKfUZMOAIpk59N9EZLjo8NHjp8NDgpcNDg5cODw1RdvTafy+at2hc7rZvFy2j1/57AXDwId157bXE/fIPPraJhwYvHR4aou4oLCxiy5Z8CgsK2bIpn1atm/Hhews54ugeABxzfC/+O+2ThLSAj20SZUPO8tXMmvEJg4ccWnpbkyYNAQghsHlzHpbAvVVt27Zi7707xToa0anjbuTk5CYuIKauPy88NYh/Ue5Jbgm0AKaZ2WwzG2VmuyZi4JycXNLTW5deT0tLjeSHlYcODw1eOjw0eOnw0OClw0ODpw6ATp13442pcwD4z6vvsnxZ3dsmHhq8dHhoiLKjddvmnHzmkZx+3E2ccsxYGjfdhS577UaTJg1JrpdcfJ+0FuSuWBv3lhIetkmUDXfe+gwXjz6RJCv/a+71Yx7jmN5XsOibHE49/aiEtGzt++9zmD//a3r23DPhY9f154WnBo+iPsRah1v/z+oQwmUhhN2BS4Es4H0zm2ZmIyLsEhGR7bhx3Pk8+c//cMqQq9iwYRP16+vTBKXuWr9uI29N/4THJ1/NU69ey+ZNebz31udRZ9VZM6Z/TMtWTdlr7/Y/WXb9TWfxyrRb6NAxnddemZPwtg0bNjFy5C1cdfVwmjRplPDxRaTqXLwnOYQwM4RwIZAB3AocXNF9zWyEmc0xsznZ2U/t0HhpaaksX76y9HpOTi5paak79Fg14aHDQ4OXDg8NXjo8NHjp8NDgqQOgY8cMHnr4Gp7+980cd9whZO6eltDxPawLDw1eOjw0RNnx/rsLSM9IpUXLJtSrn8xhfbrzyUeL+PHHTRQWFAKwMmcNqW2ax72lhIdtElXDRx98xYzp8zj+mGu4+vKHeW/2F4y54pHS5cnJSfQ/thdTX/sg7i1l5ecXMHLkLQwc2JtjjjkkoWOXqMvPC28NHiVbcHPxIMpJ8pdb3xBCKAwhvBJCGFbRN4UQskMIvUIIvUaMOHWHBu7ePYtFi5ayePFy8vLymTJlBn36HLBDj1UTHjo8NHjp8NDgpcNDg5cODw2eOgByc4sPGy0qKuLBB57jlFP7JnR8D+vCQ4OXDg8NUXa0TW/B/I+/ZfOmPEIIfDB7Ae07prFvr87MmDoPgP9MnsMhR+4d95YSHrZJVA0XjRrMy1NvZvJ/xjH+9nPZ/4A9ufGW37L4ux+A4vckvzltHnt0SK/kkWpPCIEx19xDp467MWzY4ISNu7W6/Lzw1iD+RXaMXAjhtIqWmdmwEMIjFS2vqXr1krn22vMZPvw6CguLGDKkL1lZPz0sJ948dHho8NLhocFLh4cGLx0eGqLsuPzSu3lv9mesWbOeo4+8kAv/MJSNGzfz5BP/AaBvvwM48aQj495Rlodt4qHBS4eHhig79ureniOO7sEFZ0wgOTmJzntmMOCkgzjwsL0Yd9XjPHLvK3TumsGxgw+Me0sJD9vEQ0OJEALXXf0oP27YDCGQteduXPWnXyds/PfnzmfSpGl06dKewYMuBmDU6DPp3btXwhrAxzZRg+wsLAQfu7TLMrPvYu9VrsSX/uJFRJzLL9oQdQL1kxpXfieRCCze8EXUCQBkNk78iZ28+jH/+6gTaFw/I+oEAAwnZzX6f/buOz6qKu/j+OekSQkQCBCKSEcFAQuC6IpIEaUICoIVex5dEaXZQEVUFBGxrIqxoNjbIgo2BBTLKk0FFRTUIC0BQ+hg2nn+yJBNWAGBzNwfzvfta16b3JnM+ey9Q8jh3NyRYpr8LQ7KKz+/b2ZedW7D0wPfp4GtJDvnFu7uLiCyv+AmIiIiIiIiQoCTZAonwl2A7F22O+CLyOeIiIiIiIhItAtykjwVSPTef7PrHc65jyOfIyIiIiIiEn2svD+xFUFeuOvyPdx3fiRbRERERERERMDI+ySLiIiIiIiIWBDk6dYiIiIiIiISMJ1uXZJWkkVERERERERCNEkWERERERERCdHp1iIiIiIiIlEs1vmgE0zRSrKIiIiIiIhIiFaS5W8nt2Bb0AnEx5QLOkF2UeDzgk4gxtn4lhsfUz7oBLbmZQSdQJnYpKATAIh1ZYJOkGLqlD886AQAxn+3POgEBh1VN+gEABLjDw06QeRvTxfuKkkrySIiIiIiIiIhmiSLiIiIiIiIhNg4909EREREREQCodOtS9JKsoiIiIiIiEiIJskiIiIiIiIiITrdWkREREREJIrpdOuStJIsIiIiIiIiEqJJsoiIiIiIiEiITrcWERERERGJYrE63bqEqJ0kz549n7vvfpKCggLOOaczqannRG2HhYYgO0YMf5zZHy+gSpWKvPXOOACGDHqQ9PTVAGzetI0KFcvx5uT7ItIDNo6JhQYLHb/+sorBg+8v+nzFikyuHXgeF1/cI6IdEPy+CLLhjz9yuaL/feTk5JGfn0/H047j6gE9ueyiMWzbugOA9es3c1Tz+jzwyDVhaRh+y2N88vF8qiRX4u13HgBg7H2T+HjWfOLj46hzWAp3j76GihXLh2X83Ynm14XFjkg2zHr0BZbP+46ylSrQ78HhAEwf9wwbVmcC8MfW7RxSviznjLuZzKXpzJ7wcuEXemjVryv127QMWxvYOB5WOiw0WOlQgxwMonKSnJ+fz6hRE5g48U5SUpLp02cwHTq0oVGjw6Kuw0JD0B29ep3C+ed34ZabHi3aNm789UUfjx0zicTEcmHv2MnCMbHQYKWjfoPaTH5rfFFP+1OuoFOnNhEbfycL+yLIhoSEOJ54ZgjlypchNzePyy+6j5NOPopnnr+x6DFDr3uc9h3C90P/WWe154ILTuemm/5VtO3EE1syaPAFxMXFMu7+F3gybTJDhl4YtoZdRfvrwlpHpBsOb38CR51xCjMfnlS0rfOQy4o+/uLZf5NQriwAVQ6rRe/7biAmNpat2Rt5ffA91G11FDGxsWFps3A8rHRYaLDSoQa7YpwPOsGUqPyd5IULl1K3bk3q1KlBQkI83bq1Y8aMr6Kyw0JD0B2tjm9KpaTEP73Pe8/7739J124nRaQFbBwTCw2WOnb68j+LqFOnBrVrV4/42Bb2RZANzjnKlS8DQF5ePnl5+Tj333PDtmzZztw5S2jf8ZiwNbQ6vimVKpX8XnHSP1oSF1c4yWjZsjEZGVlhG//PRPvrwlpHpBtqNWvEIbv5R1zvPT9/sYBG/zgOgPhDEoomxPk5uSX+/ISDheNhpcNCg5UONcjBIrBJsnOulXNulnPuBedcHefcdOfcRufcXOdc+H7KATIzs6hRo2rR5ykpyWRmRvYHGysdFhosdexq/rzFJCdXom69mhEb08K+sNBgqWOnd9/9lG7dTg5kbAv7IuiG/PwCzj37DjqdPIQ2bY+keYsGRfd9PONrWrc5gsTEshHr2dW/35zFye3C+tfX/wj6mFhpsNJhoWGnNT/8TLmkCiTV+u8/6mX+lM6r193Fa4NH0+7/zg3bKjLY2RcWOiw0WOlQgxwsglxJfgy4D5gGfAE84b2vBNwUuk8kcO9O+4Ku3U4MOkMMyMnJZebMuXQ5Xa+HoMTGxvDKv2/n/Zn38f2idJYtXVV03/vvzuX0rq0Da5sw4U1i42Lo0SOYf0QR2dWyz+bR6B+tSmxLaVKPfg+NoPeYG1jw7w/Jy8kNqE5ErIkxdLMgyI547/173vuXAe+9f4PCD2YAZXb3Rc65VOfcPOfcvLS0V/dr4JSUZDIyfi/6PDMzi5SU5P16rgNhocNCg6WO4vLy8vnoozmcfkZkJ0UW9oWFBksdAJ9+uoCmTRtQtWpSIONb2BcWGgAqVCxHq9aH88Vn3wGQnb2Z7xf9yj9OaRHxFoDJ/57FJ7Pmc9/Y68J+CuuuLBwTCw1WOiw0ABTk5/PrV9/S8KRj//T+yofWIL7MIaz/bXXYGqzsCwsdFhqsdKhBDhZBTpJ3OOdOc86dA3jnXC8A59wpQP7uvsh7n+a9b+W9b5Wa2m+/Bm7evDHp6atZsSKDnJxcpk2bTYcOkV+BsNBhocFSR3Ff/mcRDerXokaNyH7jtLAvLDRY6gCYNu2zwE61Bhv7IsiG7PWb2bxpGwA7duTw5X9+oF79GgDM+HA+J5/SgkMOiY9IS3Gffvo1Tz89hUcfv5GyZQ+J+PjR/rqw1mGhAWDlwh9Jqp1CYnLlom2bMn+nIL/wx6vNa9ezYVUGFaqH7+83K/vCQoeFBisdapCDRZBXt76KwtOtC4AuwNXOuWeBVcCV4Rw4Li6W2267iiuuuJ38/AJ69+5E48Z1wzmk2Q4LDUF3DBvyEHPn/MCGDZvp2P5q/jngHHr36cB7737BGRG8YNdOFo6JhQZLHdu27eCLz7/hjjuuivjYO1nYF0E2rFu3kdtveYb8ggJ8gadzl1a0a194JesP3pvLJZefEfaGoYMfZM7c79mQvZlTT/k/Blzbl7S0yeTm5HH5ZXcC0LJlE0bekRr2lp2i/XVhrSPSDR89MJHV3y9lx+YtPH/lCFr168qRnU5k2Wfziy7YtVPG4l/4evKHxMTF4pzj5Cv7Ubbin1+0sjRYOB5WOiw0WOlQg10xep/kEpz39i737Zy71Hs/ce+P/MlevAQut2Bb0AnEx0TuLaPkrynweUEnEOOi8l33/tTWvIygEygTG8yp87uKdbv9DSOJYuO/Wx50AoOO0sRBZO+a/C2mlzNXv2tmXtWhVtfA96mV343e1R1BB4iIiIiIiEj0CWxZwzm3cHd3ASmRbBEREREREYlWsYGv3doS5Ll/KRT+LnL2LtsdhW8JJSIiIiIiIhJRQU6SpwKJ3vtvdr3DOfdx5HNERERERESiT4wz8yvJJgQ2SfbeX76H+86PZIuIiIiIiIgI2L1wl4iIiIiIiEjE6f1IREREREREopjeJ7kkrSSLiIiIiIiIhGiSLCIiIiIiIhKi061FRERERESimE63LkkrySIiIiIiIiIhWkmWv534mHJBJ4hBMU7f7nbyBP9eiOXjagSdIGLaoKPqBp1A2pJfg04AIPWI+kEnSDHr/1gSdAIAifG1g04AIEFLjn9L+qlRREREREQkimmuX5L2h4iIiIiIiEiIVpJFRERERESimNOFu0rQSrKIiIiIiIhIiCbJIiIiIiIiIiE63VpERERERCSK6WzrkrSSLCIiIiIiIhKiSbKIiIiIiIhIiE63FhERERERiWK6unVJUbuSPHv2fLp0uYrOnVNJS3s9qjssNFjpsNBgpcNCg5UOCw0WOtasWUf/i4bTres1dO92DZOeezviDTsFvS+sNFjpsNBgpcNCQyQ73n/4RR7rfwvPXntPie0Lpn7CM/+8i2cHjOaTZ6cAsOan5Uy6fkzh7bp7Wfqfb8PWVZyFY2KhIciOzZu2c8vgSfQ78z7O7TmWRd+m88i4qfQ78z4u7D2OG69/ls2btodt/Iw1WVx28V307D6MXt2H8cKk9wD44P0v6dV9GC2aXsD33/0StvHl4BOVK8n5+fmMGjWBiRPvJCUlmT59BtOhQxsaNTos6josNFjpsNBgpcNCg5UOCw1WOmJjY7nxpsto1qwhW7Zso3fvwZx40tFRuS8sNFjpsNBgpcNCQ6Q7jurYhmO6teO9B18o2vbbwp/4+atF9H/oRuLi49m2YTMAVevW5MJxQ4mJjWXL+o1Mun4MDVsfRUxsbKl37WThmFhoCLpj/JgpnHDS4Yx+oD+5uXns2J5L67Z/cPV1ZxAXF8uj46cx6emZXDOoW1jGj42NYegNF9C0WX22bt1Ov97DaXticxo3rsP4RwYx6vanwzKuHLwCW0l2ziU650Y55753zm10zq1zzn3pnLsk3GMvXLiUunVrUqdODRIS4unWrR0zZnwV7mFNdlhosNJhocFKh4UGKx0WGqx0VK9ehWbNGgKQmFiOhg0OJTMzK6INYGNfWGiw0mGhwUqHhYZIdxzarBFlEsuV2Pbt+5/Rundn4uLjASiXVAGA+EMSiibE+bl5uAhcT9fCMbHQEGTHls3b+Wb+L/Q4uzUA8fFxVKhYljYnHk5cXOHroVmLw1ibuTFsDdWqV6Zps/oAlC9flvoNa5OZmU2DhrWpX79W2MY9mMQYulkQZMeLwC9AF+AO4GHgIuBU59zocA6cmZlFjRpViz5PSUkO5Ac9Cx0WGqx0WGiw0mGhwUqHhQZLHTutXJnJ4sW/0LLl4REf28K+sNBgpcNCg5UOCw0WOrJXr2PlDz/z4tBxvHrLQ2QsXV5035of03l2wGieG3gPna7uG9ZVZAh+X1hpCLJj9ar1JFVJ5K5bX6V/3/GMvv11tm/LKfGYqZPn0vYfkfn7ZNWqdSxZnE6Llg0jMp4cnIKcJNfz3j/rvV/pvX8AONN7vxS4FDg7wC4REdmDrVu3M3Dgvdx8yxUk7rKCJCJSkF/Aji3bOH/sYNpd0ot37puI9x6AmofX45J/3cIF9w9lzpvTycvJDbhWwi0/v4CfFq/i7L4nMum1QZQtm8CkZ2YW3f9s2gxi42Lo0u3YsLds27qDQQPHc+NNF+nvr104583cLAhykrzVOfcPAOfcmcB6AO99AXt4P2vnXKpzbp5zbl5a2qv7NXBKSjIZGb8XfZ6ZmUVKSvJ+PdeBsNBhocFKh4UGKx0WGqx0WGiw1JGbm8fAgffSo8cpnHbaiREfH2zsCwsNVjosNFjpsNBgoaNCciUan9AC5xw1m9TFxTi2b9pS4jHJdWoQX+YQfl++JqwtQe8LKw1BdlRPqUS1lEo0a1H4u8+ndm7OT4tXATBtylw+n/0Dd9xzPi7Ml1fOzc1j0HXj6dbjJDqd1jqsY8nBL8hJ8lXAA865bOAG4FoA51w14NHdfZH3Ps1738p73yo1td9+Ddy8eWPS01ezYkUGOTm5TJs2mw4dIv+HxUKHhQYrHRYarHRYaLDSYaHBSof3nhHDH6Fhg0O59NJeER27OAv7wkKDlQ4LDVY6LDRY6GjUpgUrFi0FYP2qteTn5lO2YiIbM7MoyM8HYNPa9axfmUnFlCphbQl6X1hpCLIjuWpFUlKSWP7rWgDmfbWMeg1S+M9nS3hh4sfc9/CllCmbENYG7z23j0ijQYPaXHxJeC4OJn8vbufpL5Y45y713k/c+yN/2u/4Tz6Zx+jRT5KfX0Dv3p24+ur9m3AfKAsdFhqsdFhosNJhocFKh4WG0uzw7N+3zvnzfuCCC26iSZO6xMQU/hvroMEXccoprfb5uQ70gj0WjomFBisdFhqsdFhoKK2OtCW/7vUxU+9/lpXfLWP7pi2US6rAied1pWn74/ngkZdY++sqYuNiOeXSXhzWogk/zJrDnDc/IiYuFuccJ/Q7ncYntNjrGKlH1N/n9uIsHBMLDaXVsf6PJfv8NT8tWcU9I98gNzeP2ocmM/zOvlx23sPk5uRRKanwtOdmLepy4629//JzJsbX/suPXTB/CRdfOIrGTeoU/f018Pq+5ObkMfru58hev4kKFctxxBF1eeKpm/fp/1tCzHF/i3cY/iZrqplJ4dHJ3QPfp1Ynyb957//C9ej3f5IsIhKt9neSXJoicVVbETkwf2WSHAkHOkmW0rU/k+Rw2JdJcjhpklz6LEySA3ufZOfcwt3dBaREskVEREREREQEApwkUzgR7gJk77LdAV9EPkdERERERCT6hPm6aQedICfJU4FE7/03u97hnPs48jkiIiIiIiIS7QKbJHvvL9/DfedHskVEREREREQEgl1JFhERERERkYDpbOuSgnyfZBERERERERFTtJIsIiIiIiISxWK0lFyCVpJFREREREREQjRJFhEREREREQnR6dYiIiIiIiJRTGdbl6RJsohIhGzOXRF0AgAV4usEnSBi1oacn4NOACApoWHQCaQeUT/oBAAmLE4POoGrjqwXdIIZVQ45IugEkbDT6dYiIiIiIiJyUHDOPeOcW+uc+67YtirOuenOuaWh/60c2u6ccw8755Y55xY65479K2NokiwiIiIiIhLFnLNz+wueBU7fZdtNwAzvfWNgRuhzgDOAxqFbKvD4XxlAk2QRERERERE5KHjvZwPrd9ncE3gu9PFzQK9i2yf5Ql8CSc65mnsbQ5NkEREREREROZileO/XhD7OAFJCH9cGil8UZmVo2x5pkiwiIiIiIhLFnKWbc6nOuXnFbqn78v/Fe+8Bvz/7YSdd3VpERERERERM8N6nAWn7+GWZzrma3vs1odOp14a2rwKKv63HoaFte6SVZBERERERETmYvQ1cHPr4YmBKse39Q1e5PgHYWOy07N3SSrKIiIiIiEgU+2sXlbbBOfcy0B6o6pxbCdwO3Au85py7HFgO9A09/F2gK7AM2AZc+lfG0CRZREREREREDgre+/N2c1fHP3msB67Z1zGi9nTr2bPn06XLVXTunEpa2utR3WGhwUqHhQYrHRYarHQE2ZCfX8D5fUZz/T8fA2Dk8Emc2eVWzu89mvN7j+bHJSv28gyly8LxsNJhocFKh4WGIDt6dbmD888aw4V97uPifuOKtr/24mz69hjNub3u5ZEH3o5YD9g4JpFs+PCRF5lw8c1MGji6xPavp37Cs9fcyXPX3s3sZ98CYGNmFg/3HcwL19/LC9ffy0ePvxLWNrBxPKx0qMGmGGfnZkFUriTn5+czatQEJk68k5SUZPr0GUyHDm1o1OiwqOuw0GClw0KDlQ4LDVY6gm54+YVZ1G9Qg61bdhRtGzjkLDqddmxExi8u6H1hqcNCg5UOCw0WOh575hqSKicWfT5vzlJmz/qOF968gYSEONZnbY5IBwS/L4JoaNqhDS27tuODh54v2rZi0U/8PGchFz54E3Hx8Wzb8N9jkFSjKhc+eFNYWnZl4XhY6VCDHCwCW0l2zlVyzt3rnFvinFvvnMtyzi0ObUsK59gLFy6lbt2a1KlTg4SEeLp1a8eMGV+Fc0izHRYarHRYaLDSYaHBSkeQDZkZ2Xw++zt69T4pIuPtjYXjYaXDQoOVDgsNljp2+vern9P/8o4kJBSuR1RJrhCxsS3si0g3HNqsEWUSy5XY9u17n3F8787ExccDUC4pcsegOAvHw0qHGuRgEeTp1q8B2UB7730V730ycGpo22vhHDgzM4saNaoWfZ6SkkxmZlY4hzTbYaHBSoeFBisdFhqsdATZMG7MGwwcfBbOlTz36LGH3+bcs+5i3Jg3yMnJjUgL2DgeVjosNFjpsNAQeIdzDPy/CfTvez+TX/8CgN+Wr+WbBb9w2fkPcNUlj/DDd79FpgUbx8RCw4bVa1n1w8+8POx+Xhv+EBlLlxfdtzEzixcGjeG14Q+x8vtlYe2wsC+sdKjBrsDfG7nYzYIgT7eu570fU3yD9z4DGOOcuyygJhEREz79eBFVqiRyZLPDmDfnp6LtA67vSXLViuTm5nH3yJd47unpXHl11wBLRSTtuYFUT0lifdZmrk19nHr1U8jPL2DTxm08/eIgfvjuN24Z+iyT37v1f/7RS8KnoKCAPzZv49z7hpC5dDnTxj7DZU+MpHyVilzx5CjKVixP5rLfePueJ+n/yC0cUq5s0MkiYkSQK8nLnXM3OOdSdm5wzqU4524EdnslGudcqnNunnNuXlraq/s1cEpKMhkZvxd9npmZRUpK8n4914Gw0GGhwUqHhQYrHRYarHQE1fDt1z8z++NF9DhtBMOHPcPcOT9y640TqVqtEs45EhLi6dGrLd8vSg97y04WjoeVDgsNVjosNATdUT2l8LfEqiRXoH3H5nz/3XKqpyTRvlMLnHM0a16XGOfYkL01Ij0WjomFhsTkJBq1bYlzjhpN6uFcDNs3bSEuPp6yFcsXdjY6jKQaVclevS5sHRb2hZUONcjBIshJcj8gGfjEOZftnFsPfAxU4b/va/U/vPdp3vtW3vtWqan99mvg5s0bk56+mhUrMsjJyWXatNl06NB6v57rQFjosNBgpcNCg5UOCw1WOoJqGDCoF+/OGM07H97F3WMv4/jWh3PnmEv5fd1GALz3fDLzWxo2rhX2lp0sHA8rHRYarHRYaAiyY/u2P9i6dUfRx1998SMNG9XklA7NmT9nKQC/pa8lNzefpMrlw94DNo6JhYaGbVqwYlHhMchetZb8vDzKVkxk28bNFOQXALAh43ey16wjKYyTJAv7wkqHGuxyzpu5WRDY6dbe+2zn3ERgOvCl937Lzvucc6cD74dr7Li4WG677SquuOJ28vML6N27E40b1w3XcKY7LDRY6bDQYKXDQoOVDgsNxY24cSLZ2Vvw3nP44Ydy8+27e6vA0mdlX1josNBgpcNCQ5Ad67M2c8P1zwCFb9nWpeuxtP3HkeTm5nHXrS9z3ln3Eh8fx+13nx+xU60tHJNIN7w7biIrvlvGjk1bePLyW2l7bleO6ngCH/7rRSYNHE1sXCxdrrsQ5xyrvv+ZL16eRmxsLC7G0fGqfpSpEL5/wLBwPKx0qEEOFq7w/ZUDGNi5gRS+sfNi4GjgOu/9lNB9C7z3f+H9TX6y8U8NIiJ/webcyL6n8e5UiK8TdIKIWRtyfg46AYCkhIZBJ5gxYXF60AlcdWS9oBPErCZ/iwsNLNv0jpl5VaOKPQLfp0FeuOtK4Djv/RbnXD3gDedcPe/9Q9i5sJmIiIiIiMjfmiZfJQU5SY7ZeYq19z7dOdeewolyXXScREREREREJABBXrgr0zl39M5PQhPm7kBVoHlgVSIiIiIiIlHEOTs3C4KcJPcHMopv8N7nee/7A+2CSRIREREREZFoFuTVrVfu4b7PI9kiIiIiIiIiAsH+TrKIiIiIiIgELMjTiy3SHxmLXQAAIABJREFU/hAREREREREJ0SRZREREREREJESnW4uIiIiIiEQxK1eVtkIrySIiIiIiIiIhmiSLiIiIiIiIhOh0a5EwyCnYHHQCAAkxFYJOkGIqxNcJOkFE9qJSQr2gE2QXVx1ZL+gEjn0pM+gEAL7oFx90ArGuTNAJAMTHlAs64W9FZ1uXpJVkERERERERkRCtJIuIiIiIiEQxXbirJK0ki4iIiIiIiIRokiwiIiIiIiISotOtRUREREREopjOti5JK8kiIiIiIiIiIZoki4iIiIiIiITodGsREREREZEoFqPzrUvQSrKIiIiIiIhISNROkmfPnk+XLlfRuXMqaWmvR3WHhQYrHUE1ZKzJ4rKL76Jn92H06j6MFya9B8DGDVu48rLRdOsyiCsvG83GjVsi1mTheFjpsNBgpcNCg5UOCw1WOiw0WOrIz8/nrF6D+L//uyuwBgv74uabH6Jt2wvp3v2aQMbfKVL7IqVcAk90bM4b3Y7j9a7Hct7htQC496QjePmMY3j5jGOYeubxvHzGMUVf0zipHM+e1pLXux7Lq12PJaEUl/My1mRx+SX3cFb3mzmrx828+PyHAPy45DcuOm8UvXsO59p/jmfLlu2lNuafGTH8cdqddCW9egwpsf3FF96jR9dB9Ow+hHFjXwhrw64s/PkQ20xOkp1z74Xz+fPz8xk1agJPPTWSadMeZerU2Sxb9ls4hzTbYaHBSkeQDbGxMQy94QKmTB3Li6+O4pWXpvPzspU8/eTbtGl7FNM+GE+btkfx9JPvRKTHwvGw0mGhwUqHhQYrHRYarHRYaLDUATBp0lQaNDw0kLHBzr44++yOPPXUyIiPW1wk90V+gWf8gl/oM20+F3/4LX0b16R+xXLc9PkSznvva85772tmrPidmSuyAIh1cFfbI7h7zjLOeXcBqR8tJM/7UuuJjYtl6A3nMXnqPbzwym288tJH/LxsFXfc9gzXDe7Lm1PupkPH43j2mXdLbcw/06vXKUxIu7nEtjlffcesGfN48637mDJ1HJdc1iOsDcVZ+fNhjTN0syCwSbJz7tjd3I4Djg7n2AsXLqVu3ZrUqVODhIR4unVrx4wZX4VzSLMdFhqsdATZUK16ZZo2qw9A+fJlqd+wNpmZ2cyaOZ+ePU8GoGfPk5k1Y15EeiwcDysdFhqsdFhosNJhocFKh4UGSx0ZGb/zycfzOKdP54iPvZOVfXH88UdRqVKFiI9bXCT3xe87clmSvRWAbXn5/LppO9XLJZR4TOfDqvH+8rUAnFCzMks3bGXphsKv2ZiTR0HpzZGpVi2JI5vWAwp/tmjQoBZr12azPD2D41odDkDbE5sx48Pw/mzR6vimVEpKLLHt1Vemc/mVPUlIiAcgOblSWBuKs/LnQ2wLciV5LnA/MG6X2/1AUjgHzszMokaNqkWfp6Qkk5mZFc4hzXZYaLDSYaEBYNWqdSxZnE6Llg3JytpIteqVAahaLYmsrI0RabCyLyx0WGiw0mGhwUqHhQYrHRYaLHWMHv00Q4ddjAvwKjhW9oUFQe2LmuUP4fDK5fnu981F246tVpH1O3JYsXkHAHUrlMXjefTUo3jx9GO4+MjwnX1Q+LPFcpq3aEjDRrWZNWMBAB9+MJeMjPVhG3d30tPXMH/+Es7rN5xLLhrJokXLIja2/nz8Oee8mZsFQU6SFwP/570/ddcb8HuAXSKB2bZ1B4MGjufGmy4iMbFcifucc3bOQRERkf8xa9ZckqtU4qijGgWdIgEqGxfD/Scfybj5v7A1L79oe5d61Xl/+bqiz2Od4+hqlRj+xRIun/4tp9ZJpnVK6a8Tbdu6gyHXPcKwmy8gMbEsd9x1Oa++MoNz+9zGtq3biY+PLfUx9yY/L59NG7fw0it3MWTYhQwd9CC+FE81FzlQQU6SR+5h/Gt390XOuVTn3Dzn3Ly0tFf3a+CUlGQyMv47D8/MzCIlJXm/nutAWOiw0GClI+iG3Nw8Bl03nm49TqLTaa2BwtOP1q3NBmDd2mySq0TmdKSg94WlDgsNVjosNFjpsNBgpcNCg5WOBQuWMHPmXDp0uJIhg8fx1ZcLGTZ0fEQbwMa+sCLS+yLOOe4/uSnvpq9j5sr/rk7GOuhwaDIfFpskZ27PYcHajWz4I48d+QV8tno9R1QpX6o9ubl5DL7+Ebp2P5FOnVsBUL9BLZ546gZeeWMUp3dry6GHVS/VMf+KlBrJdOrcGucczVs0wsXEkJ29ee9fWBpj68+H/AWBTZK9928AzjnX0TmXuMvdO/bwdWne+1be+1apqf32a+zmzRuTnr6aFSsyyMnJZdq02XTo0Hq/nutAWOiw0GClI8gG7z23j0ijQYPaXHxJt6Lt7Tscy5QpnwIwZcqnnNrhuIj0WDgeVjosNFjpsNBgpcNCg5UOCw1WOoYMuYhPZj/NzJlPMu6BIbQ5oQVj7x8U0QawsS+siPS+uO2Exvy6cRsvLllVYnubGpVJ37Sdtdtzirb9Z3U2jZLKUyY2hlgHx1WvxC8bt5Vai/eekbc+TYMGteh/yelF27OyNgFQUFDAkxOmcE7fDqU25l/VoePxzPnqBwDSf11Nbm4elStH5vfX9efjzwV9sS5rF+6KC2pg59xA4BoKT7t+2jl3nfd+Suju0cD74Ro7Li6W2267iiuuuJ38/AJ69+5E48Z1wzWc6Q4LDVY6gmz4esGPvPP2ZzRuUoc+ZxVeAXLg9X25/IozGTr4YSa/MYuataoybvx1EemxcDysdFhosNJhocFKh4UGKx0WGix1WGBlXwwePJY5cxaRnb2Jdu0u4dprz+ecc06LaEMk98XR1SrSvX4KS7O3Fr3N07++Tefz1dmcVve/F+zaaXNuHi8uWcnzXY7GA5+vXs9nq7NLrefrBUuZ+vYXNG5yKH3PuhWAa6/vw2+/ZfLKSx8B0LFzK3qdfXKpjflnhg15iLlzfmDDhs10bH81/xxwDmeffSojRjxOrx5DiI+PY/Q9/yz8tbIIsPLnQ2xzQZ3/75xbBLT13m9xztUD3gCe994/5Jz72nt/zB6fAICf9MsLYlJOQWROGdqbhJhgryoqInKw8eTv/UER4Ij874nK7h37UmbQCQB80S8+6ARiXZmgEwCIjym39wdFRBMri58HJHP722bmVSllzwx8nwa2kgzEeO+3AHjv051z7YE3nHN1sbPSLiIiIiIi8rcWoYX8g0aQF+7KdM4VvR9yaMLcHagKNA+sSkRERERERKJWkJPk/kBG8Q3e+zzvfX+gXTBJIiIiIiIiEs0CO93ae79yD/d9HskWERERERGRaKWzrUsKciVZRERERERExJQgL9wlIiIiIiIiAdPKaUnaHyIiIiIiIiIhmiSLiIiIiIiIhOh0axERERERkSim90kuSSvJIiIiIiIiIiFaSRYJg4SYCkEniIjIfsgvyAk6AYC4mLJBJ5iRU7A56AS+OtfG3+uv/JIZdAIXNaoSdIJI2GmSLCIiIiIiEtV0vnVxOt1aREREREREJESTZBEREREREZEQnW4tIiIiIiISxZxOty5BK8kiIiIiIiIiIVpJFhERERERiWLOae20OO0NERERERERkRBNkkVERERERERCdLq1iIiIiIhIVNOFu4qL2pXk2bPn06XLVXTunEpa2utR3WGhwUqHhQYrHRYarHRYaLDSYaHBSoeFBisdFhqC6hgx/DFOPukKevYYUrTt0X+9xqmn/B9nnzWMs88axuxPFkSkpTgLxySIhow1WVx28V307D6MXt2H8cKk9wDYuGELV142mm5dBnHlZaPZuHFLWDtGDH+cdiddSa9irwuAF194jx5dB9Gz+xDGjX0hLGO/8+CLPHD+LTzxz3uKtn3y4rs81P9WnhwwhicHjGHZ3O8B2JCZxb1nDSna/u6/Xg1LU3HR+tqUg0tUriTn5+czatQEJk68k5SUZPr0GUyHDm1o1OiwqOuw0GClw0KDlQ4LDVY6LDRY6bDQYKXDQoOVDgsNQXb06tWe888/nZtverTE9v4Xd+PSy84M69i7Y+GYBNUQGxvD0BsuoGmz+mzdup1+vYfT9sTmTJk8mzZtj+KKK8/kqSff5ukn32Hw0PPC1tGr1ymcf34Xbin2upjz1XfMmjGPN9+6j4SEeLKyNoZl7Bad2tCqezvefqDkJLx1z/a07d3xfx5fuWZVrvzXjWFp2VU0vzbl4BLYSrJzrqJz7h7n3PPOufN3ue+xcI69cOFS6tatSZ06NUhIiKdbt3bMmPFVOIc022GhwUqHhQYrHRYarHRYaLDSYaHBSoeFBisdFhqC7Gh1fFMqJSWGfZx9YeGYBNVQrXplmjarD0D58mWp37A2mZnZzJo5n549TwagZ8+TmTVjXlg7/ux18eor07n8yp4kJMQDkJxcKSxj1z2qEWUrlAvLcx+oaH5tWucM/WdBkKdbT6Tw5Pc3gXOdc2865w4J3XdCOAfOzMyiRo2qRZ+npCSTmZkVziHNdlhosNJhocFKh4UGKx0WGqx0WGiw0mGhwUqHhQZLHTu99OIHnNVzKCOGPxb2U3t3ZWFfWGhYtWodSxan06JlQ7KyNlKtemUAqlZLCtsq7p6kp69h/vwlnNdvOJdcNJJFi5ZFdPx5Uz8l7Zp7eefBF9m+eVvR9g0ZWTx57Rgm3fgQv333c1gbLLwuLDSIfUFOkht672/y3r/lvT8TWADMdM4lB9gkIiIickD6nXsa73/4CG9Ovo9q1Soz9r5JQSdFnW1bdzBo4HhuvOkiEhNLrqo65wK5RlF+Xj6bNm7hpVfuYsiwCxk66EG89xEZ+7iu/+Cap27jykduILFyJT56ejIAiVUqcu2zd3DlIzfS+YqzmDz2Of7Ytj0iTSKWBTlJPsQVe9dq7/3dwJPAbGC3E2XnXKpzbp5zbl5a2v5dXCAlJZmMjN+LPs/MzCIlJfJzcwsdFhqsdFhosNJhocFKh4UGKx0WGqx0WGiw0mGhwVIHQNWqScTGxhATE0OfczqyaGF4V+d2ZWFfBNmQm5vHoOvG063HSXQ6rTVQeGrzurXZAKxbm01ylfCc6rwnKTWS6dS5Nc45mrdohIuJITt7c0TGTqxckZjYGFxMDMec3pbVP/0GQFx8POUqlgegZuPDqFyzKlmr1oWtI9pfm7Y5Q7fgBTlJfgfoUHyD9/5ZYAiQs7sv8t6nee9bee9bpab226+BmzdvTHr6alasyCAnJ5dp02bToUPr/XquA2Ghw0KDlQ4LDVY6LDRY6bDQYKXDQoOVDgsNVjosNFjqAIomYwAfTZ9D48Z1Ijq+hX0RVIP3nttHpNGgQW0uvqRb0fb2HY5lypRPAZgy5VNO7XBc2Ft21aHj8cz56gcA0n9dTW5uHpUrV4jI2JvX//f08h+/WEi1ujUB2LpxMwX5BQBkr/md7NXrqFwjfBPGaH5tysHFReo0jz8d3LkjgNrAV977LcW2n+G9f2/vz/DTfsd/8sk8Ro9+kvz8Anr37sTVV+/fhPtAWeiw0GClw0KDlQ4LDVY6LDRY6bDQYKXDQoOVDgsNpdWRV7Bvp5oOHfIgc+f8wIYNm0lOrsQ1A/oyd873LFmSjnOOWrWrMXJkatHvw/5VcTFl9+nxu7JwTEqrIafgr6+2Lpi/hIsvHEXjJnWIiSlcCxp4fV9atGjE0MEPs2b179SsVZVx46/bpwuuOWL3qXnYkIdKvC7+OeAczjyzHSNGPM6Pi9OJj49j6A0X0eaEo/bpeV/5JXOvj/n3mGf5bdEytm3aQvmkCrS7oCvLFy0l85dVOOeoVL0KXa/tR4UqlVj8+Td88sK7xMbG4mIc7S44gyZtmu/x+S9qVH+fmnf1d3ptFmpiY+nzAG3M+SC4SeEuKiV0CXyfBjZJds5dCwwAFgNHA9d576eE7lvgvT9278+y/5NkERERkV3t6yQ5XA50kvx3si+T5HDZ10lyuPyVSXK4Hegk+e/n7zFJ3pQ73cy8qmJ858D3aZDvk5wKHOe93+Kcqwe84Zyr571/CCsno4uIiIiIiEhUCXKSHLPzFGvvfbpzrj2FE+W6aJIsIiIiIiISIZp+FRfkhbsynXNH7/wkNGHuDlQF9vzLECIiIiIiIiJhEOQkuT+QUXyD9z7Pe98faBdMkoiIiIiIiESzwE639t6v3MN9n0eyRUREREREJFo5nW5dQpArySIiIiIiIiKmaJIsIiIiIiIiEhLk1a1FREREREQkYDrduiStJIuIiIiIiIiEaJIsIiIiIiIiEqLTrUVERERC4mLKBp1gRl7B9qATAEiIqRB0ghnd6vwRdALD560IOgGAu1vVCTrhb0Zrp8Vpb4iIiIiIiIiEaCVZREREREQkijmnC3cVp5VkERERERERkRBNkkVERERERERCdLq1iIiIiIhIVNPp1sVpJVlEREREREQkRJNkERERERERkRCdbi0iIiIiIhLFnE63LkErySIiIiIiIiIhmiSLiIiIiIiIhETtJHn27Pl06XIVnTunkpb2elR3WGiw0mGhwUqHhQYrHRYarHRYaLDSYaHBSoeFBisdFhqC6hgx/DFOPukKevYY8j/3PTvxHZod2Zfs7E0RaSnOwjEJqmHzpu3cMngS/c68j3N7jmXRt+k88a/3ubD3OPqf8wDX/V8a69ZuLPVx56U9zztX38CHN95ZtG3D8pXMvH0sH954F5/f/xi527YX3bdkyvu8N/h23h86koyFP5R6z64svCbsiTF0C15gFc65Gs65x51zjzrnkp1zI51zi5xzrznnaoZz7Pz8fEaNmsBTT41k2rRHmTp1NsuW/RbOIc12WGiw0mGhwUqHhQYrHRYarHRYaLDSYaHBSoeFBisdFhqC7OjVqz1PpN3yP9vXrPmdzz9fSM2aVcPesCsLxyTIhvFjpnDCSYfz6ts38Pwbg6hXP4ULL2nPC28OYdLrgzmpXVOeeeKjUh+37skn8I8bBpTYNv+pF2h+bk9OGzOCWq2O5sdpheNuWrmGFV/O57QxIzj5hgF8PfEVfEFBqTftZOE1IfYFOVV/FvgBWAHMArYDXYFPgQnhHHjhwqXUrVuTOnVqkJAQT7du7Zgx46twDmm2w0KDlQ4LDVY6LDRY6bDQYKXDQoOVDgsNVjosNFjpsNAQZEer45tSKSnxf7aPufc5hgy9AOcif2EgC8ckqIYtm7fzzfxf6HF2awDi4+OoULEs5RPLFD1m+/acsFyuqdqRjUlILF9i2+Y1a6l6RGMAUpofwao5XwOwev631DnhOGLj4ylfvSqJKdVY/3N6GKoKWXhNWOQM/WdBkJPkFO/9I977e4Ek7/0Y7/0K7/0jQN1wDpyZmUWNGv/918yUlGQyM7PCOaTZDgsNVjosNFjpsNBgpcNCg5UOCw1WOiw0WOmw0GClw0KDpQ6AmTPmkpJShSOOqBfI+Bb2RVANq1etJ6lKInfd+ir9+45n9O2vs31bDgATHn6Pnp3v4sNpC7jymi5hbwGoeGhNVs//FoCVX33N9vXZAGzP3kjZ5MpFjytbJYnt6zeErcPCa0LsC3KSXHzsSbvcFxvJEBEREREpXdu3/0Fa2mQGXNsv6JSolJ9fwE+LV3F23xOZ9NogypZNYNIzMwG4auAZTJk+gtO6HcsbL38ekZ5WqRfx8/TZfDT8HvK27yAmTu9EK3YFOUme4pxLBPDej9i50TnXCPhxd1/knEt1zs1zzs1LS3t1vwZOSUkmI+P3os8zM7NISUner+c6EBY6LDRY6bDQYKXDQoOVDgsNVjosNFjpsNBgpcNCg5UOCw2WOlasyGTVyrWc3WsYnTteQ2ZmFn1638i6deFbJdyVhX0RVEP1lEpUS6lEsxaHAXBq5+b8tHhVicd06XYMH3+0KOwtABVr1aDdzQPpdPfN1DmxFeWrF67mlq1cie1Z2UWP275+A2WrJIWtw8JrwiLnnJmbBYFNkr33twGHOuc67pwsh7YvA57aw9elee9bee9bpabu379MNm/emPT01axYkUFOTi7Tps2mQ4fW+/VcB8JCh4UGKx0WGqx0WGiw0mGhwUqHhQYrHRYarHRYaLDSYaHBUkeTJofx6edPMX3Go0yf8SgpKcm88eYYqlUL3wRoVxb2RVANyVUrkpKSxPJf1wIw76tl1GuQworl64oe8+ms76lbv3rYWwB2bNwMgC8oYPFb79Gg48kA1DyuBSu+nE9+bi5b1/7Oloy1VGlYL2wdFl4TYl9g5zk4564FBgCLgaedc9d576eE7h4NvB+usePiYrnttqu44orbyc8voHfvTjRuHNZfgzbbYaHBSoeFBisdFhqsdFhosNJhocFKh4UGKx0WGqx0WGgIsmPokAeZO+cHNmzYTIf2V3HNgL707tMh7OPuiYVjEmTD4Jt7MvLml8nNzaP2ockMv7Mv99z+Or+lr8PFOGrUrMwNt/Yu9XG/+tczrFv8E39s3sK0AbfQtE838nb8wc/TZwNQ+/ijqXdKWwAqHVqLQ9scy4c33ImLjeHoS87FxYRvHc/Ca0Lsc977YAZ2bhHQ1nu/xTlXD3gDeN57/5Bz7mvv/TF7f5afgokXERER+ZvLK9i+9wdFQFxM2aATzFj/x5KgExi3qPzeHxQBd7eqE3RCSBMb5wcfoB35X5qZV5WJPSHwfRrkb8zHeO+3AHjv051z7YE3nHN1wci1v0VERERERCSqBHnhrkzn3NE7PwlNmLsDVYHmgVWJiIiIiIhI1ApyJbk/kFd8g/c+D+jvnHsimCQREREREZHo4gJdO7UnsEmy937lHu6LzBu2iYiIiIiIiBSjd/EWERERERGJarokVHFaVxcREREREREJ0SRZREREREREJESnW4uIiIiIiEQx53S6dXFaSRYREREREREJ0SRZREREREREJMR574NuOAA/HczxIiKB8AT/rdPpKppi1Na8NUEnAFAmtnLQCeT73KATAEiIqRB0ArkFW4NOACDWHRJ0AjHOxm9r9p6RGXQCAG92PPlv8RdaTsH84H84CEmIOS7wfaqVZBEREREREZEQTZJFREREREREQmycLyEiIiIiIiKBcFo7LUF7Q0RERERERCREK8kiIiIiIiJRLfBrZZmilWQRERERERGREE2SRUREREREREJ0urWIiIiIiEgUczrdugStJIuIiIiIiIiEmFpJds5V996vjcRYs2fP5+67n6SgoIBzzulMauo5kRjWZIeFBisdFhqsdFhosNJx880P8fHHc0lOrsTUqY9GfPydgt4Xa9as48YbHiQrawPOQd++Xeh/8ZkRbdgp6H1hpcFKh4WGoDr++COXK/qPJScnj/z8fDqedhxXDziTOV8u4cH7Xyc3N58jm9bltjv7ExcXG7aO4bc8xicfz6dKciXefucBAMbeN4mPZ80nPj6OOoelcPfoa6hYsXzYGjLWZHHLTY+TlbURB/Tp24EL+5/BB+9/yeP/epNfflnNy6/dSbOjGoSt4c8E8boYMXwCsz9eQJUqFXnrnfsBWLJkOXeOfIpt23ZQq3Y1xowdQGJiubC37PTrL6sYPPj+os9XrMjk2oHncfHFPSLWAJE7Hjnr17PquafJ27wJnKPySe2o2qETme+8xaZvv8bFxBCbWIFD+19GfFISf2SsYeXzE9mx4jdSepxF1c5dwtIlB4fAVpKdc1V2uSUDc5xzlZ1zVcI5dn5+PqNGTeCpp0YybdqjTJ06m2XLfgvnkGY7LDRY6bDQYKXDQoOljrPP7shTT42M+LjFWdgXsbGx3HjTZUx791FeeXUsL770btS+Liw0WOmw0BBkR0JCHE88M5hXJ9/Gy2/eyn8++45vv/6Z24dP5J77U3l9ykhq1qrC1Cn/CWvHWWe1J+3J4SW2nXhiS6a88wBvvT2OevVq8WTa5LA2xMbGMPSGC5gydSwvvjqKV16azs/LVtK4cR3GPzKI41odEdbx/0xQr4tevU5hQtrNJbbdfusTXD/4PCa/PZaOnY5n4tPvhL2juPoNajP5rfFMfms8b7x5P2XLHkKnTm0i2hDJ4+FiY6jRuy+Nb7uTBsNuYf3sWexYs5qqnbrQeMQdNLrldio2b8HadwuPQ2z58tQ85zyqdjwtLD3WOefM3CwI8nTr34H5xW7zgNrAgtDHYbNw4VLq1q1JnTo1SEiIp1u3dsyY8VU4hzTbYaHBSoeFBisdFhosdRx//FFUqlQh4uMWZ2FfVK9ehWbNGgKQmFiOhg0OJTMzK6INYGNfWGiw0mGhIcgO5xzlypcBIC8vn7y8fGJiHfHxsdStlwJAmxObMmP6grB2tDq+KZUqJZbYdtI/WhatXrds2ZiMjPD+ea1WvTJNm9UHoHz5stRvWJvMzGwaNKxN/fq1wjr27gT1umh1/JFUSiq5ar88fQ2tjj8SgLYnNmf69Dlh79idL/+ziDp1alC7dvWIjhvJ4xFfKYmyh9UFILZMGQ6pUZO8DdnEli1b9JiCP3LYOSeLq1CRcvXqQ2z4zviQg0eQk+RhwI/Amd77+t77+sDK0MdhPQ8nMzOLGjWqFn2ekpIcyA96FjosNFjpsNBgpcNCg6UOC6zti5UrM1m8+Bdatjw84mNb2BcWGqx0WGgIuiM/v4Bzzx5Fp5OH0qZtU45qXp+8vAJ++C4dgBkfziczY31EWnbn32/O4uR2x0RsvFWr1rFkcTotWjaM2Jh/xsrrE6Bho0OZOaNwHejDD74iY01w38PfffdTunU7OeLjBnU8crJ+Z8eK3yhbr3CKkTnl3yy5ZRgb5n5J9e69wj6+HHwCmyR778cBVwC3OececM5VAHxQPSIi8tds3bqdgQPv5eZbrojo79OJWBUbG8Mr/76N92eO4ftFv/LzstXcc/+V3D/mNS7qN5py5coQExPcusSECW8SGxdDjx6RmRRt27qDQQPHc+NNF+l7RDF33n0Vr7z8IX1738zWrduJjw/m0kA5ObnMnDmXLqefGMj4kZa/Ywe/pT1GjT79ilaRU3orFWPOAAAXNUlEQVSezRGjx5J0/AlkfTIz4EIrYgzdghdohfd+pff+HOBjYDqw1++kzrlU59w859y8tLRX92vclJRkMjJ+L/o8MzOLlJTk/XquA2Ghw0KDlQ4LDVY6LDRY6rDAyr7Izc1j4MB76dHjFE47LZgfsCzsCwsNVjosNFjpqFCxHK1aH8EXn31Py6Mb8szzN/D8q7dwbKvGRadeR9rkf8/ik1nzuW/sdRH5Xb/c3DwGXTeebj1OotNprcM+3t5YeF3s1KBBbZ58ejivvXkPXbueSJ3DgnlNfPrpApo2bUDVqkkRHzvSx8Pn57HiycdJan0ClY457n/ur9S6DZu+nh+28eXgFegk2Tl3hHOuIzATOBXoFNp++u6+xnuf5r1v5b1vlZrab7/Gbd68Menpq1mxIoOcnFymTZtNhw6R/0ZuocNCg5UOCw1WOiw0WOqwwMK+8N4zYvgjNGxwKJdeGtzpaRb2hYUGKx0WGoLsyF6/mc2btgGwY0cOX/7nB+rVr8H6rE1A4ards09/QO++p4S9ZVeffvo1Tz89hUcfv5GyZQ8J+3jee24fkUaDBrW5+JJuYR/vr7Dy+gTIytoIQEFBAU9MmEzffp0C6Zg27bNATrWGyB4P7z2rnn+OQ2rULHExrj/WZhZ9vPnbbzikRs2wjH+wcYb+s8B5H8wZzs65gcA1wGLgaOA67/2U0H0LvPfH7v1Zftrv+E8+mcfo0U+Sn19A796duPrq/ZtwHygLHRYarHRYaLDSYaHBSsfgwWOZM2cR2dmbSE5O4tprz+eccyJ/9cvS2hd+P3+zZf68H7jggpto0qRu0amjgwZfxCmntNrn5zrQvwQtvC4sNFjpsNBQWh1b89bs0+N/+nElt98ykfyCAnyBp3OXVqT+szvj73+DTz9ZiC/w9Ol3Chf037cJUZnYyvv0+KGDH2TO3O/ZkL2Z5ORKDLi2L2lpk8nNyaNSUuEFvVq2bMLIO1L/8nPm+9x9algwfwkXXziKxk3qFH2PGHh9X3Jz8hh993Nkr99EhYrlOOKIujzx1M17ebb/Sog5sAsnlsbrIrdg6z49ftiQh5k75wc2bCg8Hv8c0Idt23bwyksfAtCpc2uuH3zePq/ux7oD+8eObdt20OHUK5n+0QQqVNi/twOLcQd2mnhpfb/oPSNzj/dvXbaUXx8YwyG1auNCr8eUM88i+4vP+CMzA5wjoUoytc6/iPikyuRu3MjPY+6iYMd2cI6YQ8rQ+NZRJS709Wfe7HiyjVndASrw35v5tdcY1yzwfRrkJHkR0NZ7v8U5Vw94A3jee/+Qc+5r7/1fuLrE/k+SRUSi1f5OkkuTlX8pFtnVvk6Sw2VfJ8nhsK+T5HA50ElyadjXSXK4HOgkuTQc6CS5tOxtkhwpmiSXPguT5CBf5THe+y0A3vt051x74A3nXF3QT08iIiIiIiKRoelXcUH+TnKmc+7onZ+EJszdgapA88CqREREREREJGoFOUnuD2QU3+C9z/Pe9wfaBZMkIiIiIiIi0Syw06299yv3cN/nkWwRERERERGJVpF4i7iDiY13axYRERERERExQJNkERERERERkRAb13AXERERERGRgGjttDjtDRERERERETloOOdOd8796Jxb5py7qbSfX5NkEREREREROSg452KBR4EzgKbAec65pqU5hk63FhERERERiWKOg+rq1q2BZd77XwCcc68APYEfSmsArSSLiIiIiIjIwaI2sKLY5ytD20rNQb6S3OSA/8nDOZfqvU8rjZqDucFKh4UGKx0WGqx0WGiw0lEaDaXxb8V/l33xd+mw0GCl40Abysc1MdFhoSG2lBaW/g77Ir6UlpX+DvvCSsebHQ/8z6qVfWHDgc+rSotzLhVILbYpLdLHSSvJJQ9AUCw0gI0OCw1go8NCA9josNAANjosNICNDgsNYKPDQgPY6LDQADY6LDSAjQ4LDWCjw0ID2Oiw0CC78N6nee9bFbvtOkFeBdQp9vmhoW2lRpNkEREREREROVjMBRo75+o75xKAc4G3S3OAg/x0axEREREREYkW3vs859wA4AMgFnjGe/99aY6hSTJY+D0ECw1go8NCA9josNAANjosNICNDgsNYKPDQgPY6LDQADY6LDSAjQ4LDWCjw0ID2Oiw0AA2Oiw0yH7w3r8LvBuu53fe+3A9t4iIiIiIiMhBRb+TLCIiIiIiIhIStZNk59zpzrkfnXPLnHM3BdTwjHNurXPuuyDGDzXUcc7Ncs794Jz73jl3XUAdZZxzc5xz34Y67giiI9QS65z72jk3NcCGdOfcIufcN865eQE1JDnn3nDOLXHOLXbOtQ2g4fDQPth52+Scuz6AjkGh1+V3zrmXnXNlIjTu/3yPcM5Vcc5Nd84tDf1v5QAazgntjwLnXKtwjr+XjrGh1+dC59xk51xSQB13hhq+cc596JyrFemGYvcNcc5551zVSDc450Y651YV+/PaNZwNu+sIbb829Nr43jl3X6QbnHOvFtsP6c65b8LZsIeOo51zX+78u8Q51zqAhpbOuf+E/k57xzlXMcwNf/pzTQDfO3fXEbHvn3toiOj3zj10ROx75+4ait0fke+dchDx3kfdjcJf8P4ZaAAkAN8CTQPoaAccC3wX4L6oCRwb+rgC8FNA+8IBiaGP44GvgBMC2ieDgZeAqQEel3SgalDjhxqeA64IfZwAJAXcEwtkAHUjPG5t4FegbOjz14BLIjT2/3yPAO4Dbgp9fBMwJoCGI4HDgY+BVgHui9OAuNDHY8K9L/bQUbHYxwOBCZFuCG2vQ+FFTJaH+/vHbvbDSGBoJF4Pe+k4Ffjo/9u7+2i75juP4+8PSdTTRCKlNJ2RUamZdopEWlUSEhRtE/ow46FdNLWmUtbCdKlBSlBrdKplLGvRDimrHqqNNFizQhDqofWUEA+VqoxIQiRC80BHBN/54/c7sp2cc+69OHuf635ea521z91Pv+/e+97f3d+9f/u3gU3yz9tUcTwK038CnFHRvpgFHJS/HwzcWUEMDwJj8veJwDltjqHheU0FdWezOEqrP1vEUGrd2SKO0urOZjHkn0urO/3pPZ++eif5M8DTEfG/EfE68CtgQtlBRMRdwMtll1sXw9KImJu/rwGeJCUFZccREfFK/rF//pT+wLykocAXgcvKLruTSBpIOtm5HCAiXo+IldVGxThgQUQ8W0HZ/YBNJfUDNgOeL6PQJnXEBNIFDPLwkLJjiIgnI+JP7Sy3m3HMiog38o/3kd6TWEUcqws/bk6b664W/zsuAL7f7vK7iKFUTeKYBJwXEWvzPMsriAEASQL+Gbi2nTG0iCOA2p3bgbS57moSw3Dgrvz9VuCrbY6h2XlN2XVnwzjKrD9bxFBq3dkijtLqzi7Od0urO6336KtJ8keBxYWfl1BBYthpJO0A7Ea6i1tF+RvnJmnLgVsjooo4LiRVlG9VUHZRALMkzZFUxYvuhwEvAr9Qanp+maTNK4ij6DBKONGsFxHPAecDi4ClwKqImFV2HAXbRsTS/P0FYNsKY+kkE4GZVRUu6VxJi4EjgTMqKH8C8FxEzCu77DrH5+aTU9vdnLWF4cDeku6X9DtJoyqKA2BvYFlE/Lmi8k8Efpx/N88HTq0ghidYfyPi66S7dqWoO6+prO6s+vyqixhKrTvr46ii7izG0EF1p3WYvpokWx1JWwDXAyfWXdkrTUS8GRG7kq5ofkbSp8osX9KXgOURMafMcpvYKyJGAAcBx0kaXXL5/UhN5i6JiN2AV0nN0yqh9KL48cBvKih7EOkEbxiwPbC5pG+UHUcjERH4yjeSTgfeAK6uKoaIOD0iPpZjOL7MsiVtBpxGBcl5nUuAHYFdSReUflJRHP2AwcAewMnAr/Md3SocTgUX9womASfl382TyK2DSjYR+K6kOaRmrq+XUWir85oy685OOL9qFkPZdWejOMquO4sxkLa9E+pO60B9NUl+jndeyRyax/VJkvqTKoyrI2J61fHkZr13AAeWXPTngfGSFpKa4I+VdFXJMQBv372sNRP8LekRgTItAZYU7uZPIyXNVTkImBsRyyooez/gmYh4MSLWAdOBPSuIo2aZpO0A8rCtTUk7naSjgS8BR+YT36pdTZubkzawI+kizrxcfw0F5kr6SJlBRMSyfLHzLeC/Kb/eqlkCTM+P8TxAahlUemc8+fGMrwDXlV12wVGkOgvSRcbSj0lEzI+IAyJiJOmCwYJ2l9nkvKb0urMTzq+axVB23dmNfdH2urNBDB1Rd1pn6qtJ8oPATpKG5TtUhwE3VhxTJfLV9cuBJyPipxXG8eFa74qSNgX2B+aXGUNEnBoRQyNiB9LvxOyIKP2OoaTNJW1Z+07qYKPUHtAj4gVgsaRP5FHjgD+WGUOdKu/GLAL2kLRZ/nsZR3qWqSo3kk58ycMbKoylUpIOJD0eMT4i/lphHDsVfpxA+XXXYxGxTUTskOuvJaQOal4oM45aApIdSsn1VsEMUuddSBpO6nhwRQVx7AfMj4glFZRd8zwwJn8fC5Te7FvSNnm4ETAZuLTN5TU7rym17uyE86tmMZRdd7aIo7S6s1EMnVJ3WoeKDug9rIoPqZfHp0hXNE+vKIZrSU3S1pH+ML9dQQx7kZocPQo8kj8HVxDHp4GHcxyPU0JPoF3Esw8V9W5N6nV9Xv48UeHv567AQ/mYzAAGVRTH5sBLwMAKfx/OIv3zfhz4JbnX3BLK3aCOALYGbied7N4GDK4ghkPz97XAMuCWivbF06T+JWp1V1t7lW4Rx/X5d+NR4CZShzSlxlA3fSHt79260X74JfBY3g83AttVdDwGAFflYzIXGFvF8QCuAI5t9z7oYl/sBczJ/0/uB0ZWEMMJpPOtp4DzALU5hobnNRXUnc3iKK3+bBFDqXVnizhKqzubxVA3T9vrTn96z0cRndA6zczMzMzMzKx6fbW5tZmZmZmZmdkGnCSbmZmZmZmZZU6SzczMzMzMzDInyWZmZmZmZmaZk2QzMzMzMzOzzEmymZm97ySFpDvrxk3J4/epJqqe6aR4Je2QY7mizeVscNzMzMz6GifJZma9VE5oip83Ja2QNFvSEVXH1w6dnMQVkuopVcdiZmZm716/qgMwM7P37Kw87A/sDEwA9pW0e0T8W3VhbeBi4FfAoqoDMTMzM2vGSbKZWS8XEVOKP0saB9wKnCjpoohYWEVc9SJiBbCi6jjMzMzMWnFzazOzD5iIuB2YDwgYBe98vlbSEZLul/SKpIW15SRtJulUSY9IejVP/4OkwxuVI2mApB9IWiBpraRnJP1Q0iZN5m/6jK+knSVNlbQwr2u5pLslTcrTj5YUefYxdc3Mp9St67OSpkl6QdLrkhZL+pmk7ZvENVLSzZLWSFot6TZJn+tiN78nkraXdIakewtxPi/pGkn/2MWyO0uaIenlfJzukXRAi/kPl3SHpJWSXpP0pKTJzY5Tg+W3zMf58bx/1uRjfp2kkT3ddjMzs07nO8lmZh9MysOoG/89YH/gJuAOYCCApK2A2cBuwFxgKulC6heAayR9MiImv71yScCvSU27F5CaUg8AJgL/1KNApS8CvwE2AW4GrgW2AnYBvg9cAjxCalZ+JvAscEVhFXcW1jUR+DmwFrgRWAzsBBwDfFnSHhGxqDD/nsBtOfbpwNPArnmds3uyHT00Gvh30jG4Hnglx/k1YLykz0fEvAbLDQP+ADwG/AzYDvgXYKakIyLiuuLMkqYC3wKW5HJWAnsA5wDjJO0fEW80CzIf55uBPXO5lwFvAEOBfYG7gTnvZgeYmZl1KifJZmYfMJL2Az5BSpAfrJs8FvhcRDxcN/5CUoJ8SkT8Z2FdHwJmAKdJmhYRj+RJh5MS5PuAfSPitTz/mQ3KbBXrEOAa0v+jsRHxu7rpQwFyuY/k9S+sb2Ke5x0OXAosBMZExHOFaeOAWcB/AYfmcSJdDNgUOCQibijMf0LeJ+0yG9g2ItbUbcMuwL3AecBBDZYbDZwfEScXlrmYlMBeKmlmRKzO448mJci/BY6MiP8rLDOFdMHhONI+aeZTpAR5RkQcWhfrRuSLLGZmZh8kbm5tZtbL5WbMUySdK2ka6c6fgAsj4tm62X9enyBL2hr4BvBQMUEGyMnvKXl9xR6zv5WHp9US5Dz/y6S7lN11FPA3wCX1CXJe35IerGsSqfOyE4oJcl7P7aQ7y1+WtGUevSfpYsJdxQQ5u5h0h7wtImJ5fYKcx88jJdD7SurfYNFVwNl1yzwEXE26+15MZE8g3fWdWEyQs3OAl4Ajuxly/fJExFsR8ZduLm9mZtZr+E6ymVnvd2YeBqk57d3A5RFxVYN5H2gwbhSwMdDs9UW1ZO0fCuNGAG8B9zSY/86uQ37bHnk4swfLNFN7jniMpFENpm9D2s7hpCbCI/L4Rsn5m5LuAXZ8H+JqKDczPxbYHRjChv+ThwBL68bNbZRck/b5UaTWAFdK2ozUXH0FqQO3RiGs5Z3HtJE/kpq6Hy7p74AbSMf8oYh4vYtlzczMeiUnyWZmvVxENMyAmnihwbit83BU/jSzReH7QODliFjXzTKa2SoPn2s5V/fUtuPklnOt345aU+FlTebryXb0SKE5919IPZEvAv5KutBxCCnBbdSxVlex1rZpEOnu/4dZfxGlx/LFgrHAGaTnpX+UJ62RdCVwakS88m7Xb2Zm1omcJJuZ9S31HXlBasILcEEP3qu8ChgsqX+DRPkjPYhnZR5+lNQZ1XtR246Btedyuzn/tk2m92Q7uk1SP2AKKbEdERFL66a36lm7q1hX1Q0fjogRDebvttyk+iTgJEkfB8YA3wGOJ13k+OZ7Wb+ZmVmn8TPJZmb2AKnp9N49WGYu6X/IXg2m7dOD9dyXh406qWrkLVKT6Vbr6u52zM3DMfUTJG1M4217PwwhJZe/b5Agb8H6ZuCNjCg8U120Tx4+DJDv7j4BfFLS4PcccRYRT0fE5aR99gqp8zYzM7MPFCfJZmZ9XEQsJ3X8tHt+H+4GSaikHSUNK4z6RR6em3vArs03GJhM910JrAYmSRrdoNyhdaNeAj7WZF0XA+uAC3JP1/XrGiCpmED/HvgTMFpSfbJ3PO17Hnk5qWn1yJwU1+LrT+ppekiLZQeSmj6/TdLupA64VpF6sq75KenVVlPzK76oW26QpJZ3mSUNk/T3DSYNIjUH36BDLzMzs97Oza3NzAxSUrgTqefkb+ZOq5YB25M6dxpFeu3TM3n+a0nv5x0PPC7pBlIHX18jvQKqWwlmRKyQdAQwDbhD0kzgUVKP158mJcTF5Px24DBJN5HuBK8j9U59V0TMz+9Jngo8Ielm4Kkc19+S7jC/COycyw5J3yY9E3y9pOJ7kseRegk/sHu77x0OkbRDk2mzIuIaSReR3pP8WN53A0jvHR5Menfyvk2Wvws4RtJnSa+Kqr0neSPgO8Vm5hExVdJI4LvAAkm3kJ59Hkzap6NJFzuObbEtuwDTJT0IPAk8T3rOeQJpv/6oxbJmZma9kpNkMzMjIlZLGgP8K+lVT18FPkRKlP9Meib11sL8IenrpETvaFKSvZSUdJ0NvEY3RcT/5Luhp5CS0wNIHVrNB/6jbvYTSM9VjwMOJiWHZ5GSRyLiKknzgO+REs0DgFdJyd004Lq6su/Nd5fPZX2T7/tJzZe/wLtLknfJn0ZWkt4L/QNSwn4M6fneVaT9OzlvTzPPkJLa8/JwE9LFgrMj4pb6mSPiuHzh4VhgP1Iz75dJyfKPgUY9oBc9lMsaQ9oXg3Lcc4CLIuL96JXczMysoyiiUR8uZmZmZmZmZn2Pn0k2MzMzMzMzy5wkm5mZmZmZmWVOks3MzMzMzMwyJ8lmZmZmZmZmmZNkMzMzMzMzs8xJspmZmZmZmVnmJNnMzMzMzMwsc5JsZmZmZmZmljlJNjMzMzMzM8ucJJuZmZmZmZll/w8+Dxbg4EVeHQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.89      1.00      0.94       331\n",
            "           1       1.00      1.00      1.00       432\n",
            "           2       0.93      1.00      0.96       310\n",
            "           3       1.00      1.00      1.00       245\n",
            "           4       0.95      0.99      0.97       498\n",
            "           5       0.86      0.91      0.89       247\n",
            "           6       0.92      0.86      0.89       348\n",
            "           7       0.94      0.94      0.94       436\n",
            "           8       0.89      0.84      0.87       288\n",
            "          10       0.85      0.78      0.81       331\n",
            "          11       0.90      1.00      0.95       209\n",
            "          12       0.80      0.82      0.81       394\n",
            "          13       0.86      0.71      0.78       291\n",
            "          14       1.00      0.96      0.98       246\n",
            "          15       1.00      1.00      1.00       347\n",
            "          16       0.79      0.87      0.83       164\n",
            "          17       0.35      0.56      0.43       144\n",
            "          18       0.83      0.70      0.76       246\n",
            "          19       0.71      0.66      0.68       248\n",
            "          20       0.62      0.62      0.62       266\n",
            "          21       0.88      0.80      0.84       346\n",
            "          22       0.61      0.75      0.67       206\n",
            "          23       0.71      0.71      0.71       267\n",
            "          24       0.85      0.70      0.76       332\n",
            "\n",
            "    accuracy                           0.86      7172\n",
            "   macro avg       0.84      0.84      0.84      7172\n",
            "weighted avg       0.86      0.86      0.86      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kr9PGUQYRKFk"
      },
      "source": [
        "## CNN"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zOIldKkoVow6"
      },
      "source": [
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Conv2D, MaxPool2D, Flatten, Dense\n",
        "from sklearn.model_selection import train_test_split\n",
        "from tensorflow.keras.optimizers import Adam, RMSprop\n",
        "from tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FPQ4jaCIexU6"
      },
      "source": [
        "X_train, X_val, Y_train, y_val = train_test_split(X_train, Y_train, test_size=0.2, random_state=1)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D3b0WBsknouU",
        "outputId": "094640f0-029c-41f0-9d06-655ddc64897c"
      },
      "source": [
        "X_train.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(21964, 784)"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YwffPgVYoabZ"
      },
      "source": [
        "X_train, X_val = X_train.reshape(-1,28,28,1), X_val.reshape(-1,28,28,1)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fOPitzXksXsG"
      },
      "source": [
        "X_test = X_test.reshape(-1, 28, 28, 1)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hQQMskylbnJ8"
      },
      "source": [
        "model = Sequential([\n",
        "                    Conv2D(filters=32, kernel_size=(3, 3), activation='relu', input_shape=(28, 28, 1)), \n",
        "                    MaxPool2D(pool_size=(2, 2), strides=2),\n",
        "                    #\n",
        "                    Conv2D(filters=128, kernel_size=(3, 3), activation='relu'),\n",
        "                    MaxPool2D(pool_size=(2, 2), strides=2),\n",
        "                    #\n",
        "                    Conv2D(filters=256, kernel_size=(3, 3), activation='tanh'),\n",
        "                    MaxPool2D(pool_size=(2, 2), strides=2),\n",
        "                    ##\n",
        "\n",
        "                    Flatten(),\n",
        "\n",
        "                    ##\n",
        "                    Dense(64, activation =\"relu\"),\n",
        "                    #\n",
        "                    Dense(128, activation =\"tanh\"),\n",
        "                    #\n",
        "                    Dense(128, activation =\"tanh\"),\n",
        "                    #\n",
        "                    Dense(25, activation =\"softmax\")\n",
        "])"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GYt8PBrTgU2g"
      },
      "source": [
        "model.compile(optimizer=Adam(learning_rate=0.0005), loss='sparse_categorical_crossentropy', metrics=['accuracy'])"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v484eHg3itNN",
        "outputId": "e37faa9b-7d9c-4b99-8e83-c1a907ec71c3"
      },
      "source": [
        "history = model.fit(X_train, Y_train, batch_size = 512, epochs =20, verbose = 1, validation_data = (X_val, y_val))"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "43/43 [==============================] - 12s 57ms/step - loss: 2.4199 - accuracy: 0.3176 - val_loss: 1.5170 - val_accuracy: 0.5706\n",
            "Epoch 2/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 1.0243 - accuracy: 0.7322 - val_loss: 0.6615 - val_accuracy: 0.8412\n",
            "Epoch 3/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.4624 - accuracy: 0.9044 - val_loss: 0.3070 - val_accuracy: 0.9490\n",
            "Epoch 4/20\n",
            "43/43 [==============================] - 2s 37ms/step - loss: 0.2162 - accuracy: 0.9721 - val_loss: 0.1404 - val_accuracy: 0.9898\n",
            "Epoch 5/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0998 - accuracy: 0.9945 - val_loss: 0.0707 - val_accuracy: 0.9965\n",
            "Epoch 6/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0477 - accuracy: 0.9989 - val_loss: 0.0371 - val_accuracy: 0.9995\n",
            "Epoch 7/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0279 - accuracy: 0.9999 - val_loss: 0.0247 - val_accuracy: 0.9995\n",
            "Epoch 8/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 0.0172 - val_accuracy: 1.0000\n",
            "Epoch 9/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 0.0122 - val_accuracy: 0.9998\n",
            "Epoch 10/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 0.0100 - val_accuracy: 1.0000\n",
            "Epoch 11/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 0.0080 - val_accuracy: 1.0000\n",
            "Epoch 12/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 0.0064 - val_accuracy: 1.0000\n",
            "Epoch 13/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 0.0055 - val_accuracy: 1.0000\n",
            "Epoch 14/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 0.0047 - val_accuracy: 1.0000\n",
            "Epoch 15/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 0.0041 - val_accuracy: 1.0000\n",
            "Epoch 16/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 0.0036 - val_accuracy: 1.0000\n",
            "Epoch 17/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 0.0032 - val_accuracy: 1.0000\n",
            "Epoch 18/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 0.0029 - val_accuracy: 1.0000\n",
            "Epoch 19/20\n",
            "43/43 [==============================] - 2s 38ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 0.0025 - val_accuracy: 1.0000\n",
            "Epoch 20/20\n",
            "43/43 [==============================] - 2s 39ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 0.0023 - val_accuracy: 1.0000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 342
        },
        "id": "yD9P9IH5rvW-",
        "outputId": "6158df18-69d7-4930-fea6-c16711befe56"
      },
      "source": [
        "#Visualizing the training performance\n",
        "plt.figure(figsize=(15, 10))\n",
        "plt.subplot(2, 2, 1)\n",
        "plt.plot(history.history['loss'], label='Train Loss')\n",
        "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
        "plt.legend()\n",
        "plt.grid()\n",
        "plt.xlabel(\"Epoch number\")\n",
        "plt.ylabel(\"Loss\")\n",
        "plt.title('Loss evolution')\n",
        "\n",
        "plt.subplot(2, 2, 2)\n",
        "plt.plot(history.history['accuracy'], label='Train Accuracy')\n",
        "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
        "plt.legend()\n",
        "plt.xlabel(\"Epoch number\")\n",
        "plt.ylabel(\"Accuracy\")\n",
        "plt.grid()\n",
        "plt.title('Accuracy evolution')"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Accuracy evolution')"
            ]
          },
          "metadata": {},
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eMTKdd_Wcd_-",
        "outputId": "034d8dfc-cfbf-4b2c-bb6e-c443c5a381fe"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 26, 26, 32)        320       \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2D  (None, 13, 13, 32)       0         \n",
            " )                                                               \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 11, 11, 128)       36992     \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPooling  (None, 5, 5, 128)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_2 (Conv2D)           (None, 3, 3, 256)         295168    \n",
            "                                                                 \n",
            " max_pooling2d_2 (MaxPooling  (None, 1, 1, 256)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 256)               0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 64)                16448     \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 128)               8320      \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 128)               16512     \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 25)                3225      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 376,985\n",
            "Trainable params: 376,985\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7p9If6TjsN82",
        "outputId": "41cdc8f5-6c09-4cf7-cc54-c1b41819adc9"
      },
      "source": [
        "loss, accuracy = model.evaluate(X_test, Y_test, verbose=1)\n",
        "print(loss, accuracy)\n",
        "\n"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "225/225 [==============================] - 1s 5ms/step - loss: 0.1859 - accuracy: 0.9550\n",
            "0.1858731508255005 0.954963743686676\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "axx634e8Y1rk"
      },
      "source": [
        "Y_test_pred=model.predict(X_test)\n",
        "Y_test_pred=np.argmax(Y_test_pred,axis=1)\n",
        "\n"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "fG_oGn2pYRKz",
        "outputId": "48faef2a-00b2-4ce1-c4a9-a5590bd1e709"
      },
      "source": [
        "cf_matrix=confusion_matrix(Y_test, Y_test_pred)\n",
        "print(\"Accuracy score : \" , accuracy_score(Y_test, Y_test_pred))\n",
        "labels=np.unique(Y_train)\n",
        "cf_df=pd.DataFrame(cf_matrix,index=labels,columns=labels)\n",
        "plt.figure(figsize = (18,13))\n",
        "plt.title(\"Confusion Matrix for CNN \",fontsize=20)\n",
        "ax=sns.heatmap(cf_df,annot=True,fmt='d',cmap='YlGnBu')\n",
        "plt.xlabel(\"Predicted Labels\",fontsize=20)\n",
        "plt.ylabel(\"True Labels\",fontsize=20)\n",
        "plt.show()\n",
        "print(\"\\nCLASSIFICATION REPORT\\n\")\n",
        "print(classification_report(Y_test, Y_test_pred))"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score :  0.9549637479085332\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x936 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "CLASSIFICATION REPORT\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       1.00      1.00      1.00       331\n",
            "           1       1.00      1.00      1.00       432\n",
            "           2       0.93      1.00      0.97       310\n",
            "           3       1.00      0.99      0.99       245\n",
            "           4       0.99      1.00      0.99       498\n",
            "           5       1.00      1.00      1.00       247\n",
            "           6       0.80      0.83      0.82       348\n",
            "           7       0.91      0.95      0.93       436\n",
            "           8       1.00      0.85      0.92       288\n",
            "          10       1.00      0.96      0.98       331\n",
            "          11       0.99      0.99      0.99       209\n",
            "          12       0.94      0.99      0.96       394\n",
            "          13       0.99      0.91      0.95       291\n",
            "          14       1.00      0.88      0.94       246\n",
            "          15       1.00      1.00      1.00       347\n",
            "          16       1.00      1.00      1.00       164\n",
            "          17       0.96      0.99      0.98       144\n",
            "          18       0.98      0.98      0.98       246\n",
            "          19       0.86      0.74      0.79       248\n",
            "          20       0.92      1.00      0.96       266\n",
            "          21       0.95      0.93      0.94       346\n",
            "          22       1.00      1.00      1.00       206\n",
            "          23       0.92      0.96      0.94       267\n",
            "          24       0.87      0.95      0.91       332\n",
            "\n",
            "    accuracy                           0.95      7172\n",
            "   macro avg       0.96      0.95      0.96      7172\n",
            "weighted avg       0.96      0.95      0.95      7172\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e-VO9GGt5wQ4"
      },
      "source": [
        "# Reading live image"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RumB2u3B5vbA"
      },
      "source": [
        "from IPython.display import display, Javascript\n",
        "from google.colab.output import eval_js\n",
        "from base64 import b64decode\n",
        "\n",
        "def take_photo(filename='photo.jpg', quality=0.8):\n",
        "  js = Javascript('''\n",
        "    async function takePhoto(quality) {\n",
        "      const div = document.createElement('div');\n",
        "      const capture = document.createElement('button');\n",
        "      capture.textContent = 'Capture';\n",
        "      div.appendChild(capture);\n",
        "\n",
        "      const video = document.createElement('video');\n",
        "      video.style.display = 'block';\n",
        "      const stream = await navigator.mediaDevices.getUserMedia({video: true});\n",
        "\n",
        "      document.body.appendChild(div);\n",
        "      div.appendChild(video);\n",
        "      video.srcObject = stream;\n",
        "      await video.play();\n",
        "\n",
        "      // Resize the output to fit the video element.\n",
        "      google.colab.output.setIframeHeight(document.documentElement.scrollHeight, true);\n",
        "\n",
        "      // Wait for Capture to be clicked.\n",
        "      await new Promise((resolve) => capture.onclick = resolve);\n",
        "\n",
        "      const canvas = document.createElement('canvas');\n",
        "      canvas.width = video.videoWidth;\n",
        "      canvas.height = video.videoHeight;\n",
        "      canvas.getContext('2d').drawImage(video, 0, 0);\n",
        "      stream.getVideoTracks()[0].stop();\n",
        "      div.remove();\n",
        "      return canvas.toDataURL('image/jpeg', quality);\n",
        "    }\n",
        "    ''')\n",
        "  display(js)\n",
        "  data = eval_js('takePhoto({})'.format(quality))\n",
        "  binary = b64decode(data.split(',')[1])\n",
        "  with open(filename, 'wb') as f:\n",
        "    f.write(binary)\n",
        "  return filename"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "liRf1s7-52DS",
        "outputId": "398f0742-0e7a-4c07-b530-524cc7d1d1c5"
      },
      "source": [
        "from IPython.display import Image\n",
        "try:\n",
        "  filename = take_photo()\n",
        "  print('Saved to {}'.format(filename))\n",
        "  \n",
        "  # Show the image which was just taken.\n",
        "  display(Image(filename))\n",
        "except Exception as err:\n",
        "  # Errors will be thrown if the user does not have a webcam or if they do not\n",
        "  # grant the page permission to access it.\n",
        "  print(str(err))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "    async function takePhoto(quality) {\n",
              "      const div = document.createElement('div');\n",
              "      const capture = document.createElement('button');\n",
              "      capture.textContent = 'Capture';\n",
              "      div.appendChild(capture);\n",
              "\n",
              "      const video = document.createElement('video');\n",
              "      video.style.display = 'block';\n",
              "      const stream = await navigator.mediaDevices.getUserMedia({video: true});\n",
              "\n",
              "      document.body.appendChild(div);\n",
              "      div.appendChild(video);\n",
              "      video.srcObject = stream;\n",
              "      await video.play();\n",
              "\n",
              "      // Resize the output to fit the video element.\n",
              "      google.colab.output.setIframeHeight(document.documentElement.scrollHeight, true);\n",
              "\n",
              "      // Wait for Capture to be clicked.\n",
              "      await new Promise((resolve) => capture.onclick = resolve);\n",
              "\n",
              "      const canvas = document.createElement('canvas');\n",
              "      canvas.width = video.videoWidth;\n",
              "      canvas.height = video.videoHeight;\n",
              "      canvas.getContext('2d').drawImage(video, 0, 0);\n",
              "      stream.getVideoTracks()[0].stop();\n",
              "      div.remove();\n",
              "      return canvas.toDataURL('image/jpeg', quality);\n",
              "    }\n",
              "    "
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved to photo.jpg\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mFTo0eEu6NAz",
        "outputId": "cbc9ec9a-ce63-44a5-a1dc-6b2c83d18ef1"
      },
      "source": [
        "import cv2\n",
        "pic=cv2.imread(\"photo.jpg\")\n",
        "print(pic.shape)\n",
        "pic_array_format = cv2.resize(pic, (28, 28))\n",
        "pic_array_format = cv2.cvtColor(pic_array_format,cv2.COLOR_RGB2GRAY)\n",
        "pic_array_format = np.reshape(pic_array_format,(1,pic_array_format.shape[0],pic_array_format.shape[1],1))\n",
        "#pred = model.predict_classes(X_test)          \n",
        "pred = model.predict(pic_array_format)\n",
        "np.argmax(pred)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(480, 640, 3)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 185
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ERYyurrZUrWI"
      },
      "source": [
        "## We notice that the captured images is classified to label 2 , which is the label for letter C . Thus our model correctly classifies even live images."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "QdJl-M_E9nCV",
        "outputId": "c5cf1583-b33a-435a-d99b-fc2afcae663a"
      },
      "source": [
        "image = thresholded.reshape((28, 28))\n",
        "plt.imshow(image,cmap='gray')\n",
        "plt.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}