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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#References: \n",
"#https://www.kaggle.com/prabhat12/fruits-image-classification-using-keras \n",
"##https://www.kaggle.com/jnelson790612/fruit-360-transfer-learning\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np \n",
"import pandas as pd \n",
"import matplotlib.pyplot as plt\n",
"from tensorflow.keras.utils import plot_model\n",
"import keras\n",
"from keras.models import Sequential\n",
"from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D\n",
"from tensorflow.keras import backend, models, layers, optimizers\n",
"from tensorflow.keras.layers import GlobalAveragePooling2D\n",
"from tensorflow.keras import backend, models, layers, optimizers\n",
"from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
"from tensorflow.keras.callbacks import EarlyStopping\n",
"from tensorflow.keras.models import Model\n",
"from tensorflow.keras.models import Sequential\n",
"import tensorflow as tf\n",
"import os\n",
"import cv2\n",
"from sklearn import preprocessing\n",
"from pathlib import Path"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# storing labels for train test\n",
"l_train = []\n",
"l_test = []\n",
"\n",
"# storing path for train test\n",
"pTrain = []\n",
"pTest = []"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The labels for train are: ['apple' 'banana' 'mixed' 'orange']\n",
"No. of jpg images in train are: 240\n",
"\n",
"The labels are for test are: ['apple' 'banana' 'mixed' 'orange']\n",
"No. of jpg images for train are: 60\n"
]
}
],
"source": [
"train_path = \"C:\\\\Users\\\\LeonFremz\\\\artificialNN\\\\train_zip\\\\train\\\\\"\n",
"test_path = \"C:\\\\Users\\\\LeonFremz\\\\artificialNN\\\\test_zip\\\\test\"\n",
"\n",
"for filename in os.listdir(train_path):\n",
" if(filename.split('.')[1]==\"jpg\"):\n",
" l_train.append(filename.split('_')[0])\n",
" pTrain.append(os.path.join(train_path, filename))\n",
"\n",
"for filename in os.listdir(test_path):\n",
" if(filename.split('.')[1]==\"jpg\"):\n",
" l_test.append(filename.split('_')[0])\n",
" pTest.append(os.path.join(test_path, filename))\n",
"\n",
"\n",
"check_label_train= np.unique(np.array(l_train))\n",
"check_label_test= np.unique(np.array(l_test))\n",
"\n",
"\n",
"print(\"The labels for train are: \", check_label_train)\n",
"print(\"No. of jpg images in train are: \", len(pTrain))\n",
"\n",
"print(\"\\nThe labels are for test are: \", check_label_test)\n",
"print(\"No. of jpg images for train are: \", len(pTest))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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6zxfzg0/+McrpKrZ1+FgRfCTGSH9hgTwrOiEiggL1tKWpG0SE4WiIhkiKEZIS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Kr+eeVeHbnpVvdpoBEGZUhKDE4DzI/4g2EExpQIEthyJaaEhkDt2EiujnmkIWHNWYcq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\n0KNHj/vQJ4UePXrchz4p9OjR4z78P9QyxYyyCKXyAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176a81cd6d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img = cv2.imread(pTrain[0])\n",
"\n",
"rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) \n",
"\n",
"plt.imshow(rgb_img)\n",
"plt.title(\"Label: \" + l_train[0])\n",
"#plt.axis('on')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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DwaV6jy9OryjmgTWJoVE6xkpEAoJDdMSrWR/qB1R4iekJRulLK0ZQ647mmMIA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\nLZhCtCNK6lRYOeSRcFoMrjq6vpLDoP11A83cc3BhRi09i3sPbtp/+fW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Uv2hyb71b9p2q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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176a81915f8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img = cv2.imread(pTest[50])\n",
"\n",
"rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) \n",
"\n",
"plt.imshow(rgb_img)\n",
"plt.title(\"Label: \" + l_test[50])\n",
"#plt.axis('off')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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oi7sRegIiiUBGaKnCYjoO081sRMSRlNKAUlOfCXFEM0Gb4oAom5t2ZdMqglbqZhuJ03vn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sHC4rLgi/8zn4lc/8BsPdU95+9Ys8fPOL5OkCKclMrIYN/v63kz/0o4T7f52SJ5YxsxyA7EiH\niitK9EIXHF0Qol+n5TZsc67NYlcql4PNdkvofeuNKpsYGIIB4bveeN41ee589O/y3Pf+OyzdlnL9\niN3lQqmWlcwTpAmWnBgFZu24mj06Q51hGY1dNmdhXCo1KXWCkha+/YOB+/cF70xEt1lAcuIrQ7ew\nuwMnzyXub2Fz/wWCWziJgFYyMDhPDJjyOjfkhxAcXefZ9FYtzHMilYLfbKk9+KFBc8oZw/IOh+vM\nrMKFQskVF0ziz/eCusJcRsoivPKv3uXh67CTATl5EXyGNOGdtanER9R3+NghQfBuy3zxOq98+fM8\nfPAEUei7zrAmWo488dtU5Ns9x1orpVZS44Kb46l5Pq00xlSywd5qU/lScxIwIgktO1WchHYDmgHj\nsuSnss0b9Ai3WnzLTYZ5C6lyGwBvt/lfwiBIRE6AXwT+E1W9BP474DuATwJvAf/1N/2qgKr+nKr+\nsKr+cOwi7779gJIWg3l0HpywPdmhAi54fAzMaWEYtlxfH546Uefn58YOUmfOiVL4P3/zRS7HwvUC\nTw6O673j4UN4/KiaoZgTZmyqLmqK0bYbKrlAxpEU5lIZk7IUKOIMulRB6cgI/dbxm//I8W4HxXUN\n1mTBOADZCU1AnSnZfLvFSsteW5lQ1aheiHmilypobbJ2/Tk+bhl2d+i3ARms3PEiOA1oeIySEbao\nTIhTsySu7qkMQDFQv5lNNaBxa8CLVpqUiYkKs1BLQJmQKhZc68zJyZbnn8sMZUOulcFbf+mKyP/y\nS6/x/Esvczi8ycPX/5Dx4VdYLt+AOiFdIA736O88j/vIz+C2927Wlla2g6PvlHWbsfcM0Xk6Ly1G\nquEivbmQ5grjOFkJ3hAQ85ztGubasnOgKvrgs6R3fo9tFjaxWRhjm1+arD962ivDAJ0uzFOhy0AR\nk2xrfThtw4kQHLvBMXSZ7aDsBvMDigK73uM3EIPQi9ChzBlyfBHfv8RSPX57ChKbYrkNqPqNJcXe\ntz5eLQxdZuitJTHN4NyB6MAVJV1/HQ7nzGo6mb14hKnMYQAAIABJREFUNsFRxZFKQwto0w+QwPVB\nSfvMnBR39xMkZ+Zmrma0JFQF4gYNA77bELstw7DhwVe/wBe/+Mek4/BmFR6+cZ58r3gG8NTvcs6U\nVZ9TzJnBx2jZoRgCQqXigiIkcroGbobCKSWWJROjVT0pNYTGrdLdAnRzmy1twBja2q/r+6rH5z0K\nzIjQh79gN0oxs5dfBP6hqv6S3fD6jqoWtdD+89yU4G8AH7z18A+0n/2ZRymFu2dn5Fosw1S4vrzC\nIew2W6Z5Yeg3DMPA0PUEF1vDOBxLhLONTeV6V/nyGwu/9pmeYesZS+HhZeXxJRz2wjiJDXXUgtqU\nleX/o+7Ng2bLz/q+z285Wy9vv8vd545GM9JoG4GQEEISWoyEYgJCBpsECBBsEuzExEnZVVQlsROS\nSkGlqJTLVSmnsMFObEwAEQLCNiAkQPsy0uz7jGbunZk7d3333s45vy1/POf0+95hLI2qkspwqvr2\n+97ut/v06XOe37N8l6hovEBgohKWCN19TJBMdyIiAW7hW4LTfPaPI1/8jOej9wGxJSiFStLoTMAs\nCOHaeY3TEY9Mr4WJBARFipL5Se+xJSYj1gXGEeOQGC1aK0wRyQcVVX5eMKpKo/QU4rDzWa85amp7\ngp0RMYSU4XVDTJlMSJUVcQQSKllSKEmqJhFWTAvFkRiD0g5jGmwssaUnGyt+4q1LTLTUMaCCJ9eK\n57YN88Nn0Wvr7F15jmsXH+Dg6sPExQ3yALZoMYMR6fRrMOf/e2y+hbYlygIqdnhMwceCDH9C9KBE\n8VzsfkGlhEoJo8A1gTCHuEAwYhrINSZXBK+JAYo8srt4kP32ERYsabPEfi3MnMU8YozGaChHt7F1\n/o0U+YjR2dO0w9Po3IivuhabzExFTA5ZGTFFpChyKmuxKjIoEiLiHsgRZfOsOEUTLSaA2bkf5S6j\nQkQtZOLY0CEIFOIaqTsuTpJ5d241kw3D5IRmOFL4RaecruX8smnI5sn3oQoIzZLlLNK4CCiaNhGD\noazWWbZJMMxLxSJowpt+GJX2UC00WkSFldGYokJlJVk1wNgB2i54/L4nuOfup8gKvQpUEjiPytwj\nuuVRad5nmz2+2lpLOIat7GcY8VgwFUywxdpi9Zr9fVnmONcQoiPLDSE6nHM3vf+q/79SRepkFHus\npoo39UT7TLM/517O9nKm5wr4Z8BjKaV/eOz/zx572g8BD3c//z7wo0qpQil1O3AncPc3ep+eR96v\nSrnNsNrgmpbgJA3v1d179aOUEoPBgBCCMIncUg5WcpSjxPWdCpUSrY80DkKUQUzTRlwbaXzC+ySe\nJynilegcxh482/VsYgdB8vHowEo/JfDIvYrZFA6DxiDPk/tuqCTd7w631vVW0jGbi75Z2j1bfMzF\nu93HBjCdWOsQzRCtKnHRQywW8OsoO0dsfh1HZlby1SZFJ1IA4uYj+9NbFisl5bui0wyNMjhKySBq\n4JlknNEintEZyibe8RbIqPD9ah0VgcCVy1+jGK/j2pb5bJf5bI+2mRN9IBpDzCt0AeXJLQblBGOq\nbj8Vkpsfh2PdPGE1RtOTCYAVW0onJdYNPZRMakdCEC+mlBI2z6QvFiNp7lmPmuBhMRcOcp5D9PvM\nppcp0ozot8nKmqgi1kKeZ1jdEWdSB0vKhS0j5bTIvekex+szMrXBZPM12NEt1Aqs6dhomWYZO3hd\n/wFDh0HtL+bQtYEaaJ3HZomyMhSV73p0imiBYs5s8Syx+1pNLouLXEdC+V0slquy37cGY0e46iSk\nVtpFchTRynYcbttlkZa6mXLj6jbXru78Oa3b42Xv8QxzBe3prufeYhfoxG6OgOxHwbXTXej44DHY\nVeDrA57zDT3bzTmHMUfBsC/1j0DsR6Htxa9zPKj3AfcoE/3G28vJNL8L+EngAy+CF/2SUuohpdSD\nwHcDf7fb6UeAjwKPAn8E/Gzqw/+/Y0vdwdve3Wc8nlBkJa3z1G1DJBCSJwaPzTqfZK06mpgEz6os\n0EahTUU5HJAPKgY655mrjlaVRGPZnsLeoeHaXmI6h2UrJ97C0cGIumDmhXcclGYZRUqsDZq6DdBl\nQW2CZYi0ER57IDE4nUPWu/tIrwo6SiYB13hy68mdERpc7GiBDpzu8GVR0UaN8gaNrIRiOdui45iQ\nDkFJQJRRTkUMQ6KuiT4jpWWndtSdoLrtONgBRSte6ixQygkesxsGaTwpzUlhgTRa5aJBNaACiSVG\n95i2HBM8A4b80H+U81Pv9qAhUGBUQ7I5/+uvPMDaIMLahJ0bz7Fz8VEOLz/JsrmMDWBjIB9ukU6+\nFt7ycxTn/w66RtgfyncajQadKaxJmGhQvvP6iRHTYU6VSmgr8wpvEsEKfZIAKognuI6J3GgoNNoM\naNuC2glGemkhqzLKCobjQLEG2tUMFgfoEWQuoNyMsY0yzS8ieSFIi9KAahVWlRRKMc48tlQUg4pk\nYGA0aeRAL2nrA7JwB/np95MPxJIjxMBseJrKW9F61BayEuel6tAxYCXZlJ72HDKfyK0naSX9XnTn\neKKh/RrJCVwueUWYWVJh2avBtWOWi8j8wHLwnMKOHMPz76BSh7Lo2YZcSXaXigE6G1KUQ8qswk4q\nrj/+GJ/40hd48sYVysJC9EfBE9VlhZbkRWDbYjp3R3A+kjDkyYixn0rozBLo7DKs4J+TVshVKMD1\npDwpuRX8Ts5JCepGCVROhrCR3GqMSiuh49xYMp2Rm4xeRV4YW/I81cGa+uFVX9p3tqsva/uGekgp\npc8BLxWG/+Dr/M0vAL/wcneix1JFEovFYtVczvOc0WiEc46y1LRty2g0Ymdn5ybXyjzPQSlMptk7\nnAIBpSuqYcmffWGPb3+dh5Rz47DFayiHMKoMqQqoQjIUHwTFqFSiANo2dn1UMbjyne82dHAXEs8/\nC2dvyfgXj7TgMuBFmnzdgGfnEKoKZvsajQgxRCU4UAKkY/7u9FkkkdQ5YyYVUCpIBmXmEAYirMwS\nQkGMSzED0zkqDSQjDBVo4aH3QF5SQqleYKEbqsSEUTlaWRlU6aYrcSKKAt3JvaXYq9Y0OAwxNvzc\nf9byy18G45YUmUbFlrsvDWh2rrM+uZW5v8rhdIcXnr6fzFjsrRmmHJPyIYzW4NybUCdvp4z/NYvn\n/2fsIEMZR54HsiJD4ah9wGRdKyPRtRCOwOryWdSKormYi6OkzTrtqBgpyBhVdxCLBdevPQFAs9Qo\n49hYM1gViAFGG7fjTMvw1PtYPPW7DM0Bc06h4y42eZIBW2hCHSmrROtrfH0b+uxfgcPHMaVm8p4P\nk3YPKR75HzDjJfPBHJ77NPV1hV3bYmnGKJ/YGv0lFvu/Tgib2LQLOlIohU/SiiAHYy2pCaDET0kE\nLmRhjySqYUUxqGjaQ9pO9ESpRKw8VYCTm2DSnP3kWVyDaQOn3/CdjO78a9hYo2MH21EapS1ZsUZe\nDSjWRlCOUO0hX3v8YZ5+9ipbVU7dRIwyKz1LaZEpfPCrqkBHTWY6ZbEVnKg735IgFYwRZEcISaQ7\nlKBOFJ0gi1a4EMg5Mm7T2lA3LdoKtVIpTUwJw81ltQTAVvanB9jrHv6kSQTUMQxpL5Lz0iHupbdX\nBCMoJhmQaK2FU17kK4DsYrFgsVjQtu0KpDocDsmyjBgF7K6Uom1bFrM5Z0+dZlBU5JmiKg1fvm9C\nzGBWt7RJ45PlYAaHcxE4TS14p1g2MFsmFktF7TRLJ5NSHwzLtsW1Xb8NhUvQOpjuZvzTrzp2WzAv\nDpiAxQCORx61FDkdxEnwhP1ryc9HcnHQl2wSJSKekBwxronxV8pkZU4awho9p1xTkEJBTEspr9Wy\n69n0JcvR5BAQrJ1WaKVQKYgcGUeir8LsOAYjUR5RYQxEc4h1GcNboAoZVkHTivhGMgt+7bc/z3Bk\nyYcVphqyvXOVy8/ey/TKE9R7z6L8EpPlxK0Jxdoa8Vs/QHnuv0XNHZkWtpVvEm4pZbDNoCw1eWFk\nn6GDfHWBU4nOkHciG7YCSyOzlqZx7O/fz/Twa2TdZ8sKT25FjT548ahZuovU84uk/BSbH/4XMPwA\nG2ffC4MRQXd+SS5hqyGuVaQ2svnB32Pw4/8L9p1/j/kdH2b4LT+DfesPEte/l6Z4I/UjB4ze9lm2\n3vpbtHtnSMO/hgqe+uKvE0LF1mv/Clmy+DYRfURpMFa+Ix8EP2isIrhE9JAbI59fJZxrWM6mtK7D\nZyn5ln0NbQYDwI4jRUAEUypYe81fJQwXkGRBlR57DtkQU62TV+tYO2BYGa48+TB//KkvkVUDktUo\nPD728m99WS6QoiwzZFnW8efblVQbgFdBWkpGAPcq0gW+jinUXeuxlzRMGkLs+oziJBmCQIr6Mlxr\n0drt8c19Rmpt3g13XrpM72mA/QDp6Oe/YEFTcWSspoxeof6hm8BxpFTSu1GORqOO8ZCtGrtlkXXQ\nnkh0osxsy4LpwuARBk89CzQtzOtEaMVLyLUJRUYMirpJHM4UsI4POT4NiKb7kqPgNF039d7dD8zR\n5IkjZbabNlGSuX5dyoNIJAaZ5CXkpBNhhrSCo4VOaOGoxRKld6kbEg50589sOnm4NBCYUK8JqMLq\nhDnOfLh5uxmUJmybTmNTeaTGdSswPL3ShRL2h1B0pFQ9rZ1MrqVzChEefbohxAV5UWKyEpRh9+A6\ns/0rLA+3ifUSFTxZKjF2HT2YkF79BtLgLfhazMy8D7310LHA3x9ViRFw5CwqIPQu2zEdhvf4ZwyQ\nXBAReR1l+NTJnqWkCEkTgDUTMcsn2I8HDE99N/PrFzDJyfN0QtlEjHOcnxCyjMXBQ5C1lKPAcPPt\nhDUoR2eIi+vo4i6Gt30P2fe+g/i+N5C/+ocZvucnOTyo8QqUX3Kw8yWCE/UXnR15s2dWbjZTHaUR\nrO6DlZyLKUkPXGuDtplYL2tgKHnT1WbCrP5O6qZg4S3jtRFUaxB6wkQUBKU26LxCWYPNK6zNQXsO\nt2/wxNOXUCkRVYbVXSabPIkgvkREqcBWC2y4if54FGA74Hu3gAvlUh6X19OrrC8lhVF/vgi2ndCJ\n1VqyxRBuOi9A2mchiMiNYDAFfH98f47v32r28BdN5UiEKwxGW9ply3R/ymg8oCy7SZ0+msh571ks\na1rnKcuS4XBIvWxIXjyXb+zfwJQ5oKkyS17N+OJXT2K1JtQwrQ0+wXQfruxFwrRgVsPhIrKYJ+YX\nwT0WyOIebrbO3g0REClyICgO9hW61pgEv/ybEXTERQErv3gLyMX2+fsC+3UUCmcSALGLXcnZXfwg\nbQJRyJbpZ9KapA2CTguiARpHHRVNyg7yKarISHlNsAvxOU8bHZ++pvdmgQ6CwtGJ1p/AKYrFAVqc\n+VK0kIT6FlWNMsKa0AkMhjyUZHnE1zl/+8ehoWRghCZYJHjyRuTzX36EKl9jXG2QDyZMF1MuPn0v\nl792D4urT1JPb5AFB1aRjSdkZ16Nffffp7HfhZtpjDcCAg/QJs0iZIRFJx5rZaiikxiT4SC2ENvU\nk066iS1kue7EPRKFVYzWYDg60h6NQROCwc0D6sCxt4AbD32c9cf/mKtP/m80u/cz1XOMs9QxYSLM\nd8F+z//Eia1/QLzwcer/+xepr7xAvP6HmJ3r3FAPM77rP8C2lsPTt5KuPE918QKLh/8x6ZHfwFjL\nQq0RFIRrj+OjcOpR0MeKwlpsApuXKDJ8FAlD4w2qhGEBdnCW0akfRBuPiVbA+LogHsLO8/Cmv/H7\nxBNLnryvYnrJsPHG7yfXe9goSulBa5QtoBijhlvkgzVUUaCLIXvPX+CL9z7B7t42eW7JrSb6TCok\nnzqkQwA6D6+UUMFRma5nmKL0xpNF9f3CGDA4DC2xdbIOR4VVFheFP++TJwJZVaKM6XQitBBCgvQ5\nhVrqCcERtSMgGNaIwdoO30cU245j0/MjDCkdrrkb8HovwtMvc3v5Gu//H25aa0L0hFaGPQDzWcNy\nucSajNFojNIwm806NfcW7z1lkdM0Devr6+zuCm0v05bpwaHgLrMCg+fSlZaQR3S0DJTnyWcMdhp4\n43corriGc+Ocej/yj355yPMzhzVD7hof8B9/b0uTTvLIY3ts7+W894OK9/5Qy0IV3P/pfR66lGNo\nMFjalyjPE0DU3PtA4KlnMjYniWA8LorVq8BrujKzU+6JkW6ROD6VHEPMITiScoIVTFL6y3MqdNpE\nstJDktpBUXSZYY+fE6hOv0Xk/Vhlc6krzxcSLIEYFUYbYiwR5cxEUo2YtbWeCsN3/yWN/1ctPoLS\nitwKzvV3P3Y/7/j2OzB2RDGEtt7kYLrPYrkk2oqzSjNCkZdDdDHCTE6AMoy+/e9grn6Y+ulfQBd7\nuACYSEVL0tDYjFIFlJG+l8Hgo4hQGCNQHKXB5oqoJbsRuTe1yiqJYr8bo1D8pGyDNgZGuaY4WXP5\n2d9gsHUOr08z3L9CO6oo0pBlex1qxei5r7J3eB++fhB3SVFuvI3Rt/4El//hh6jO3cXl9gJx9iSj\n+K288Et30BiLPuFpv/qrFBNFtTwklV0vW0u3WGktQssOVO1RCnxsumm19AJD0ZJ5qDNNbHc4vPpJ\nzOBNOPso9jBnaRu0g4N2wCf+9vtZLgumTcMt37FGdf79OD2jMgkXa5ReI6s2oRwyWBsxGK8zXFsD\nv+ChJx7h9/71768IJcQkOgzBE1x3zMpMhlgJ0BZtO6OyKAgQ5xqcD5iYo40lEfAhQNLkucDJZIqe\nRKP2JSbbwCrg9RJyx50n5ch1i38SGcgjNtJRfOnvj/cy4cjT6JthBKkXp7f/f2zjYZW+4y2vxRhD\nWZbM53Oa2nc2rjl7e3uMhsL6Ga2NaWpxpJwvZpRlyWRtnQsXLtD6QFHI3/gkcnK4kgM3Y2Qi73+f\nx+Aos4jXI65fmHHtEoRDzbP7ibtut7zhDWv88id2eNPJgjyPfO05TTk0vOPMBlevvcDPfP+d/OHd\nz3F5Dl89bMiWGUo5GRO9GCTQfW/jZPjR74n85EcUPsaVbJVRiszKBZFnQpezRhwgTQdCN0aBTZhU\ndjYbjoQlMw1H2ocFml4EIUIco/NtoSLqvp8pOoz9CSWUNIHrpA6j5pMhao5EG7Q04pXqp1YLSBkx\nGVhGtK3ZcZbb/2rLMDM4L1PQOinecnviXd824d/74HcR3YhcRabzGd7VkAy3nHsz5+58O4PJhGJy\nlny4QfCR5Xwb184oL15EPfpPsemrUp5WhqYGGwLaQOyortopGWAhJWAHr4UIxUALmcBJS0RKQel7\ndlZUgr5SoiTuTaRM0unwDZw89724jQE+nKd+9lfwsWGoDK1zuAb05jr6cJ8mGIpgsaViNq8xFihk\n2FcGONCWcfLCIbdQFpBihjYe70WiThtQ4QiiY7POLzxKS0ppaaPkmcauvYvF9G5s9ESlifk6brHD\nwQJqB9MWbjxieH4W8A5ee7vltu/+eeI4UBhIJidTGlOcwUxuxQ6GVOtrlOMt8DVXn3qIj370o/zh\np77IaDAEJHNvWumT+9AbIOakpFbzhT4YqW5G0cMCjRKL6qT6LLSTB9RqNQRG25tsK17MMAohYNQR\nxMhagSS5ru8ZuvOiN4U9jhntr5LjQffINaD3bs/47D2P3ZNSevs3ileviEwzxohvA0tXMz2YMRgM\n0EaR5ZaEZzSuWBut4ZxjuVySUmI4HFJWBQDb29tiLRodFoVvHXuzGUVZYvIDhmqN/cOWP/sTeO93\nNpy/I+fhx2bMnxszMjl/crjD2EJ9GPnDz+4wAR673nBCr7MxWTLc1IxONGxkZ/i1zz9FOTrJV5+5\nQUaO023XMnmJxSdpjI7MUuCL98B/8SOanTmrQVBSotBjrWQcJE0ikWKS0pvOdS8VpGjRJoDKiCiS\nH4NqugC4TtLbiGVvQqnQDYgCMtFP3TSz389eFFZ+7SebRiViylZZrqbDPCah8hHHJLNHkUqmQ0/Z\naHybeNc5uPdaBDJhVWGJueO++6Yc7n2On/npH2d5uENZDPAmZz6f89xzj5GUYWPzBCfOi2NkVo4Z\nj9aJzZjFbTnZ4GepH/9NUn2RMjyBNqBTRrJO2FAuEboIqZQoI0kQ7Djsnc+2i6ISr3pKZgKVK/LQ\n4WVJGA0miIK5alqMhRcuforB1QENuxQt5BslrauJQwtZIGQ5zsr0fVEEkgc7Kln4mrFXZIViFiJj\nPJSW2CYGWuMyT+6A2AVMLR70saOKokUAw3sIvcd410/0KtLMHyI6RwwQdMAvd/BYbBmw3nJwzXGw\nEyiAMxuKte/8EfS4xaQxuW3xqQH7KtR4k2yygc0rqmJCmWseufcLXHj6An/0ic+RTYa03hHbptOf\njVRlKaZmAEZjkj5WEXVBLsqxljmExkf5PhQRUiJXVrDPdELfRszcZKDTVUZaWgB9VtkHV6UFKBtS\nwq381/VKocnoI8fZns6pba9gJIB8rf+8lXDrFi87Xr0iepp9ih5CZH19g7Z1TCYTmmbZrbIykUsp\n0TQNRVFw7do14Zs7MV6TIJqvHledKGnbBLxboLIFu3tCjdNZi2k0G8OG6zd2gIo14Mt7imfnljMb\nChsKbtg5y2XDWmN58MIebzh/isN5xs7hDrCGpoVUoFR1LOs7vmVdcITtPTC6N2+TMyYlVuZXYTVF\nXzU66b+ePoOMaUGICyJz0DMZCqkl6MOuXDeABy0Z4Z8fAPUDFNkkcB4P9glir7RkuixBdcMgLa8b\nc1KqSZnHR4+xiTfcJj5OK+y/MjgH0Wdcv7pgd+86Pf7TmAxrc9q2Zu/GVfZ3rjE72GY5OyD4VsTr\nTEINT8LGWdZP/TDV6P3oNiN4aM1Rttz71K8+Wz8IAWymO1GJDmjdoblWmbbWwgQyupPpUxSZw1YN\nhZGL0tiaw7BL3kAqoJnXRFfAviHVidwtqVJEGRipjPUIqfVsKmjKjPksUhagx2BzT5UHTHRYn/Cd\nZaxSWoSho+rU4+3qO+/l8FLsJ8nd19wsO6ERDW5AcoIJji6RnCc1kIZgNzLUVsap9deB02IvkRS5\nytF2SJYPsGVBlueU5YjpwR4HO9d58qmnaaNk5z1r53jZvEJUJE1mtPg1dbfUOUxCP/xBKMHKAJYY\ntGjCvijQyvNvVmQ/PoE//vzjj/eso95U7eZz/WbL7uPvczyj7YfML3d7RWSakJhM1pjOZ+zt7+O9\np1ouGJQVewf7DIdDDqaHInsfA863nD5ziv29A6qqwvtGMs1Gs7G5xf7+PlVm0cAsFNjcUKkS1jxP\n3oBzN6C+HHl6p+XxRQYsuRE1b1rznF7P0YNTbGxm3P/Es8yAZ/cd8zbwmQcfxoxO8uz2FDikAUjN\nS4ZLAIWTuJdgB/jas56NzQxDkCm6KrG2kQFQxwBJVrB6JIXqvVpSDVqhtQgl2KQIxqM6iEamu0Ab\nJoBFxRFkV9Axk2iRDKREtOI51Cs00a3mPcslktDJyWuROnC+Be3RaCIBlSx1VJSNJeWKLLV8/3tm\n/MqXIKclqRyjai4+B+9+XWTqIh/9nU/yN37qwyggS5bcR0IV2N5/lt2Dq8yXDbf6SOsSa5snsFnF\ncGDxnGD+OvD1GfLnz2Ie+y2ifZy2Au0TFBm5lmwrdKZ3KYDVkbajEoauDA+d2IfWGu0jWQgELVmn\n1oiTplZYFIwiA6epk4DlXaZEpADwuiEZ+Vrbw6n4gFswKdFES1V5dAYT41ClJgi2TIJ2pmlTxDbC\nYIo6oQvxqDEamgjgscESmijY00GknYt8Xm0A+5dBfxxnLIPgmUVEwas9w/b2JQ53Eteuy1Dx1m8Z\nMzn/n6Kylhg0pW5BT4jlGnbrLPlwnUE5IisrWlVz4bGH+e3f+QQPPfE4psiFjRc9ykhvO6WMmAJa\nR5TKMEpseOGoXxhJOB+wMYoNdxKF9hAks4s6omxARb0q68VcrSWmIyolEcocfOyEWlICZQlxgUEW\nbk0GhmNBvGOEAfTB0hj0StUoYBT4pOmRF1p3VhvfRP74igiaWhvm87n0KjIjZbdWuOCZTCarPkSe\n52xubrJcLlksFgxHA2KM2MzQuobRYLhaDZvoyW1OUWbUy5Zl02KM4SsPbLBW7rGxDhcuwkA7KDJC\n7dlOQ556bk60l5mMhqA1g1FFo2CcFew5xbVr11aMn2+0mS7waDQxwb/5VORv/phjOS+hqEm+FYmM\nJN7UQAdHEhCzhk65ux/kHEnSJS0TQJ26jFAXJLuPSkOUnZGS6VZe26Vf4Ujqrtu/lEArJW0CkFJd\nJ1JXzoskXpC/1VOIFkVJpgXq4lt53plzFqNECUilSDKwiBn5MEN7xfP7h3zuM/fwrne+jeQVVTkQ\nOS/tqZeeFy49Sevm3LGco+Kd5NWYcnwSU66hs1NU/gaNfR9x47Xw4O8Rph8D41mzgaUyVIVBecmS\nnYu4qDBZ6uo/kQNMqvtdS2YYI0Rt0C5gI5BHsq60S6HjuRdQJmGL+SjA7Ehno4Ai+oQmoZXCRY8d\nQJFb8kqyLefkuPoOtaVS7Ow+ErbDVQ6qjLZuSUqsKhQFbdtQFOfI7YRm8QLWLnE4YqoYbu2wmFfk\nrmZpFIVecGMfdq9f4upVw6KBUZUYvdlw5s6fxBUD/KwmG2SYfAyjM+hqQlGtUYzWqSYTVHA8/sCX\n+cQf/DFfefhBUWpXmpAcWZeBGWXRuZbzBRFbdkEouH22l1JnsW01wQtMUJuIcQrdmfolMqKLnf9P\nj8F0hCRZtneC+XRODP76gU0PVpeeqZT/znm0LboKQnBYL1VdobvFq2MCCVXzWA9WqS5BeHnbKyJo\nhhAEoxlFRmyxWNC4lkFZsVw2bG1sYrX8f3CBFNKqbBiPxyvAa88qOn36NE0j/c8sy7jRHnDu3Anm\n8ym2POCeJ89x25kFP/DWJQ9e8FzddzTKcn06J8sUowBpVkOMpBiYzmoaC7UHyATL+DIGaKnrSabu\ni//4l+GnfyIH7/BWMqIQJJxFo1a9Gt1x3vtvfJ2QAAAgAElEQVRS/qg06ZrjOkmWGTVJtUi3yMsE\nXc8k4JoMYiZTDdWssGr9iiwvxCpg9lx4FcVnaNUmULHDTVsJosHLSarBZCJUXBSeLEINogQaNSop\nHr204K2vP4HfX3DP/Rc5fcst3HbreWJsyMuy8zHy1IuaK1efZTFvuHUxY23jJJMzSwZrp7ETR8wn\nlMWYUBa0az9GefFDhP0vMb/yW1TFkjbv2g6qa5T1PVqtadqAUmJZEUL3GXV3H7rpbALlEy6TwKsT\nAqIvQTlZ0HSU4RyANsIqUYW8j59btjbvRJUHRP8CuAydi2c5UbzVY5Jgm5cGFQO9UZyvWylXO4B+\nYRoSBt9cxrWXcRGsgmK8iVksKNb/PvWlX2J54gT57t3c2Fvw/IWa7RuOaBO6igzOw7lv+XugMlTb\nkkYVqtxAr52n2LgFWwwpR2uMJyNuXH2O/e3rfOXzn+Vff/yPUFlOdJ48N1gjmElr8xWQ3dP1AZOG\n2BA4Cph9jzDFIw5+CqKirpQCZdBGGEXQT8W76U2im6pLSLI2J4TmGABdzOaMMagguG5rq477L0y3\nPggeV1fqE64XtwP68nzl1/7yEUevjJ6mMYbFYkFZlsQY2draWnFCF4sFh4eHtG171AxWiqqqVrjN\npjOV9/EIWDsZr7ExWWcymTAYDFBKHC8nkwlVHnj+muFrBwpnI3/5/W+jzBKDwhJc4iAmZlpRK9hf\n1gQFTdSrEco3hTg4FqAOGtifgzGBlLT0MY8FxtSXF921L8D3XhGpF/rozasi0Peauh6SmoLyKO26\nQNndY+mHSv2t35Tqb8f7S+mmx2UPq64XKLqRYZUBdEiA459ZWzSea7uwd3CIRdHEjEefvMALV65i\ncwEdW51hdY42GQHF7sEhu9cvs3/9BRb727h6iqkhtREyT1EOYXiO5swW/vx3oSffx7Iuca6DFKUe\nrqW649c1Mo0wfo4+q9xy3WH+FBA6cWolq0dMMizzx4gGqlM/XvkUWSPShcZJRtV52BgtJAaQoGGU\nKPmLurzQQI3pqooEqECKlibIjSzhfE5bV+gow84YRqgM/IXfhTf+54zPvI+wmLKop9S1oQkQbaQY\nwOar75IgkDQm05TlAFNNyAbrmHyAyXOS1aTo2L9+mf0bV3ngvgeZNy29uHfvYpDnpQwoexB4x+II\n0aFSXJFNbrqFiNVRDOmUEjhRZ+Er57cMLPsepjgWHBskHZucv1Tm2L9Pf+4b0w+Qbu6BHvVWVRec\nO12FY+/TB9BvQrj9lZFpGq1p25oYhxiTsbOzR1WWK7bPYFQxXziWixlFmTMYVKJ0dOhQSgnAva47\nqpkjKyzaKtp5Q3ItxiZGgyH7rUPFIY3fYzAcsFCncNmCP33oKYbjIYu6obKGetEQW08B3Lo15Nnr\nc1xvl/j1ivOb443AX/rfE8xQfPrTgR98P7QmUoQMrQSW4aNAkGgTqdBSfqvupNISNDFy8XWnRSec\n2mekkT5lTJIrIm6TAEHokqqzTtCQJYUOAg5PwkADDwktiuhIXFYK0Lmc7NGJAIgpOlhPkH5cYblr\n5Ll7mVOGltRRROtGc/8jkQ+8vaKOkWcubHP1ypQf+P53cGK4jsrGkGogEFPDwh3y9KVHGF4fsTjY\n4/xr57hTC4pqSBqNUdUaVTbCWYNfP4WdrJMuvQ3/zG/SLm6QuAq6wMYGXUDUwlbRmcJ3B04H0EbT\nxigQHxXRGWL30BoCAZWnDtmgJXvzCafWyMKSgBPFdy3GYt5rLDmLg8fJHGTj0/g8w+1cwiP4TwaJ\naDRFtk4zn2NtwSxfolOODguUSZj8NoZ3fYDF8/fB7t1UJjBVLXTMP7d8AYLh6v6/pHz+gPnocS4+\n3rCcw+XthsFIc/q8ZXLbXVRn3kUWa+xgSMrWMJPbGWyegqKkXBujTEE5tDx53908/dCDfO7L9/K5\nB59mWAgpRJdZF9zEutoqjcYSfBAUfpBjuXR+JSWYOtyxVoaskJaPS6lTFpOAZkwXsHSLspbkenk2\nT6aO2H0S8GTKZ4yQRtq2BW1wbQLVCNPM0AkTH2ExvU8r/yA6JqFSntT5wHsfRaKuS75iFIFzH1++\nCPErImi2znHbbbexs7fLYlGvPpD3fmXb613DeG20YgUsFjOOq5UMh0OCl6bydD7rnPhESCDPc7a3\nt6Xhm2A4HLJcLldtAa01xIRrPW3w4gOEIuiMC9fnBK17lY6vvx3P4Fb3qgP4SJb6ic8EfvQHcqpD\nQ2TZTdEl2saYsIUhEtEpdTjLPnM6anb3r3xT2a6ATlZuJfumNSlpVArSwI+SVSnA0blJIkMDAS+D\nisc8qrt90xSQMjQlPV8Y+imkcKXf9EbNV74axO89iTSC14mDNhKylspZfFmycAs++Wf38+9/4N1k\ntqUoC3Qa0xqh9tQeZrOWxy48w+6i4fxth4zX1pmcPsdwEqiqMfnwJHasqat10ugknL0dO61RT3+C\n2fZvY/MKrxPEGhJkSkmJGKUPiU9k1hK0x9qOvx4j0YulcmxFZNgUGhU9o833MJ/eg4uGkXIEE6hM\ngachZMI8MVoEjSs2ca1i/cwHmS8eJ00vk2WWNlMU9q1ofZ3YPESVgy4VbpFoSijNLuVjn8fOnmCZ\nQ0iGJiXyYKiNRptX04Sn2N3JWF7+GHuX4NKywPnAZD1x8vUFZ+76CJhNtCoo189gJmex1YRy/RRZ\nOSYbjRkOKmLb8Mz99/How4/wv/8f/4pr29vkowlGFyKhh6b1vb+5IkTpW1prqZc1phB1MfFuF70I\n3V0z1mi8d6L/agw++U5GrsdIRo5EYyTLy02Owaxk2hrnbkIR9PcpOnIrK7wEaPuiEoeVM2XvLwas\nynWJBxzLUtVq//kmuOeviKCptaZpGprOEL4ojgRIxc6iZDweMpvNVoDZGCPLZcOJEyfYO9hn2dQQ\nYDQaMZls0DQNWWZWQh95LirVy6albVvG4zExRuq6JssMh4czslwMplzdslbBzrLtsIzfBF0AuhOo\nK+URAa3+9wuH8Ll7Wr7lDi3Y8Y63HXoaXZAJX+roOpqjlV36QuKLTldiyglAV5omjtcZIhIrJWdK\nkNEno51maN+cUX3ghqTisXJUoZXpSsgZqBaVhqTUykQzKvqG3+tfk6i+Ap5OALnLspKy/NkXD/nI\ne27HqcBwOGT/oOFPPvdV3v+eu4hIOltVJXEZycslKfcs65bnLz3D/PCAwXiN87e9jhPn5qxtnqQa\nj7B5wWBYoorThMFp6q1dwulTDK58CPvcn9LMv4A6vEAoEi4TlfqQkkyyTcJYjym16FaGeIRbRYDv\nvTqUtprF8nEG+euI4QEwlsHkDTSzp0keSjPAZUucl+tuWT8ryluFBr0kFYpGOwbzjOvlpygOAmun\nf5x6AO3BJ3DtdTa3/hbz6b3sha8wLwx2Dj5vcQHqpcbXDXn2LM1BZHkRHptCjANcteBUBlvftsbk\nzIfI0ylsNabaOo9dP4dZP4fKcvLhkLIaoYuMy889w2zvBo/dex//7P/8DXZmNbocoonozkd8BeNS\nER8ChRX4mnOCCxZ8qSiAZcYSOxtdEyNGG4h+1UrzMVIWFu/CEYzNaNpGVNhTEtRDz7k/Tnc0x8zU\npNQ+9pgxWJtRd/vUB8D+fY//Xa+7KaD2fLUAHAe6h2/iGn9F9DRTSuzv71OWJSADnbZtVx+0bUWI\nODOWqhriXKBpHKdPnhLDr66/qY1id3d3JVLcYzv7g9TLzQ0Gg9UgqSxLjDFMJpMj+X4NZzbXOhVt\nbsogv9H2jdarOsJjT4HJIvh+mt2vpnTYwyNBjxf3IOV43XzPsX08ekxJQCKRjkE5QlKdKAgQ1Yp/\nC735FDdhH+WlRahDd0OwuOqhypmuTWJjDJVSJCXm5QL70JBg3lpMJYLQ3kfKQcXe4ZLLl3eZLht0\nJu2ULMswusSoEmsGEAt2D/bZ2dnh+tUX2N+5yvxwm0XdyOLnAlHlxFJhB+uY4SnCyZOoOz5EvO2n\ncevvJS4tuolCDoj2mJc9K2m5HkurrKASevaNQqOaRLn+ehp3iTrJ52uCJ9oTJHVO9l1V8nyThIaq\nA7Hex7VTINJ62DeJaj+n3PxBirf/dUZ3fZg02yEb3oF683swm+/HH1jcNJBaQzwYkbxkr4tdONiu\nOdyDg1mB24X5NLI5gdEtUK6/nlBkDNfOUI3OYSdnsKN18sGQvCjJ8gKtNcuDXQ52brBzY5sv3HMf\nN3YPVn7ifaJyk4d4Bx4/qtqOsJErrKM9ClIRLe6e6mZsZe9yueq9p+ML+1H/sn9POMoYj+NC+6Db\nP94D1Y87TfbVZ5+1Hn+N46pG/b2U7P6lp+7/ju0VkWn2EX9clt1FLCIAvZrRZDLmxrXtTkNTi/VF\nOWB/f59IoqhKgYXUDbfccp7ZYkm/HlirKIcDdrb3JHCgWCwWqyDqvce3jfRFWxiUJdPFgnmzIGAg\neUSw95vLNuGoNE/Hom4d4TN3K37kI73wgMAlYgRtlEzSuzJaH2uK92WF7lKimyfqMuXsM1B5b4PS\nHpmFd8dYscp8e+pgDD37SKBRAbFnlYm8FvxaEk3NGCNGD1DqkBCPSvgs05w5GTmzvsHu3i45Fq/B\nRkNUjkDG5x98lO983a0YlYu7YbPGAw9dZzw+4Nvfegdr1ZCimBBYgGvQqqHVjmVtWdY1Tz/1JDvb\nu5x79au59dyccjxktHGCYrRGMRhSFRbshOVgSFg/xWBxK+7MXbD3o/inPsVs5/dwzlNUsHlmSDAN\nofUyT0vS741REUmUa6AxLKeBYTzH/s7n2SjeiYoPUpOosvNk4/PsbT+O0Q+hjSg92ahWnjwHs0sY\npbDBUtiIUx5XejZv+T6WdpsiXqEx72PzHb9K/NrPk+oDUnGa9Xf+I2aPf5pT7/m7zB/4XR79Nz+H\nD3BtWjCtGw4OlyQF5Wtqzr/mdvLRO1k/s8X45JtJJ8+iyzG6GjMcVuKnkxVolXE43eHio/fxwL0P\ncM99D/KFB59ka3MLoyNlVhK9nB+tk2pPaIqaPMtplktAobVgtfpsLssL5ssGpS21F8O+PDPkSvri\nSinxXVcCC2xqt8JG9jKPxzPBI3hR51/uegJA5wOUNNYaYvIEAtYqbLQ3cdGbplkFQ6k2M7FNORZI\nj2ezK0rmN5EZvSKCJgjmcHY4pSgGOOeYz6ecOHGC/d09Xjg8QBnNsBhhjKFY5hgF1VgEipeLJSbB\ncDJh2S45ONhDa01VVcynMyAyHFU0TcPaYEyRWfb398kGFXlekKpiFYSapiEv18htiwkzgjJYHfFf\np0/cr1G9dIBWR4EOViiYzjZDc+kg8iefhXe+RZMVUOaJ1Ik15N0kN2lh2GgluGrLMesNlbAdDbOf\nPimOr95IRohCp3RUd3IEQk5JPCgjrJTikha4k+xzBG3wSUGMaJ2RdItPDqVEfEEp3+E5I4MR3Hp6\nn0f2oU0RHZWoPCUAx9OXFN/y+sBk6ImLjOGwYt54dg5q7rv/OV7/hlvY2ohUgzFVHNE0jvmiJjKX\nisMrtvd2OZjN2b16nbX1Tc686nbWT55hvLaBtjnFcI08zynWNgjDNdJkAlvrqNPnyHa+G6aHxEuP\ns5zez3B8FT0oqdqzHMwfJMYZRRc4tC5pDiu2vu8XWSweZeORlqvX/wkbA4jtiPbGE9RbmqIaMT1Y\nYpWFTOx3s5ObpFhRHlzFLgODV/8D6ukfE5svEB28cM/fJHv0rehhzfjERzi0H6OcwZWnH8EtrlD8\nwS+CCjyzdy/L577Kpd3EzqGmca20A9Zg68wm5+78IJuvfRvFcEC5dZp8cgozWEfbDDsYyEAmG1Av\n5jRuj0e/ejef/OQn+ZPPfIGIYm1YkluDtQU2y2hSQ6wbjFZ459DWklvbBcyjQQta03YGa6mbPaQO\nGaB0IoQlS2WxqqMppoywFC94lRJFURJSpCoKnBN8Zp7nhOhk8U4aqzXL5XJ1ruqunWR1IvrQQZi6\nNqRGzAITeO+xStOGo8wxIrjbnq754qyyL9PT17vAX3y9vyIEO0aD9OY7zzMeD4lBMZvNWJuMRWA4\nwcbGBoezKSEE9vb2OHnyJCEE5vO5DIBCWK0gwk+VlaxpGmrnRQI/K2jblvlSqJkbGxvs7O0ymUyY\nz+erZvVsNuNwXnPLxoDnr+4wb+OLh+I3bceT+hdn+IabIRQ+AcqQa8WbNzwf+WDGu7/NUQxs1xYI\n2DJQJhHe1Vo0FbWBzIiznlJJrD263tARoDetys10rP/ZnyA6Sfm9ek4XHFXofYvk//XxxnpSQntT\nGQoteooMiExRqgUMTQwczuC5ryn+5b+1/PNPBVHTwL8ox4ZhBt/xljVeNTmH1/tk2Wm0MSxcQ2Hg\nrte+hjMnJlIq6oqlS8zrPSErNI4YZFHzTsqytfUNbrnlVk6fPUdVDRlvnqQaTyirIcpWaGtQCZLz\nLJo5vm1hMaeYXyXNnqdq5ygVWO48T9j9NJl9nugyIo7RLX+dyQ/8LFxd54VP/1dUw032Lv8Wg8ah\nBmD9HbT2GcYn30Hw1zi88CzFCGz1KqwdMQ9XObv5w1xtHmDj3BuZX36Y4Zv+Ow4u/AZ7N36Tsob5\nHmzkb2HmT6LuPMtzX/o1ps9m7HiH9hBLzWw70dQwOG0Ybw159Vu/n9N3voUweRXDzU2KIkNl65ii\nIi8K8ixDJ00TG/Z391kblPzpH/0mv/uxT/HQU08xmWygYmIwFHhflmWrEnUFH+pK3L6FVRQCe8qy\njLYNKNWVzASsKTsh8F6sOjIoBgRfEyK4II4K0Xfmah28p41hVVYfZZzmplJcqbSCGsYobltidyNs\nIgBlJOhFH1aTcOfcqq1wvJ3Q9znzPF+17eAokfjcvY//xRHsICWKoqCuRQEnyzKm06n0GFFsb2/j\nvByA8Xi8Uj/qD0Zd11hrGY1GHBwcEHxDVuR47zl76jSz2Yy9vT20tkwmEw4ODlgsRAJtPp8DdIMl\nMaCajCqu7x1SliW1X7zk4Pz4dBykGSA0xA4HmDp4z6pnI7fMBBoPz+xm/NHnHO98a0btHGUOhcow\nHXOhawoeK88T/UMSILtg3DEluvbhsb1Kq6G6Uv3U/Ei0t+97h5SOlIEQ3OjxdTQhuDulI5EWQ+gE\nleX1euydzRKnT4oNrFaKl1qLlbXcc/8hd3z4PLrZBGbEaKiyCh8yHn7iCvPljBObG6xvBKrROnl1\nFu89dV1T1zV5UbFspVVweDhjNn2SK9euMxqNOH36NCfO3MJ4skVVVJgyp6zGFHnFml2DIfj1TdJ8\nC7V8DfMiYqdX4ZbvwDz3DtS1ewlmjyJMaW3i6hd+h9EkJ995ljYoMuVYUGLrmsY8wzA/z2J+iuI1\n/yNnTu9w8YmfItu7RDu8jVP6zVy89hVu/9DPs88JirVrPHXpH3Pn8hYOrg/Yjwume2tcLB4gXBww\nvX/Bcqm5sutwLVQFeGt50xtfxdm3vJe1274NW57AbJXo8gyjcUWpCjJdoAYZWZETXEtd18znh7TL\nQJbV/MG//Ri/+k9+nXkbWF8X2+Q8N7geoRJjNykXAWzdrZrL5aLDP7LKzrz3GJMdBaHo0cp3bSb5\nwjMrVVvwSgTFM1mgrRWzNte2gvNViRTSqpTuS2dRfbfde4SbymkFjMdj2i64Czb76EQTScN0ROmM\nkeTDMUHvI25/X673gfv/1Z6mUqoEPgMU3fP/r5TSzyulNoHfAl4NXAT+w5TSXvc3/w3wnyBx479M\nKX38672H975TYS/YvrEHQFkVIg6ad+De1AlbhMh0OsVazebmFjs7O0eDoK4Xo5VAkNq2ZXZ4gLYG\nnUlQXcyXDAYD2rZlMBisJvYhBDY3N5lOpxATylh867AKotU4/417mrrP1kQTaNUnSf0/ClKQQNak\nwPUDuHbVcfK0gjwJLCgkok70YO2UWAlT9JPyl9w6fKYIxaROvj/1734EI5JvVRgoXVbB8YGTOj6l\nT4LbJKECKK2IypAQDns/EFIKjIKyRF6rZy4dg1sBOOcZ5Jonn7nOa2852YnUaqwSm9yYwY3dOT50\n32U2pCgGGJOhtUUpuaiUKST71J66cezuHVA3rnM6VDgfGVYjBuOR7H/fI1cGYwvUQNMmRZ5ZzOYa\n2i6ZLUANzxDCZcxMM0tL1t0O06efYZkpSjfj8AbYqqaDJrKbbvCqc+9Gvf3bUJceRT+cUW39Lc7e\n/iaax38d1W7x6Jf+Oa9/14/x1POP0VxRXF1+mZ3FgqaB5lrD3rzkYLFg0WT/D3VvGmtrdpf5/dZa\n77zfPZzpnntvVbnKVXZ5wAYMGGhIoBUnoZN0JyQfMnWn6aRJJ4iW+kuiRJEi5QsKrSgRaQkp6URq\nhlZISBSaoZnCDAEMxjRg7HZ5KFfdunWHM+3xndda+bDWevc+5QaMBJG9paNTde4+++zhff/v//88\nz/950KueOImYn8e8+11fjzhPufPCN5LefRE7y4mzlCw9ReUCGU2JIkWaCoyQaN2zq7Z0Tcuuajid\nT/jpf/yT/D8/94s8vdlwdMctjMRxhFJiPO5HQxOP7wdSxx0r0iszBMYE56C9ibUzxbltiGGtdUJ+\npTDWu7JrSPOcKJJ0TUOve+LcwXAuSM+NP4dFLGCNh2YhwkqH1Quv40Ri7e1x+/ONQOxYdMMtFMzb\nJh5/huO5cI86sdZuhcs//zXg7wD/FnBtrf1uIcR/CRxZa/8LIcR7gR/C5aDfB34OeNn+Mc/qeDGz\nH3jvS2w2O9LMHZHGwGKxwFrLbrfj9PiIuq7ZVju01szncy4uriiKgqqqmM1mrnuUEV03EEWSSeny\n0lerFZ1nqpPEOSGB+2CTJOFmtSTPc7fPPpmwWm32sgVPTK3XO4yMMHbwBgT+YLEgsCgpUAY6LInw\nGKSQDMZ5PDoZuiDBraKBpVDwF98t+M5/T1CUgtZqZlISpYY4kcSRRAQtYcj99tskyoYx3FnLhSxM\nb6CEERBL4Tcv3P0khzirO2EGezCa+1FmP8L7HW1fUJUfmWK1P0F6C9tG8+rr8JlX4Du+R5Jg6MVt\nTBevCZ3koAb4S//Cu8hVjmGDEiVC5GhZYW1OPxhm05z3vHCfO+enJHGOYMogLM2wQTf7fee+7+mM\nGHeV4zhmNl0wLxNOTu+wOL7DbH5MOimJ45g4zVBxShwnDGgiqdBNh+6dEYy0BtvV9PWG7fqaZOck\nb93uhu2jB9TbDcn2Y+i65+wD38SsfIF2tiW6fMonf+ZHeOFD38IbrSV9/DEefeY3OS7eQyfWJDcV\nn/nMUzSQlI7k7LoB5qccvf3LyebHRHdfZnZ2HzE9Ip2UTiYXF8RpTpxmICPiJN2rPLw4e7Ne0dY7\nmmFH10c8dxrzj370p/je/+kfEKmEOMuQ0npzm4E0Tdns3KSVRPH42Q8Ymm2FEM64RB+QPqGIhdTG\n0MkpHxs9DH5kF8rFjeBG/iTJUEKPjUnTuGYFj1sGaCCKImf3519X538WOs/xJsUtEfyYme4LdWDf\n37pbHm57GdI+CiZ0s7/ykY9/QeP5nwrTFEIUuKL5HcAPAH/RWvtIuAz0X7LWvst3mVhr/1v/Oz8D\n/DfW2t/4ox63LDL71e97p9NMxYrJJGe7rUiSZHxjdT8QJW4sX61WZFk2YhaBaX/++ef5g9//GHGc\nUhQZTVuz3mx55pnnWK/XVE13S3pQ17Vj5JX0o4divV77DrSnqip2u53bGOh61lUXxJFIITHW7KNW\ncV+xcN6IFoK5ENbsLb4csSMYcKbAz07hP/1WePltMF8syPMlcYRbQVOOmVaRRUrnhBOKZwQhI8rL\nXQ7eUL8aKG0Qx+/H79BRGvZFEfbdrEtN9SC6AGMtmH1MQBJJhDAo38n2VlB3lkdPY/7g4z3f+d9F\nJAwM/4yiiU1RGF68l7C83vFv/CsfpO81kiVSzbFIVBKjjaCpB/JE8sKzx0zLOed3nyHNZwhiuqF1\nFzX21mXh5GkbVzyVEEQ+zfTo5JTj42OSJGFSTsmK0jmSR/E44SjlDJgxlmHosGbADi5eo2obhDV0\nmxWpktihR7QDg4ph22G2T2iFRmyv6TtDMTvhjadvcDKN2VU9WgmUnBCrmKSYIJOcOElo0pg4L0C6\nsPJpmoOKEGkxpq1GEoSKUV4rKf2Y7MbwnV8jbhiGgUm6YDKx/N8/8n/xfd//gyRZiRVQFAVm2Bv8\nOitCn/kt5FjQDnPA/bm7L44eb4wieQuDlITfiT2fKFFKjBewpunIU/d4YbxXStEdjPzgilzh5X99\n7+IrfB1Ba+sD2XzkLgeyIz+B6X4Yx/vD7jk8xlulTeOe/FhADb/823+GJsTCLW7+DvAO4HuttR8W\nQpxbax/5uzwGzv1/PwP85sGvv+F/9sfe0iwZJQJXl0vmi5mzeMtzhy2KhjRNnV9mniH9h3h6euqc\nh4aBj3zkI5wcn1JVzQhqH80XXFxc+K2fASGj8cAJzJm0MHQ9Inaj9WKx4PXXXydJknGzQOuePJW0\nrfEREK5gYl0Hl6iIRg/OVxCwB/KhRIa1Ll9g/eijgUcbzc/+CrzrbyhWV0uiBYipRChDZMPI70ae\ncVR3zlYHsom36kMPqKswdst9oQS30+5GLunCqKwX2BscRgrYSLji67l5gaDRDiuNIwcBaONWQDvb\nc3wGEQNWSEZK/vAmW4yBm7Xm6GzKj/70b/P+993n7c/exZrayZlsj5Ix5bSgrno+/dk1RV6zqVvu\n3Tvn+PiULJtgpUIbPGHR+RMeiok7SfpWMww9VVNTv/kGl0+fEEURs9mC6XzGfD4nihPyckKS5kRZ\nTh67KOM4SRBxjswjpK4pJ8cuWnZ2F60HzOBccxLRoIaaTryA1APKSKTQaDvw7i/7RvpWc5xqBhm7\nlVYLyIjeWgyCIytQSUySZggVISzEsUKw93vU3ml+GFxQYNvUNE0zLm0EguP4+Jgnjz7BD//Qz/Nj\nP/Nr5OWR26jLc7QdwEKapmN6K9a/d0Extt8AACAASURBVLof4QtpofePGacJxjPKezzTyX1U5FoE\nrQfCDu7gC26WFcDe6DdJIidAd7QoehiIYCyO4RZG8XA7xDLBPfe+aW+tP6okoenaUZs5HmYHus1D\np6TQoVtrb/3t/drlF3b7goqmH62/UgixAH5ECPG+t/y7FbfdbP/EmxDibwF/CyBNYj9qtaPRwWq1\nGq+Ah4J1w4Ers2f4Li4uuHv3LkVR0NQts9mMYehIkoRq15KnGd3Qe6BYjMU4jOrh72RZRp7n479X\nVYXWjm1L05S+7RCANn7R8qBYOQWo52Xcusy4OSCka+2UdKYiwhqCEw9CcLGOeHQxcO9I0NYWkUji\nxBvh4hyNnMWcL10HVXKv1dwXKuvn8YA5ShnWMNkL1y0Y4Zysh9B9+q8xwc/49ABfYI2xKD/mG6+C\nd6/XYa15BlMFa/NHFE3//mwbw6kSlIuU3//Ym7z04nPopgUbYcyAlO49iiNJryOqznBxuSJOE7Ks\noCgyFBCpCKWS0W/RpRD6zqeIMcaRha5zFAyDYb1eu4tgPxCnCX3fkeY9Wa8RcQpKkvQZKopRSeyi\nK6zBKomxGqEi0twymASjC0dqDFsWwmIHhZYaI3qkjVGlQNsehCS2xVg0kyxHKEleRE7NERhhjYN5\nBAzG+qJmaNuWrm9d4Ww7pyDwTYEQgkkxI1Y1P/ETP81vf/hjJElClmWuMBiLMRrpx+W+d34NYZoY\n1RVjkUtujeQH57jXbu47xKAxtmJvN6iUQGuJUvsRWYro9qaPihmGbvy7Y8yF2DupBwY8FMjhYFy3\nUmDZj95hxA6vZ49T2hEnDf8Wus63CuLfamD8x93+VOy5tXYphPhF4C8BT4QQ9w7G86f+bg+B5w5+\n7Vn/s7c+1t8H/j7ArJzYgLW0zUBZzmiHetwJnUzLMZpXSedwtNvtyPOc7XbLCy+8wPX1NXmeE0UR\nbdtijAtpC3qv9XrN2dkJVzcb1+oLt6JZliW7asOkzAEXM5BmBdfX10wmk1GGZK3g/t07PH16iVAx\nddWBdfknAkdQxd5INhPu52iXLd4PJmzxehzUFZ9YCTod87Dt+JGfhQ99A7x4kpHaBhtBkoJS1m2o\niDBa2wNgHu95Gd7VfbEyngwSwo6u38EQ2SA8sWbxq9hoC93gOlkVmfF5WosznsB1moNxJhi6dZCB\nS72EKFHESvPVL7+NX3/1hqbdfN7xI0yMFdBoy+XTHdPTOfeeP+Wnf+Z3+cvf8pUM3eDIBW1J5UAS\nS9bKdRDrnab69AWbJdy7s2G6mDObn6DSjMlkCuy7Cq3tCOw7vf/UFQFvY1b5bk1ITZxkTIoZWVaQ\nTgqiKGIymRDHMWmaMsiILMmIRESURhijsWlBJAYXjqcUUTpHiJreJggNiTLISNE1NXl2ihEdg7Eo\nXDR1PCn9yBFRGEm3W2GHhtamGO2235peMxigr12h0L3Xq3qWOo7Jc2dcc1M94nv+6+/lI//kE0Rl\nTpmnNHVFkqQHa8Sus8vzfLRQFEKg+/3WT5QlSN+9Z1FMrfsDuY9jpq0VtN6bNo4dWauke11937p4\njMGOEiQV7QtasIJrmgbwRhn+vO/7fsSQxtFfyrEDFMKtwQ7CgtGjycbh2B2K/iGZ9Vb39z1DL2+J\n3c2fwlDzC2HPz4DeF8wc+JeAvwv8GPBtwHf77z/qf+XHgP9NCPE/4IigdwK/9cf/FUO1cwYak7Kg\n63dMipJGOLu49XqLkhHT6ZTVeslucIFqQ9fSDRolI8rJdOwKu64hzRK6rmO2mCLjCLXzI4awHB0v\nHG4SRVRVBVaOHaYQLsyqLCbUbYWKM1Qck0SK1WZHPpk4s4JU0TQDCJ/77ItaGD10P2A9YRRHblQf\nBpfDo4WPbEVgbMe2gk89gfaX4du+taG7dhGubT4gjx1maaXv+iRud1xYopHVBu0LtJ/bUZjRhAM8\nj659d4kz1O2N+669/VzXO/yy7yxRbJ1hrpc4Cd9aWwMdEFscfKBd15IISCPB8y8NfPhBxISYpu0d\niYQAobA4H1IhBFe15dQ02NYwWSz4xz//W/zlb/kQpmtAGVqdEkvBonAnVic0bTfw8OIJq2pJOZlw\nfr7jmbvnyHLhBM5xRCQUiXQREgGng/0q3eG6XhjpdvWOutsh1pHfaY7Isowsy5BxRJrkqDjyOKMi\njtLxfkIIUPtVPiklHRBMKdr6IpxH4I+NovPMtVSslzfsths/Mt7cwmhDVzR2bFJiVcS0TAGFSuDJ\nxUP+7nd9F2883ZDMppi+w/hdUOv/XhCgg6WqqvH1h38LzytyCCVCCJqhRwXLNM+cYyza7mGtwWhU\n7OEuLFHiiqj1KZNuW9XFziil6IWmG1w8jROja6SM6HtNIgVGKjpwGuSDFckBt9nW1PW4au3sZ83I\npBsLaZYz9N2t9++gjvmudb8Oehh3IdWfrcvRPeD7RTCkgx+21v6EEOI3gB8WQvxN4DXg3waw1v6h\nEOKHgY/jbHe+849jzt1H6Q7qwO5NpxOv0xTsdjuMtpRlQj80pIkbO7pWk+U5pmlo6hYZKfeheoym\n6zrOzs7YVjuqtuHZZ5/l8vKSk5MjqqpxB48UpFnKduvC3Oq6HjOH1rs1k6Jg0JYkioh9xGjoXO+d\nLbhertjVPYOGKI6J/Mu02vhx1yVN9oPzBYojFzHcdwOxv/qmQqBFxJu7nmqAn/9twTe/X5GtB7Ie\ndlogTyyRkqCMcz7ym0DaOnd3Jd3GBL57wGNmTjAkR7B88IwoVtBZS+eLaOtzrPsBjJb0ViOt05jF\nUiCFvc2+C49hAYlwWlQpLUJa7p8PFEmMmkxQVUPX9rR9EBI7GMF6HPizDyvunLWcTOeUJy/xIz/1\nq/yVf/EbKfOULIppuhYpFFme0KeapO3Rg6VtNU2zYrtrub7ZcPf+OZO84HRxhMpSrBQolRJL79iN\nxJq9pZ8xhuSAHLD+vRt6H+9qLVXTsatblLBEkRtZVewcgNI0HotmOPlCAdpjkYz/7/7IvuMZR0MD\ndVvTDg5fk/Z2cRVCYiTkeb6X00WKaltRFvAP/tf/hV/9lY8g44y8cFCESidYY0csXvpi4chSM3aV\nobtLEhc61ntnoSByDzro/fvjt2cEdI3DEbMsHwt6wAgdg+2gBRFWlbVB+2Mzkp4tl3u5kjGGgSBc\n91InJUeySFiLGPZk1OF7ZAdnpBBJMa5uHhI8hwmXg1/1fGsH6zrhP8NO01r7+8AH/hk/vwI+9Ef8\nzncB3/WFPglr7Ch+xbjCdO/ePV599TPcuXOXzXrLYrFgvV5jtHvzptM5Ty8eMZvNQEifkS6Zzafs\nvGwiSRKG9Yq2bcfM9K7r6HuXKXSzXiGE4OTkhMePH1MUhbezMsSJa9tjFVMcTdhtbhBWE0nIMod3\nFkVB229whgTuyxhL5AXAaapcTKx3ptYaEhXAyLBVAcY4tnnXwasPLR98f0RRD65jjCxJvWfThQCh\nrbPzxned4YJqJYj9lrwP6nV/2wq36eENZbU32h2sK5aDcV/GGJ9A6QKxXK71QICsBRI9uIM0OCVF\n1pl2iAiKXDP0hqJMsdYB9JF2GT5vvXIaFI8vNHdPFcJaZos5n3jlNV5+6Vny0wlZMQPtEwdtjFIx\nXTvQDW786tqem+slKpbUxYRURUwAJVIGO4zbLkL4zN/wd0P3OS4PuBM/TfZO3uPYZ/fEgx28GYnV\nY6EMo+dbi2fwcgyFUvuCtd94Ec5hCUYZj/BMdiiQQjgiLhRopRS76obNWoPt+cVf+DWccDxj0MNY\nDHS/f+1SCOdFCWMXe7h581b88hDvOxxxD7ve8HrDeNv3/a3/joSDcay19Fq7fPqDET2O4/FxhRCe\nBOo9seis41qfX26M8aqT24Ybhyx4eG7hNRzKjcL7eCg7Gi9k7LeBbsma/oTbF8dGEPvVJiEEaZrw\n+oM3OL1zRtXUpHnGZz79OSaTCZOyIIpyuq4mS3M26y1JlrpsoSRmu936N8xydXXFZrOhmJbstk7f\neXJyQlmWPH36lMRLUq6vL7l79z4PXn/I0dHRiIdJKYmVoqm2TKdTjo+PWa1WRFFE1RRU9ZZJmRNL\nwWq1dQXNQtv1CAF9r8etCiFcXELT9uEcGdlRZd240Wh4cJ3wWx+zfPP7oLqxDEYhpHFxg0jiBIRw\nTHEQmIc6rLAj+w0+odDvrGssevAnFS68bbDQDoLBCjTQGR9NoJyBBcYitNv4kMZboGgL2lsxC5DG\nutW4QAZFHWU6pW0bsiwbdbSb1ZJd6wgz50zv/q4SCZ99/ZK3Pyc4mZSsq46f/eWP8PVf+x5efuFF\nyqPTgxPCWQiG8atuXBrp5ZNrLrnm8mrJ2dkpd05OycqMsixJ8wlSKVScjV3FSBaJsGLnUxP9mtSh\nbZgUFryTuTtBhVteOBjt4FC+5brW/WDo0wSUUylIKZFhnI/3KYhCCIS8XYCFEBSeJF2v19R1TZ6k\nnN8r+Wt//dtYnNxFa02924Jxet26romjhKZpKEuHnQbPyLA5N7LjWLbVzjHnkRqZdSklXdeN3Wpg\ntp0RsOMUwF10ArEUGOkkSVDGXQeEd0A6LFxCOGF9IGJHIb3fcHNaYJCRIhbueYgoorcGq/drn33f\njsFs1gYzDkHb9uP7Fy5it2EOO9ab0FkD4/cv5PZFUTSlVGgzeJY6dy9w0LR1h9GaJMs5Pjtmt9li\ntWG5XboTb7As5jPquqZtBpqqZj6f0zTNeBBkSUoRp6jC6dVuVkt2ux3T6ZSs77l6+oSzs3OWV9ec\nHi+QUtDUmvlswna3QaNIk5yqaTFVQ9cNFFFCs90xn5Y0ssIYw9F8TtO19H2L8oVH2YyqrokkxFLS\nt4ZIeeJFh11dQDjnISksjzcdH3kl5ngOL92L0FeDc+/uLBGGIYG8dBk0InNEz9CDjAJmeRh1ar2W\n02Vot9JgcPil0YpeQ6cNvXYi/MGCiNmbf0horfXhYt57sncFW0q3D09sGJSBHuSgKLKCNK7RRrqo\nBy+lmc0WiI0zh277ENmh0dawbCKWW8O9xcDRvODes2d84tOXXF/WfPM//y6ytCSNjzEWJpMcIWO0\nHuhNT1139J0e12AfPHiTx48vmMwmnB4dc3pyzPFiTlJOfaGLieMUGbm00sif8FJKrO/WBrOPhFU2\nZNzsO1WhXA5OKBb7TnHf0byVfAgZNodre8Yz0mPXJLnVrXZdx+PHbzK0Ayq1TGenpKnlr/67f5Vn\nnns7u6ah7hzOpywuVsK4UXs+n7PdbYgd/U/XdaP201rronb1QCQFWRL7teJ4HN/Dcwj3H4Xm7H0r\n+753BstdR5bEY3HuDR4u06Cc8UwS+SA1LEmWYgX7JRMEiYhIMoeJDtY4OZkU4CWCbV2Te2OdIC+r\n632GULj4RJH9PLikaapxogDhcVBN32vfURuUSvhCb18Uhh3lJLdf8e7nR6H6oRYrMOUGS5HlJFFM\nkqU8ePgGRVow9B3Hx8f0xjApcp4+fcpsNmO5XhHHMVmccXl5yWKx4ObmBqQiTR2OOZ/PnSv8MFCW\npft3IE3didX3mr6vPabkrtBV5UT3ujdo3ZMkEZeXl+5ElM6WP0rcFXpb7xj04M2lhZdTRdRtEPQ6\n5lkEgbzvGFMLLxwrXn7B8HXvtsRCcn5HcnQ0EEdQzhRFKSHqkZEgiV3qn5TeQFbuCaAgvRy0c0sa\ntCva/QERFLpRpMBYse+EPdiuOhzr3kJfRxiTYI0mVpppaZnNBJ3R7OoF/+QPpnzfjxuaQYzMbdd1\nRJEjUqyAm+slu6Z1nZdSTsJl4QNf9hLzPENJSZ4ZGh2xulry3DPnfP03vJ/5dIE0BZreH+w9cZK5\nNEdr6YaeXePY5n4wDF1PnCjunp0xnzsjkPl8QTYpXKGR6a2Ty+kLHW4nhHAmy8L4oDDpjaEDpny7\nUB7KV8L3w3ESIT//vtwukuCgqeCNYK1lNikRSclLb7/PJ/7ww/wn3/mf8Y53vEzX9qw9vh5Z5wSk\ntUYfCNT7oRtF367A7SNz0zQdibBxC8d3mntJkRlVBIdpCmOn6bfHqqq6Nf5GUTJ25kI4D9VY3R6T\ntdajWF1K6RYpfFEVQjhpnid2g1TKWs10OgfwChnzebKjwGdIKT0p3I1TATBOEMD42FJKoiTmF379\n9750DDukFOMIcGgKOgwDTd3SdwOT2cR9kINmtVkzmUyw2nB+fsbNzQoZx6xX7v6RqinyCdZabm5u\nyPN8TKYMAH0cx+OokmUZ1lqOj4+dFs32bDctbdNz994dtBnYrd14n6fuah1nGWk6ZbUKrkuW1fqa\nYTBU1YZed4goJs9KP/5JtpuKIovR1pEZaRrRtIN/zcFmy9IIeDxYqgeKSTnw7ruGJ08Mos+IY03f\n9bS1pshBpRabWEhAxQIrXZdrvLWcFX6itqAH6XNbLLUv2Ii92YILqbKjvEkP0LXQLd333Tpmt0rZ\nbgqmhaRI4XjRo08kRg5s2whtLQmSVol9JnakSLKU3W6DEIL5oiRrU7qmpe16Kg1CSj76h5/hQ1/3\nZeRFhlAJqtlxdu8O207zUz/9Yb7qK97Nl33Zi6RigkETRTlaWzLvwqONYc6CwWj6DnTvLohV07Hd\nvomUkix7zGI+pyxL4mxCnucUhSuiUeS6jZFdVQp8Rg04SEEIgZLBhWffpbr37/M7zfF3xe0Cab0w\n1uHtrfNJWK0Rwo2/k8wtdeTTIzJxxb/zb/5rPHi85cWXX0QPLrUgBAqGtieM30HGE1zCglF3uH84\nt0IXHApJ4AFCAQq45WHa66FfgxvjNYknZ8P9R1G6tXR9O06PWmuy2LkQWeO35jyTb6N9JEXovpMk\nviXiD8/tULN5+DcPN4HC4wZcMxBCDk4Im1HWTULitjj+T7p9URTNwFzN5/ORwVYqOHkryrKk7Vqy\nJCWNE7phz9S1rTMQrjsXY5FlGU3TMPOseBQ7g4k4iTCt9lKUHmMG0jSmrnfUde+F7SVt63Cy6dQZ\nfux2DvOZzWas1+sRH4ljdwJMvATJWrfbm6Se8a81kUooc6f5REZMp3OGrvLMozt4IuVD7KUrWi5V\nVnGz1Ugb8fFPwTvvS1prWG0NaSJRqVuljJU7UXtvZ2SkACuxY1yvQEvXKQ1G0ofNn9BZjt895npw\nnkvAaoHtLbtdTFsrNss56xvJxaXgaJZyNI2Y5dDUlr5v2fSCtkkYhobaY2LAeCLnef55J3Ycx2h2\ntJ070T7yB5/ia7/inUxTS2Ugkpo8z5BW8YlPfprZccGLz72TRDk3rK7X3jTZjdqDNSityeIIrdNx\nP72td14krVmvNu55ZFvyPGc6nVIUBXnm9JkqdqSLkBYp3D717S7RHJx4jvF9K9kg1G19YMirFxZ6\nn0rQNM0Y4aK1RkXOCyHO0lH2dHKW8fe++wd58/GO+2971j0/4VYVi9RnNg09vWeOrTFjZ+9kP2Jk\njsPncchaB4w3NCpvlWYdkj8hLfawsB3ugB+SXrGfzKIoQsXe/CaKnNelkpjBSfIEIKQY/3aAB5Ik\nGbeWwvM57OKVcnrP8PPIj/+B2DqUbIUiGjpnd8EwSKkwxisJ9JcYpokfewNAbIxhNpshhGJ5s0Kp\nmGySEilvHpwmJFmK7odx40N75jeM9AGAjtSe5SvLku12i/GjPNbQdy0vPP92XnnlFartjtlsRt8J\num5JOU1ZLSsilTCduTFWSsnJyQlPH18QHKebpkGpGGLBUDsCJi0LChkh6Hnm/hl129C1mqYaeP6F\n53ntcw+YzUpWqw3TaX7rylh3miiSXG86jmcTfuE3dnzwayVV35EoWFs4aiXT1pCklqSUZIMh1gaj\nnFjUic4tKLDCMmhN7wkfa4IdXOiU/MHoyRbbuzz2ZqtYLw2XFxN2m5xHr5csl4aqheWV5aowmCaC\nYcIbl5fcVBkPVzk2EaRCjMUgHMBZ6jrDrnP5MHXnHPTPjo7Y7LZ0g2ZbG37hNz7BN37NuzlZFMSx\nI5XSCURqxi/96sf57PnrvO35Z3nXe99FPplyKBdJjR2LFOydpgbORkla1zQYM9B7gmWz2ZAkyUgO\nxD4SJUkyYhW54y3JRtZXeKegwXtEHq77he+BUR61or32yo3+VleUJAlFmrkil8bjcwgX/2//97+d\nlZScvXQfZSzTWcnNxRUMA0q4z9ipC/YSmlDchBAkvrM73CkP43rorg5JkPCcw4Vtj8mKkRwKMqUw\nzoepLXR13dCPnWeRpTTaeau2rVuFHrRGe08EIyxxHGG6YewEJ1mOEoptU93CLJVyx1TbOvVLgPPC\nz8LzCsV8GIbR7eyw8IY4b/ccHcyD/sI3gr4oMM3pJLfve/k5iqJgtVoxmUxoG9c1hg5lceTMgrXW\nYF1kRZxE1HWNEII0z4hlPHZ9IWmybVsmZUHfuQOg610nmWfFiJ/0rXNeMcaw2+0QyoW73dzc8Nxz\nz2GMYXWzpCxL1tsNeZ5jtSEvMpqmYj4/4uryGiskjx8/Hj07hbBIkWFsw3q9piwXVG014ksjs2cC\nceMO/KppSZIIJVyHcFpKnjlq+br3ZkSmoYggLiTTmSGTUEwhL90GkYhApoAX1BvhC6jy7K733RTC\nAfBBuK4i5xwvBPS7mLYeuL6wPHkj4+njE3abhE0jqTuLJSFNIJaaUta8/Ow9LtdLLrYdbzYxD69r\nWu06m6HrxwLRedOIUBCOj495+PDhWLA2m417D1TCzXLFV7/3bbzv5XdTNTUoiFSC1ZpeO9yqzGK+\n8svfx/vf9y7iOKVpB2SSMliD0IOfCPYuPoeSFACsvFXY+6Edj8lQ/OIoHbuqQDYcSmaCsPvz5DBG\n3erY4pCJHkUkeTZ2PHmeY4V7TAzkecbV9RP+4ff/AK+88gq7RhNlE6aTfFSHtG1L0zQMxkmvpJ8Y\nwvEuZeQfvxtJvSB5yrwAPTDddV2PEdih0xtxQr/po81wy8ItSK2GYRgJprBpE0XSXxg7ZOSlUkKx\n221HL4fQrbdtKOZeGeL5DLRrfJa7DUmU+PdZIH08jNb6Vo7V2BEPevzcwud86J95qHgQ/qJujHHr\n113Nr3/0U3/2Lkd/XrdJntpv/gtfSdu2WOsMibeb3aiFdEyjZjabuZYcyXa7ZXE0H7GN5XpFJKLx\nAMiyjLquSdOU2XzK5cWVO0BKh19VuxqkcPdN0vFq2XUdtXeNKctyP55oQ5ZlXPn1SmMMWZ7S9y3D\nYDhaHPP08oI7d+7w2muvjRKq7aaj7Tbcu3ePi4sbBjvcyjFRymWnBDzp5mZJUWZEMsZa9/wsivOT\nIxbJm7z9bsTzJxYVGVRiKdOULGqZTCXFRCEijcwMKosQQkPsx3WFkyL5UDElnGZUCMfagiM72wY2\nV1BtBU8epHzu0xG76gxrU5e7riTSWIahIVICqzvyLGLXwdWuZW0jWqNQyu34OxzZd5pJjlKKi6vL\ncTc64M3T6dStwNZuZJ3NZrz+5ptkwDd/01/gxWfvcHFzjRYJuR9Lw152LDXn52d87Qe/irOzc4xW\nGPqxswJQYj9UHZ5Yh5jeYIOZhY+cNfu1vsMx75DkOcTRwuNJKVGZ6xjDl8TJaqSUqDgan4MScjxW\nHr3+Brt2w//xf/4wr776CK0ti9mEKImZlVNWqxWbzd62MMBUwnJLvmMQowzNGEPXtyQ++bHzuGaS\nxKNMaBgGZrMZYXkjvEdh28dt0kniWLHdOvvE8F5st9uxsw3EkFLxWKS0deC58nBKUDmkaewnjhgw\nDMNeH5tlGbrrIVZIgr+mIYokg4/pDrCIEk6GlvhMdeVx0Ld+TmH8D13+ocA9vHdfqDXcF8d4LnA4\noMdLwLX+9+7dY7fb0TQNxSRnvV67FSzEaA0X2uzj42N2693YqRpjxg/zyZMnHC2OkVJS19XY2fQ+\nSyRcZdPUmdtGUpFPMqSQVHUFQJamY2pf6JTAOUmDZLN2TvOPHz/mzp07XF9fE0UR5+fnPHnajc40\nqNtJe24Dw+3hOtmHs5DTVjMMhsm0ZLneUNuOVC94dNUyn2hOM82gYWdbdARWOJmGiA1yAGWcg2ec\naax0fIZQEistygqQBiNdZJz1yzpaO8Kn2sFuA9fXUNcSM3SO5Vcpve4xfQPaEBtBqiTVrmfVG9ZV\nhcmm9H2L1vsiUlfNiFU1TcPRfEHbO9ytqqpxO8UYw2A0x8cLAE5Oznjy9IKf+oXf4D/+a9/Kopyz\nq3uyyJ0Mu6FjMZ+xWm55+OiKj3z0d/nAV3w5p6d3nHOQ2Aucg5zgcIy2ntFWUqKsJSGQPhIpEqxf\nPXxrlyKlukX0jJHHByepitUoSh/dtHxnyoGMJ4li6rpmuVwy2IGPfvSjfPpTn2VSnhBHKVL05GnG\noPuRFAFuHfvWj9SBSNVmQMM4qUTeji2M6I4kam/hmkE/eTiOHwrghe9Ugw1jeL2H9w2jPVIweIMc\nKSVIeGt42iizEk5TPRhNEu9Jt8EaIvZLAuD0wJ3Zp1WGbvHweQYhf/j/sC4KjKN8uEgeQhaHF9I/\nsVx9MXSaZZHZr37/O8ar/m63I/b5xMGJqJy6LKDtdkueFU6KVLlR5ezsjOvlDbF0WrE0Tb3PoCOJ\nNts1eea2fara4ZZ5VjjZUlGMIHVVVePWUDBEOLSQEsJ1C9PpFDM401qlBHXd0rVu5A4Qg5SSfFJw\n8XRF3ayYTqdcXi5J8mTEtsLIFzwgw/palhV0XUNW5OOVP0kyMJYIzck85r13O+5M1ljpxvJYue8o\niDKwqULFlii1SGWRMaSZJEqdxjJPLEliiZVCSI21gr6VLK8MF29mLC9jPvepiGonqTpDlCQgFUJG\ndFZjO7cKF0cu9KuyEZ2VXG93fjQ0WCEoisJpMTdrTibOVLpqG0cWeIgiXAwdhqZpe1cQyqJAxa6o\nvPngMd/wNV/Gv/yhf46b6xVN05DnuTN56QcilbDb7VhtV8zmJSfzGe95z3u4f/++L4zp5zHbhyOe\n69DkrfsIIYgPBOfj/Q6K5Fu/73hdCwAAIABJREFU9g94ex893Jx/pys8F5ePefLoMUfzOXma8UP/\n6H/nd3/n4/S95XgxxeImmN1243C7rh8v1m7BovYLGNFIigBuJ1y5qJhA2oyQkJR+hHcYZVjR1NqZ\nGAQJjlt/7D004UZfVxgZi2fADg+3jKQE/GNLPBsvLX23N1DJ84K+bwgoSd+3oxRQCGci4j4fQ+z1\nk0q5ILdIuXG9Nw4jbvtuLH6OIFO3CmmQHoXi+Nbd/sML65+LCfGf120+ndgXnzllPp+PeIpGYwbN\n0dERSkieXl5QluX4AYX2Omgnw5Unz/NxbHAni7MOQ2ikAknK5aWLAy68S8yg976BTecA5SxO6OqG\nVg8U5YSmqseDv2ma/WaEt5QTxtLoHukjGaxgtB9brTbjwWgMbDYbytnMXQSq3XhhCPu/6/WG6bQc\nRxUpHXYb8tonkwknZcpCvcb5XDKLG6xyUahSWYgBJYgiCakGCXkWYcuBPIFEwWwCWaooCrcqiIXl\nBq6eCp68esLqWvDGg5hVu3UguRSoRDnRupUM1u3rWmuIhGbp40B2TUviL2pVVTGfz7m8vOTo6Ijr\n66XLePE42GqzHvWbUkqur68pi8n4PvR9z9HRHCklz9x9ll/6tf+Xehj4r/72f8Bz9+9zeXlJKyW6\naZzBcFHQtQNWa1ptuLq6QkrJ29/+dt7+9nMWi4UTyicFQrqT2a2N+rHZnwr7blSN21UBG1NK0dt9\nwXQStf3vjZ3mweOE3ea+71gur3n4+A1HksgpL7z4Nn75136ZD3/kN3ntc1fuOMZw967b9tmsr9lV\n1XgBb7x0bhicSXKSJLTar0d6obn1a6FDr8ei09S70cHJyYg6d6zHKQZLHKcI9kbEeZqNPgsB93XS\nvD377gqlGbvMIO1J08yP2vtR+rBzDcz+PkEhQuvBWzoOI7btpjhGP4hwXEgpR21o4C4O8eOw0RTI\nKRmpPTuPuDU5hN8jkvzKb37sS6doFllqP/jlLxNFEZvNxjHYph+vbkVRjHhLuJIEDPAwIMmZfUy5\nuroiTR2G88yz51w8vUEKB6JLCcfHx05y4mULxn/oaZoSJQ5MR3v2MU1RccTqZsnR0dE+WtRo8jzn\nZrnyGrKMfmiQwovnq52LUrBOMH3YCWy3W+IsZb1eI0U0suZhXA8YV8gxEioaDxat9Sguto2hzAz3\nj5/ytpkB441uE8nGGISS6NgRQTIxzFKYzmKiRJMVhskUFplCSWenVm0Ul09iLl47Y7cRvPqgYZBu\n+8Jat3bZdc5wOMYVutZqbOL9bCKnarherkdNX2AxXZFR4/Ov69qtynmc6+bmhqOjIzarNdPpdOyw\nO6Mpi4Iiy530rO/42B98Am0s//nf+Ru887lnqTrBer0miiV57jogJaKxiC2XS7bbxrPCcPfeHc7v\nnVPmMxaLBUkWnNuDO/rhOmN0axwFZ8ociqZSyl2ouL0FBE6AfXV1xfX1NQMdwkqO5ieUeenIh37H\n9/3AD/KHH/s4TddzcnJClmXcOT1ju12TJAkPHz5005VXhARSKcAaQrh97YBPKqVo2po8K8bn2zQd\nRrtOM8BgWZF5qMt1Z23foYd+j/NF8QgBBLlSmJBms9l4zh3CK+HYDedh1zW+QLtjARgL8KFcSQiX\nXQSMutDAyockzMBThNv19TVFUYwFFbh1HoXuU0o5ThRB8jXirQevL0kSfv43vjBxu/yT7vD/x00p\nd9UJUgJrLfXW7ZbrwRCpeBTUBknFycnJLX1WGFviOB6xzN1uh0Cx2WxYr5ej7Gi1cuPd4YEWZBZt\n2xJJhfBCZCklSRTfyqBp25ZYibFgH52cst5ukFKOek7XMbrvoevtvD5vPp87DMt3n+EkG4aBoihY\nLBajEw2AsIa+bUgiRZ4mDF2LtT2rbsdmEDy+nPNkNcOqCTIGawyRdSOy7hR9q9jtYLuDzQ52laRt\nYWig7Sx9Z50YfJAMraTvIrCJNy9xn5EQbqNpGMxYSKz1bkpxQtfrkbkN7+WhzVrA9UJ3EZQRi8WC\nqqp45plnxmiRgANmPv6gahpWmyVWt7z84vOc3T2jnM747//H72O123E0S3n++bskscBoTZ4WTCcT\nYqXI05Rn79/n+eef44UX3kYcp1w8veIPfv9j/N7v/R4f//jHefjgDZbLJW1dofsOKcyY++TMOdx4\nOH5FEMWCKHadvTNqGej7lu12zWp1w4MHD/jkJz/J48ePfReWcf/+sxRFwfn5GfP5lJ/62Z/kk596\nhTgtmBRzb1oBbVvT9S3b3WZ8LwAij0tqs7e701oT+Skr3M8aRpxeCEGUuIvAZDIZH88Ygx7MCGMF\nX80gug8Yc8BRQ6FJkgi36z3QtvX4HEKH57TLuZN2BZd49mRaOJYCdxF+L0R4hG4yTB/hdohRhqIb\nOszDUTs8z0Mn+PDehPcn/L1DUuhP0zx+UXSa00lu3//y86Mcpe/7cT/cGEPV1JTeIDZsARwaCoTW\nO0h9jo6OuLq6cmYcVyuKIqOc5kSx5PLpahyHCx+lMXiCQkpJ1dQUaUY/DG4H2bqrY+lHBfCu0sJl\nDJXTmSM76pbZfMLTJxecnp4yGE1T1X4TJBoZvXEsUe61rlfb8W+HA6JtW87Pz8cOIxw8YVQ6OTnh\n6aOnqCxBCEu33TIpM+4fJ6hhwzS+Zj51+FPn1yQrA0NmUREkCZwv4HQqKY4seeSckPpWcvMo5bV/\nesKuMlzXA+vBkOJwvOlsTpQUXC1XdI0rflvd01lJErltoHAShXHSMbUJ2+2W4+NTjDHjxUQoOS4k\nBNhhvVwBe9dtK/AXuhuySPHC2553FwNrePDoMQ8fPuWlZ1K+5qu+mm//D7+dtmpYXa/YtM6kWinl\nfTHD1ocCm9APGoGmqiqqxnm5Kuvw6yiKxy4uSvf6zXDR1mJfsAD0IG5tl7mCX3itcViZjDi7c8LV\n1VN+8B9+P5/97KfZ7Fxmzmy2QA+Wu+dHTl1wfcFm4z02O7cOOp2UGGPYNs6tq62b8fnkWeYu9p5I\n6VsXSRE60MEOTNKCpmlGlUjTd0TSRVgL6V6PkhFG77WnJqT+yH2iZyTV+Dh975ZCghok3K8sC5fq\nyt6xKRThcAwfis3TNAMclxHewzBthQIZuuHwGC5/qEEixkbGaUv3YvhQxAczjI1RmBIC1iuldPKt\nYeC3PvbZL53xfDop7Nd/4D0sl8sR1xz6HmMtwnehSRyNuErYO9Vas1gsKIqCx48fj3jNMAwcHx9T\nVRVdX9E2mjwr/Rvl3sjtdks5cauW2uyjQwejkYMhn5ZcL2+YTUr6pkX5k2e1cid1ANvnZcnFxQXP\n3rvPut6RpTmXl5ccn56wXrqIhjR1+F5g3fu+Jy8nVFVF3/Qj6RQclJbLpYMo/Oix2my8G9P1ONqW\nRxNO5sd87tXXmR6dEQ07stKZlRRi4DiXTNVj4qxBKugBoyN2VmMUZKVlMZfcP4EyNSSRQPeSeqW5\nfPASq/XA03XHspVExkUMyEgwGIGKS5bbtY8dUPSNRebK7fwvXUdfVRWLxcKdoE3IbBKjcmG73SKj\n/a5w6ASGzr3msDl0NHNbYlXfOgepbcXxvVPyKOP+3fu88fR1LpaGerfj6aPX+aavfTd/+zv+I+7c\nfY6macZ4izSZYK0miiXGaPJJhtVuIrE+4TB0/kLsFyKsdVPMoXBaelPdOI69vGi/+TRqb7UjMU9P\nT9Fa8/DBH/LjP/HTfOZzj6jqgTSfkKiUttnx7LP3kRKWyzVt6xJXAwHZdQNd05LGbozUPtlxGAYm\nuYuixheaysNXtjcUZcnN6hptBvJJQV93TKfT8cIs44S2rRl8IZqVU6qq3m/jaAOxHNcxw7Gre31L\npxlFatSbhotkaBCs13a2beNTENy0FTb5wrFQ1w3CNyFSSsqyHD//Q2neersZR/SgMxUeYw163O12\nd7vIRxGDZ9xD0QwTYtu2HB0duQlQwq9++A+/lIpmbt/7jmduYWAjrqQEZVlS1zXW2pFgAMYPq6qq\n8cphrWWxWNC3DUopNjtnfHBycuJWNLuBfujIsoQsdWbHxydHjojphhEiAOj1fmRpm5o7d+5wcXHh\nroTxPkqgnE64vr7m6CCHva5rrNGcn5+PLP7l5SXau+NEacL19TVZ7LqYjT9R0iS/NSoIIUiiyPkS\neqwnzTMGz6SGK3M/2DEKZLu+JoliItGxKAUYSx51WLkmSmNXPNIBlcK8gMUCikySRYphk7BbZaw3\nKU8uBBfLhnVjiJUlTWNkkhNlKav1jrbXZEXOZrdGRoXvIlrquuZodsS2rkj9lkucJuxWvoDlOYPZ\nwyFZko4dSJDGbLdb0jQlyZwMbOMvHFJKtts18/mcOIp49ztfZrNzYu8oifn0pz/N9XLJZlPx7nc+\ny3f+zb/OBz/wAbSfRq6v1yTxBD1YTLQd5ThKxSgZj7DIKEoX+1XJyHecjq3fTzlZDH1nybIJeTZ1\nEJNq+L3f/11+4sd/kgdvPKJqap577nm6bqDv3DTx7DPnlGWB8NncD998ws1qyTB0XhfpCkHozMFt\nOEkEWZqy3e2wwoeS9QO579C6uqH3mLsQgs12S5nl7LxqYRgGppPSZ2DpW11f6OSiKMJ4Sd6hEcYt\nPagxGFwj0/sIDEf0JGht/DQYjZOdg2c6z7zvR3OlInb1zr2uzAn/Y6loh368MLVty66uHK5dN2OX\neEgaZllGVVW3sP+Abx5isnG6N1jGZzElacYvffj3v3SKZjnJ7de8753UdT3ml48aMLnXVwWyBhgx\nzEMzgjRNqWtnD3fx5LHDV6YzNpvNiGtMipKq3lGWBW88eOSEun7PPXRER0dHbDZuPzmMWNPplKdP\nn3J8fOw74inbbYU1+CvoQBQ7ic1YzNIJb7755qg3dfiSw2Gurq5GcFxrzWQ2ZbvdomQ8vr7xihxF\nJFnm3ewdk+2iZocRF2y63q+VujHXDAPTxZRHjx45X8koxnZbun6HkoY43jFbpEzSltMTiBQUKaTE\nNNs5fSu5vphQtz3b3iIiRWcFu067/W6Z0PYDdduQpjFt767sm82K8/Nz1uutnwrcxonWmiSKkFE0\nulbptnNdZde5dUclmeXuQhZGsMHscanQgYaLUiAK79+9O3ZRzz//PDc3N6x3DU+ePsaYgVdeeZX3\nvvM+Z3dO+Nf/yr/K1331VzKfTxnaYtxN73t9yyh49GqM9zhZKApF4TrKJHZBfEWSst2ueeVTn+CX\nfunneP3113n19SvyYkqaTxEyJlfKMcTzkixza5p5mlE1O25WS66uruianrptmC6mLovdF/BwPEkp\nqduGSCrKyYTVeo2KI2IVeT2sKxh5ktL5C75SCmMtsUpYetNtN5JWt15TmqZo7wcQyDPYvw/h/An/\nH7rvEH8xdP1YrEKX6YrZ3mUoiiJ2u8p3gGp0h7++vqEoC2IVjT9TOB+BUOyGYUBGXk7kN4bC/vmh\ni9OhqiaK9huDoets23YkhqSUmMGbBGnDr/3Ol5K43e5TBA8B5b7viWJH5KRpOhbHw8IWRpXAtiql\nWC6dtKXv+xEDDXKl1WrF4mjOauVG4K7rKCZu9D07O7u1TRAig7Ms4+bmZhw1R8DdWmazOdZarq+X\nnJ+fj8x9kiRstjV3799js92OBsZZknJxdTluG40Httek7rb1yB4HV5qTkxM+9/rrvPDCC2w2G3o9\njFd28CMjgsYbs+52O972trfx4I3XmM1mZJnTMEoiVDJn6GuGxhLtUvpmIIo1eaaQ0q2nCSlRiaCY\nKJJJBHVNqzV17WzlDJa+axl84ZbR3hPycNfXnSTDKDhurSUJQugDsmg6nfLk4inFtByVAQH3Cs42\n4YQMr8/ZzEm/vPCItq05Pj7m8eM3mUwm3JkWxOaMi9WaF156iQHBZ1675Hv+3v/M137wy3nPe17k\n+Wde4sUXX+Tu3bsOHhDJKMAPf7fxUpqAzRpjmKQOo+66js++8kkePn3IRz/6u/zTT3yam2vXTZ/d\ncaQPSjKYnjzJqeuKO3fuMJ1OHGzQdTSNM4Wp2oZExv492xEJybQsWS6X41JFIEPDsReKBn41Morj\n0XR4kk18IKCHn4QgjtVIwIRROcuyccEj8kRp6Oyapr5FrgT4IhCkbdtSlJNbmuNg5dj3w/i3wmcX\nZEmuA+bzNuPsQR0o8gKGPfYZRdFoVByee1EUe4mX/33Ye1AEIhLcVJplmYOCPNR32EWPnecXcPui\n6TTf+9J9ptPp+EYKT+xLtbeNg72rddM4Ccnp6Sl17bCYoNdUSjGdOAurbVWPfoCu+8tJ0hilBKvl\ndiQhur4dtyXW2w3HiyPiOGa7dgU7ThOePHnC8fGxH73Z20l5A4DdthrHl7quOT49GQF9rTVlWVL5\notgdyDu6rsMIPM7qOtu6rvfJen1P7LeVhBC0vTNX7joX53p8fDxqIbfbLZNpyRtvvMn52blzri+c\npKYsCi4vrv3WSI9SFik7ikwzzTKSuOeosBSTDGskUZyz2cJy3VN3lm0vMFpglMBoSdeFk8Jhb+75\n+XC7QZNE8dhpSiDxq63T6dSdWN5ZJpJuWri8dBeTgFenaTqK4AMUEiaKwxE6dGJFljMrS6bTKef3\nz3n42iPu3zvnne94gd/63Y8BsFyuqHYdQiiKTPL666+jtbsID8bJ3Y6OjpzfwWKBRNDWLlOq89PN\naltzdXVDURTcvXsXKyfEsWJxNCUvYrc+GuUIA+946QV21RK0ZLFYEMcxjx4/pKoqHj1+6roxr7Ps\n244oTwFDs6uI1W1Ls7CWWBYTljc3CP//02LC2sMXWmtSFaGxY8FovXZTW+MutsL5DATSKjQrYfwO\nt77vxn3wt0JGwbGq7btRWB7G8DiOPU4p6Lp2XBtNkgQ9+KUGKbi5ufERMxFCufyg8BkXaYZmP2U4\nQtg1MGHCmM/n3NzcjE1H3/ejDOlQt3noB9o0DULJEcrDG7wgBb/6219ineZsOufi4mJfBE3nx+2G\nk5MTlIy4vrkiTWOqyln5103L5aXbYy7LkpOTE7qu48mTJ9RJTJrnxJ4sCuuRTVOxXoZsoFM2mw1t\n40b6cdVMOqLCakOWF0RxxtXFU+bTGU1VkyaJWxUcLNPp1HW8WOa+c43jeASzhYWT01NublZYK5hM\ncjabHUkSoYcOpAvrssYynx25K76E48WMqnEdWuI/4M5LnspiMq58lp6IKsuSzdatkF5fXXD/3hnV\nrqIs9915lMT0DK5DEy56w2pJkh9zsesospJl1VNsU78258aW3iiEUojesK0qTs7OaNoKZTR9Z4EY\nISxRJMeOKIijp9M5SRJh7EDb1UgFxg5MZxPWG6cZ1NaQFTl3799zKZ5WsFp5hl0oYhVR7xqSLIFI\nMc1L370KttsNJ7PFCOyvlhuauuON119lPp/TtiWPnzwhlQ57m2bHnByfuckhLZjPZw5DUxHbekUc\np+jB8vTJFVKkCBNT1RUnJ0doXSGE/P/ae9NY27bsvus3V9/s9rS3e13Ve664XHaVLcuKRISiSIFy\nQAl88wdEJCKM+ABEICEbSxD4gkB0XwApNJJFFyEgwoocGZs4GIvYTlXsiqvKVe/53dfe5nS732vt\n1U4+zDnm3reIq95LXvLevZwpXd1z9tn7nDXXmnPMMf7jP/6DH/7iF3j69Kmjr/lohlnOeDAiTRNO\nj05Rneb+gzOePHlCGESUTcl8OePb3/42g8HAGcvx9IjHH35AliUQ+uw2G1u2aLSbfD+ka2siG14W\npXRtNTi/j8e2KAjSmPXOaDWsioIsSZ3B7S1lqO97fGUOKB9Tunx8fMTVzTV+GBD0gUukiqESHuNh\n2wvA8TONgI5p8CGGab3ZEieRSyqlqfGE0RCFIV2rafrKsWHCUBOqEK32+p6lLTLZC1jHqLKibzsX\naS6XS4dbSoJJrmFvWrSJnnzbpjgKQSsCP6RuKpSnaOqG0Au/1yr9keMHeppKqQT4DUxzwgD4X7TW\n/45S6i8B/yJwZd/6b2mtf9l+5ueBv4DpOvuvaq1/5fv9jfEw11/+Y6+5hEld17TdHqPoOtNEK7P8\nrywzEm8aRWBPDQnZJKuWWk9Ta02xMeHqYDDg/Xffc1zQum4sn9OEz9J8rVeKrm2YjidcXllxidp4\nOHJCad2RpgOePn3K3bt3Wa8XhGFCaJVj6ro2Op9lSbEzxmM2m3H3/IyqaizNCIIopigK0oGZd1mW\n5EnKrqkJA0Ma9pVVZMGIC8xmM05OTqwXmdmQsubk5ISi2NhkycZBGmEY8vDhQ+49uO+k8aLIQA6e\nh9NcDMOQrilJ4gj6jsnkiKLckaSxoVDVHdtNZZSdJqaXeBwZuTfxRuTgMaFf5Grux+O9uMrR0ZHL\n4g6HRojC0LZK+wxi27akAFvn3bcdQeSb+2LDWOmDI+rkkkQ01WHaqFKtVvi+z+uf+5zVzsxZrRY8\nePCAP/jWd7hz5w6Xl5d88Y/9MPPlwnx/MWM4ygkCj6LY8cEH73F8fMzJyRllWXJ+fsrV1RX37t3j\nu9/9Lqen59y/f5833/wOL7/8gPl8zp3zc771rW+iUcznS5qmcnisYOxRknJ0dMLFk8eGD2p76qRx\nwmazsUbH4MLSVXJgizdkfQknVrx2KZ88NBqBzWgL9FHXNXVrsuZZkjrMME5St3+EVlfXtavMKcvS\nhcqH3SvleykoCcKI1dowQUx2u8P3Q7s+AleRlOe5gzzW6zV5nru/c8jEEMMtGXvxHrfbLYPBwHmW\nkpeQhKKUVFdN7Q6Buq6JQpMX6W2DvL7vyfOc/+M3vv6Jkdsr4E9prb8MfAX4qlLqj9uf/ada66/Y\nf2Iwvwj8DPAjwFeB/0IdNlj5e4yu61CmVTPKMzJlujckXd8L2JWVWxziUQimopRyCRW5mVKtobWp\nmW2ahqIoePz4saNQ1HXNYJCTJPEz7S/EzRdytXhOUWJC9LptCKLQtFYoCoajEbP5nKZr2VWVow3J\n3wEcdSKOY9brreWyDWjbfl+nHsXPgNdC8RAZL1HMDsOQPM8dlCCYaxiGfPjhh3aDNi6UXywWrNdr\nzs/PKbcF5bZAd2azNJU5xbNsQJ4PKcsKgpim1eyajk1ZsS5r1mVJ02EyztqIlAR+5KTVDNG5ct4v\nwHg8dCpTp6enaK3ZbAq6TrPdlgRWW8BI6Cl3z46Ojojj2LUVMQTmDqX2ghdt3ZhMaxRTlaaktdiZ\nCqNO97YUNuHk5Myq52g+fPyUh+++z7e/8yYq8Hnlc6/yhS+8wdnZCdPJiMVyRrHZcvHkKWkSsVmt\nOZ4ecXZ2xunpKV/+8pcJQ59XX32VKAjJ0wzdmbK89WpGWaw4PZkyGg6IwoC33nqT7775FrPZwvay\nMdzNtu0JgojxeOqgBTlQxKMTY2GeTWaTlWYLrVYrAEf+Fk6jhNH1rnIHuxOvsPtMjJLWmihO8JRv\neY2QRonrY45nICAZ36uefii6IV8fHlqSgU+i2JkZgQCEh334GfFIDzUZZC8f/l7R2xXjLCXVkpwC\nnBEXoymepyujPMCED0s/JSfyUcbHwjSVUhnwm8C/DPw0sNFa/0ff856ftxf179vvfwX4S1rrv/VH\n/d5Bluif/LE3HEG1701vbulkaFz0CE3rEgee8tmWBejeGQXBtpRSdNqEFn2zb+NZNTWtzdh6FlQW\nDGU0GjlPd7ZccjSdUO9K/DCi7zRVveP09JRHjx6ZdgR5ytXlvpTLD2A4MG2GtTLhSxSY09XgPqZS\nKQ4jrq8vGQ7HzjiWlcHK5GDY1aYO1/OBrmdne+CsrCcsxtXzPNMsbj7H90NOT09ZrRau6uawAsMI\nMvSEgTG0YpSarnfexTAfcjWfEfs+SRJR1y0ahTa9J4kiQ+mYjkeAZ5NsEIQebdM772e73TIc5XtK\nS2/YB4J5SdlaXdeOjxqGIU+fPuXVV1+lbVu225LxeMhyfkOre6rafGY8nLg6/T3WZwjwVVU5zzWK\nEue9Hh8fM5/PLdyzJc2McRcxjh96/Q1bHGGucTAYWVJ8ZPVRp5aG9mxvncePH7Pdbrm6vnS10nJv\nAz9E+cK5HZBlJpRPLAsiTVM8zAGSDXJLx6ncz3XXu0aA4/GQqjQH6OnpqdsTYiibpsEPA8bDEU1d\nsy1Ms7/W0o5WqxWnR8cu0+x5HkW1w1d7onkUhvRau2yz7/sksVHeyvPcGSNJsoiHpmwUJN6mYbz4\nTsdTkkFSICAREPCM8ZX17Pu+Y5porZ0HKftaIAPhg0rCR/a+GPbD/4udMYjy+zsrQxcnkYMiPM/j\nb/7W739ymKb1FL8OvA7851rr31ZK/TTwryil/nnga8C/obWeA/eB3zr4+If2te/9nT8L/CxAbDXw\nDj20pu2YLxdMJhPTTkB7DAZDs0A77UIS31M8ePCA2WzGZDIxrSWAfGg2URal7KqKtjeYTu5IuCGe\nB1mWu5PZ8zy2W1NJcnn5lNPjE3Z1TbWrieKQDz74wIHtUlJZFAVHR0doWmO8woDO6hOKyIfBYExS\naLPaHiw+Qy2Ko8h1QIzjmGJnarel6iMIQqctCiZ8ETKxtOTIsownT8311Y3xXtarLYDbjALe933P\n6ekp19fXaAvgR1HAu+++zZ1796l3JTuLWe1qgx8ppVmv19w5OWa+mqN7CZsa/MAnCH3CKKWqSgbD\njNVqwXBoPHfd24RNZWguYeTTdrVJrAwG0Pd4wGQ0Yr64IQqNNzKbX0PTEUYhOrLixduCxt6r+XzO\n5z//eZbzG26urrh79y7ldmuoTZhmXtEwZ7WYcf/uHcP/DDyKrRFADmIDH/zhux+QRjHpIObhm+8Q\nxylxHJoOqUHIN77x+xwdHXFzc0XdVJye3WWxWLh2HVmWsNkUbLbmeWl82l6zuJkzGmf4sanRlkoa\niRqUNlVsPYr1ekkQ7zd72xqxlzCJHS7nBT7LtYEbwjji3r17vP/++4A5cC8vL/E9D2UTpWFsDill\nW/uKAlcYhvgWksFTeMqWqp3eAAAgAElEQVRj21RkQcR0MjFG20Z0Ulcu+7KqKtfxtWka06tL62dK\njJXq8H1jkO+cnnE9n7u9JeG0eHxiLOdz6bXVHUBg2gkdy8Ev3rKwYsSzFdWlsiwd+0Fq44UqJd6k\nSPuJ1oUIkH/U8ZFqz7XWndb6K8AD4KeUUl8C/kvgc5iQ/QnwH3/kv2p+51/WWv+k1vonA39PSZCs\nuK88As9ns14RRyF+AEW55eT41GEbSRSDVlxdXqPwuL6+dmVz9a5E6Z51uUF5kKUJngICRRDZsi5M\nxVHdt2y3W3tDPbI4ZjKast2WREFI37X4XkCW5kRBRBaaTRKExlhUu5J619B0ratWWq1Wjh82GY1N\nvXjXcn73BD8M6NH4oXlwu67Bj0J2TU3fdmRJROjvFZt2dU3dthwfH9P3vSXvV25hyZx9L2S7KQn8\niKbeh1NCI6mbjtFwwtnZGcvlkuF4xOnxCYkf0pYNZ2dnVKVZcMPxmB6PKIqf8V6X6zVhENseSrZW\n2DfFAGVZmlr/Vcmd8wfUVYt3IP6L9gxOW3dcXy2I05TFaoVWis1mQ5ZljIYTGzq1+F5IPj7CD41S\nvqJHhcbzCMPQJQ21Upyen/Pk4gKtlEkAxilt37PabPBCj7I0lSI9sGtqmr5jV2yodwVh6OOFHt/9\nzkMgoG17FosNbaN49PiKwWjMarMlG4wZT07JsgHFrqYsK46nJzSNCTuXy6ULKdu25+VXHuB5AQEp\nZbnl5ZcfkGUJvq8YDDKSLGexWpoGcHUDTcdisaDvW7I4otmVDGIDQQzzAYM8c4mSqqp4++23Xamp\nkOHDMET3PednZ6heo9uOcWrgnNlyQZxkJLEtIun3nUL9TpNmGevNhsDqN/ihdUzCgE73hrWRJIa+\n5pnDdrVaOR6meKNxGrOrK3o0F9dXdLqj2JUo3zNMAVtlVVWV82wnkymLxZLVak3bdnTdQYM2DFdb\nqncMr7ZxUaI4MV3XkWY5nm9ablSN6dPeNI0zpEmSEPhQ7XasllvybADeXnn/o4yPJdihtV4Avw58\nVWt9YY1pD/xXwE/Ztz0CXjr42AP72h85lKdckkXwDakvBxy2J+V5YFx6OQmlBDLPBo6ONJkc8eDB\ny9S7yp02abzv8yK4iNAeJpOJqXVnf8JJuJXnOdvNBt/zqJuGZbl9BnuRcDn0A6bjiVnAlnAsD1dO\nRpP02JfsaQWRb1RrdGvUuKMoII5DFosZpkezUQiazRYYmbjKbRCA6XTK2dmZw2rFOxBCr2C6dV2z\nWCy4ubpiPB7b/jhLkjwxWma25YB8XkIvwX+EkiKLUHAnYzgjsnRgMWbTNlmSUII/Cy1st9txfn7q\n+KzSKXS3M+V24/HYwSVVVVJVxksK/IhdWZvKJGlEZxOGWmum0ynn5+dcX18DvRNvMUZCO2raq6++\nTNvW6F6RZAO6TlMUO8fxFbEV6R10fX1tukVuNlxfX/P48WPG4zH37t2jKArKsnSJyLquOTs7Q3ua\ny5tLmr5hvpozGB1xeb3gg0cXrDY7FqvC8SQFllrtCo4mUwZRxmq7odIdneeRDHMaeggCdNezK0rG\nw5E9jJtn1poG8sGA9WaD5/uMxmO2RWH68nQds9k127LA83101zMZjdFdT5wkznsWr1DCcKHqHOYL\nhEOc57np7Cn9k5RpHzPITJJHhb5jkghmKzCKlFHudjvDTbWR5uH+FCy0aRoWi4WLtgSaOGwb43lG\nwDuOIteEMQ4jl/iV/ACeT2iz+k3T0DW9sysfZfxAo6mUOlVKTezXKfCnge8ope4evO2fBb5pv/4l\n4GeUUrFS6jXgDeB3vu8f0Xu9QgFv5SQ7LPOSEEBuUpqmzyRb+r4nCmPXb0ba9yqlDGjveU5eTjZx\nlmX0befKrkQMV4B5qTxK05Su79kUW6qqYjKZOAN1KOUmHSsPcRrYK02L4ZGHWNhyz9xKn62LrVu0\nk8mEzWbjWkE0TcN8Pmc0Grk5CK4jXTOHw6EL3WWxS8gDuEUn+KMYnMMwS1Tk0zR1oZJgW/K6SN0J\nUH94wFVVxWAwMI/W4saHeJio7su9OTo6YrVaOTxvNpuRJAknJyf7yiAbhvm+z3w+dwUPcvjIofDo\n0SMX/nZdx3q9doeJMDPEwHHQMVJa5h5WhsnGdHJqSbJX4Sr3Cj/CGJA1cMgdLIrCaYjKPZP1cZjw\nk06s2+0WzxqPfWjquzJiV6mk9wK7YDq5SpLFiGXsBXdNIke7ijTP2zdXOySrSxJUIhRJkBwaT3mP\n/G6Z/2EoLdGPODoiviNrVrjRsrclq39Y3y9JMLk2eU2eg/wtwc0lMXr4OwRflnUo89iVVrVeWxqW\n7an0UcdHoRz9GPCL2C4zwP+stf73lFL/HSY018C7wL+ktX5iP/MLwL8AtMBf1Fr/9e/3NwZ5or/y\nw6+5+tG+7+k7m8SwD1hc9TwbuKobuYGiEpTnuWt3satK59rnabZ39QOP7XrDMB+YmmnPQ2tTUZNk\nqRPMkBs/Go2ckvx2u3VVREHou9/vYdr2+sG+3FOM8CFYDXByds7l5aXFiVKqtuJoPOH68srw9o6m\n9M1eXToIAralCY1lkRleoU8YxywWRuez73uH56Rp6mryRQxktVoZEY3RyFUbRUnCeDLk6toS3hup\nypJDK6GqauI4eMaIiCGVwwV7F9rWhHpNWxH4e5BdSkuDIGI4HDKf3zxjtLfbLZPRiCzLmC0Wzyjn\nTMeG7rJabVgsFty7+4CdzeyKp3FycsSTJ0+cFoEYcOPlmg2hemPQ/MhkW/NBShjEvP3224yHQ8tm\nMNJ8oiRvSvWUi0hkPWw2BVXT0NY10/HEKqjjDtLZbMa9e/ecZ2U2s/Fexftt25bl0gpQ2P7nfhgZ\n8e2+J1I+WZax3m5cQkspbbpjhqETdfF9n7ZpTH35yNwr3fUOw9RaO8WhOE0oyy2hbxSmsiRlu9nQ\na02cJg5D9zzP9BIKfVfGKfe6tx040zR1kodSyuv7vtFmyFKH93sooiR2CaHJZOKkGSX7bzjUgYvK\nptOpwWd9z60RoQ/KgSEl1Ye15WZNiCZt6A7nXb1vmNd1HRqfKPSo6x1REIP2afrqI5PbPxMVQcM8\n1V9642Xnjfm+T1ntjHL70cThJnEcP+NFyLXLDVS+x2a1dgrndV3j+YYrluc5aM3SVvtst1uSNN7r\nZ1o1pSwznSuLosAPPALPtultOvIsxUPR9y11p2jbmuloZDxKepabyp2+WZbRdhW7siFJMpqmIgzN\n4g8sFSNJEharAs8D3VXESYSvYF107jQ/DIkkFN7LYLUo63HUXc0gHzmPs6pLwiB2tJ+u61C+505/\nX3lG3HeYcXM9d0aqaTqnyARmkUmpXBCYDdU1rdMDkM0RhjFFsSHLE5vIkcRW6Kqb6mbn6viVUqzm\nC1TgozBVXFGScnN16cjfBrIxhQbn5+d0XcPNzY2Db1IRn+33+pK+b8tuowGonsEg5+rqitE4M5VT\nVzM8LzCHoU00Xl5f8dJLL3F5eemUrE5OTpjdLBgMDYPjlVdecT9vuo6ush5VbA6Ho8nErL1BjlaK\npqrMGksS0th4qJvNirIsuX//PlVVcXl95Q7lKIr43Kuv8M477xAEgYONxMOqGlMqPLYJziRJnOrV\nYDTk8ePHTMcTPM/jcm4U6wdp5g45z/OYXd84Wh3gDgpDhVs7jz205ZhRFLGzHEetDYG/qmt2lanq\n2qw2BlawXj9WLaoqymcqiSaTCY3lVzZd62QApe6761sG2YD1eu0iCgAv2EebEtUJ1DPIcgLlUVin\nRHQnDttwCFQ3GprkU7ErSTLrTFi+aBSEDob6zb/znedHhFhrnsEuNrYqIssyRzgPgsCVSYqqkRhP\nMEmIpmnMw7SfES1KCVfX9vdKl8SrqyvXb13oEiKGLKV7r7/+Q7zyymuksck+G+8qckoxy7XZCNuy\nQilNmsZ4nul7YsLUDOj34hvR3gNbLpcEIdTNjjTNqXYtm60hIY9GI46Ojp6BJcR4yuePj485OTtz\n5NwgCEwm/4CSNBqNyPPchS55nhP6hoNa7HY8emTgZnl/nufOmw7DkPF4TLHZUu8q2rpB2WclYd1m\nszGbomm4d++ek4MTOtBhpUbgR4RBzHZTcnM9NxnsIHBY9vX1pc3UqwMPCSvisnGlcwI7hNYLWq9N\nt0+h1JydnRHFAW1bMZ7k5HnKdDrl4uLCcnzh+vqSk5MTLq4uHVG668zBIPBJkkaWXpbzzjvvuPmK\nlsH5+Tm+PcyGQ0P2XywWFEXBZrPi/PyUNI1RPsznc+cx3dzcuOo3gUOUUrz11luOOnXv3j1Hq5H1\nenJywmazcYZEaq8fP37M+bkpmV0ulwzSjPtnd9gVJb7yDD+3LDk9PXWQkxjry8tLpz3b9z3T6dTB\nGGVZQm87JigDGZVl6aAimU+SJIZPaiM68U7loI+DgMD3UGgi30f3HW3duDp/z/OMpsIBf3MwGJj3\nNCbhm6eZ2/tJZJyHxXrlPgO49XYYATl1+850s+0aI6knySShK0lxwEcZnwmjia2TFZzG8QrtECwl\nz43XcJigkIoBMXaAIwYHQQC6p+tbU8Me7qsLuq5zGNYhsbaua4ajAZ5vamXfe+89Li8v8XwTgne6\nN10sde9Os0NcRqpettst2vYDknBCcCUw+E0cxzS7kjQKkYZqhvgduKymfFY2kOCWgrvNZjN3/WLU\nDyEBCVUFcNc2fJFQSDKxshGNwr3J7m63a/q+JQkjBmmG0pr+oMROvAihMV1dXbnEzyFNRMKoum4p\nCtNQK0kyimLHcrHek6FtWC6HlsEId1RV6TaB8rQ7NETt/ejoiNls5ojM19fXBIFP05qQzvPhvYfv\nMLu6ZjQY4AFZkvD08oKTkxNjTHpD/zEcwt4pbUkCRAy/7/skUcTVzbWbo3STFBEW834TicjhCDiO\n4htvvOG4w5tN8QwGXRRGyvC9994DYDydMDmasiu2VOXOOQNibA71C1zisWnZbDagNXEUufogeU8c\nx456JAeXYJGSlBFGhtT5H9aki/fbdR1JmjrKju/7NFXtDKrct7rZ4dukXdNU9G3jrj2OY6POpTUo\n0xe+7Tqag7JN4VE2TeOgDEkcCVQgcJbsR5GIkzJd8XD7vqdtOgI/NB0h6sZ2Wv3opvAzFZ6Ld6eU\ncvJnYRS4ByYeqHgihwkVE97FlNvCKbeYEkSTSNgUBowud5VTCOq1qUvfFSVltXOY1CGPrLdE2DAM\njHahHzpwX/iSApgfAtLmMzFVVbprLoqaKPLAM8kMgDD0GY0mrFYbWyaZOGzwEH4QIyUP/uzkhPly\n6a41igPWq70BSdKIsqie0SjN89wZpE1hFt0br3+Odx6+5wyceBGCkZpDzOCxph2D53DKvThDyXg8\nJcsSFssZuldMJkeuTFMOii9+8Yu8//77zOdz80z7Hu+gEubk7JiqrF2WXSnFnbMzowJUFIxGA+fh\nZlnGcr1lOj2m783hkec5l5eXHB8fE0UJXddQlBvybEgUBNaD2nFxccGP//iP8/77H9I0DaVlYYyH\nOWdnZzx8+JAsG1iGQOfui1RgnZyc8MHjR0yGI9q6oe5Ne9ksSdEKmq5jlMVsCourewEnkynr9dJi\nuoaT+P6H7zEcHHN9c8nx8Zimag8I+DYpNl9xdnbiiOjL5ZIvfelLvPvuuy5JKNU70v1ROh8kcezK\nETuMoIl5jp1lmEzcs5AErAxl3xfbnEFd1+RZhvI8wigwmg9RQioG064Lo460c1xOrTWd7lB6XxnX\nNy29TfBVux2gSdJ9DyGp6Nlu1ntminUWRB7RCyy10JYkyxoTqEMUjfq+R9tIL0kSis0WJa2Nwz0/\nXNPzt373zecH0xxkif6xL7y6D+MCY6CaqibNEudGS6ZUivQFKxMMKIhCV0srp2FbVgzGI+q2sQmc\nCA/jHZyemXCn3lXEaeJECOp6RxjGFqsUEuyCKEmpq8ZoCCqj8u57gQubo9iA0ZKh35UNSmmC0MdT\nPkqFaN3Qs8coF7Ml2cBUXNRdbRkAiVsIshBHo5HrpX52dsbVxQV37tzh0ZMn5lRPQsrClJeOx2NW\n6wWBv1ed8TwPLG9xNBo5cHy7WZGlBtsaj8dst1uXuZXQp9PYslOjFD4aDF3ICCLHtyLPU3rdEoUJ\nWivrQe2hj6Y1fzPPDUaaBBlhEjOf34DqUZ4RlxBYYLlc0tvk1NGRYRJ86Utf4u233zbG2w/t3zHY\nZlEUnJ6ecnFxwfHxGU+fPuL4+Nhk/C1u9+DBPbQ2WfUwNDzYNM9NxVCoKIodw+HQJRGGuRFEuX//\nPh9++KGJDg4Sdk1Z0ShFud1yNJmy2qyJkoTY99iWO7zAhPiqa+m6xhHym6bhenZF1/ooT5PnMU3V\nWq8/oOutV4RHudnioRkNh8yWC+cQHIrMhGHIarE00UgcWY84duwP5XvUu8qV4EoEdJhklb0XBAFJ\nHKPbjt5Tjurja6g6E7UB0BsZwdFoxOzmxrSpvrjk7oP7LJdLl7Rs9b5ZW9u2BL7PtijwrAfpeYrQ\nXutotNe/rZvKwR5939PtauLM1scnxjGpdrWjBQZBQJobSE/WbpIkVLWpfiqKgvPTM5bLFWmakqSp\n6YA6GqKall/5f373+TGaeWqy573eZ2Z7m7yRWu627sgyE04X5dZREZqmcSRwD1Mz3feAbonDgLbb\ntxyNooidFQOom8bJs/Vtx9HxmL6Hpm6pLcaZHnDCJDwPA4snpQlVUxsXv6kpih3jUe7KBNHKlZ+Z\nMAE63dO3jdP2E7yybhvCxADUaRRb7MyGh82O44lRne/0nkQtBg7MwijL0npjIwB3cDyjf1gb4ruI\nXcgBJBjxZDJxfVrMve0sH2/fh0WoMWLM3eHUG2NXlTVJFBBa0P6QmnSIW+e50XsUeTKpNpkejWnq\nzlFbjqz3L0Y8iiKSLHMJG9/3Cb2Qo+MJdV1YxasJ0PPkyRPOzs7Yrjfm3luIZCi9pCxXtSgK7t69\nS9eZypfZbEZVNbz++uuU24IgMOT40chUy0ynUx4+fOgESfB8RysSb6oodpyeTmmajsV8gx8oPv/5\n13jzzTeZTEZcX1/Ttj1nZ2csZnPrPScu3Ban4OzszKi52zYgxa50EZbSOL6kPFPl2z49We54poYX\ne87Tp08d91jCWDG+hx0v5XmUZWUdCHM49rpD22Bf9mka7XU+m8b0r1qt1y4Sq+uazkaCsaVriYcs\nEcVoNGJXlW6vSZIx8PbUwDzPqZr6/wNXxaE5lIrSQESB7zkIY7PZGAqXTfpINZGIfoikoumYEPF/\nf0QR4s8IpmkwN9HQPAxLZVNKaFpVFbrH4ZeCn5nFZjK7QSC8rj1nS0QHPM+jtAkD+bwxKibRJBtT\nIAFZWE3TsCsrdx2dNt34/MDDU5DlsVuIvhfYfuV7FXAxGgLeS8hssuC22b19zyE3Vbwy2Ot3CgYm\nWJJ8RnQqRZRZwl4xhFInLwbS84xC92uvveay8UJzOvQ8AOetCl9QeIdxHBvvRRkhjcP3CSwxGAyc\n1yxzOKQuyXMRKs6hgIXMT2qOJWly6OkadScjBjKbmXYRdV0bT9XS0qQUMAgCqrJktVrx9OlTV5xw\nfHzMYrFiuVzT93B8PGW5nJtSU62dsRGR3Tt37tC2EEXmYJUyw8lk4kjiVdUYOptnujje3Ny4A+r4\n+JjBwLAqTN8q5RKSksgcDEyfKjlk1lasQw5bya4DDpMUGEb4pcKv9ZSia1uOplPGo5FriSuliMZr\n29F3HcV2yyDPGWQ5k/GYwPeJowhfedBrAs8nDk1/nvF47LB2SXaK8T2kzck+koKHw26scvjKuhCc\nvapqlPLQGtq2I45MmxnfC0yEh0dVN8wXS0PxS2LOz8/d/TCqVoZEP5lMHK9ZnvlqtdqXrH6SPM1/\nFGOQJfqLb7zksmNpmhL6VkDV0mtkUYohgmfbegr2EUURTVujbCc88YgON7OcZoJJipER4reoigcH\nYeKhekvdVKD9Z+pZoyii1w1xtPecZDGZUDxluV4RRYED5MuyZJANwVMsN2t0r8hsi4ggsDgTHYF6\ntk2xspie4H51XTt9QfFgJbu6XC6dMIbGiGeUpREG/l6CeN+bNgKu8Zkn+GbrSPly2Ighl0qhzGJI\n2WCEUvs1JR7qIV4q1R4G892LP19fXzMcpU4ST+qUD0tshXB/+PuUTb4Ix/Ts7IzttrSKUClKw+np\nKU3T8PY7D7l7977z9p88eeK8RE9ZVkG54ebmislkxPH0jNVqwWCQsdsZ2svx8TGXl9eMR1MTsmd7\n8RG5p8r3qeuWxWLGSy+9xK7YGOGM01MuLy8ZjUaMRkaZXfr1RMm+tYXc49IeRKrtGQ9HzNdzVqsV\n9+/fZzlf8NJLL/Hmm28ynU4ZDAYsVuZ5F5stP/IjP8Irr7zCL//yLzMZj5/x8jaWcF7XRgH95uaG\ns9NTpzo1HA4pN1vqrrV0qQ2pNdKHeQSJBMXbvXPnDldXV2ZtW52G2lYA1YK12gSs/H2ttYsaDlWK\nhClyyPGUQ9t5nKHpyKrb1u6t9pmEqHGSKuccyT+JcC4uLsiyjO12y9e+9dG6UX4mPE2NeJU+mS1r\nO/TE4jhmV5UOywzDmKbp3GkGZnNq5bGrSpIoNFJt9Z7yIgkTaQss4gl93xNEIWGc0PZGwXk4HDoD\ne3Fx4U7jtm1dPyGtQCs4OzthMhmhMKHLrq7odA+e7078Z6s0jFBHlg0YDAztY7PZEPiR2/iHWfO6\nrokC3yaUFF3XMMgS52GL9uBmswFw1CwpT9xn7jv3HlEiunPnjvNWDyushLt3mHQTvFk8eplH34NS\nPqfHJ+Y0L8whIu8VLyIMQzzg7OQEpTW662gaCf98tts1d+6cOWOslGK1WjkvVWg+ks2VZ5JlGeOj\nMfPlkvH0mE4rVtuV4/YZeEDz5ptv8ujRI46nRyilHVNCKcUrr7zCxcUFw0FC1+7IkpjRYMy9Oy9x\nc3PzTGmvUoqLiwu6ruGll885O58wHg85Pz8lyxJOTo6I45C+LkkCn8kgh7ai6xpOT49ZLBacnZ0x\nmy1YrTZsNgV13bJabayalcmoF8UO8KhLW6Nd7SDwXEQhPazeeust10plPp/v14ytC3/rrbdMcmm3\nA6WIk4TVeu1auEjVVBybRm2SxV5vNiS5qabbFgXaU2zttYg8nGDVURS5PfPOO+84es9hlZrouEpk\nUu4KFss55a5gtV46ibvpdOoYFFW9YzgacHQ8JctTgtAnzRLTbHGYk2YJwywhTxKatmNXtZjzRtG2\nHWEY0badq3aTaEEq60Tkx1AZn0NP80d/6BVHAxIMUsIQ8TIPS6iCIACl3WkyHo/NyVzUJKlvDY9i\nuVi50MHzPOJkLxIsYQT6WWpMVe9QeM51b5qO4dC0IA2jwC20QwLvIW2m6zp0D0Hos1ysHHYIErYq\nF8LFieFOboVzqnz6rkP1miTJbMne1oU3YMoOr2cLR+IX4yQlh6JHeUhvkusUj1K85Mxer9xjWfBC\n6xgMBmhP07XGu1iv16B6xqOpo4PM53P3zKZTUzggoiByDyWklwMhyzLoe5oDL/Lo5Jhis2W9Xjtx\nEtEAWK/Xzks7OT1yAsQ3NzcMcsMrXa/XjMdjsiwjDkM2m43ziKquJ0tilG44PT4hjlOavmKzrmjq\njnwQEtka7sViwd27d1kul4yGR8yXM5quZ7XcovyQu/dOaKqS2Cpa+YHtP2+jC0NDMtj2/ZfuMZ/P\nqRqPINQMkoC+Bd0rVrb0U4SJm6rmpVce8MEH7zEYmLYnIpAh0FGW5GRZdqDY46FUBwQEgUfXNUbh\nq9wxn8+5d++eC/nBtruNTILTj0Kn8hP5AVVr1vXEKh2dTCcsFnPn+T64e48PnlyQJkbdSukOPzKd\nAZSH4082jfEMexsBtN2+7NJT5vBNrPE0h/zWZc0nkwlXV1dMp1Ourm8YWnHupjee9mKxcJGQEwWn\n57XXXuPiyVM8P3DOgu+H1mnal/vK+p7NZg7OMvmOhP/rd77xPCWCYv2TP/pDLsEgIbgYo0O8QTa4\nbFLZiGBKLtE+va4MnqmVMxzi6ss4VDUR3p+EqXFi8NXVamVxIx/obYWRemYxy+8XHDCKIprahPtx\nEtHaPtFSrmnud+88xen0mOvZjcFrWyN8MR7mtvKncd6fYH8Slvo27JUDQZRn5PQXj1MyrFI6KQbc\n9ZjOMncgyfWLdyz0ld7qcDqyeqBAe+6+Si3+brdzWJnv+w7Ql2uXWnqHr1YVPbiQfVdXrveRkI4P\n8VWBVSRKqCrTt1qwWTloPc8o10+nUwfbbDYFw2GOpuP0yBjnIPLJshHFdkdVG3X/q6srXn75ZRe2\nGUX8I/q2oeukmVmB5wUs1yvyPHedRU0rFnNYRYGdRxiYstQwYLXaEPkR9c7yOkdjh9nLoTUYZCwW\nM8Zj0zhQ5i1FBIvZjcN2Z7OZI8MfH5+z2azQ2ggJb1ZrkwW3lV1aK3a7winVKyDJM7cuVK/R4AS5\n8zynbExS6tgehEkSEShtvbiQbVEgIi++r9jZWvrxeMyjx4/dvhyNDc0qsN6cURryD4pKPMcQEf7l\narUizXIC3zgvddehu97h/uJAiYh30xqREG37mhsdg611wjq3XiSfIBCaeO5dp/nNr3/z+QnPAZfY\nOCSMS/IA9kZOPCXBVeS95mY09mvpZWI+I6G+ueEmpDQbILTf7+tXDzfrYaJCws0otD2669bgl36I\n7rGUImMURdhBrv1Q2AH2bQMMX7I0iul4BH70THYToLBJK7k2+R1i5KR8TP6eLFTBP8XL01ozsiWf\nko2Moojlek3TdSjfB8+j6Tq0UmilSPOcxh5SwpUTyoooJ0nofpgMkKy+eMFy/6SdhRhCuS55fmLI\nZYhog7xHIgzBVsWASrLN8zxnKKRFQ9eZhnZHRxMye0BUVUXT9WitePz4MbvdjpOTE55eXlM1HU8u\nrih2NYvVBq18PjFmZecAAAtWSURBVHzymKvZFWHo43uQWraC7/tUzb5nzvX1zFVD7XY7ekTEZUNV\nG6+y2jVkg5x79+64mu6maZz3I1VsksS6e/cuNzc3vPzyy9zc3DCdTl0ybDQaObhqtVpYfHrft1yS\nH2IIBwNTqpgkCYHF2tPUVEsFYcj9e3d5+aUHvPTgPi+/9IBBlpFEAfP5DUr3VGVBEgUsFnMuLi+J\non0iSXBEz/NY20SWCG5UVUVT73MCu92OcrdjWxSU9j6FUcyuquk1xEnKYGgq2aQ4QNaBrItDvFNk\n4wS+ExUuWesiKHKYUBRHRrz8tt0r1f+g8ZnwNLM01j/xxc87jw9wRk6UXBzXz7rxEhoeEt173dC1\nHsrr0T00jSaKPPfgzI3jmZsmvExJOGmtyQem/nxvjDVtV7nQIgiCZ+pcnazZIKPvtCOHKw8UezVq\nQ7juEE9TKUXbKxei9b1ZdG3dEKcJ4NH2ewWjruvcdYqhkuSIqGHHccxqtXL3SBIeh/MT71AM0KFa\nt9A55L42TUOSRuh+X77Z65YwMFUiV1ZmThawVKvIMxQjIhtKFnkYhkRBwOn5uSWTZ2zLgjxO3O86\nOjri4urK4auHSkmy+JumIbQ/O0wW9hhFp6urK5Ik4eh4wnq1RSnfap6a52t60pdsNiuiKHEbe3+I\nKqZjg4nd3NxwdHRCuTWC0E1XW0Wo2h0qu13h1oeJBExSaDRIuFksUfg2CgkZ5QMnh3d1dUU2GNHW\nO/q+JU+NB9mqzijM93uqlmgDCG3M8wKkVBc8yqpgNBi6A99ko4WBYdZmOhrgdXrP10widNU4vHI6\nnVIVBXfvnXNqE0TvvP2Q4fQIzzfP9MMPP3SGCuD4aGqy4lYLs+3NgSusCpPUM/Ymz1NHsL++uSJN\nsmekHgVqiULzzGfLJcN84Na9lINKJZ7necRRyGZbHNgFZfdEaMpLraaBNGQTZkrfmwqwv/3Nt58f\nT1OBKyMTqoy4z1LKJsC+3HxDVTBN1tq2p2n2mpUmhE+dhyICpCZrFhEEHmka0/ctu13hPBzxYK+v\nr10W8bC1gj5odyAPS8owoyhis946LzGO98bjkL8n0MJuZ9rCDkYj4jhktVown9/QtrXD/5brtdOf\nlENkNBq5euW+7zk+PnbzlBFFkaMZCTctTVOXMZQTXIywgPmH912MrlH68Z+hZUjmfjabmdp0WxQg\n9BHxeiV5IoeP7/tOqk8M17f/4JsEocdmu7LPxGzAPDe9wfM8dxCFbBgJuUFKbFvW6yVta9pvtK1R\nhW/rmigIwCYgTBVTjef5TI9POD4+ZbFYEQQeg8GIo/GEYZYzygdMR2N224LpcMDjx48Jk5Tei7m8\nWeHHGcv1ijSJ6eodu7J2OJppsxG6Z+WHIV2nuXxqxJs9v2M4ysmzoZOQk4OtKApUYCKJ8XhMGifu\nOZ2enlo+rjHEnhcwnR4ThvZACQ3zZLFYkOc519fXzOdz51mPpxO2ZcHJ2bkR37aemnRybZqGOMlA\n+URxytX1jKLt+PZb7/DbX/sGb779Pg0ei/WWhw8f8vCdtxmPcpegOTs/dvSpu3fvOi8bDD95tphT\nNTWbYmt6bdVGS1Qa1EkSSxwQOXxvbm5cZwKhkYktMMyWtWOMRFFsDxHPiYCbnEDpDlRxQHa7HdfX\n15Rl+UxTt49krz4rnuaPWpWjuu1o254oUJZSIvjDznmdcND8vTEeoHTtU/YYCKzQr+HJ7bFQCWvF\nEMqmblsIIysc0uPoLOIRCnn4UGBCFvQhnCCGR9SB1uutSTo0la297cjzFAhQuqfpauh6osGAzXZL\nGpp+z4LibssdbQ9pHLMrjPp1EEUkUcTG9oIJPI+iKhikGVmS8uTiknw4pKs70kwwwJhhnnA5Wzre\nYhL4aP+gb4vFiYqioLFYT1EU+FK5Yefl9R1+nNDWOwKlWTVQ2/7yQfAsJcwYeLP5faVp7cEU+j49\ne7ilqkz/9sVyRuBHdJ3G8/ac1K7TxKFvGARaOa9WDLZSCvqWptMEUczRZOpwyTSNmS9uqKuWk5Mz\nW2Zo5NJ83/B5NRV13ZKlRjov8FpGwxPWxdY+54bTY9Nnx7MVXXJgbnYVTVMR+j5NU3H37l2iKOLR\nkwtGg4S2UtS6QdOADujbms1mRZgO6DrjLAShx2pZcDoe03owu7lhlOb0GJx2OEpoq9Z5m6vN+uAw\n9hlkqVXB6oyaUlUTp0OSKKDYbMHTpPmQXbEijRPmyw1ds+P1z3+ed959l+PTO+iupq5bmnbHvbv3\nefToicWbQ3RvJNuub2akaY5Wljmhe6cNkKUpdV25IghxFIaxx+ff+AJaax6++x5f+MIX+LW/8VuE\ncUvfhSh/x67QNsG11y7tdYfu7R5VvVHvV3vx8e12S56PiRMP3Xtsi0uOJncp6xrPMzxfz7YWjsKQ\nZWkxznrf0VL0X+M45bf/7nefn0SQUuoK2ALXn/a1/EMcJ9zO73kfL/oc//8+v1e01qc/6Jd8Jowm\ngFLqax/Fyj+v43Z+z/940ed4O7+PNj4TmObtuB2343Y8L+PWaN6O23E7bsfHGJ8lo/mXP+0L+Ic8\nbuf3/I8XfY638/sI4zODad6O23E7bsfzMD5LnubtuB2343Z85set0bwdt+N23I6PMT51o6mU+qpS\n6rtKqT9USv3cp309f79DKfXfKqUulVLfPHjtSCn1q0qpt+z/04Of/byd83eVUv/kp3PVH20opV5S\nSv26UurbSqlvKaX+Nfv6CzE/AKVUopT6HaXUN+wc/137+gszRwCllK+U+l2l1F+z379o83tXKfX7\nSqnfU0p9zb72yc7xUDThH/U/wAfeBj4HRMA3gC9+mtf0DzCXfxz4CeCbB6/9h8DP2a9/DvgP7Ndf\ntHONgdfsPfA/7Tl8n7ndBX7Cfj0E3rRzeCHmZ69ZAQP7dQj8NvDHX6Q52uv+14H/EfhrL9IaPZjf\nu8DJ97z2ic7x0/Y0fwr4Q631Q611DfwV4M99ytf09zW01r8BzL7n5T8H/KL9+heBf+bg9b+ita60\n1u8Af4i5F5/JobV+orX+O/brNfAHwH1ekPkBaDM29tvQ/tO8QHNUSj0A/ingvz54+YWZ3/cZn+gc\nP22jeR/44OD7D+1rL8o411o/sV8/Bc7t18/tvJVSrwI/jvHEXqj52dD194BL4Fe11i/aHP8z4N8E\n+oPXXqT5gTnofk0p9XWl1M/a1z7ROQaf1JXeju8/tNZaHTbPeQ6HUmoA/K/AX9Rar0TGD16M+Wmt\nO+ArSqkJ8FeVUl/6np8/t3NUSv3TwKXW+utKqT/593rP8zy/g/EntNaPlFJnwK8qpb5z+MNPYo6f\ntqf5CHjp4PsH9rUXZVwope4C2P8v7evP3byVUiHGYP4PWuv/zb78wszvcGitF8CvA1/lxZnjPwb8\nWaXUuxgY7E8ppf57Xpz5AaC1fmT/vwT+Kibc/kTn+Gkbzb8NvKGUek0pFQE/A/zSp3xNn+T4JeDP\n26//PPC/H7z+M0qpWCn1GvAG8DufwvV9pKGMS/nfAH+gtf5PDn70QswPQCl1aj1MlFIp8KeB7/CC\nzFFr/fNa6wda61cx++xvaK3/OV6Q+QEopXKl1FC+Bv4J4Jt80nP8DGS7/gwmG/s28Auf9vX8A8zj\nfwKeAA0GG/kLwDHwfwJvAb8GHB28/xfsnL8L/PSnff0/YG5/AoMV/V3g9+y/P/OizM9e748Bv2vn\n+E3g37avvzBzPLjuP8k+e/7CzA/DwvmG/fctsSef9Bxvyyhvx+24HbfjY4xPOzy/HbfjdtyO52rc\nGs3bcTtux+34GOPWaN6O23E7bsfHGLdG83bcjttxOz7GuDWat+N23I7b8THGrdG8HbfjdtyOjzFu\njebtuB2343Z8jPH/AhX/2QOZPyYDAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176a81e3fd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"img = cv2.imread(pTrain[80])\n",
"\n",
"rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) \n",
"\n",
"plt.imshow(rgb_img)\n",
"plt.title(\"Label: \" + l_train[80])\n",
"#plt.axis('off')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"XTrain = []\n",
"\n",
"for path in pTrain:\n",
" \n",
" img = cv2.imread(path)\n",
" \n",
" rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) \n",
"\n",
" final_img = cv2.resize(rgb_img, (50,50))\n",
" \n",
" XTrain.append(final_img)\n",
"\n",
"XTrain = np.array(XTrain)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"XTest = []\n",
"\n",
"for path in pTest:\n",
" \n",
" img = cv2.imread(path)\n",
" \n",
" rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) \n",
"\n",
" final_img = cv2.resize(rgb_img, (50,50))\n",
" \n",
" XTest.append(final_img)\n",
"\n",
"XTest = np.array(XTest)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'apple': 0, 'banana': 1, 'mixed': 2, 'orange': 3}"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fruits = {}\n",
"\n",
"for i in range(len(check_label_train)):\n",
" fruits[check_label_train[i]] = i\n",
" \n",
"fruits "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of train data: 240\n",
"Number of test data: 60\n"
]
}
],
"source": [
"# storing the values in a temporary list\n",
"temp_train = []\n",
"temp_test = []\n",
"\n",
"# all the fruits names are being mapped\n",
"for label in l_train:\n",
" temp_train.append(fruits.get(label))\n",
"\n",
"for label in l_test:\n",
" temp_test.append(fruits.get(label))\n",
"\n",
"print(\"Number of train data: \", len(temp_train))\n",
"print(\"Number of test data: \", len(temp_test))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape before one-hot encoding: (240, 4)\n",
"Shape after one-hot encoding: (240, 4)\n"
]
}
],
"source": [
"## one-hot encoding using keras' numpy-related utilities\n",
"n_classes = 4\n",
"yTrain = keras.utils.to_categorical(temp_train, 4)\n",
"print(\"Shape before one-hot encoding: \", yTrain.shape)\n",
"\n",
"yTest = keras.utils.to_categorical(temp_test, 4)\n",
"print(\"Shape after one-hot encoding: \", yTrain.shape)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Length of X_train: 240\n"
]
},
{
"data": {
"image/png": 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vv04e2C0dU5Z94OuOTnOXvN8DKqNGLuF+zBqcarSeikPKDlMXqqAXT5CUrhDs\nrG6+PbFO7JKUcsaTQENXJdIFkJFxP4PZftnPpp/c7bTpSqsKScrQsb5hoqNzOLu2j2IoxtrfRkST\nor/rAJwKYAWAuwHMj5rNB3BXSSMwDGNMKGblnwrgFiJKIP9lcQcz30NEiwHcQUQXA3gNwHtHcZyG\nYZSZgpOfmZ8HcKzn+FYAp4zGoAzDGH3Mw88wYsp+kcmH9XdY+LrTJkHSuBWSLK8UOjWjAZDyqGCZ\nYYf73Ki+mrTM1vvy4qVSfv5ZR+dXM6QR5+/OOk2Obb17PQg2CTFxgOvkk0rJzDG5QNpkA7geI7mU\nNBIGddJw9YY7P++ORZX+fuTcLwi51uPwUqcMYoHHMas2K+93Vmf28WT81ceKyfKkMzdTqIy/nvLh\nnFPGR/2wy3PNWRUxuaPOHf9adao25YB06h9/53ZcouOcrfyGEVNs8htGTLHJbxgxpeJ7/sF7MJ8z\nTqE9mjdLj4rWyPS87LSpSaj9baD6IfdWBEqHVVWWsK8HGs7IjL7v+cS7hfyVs593dFbdJrMbfeSG\n+4T8tR9c6+i0HiyvOdi5y2mTm3KMkBONrfL1PR5bQviaECmpHZ3c9SJMyH3p236vHIG2uRlrlp19\njZDTOff+p2bJgKbcGjm2lGerm1QxRKwyB/sKAzmHVMbiMOFRygyfVSjMuToZ9dndGrrXHKrb2xuo\nwKqEZ354siMXg638hhFTbPIbRkyxyW8YMaXie/7Be3bf/r5Qsg+/TUDueVK+AENdbZbUc30tA3Bq\nyWbU3rW329VQgSUth8sqP391nkyoAQDL7/yjkHfvkM+3rzhvgaMzrV36Blz/xH84bWhgg5DD7GQh\nBw2HOzrITREi98hKxJzb5p5HbVTDGtkHWlydNzz+70Je+907nDa7f/yEPLe6t7599YC25bD2J/Bk\n73WOSEKfnUnv8ZWc8SyruaQ8uMqTWWS68r049q6fywa+pDPeCseFsZXfMGKKTX7DiCk2+Q0jptjk\nN4yYMqZOPsW8rg2AXscgfaCImlJOP17jo8oem5VZbdDvZvLhPuk4Q81ThXzWp9/nDqZBZgHmn94v\n5OxWdV4A1L1TyLu2u+W6aqfKbEU1GekkEyYOcHR02W6ul214j+tQQoEcX88u6XDUWCdLWwFukM60\nS+c7bYJ3nSrkF//uy0LOJD0f32LqiSmc0t86k5In6MspS64Nfp6Pea9ykHrFY2psVB/LuoMOcjty\nGKVMPobbJSXWAAAOvklEQVRh7J/Y5DeMmGKT3zBiStUn83C34p7NlA7EYPeyEtoRQnUceirRpALp\ncBFm5R7fZ76gGrlnDnNbhdwySWUNBnDOJ+V+95z3v03ILz4qE4IAwPIXpAPPg/fucNoce47cC86Z\nIxNQvPz4bY7OnKPfKWRKyIQgiaQny3FOnqehXuqQ5/1IqopDWU+bcPYsIR/x888I+akLv+noJJwS\n3Cq5h6MBBPqoEkN4AmdIO/lIpT6PbWqbWmoTuQGnzXuWvqDOM3rrs638hhFTbPIbRkyxyW8YMWVM\nA3uKodBzfwAg9ZwzCN3EmqwTJ6hHo0lPkEWYk/vqQO0nw1r3+TWn5TP7gRppN6gN3WeyLY2yqg+m\ndQjxxDfIfTgAvLVfJvAM2JNYRFXOQVYm8Jx75BGOTrBnpZDDWlmCMUuygjAABKraUegkxPQE05BM\njBLA9WUA5Lkyc+cKebdnz1xLOoCLhpUB9zMVqAAi9tl21F58ICftAj2Bu64uVbaDUy75qNMmVMk7\nRnN1tpXfMGKKTX7DiCk2+Q0jptjkN4yYUnWBPTorj7bvhewaedbwCiHP7PVkm0lKw1sQygo+Ossr\nAAQ5mbmHVZaYoGGSo5NQBr4gIw1b1C2dfgAAW2QwUFijMubWqVLbABI1suJQLukJPtGZiHLS+SYI\nXeNpqMppJ7ZLAyAmHeXo7FkrA4auv/CrQj7weGmoA4B/vOlTciyeCje5UI43WSOzF63zpO9tVcEz\nSfV5C3z+OvqAui/scQ3SWXm6k7KNW1QdWF8vDZgnXn6ZOxZ1Km2MLKYCUbHYym8YMcUmv2HEFJv8\nhhFTKh/YM2jP5XX3UVuabVgv5ItWyiouAEAqKOfegevdfuuapRyo4BNP9t5QVWJ1YkZSrpNPoPrp\nzcr9errB1cmw3PAmVYWYPST3ugBQn5KOTD7HJlI2C2RkYJKv+o6zpVQBN7zhCWg2rpA2lssuPEvI\njy1+xtF57Kofy361QxKArldlsFLXWmkvCZKuLaRfBXmRsnvUeRJzOJesKhAlPJk5dqlPbxfJ82xK\nSpsMAPz7Ypml2ZcV2NnTl3GPr7GV3zBiik1+w4gpRU9+IkoQ0TNEdE8kTyaiB4jo5ej/5kJ9GIZR\nPYxkz38ZgOUA9m5AFwB4kJmvJ6IFkXxloU4Gx3iQZ9e/i+S+7owHZ6oWro7KN4Hf5/7otHnnAdPl\nOFLymauuOgMApIN91DNi8lRK4UD2W9sgE2AOkKoWDCDFcm+eISnX59zKQMiq/bwnyEVXGGK159dV\njACPHUAlxKQB94F87/0yAUW7Sjo590CZlAMAenbJe1cfpJ02QVIGST22VlY4/t5Frp8FVGKRI7fI\n81y40k1GklKBR5SV97LHkx8zoywFNG+2kM/6wIWOzrOPPyLk5rY2p01zi6yknG6U15hKeSr2lEhR\nKz8RzQBwFoD/GnT4XQBuif6+BcB5ZRuVYRijTrE/+28E8BnIta+dmffGvG4E0O5oASCiS4iok4g6\nN2/eXPpIDcMoKwUnPxGdDaCLmZcM1YbzPojeJ3fMvJCZO5i5o83zM8cwjLGhmD3/WwGcS0RnAkgD\nmEhEPwGwiYimMvMGIpoKoGvYXgzDqCoKTn5mvgrAVQBARCcB+DQzf5CI/j+A+QCuj/6/q5gTDvZZ\n6Avd7DNv/8U0Ie/SjhD9nqwwqsnXG12D3zu63i510tKQEgS+6i/SwqcdMHIe4x0CabDJkjRkpdgT\nwULSmSiZk/eFs7ICDgAkstLKGYYeg19WZ/KRbTyxTIDKNET90mh4/2mfdVQOPe10Ife9Lrd3Bzep\nkt0AulNyLNkm91fh7568U8iLLpXv2YENytILYPt2Of6lKfm+LjzBDbk542bZbzIpjbZ9Sfc9m/e2\n44Q8eaY0KA/0KYMsgGyfdMTK9GecNhn1ntV4skqXi315zn89gFOJ6GUA74xkwzDGCSNy72XmhwA8\nFP29FcAp5R+SYRiVwDz8DCOmVDSwZ93Wdbjq5qv/LN++7SdOmwk10qnnkAPkfrE3sd3RaWyS+6SJ\nboJZ/Pi1Xwh5fpPMnBo2u/tSVpkfwpzcvycT7omyKnAkCbn3C9gTgJNVTjw5mck2we7e0EnykHPb\nhC1vlAfWLZb9Zt0qwxiQ/f62Y4GQm8l1Mul59k9CTh40W8ipqW4wU+Mk6RB6zx8ectr8dpqsPFx/\nmDz3hKzrfTNlonzP1vVLp7HJgRsk9fGFPxByol4G5dSn3SCd9AQVsFUn29TUujoJ5aDjLcbjCTAb\nLWzlN4yYYpPfMGKKTX7DiCkV3fNPb5mO6//+uj/L19FXnTYXfedSId/x6ANCntzsfl+1tMh9dEuT\n+2z01dQaIdc9LJ8hv/cENzQhMUn6HFCtqgbsqd4aZKVNIlSBMgHcZ/asElVC2Q3Yk0yCVdIKXzJO\nrJOJN6hfPlvvXefu+V+4+m4hJ3Jyn9rvcW1I90l7Q39SViJun6dsDwD+8MjDQr5pwyNOm+YbJgt5\nSr/8uP5uu+tX1tQon8k3TpE6i05b7eika+R4i6kpVVqKDf15Gdu111Z+w4gpNvkNI6bY5DeMmGKT\n3zBiSuWz9waD/3RNK7f/y01CXghpwGm97FhHJ9MvnW26e1yHlwk18lKvzC4T8jfOW+ToPPG9zwg5\nOVUaoLjJzSSzfY/MPjO5RWbyYZ1RN39QiGFGGgAToccZRzv19LjOQ4u++nMhb7ztcdkv3Pt0/o9v\nFfL9V3xSyJlud/yZnHwfuzfICkSrH3d1btj4kJAb3u86Dz39JxkglJYxU5g2xTW7TWiV/bTUyfuf\nVMY9wDXwjVa+XFZr7ejl5S0OW/kNI6bY5DeMmGKT3zBiSsX3/DIgxZOYQ2WYmMjSq2TgxqWOzgub\nXxXyhTd9zGkzb44MGLr/SelUcuY1bsXUp7uPEfINp7xPyH8/XyZ0AIC/nX+yPLBFBpJQv+sYtGWN\nTDDx8H9L+8OK36lKuQC4W9oF6kL3XqaVLWHmUYcLueuF5Y7OT+dfLOSEti2k3cAYVkkp+nZKR6av\nvVVm3QWA3FukjaKpwV2HmtrkNbU0SuenWk+y+FSj1PnlIauFnIAn6QnkZ2zUKuPqxDRF9GtVeg3D\nKDs2+Q0jptjkN4yYYpPfMGIKaYPCaNLR0cFPPfXUsG1IGa5CVbrZUyHLSYmi+wCAUCmGKpNtX6/r\nJLN7t8yoQ8qQ9eE3HOnoNKr7GaiSWLWeSMCUMnzqNm4hK9dWlGbXdlujnHj0XfHljEmoo1OOPEzI\nr760ytHZ1C6zIF39u18LOdfuOvB8YtF7hdzXuM1pk6uTTj6JZunwNaHeDTH82YGyrHettmmzx2Cm\naq+XMidKMcwV02akYznuuOPQ2dlZlFXQVn7DiCk2+Q0jptjkN4yYUnV7/pJQWWz27HZLWvfslBl2\ntm/dIuQdm9wiols3yuyxm7vWydfXbXJ0ulZIx5lV98vqQYHndifVDi2l3pO05zs6qcJRtAwAgTaQ\nqP2urxZMTu1D19dJG8CxF5zj6ExslxmPJqmMy1PaZTUbAGhVJdMbproBN5NURuWJqqpPba0MogI8\nfjM6Ra7n86733qXMiVL68O3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"text/plain": [
"<matplotlib.figure.Figure at 0x176a8337ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"print(\"Length of X_train: \", len(XTrain))\n",
"plt.imshow(XTrain[34])\n",
"plt.title(\"Checking X_train\"+str(yTrain[34]))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Length of X_test: 60\n"
]
},
{
"data": {
"image/png": 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+jtxO+kU9AYrfKCczzTtDJv0M/kivIts1/BMh9+VlQZCWD96udIbXOIlNfetV\nn2Bl+IqxbfiZkDNel9JJQMYkBobeKuQ26IlVHmRSGHdJf50Tb1M6ybXymOlYuZJO2ysy8QkA8q/K\nWEKqsVX1KRdkFWMvvUSOJapoixXzMAxjIpjxG0ZMMeM3jJhSY59/eqDWHtWWSDqTf0iuwuKlI1aJ\nLTvvzovO6rMRl85EwlntV03E0KsBu0U3iiU5lrRT4BMA/IQ8noQOWYAh+5SciUjk64ITybUXyj5L\n/p+QG9v0eUocLOMALSOyGAbfoVcGanDyEqIW6c22SZ+45GzXS+lYiJeQ52rO9geFnN+l40F0wFLZ\nsO5hIZbTzpLOALLzZO5C8Un5nt8f3KB0Mg3ymGmOdtb91lOEzKWICUJThN35DSOmmPEbRkwx4zeM\nmDKu8RNRlogeJaKniGgVEV0ets8honuJaE34f8QSEIZh1CvVBPzyAE5k5gEKsi4eIqK7AbwPwH3M\nfAURrQCwAsAl0zjWqsksWKLa/HSPkBMFZ/JG1GUwKQNK5GRTcFlPuOGCjFyVUjIAlRzsVzrUJFer\n8bY4iUINOrBF5AzYj5iZlJRfb0OTHD9lD9c6r8kAGR8gJzOVO/S5LT1zj+yTlEE1L6ODnLxbnqdC\ni176u69RVrrp3iUrKW1JOYE6AF3OrgYHHhNyrv0QpVPa+pyQU2l5brf26sDc/P3fLOShLbLKkNci\nq+4CQKkgE38SIxGrFKXkxCR/wFnivXFqJsMBVdz5OWA0PS4V/mMAZwEYXez8OgBnR6gbhlGnVOXz\nE5FHRE8C2ArgXmZ+BEAXM4/ePjcD0LmWge5FRLSSiFb29vZOyaANw9h7qjJ+Zi4z8xEAFgE4kogO\ndT5nABHPnQAzX8PMy5h5WWenXnDSMIzaMKEkH2beRUT3AzgFwBYi6mbmTUTUjeCpoD7QOTEgp8CH\nP+QUAGHtS7Hrqxaln1qmiOudczl1h+JHJONQXq7o6jU4HdIRPnO/TAwqR8zu4CEZK3AW7UV58FWl\nU87LnXsvfkrIqeN+qHToxyfKBl8e9e4+XVyldWmPbNiwW/XpPlR6kqUHbhXy3CG5AjIAcELGS5JF\nWcyjr1MX2WjcvFrI5UXLhLygVcey/bUyztHWLROSBnbIWAkApCDHVs6XVB8uOxO2GuR4/Yjf3GSj\nANVE+zuJqC38uwHAyQBeAHA7gOVht+UAbovegmEY9Ug1d/5uANcRkYfgYnEzM99BRL8BcDMRXQjg\nFQDnTuPTLDSNAAAOBklEQVQ4DcOYYsY1fmZ+GsCbI9q3A3jXdAzKMIzpxzL8DCOmvC5n9UUy71gh\nUv9TQubSa1rHqd5bKjlLXkfm1chgV6noLqOlq+wmZLwP7ASGUIx6kSKv215Kf5XsFB4q9zrLmLXp\n5KEUZOCqvM6ZCdj2RaXjf+BZIQ9dd7qQm9/6RqWTXyOrHKeadPBr6K4/FrJTFAl+Zn+lM+DMXGxq\nkwHM0ksPKJ3U4ZcKmTffIORCTt8j001OKDctA3PUpiO7QyVZQbr9pMtVH583C7m86Q4he0v0svCT\nxe78hhFTzPgNI6aY8RtGTImNz++/XVZX5TVXyQ6kl5FO+NJfT6Wc5Z+H9NLZXkH6eoUhZ/WdrPYF\ny06CkZeU1+RyQfvDnie/uuHNeonupLOdQp9MpMnNc5YTB8BDMgW73Cer3SZTcjUeAKA5jwi5afld\nQvbvOFrrsExc8gf1+Bvnz5NjG94lZWzROiPyOyl0yH03ZtYqncJaWaE4OSLHkpzvrOgDYNfgW4Tc\ntkmurJNs0zrlzm7ZkDxC9UkMylWI8vs/KWQdMZo8duc3jJhixm8YMcWM3zBiSmx8/kTKmRzTuJ8Q\nuc95Bw6Ancq7PCTlRDliMk3KmVjiFF/wS/qdfaLk9Mk6xTzcwh0Aymm5nWyr7lPY7WzHqUZMOmSB\nUllWNU6n5TH7m3WZXXr4Y7LhGOlDJ069Wul4N58vx9rhzmYChnbL89LsySq63na9YlJ/Vm6noXGj\nkMsRM6vyaVngI8GPyv2sekjptB/jrBCcl78v72lZFAUAmt99r5BL5adVH2+dnBCU0WGBKcPu/IYR\nU8z4DSOmmPEbRkwx4zeMmBKbgJ9b7dY/Q1aFwc0yaQMACDK5hmlYyImIikF+wQmquQk8UTpFOcHG\nWU0cyZQOLJKz6lS5rKN3QQmGiv04sa4tq3QlnzlLZfVY+E7F35KuKkQbnYNaKav/+Ef8hdLxzvh7\nuY27/171aW6QxaESPacJufzSnUonMyCTkgrPPyPkZEn/5LN9MsCXWCAnIvWt1ctt5za9LORSs5xk\nlDr2KKXDRfmlFXbp+jfJI2RST8TPZcqwO79hxBQzfsOIKWb8hhFTYuPzuyQaZaWLInWoPilf+vjs\nVO8o6/k2SDh9uOAk2kRMBqKc9M2TTh5NVHVWp84IPF9P+SjlpZNPJL/uxE5dMZdJllf3c/IcDGzT\niTUNGScxaJ2s1stwJlEBwLJPCDF17pW6z23LhVhYLX38fFavHuQNy6SeVFZO0kmn9Hmit35GyP5K\nmaSUbdNxjt1bZOXg1qNkVWPPj1jGIi99/NzzuoAMdzkmOXUL9Cjszm8YMcWM3zBiihm/YcSU2Pr8\n7nUvef4jqkfxe7LYRSolK20mBiMmuTjOeNmJAZCnr7cJZ+Fe9px360NR12jnpX1U/MH5eotF2SnB\n2v995UFZ7GLfUxYKuanjMKVT3C3zBYp5+a6dVkc4rvnvCNHviogLnH69EJMJWVw0XdKTdAbuvEDI\n3CnHn96l/exiYbuQd86X7+g7TrhR6bQ737PHMjaC0s+UzsgzPxJy5oSIwihuMGcasTu/YcQUM37D\niClm/IYRU8z4DSOmxDjg58D6VCQ+8oKQC1fJBJhkQid/wJdBwWTeCaoldSUfdifPwOlDOrBV2C3b\n0m6loqjtOsEkn/VYGtzkoaJMhkr4umJuypeJSyO+rIScTujAIq93AqFRyU8DH5bj3edk2aHrHKWT\nOVdWy4Enk7fYl8E9AEiUZLJTx0EHCLnsr1I6SSd5CyX5Wyk9812lk95Xts1kcC8Ku/MbRkwx4zeM\nmGLGbxgxxXz+MXB9stJFm+TnPzhU6Xh56ROXE7IyhxeRWMNuskrZmRzkRyQGOfJIn44LlIo0plyO\nuPYPj8jtPHGPPJ63nblA6RRKsthFY4szjmF9zL7jMyfWNak+hbUyiSq57udCzndIGQAa9mmU+25d\nJvdTfkXpsBP7KAw6sR1n4hIA5B93im4kZfJTIrNI6eDYZbqthtid3zBiihm/YcSUqo2fiDwieoKI\n7gjlOUR0LxGtCf9vn75hGoYx1UzE5/8kgOcBjHp0KwDcx8xXENGKUL5kisdXU1xfsFySPuiO9+tV\nWRpu+qCQ2wvOO+KiLobB7io+Sef9vF7AFmVnTtFwxHvyUkFup69P7meA9XvmdSkZxzjgS/8p5G3z\n9TW+5abj5Fh6ZUGN7NyItWVTsmgpqF91SaZlMVGvV54Iv1evrOy/LLdLLXK1HT99jB6L95QcWklO\nTEoMOkVNATDPl/txisOUzrxZ6STdXJLavuav7s5PRIsAnA7gexXNZwG4Lvz7OgBnT+3QDMOYTqp9\n7L8SwGcBVN5euph5NPy9GUBE3SKAiC4iopVEtLK3tzeqi2EYNWBc4yeiMwBsZebH9tSHg+djnSsa\nfHYNMy9j5mWdnZ1RXQzDqAHV+PzHAjiTiE4DkAXQQkQ3ANhCRN3MvImIugFsHXMrhmHUFeMaPzNf\nCuBSACCiEwB8hpk/RET/CGA5gCvC//XyI7McN8knkZAPSl7EEt0b3vFNId+3ZrWQD135z0rn4OIT\nQi44ZYGLef2ANuQE+PoG9cSeTf1yfL/KHiTk1vdcpHQOOnCpkJNpN1ing3eDH/ofIbfc+gEh+7se\nVjr5khx/LqJCbtLZVTnpJNuU9cNmOSOThbggl+xODOskn3K/DBz6vlyuPdXiZC0B4KwMfO5493VC\nboqYNFVv7M17/isAnExEawCcFMqGYcwSJpTey8wPAHgg/Hs7gHdN/ZAMw5gJLMPPMGKKTewJiSqs\n4Cb5JJPydGWzOsmkvU36ggcsOVDIW+Z+Vek8uXuzkPu3yESg/gFnSV4Axbz0kRsy+qucO0dWuz2k\nUxa2mNsuE1MAYM4c2dbUJH3oZDKigInD7066QcjbNq1Xfd78ywuFXNi6UfVJFmVF3OGyTL5p6tTj\n953JS4P5nUJuyGr/3XPOXXJIxhbWpY5XOsNHrxByN5ykJejfRr1hd37DiClm/IYRU8z4DSOmmM8/\nBm4cwPPki+con9/NBXD7dHTo1YD3K+wn5HJZF+ZwceMRUbhjSTlFPl0ZANLp9JiyG/cA9HhTzkq4\nqZyMPQDAbQf8o5DXrFuv+rxhrVzV5/TGdUIuDulYyNCQ8x05x7ijoGMLvywdKbdx5J8KeclSmfsA\nAPOdU+f+NtxzX4/U/wgNw5gWzPgNI6aY8RtGTDHjN4yYYgG/MRgv4BeVGDRekC0qUDdegM/3dZWe\nanDHMt5EJUAfYzXHXCrJiUgNDXIyTVtbm9I5YOkSIXfN09O9hw77tpBv3S0rIQ8N6uo/KWeylZeR\ncmODrhLc0SYTf1paxpYBoLlZVvdxA6PueatH7M5vGDHFjN8wYooZv2HEFPP594Ion9lNgnHlKJ9/\nvISdqfL5q2E8Hz9qrFHJQmNtEwByOTl5xp1QBOhYyFJHjoqVuONzxx+VpOSeJ7eP689Htbk6tV6B\ntxrszm8YMcWM3zBiihm/YcQUM37DiCkW8JsA1QRxZsNsrr0h6vjcIFs1CS+TCYS6gc+o72O8PlE6\n432v1Yy/mu+93oKAr+9fqmEYe8SM3zBiihm/YcQU8/mnmHrz62rBeBOiotqqqUxUjc8/3naq8fnd\nbUT58+N9z7Phd2B3fsOIKWb8hhFTzPgNI6aYz2/sNTPl30ZNynEZb2LPZHSq2cZs8PFd7M5vGDHF\njN8wYooZv2HEFDN+w4gpFvAzpp2ZDJhNZjuzMVg3Fdid3zBiihm/YcQUM37DiClUzYSKKdsZUS+A\nVwB0ANg2Yzvee2bTeGfTWIHZNd7ZMNb9mFkvfxTBjBr//+6UaCUzL5vxHU+S2TTe2TRWYHaNdzaN\ntRrssd8wYooZv2HElFoZ/zU12u9kmU3jnU1jBWbXeGfTWMelJj6/YRi1xx77DSOmmPEbRkyZceMn\nolOIaDURvUREK2Z6/2NBRD8goq1E9GxF2xwiupeI1oT/t9dyjKMQ0T5EdD8RPUdEq4jok2F7vY43\nS0SPEtFT4XgvD9vrcrwAQEQeET1BRHeEct2OdTLMqPETkQfg2wBOBXAwgPOI6OCZHMM4XAvgFKdt\nBYD7mHkpgPtCuR4oAfgbZj4YwFEA/iI8l/U63jyAE5n5cABHADiFiI5C/Y4XAD4J4PkKuZ7HOnGY\necb+ATgawD0V8qUALp3JMVQxxh4Az1bIqwF0h393A1hd6zHuYdy3ATh5NowXQA7A4wDeXq/jBbAI\ngYGfCOCO2fRbqPbfTD/2LwSwoULeGLbVM13MvCn8ezOArloOJgoi6gHwZgCPoI7HGz5GPwlgK4B7\nmbmex3slgM8CqFwsoF7HOiks4DcBOLjk19W7USJqAnALgE8xc1/lZ/U2XmYuM/MRCO6qRxLRoc7n\ndTFeIjoDwFZmfmxPfeplrHvDTBv/7wDsUyEvCtvqmS1E1A0A4f9bazye/4WIUggM/0fMfGvYXLfj\nHYWZdwG4H0F8pR7HeyyAM4loPYCbAJxIRDegPsc6aWba+H8LYCkR7U9EaQB/BOD2GR7DRLkdwPLw\n7+UIfOuaQ0H5me8DeJ6Zv1HxUb2Ot5OI2sK/GxDEJ15AHY6XmS9l5kXM3IPgN/oLZv4Q6nCse0UN\nAimnAXgRwFoAn6910MMZ240ANgEoIohHXAhgLoLAzxoAPwcwp9bjDMd6HILHzqcBPBn+O62Ox/sm\nAE+E430WwN+G7XU53opxn4DfB/zqeqwT/WfpvYYRUyzgZxgxxYzfMGKKGb9hxBQzfsOIKWb8hhFT\nzPgNI6aY8RtGTPn/jkOmCgrS/3QAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176a85572b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"print(\"Length of X_test: \", len(XTest))\n",
"plt.imshow(XTest[45])\n",
"plt.title(\"Checking X_test, Label: \" + str(yTest[45]))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"XTrain = XTrain.astype('float32')\n",
"XTest = XTest.astype('float32')\n",
"XTrain /= 255\n",
"XTest /= 255"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X_train shape: (240, 50, 50, 3)\n",
"X_test shape: (60, 50, 50, 3)\n",
"\n",
"y_train shape: (240, 4)\n",
"y_test shape: (60, 4)\n"
]
}
],
"source": [
"#checks the shape of the dataset\n",
"\n",
"print(\"X_train shape: \", XTrain.shape)\n",
"print(\"X_test shape: \", XTest.shape)\n",
"\n",
"print(\"\\ny_train shape: \", yTrain.shape)\n",
"print(\"y_test shape: \", yTest.shape)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"8/8 [==============================] - 9s 926ms/step - loss: 1.4396 - accuracy: 0.2829 - val_loss: 1.2947 - val_accuracy: 0.4167\n",
"Epoch 2/10\n",
"8/8 [==============================] - 3s 375ms/step - loss: 1.2796 - accuracy: 0.3942 - val_loss: 1.1239 - val_accuracy: 0.5167\n",
"Epoch 3/10\n",
"8/8 [==============================] - 3s 410ms/step - loss: 1.0893 - accuracy: 0.5509 - val_loss: 0.8252 - val_accuracy: 0.6667\n",
"Epoch 4/10\n",
"8/8 [==============================] - 3s 414ms/step - loss: 0.7361 - accuracy: 0.6881 - val_loss: 0.8391 - val_accuracy: 0.8167\n",
"Epoch 5/10\n",
"8/8 [==============================] - 3s 411ms/step - loss: 0.6519 - accuracy: 0.7672 - val_loss: 0.6778 - val_accuracy: 0.8833\n",
"Epoch 6/10\n",
"8/8 [==============================] - 4s 562ms/step - loss: 0.5661 - accuracy: 0.7896 - val_loss: 0.5603 - val_accuracy: 0.8833\n",
"Epoch 7/10\n",
"8/8 [==============================] - 4s 531ms/step - loss: 0.4893 - accuracy: 0.8701 - val_loss: 0.5407 - val_accuracy: 0.9000\n",
"Epoch 8/10\n",
"8/8 [==============================] - 3s 431ms/step - loss: 0.3739 - accuracy: 0.8887 - val_loss: 0.5710 - val_accuracy: 0.8000\n",
"Epoch 9/10\n",
"8/8 [==============================] - 4s 469ms/step - loss: 0.3315 - accuracy: 0.8826 - val_loss: 0.3921 - val_accuracy: 0.9167\n",
"Epoch 10/10\n",
"8/8 [==============================] - 5s 593ms/step - loss: 0.2396 - accuracy: 0.9373 - val_loss: 0.4474 - val_accuracy: 0.9167\n",
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"conv2d (Conv2D) (None, 50, 50, 32) 896 \n",
"_________________________________________________________________\n",
"conv2d_1 (Conv2D) (None, 48, 48, 32) 9248 \n",
"_________________________________________________________________\n",
"max_pooling2d (MaxPooling2D) (None, 24, 24, 32) 0 \n",
"_________________________________________________________________\n",
"dropout (Dropout) (None, 24, 24, 32) 0 \n",
"_________________________________________________________________\n",
"conv2d_2 (Conv2D) (None, 24, 24, 64) 18496 \n",
"_________________________________________________________________\n",
"conv2d_3 (Conv2D) (None, 22, 22, 64) 36928 \n",
"_________________________________________________________________\n",
"max_pooling2d_1 (MaxPooling2 (None, 11, 11, 64) 0 \n",
"_________________________________________________________________\n",
"dropout_1 (Dropout) (None, 11, 11, 64) 0 \n",
"_________________________________________________________________\n",
"flatten (Flatten) (None, 7744) 0 \n",
"_________________________________________________________________\n",
"dense (Dense) (None, 256) 1982720 \n",
"_________________________________________________________________\n",
"dropout_2 (Dropout) (None, 256) 0 \n",
"_________________________________________________________________\n",
"dense_1 (Dense) (None, 4) 1028 \n",
"=================================================================\n",
"Total params: 2,049,316\n",
"Trainable params: 2,049,316\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"\n",
"model = Sequential()\n",
"\n",
"model.add(Conv2D(32, (3, 3), padding='same', input_shape=(50, 50, 3), activation=\"relu\"))\n",
"model.add(Conv2D(32, (3, 3), activation=\"relu\"))\n",
"model.add(MaxPooling2D(pool_size=(2, 2)))\n",
"model.add(Dropout(0.25))\n",
"\n",
"model.add(Conv2D(64, (3, 3), padding='same', activation=\"relu\"))\n",
"model.add(Conv2D(64, (3, 3), activation=\"relu\"))\n",
"model.add(MaxPooling2D(pool_size=(2, 2)))\n",
"model.add(Dropout(0.3))\n",
"\n",
"model.add(Flatten())\n",
"model.add(Dense(256, activation=\"relu\"))\n",
"model.add(Dropout(0.5))\n",
"model.add(Dense(4, activation=\"softmax\"))\n",
"\n",
"# Compile the model\n",
"model.compile(\n",
" loss='categorical_crossentropy',\n",
" optimizer=\"adam\",\n",
" metrics=['accuracy']\n",
")\n",
"history= model.fit(XTrain, yTrain, batch_size=32, epochs=10, validation_data=(XTest, yTest) )\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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IxhSR3SmYkNx1Fyxb5q6zUdUKs2cPvPgiPPkkZGTAww/D/fe7SWfGmCKzpGAK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\nScEYY0y2/wf+RLZGsJA1iwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176a85dd208>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# displaying the model accuracy\n",
"plt.plot(history.history['accuracy'], label='train', color=\"red\")\n",
"plt.plot(history.history['val_accuracy'], label='validation', color=\"blue\")\n",
"plt.title('Model accuracy')\n",
"plt.legend(loc='upper left')\n",
"plt.ylabel('accuracy')\n",
"plt.xlabel('epoch')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"8/8 [==============================] - 1s 127ms/step - loss: 0.1712 - accuracy: 0.9542\n"
]
}
],
"source": [
"accuracy = model.evaluate(XTrain, yTrain)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test loss: 0.44743674993515015\n",
"Test accuracy: 0.9166666865348816\n"
]
}
],
"source": [
"#test the model\n",
"\n",
"test_eval = model.evaluate(XTest, yTest, verbose=0)\n",
"print('Test loss:', test_eval[0])\n",
"print('Test accuracy:', test_eval[1])"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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fwCzNw/U+r81H9wJtVPVqVb0Kaxq6L5fP/AbUTve8Vui19K4BPgzFvDSUFBrl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\nOedcmv8Pebaik/nSbwUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x176aac377b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# displaying the model loss\n",
"plt.plot(history.history['loss'], label='train', color=\"red\")\n",
"plt.plot(history.history['val_loss'], label='validation', color=\"blue\")\n",
"plt.title('Model loss')\n",
"plt.legend(loc='upper left')\n",
"plt.xlabel('epoch')\n",
"plt.ylabel('loss')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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bb75ZYDzcgOu5cuDAAZogdXZ2vv7661u3bi06IkbA9Vzp7+8vlUpCCN/3Dxw4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\nqBTDMOr1+moKyoSUVQ62uW3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ddzZv3lx0IGsA27ZPnDiRSVaZub5jx47BwcGsclvfPP30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\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from keras.applications.vgg16 import VGG16\n",
"from keras.utils import plot_model\n",
"model = VGG16()\n",
"plot_model(model)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"train_datagen = ImageDataGenerator(\n",
" rescale=1./255,# The image augmentaion function in Keras\n",
" shear_range=0.2,\n",
" zoom_range=0.2, # Zoom in on image by 20%\n",
" horizontal_flip=True)\n",
"\n",
"test_datagen = ImageDataGenerator(rescale=1./255) "
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 0 images belonging to 0 classes.\n"
]
}
],
"source": [
"train_generator = train_datagen.flow_from_directory(\n",
" train_path,\n",
" target_size=(50, 50),\n",
" batch_size=32,\n",
" class_mode='categorical')\n"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 0 images belonging to 0 classes.\n"
]
}
],
"source": [
"test_generator = test_datagen.flow_from_directory(\n",
" test_path,\n",
" target_size=(50, 50),\n",
" batch_size=32,\n",
" class_mode='categorical')"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from tensorflow.keras.applications.inception_v3 import InceptionV3\n",
"backend.clear_session()\n",
"conv_based = InceptionV3(weights = 'imagenet', include_top = False)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"InceptionV3_model = conv_based.output \n",
"pool = GlobalAveragePooling2D()(InceptionV3_model )\n",
"dense_1 = layers.Dense(512, activation = 'relu')(pool)\n",
"output = layers.Dense(4,activation = 'softmax')(dense_1)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"import tensorflow as tf\n",
"vgg_model = tf.keras.applications.vgg16.VGG16()\n",
"print(type(vgg_model))\n",
"vgg_model.summary()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"mInceptionV3 = models.Model(inputs=conv_based.input, outputs=output)\n",
"mInceptionV3.compile(loss='categorical_crossentropy',\n",
" optimizer=optimizers.SGD(lr=1e-4, momentum=0.9),\n",
" metrics=['accuracy'])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[name: \"/device:CPU:0\"\n",
"device_type: \"CPU\"\n",
"memory_limit: 268435456\n",
"locality {\n",
"}\n",
"incarnation: 6425448118712103756\n",
"]\n"
]
}
],
"source": [
"from tensorflow.python.client import device_lib\n",
"print(device_lib.list_local_devices())\n"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"from keras import models\n",
"base_model = VGG16(weights='imagenet')\n",
"model_VGG16 = models.Model(inputs=base_model.input, outputs=base_model.get_layer('flatten').output)\n",
"model.compile(\n",
" loss='categorical_crossentropy',\n",
" optimizer=\"adam\",\n",
" metrics=['accuracy']\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/15\n"
]
},
{
"ename": "ValueError",
"evalue": "in user code:\n\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:805 train_function *\n return step_function(self, iterator)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:795 step_function **\n outputs = model.distribute_strategy.run(run_step, args=(data,))\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:1259 run\n return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:2730 call_for_each_replica\n return self._call_for_each_replica(fn, args, kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:3417 _call_for_each_replica\n return fn(*args, **kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:788 run_step **\n outputs = model.train_step(data)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:754 train_step\n y_pred = self(x, training=True)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\base_layer.py:998 __call__\n input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\input_spec.py:274 assert_input_compatibility\n ', found shape=' + display_shape(x.shape))\n\n ValueError: Input 0 is incompatible with layer vgg16: expected shape=(None, 224, 224, 3), found shape=(None, 50, 50, 3)\n",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-30-d4ea7ff60b98>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 14\u001b[0m )\n\u001b[0;32m 15\u001b[0m \"\"\"\n\u001b[1;32m---> 16\u001b[1;33m \u001b[0mhistory\u001b[0m\u001b[1;33m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mXTrain\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0myTrain\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m64\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mepochs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m15\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalidation_data\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mXTest\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0myTest\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 17\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[0;32m 1098\u001b[0m _r=1):\n\u001b[0;32m 1099\u001b[0m \u001b[0mcallbacks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mon_train_batch_begin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstep\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1100\u001b[1;33m \u001b[0mtmp_logs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtrain_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1101\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mdata_handler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshould_sync\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1102\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masync_wait\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 826\u001b[0m \u001b[0mtracing_count\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexperimental_get_tracing_count\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 827\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mtrace\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTrace\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_name\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mtm\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 828\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 829\u001b[0m \u001b[0mcompiler\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"xla\"\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_experimental_compile\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;34m\"nonXla\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 830\u001b[0m \u001b[0mnew_tracing_count\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexperimental_get_tracing_count\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36m_call\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 869\u001b[0m \u001b[1;31m# This is the first call of __call__, so we have to initialize.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 870\u001b[0m \u001b[0minitializers\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 871\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initialize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0madd_initializers_to\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0minitializers\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 872\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 873\u001b[0m \u001b[1;31m# At this point we know that the initialization is complete (or less\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36m_initialize\u001b[1;34m(self, args, kwds, add_initializers_to)\u001b[0m\n\u001b[0;32m 724\u001b[0m self._concrete_stateful_fn = (\n\u001b[0;32m 725\u001b[0m self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access\n\u001b[1;32m--> 726\u001b[1;33m *args, **kwds))\n\u001b[0m\u001b[0;32m 727\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 728\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minvalid_creator_scope\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0munused_args\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0munused_kwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\function.py\u001b[0m in \u001b[0;36m_get_concrete_function_internal_garbage_collected\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 2967\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2968\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2969\u001b[1;33m \u001b[0mgraph_function\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_define_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2970\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2971\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\function.py\u001b[0m in \u001b[0;36m_maybe_define_function\u001b[1;34m(self, args, kwargs)\u001b[0m\n\u001b[0;32m 3359\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3360\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_function_cache\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmissed\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcall_context_key\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3361\u001b[1;33m \u001b[0mgraph_function\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_create_graph_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3362\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_function_cache\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprimary\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mcache_key\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3363\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\function.py\u001b[0m in \u001b[0;36m_create_graph_function\u001b[1;34m(self, args, kwargs, override_flat_arg_shapes)\u001b[0m\n\u001b[0;32m 3204\u001b[0m \u001b[0marg_names\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0marg_names\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3205\u001b[0m \u001b[0moverride_flat_arg_shapes\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0moverride_flat_arg_shapes\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3206\u001b[1;33m capture_by_value=self._capture_by_value),\n\u001b[0m\u001b[0;32m 3207\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_function_attributes\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3208\u001b[0m \u001b[0mfunction_spec\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunction_spec\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\framework\\func_graph.py\u001b[0m in \u001b[0;36mfunc_graph_from_py_func\u001b[1;34m(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)\u001b[0m\n\u001b[0;32m 988\u001b[0m \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moriginal_func\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtf_decorator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munwrap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpython_func\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 989\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 990\u001b[1;33m \u001b[0mfunc_outputs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpython_func\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mfunc_args\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mfunc_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 991\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 992\u001b[0m \u001b[1;31m# invariant: `func_outputs` contains only Tensors, CompositeTensors,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36mwrapped_fn\u001b[1;34m(*args, **kwds)\u001b[0m\n\u001b[0;32m 632\u001b[0m \u001b[0mxla_context\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mExit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 633\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 634\u001b[1;33m \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mweak_wrapped_fn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__wrapped__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 635\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 636\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\framework\\func_graph.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 975\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# pylint:disable=broad-except\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 976\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"ag_error_metadata\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 977\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mag_error_metadata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_exception\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 978\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 979\u001b[0m \u001b[1;32mraise\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: in user code:\n\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:805 train_function *\n return step_function(self, iterator)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:795 step_function **\n outputs = model.distribute_strategy.run(run_step, args=(data,))\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:1259 run\n return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:2730 call_for_each_replica\n return self._call_for_each_replica(fn, args, kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\distribute\\distribute_lib.py:3417 _call_for_each_replica\n return fn(*args, **kwargs)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:788 run_step **\n outputs = model.train_step(data)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\training.py:754 train_step\n y_pred = self(x, training=True)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\base_layer.py:998 __call__\n input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)\n C:\\Users\\LeonFremz\\AppData\\Roaming\\Python\\Python36\\site-packages\\tensorflow\\python\\keras\\engine\\input_spec.py:274 assert_input_compatibility\n ', found shape=' + display_shape(x.shape))\n\n ValueError: Input 0 is incompatible with layer vgg16: expected shape=(None, 224, 224, 3), found shape=(None, 50, 50, 3)\n"
]
}
],
"source": [
"import tensorflow as tf\n",
"with tf.device(\"/device:GPU:0\"):\n",
" \n",
" history= model.fit(XTrain, yTrain, batch_size=64, epochs=15, validation_data=(XTest, yTest) )\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"history_dict = history.history\n",
"loss_values = history_dict['loss']\n",
"valLoss = history_dict['val_loss']\n",
"accuracyValues = history_dict['accuracy']\n",
"valAccuracy = history_dict['val_accuracy']\n",
"epochs = range(1, len(history_dict['accuracy']) + 1)\n",
"#model.compile(optimizers, loss)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"k=list(history.history.keys())# access to dictionary keys\n",
"a=list(history.history.values())# access to dictionary keys\n",
"accuracy = a[3]\n",
"val_accuracy = a[1]\n",
"loss = a[2]\n",
"val_loss= a[0]\n",
"epochs = range(len(accuracy))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print('Test loss:', test_eval[0])\n",
"print('Test accuracy:', test_eval[1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# Plot the training/validation loss\n",
"plt.plot(epochs, loss_values, 'bo', label = 'Training loss')\n",
"plt.plot(epochs, valLoss,'b', label = 'Validation loss')\n",
"plt.title('Validation loss on Training')\n",
"plt.xlabel('Epochs')\n",
"plt.ylabel('Loss')\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.show()\n",
"\n",
"plt.rcParams.update({\"figure.figsize\" : (12, 8),\n",
" \"axes.facecolor\" : \"grey\",\n",
" \"axes.edgecolor\": \"grey\"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot the training/validation accuracy\n",
"import matplotlib.pyplot as plt\n",
"\n",
"plt.plot(epochs, accuracyValues, 'bo', label = 'Train accuracy')\n",
"plt.plot(epochs, valAccuracy, 'b', label = 'Validation accuracy')\n",
"plt.title('Validation accuracy on Training')\n",
"plt.xlabel('Epochs')\n",
"plt.ylabel('Accuracy')\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.show()\n",
"plt.rcParams.update({\"figure.figsize\" : (12, 8),\n",
" \"axes.facecolor\" : \"grey\",\n",
" \"axes.edgecolor\": \"grey\"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"test_loss, test_acc = mInceptionV3.evaluate(test_generator)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
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"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
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"nbformat": 4,
"nbformat_minor": 2
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