Naive_Solution.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#Input Handling and Data Preprocessing"
      ],
      "metadata": {
        "id": "xqyLNKCzLXG7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Importing the libraries"
      ],
      "metadata": {
        "id": "gk6N0j1miwEh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "QcLGNBOIi1CN"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Importing the dataset\n"
      ],
      "metadata": {
        "id": "UJyPeVg9ifuO"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "6uwoWS2VhqHC"
      },
      "outputs": [],
      "source": [
        "csv_path = 'isolated.csv'\n",
        "# Ensure the file is uploaded in the folders section"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Reading the CSV files via calling the function"
      ],
      "metadata": {
        "id": "V6_dq2JxjUCo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def read_csv(csv_path):\n",
        "  np_path_XYs = np.genfromtxt(csv_path, delimiter=',')\n",
        "  path_XYs = []\n",
        "  for i in np.unique(np_path_XYs[:, 0]):\n",
        "    npXYs = np_path_XYs[np_path_XYs[:, 0] == i] [:, 1:]\n",
        "    XYs = []\n",
        "    for j in np.unique(npXYs[:, 0]):\n",
        "      XY = npXYs[npXYs[:, 0] == j][:, 1:]\n",
        "      XYs.append(XY)\n",
        "    path_XYs.append(XYs)\n",
        "  return path_XYs\n",
        "\n",
        "shapes = read_csv(csv_path)\n",
        "print(shapes)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aLCoYvSUjX5h",
        "outputId": "bae04ef7-a76f-4c89-99d5-cbe0dc8c70c7"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[array([[109.14299774, 125.58000183],\n",
            "       [110.15747833, 125.49578094],\n",
            "       [111.17194366, 125.40398407],\n",
            "       [112.18638611, 125.30522156],\n",
            "       [113.20079041, 125.20011139],\n",
            "       [114.21517181, 125.08926392],\n",
            "       [115.22950745, 124.97328949],\n",
            "       [116.2437973 , 124.85279083],\n",
            "       [117.25804138, 124.72838593],\n",
            "       [118.27222443, 124.60068512],\n",
            "       [119.28635406, 124.47029877],\n",
            "       [120.30041504, 124.33782959],\n",
            "       [121.31440735, 124.2039032 ],\n",
            "       [122.32831573, 124.06912231],\n",
            "       [123.34214783, 123.93410492],\n",
            "       [124.355896  , 123.79945374],\n",
            "       [125.36954498, 123.66577911],\n",
            "       [126.38310242, 123.53369141],\n",
            "       [127.39655304, 123.40380859],\n",
            "       [128.40989685, 123.27674103],\n",
            "       [129.42312622, 123.15309143],\n",
            "       [130.43623352, 123.03347778],\n",
            "       [131.44923401, 122.91851044],\n",
            "       [132.46208191, 122.80879974],\n",
            "       [133.47480774, 122.70494843],\n",
            "       [134.48739624, 122.60758209],\n",
            "       [135.49983215, 122.51730347],\n",
            "       [136.51213074, 122.43471527],\n",
            "       [137.52426147, 122.36045074],\n",
            "       [138.53623962, 122.29509735],\n",
            "       [139.54803467, 122.2392807 ],\n",
            "       [140.55967712, 122.19360352],\n",
            "       [141.57113647, 122.15868378],\n",
            "       [142.58241272, 122.13512421],\n",
            "       [143.5934906 , 122.12354279],\n",
            "       [144.60440063, 122.12454987],\n",
            "       [145.61509705, 122.13874817],\n",
            "       [146.62559509, 122.16675568],\n",
            "       [147.63587952, 122.20919037],\n",
            "       [148.64595032, 122.26664734],\n",
            "       [149.6558075 , 122.33974457],\n",
            "       [150.66543579, 122.42910004],\n",
            "       [151.67483521, 122.53530884],\n",
            "       [152.68400574, 122.65899658],\n",
            "       [153.70085144, 122.80228424],\n",
            "       [154.71440125, 122.96405792],\n",
            "       [155.72444153, 123.14414215],\n",
            "       [156.73077393, 123.3423233 ],\n",
            "       [157.73316956, 123.5584259 ],\n",
            "       [158.73139954, 123.79224396],\n",
            "       [159.72528076, 124.04360199],\n",
            "       [160.71458435, 124.31228638],\n",
            "       [161.69911194, 124.59812164],\n",
            "       [162.67861938, 124.90090179],\n",
            "       [163.65290833, 125.22045135],\n",
            "       [164.62176514, 125.5565567 ],\n",
            "       [165.58499146, 125.90904236],\n",
            "       [166.54234314, 126.27770996],\n",
            "       [167.49362183, 126.66236115],\n",
            "       [168.43862915, 127.06280518],\n",
            "       [169.37712097, 127.47885895],\n",
            "       [170.30889893, 127.9103241 ],\n",
            "       [171.23374939, 128.35699463],\n",
            "       [172.15145874, 128.81871033],\n",
            "       [173.06181335, 129.29524231],\n",
            "       [173.96459961, 129.78642273],\n",
            "       [174.85958862, 130.29203796],\n",
            "       [175.74659729, 130.81192017],\n",
            "       [176.62538147, 131.34585571],\n",
            "       [177.4957428 , 131.8936615 ],\n",
            "       [178.35746765, 132.45513916],\n",
            "       [179.21032715, 133.03012085],\n",
            "       [180.05412292, 133.61837769],\n",
            "       [180.88864136, 134.21972656],\n",
            "       [181.71366882, 134.83398438],\n",
            "       [182.5289917 , 135.46096802],\n",
            "       [183.3343811 , 136.10046387],\n",
            "       [184.12962341, 136.75228882],\n",
            "       [184.91453552, 137.41624451],\n",
            "       [185.68887329, 138.09214783],\n",
            "       [186.45243835, 138.77980042],\n",
            "       [187.20500183, 139.47900391],\n",
            "       [187.94650269, 140.18939209],\n",
            "       [188.67697144, 140.91056824],\n",
            "       [189.39637756, 141.6423645 ],\n",
            "       [190.10472107, 142.384552  ],\n",
            "       [190.80195618, 143.13694763],\n",
            "       [191.48805237, 143.89935303],\n",
            "       [192.16297913, 144.67155457],\n",
            "       [192.82673645, 145.45336914],\n",
            "       [193.47926331, 146.24459839],\n",
            "       [194.12054443, 147.04502869],\n",
            "       [194.75056458, 147.85447693],\n",
            "       [195.36929321, 148.67272949],\n",
            "       [195.97668457, 149.49960327],\n",
            "       [196.57273865, 150.3348999 ],\n",
            "       [197.15740967, 151.17840576],\n",
            "       [197.73066711, 152.02992249],\n",
            "       [198.29249573, 152.88926697],\n",
            "       [198.84286499, 153.75624084],\n",
            "       [199.38174438, 154.63063049],\n",
            "       [199.90911865, 155.51223755],\n",
            "       [200.42494202, 156.40087891],\n",
            "       [200.92921448, 157.29634094],\n",
            "       [201.421875  , 158.19842529],\n",
            "       [201.90292358, 159.10694885],\n",
            "       [202.37231445, 160.021698  ],\n",
            "       [202.83003235, 160.94247437],\n",
            "       [203.27604675, 161.86909485],\n",
            "       [203.71032715, 162.80134583],\n",
            "       [204.13285828, 163.73902893],\n",
            "       [204.54359436, 164.6819458 ],\n",
            "       [204.94252014, 165.62989807],\n",
            "       [205.3296051 , 166.58270264],\n",
            "       [205.70483398, 167.54014587],\n",
            "       [206.06816101, 168.50202942],\n",
            "       [206.41957092, 169.46815491],\n",
            "       [206.7590332 , 170.43832397],\n",
            "       [207.08651733, 171.41233826],\n",
            "       [207.4019928 , 172.38999939],\n",
            "       [207.71740723, 173.41233826],\n",
            "       [208.01927185, 174.44024658],\n",
            "       [208.30667114, 175.4733429 ],\n",
            "       [208.57861328, 176.51119995],\n",
            "       [208.83418274, 177.55345154],\n",
            "       [209.07241821, 178.59970093],\n",
            "       [209.29237366, 179.64955139],\n",
            "       [209.49308777, 180.70262146],\n",
            "       [209.6736145 , 181.75849915],\n",
            "       [209.83302307, 182.81680298],\n",
            "       [209.97033691, 183.87715149],\n",
            "       [210.08462524, 184.93913269],\n",
            "       [210.17492676, 186.00236511],\n",
            "       [210.24029541, 187.06645203],\n",
            "       [210.27978516, 188.1309967 ],\n",
            "       [210.29243469, 189.19560242],\n",
            "       [210.27731323, 190.25990295],\n",
            "       [210.23345947, 191.32348633],\n",
            "       [210.15991211, 192.38595581],\n",
            "       [210.05575562, 193.44692993],\n",
            "       [209.91999817, 194.5059967 ],\n",
            "       [209.74794006, 195.58335876],\n",
            "       [209.54348755, 196.65368652],\n",
            "       [209.30767822, 197.71676636],\n",
            "       [209.04151917, 198.77232361],\n",
            "       [208.74604797, 199.82012939],\n",
            "       [208.42225647, 200.85995483],\n",
            "       [208.07119751, 201.89154053],\n",
            "       [207.69387817, 202.91464233],\n",
            "       [207.29130554, 203.92903137],\n",
            "       [206.86451721, 204.93444824],\n",
            "       [206.41453552, 205.93066406],\n",
            "       [205.94236755, 206.91744995],\n",
            "       [205.4490509 , 207.89453125],\n",
            "       [204.93559265, 208.86167908],\n",
            "       [204.40301514, 209.81866455],\n",
            "       [203.85235596, 210.76522827],\n",
            "       [203.28462219, 211.7011261 ],\n",
            "       [202.70082092, 212.62614441],\n",
            "       [202.102005  , 213.53999329],\n",
            "       [201.53799438, 214.37246704],\n",
            "       [200.96247864, 215.19587708],\n",
            "       [200.37559509, 216.01026917],\n",
            "       [199.77755737, 216.81562805],\n",
            "       [199.16853333, 217.61201477],\n",
            "       [198.54867554, 218.39941406],\n",
            "       [197.91819763, 219.1778717 ],\n",
            "       [197.27726746, 219.9473877 ],\n",
            "       [196.62605286, 220.70799255],\n",
            "       [195.9647522 , 221.45970154],\n",
            "       [195.29351807, 222.20254517],\n",
            "       [194.61254883, 222.9365387 ],\n",
            "       [193.92201233, 223.66169739],\n",
            "       [193.22209167, 224.3780365 ],\n",
            "       [192.51296997, 225.08560181],\n",
            "       [191.79481506, 225.78437805],\n",
            "       [191.06781006, 226.47441101],\n",
            "       [190.33213806, 227.15570068],\n",
            "       [189.58798218, 227.82829285],\n",
            "       [188.83551025, 228.4921875 ],\n",
            "       [188.07489014, 229.1473999 ],\n",
            "       [187.30632019, 229.79397583],\n",
            "       [186.52996826, 230.43191528],\n",
            "       [185.74603271, 231.06123352],\n",
            "       [184.95466614, 231.68197632],\n",
            "       [184.15605164, 232.29414368],\n",
            "       [183.35037231, 232.89775085],\n",
            "       [182.53781128, 233.49282837],\n",
            "       [181.71855164, 234.07939148],\n",
            "       [180.89274597, 234.6574707 ],\n",
            "       [180.06060791, 235.2270813 ],\n",
            "       [179.22229004, 235.78822327],\n",
            "       [178.37797546, 236.34094238],\n",
            "       [177.52784729, 236.88525391],\n",
            "       [176.67208862, 237.4211731 ],\n",
            "       [175.81086731, 237.94873047],\n",
            "       [174.94436646, 238.46792603],\n",
            "       [174.07276917, 238.97879028],\n",
            "       [173.19624329, 239.4813385 ],\n",
            "       [172.31498718, 239.9756012 ],\n",
            "       [171.42915344, 240.46159363],\n",
            "       [170.53892517, 240.93933105],\n",
            "       [169.64450073, 241.40884399],\n",
            "       [168.74604797, 241.87014771],\n",
            "       [167.84373474, 242.32324219],\n",
            "       [166.9377594 , 242.76818848],\n",
            "       [166.02827454, 243.20497131],\n",
            "       [165.11549377, 243.63362122],\n",
            "       [164.19955444, 244.0541687 ],\n",
            "       [163.28067017, 244.46661377],\n",
            "       [162.35899353, 244.8710022 ],\n",
            "       [161.40872192, 245.27859497],\n",
            "       [160.45437622, 245.67819214],\n",
            "       [159.49604797, 246.06944275],\n",
            "       [158.53381348, 246.4519043 ],\n",
            "       [157.56776428, 246.82521057],\n",
            "       [156.59794617, 247.18894958],\n",
            "       [155.62446594, 247.54272461],\n",
            "       [154.64738464, 247.88613892],\n",
            "       [153.66677856, 248.21881104],\n",
            "       [152.68273926, 248.54032898],\n",
            "       [151.69532776, 248.85031128],\n",
            "       [150.70465088, 249.14834595],\n",
            "       [149.71075439, 249.43403625],\n",
            "       [148.71372986, 249.70698547],\n",
            "       [147.71365356, 249.96681213],\n",
            "       [146.71060181, 250.21310425],\n",
            "       [145.70465088, 250.44546509],\n",
            "       [144.69589233, 250.66351318],\n",
            "       [143.68438721, 250.86685181],\n",
            "       [142.67021179, 251.05505371],\n",
            "       [141.65345764, 251.22775269],\n",
            "       [140.63420105, 251.384552  ],\n",
            "       [139.61250305, 251.52503967],\n",
            "       [138.58847046, 251.64881897],\n",
            "       [137.56214905, 251.75550842],\n",
            "       [136.53363037, 251.84469604],\n",
            "       [135.50300598, 251.91600037],\n",
            "       [134.43032837, 251.97042847],\n",
            "       [133.35682678, 252.00489807],\n",
            "       [132.28288269, 252.0194397 ],\n",
            "       [131.20883179, 252.01411438],\n",
            "       [130.13505554, 251.9889679 ],\n",
            "       [129.06192017, 251.94404602],\n",
            "       [127.98977661, 251.87940979],\n",
            "       [126.91899109, 251.79508972],\n",
            "       [125.84993744, 251.69113159],\n",
            "       [124.78296661, 251.56759644],\n",
            "       [123.71844482, 251.42453003],\n",
            "       [122.65673828, 251.26197815],\n",
            "       [121.59820557, 251.07997131],\n",
            "       [120.54322052, 250.87858582],\n",
            "       [119.49214172, 250.65786743],\n",
            "       [118.44532776, 250.41784668],\n",
            "       [117.40314484, 250.15858459],\n",
            "       [116.36595917, 249.88011169],\n",
            "       [115.33412933, 249.58248901],\n",
            "       [114.30802155, 249.26577759],\n",
            "       [113.28800201, 248.92999268],\n",
            "       [112.30471039, 248.58607483],\n",
            "       [111.32832336, 248.22494507],\n",
            "       [110.35888672, 247.84690857],\n",
            "       [109.39648438, 247.45228577],\n",
            "       [108.441185  , 247.04138184],\n",
            "       [107.49304962, 246.61447144],\n",
            "       [106.55214691, 246.17190552],\n",
            "       [105.61855316, 245.71394348],\n",
            "       [104.69233704, 245.24092102],\n",
            "       [103.77355957, 244.75312805],\n",
            "       [102.86228943, 244.25086975],\n",
            "       [101.95860291, 243.73445129],\n",
            "       [101.06256104, 243.20417786],\n",
            "       [100.17424011, 242.66035461],\n",
            "       [ 99.29370117, 242.10328674],\n",
            "       [ 98.42102051, 241.53326416],\n",
            "       [ 97.55625916, 240.95062256],\n",
            "       [ 96.69949341, 240.3556366 ],\n",
            "       [ 95.8507843 , 239.74862671],\n",
            "       [ 95.01020813, 239.12989807],\n",
            "       [ 94.17782593, 238.4997406 ],\n",
            "       [ 93.35371399, 237.85845947],\n",
            "       [ 92.53793335, 237.20637512],\n",
            "       [ 91.73055267, 236.54379272],\n",
            "       [ 90.93165588, 235.87098694],\n",
            "       [ 90.14128876, 235.18829346],\n",
            "       [ 89.35953522, 234.49601746],\n",
            "       [ 88.58646393, 233.79443359],\n",
            "       [ 87.82213593, 233.0838623 ],\n",
            "       [ 87.0666275 , 232.36462402],\n",
            "       [ 86.31999969, 231.63699341],\n",
            "       [ 85.56887054, 230.88719177],\n",
            "       [ 84.82626343, 230.12791443],\n",
            "       [ 84.09259033, 229.35922241],\n",
            "       [ 83.3682785 , 228.58113098],\n",
            "       [ 82.6537323 , 227.79371643],\n",
            "       [ 81.94937134, 226.99697876],\n",
            "       [ 81.2556076 , 226.19096375],\n",
            "       [ 80.57286835, 225.37573242],\n",
            "       [ 79.90156555, 224.55130005],\n",
            "       [ 79.24211121, 223.71769714],\n",
            "       [ 78.5949173 , 222.87498474],\n",
            "       [ 77.9604187 , 222.02319336],\n",
            "       [ 77.33901215, 221.16235352],\n",
            "       [ 76.73112488, 220.29249573],\n",
            "       [ 76.13716888, 219.41368103],\n",
            "       [ 75.55756378, 218.52593994],\n",
            "       [ 74.99272156, 217.62928772],\n",
            "       [ 74.44306183, 216.7237854 ],\n",
            "       [ 73.90899658, 215.80947876],\n",
            "       [ 73.39094543, 214.8863678 ],\n",
            "       [ 72.889328  , 213.95452881],\n",
            "       [ 72.40455627, 213.01397705],\n",
            "       [ 71.93704224, 212.06477356],\n",
            "       [ 71.48721313, 211.10691833],\n",
            "       [ 71.05547333, 210.14048767],\n",
            "       [ 70.64225006, 209.16549683],\n",
            "       [ 70.24795532, 208.18199158],\n",
            "       [ 69.8730011 , 207.19000244],\n",
            "       [ 69.54187012, 206.25941467],\n",
            "       [ 69.22902679, 205.32443237],\n",
            "       [ 68.93431854, 204.38523865],\n",
            "       [ 68.6576004 , 203.44204712],\n",
            "       [ 68.39871216, 202.49502563],\n",
            "       [ 68.15752411, 201.54440308],\n",
            "       [ 67.93386841, 200.59034729],\n",
            "       [ 67.72760773, 199.6330719 ],\n",
            "       [ 67.53858948, 198.67274475],\n",
            "       [ 67.3666687 , 197.70959473],\n",
            "       [ 67.21168518, 196.74378967],\n",
            "       [ 67.07350159, 195.77554321],\n",
            "       [ 66.9519577 , 194.80503845],\n",
            "       [ 66.8469162 , 193.83247375],\n",
            "       [ 66.75822449, 192.85804749],\n",
            "       [ 66.68572998, 191.88194275],\n",
            "       [ 66.62928772, 190.90437317],\n",
            "       [ 66.58874512, 189.92552185],\n",
            "       [ 66.56395721, 188.9455719 ],\n",
            "       [ 66.55477142, 187.9647522 ],\n",
            "       [ 66.56104279, 186.98323059],\n",
            "       [ 66.58261871, 186.00120544],\n",
            "       [ 66.61934662, 185.01887512],\n",
            "       [ 66.67108917, 184.03643799],\n",
            "       [ 66.73768616, 183.05407715],\n",
            "       [ 66.81899261, 182.07200623],\n",
            "       [ 66.91485596, 181.09039307],\n",
            "       [ 67.02513885, 180.10946655],\n",
            "       [ 67.14968109, 179.12939453],\n",
            "       [ 67.28833008, 178.15039062],\n",
            "       [ 67.44094849, 177.17263794],\n",
            "       [ 67.60738373, 176.19633484],\n",
            "       [ 67.78749084, 175.22166443],\n",
            "       [ 67.98110962, 174.24884033],\n",
            "       [ 68.18809509, 173.27806091],\n",
            "       [ 68.40830231, 172.30949402],\n",
            "       [ 68.64157867, 171.34335327],\n",
            "       [ 68.88777924, 170.37983704],\n",
            "       [ 69.1467514 , 169.41912842],\n",
            "       [ 69.41835022, 168.46144104],\n",
            "       [ 69.70241547, 167.50694275],\n",
            "       [ 69.99881744, 166.55584717],\n",
            "       [ 70.30738831, 165.6083374 ],\n",
            "       [ 70.62799072, 164.66462708],\n",
            "       [ 70.96046448, 163.72489929],\n",
            "       [ 71.30467224, 162.78933716],\n",
            "       [ 71.66046906, 161.8581543 ],\n",
            "       [ 72.02768707, 160.93154907],\n",
            "       [ 72.40618896, 160.00968933],\n",
            "       [ 72.79582977, 159.09280396],\n",
            "       [ 73.19644928, 158.18106079],\n",
            "       [ 73.60791016, 157.2746582 ],\n",
            "       [ 74.03005219, 156.37380981],\n",
            "       [ 74.46273804, 155.47869873],\n",
            "       [ 74.9058075 , 154.58950806],\n",
            "       [ 75.3591156 , 153.70645142],\n",
            "       [ 75.8225174 , 152.82972717],\n",
            "       [ 76.29586029, 151.95950317],\n",
            "       [ 76.77899933, 151.09599304],\n",
            "       [ 77.28591919, 150.21913147],\n",
            "       [ 77.80758667, 149.34925842],\n",
            "       [ 78.34383392, 148.48681641],\n",
            "       [ 78.89452362, 147.63224792],\n",
            "       [ 79.45948792, 146.786026  ],\n",
            "       [ 80.03858948, 145.94859314],\n",
            "       [ 80.63166046, 145.12039185],\n",
            "       [ 81.23855591, 144.30186462],\n",
            "       [ 81.85912323, 143.49346924],\n",
            "       [ 82.49320221, 142.69564819],\n",
            "       [ 83.14064789, 141.90885925],\n",
            "       [ 83.80130005, 141.13352966],\n",
            "       [ 84.47501373, 140.37013245],\n",
            "       [ 85.16162872, 139.61911011],\n",
            "       [ 85.86099243, 138.88090515],\n",
            "       [ 86.5729599 , 138.15596008],\n",
            "       [ 87.29736328, 137.44474792],\n",
            "       [ 88.03406525, 136.74769592],\n",
            "       [ 88.78289795, 136.06524658],\n",
            "       [ 89.54372406, 135.39787292],\n",
            "       [ 90.31637573, 134.7460022 ],\n",
            "       [ 91.10070801, 134.11009216],\n",
            "       [ 91.89656067, 133.49058533],\n",
            "       [ 92.70379639, 132.88793945],\n",
            "       [ 93.52223969, 132.30259705],\n",
            "       [ 94.35175323, 131.73501587],\n",
            "       [ 95.19218445, 131.18562317],\n",
            "       [ 96.04337311, 130.65489197],\n",
            "       [ 96.90516663, 130.14324951],\n",
            "       [ 97.77741241, 129.65115356],\n",
            "       [ 98.65995789, 129.17906189],\n",
            "       [ 99.55265045, 128.72741699],\n",
            "       [100.45534515, 128.29666138],\n",
            "       [101.36787415, 127.88723755],\n",
            "       [102.29008484, 127.4996109 ],\n",
            "       [103.2218399 , 127.13422394],\n",
            "       [104.1629715 , 126.79151917],\n",
            "       [105.11333466, 126.47195435],\n",
            "       [106.07276917, 126.17596436],\n",
            "       [107.04113007, 125.90401459],\n",
            "       [108.01825714, 125.65653992],\n",
            "       [109.0039978 , 125.43399811]])], [array([[140.84300232,  11.85200024],\n",
            "       [141.45674133,  12.43616676],\n",
            "       [142.09480286,  13.01455879],\n",
            "       ...,\n",
            "       [141.49961853,  13.91237926],\n",
            "       [141.1630249 ,  12.89239883],\n",
            "       [140.84399414,  11.84700012]])], [array([[  7.98000002,   0.83999997],\n",
            "       [  8.98950958,   0.84788334],\n",
            "       [  9.99900818,   0.85685998],\n",
            "       [ 11.00849438,   0.86692989],\n",
            "       [ 12.01796722,   0.878093  ],\n",
            "       [ 13.02742577,   0.89034915],\n",
            "       [ 14.0368681 ,   0.90369827],\n",
            "       [ 15.04629326,   0.91814029],\n",
            "       [ 16.05570221,   0.93367511],\n",
            "       [ 17.06509018,   0.95030266],\n",
            "       [ 18.07445908,   0.96802288],\n",
            "       [ 19.08380508,   0.98683566],\n",
            "       [ 20.09313011,   1.00674081],\n",
            "       [ 21.10243034,   1.02773845],\n",
            "       [ 22.11170578,   1.04982829],\n",
            "       [ 23.12095642,   1.07301033],\n",
            "       [ 24.13017845,   1.09728456],\n",
            "       [ 25.13937378,   1.12265074],\n",
            "       [ 26.14853859,   1.14910889],\n",
            "       [ 27.15767288,   1.17665887],\n",
            "       [ 28.16677475,   1.20530069],\n",
            "       [ 29.1758461 ,   1.23503411],\n",
            "       [ 30.18488121,   1.26585913],\n",
            "       [ 31.19388199,   1.29777563],\n",
            "       [ 32.20284653,   1.33078349],\n",
            "       [ 33.21177292,   1.36488283],\n",
            "       [ 34.22066116,   1.40007329],\n",
            "       [ 35.22951126,   1.43635499],\n",
            "       [ 36.2383194 ,   1.4737277 ],\n",
            "       [ 37.24708557,   1.5121913 ],\n",
            "       [ 38.25580978,   1.55174589],\n",
            "       [ 39.26448822,   1.59239125],\n",
            "       [ 40.27312088,   1.63412738],\n",
            "       [ 41.28170776,   1.67695415],\n",
            "       [ 42.29024887,   1.72087133],\n",
            "       [ 43.29874039,   1.76587903],\n",
            "       [ 44.3071785 ,   1.81197715],\n",
            "       [ 45.31557083,   1.85916555],\n",
            "       [ 46.32390594,   1.907444  ],\n",
            "       [ 47.33219147,   1.95681274],\n",
            "       [ 48.34041977,   2.00727129],\n",
            "       [ 49.34859467,   2.05882001],\n",
            "       [ 50.35671234,   2.1114583 ],\n",
            "       [ 51.36476898,   2.16518664],\n",
            "       [ 52.3727684 ,   2.22000432],\n",
            "       [ 53.3807106 ,   2.27591181],\n",
            "       [ 54.38858795,   2.33290887],\n",
            "       [ 55.39640427,   2.39099503],\n",
            "       [ 56.40415573,   2.45017076],\n",
            "       [ 57.41184235,   2.51043558],\n",
            "       [ 58.41946411,   2.5717895 ],\n",
            "       [ 59.42701721,   2.63423276],\n",
            "       [ 60.43450546,   2.69776464],\n",
            "       [ 61.44192123,   2.76238561],\n",
            "       [ 62.44926834,   2.8280952 ],\n",
            "       [ 63.45654297,   2.89489365],\n",
            "       [ 64.46374512,   2.96278071],\n",
            "       [ 65.47087097,   3.0317564 ],\n",
            "       [ 66.47792816,   3.10182023],\n",
            "       [ 67.48490143,   3.17297268],\n",
            "       [ 68.4917984 ,   3.24521327],\n",
            "       [ 69.49861908,   3.318542  ],\n",
            "       [ 70.50536346,   3.39295912],\n",
            "       [ 71.51202393,   3.4684639 ],\n",
            "       [ 72.51860046,   3.54505682],\n",
            "       [ 73.52510071,   3.62273741],\n",
            "       [ 74.5315094 ,   3.7015059 ],\n",
            "       [ 75.53783417,   3.78136182],\n",
            "       [ 76.54407501,   3.8623054 ],\n",
            "       [ 77.5502243 ,   3.94433665],\n",
            "       [ 78.55628967,   4.02745533],\n",
            "       [ 79.56226349,   4.11166096],\n",
            "       [ 80.56814575,   4.19695377],\n",
            "       [ 81.57393646,   4.28333426],\n",
            "       [ 82.57963562,   4.37080145],\n",
            "       [ 83.5852356 ,   4.45935535],\n",
            "       [ 84.59074402,   4.54899645],\n",
            "       [ 85.59615326,   4.63972425],\n",
            "       [ 86.60146332,   4.73153877],\n",
            "       [ 87.60667419,   4.82444   ],\n",
            "       [ 88.61179352,   4.91842747],\n",
            "       [ 89.6167984 ,   5.01350164],\n",
            "       [ 90.62171173,   5.10966206],\n",
            "       [ 91.62651825,   5.2069087 ],\n",
            "       [ 92.63121796,   5.30524158],\n",
            "       [ 93.63581085,   5.4046607 ],\n",
            "       [ 94.64029694,   5.50516558],\n",
            "       [ 95.64468384,   5.60675621],\n",
            "       [ 96.64894867,   5.70943308],\n",
            "       [ 97.65310669,   5.81319571],\n",
            "       [ 98.6571579 ,   5.91804361],\n",
            "       [ 99.66109467,   6.02397728],\n",
            "       [100.66491699,   6.13099623],\n",
            "       [101.66862488,   6.23910093],\n",
            "       [102.67221069,   6.34829044],\n",
            "       [103.6756897 ,   6.45856571],\n",
            "       [104.679039  ,   6.56992579],\n",
            "       [105.68227386,   6.68237066],\n",
            "       [106.68539429,   6.79590082],\n",
            "       [107.68838501,   6.91051579],\n",
            "       [108.69125366,   7.02621555],\n",
            "       [109.69400024,   7.14300013],\n",
            "       [110.97899628,   7.55999994],\n",
            "       [111.49099731,   9.56499958],\n",
            "       [111.43617249,  10.57774258],\n",
            "       [111.38134766,  11.59048462],\n",
            "       [111.3265152 ,  12.60322571],\n",
            "       [111.27169037,  13.6159668 ],\n",
            "       [111.21686554,  14.62870693],\n",
            "       [111.16204071,  15.64144707],\n",
            "       [111.10721588,  16.65418625],\n",
            "       [111.05239105,  17.66692543],\n",
            "       [110.99756622,  18.6796627 ],\n",
            "       [110.94274139,  19.69239998],\n",
            "       [110.88791656,  20.70513535],\n",
            "       [110.83309174,  21.71787262],\n",
            "       [110.77827454,  22.73060799],\n",
            "       [110.72344971,  23.74334145],\n",
            "       [110.66862488,  24.75607491],\n",
            "       [110.61380768,  25.76880836],\n",
            "       [110.55898285,  26.78154182],\n",
            "       [110.50416565,  27.79427338],\n",
            "       [110.44934082,  28.80700493],\n",
            "       [110.39452362,  29.81973457],\n",
            "       [110.33970642,  30.83246422],\n",
            "       [110.28488159,  31.84519196],\n",
            "       [110.23006439,  32.8579216 ],\n",
            "       [110.17524719,  33.87064743],\n",
            "       [110.12042999,  34.88337326],\n",
            "       [110.06561279,  35.89609909],\n",
            "       [110.01079559,  36.90882492],\n",
            "       [109.95597839,  37.92154694],\n",
            "       [109.90116119,  38.93427277],\n",
            "       [109.84634399,  39.94699478],\n",
            "       [109.79152679,  40.9597168 ],\n",
            "       [109.73670959,  41.972435  ],\n",
            "       [109.6818924 ,  42.98515701],\n",
            "       [109.6270752 ,  43.99787521],\n",
            "       [109.572258  ,  45.01059341],\n",
            "       [109.5174408 ,  46.0233078 ],\n",
            "       [109.46263123,  47.036026  ],\n",
            "       [109.40781403,  48.04874039],\n",
            "       [109.35299683,  49.06145477],\n",
            "       [109.29817963,  50.07416916],\n",
            "       [109.24337006,  51.08687973],\n",
            "       [109.18855286,  52.0995903 ],\n",
            "       [109.13373566,  53.11230087],\n",
            "       [109.07892609,  54.12501144],\n",
            "       [109.02410889,  55.13772202],\n",
            "       [108.96929169,  56.15042877],\n",
            "       [108.91448212,  57.16313553],\n",
            "       [108.85966492,  58.17583847],\n",
            "       [108.80484772,  59.18854523],\n",
            "       [108.75003815,  60.20124817],\n",
            "       [108.69522095,  61.2139473 ],\n",
            "       [108.64040375,  62.22665024],\n",
            "       [108.58559418,  63.23934937],\n",
            "       [108.53077698,  64.25205231],\n",
            "       [108.47596741,  65.26474762],\n",
            "       [108.42115021,  66.27744293],\n",
            "       [108.36633301,  67.29013824],\n",
            "       [108.31152344,  68.30283356],\n",
            "       [108.25670624,  69.31552887],\n",
            "       [108.20188904,  70.32821655],\n",
            "       [108.14707947,  71.34091187],\n",
            "       [108.09226227,  72.35359955],\n",
            "       [108.03744507,  73.36628723],\n",
            "       [107.9826355 ,  74.37897491],\n",
            "       [107.9278183 ,  75.3916626 ],\n",
            "       [107.8730011 ,  76.40435028],\n",
            "       [107.8181839 ,  77.41703033],\n",
            "       [107.76337433,  78.42971039],\n",
            "       [107.70855713,  79.44239044],\n",
            "       [107.65373993,  80.4550705 ],\n",
            "       [107.59892273,  81.46775055],\n",
            "       [107.54410553,  82.4804306 ],\n",
            "       [107.48929596,  83.49310303],\n",
            "       [107.43447876,  84.50578308],\n",
            "       [107.37966156,  85.51845551],\n",
            "       [107.32484436,  86.53112793],\n",
            "       [107.27002716,  87.54380035],\n",
            "       [107.21520996,  88.55646515],\n",
            "       [107.16039276,  89.56913757],\n",
            "       [107.10556793,  90.58180237],\n",
            "       [107.05075073,  91.59446716],\n",
            "       [106.99593353,  92.60713196],\n",
            "       [106.94111633,  93.61979675],\n",
            "       [106.88629913,  94.63245392],\n",
            "       [106.8314743 ,  95.64511871],\n",
            "       [106.7766571 ,  96.65777588],\n",
            "       [106.7218399 ,  97.67043304],\n",
            "       [106.66701508,  98.68309021],\n",
            "       [106.61219788,  99.69573975],\n",
            "       [106.55737305, 100.70839691],\n",
            "       [106.50254822, 101.72104645],\n",
            "       [106.44773102, 102.73369598],\n",
            "       [106.39290619, 103.74634552],\n",
            "       [106.33808136, 104.75898743],\n",
            "       [106.28325653, 105.77163696],\n",
            "       [106.22843933, 106.78427887],\n",
            "       [106.1736145 , 107.79692078],\n",
            "       [106.11878967, 108.80956268],\n",
            "       [106.06396484, 109.82219696],\n",
            "       [106.00914001, 110.83483887],\n",
            "       [105.95430756, 111.84747314],\n",
            "       [105.89948273, 112.86010742],\n",
            "       [105.8446579 , 113.8727417 ],\n",
            "       [105.78982544, 114.88536835],\n",
            "       [105.73500061, 115.89800262],\n",
            "       [105.5490036 , 117.41750336],\n",
            "       [104.8710022 , 118.71499634],\n",
            "       [102.44000244, 119.60900116],\n",
            "       [101.43859863, 119.74288177],\n",
            "       [100.43685913, 119.87176514],\n",
            "       [ 99.43478394, 119.99569702],\n",
            "       [ 98.43238831, 120.11471558],\n",
            "       [ 97.42967224, 120.22885895],\n",
            "       [ 96.426651  , 120.33818054],\n",
            "       [ 95.42332458, 120.44271851],\n",
            "       [ 94.41970062, 120.54251099],\n",
            "       [ 93.41579437, 120.63759613],\n",
            "       [ 92.41161346, 120.72802734],\n",
            "       [ 91.40715027, 120.81383514],\n",
            "       [ 90.4024353 , 120.89507294],\n",
            "       [ 89.39746094, 120.97177124],\n",
            "       [ 88.3922348 , 121.04398346],\n",
            "       [ 87.38677216, 121.11174011],\n",
            "       [ 86.38108063, 121.1750946 ],\n",
            "       [ 85.37516022, 121.23407745],\n",
            "       [ 84.36901855, 121.28874207],\n",
            "       [ 83.36267853, 121.33911896],\n",
            "       [ 82.35612488, 121.38525391],\n",
            "       [ 81.34938812, 121.42720032],\n",
            "       [ 80.34246063, 121.46498108],\n",
            "       [ 79.33535767, 121.4986496 ],\n",
            "       [ 78.32807922, 121.52824402],\n",
            "       [ 77.32064056, 121.55381775],\n",
            "       [ 76.31304932, 121.57539368],\n",
            "       [ 75.30530548, 121.59302521],\n",
            "       [ 74.29742432, 121.60675049],\n",
            "       [ 73.28941345, 121.61662292],\n",
            "       [ 72.28127289, 121.62266541],\n",
            "       [ 71.27302551, 121.62493134],\n",
            "       [ 70.2646637 , 121.62345886],\n",
            "       [ 69.2562027 , 121.61829376],\n",
            "       [ 68.24764252, 121.60948181],\n",
            "       [ 67.23899841, 121.59705353],\n",
            "       [ 66.23028564, 121.58105469],\n",
            "       [ 65.22149658, 121.56153107],\n",
            "       [ 64.21263885, 121.53852844],\n",
            "       [ 63.20373535, 121.51207733],\n",
            "       [ 62.19478226, 121.48222351],\n",
            "       [ 61.1857872 , 121.44902039],\n",
            "       [ 60.17676544, 121.41249084],\n",
            "       [ 59.16771698, 121.37268829],\n",
            "       [ 58.15865326, 121.32965851],\n",
            "       [ 57.14958191, 121.28343201],\n",
            "       [ 56.14050674, 121.23406219],\n",
            "       [ 55.13144302, 121.18157959],\n",
            "       [ 54.12239075, 121.12602997],\n",
            "       [ 53.11336517, 121.06746674],\n",
            "       [ 52.1043663 , 121.00592041],\n",
            "       [ 51.09540558, 120.94142914],\n",
            "       [ 50.08649445, 120.87404633],\n",
            "       [ 49.0776329 , 120.80380249],\n",
            "       [ 48.0688324 , 120.73075104],\n",
            "       [ 47.06010437, 120.65493011],\n",
            "       [ 46.05144882, 120.57637787],\n",
            "       [ 45.04288101, 120.49513245],\n",
            "       [ 44.03440475, 120.41124725],\n",
            "       [ 43.02602768, 120.32476044],\n",
            "       [ 42.01775742, 120.23571014],\n",
            "       [ 41.00960159, 120.14414215],\n",
            "       [ 40.00157166, 120.05010223],\n",
            "       [ 38.99367142, 119.95362091],\n",
            "       [ 37.98590851, 119.85474396],\n",
            "       [ 36.97829437, 119.75351715],\n",
            "       [ 35.97083282, 119.64998627],\n",
            "       [ 34.96353149, 119.54418182],\n",
            "       [ 33.95639801, 119.4361496 ],\n",
            "       [ 32.94944763, 119.32594299],\n",
            "       [ 31.94267654, 119.21359253],\n",
            "       [ 30.93610001, 119.09913635],\n",
            "       [ 29.92972374, 118.98262787],\n",
            "       [ 28.92355537, 118.86410522],\n",
            "       [ 27.91760254, 118.74360657],\n",
            "       [ 26.91187477, 118.62117767],\n",
            "       [ 25.90637589, 118.49685669],\n",
            "       [ 24.90111732, 118.37068939],\n",
            "       [ 23.89610481, 118.24271393],\n",
            "       [ 22.89134789, 118.1129837 ],\n",
            "       [ 21.88685036, 117.98152161],\n",
            "       [ 20.88262558, 117.84838867],\n",
            "       [ 19.87867546, 117.71360779],\n",
            "       [ 18.87501335, 117.57723999],\n",
            "       [ 17.87164307, 117.4393158 ],\n",
            "       [ 16.86857224, 117.29988098],\n",
            "       [ 15.86581135, 117.15897369],\n",
            "       [ 14.86336613, 117.01663971],\n",
            "       [ 13.8612442 , 116.87291718],\n",
            "       [ 12.85945415, 116.72785187],\n",
            "       [ 11.85800362, 116.58148956],\n",
            "       [ 10.85690022, 116.43386078],\n",
            "       [  9.85615158, 116.28501892],\n",
            "       [  8.85576534, 116.13500214],\n",
            "       [  7.85574961, 115.98384857],\n",
            "       [  6.85611153, 115.83159637],\n",
            "       [  5.85685921, 115.67830658],\n",
            "       [  4.8579998 , 115.52400208],\n",
            "       [  2.79200006, 114.73000336],\n",
            "       [  2.08400011, 112.32499695],\n",
            "       [  2.03795004, 111.24328613],\n",
            "       [  1.99276388, 110.16156769],\n",
            "       [  1.94838667, 109.07984924],\n",
            "       [  1.90476382, 107.99812317],\n",
            "       [  1.86184072, 106.91638184],\n",
            "       [  1.81956267, 105.83463287],\n",
            "       [  1.77787495, 104.75287628],\n",
            "       [  1.73672307, 103.6710968 ],\n",
            "       [  1.69605207, 102.58930206],\n",
            "       [  1.65580761, 101.50749207],\n",
            "       [  1.61593473, 100.42565918],\n",
            "       [  1.57637906,  99.34379578],\n",
            "       [  1.53708565,  98.26191711],\n",
            "       [  1.49800003,  97.18000031],\n",
            "       [  1.46131647,  96.1638031 ],\n",
            "       [  1.42468441,  95.14744568],\n",
            "       [  1.38814735,  94.13093567],\n",
            "       [  1.35174859,  93.1142807 ],\n",
            "       [  1.31553173,  92.0974884 ],\n",
            "       [  1.27954018,  91.08055878],\n",
            "       [  1.24381745,  90.06349945],\n",
            "       [  1.20840704,  89.04631805],\n",
            "       [  1.17335236,  88.02902222],\n",
            "       [  1.13869691,  87.01161957],\n",
            "       [  1.1044842 ,  85.99411011],\n",
            "       [  1.07075751,  84.97650146],\n",
            "       [  1.03756058,  83.95880127],\n",
            "       [  1.00493681,  82.94101715],\n",
            "       [  0.9729296 ,  81.92315674],\n",
            "       [  0.94158244,  80.90522003],\n",
            "       [  0.9109388 ,  79.88721466],\n",
            "       [  0.88104212,  78.86914825],\n",
            "       [  0.85193598,  77.85102844],\n",
            "       [  0.82366377,  76.83286285],\n",
            "       [  0.796269  ,  75.81465149],\n",
            "       [  0.76979512,  74.79640961],\n",
            "       [  0.74428564,  73.77812958],\n",
            "       [  0.71978396,  72.75982666],\n",
            "       [  0.69633359,  71.74150848],\n",
            "       [  0.67397797,  70.72317505],\n",
            "       [  0.65276068,  69.70484161],\n",
            "       [  0.63272506,  68.68650818],\n",
            "       [  0.61391467,  67.66817474],\n",
            "       [  0.59637296,  66.64985657],\n",
            "       [  0.58014333,  65.63155365],\n",
            "       [  0.56526941,  64.61328125],\n",
            "       [  0.55179453,  63.59503937],\n",
            "       [  0.5397622 ,  62.57683182],\n",
            "       [  0.52921593,  61.55866623],\n",
            "       [  0.52019912,  60.54055405],\n",
            "       [  0.51275533,  59.52249527],\n",
            "       [  0.50692803,  58.50449753],\n",
            "       [  0.50276059,  57.48656464],\n",
            "       [  0.50029653,  56.46870804],\n",
            "       [  0.49957937,  55.45093155],\n",
            "       [  0.50065255,  54.4332428 ],\n",
            "       [  0.50355953,  53.41564178],\n",
            "       [  0.50834382,  52.39813995],\n",
            "       [  0.51504886,  51.38074493],\n",
            "       [  0.52371812,  50.36346054],\n",
            "       [  0.53439504,  49.34629059],\n",
            "       [  0.54712319,  48.32924271],\n",
            "       [  0.56194597,  47.31232452],\n",
            "       [  0.57890683,  46.29553986],\n",
            "       [  0.59804934,  45.27889633],\n",
            "       [  0.61941683,  44.26240158],\n",
            "       [  0.64305294,  43.24605942],\n",
            "       [  0.66900098,  42.22987747],\n",
            "       [  0.69730455,  41.21385956],\n",
            "       [  0.72800708,  40.19801331],\n",
            "       [  0.76115203,  39.18234253],\n",
            "       [  0.79678285,  38.16685867],\n",
            "       [  0.834943  ,  37.15156555],\n",
            "       [  0.87567604,  36.13646698],\n",
            "       [  0.91902536,  35.12156677],\n",
            "       [  0.96503448,  34.10688019],\n",
            "       [  1.01374686,  33.09240723],\n",
            "       [  1.06520605,  32.0781517 ],\n",
            "       [  1.11945534,  31.06412506],\n",
            "       [  1.17653835,  30.05032921],\n",
            "       [  1.23649848,  29.03677368],\n",
            "       [  1.29937911,  28.0234642 ],\n",
            "       [  1.365224  ,  27.01040459],\n",
            "       [  1.43407643,  25.99760056],\n",
            "       [  1.50597978,  24.98506165],\n",
            "       [  1.5809778 ,  23.97279167],\n",
            "       [  1.65911365,  22.96079636],\n",
            "       [  1.74043107,  21.94908524],\n",
            "       [  1.82497334,  20.93766022],\n",
            "       [  1.91278398,  19.92652893],\n",
            "       [  2.00390649,  18.9156971 ],\n",
            "       [  2.09838438,  17.90517235],\n",
            "       [  2.19626117,  16.8949585 ],\n",
            "       [  2.29758   ,  15.88506413],\n",
            "       [  2.40238476,  14.87549305],\n",
            "       [  2.51071882,  13.86625385],\n",
            "       [  2.62262559,  12.85735035],\n",
            "       [  2.73814821,  11.84879017],\n",
            "       [  2.8573308 ,  10.84057903],\n",
            "       [  2.9802165 ,   9.83272266],\n",
            "       [  3.10684848,   8.82522774],\n",
            "       [  3.23727083,   7.8180995 ],\n",
            "       [  3.37152672,   6.81134462],\n",
            "       [  3.50965953,   5.80496931],\n",
            "       [  3.65171266,   4.79897976],\n",
            "       [  3.79772997,   3.79338217],\n",
            "       [  3.94775462,   2.78818202],\n",
            "       [  4.10183001,   1.78338599],\n",
            "       [  4.26000023,   0.77899998],\n",
            "       [  5.6753335 ,   1.34307408],\n",
            "       [  7.1833334 ,   1.5595926 ],\n",
            "       [  8.69999981,   1.41700006]])]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Visualizing the results"
      ],
      "metadata": {
        "id": "qma6sXK9DZli"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Plotting function with an option to save the plot and without axis points\n",
        "def plot(paths_XYs, save_path=None):\n",
        "    colours = ['black']\n",
        "    fig, ax = plt.subplots(tight_layout=True, figsize=(6, 6))\n",
        "    for i, XYs in enumerate(paths_XYs):\n",
        "        c = colours[i % len(colours)]\n",
        "        for XY in XYs:\n",
        "            ax.plot(XY[:, 0], XY[:, 1], color=c, linewidth=2)\n",
        "    ax.set_aspect('equal')\n",
        "    ax.axis('off')  # Turn off the axis\n",
        "\n",
        "    if save_path:\n",
        "        plt.savefig(save_path)  # Save the figure as a PNG file\n",
        "    plt.show()\n",
        "\n",
        "# Example usage: plot and save the shapes without axis points\n",
        "plot(shapes, '/content/isolated.png')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 584
        },
        "id": "kNo4CXhSDcn3",
        "outputId": "97ac6e13-40e8-48b9-8e26-6c7d78254172"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAk4AAAI3CAYAAABtdNT8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACF+UlEQVR4nO3dd1hT1+MG8DdhCKgMEQcKioo4cYC4957FvffWaqutVWurrauOurVutO69Vx1VFLdg3eLEBSoioGxC8vuDH/dL6ihgwrlJ3s/z5OHeBOHVFng599xzFBqNRgMiIiIi+k9K0QGIiIiIDAWLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGmYsOQESmQ6PRICoqCq9evcKrV68QERGB9+/fS4+YmBioVCqoVCqkpKRApVLB3NwcFhYWsLS0hKWlJaytrWFvbw87OzvY2dkhT548cHZ2RoECBWBuzm9pRKRf/C5DRDr1/v173L17F3fu3MGjR48QEhIiPUJDQ5GcnKyXz6tQKJA/f34UKlQIhQoVQuHChVGyZEmUKlUKHh4ecHV1hVLJQXYi+jIKjUajER2CiAyPRqPBkydPcOXKFQQGBuLq1au4desWnj9/LjraR1lZWUlFqnLlyvDy8oKXlxccHBxERyMiA8LiREQZkpSUhMDAQJw5cwZnzpzB+fPnERERkeE/7+joiMKFCyN//vzIly8f8ufPj7x588LW1ha5c+dG7ty5kStXLlhaWsLMzAzm5uYwMzNDSkoKkpKSkJycjMTERMTFxSE6OhpRUVGIjo5GeHg4QkND8eLFC4SGhuLly5dQq9UZzlWsWDF4e3vD29sbtWrVgre3NywsLLLyT0REJoDFiYg+SqPR4Pbt2zhy5Aj++usvBAQEID4+/rN/xt7eHmXKlEHp0qVRpkwZlChRAm5ubihSpAhsbW2zJbdKpcKrV68QEhKC4OBg6XH37l08fPgQKpXqs3/exsYG1atXR926dVG3bl34+PjAysoqW7ITkfyxOBGRJCkpCSdPnsSuXbtw8OBBvHjx4pPv6+joCB8fH3h5ecHb2xteXl4oVKgQFApFNibOnOTkZNy7dw+BgYFalxg/VwitrKxQr149NG/eHC1atECJEiWyMTERyQ2LE5GJS0pKwuHDh7F9+3YcOHAA0dHRH32/woULo27duqhTpw5q166NUqVKybokZZRKpcLdu3dx/vx5+Pv7w9/f/7PztEqUKIEWLVqgRYsWqF+/PiwtLbMxLRGJxuJEZII0Gg0CAwOxbt06bN68GW/evPngfaysrFC3bl00bdoUTZs2RenSpY2iKP0XjUaDx48fSyXq+PHjnxx5s7e3R5s2bdChQwc0btyYl/SITACLE5EJCQsLw7p167Bu3Trcvn37g9ft7OzQunVrtG3bFk2bNkXOnDkFpJQXjUaDGzdu4PDhwzh06BDOnj2LlJSUD94vd+7caNWqFTp27IgWLVogR44cAtISkb6xOBGZgEuXLmHhwoXYtm3bB+soWVlZwdfXFz179kSjRo146ek/REVF4fjx49izZw/27duH9+/ff/A+Dg4O6NSpE3r27IkaNWqYxEgdkalgcSIyUklJSdixYwcWLlyIixcvfvB6rVq10Lt3b3Ts2BF2dnYCEhq+xMREHD9+HDt27MDevXsRGRn5wfu4ubmhR48e6NWrFyeWExkBFiciIxMTE4Nly5Zh7ty5CAsL03rN0dERAwcOxIABA1C8eHFBCY1TcnIyTpw4gY0bN2LXrl2Ii4v74H0aNGiAgQMHom3btryUR2SgWJyIjMS7d++wZMkSzJ0794PJ3p6envjmm2/QtWtXWFtbC0poOmJiYrB7926sX78eJ06c+GBBTkdHR/Tp0wcDBw6Eh4eHoJRElBUsTkQGLioqCosWLcK8efO0LhUpFAr4+vri22+/Re3atTnPRpDQ0FBs2LABK1euxIMHDz54vUGDBvjmm2/QsmVLmJmZCUhIRJnB4kRkoBITE7F48WJMmzZNqzAplUp07doVEyZMQOnSpQUmpPQ0Gg1OnTqFlStXYufOnUhKStJ6vVixYhgxYgT69euXbausE1HmsTgRGRi1Wo2tW7fixx9/REhIiPS8mZkZevTogR9//BElS5YUF5D+05s3b7Bu3TosXbr0g1GoXLlyoV+/fhgxYgQnkxPJEIsTkQHx9/fH999/jytXrkjPKRQK9OrVCxMnTkSxYsUEpqPMUqvVOHz4MBYsWIBjx45pvaZQKNCqVSuMGzcONWrUEJSQiP6NxYnIAISGhmLUqFHYtm2b1vONGzfG7NmzUaFCBUHJSFdu376NhQsXYt26dR/snVe3bl2MHz8eTZo04Vw1IsFYnIhkTKVSYfHixZg4caLWQouenp6YPXs2mjRpIjAd6cPbt2+xatUqLF68GM+ePdN6rXLlyhg/fjzatm3LieREgrA4EcnU+fPnMXToUFy7dk16Lm/evJg5cyZ69+7NH5xGLikpCZs2bcKMGTMQHBys9ZqHhwfGjRuH7t27w8LCQlBCItPE4kQkMzExMfjhhx+wdOlS6TmFQoFBgwZh+vTpyJMnj8B0lN1SUlKwZ88eTJ8+HUFBQVqvlShRAr/++iu6dOkCpVIpKCGRaWFxIpIRf39/9O3bF48fP5aeq1ixIpYuXYpq1aoJTEaiaTQaHDt2DNOnT4e/v7/Wa+XKlcOUKVPw1VdfcQ4UkZ7xVxQiGYiLi8M333yDevXqSaXJxsYG8+fPx+XLl1maCAqFAk2aNMGpU6cQEBCAevXqSa/dvHkTbdu2RdWqVXH06FHw92Ei/eGIE5Fg586dQ+/evbXW86lduzbWrFnD/eTokzQaDf7++29MmDDhg02c69Spg1mzZqFq1aqC0hEZL444EQmSkpKCadOmoU6dOlJpsrKywrx583Dq1CmWJvoshUKBhg0b4vz589i3bx88PT2l106fPo1q1aqhW7duePLkicCURMaHI05EAoSFhaFnz544ceKE9Fy1atXw559/ctVvyhK1Wo3t27dj4sSJuHfvnvR8jhw5MGrUKIwfP55buRDpAEeciLLZkSNHUKFCBak0KZVKTJo0CWfOnGFpoixTKpXo3Lkzbt68iSVLliBv3rwAUvc0nDFjBkqUKIGVK1dCrVYLTkpk2DjiRJRNVCoVfv75Z8yYMUN6ztnZGRs3btSa6EukC9HR0Zg+fTrmz5+vtaGwj48PlixZAm9vb4HpiAwXixNRNoiIiECXLl1w/Phx6bmWLVti7dq10sgAkT48fvwY48aN09quJ21dsGnTpsHR0VFgOiLDw+JEpGfXrl1D27ZtpWUGzM3NMWvWLHz77bdcc4eyzalTp/D111/j1q1b0nN58uTBzJkz0b9/f/6/SJRBLE5EerRlyxb069dP2rQ1X7582L59O+rUqSM4GZmi5ORkLFq0CL/88ovW3of16tXDihUr4O7uLjAdkWHg5HAiPVCr1Rg/fjy6du0qlaYqVargypUrLE0kjIWFBUaPHo27d++iW7du0vOnTp1C+fLlMWPGDCQnJwtMSCR/HHEi0rH4+Hj07t0b27dvl57r06cPli5dCisrK4HJiLQdO3YMgwYNQkhIiPRchQoVsGrVKk4eJ/oEjjgR6VB4eDgaNmwolSalUomFCxfCz8+PpYlkp3Hjxrh58ya+++47aZPga9euoVq1apg0aRJHn4g+giNORDoSHByMFi1a4NGjRwCAnDlzYuvWrWjZsqXgZET/7cqVK+jfvz+uX78uPVe5cmWsW7cOZcuWFZiMSF444kSkA2fPnkX16tWl0uTs7IwzZ86wNJHB8Pb2xpUrV/DLL7/AzMwMABAUFAQvLy/MmTMHKSkpghMSyQNHnIi+0OHDh9G+fXtpErinpycOHjyIwoULC05GlDVXrlxBr169cOfOHem5unXrYsOGDfz/mkweR5yIvsCWLVvQpk0bqTQ1btwYZ86c4Q8XMmje3t4IDAzE6NGjpfWd/P39UbFiRezfv19wOiKxWJyIsmjZsmXo1q0bVCoVAKBjx444cOAAN1Ilo2BtbY05c+bg5MmT0i8CERERaNOmDb799lskJiYKTkgkBosTURb89ttvGDp0KNKudA8cOBCbN2+GpaWl4GREulW3bl1cu3YNvr6+0nMLFixA9erVcf/+fXHBiARhcSLKpMmTJ+PHH3+UzseOHYvly5dLE2qJjE2ePHmwa9cuLF68GDly5AAAXL16Fd7e3ti7d6/gdETZi8WJKBMmT56MSZMmSeczZszAjBkzuM8XGT2FQoHhw4fj4sWLKFWqFADg3bt38PX1xYQJE3jXHZkM3lVHlEH/Lk1z5szB6NGjBSYiEiMmJgb9+/fHtm3bpOcaN26MTZs2IW/evAKTEekfR5yIMoClieh/cuXKhS1btmDu3LnSJepjx47B29sb//zzj9hwRHrGESei/zBjxgyMHz9eOmdpIvoff39/dOrUCa9fvwaQumL+pk2b0KZNG8HJiPSDI05En7F8+XKWJqLPqFu3LoKCglC1alUAQGxsLHx9fTF79mzw93IyRhxxIvqELVu2oFu3btI3/99++w3jxo0TnIpInhISEtCvXz9s3rxZeq5fv35YunQpl+kgo8LiRPQRhw4dwldffSUtbvnDDz9g5syZglMRyZtGo8GUKVO05gPWrVsXe/bsgb29vbhgRDrE4kT0LwEBAWjSpIm0jcqAAQOwYsUKLjlAlEFbt25Fnz59kJCQAAAoX748jhw5AmdnZ8HJiL4cixNROsHBwahevToiIyMBpG6jsnnzZi5uSZRJFy9eRKtWrfDmzRsAQJEiRfDXX3/Bw8NDcDKiL8PiRPT/wsPDUa1aNTx69AhA6ro0Bw4c4PwMoiy6d+8emjZtipCQEACAo6MjDh48KE0kJzJEvKuOCKkTW319faXS5OnpiR07drA0EX2BkiVL4ty5c6hQoQKA1E2CGzRogGPHjglORpR1LE5k8tRqNfr06YNz584BAAoWLIgDBw7A1tZWcDIiw1ewYEH4+/ujXr16AIC4uDi0bt0ahw4dEhuMKItYnMjkTZw4EVu3bgWQunjfgQMH4OLiIjgVkfGws7PDkSNH0LZtWwBAYmIifH19uUEwGSTOcSKTtnPnTnTo0AEAoFQqsXfvXrRq1UpwKiLjlJycjB49ekh73Jmbm2PTpk3o2LGj4GREGccRJzJZt2/fRp8+faTz33//naWJSI8sLCywceNG9OjRAwCgUqnQpUsXrUUzieSOI05kkqKjo+Hj44N79+4BALp3747169dzrSaibJCSkoKBAwdizZo1AAAzMzPs2LEDvr6+YoMRZQCLE5kctVqNtm3bYt++fQCAChUq4Ny5c7CxsRGcjMh0qNVqDBkyBCtXrgQAWFpaYv/+/WjSpIngZESfx0t1ZHKmT58ulSYHBwfs2rWLpYkomymVSixbtky6bJeUlARfX1+cOXNGcDKiz+OIE5mUgIAA1K1bF2q1GgqFAocOHUKzZs1ExyIyWSqVCp06dcLu3bsBALlz58aJEydQpUoVwcmIPo4jTmQyIiMj0b17d6jVagDAL7/8wtJEJJi5uTk2b94sfS2+f/8eLVq0wIMHDwQnI/o4jjiRSdBoNOjcuTO2b98OAKhduzZOnjzJPeiIZCIuLg7NmzfH6dOnAQDFixfH+fPn4eTkJDgZkTYWJzIJfn5+6N+/PwDA3t4e165dg6urq+BURJReVFQUatWqhVu3bgEAqlatir///ptzEElWeKmOjN69e/cwYsQI6XzVqlUsTUQyZG9vj8OHD8PZ2RkAcPHiRXTr1g0pKSmCkxH9D4sTGbWUlBT06dMHcXFxAICBAweiffv2glMR0ae4uLjg0KFDyJ07NwBg7969GD16tOBURP/D4kRGbfHixTh//jwAoESJEpg3b57gRET0XypUqICdO3fC3NwcALBw4UJpsUwi0TjHiYzWo0ePUL58eWm0yd/fH3Xq1BGciogyatWqVRg4cCCA1AUy/f39Ua1aNcGpyNRxxImMkkajwcCBA6XSNHz4cJYmIgMzYMAADBs2DEDqApnt2rVDaGio4FRk6jjiREZp5cqVGDRoEADA1dUVN2/elOZMEJHhSE5ORqNGjaRlCqpWrYpTp07ByspKcDIyVSxOZHRev36NkiVLIjo6GgDw119/cf8rIgMWHh4Ob29vPH36FAAwZMgQLF26VHAqMlW8VEdGZ8KECVJp6tWrF0sTkYFzcnLCnj17pFGmZcuWSYvZEmU3jjiRUQkMDESVKlWg0Whga2uLe/fuIX/+/KJjEZEOpJ8sbmtri6tXr6JYsWKCU5Gp4YgTGQ2NRoORI0ci7XeBSZMmsTQRGZH+/fuja9euAIB3796hc+fOSExMFJyKTA1HnMhobNy4ET169AAAeHh44Pr167C0tBScioh06f3796hcubK0CfA333yD+fPniw1FJoXFiYxCbGwsSpYsKd2qfPjwYWm3dSIyLlevXkW1atWQlJQEADh27BgaNWokOBWZCl6qI6OwYMECqTS1bt2apYnIiFWqVAmzZ8+Wzvv16yfdEEKkbxxxIoP39u1bFCtWDNHR0VAqlbh16xZKlSolOhYR6ZFarUbjxo3x999/A0gtT6tXrxacikwBR5zI4M2ePVv6bbNPnz4sTUQmQKlUws/PT1rY1s/PDwcOHBCcikwBR5zIoL169Qpubm6Ij4+HpaUl7t+/D1dXV9GxiCibpF+ioECBArh16xby5MkjOBUZM444kUGbN28e4uPjAQBDhw5laSIyMf3790fz5s0BAC9fvsR3330nOBEZO444kcF6+/YtihQpgpiYGFhaWuLx48dwdnYWHYuIstmLFy9QtmxZ6ZK9v78/N/UmveGIExmsRYsWISYmBgDQt29fliYiE1WoUCFMnz5dOh8yZIi0VAGRrnHEiQxSXFwcXFxc8PbtW5iZmeH+/ftwc3MTHYuIBElJSUH16tVx+fJlAMD06dMxfvx4wanIGHHEiQzShg0b8PbtWwBAly5dWJqITJyZmRmWL18OpTL1x9rUqVOltd2IdInFiQyORqPBggULpPNRo0YJTENEclGpUiUMGzYMQOqo9I8//ig4ERkjXqojg3Ps2DE0adIEAFCzZk0EBAQITkREchEREYESJUogKioKAHDlyhV4eXmJDUVGhSNOZHD++OMP6fjbb78VF4SIZMfR0RGTJk2SzkePHg2OD5AuccSJDMrLly9RuHBhpKSkoGDBgnj69CnMzc1FxyIiGUlKSkL58uVx7949ANz0m3SLI05kUP7880+kpKQASF2CgKWJiP7N0tISU6dOlc5/+uknjjqRznDEiQyGRqOBh4cH7t+/DwB48OABihcvLjgVEcmRWq2Gl5cX/vnnHwDArl270LZtW7GhyChwxIkMxsWLF6XS1KBBA5YmIvokpVKpNeo0ceJEqNVqgYnIWLA4kcHYtm2bdNyjRw+BSYjIELRo0QLVq1cHANy8eRMHDx4UnIiMAS/VkUFQq9UoUqQInj9/DgsLC7x69QoODg6iYxGRzO3fvx9t2rQBwOVLSDc44kQG4eLFi3j+/DkAoHHjxixNRJQhLVu2RJkyZQAAZ8+exdmzZwUnIkPH4kQGIf1luk6dOglMQkSGRKlU4ocffpDOZ8+eLTANGQNeqiPZ02g0cHFxwYsXL2BhYYHXr1/D3t5edCwiMhBJSUkoVqwYXrx4AaVSicePH8PV1VV0LDJQHHEi2btx4wZevHgBAGjYsCFLExFliqWlJQYNGgQgdb7kihUrBCciQ8biRLJ39OhR6bh58+YCkxCRoRowYADMzMwAAKtWrUJSUpLgRGSoWJxI9o4dOyYdp23uS0SUGc7OzvD19QUAvHr1Cnv37hUbiAwWixPJWnx8PE6fPg0AcHFxgYeHh+BERGSohgwZIh1v2LBBYBIyZCxOJGsBAQFISEgAkDrapFAoBCciIkNVv359FCxYEEDqxr9v374VnIgMEYsTydqJEyekY16mI6IvYWZmhq5duwIAkpOTsX37dsGJyBCxOJGsnT9/XjquU6eOwCREZAy6d+8uHW/atElgEjJUXMeJZEulUsHOzg5xcXEoUqQIQkJCREciIgOn0WhQqlQp3Lt3D0qlEq9fv4ajo6PoWGRAOOJEsnXr1i3ExcUBAKpWrSo4DREZA4VCIe1dp1arceTIEcGJyNCwOJFsXbhwQTquVq2awCREZExatWolHR84cEBgEjJELE4kWxcvXpSOOeJERLpSo0YNaQeCI0eOQKVSiQ1EBoXFiWQrKCgIQOqdMJUqVRKchoiMhYWFBZo2bQoAiIqKwtWrVwUnIkPC4kSylJKSguDgYABAiRIlYG1tLTgRERmTunXrSsdnzpwRmIQMDYsTyVJISIi08GWZMmUEpyEiY1OrVi3pOCAgQGASMjQsTiRLd+7ckY5Lly4tMAkRGaOyZctK85wCAgLAlXkoo1icSJZYnIhIn5RKJWrUqAEACA8Px+PHjwUnIkPB4kSyxOJERPqW/qaTGzduCExChoTFiWTp0aNH0nHJkiUFJiEiY1W+fHnpmMWJMorFiWTpxYsXAAA7Ozvkzp1bcBoiMkYsTpQVLE4kOxqNBs+fPwcAFC5cWHAaIjJWJUuWhKWlJYDULZ6IMoLFiWQnMjJSWoqgUKFCgtMQkbEyNzdHkSJFAABPnz4VnIYMBYsTyU7aaBPAESci0i8XFxcAwPv37xEdHS04DRkCFieSnbT5TQCLExHpV1pxAoBnz54JTEKGgsWJZCciIkI6dnJyEpiEiIxd+l/OWJwoI1icSHbSD5fb2dkJTEJExi5fvnzScWRkpMAkZChYnEh20hcnW1tbgUmIyNil/x7z7t07gUnIULA4kexwxImIsguLE2UWixPJTvpvXixORKRPLE6UWSxOJDvpv3lx1XAi0icrKyvpOG39OKLPYXEi2UlKSpKOc+TIITAJERk7hUIhOgIZGBYnkh21Wi0dK5X8X5SIiOSDP5VIdlJSUqRjMzMzgUmIiIi0sTiR7KQvThxxIiJ94vcbyiz+X0Kyk/5SHUeciEif3r9/Lx3nypVLYBIyFCxOJDsajUZ0BCIyETExMdIx7+KljGBxItlJfyddYmKiwCREZOw44kSZxeJEsmNjYyMdx8XFCUxCRMaOWzxRZrE4keykL07x8fECkxCRsXv16pV0nD9/foFJyFCwOJHsWFtbS8cccSIifQoLC5OOCxQoIDAJGQoWJ5IdjjgRUXZ5+fKldFywYEGBSchQsDiR7OTMmVM6Tj9xk4hI10JDQwGk7lnHOU6UESxOJDt58+aVjt+8eSMwCREZM7VajcePHwMAihYtyn3rKENYnEh2nJycpOPXr18LTEJExiwsLEyaDlCiRAnBachQsDiR7OTLl086Dg8PF5iEiIzZgwcPpGMWJ8ooFieSnfQjTixORKQvLE6UFSxOJDssTkSUHW7evCkde3h4CExChoTFiWQnT548MDc3B/C/O16IiHTt2rVr0nGFChUEJiFDwuJEsqNUKuHq6goACAkJERuGiIySRqPB9evXAaQufJl+pJvoc1icSJbc3NwApO4jFRkZKTgNERmb0NBQREREAAA8PT0FpyFDwuJEslS0aFHpmKNORKRrly5dko4rVaokMAkZGhYnkqW0EScA0gJ1RES6cu7cOem4Ro0aApOQoWFxIllKP+LE4kREunb27FnpuHr16gKTkKFhcSJZSr+mSnBwsMAkRGRsEhISEBgYCABwd3fnxHDKFBYnkqUyZcpIx+nXWiEi+lJBQUFISkoCwMt0lHksTiRLuXPnRpEiRQAAt27dgkajEZyIiIwF5zfRl2BxItkqW7YsAODdu3d4/vy54DREZCz+/vtv6bhmzZoCk5AhYnEi2SpXrpx0zMt1RKQLCQkJOHXqFADA2dlZa1oAUUawOJFspS9ON27cEJiEiIxFQEAA4uPjAQBNmjSBQqEQnIgMDYsTyVbFihWl48uXL4sLQkRG46+//pKOmzZtKjAJGSqFhrNuSaZSUlJgZ2eH2NhYuLq64smTJ6IjEZGB8/T0xI0bN6BQKBAeHg5HR0fRkcjAcMSJZMvMzAze3t4AgKdPn+Lly5eCExGRIXvx4oV02b9KlSosTZQlLE4ka1WrVpWO0+8tRUSUWQcPHpSOeZmOsorFiWTNx8dHOmZxIqIvsXPnTun4q6++EpiEDBmLE8la+hGn9IvWERFlRmRkpLR+U5EiRVC5cmXBichQsTiRrBUuXFja8PfcuXNISEgQG4iIDNL+/fuhUqkAAO3ateMyBJRlLE4ke/Xr1wcAJCYm4sKFC4LTEJEh2rVrl3Tcvn17gUnI0LE4kew1aNBAOk6/VQIRUUbExMRI6zcVKFAA1atXF5yIDBmLE8le2ogTAJw8eVJgEiIyRLt375Yu87dt2xZKJX/0Udbx/x6SvUKFCqFkyZIAgAsXLiA2NlZwIiIyJOvXr5eOu3XrJjAJGQMWJzIIaZfrVCoVR52IKMNCQ0Nx4sQJAICbmxtq1qwpOBEZOhYnMggtWrSQjg8cOCAwCREZkk2bNkGtVgMAevTowbvp6ItxrzoyCHFxcXB0dERCQgIKFSqEZ8+e8RsgEf2nChUq4Pr16wCAe/fuwd3dXXAiMnQccSKDYGNjI12ue/HiBa5duyY4ERHJ3bVr16TSVK1aNZYm0gkWJzIYrVq1ko73798vMAkRGYIVK1ZIx7169RKYhIwJL9WRwXj69CmKFCkCAPD29sbly5cFJyIiuYqJiYGzszPev3+PnDlzIjQ0FLa2tqJjkRHgiBMZDFdXV1SsWBEAcOXKFTx+/FhsICKSrc2bN+P9+/cAUpcgYGkiXWFxIoPSsWNH6Xjbtm0CkxCRXGk0GixdulQ6Hzx4sMA0ZGxYnMigdO7cWTreunWrwCREJFdXrlzB1atXAQBVqlSBl5eX4ERkTFicyKAUL15c+iZ49epV3L9/X3AiIpKbRYsWScdDhgwRmISMEYsTGRyOOhHRpzx//hybN28GADg4OGh9vyDSBRYnMjidOnWSjjdu3AjeGEpEaRYtWgSVSgUAGDZsGHLmzCk4ERkbLkdABqlOnTo4c+YMAOD8+fOoVq2a4EREJNr79+/h4uKC6OhoWFpa4smTJyhQoIDoWGRkOOJEBqlfv37SsZ+fn8AkRCQXfn5+iI6OBgB0796dpYn0giNOZJBiYmJQsGBBxMTEIHfu3AgLC+OQPJEJU6lUcHd3R0hICADg5s2bKFu2rNhQZJQ44kQGKVeuXNKkz/fv32PXrl2CExGRSBs2bJBKU7NmzViaSG844kQG6+zZs6hVqxaA1DlP/v7+ghMRkQgqlQqlSpXCw4cPAQBnzpyRvjcQ6RpHnMhg1ahRAx4eHgCA06dP4+bNm4ITEZEImzZtkkpTgwYNWJpIr1icyGApFAoMGzZMOl+8eLHANEQkgkqlwtSpU6XzSZMmCUxDpoCX6sigvXv3DoUKFUJMTAxsbGzw/PlzODg4iI5FRNlk/fr16NWrFwCgfv36+PvvvwUnImPHEScyaLa2tujduzcAIC4uDmvWrBGciIiyS1JSEn799VfpnKNNlB1YnMjgff3119LxkiVLkJKSIjANEWWXFStWSHOb6tevj7p16wpORKaAl+rIKDRp0gTHjh0DAOzevRu+vr5iAxGRXr179w7FixfHmzdvAACXL1+Gt7e34FRkCjjiREZh1KhR0vFvv/3G/euIjNysWbOk0tS1a1eWJso2HHEio6DRaFCxYkVcv34dAHDy5EnUq1dPbCgi0osXL17A3d0d8fHxsLCwQHBwMNzc3ETHIhPBEScyCgqFAuPGjZPOZ8yYITANEenTTz/9hPj4eADA8OHDWZooW3HEiYyGSqVCyZIl8fjxYwBAUFAQKlWqJDgVEenS+fPnUaNGDQCAnZ0dHj58CEdHR8GpyJRwxImMhrm5OcaMGSOdT58+XWAaItK1lJQUrbtoJ0+ezNJE2Y4jTmRU4uPj4ebmhlevXgEArl69iooVK4oNRUQ6sXTpUmm3AE9PTwQGBsLc3FxwKjI1HHEio2JtbY0ff/xROp84caLANESkK2/evMGECROk8yVLlrA0kRAsTmR0Bg0ahMKFCwMA9u/fj0uXLglORERfaty4cYiMjAQA9OzZkxv5kjAsTmR0rKys8NNPP0nnP//8s8A0RPSlTpw4gdWrVwNI3WZp1qxZghORKeMcJzJKSUlJ8PDwQEhICADA398fderUERuKiDItNjYW5cuXl+6WXbJkiTTPiUgEjjiRUbK0tNTa8PO7776DWq0WmIiIsmLChAlSaapTpw6GDBkiOBGZOo44kdFKSUlBpUqVcOPGDQDAhg0b0L17d8GpiCijzp49i9q1a0Oj0cDKygrXr1+Hu7u76Fhk4jjiREbLzMwMc+bMkc7Hjx8vrTZMRPIWHx+PAQMGSPtOTp06laWJZIHFiYxa48aN0aJFCwDAs2fPMG/ePMGJiCgjxowZg7t37wIAfHx88O2334oNRPT/eKmOjN7t27fh6emJlJQU5MqVC/fu3UPBggVFxyKiTzhw4ABat24NIPUu2cDAQJQpU0ZwKqJUHHEio1emTBkMGjQIABATE4PRo0cLTkREn/Ly5Uv069dPOp8zZw5LE8kKR5zIJLx58walSpVCREQEAOCvv/5CkyZNBKciovTUajVatmyJI0eOAABat26NvXv3QqFQCE5G9D8ccSKTkDdvXvz+++/S+dChQzlRnEhmFi5cKJWmAgUKYPXq1SxNJDssTmQyevfujbp16wIAHj16hGnTpglORERpzp49izFjxkjnf/75J5ycnAQmIvo4Xqojk3L37l14enoiOTkZFhYWuHr1KsqWLSs6FpFJe/nyJby8vBAaGgoA+OGHHzBz5kzBqYg+jiNOZFJKlSqFsWPHAgCSk5PRq1cvJCUlCU5FZLpUKhW6dOkilab69etzNJhkjcWJTM6ECRNQunRpAEBQUBCmTJkiOBGR6Ro/fjz8/f0BAM7Ozti8eTPMzc0FpyL6NF6qI5MUFBSEqlWrQqVSQalU4uzZs6hWrZroWEQmZevWrejSpQsAwNzcHP7+/qhRo4bgVESfxxEnMkmVK1eWNgFWq9Xo2bMnYmNjBaciMh0XLlxA7969pfO5c+eyNJFB4IgTmSyVSoXatWvjwoULAIDBgwdj2bJlglMRGb+QkBBUrVoVr1+/BgD07duXSw+QwWBxIpN2//59VKxYEXFxcQCAjRs3olu3boJTERmv6Oho1KxZE7du3QIA1KtXD3/99RcsLS0FJyPKGF6qI5Pm7u6OhQsXSueDBg3C7du3BSYiMl5pd9CllaaSJUti586dLE1kUFicyOT169cPffr0AQDExsaiQ4cOiImJERuKyMio1WoMHDhQWhk8T548OHDgAPLkySM4GVHmsDiRyVMoFFiyZAk8PT0BAHfu3MGgQYPAq9hEuqHRaDBmzBisXbsWAGBpaYldu3bB3d1dbDCiLGBxIgJgY2ODHTt2IHfu3ACAzZs3Y8GCBYJTERmH3377DXPnzgUAKJVKbNq0Sdr+iMjQcHI4UTq7du1C+/btAaR+g9+7dy9atWolOBWR4Vq6dCmGDRsmna9cuRIDBgwQmIjoy3DEiSiddu3aYcKECQBS52R06dIF165dE5yKyDBt2LABw4cPl85nzpzJ0kQGjyNORP+iVqvRtWtXbNu2DQBQuHBhXLx4Ec7OzoKTERmOP//8E3379pXmCo4dOxYzZswQnIroy7E4EX1EfHw86tevj4sXLwJIXWn89OnTyJkzp+BkRPLn5+eHAQMGSKVp2LBhWLx4MRe4JKPAS3VEH2FtbY29e/eiSJEiAFL3tmvbti0SExMFJyOSt5UrV6J///5SaRo5ciRLExkVFieiT8ifPz8OHjwIW1tbAMCxY8fQpUsXqFQqwcmI5OmPP/7AoEGDpPNRo0Zh/vz5wkrTtWvXMG/ePERHRwv5/GScWJyIPqNs2bI4dOgQbGxsAAB79uxB3759oVarBScjkg+NRoNJkyZpTQT//vvvMWfOHGGlKTg4GDVq1MDo0aPx/fffC8lAxonFieg/1KxZE3v27JG2hUi7U4jTA4lSt1EZPHgwJk+eLD03fvx4zJo1S1hpSkpKQvfu3aU9KF++fCkkBxknFieiDGjcuDG2bdsGMzMzAMCyZcvw7bffsjyRSYuPj0f79u2xcuVK6bl58+Zh+vTpQuc0TZo0CYGBgdJ52uV2Il1gcSLKoK+++grr1q2TfiAsXLgQQ4cO5WU7Mklv3rxB48aNsW/fPgCAhYUFNm/ejG+//VZoLn9/f8ycOVPrORYn0iUWJ6JM6NatG/z8/KTytHz5cvTt25cTxsmk3LhxA1WqVMHZs2cBALly5cKhQ4fQpUsXobkiIyPRs2fPD0aC07ZSItIFFieiTOrTpw82btwoXbZbt24dOnbsiPj4eMHJiPRvz549qF69OkJCQgCk3n3q7++PRo0aCc2l0WgwZMgQPHv2DID2KBNHnEiXWJyIsqBr167Yvn07LCwsAKT+MGnUqBHevn0rOBmRfmg0GkydOhVt27ZFbGwsAMDLywtXrlxB5cqVBacD1q9fL6327+DggB9//FF6jcWJdInFiSiL2rZti0OHDiFXrlwAgHPnzqFmzZp4/Pix4GREuvXu3Tt06tQJP//8s/Rc165dcebMGRQuXFhgslSPHz/WWgph+fLlsLOzk855qY50icWJ6As0atQIp0+fRoECBQAAd+/ehY+PD06fPi04GZFuBAUFoXLlytixYwcAQKFQ4LfffsPGjRthbW0tOF3q3pJ9+/ZFTEwMAKBv374fXDpPW4eNSBdYnIi+UKVKlXDu3Dl4eHgASL3bqFGjRli1apXgZERZp9FosHjxYlSvXh0PHz4EANjZ2WHv3r0YN26cbLZQWbJkCfz9/QEARYoUwYIFCwCkruWUJm0NNiJdYHEi0gE3NzdcuHABTZo0AQAkJydj4MCBGDp0KBISEgSnI8qcqKgodOjQASNGjJAKSJUqVXD16lW0bt1acLr/efDgAcaOHSud+/n5SZfl0henHDlyZHs2Ml4sTkQ6Ym9vj4MHD+Kbb76Rnlu2bBlq1qyJR48eCUxGlHHHjx+Hp6cndu3aJT03atQoBAQEwM3NTWAybSkpKejTp490SW748OFo0KCB9Hr6Dbk54kS6xOJEpEPm5uaYP38+/Pz8YGVlBeB/c0R27twpOB3Rp8XExGDYsGFo3LixdEu/g4MD9u7di7lz58qufCxcuFBaR6pYsWKYMWOG1uu8VEf6wuJEpAd9+/bFhQsXUKJECQBAdHQ0OnTogL59++Ldu3eC0xFp8/f3h6enJ5YuXSo9V79+ffzzzz9o06aNwGQfFxwcrLXcwJo1a6S7W9PwUh3pC4sTkZ5UqFABgYGB6Nixo/Tc2rVrUaFCBZw5c0ZgMqJU0dHRGDFiBOrVqycto2FjY4PFixfj+PHjcHV1FZzwQ2q1Gv369ZPmDn7zzTeoU6fOB+/HESfSFxYnIj2ytbXF1q1btX4jDgkJQZ06dTBs2DCOPpEQGo0GmzdvRqlSpbB48WLp+dq1a+P69esYPnw4lEp5/nhYtmwZzp07BwAoUaIEpk+f/tH3S05Olo7Nzc2zJRuZBnl+ZRAZEYVCgT59+uDatWuoWbOm9PzSpUtRpkwZ7N27V2A6MjV37txBw4YN0a1bN7x8+RIAYG1tjblz5+LUqVMoXry44ISf9vz5c4wbN046X7FiRYbWaJLL0glkHFiciLJJsWLF4O/vj7lz50rf7F+8eAFfX1+0aNECd+/eFZyQjFl0dDTGjRuHChUq4OTJk9LzX331FW7fvo1Ro0bJdpQJSB0lGzZsGN6/fw8A6N+/P+rXr5/hP0ukK/L9KiEyQmZmZhg1ahRu3bqFpk2bSs8fPnwY5cuXx+jRoxEZGSkwIRmbpKQkLFiwAMWLF8fMmTOlS1hubm44cOAA9uzZg6JFi4oNmQE7duzA/v37AaRuLDx79uzPvn/6USYWJ9IlFiciAYoWLYrDhw9j8+bN0l5fKpUK8+bNQ7FixTB9+nRpCwmirFCr1diyZQtKlSqFb7/9FhEREQBSJ0r//PPPuHXrFlq2bCk4Zca8ffsWX3/9tXS+ePFiODg4fPbP8PIc6QuLE5EgCoUCXbp0QXBwMCZNmiSt+xQVFYUJEyagePHimD9/vrQTPVFGaDQaHDp0CD4+PujatavWptPdunXD3bt3MXnyZFnsM5dRY8aMwevXrwEAbdq0Qfv27TP15zniRLrE4kQkmI2NDX755RcEBwejb9++0jyT169fY9SoUXB1dcWkSZMQHh4uOCnJmVqtxs6dO+Hl5YWWLVsiMDBQeq1hw4YIDAzExo0bZbX6d0YEBATAz88PAJA7d24sWbIkQ6NJvFRH+sLiRCQTrq6u8PPzw+3bt9G5c2fp+bdv32Ly5MlwdXXFoEGDEBQUJDAlyY1KpcLGjRtRvnx5dOjQAVevXpVeq1ChAo4cOYJjx46hcuXKAlNmTXJyMoYOHSqdT58+Xbq0/V94qY70hcWJSGY8PDywZcsW3LhxAz179pTWoElISMDKlSvh5eWFqlWrws/Pj+tAmbCIiAjMnj0b7u7u6NGjB27fvi295uXlhd27dyMoKAhNmzY12BKxaNEi3Lx5EwBQuXJlrRKVGRxxIl1icSKSqXLlymHdunV4+PAhvv32W60tJS5duoT+/fsjf/786NixI3bv3i2tpEzG7Z9//sGAAQNQuHBh/PDDDwgJCZFeq1mzJg4fPozLly/D19dX1ssL/JcXL15g0qRJAFJHj5YuXQozM7MM/3lDLYskf4b7VUVkIlxdXTFv3jyEhoZi+fLlqFixovRaQkICduzYgXbt2sHJyQnt2rWDn5+ftLAhGYf3799j7dq1qFWrFipVqoTVq1drFeVmzZrh1KlTOHPmDJo1a2YUpWH06NHSnaWDBg2Cj49Ppv58+tKYkpKi02xk2hQajmESGRSNRoPLly9j3bp12LZt2ycnjVeoUAG1a9eGi4sLLCwsULFiRRQoUAAFChSAvb29UfxwNWYpKSk4fvw41q9fj127diE+Pl7rdVtbW/Tt2xfDhw+Hu7u7oJT6cfToUWmds7x58yI4OBh58uTJ1Mf47rvvMHfuXACpE8zTr9pP9CW4gQ+RgVEoFPDx8YGPjw/mz5+PEydOYMuWLThw4ADevHkjvd+1a9dw7dq1j34MS0tLqUSlPZydneHq6ooiRYrA1dUVhQsXlpZIoOyRkpKCCxcuYPfu3di0aRPCwsI+eJ8yZcpgxIgR6NGjh9blW2ORmJiotWbT7NmzM12aACBHjhxaH5NIV1iciAyYubk5mjZtiqZNmyIlJQWXL1/GwYMHcejQIVy9evWTk2KTkpLw9OlTPH369LMfP3/+/FplKu24aNGicHNzg52dnT7+WiYlPj4ex44dw969e7F///6PjiA6ODigS5cu6NmzJ6pVq2bUo4ULFizA/fv3AaTO2erVq1eWPg6LE+kLL9URGano6GicO3cO8+fPx9GjRwEAvXr1wsuXL6VHeHj4F91xZG9vL5WookWLfnCcO3duXf11jIZarcb169dx8uRJnDx5EidOnEBcXNwH72dhYYGWLVuiZ8+eaNmypVYRMFYvX76Eu7s7YmJioFQqERgYqDWnLzNmzJiB8ePHAwB2794NX19f3QUlk8YRJyIjZWdnh+bNm6N58+YAUn9g//suK5VKhfDwcISFheHFixd48uSJNBL19OlTPHnyBGFhYZ8sV1FRUfjnn3/wzz//fPR1R0fHjxYqNzc3FClSBDlz5tTp31mOEhMTcfPmTZw9exYnT56Ev7//J/cjtLGxQdOmTfHVV1+hVatWcHR0zOa0Yk2YMEGaED5w4MAslyZAe8SJd5ySLrE4EZmIj92abm5ujoIFC6JgwYKfXCAxKSkJL168kIrUkydPEBISgsePHyMkJARPnz795F1LERERiIiI0FrFOj0nJ6ePjla5ubnB1dXVoLYFAYC4uDjcvHkTgYGBCAoKQlBQEG7cuCFtrPsx+fLlQ+vWrfHVV1+hUaNGBvd31pXAwECsWbMGQGrpnzJlyhd9vPTz83ipjnSJxYmIPsvS0hJubm6f3KpDpVLhxYsXWmUq/fHz58+hVqs/+mfDw8MRHh6OS5cuffT1AgUKwNXVVZrAnj9//g+OnZyckCtXrmxZsyg+Ph4vXrzQejx+/Bj37t1DcHAwnj9//p8fI0+ePKhbty7q16+PevXqoWzZsga93pIuaDQafPPNN9LI5qRJk+Dk5PRFH5NznEhfWJyI6IuYm5ujSJEiKFKkCOrWrfvB68nJyXj27NkHhSrtODQ09JOXAtPmYv0XhUIBOzs76WFvby8d586dG5aWlh88lEolVCoVUlJSoFKppOP4+Hi8e/cO0dHR0tvo6Gi8efPmk5fYPkWpVKJUqVKoXLkyvL29Ua9ePZQvX97ki9K/bd26FWfPngWQunL+8OHDv/hjsjiRvrA4kd4lJiYiLi4OiYmJGX4kJydDo9FArVZLj/Tn/35NoVDAzMwM5ubmn31raWkJa2trWFlZffZtZlYops+zsLBAsWLFUKxYsY++npiYiGfPnn10tOrx48cZKk4ajQZRUVGIiorScfqMc3BwgIeHh1SUvLy8UKFCBZOYx/Ul4uLi8MMPP0jnc+fOhaWl5Rd/XM5xIn1hcaKP0mg0eP/+PSIjI6VHVFSUdPzu3TvExMRIj/fv32udp398bn6HXOXIkQO2trb/+bC3t0fevHnh6Oio9ZbrH2Vcjhw5UKJECZQoUeKjrycnJyM8PByvXr3Cy5cvP3j75s0baVQoKioK0dHROh1hUCqVsLW1hYODAwoVKvTBw8XFBSVLlkTevHl19jlNybx58/Ds2TMAQPPmzdGiRQudfNz0X4MsTqRLLE4mQK1WIzIyEq9fv5bmlISHh2udR0REaJWjqKioT85LMQWJiYnSv01W2NjYIG/evFKZyp8/PwoWLAhnZ2ettwULFuSIxH+wsLCAs7MznJ2dM/xnEhISpDKVVt6TkpK0HikpKTA3N9calTQ3N4elpaV0mc/W1ha5cuUy6nWTRAoPD8fMmTMBAGZmZpgzZ47OPnb6r6vY2FidfVwiFicDpVar8ebNG4SFhSE0NBShoaEICwuT1ub5dynKrr2aFAoFcuXK9cHDxsYGOXLk0HpYWVl98FzaI+2HmVKphEKhgFKplB4fO9doNNJclU+9ValUSEpKQkJCAuLj4z/5Nj4+HrGxsXj37p30UKlUmfp3iIuLy9ACk0Dq1hlpRcrFxUW6w6xo0aIoUqSItGUKZZyVlRWsrKyQP39+0VHoM6ZMmYL3798DAPr374/SpUvr7GOnX0Ms7XMQ6QKLk8xoNBpERkbi+fPnUhlKK0bpz8PCwjL9w/y/KJVK2Nvbw8HBQXqb9vj3ua2tLXLnzq1VjnLnzg1ra2uj++1co9EgISFBKlHv37+XJg1HRkbizZs3iIiI0HqbdpyR0pr2ce/evfvR15VKJQoVKiSt2F20aFHUrl0bDRs25FwsMlgPHz7EsmXLAKSO0P7yyy86/fgsTqQvLE7ZLD4+Hs+ePcOzZ8/w9OlT6W3644+tIpwVVlZWcHJyQr58+eDk5CQ9Pnbu6OiI3Llz826fj1AoFLC2toa1tXWmRzDUajWio6Px6tWrD4rvv4vxp/67q9Vq6f+ZgIAA6XlnZ2d0794dvXr1Qrly5b7o70iU3SZMmCDNf/zuu+9QsGBBnX58FifSF265omPR0dF4/Pix9AgJCdEqR+k3Yc2qfPnySfNk0s+ZcXZ2lta1yZcvH3LmzGl0oz/GSqPR4N27d1q37YeEhEiLTYaEhHz2/53KlSvjjz/+QNWqVbMxNVHWXL58GT4+PgBSF0F9+PChzrfnef/+PWxtbQEADRs2xPHjx3X68cl0sThlUmJiIp48eSIVo0ePHmkVpbdv32b5Y9vY2MDFxUXamb5QoUIfFKT8+fPr5FZdMjyxsbF48uQJbty4gc2bN+PgwYNal2vz5MmDR48eceNdkjWNRoMGDRrg1KlTAIDFixfrZN2mf1Or1dKlbB8fH1y8eFHnn4NME4vTR0RERODBgwe4f/8+Hj58qFWOXrx4kaVNUc3MzODs7AxXV1epHKU/dnFxQZ48eThCRBkWHh6OrVu34o8//sCdO3cAABMnTsSvv/4qOBnRpx05ckTaP7FEiRK4ffu23m5+yJ07N2JiYlC6dGncvn1bL5+DTI/JFqe3b9/i/v37uH//vlSS0o4zuzowkDqBt3DhwihWrJi0PUWxYsVQtGhRuLq6omDBgjA355Qy0r1Hjx7Bw8MDKpUKuXLlwrNnz2Bvby86FtEHNBoNfHx8cOXKFQCpK4Z36tRJb5/P2dkZYWFhKFy4sLRWFNGXMuqf5G/fvv2gFKW9zcoltbx580qFKK0cpZ27uLjwEhoJUaxYMfTu3RurV69GTEwMLly4gGbNmomORfSBffv2SaWpYsWK6NChg14/X+7cuREWFsbJ4aRTBl+cEhMT8eDBAwQHB2s97t27l+lypFAo4OLighIlSsDd3R3u7u4oXry4VJR0PXmRSFd8fHywevVqAMCTJ08EpyH6kFqtxs8//yydT548We938aZ9z37//j00Gg2nQpBOGFRxevHiBQ4ePIg7d+5IBSkkJCTTK1y7uLjA3d1dqyCVKFECxYoVg7W1tZ7SE+lP0aJFpeOQkBBhOYg+ZceOHbhx4waA1KLfqlUrvX/OtLvq1Go1YmNjkStXLr1/TjJ+si9OSUlJ2L9/P/z8/HDkyJEMl6RChQqhZMmSHxQkliMyRoULF5aOw8LCBCYh+lBKSorWApeTJ0/OltGfPHnySMeRkZEsTqQTsi5O69atw3fffffJ9Wty5cqFkiVLwsPDQ+tRsmRJ7v9FJiX9EgScz0Fys3nzZunOz5o1a6JJkybZ8nnTF6eIiAi4uLhky+cl4ybb4pSQkIDhw4cjJiZGes7V1RV9+vRBvXr14OHhgYIFC/KaNRH+d0kCSN3ChUguVCqV1hIZU6ZMybbv246OjtLxl6yxR5SebIuTv7+/VJqqVKmCadOmoWHDhtwShOgj0laJT1uBnEgutmzZggcPHgAA6tevj/r162fb504/4sTiRLoi2xZy8OBB6Xjs2LFo3LgxSxPRJyiVSukOIhYnkgu1Wo3ffvtNOp80aVK2fv5/X6oj0gVZNhGNRoMDBw4AACwsLNC4cWPBiYjkj8WJ5Gbfvn3Sit01a9ZEnTp1svXz81Id6YMsi9Pdu3fx+PFjAEDt2rW15m8Q0celfZ2wOJEcaDQaTJ8+XTr/8ccfs31OKkecSB9kWZyuXr0qHXO0iShj0opTTExMptc2I9K1EydO4PLlywCAChUqSPvTZSfOcSJ9kGVxio2NlY6dnJwEJiEyHOlHZtPfjUokgujRJoCX6kg/ZFmc4uLipGMbGxuBSYgMB5ckILk4f/48Tp48CQBwd3dH+/btheTgpTrSBxYnIiPB4kRyMWPGDOl43LhxMDMzE5IjR44c0mrhn1pImSizWJyIjASLE8nB/fv3sX//fgCpWwH16NFDaJ78+fMDAF69eiU0BxkPWRan+Ph46ZjFiShj0pYjAFicSJwFCxZAo9EAAEaMGAFLS0uhedKKU2RkJBITE4VmIeMgy+LEESeizOOIE4kWGRmJNWvWAEj93j1w4EDBiYACBQpIxxx1Il2QfXGytrYWmITIcLA4kWirVq2Svn/37dsXDg4OghP9b8QJYHEi3ZB9ceKIE1HGpC9O79+/F5iETJFKpcKiRYuk85EjRwpM8z/pR5xevnwpMAkZCxYnIiPBEScSaefOnXj27BkAoFWrVihZsqTgRKk44kS6xuJEZCRYnEikefPmScejRo0SmEQbR5xI12RfnKysrAQmITIcLE4kyuXLl3Hx4kUAgKenJ+rXry840f+wOJGuybo4WVtbQ6mUZUQi2eFyBCTKihUrpOMRI0YI2V7lU3ipjnRNlq0krTjxMh1RxnHEiUR49+4dNm/eDCC1vHfp0kVwIm3pixNHnEgXWJyIjARHnEiEjRs3Shuz9+jRQ9riRC6sra1hb28PAAgNDRUbhowCixORkciRIwdy5MgBgMsRUPbQaDRYvny5dD5o0CCBaT6tcOHCAIDnz59DrVYLTkOGjsWJyIikXa7jiBNlh8uXL+PatWsAAB8fH1SsWFFsoE9wcXEBACQlJSE8PFxwGjJ0sitOycnJSE5OBsDiRJRZLE6UndJPCh88eLDAJJ+XVpwASGtNEWWV7IoTN/glyrr0xSlto1UifUg/KdzW1hadO3cWnOjT0hen58+fC0xCxkB2xYmLXxJlXdoE8eTkZO4ET3q1fft26ft19+7dkTNnTsGJPi1tjhPAESf6cixOREaESxJQdlm/fr103LdvX4FJ/hsv1ZEusTgRGREWJ8oOISEh8Pf3BwB4eHjA29tbcKLPY3EiXWJxIjIi6YsTlyQgfdm4caN03KtXL1mtFP4x6S/VcY4TfSkWJyIjwhEn0jeNRqN1ma579+4C02SMjY0NHB0dAXDEib6crIuTtbW1wCREhofFifTtypUrCA4OBgDUrVsXRYoUEZwoY9JGnV68eIGUlBTBaciQya44cTkCoqwzhOKUnJyMxo0bw8XFBf369cPBgwd5B6AB2b59u3RsCKNNadzc3AAAKpUKL168EJyGDJnsihMv1RFlnSHsV/fgwQMcP34cz58/x5o1a9CqVSs4OTmhW7du2Llzp7TvGcmPRqORipOZmRnatm0rOFHGFStWTDp++PChwCRk6FiciIyIIYw4eXh4wMfHR+u59+/fY/PmzejQoQOcnJzQvn17bNy4EdHR0YJS0scEBQUhJCQEANCgQQPkzZtXbKBMSF+cHj16JDAJGTpZFyfOcSLKHEMoTkqlEmvWrIGlpeVHX4+Pj8euXbvQo0cP5MuXDy1btoSfnx/evHmTzUnp33bs2CEdd+jQQWCSzGNxIl2RXXFKP8eJxYkocwxlOYIyZcrg119/lc5LlCiBvXv3YtCgQciXL5/0fFJSEg4dOoT+/fujQIECaNiwIf744w+EhYWJiG3S0l+mUyqV8PX1FRsok1icSFdkV5wSEhKkYxYnoswxhBGnNN9//720cOKDBw9w7tw5LF++HKGhoTh16hRGjhyptf5OSkoK/v77bwwfPhyFChVCzZo1MXfuXOnSEenXzZs3pblB9erV0yq4hqBo0aLSelMsTvQlZFec0o84WVlZCUxCZHgMqTiZm5tjzZo1sLCwAADMmjULp0+fhpmZGerWrYsFCxbgyZMnuHDhAsaMGaM1YqDRaHDu3Dl89913cHNzg7e3N6ZPny7dJk+6d+DAAen4q6++Epgka3LkyCEVcU4Opy8hu+LEESeirDOk4gQA5cqVw+TJkwGklqGePXsiKipKel2pVKJq1aqYNWsWHjx4gH/++Qc///wzypQpo/VxAgMDMWHCBJQqVQrlypXDpEmTcP36dWg0muz86xi1gwcPSsetWrUSmCTr0sp3REQEbzygLJNdceIcJ6Ksy5kzp3Q5whCKEwCMGTMGderUAQA8ffoUw4cP/+j7KRQKVKhQAZMnT8atW7dw584dTJs2DZUrV9Z6v1u3bmHy5MmoUKECSpYsibFjx+LSpUssUV8gIiIC58+fBwCUKlVKa/TPkKTP/fjxY4FJyJDJujjxUh1R5igUCmktJ0MpTmZmZli/fj3s7OwAAJs2bdLaC+1TSpUqhR9//BGBgYF49OgR5syZgxo1ami9z4MHDzBr1ixUrVoVrq6uGDlyJE6ePAmVSqWXv4ux+uuvv6BWqwEALVu2FJwm67iWE+mC7IoTL9URfZm0y3WGUpwAwNXVFcuWLZPOhw0blqkRATc3N4wePRpnz57FixcvsHjxYjRo0ABK5f++xT1//hyLFi1CgwYNUKBAAfTr1w8HDhzQ+p5DH3fo0CHp2JCLU4kSJaTj+/fvC0xChkx2xYkjTkRfJq04yXk5go/p0qULevToASC19HXu3BlJSUmZ/jjOzs4YPnw4Tpw4gVevXmHVqlVo3ry51rpRERERWLNmDVq3bg0nJyd07twZW7ZsMaiymV00Gg2OHz8OIHVl+lq1aglOlHWlSpWSju/cuSMwCRky2RUnjjgRfZm04hQTE2Nwm5kuXrwYxYsXBwBcvnwZY8aM+aKPlzdvXvTv3x+HDh1CeHg4Nm/ejI4dOyJnzpzS+8TExGDbtm3o2rUrnJyc0LJlS6xatYprRf2/O3fu4NWrVwCA2rVrS3dBGqKSJUtKcwDv3r0rOA0ZKtkVJ444EX2Z9HfWxcTECEySeXZ2dti2bRty5MgBAFi4cKHWatVfwtbWFl26dMG2bdsQHh6Offv2oW/fvsiTJ4/0PmkLbg4cOBDOzs7w9vbGpEmTcOnSJWmOj6k5efKkdFy/fn2BSb6cjY0NihQpAiC1OPGGAcoK2RYnS0tLrfkJRJQxhrYkwb9VrlwZCxYskM779euHBw8e6PRzWFtbo3Xr1vDz88OrV6/w999/4+uvv0ahQoW03i8wMBCTJ09G1apVUbBgQfTt2xc7duwwyH/XrDKm4gT873Ldu3fvOKpIWSK7ZpJ2qY6X6YiyJu2uOsAwixMADBo0CN26dQOQOlerQ4cOWvtY6pK5uTnq16+PRYsW4enTp7h48SJ++uknVKpUSev9Xr9+jbVr16Jjx45wdHREgwYNMGvWLAQGBhrcJdGMUqvV8Pf3BwDY29ujYsWKYgPpQOnSpaVjXq6jrJBdcUobceJlOqKsMfQRJyB1WYXly5dLowPXrl3DwIED9X5pRalUwsfHB1OmTEFQUBCeP3+OFStW4KuvvtKaF6VSqXDy5EmMHTsW3t7eyJcvHzp27Ihly5bhwYMHRnMJ6M6dO9LmynXq1IGZmZngRF8u/QRxFifKCtkVJ444EX0ZYyhOAJArVy7s2LEDuXLlApC6vtOcOXOyNUOhQoUwcOBA7NmzBxEREfjrr78wYsSIDxaAfPv2LXbs2IGhQ4fC3d0dRYsWRd++fbF69WqDnktz6dIl6bhmzZoCk+hO+hEn3llHWSG74sQRJ6Ivk744GdqSBP9WtmxZrFu3TjofO3Ys/vrrLyFZcuTIgSZNmmDhwoV48OABgoODsWTJErRr1w729vZa7/v06VOsXbsWAwYMQOnSpeHk5IQ2bdpg5syZCAgIMJi1o9IXJx8fH4FJdIcjTvSlFBqZ/SpkaWmJ5ORkVKpUCUFBQaLjEBmcFStWYPDgwQCA1atXo1+/foITfblJkyZJe9rZ29vj8uXLWosZipaSkoKgoCAcP34cJ06cQEBAABITEz/5/paWlvD09ETlypWlR/ny5WX3C6OXlxeCgoKgUCgQHR2tNX/OUGk0GuTNmxdv375FoUKF8Pz5c9GRyMDIqjilpKTA3NwcAFCjRg2cPXtWcCIiw7NlyxZ07doVADBv3jx8++23YgPpgFqtRrt27bB3714AQJkyZXD27NkPRnrkIj4+HleuXMHZs2dx9uxZnDt3Dm/fvv3snzEzM0OZMmVQtmxZlClTBqVLl0bp0qXh7u6utXhndklISEDu3LmhUqlQpkwZ3Lp1K9sz6EudOnVw5swZAKmLoaZfkoLov5iLDpAe13Ai+nLGcFfdvymVSqxbtw7VqlXDnTt3cPv2bXTs2BGHDh2S5YKM1tbWqF27NmrXrg0gtfjdu3dPKlLnz59HcHCw1tynlJQU3LhxAzdu3ND6WGZmZihevDjc3NxQtGhRFC1aVDp2cXGBk5OTXv4N/vnnH2lPP2O5TJemQoUKUnG6fv066tWrJzYQGRRZFSeuGk705Yxlcvi/2draYv/+/ahWrRrevHmD48ePY+jQoVi5cqW0GrRcKZVKlCpVCqVKlUL//v0BpC5Oeu3aNQQFBUmPW7dufbC0QUpKCu7du4d79+598uPnyZMH+fPnR758+ZAvXz44OjoiV65cHzysrKygVCqhUCi0HhqNBvHx8YiPj0dcXBzi4uJw4cIF6eN7eXnp5x9GkAoVKkjH165dY3GiTJFVceKIE9GXM9biBADFixfHnj170LBhQyQmJmL16tVwd3fH2LFjRUfLtFy5cqFmzZpad6slJSXhwYMHuH37Nu7cuSONrt2/f/+z61i9ffsWb9++1dtdYumLhjHw9PSUjq9fvy4wCRkiWRUnjjgRfTljLk5A6m3xa9euleZxjRs3Dm5ubujUqZPgZF/O0tISZcqUQZkyZbSe12g0ePPmDUJCQqTH48ePERoailevXuH169d4/fq1XrbYKVasGKpUqaLzjytSuXLloFQqoVarce3aNdFxyMDIqjilH3FicSLKGmNajuBTunTpgkePHmHChAkAgJ49e8LJyckotgT5GIVCAScnJzg5OX22xMTFxeH169eIjIxETEzMB4+EhARoNBqo1WpoNBrpAaTu45b+YW1tjZw5c8LHx8forgDY2NjA3d0dwcHBuHnzJlQqlXRjEtF/kdX/KbxUR/TljHFy+MeMHz8eDx8+hJ+fH5KSkvDVV1/h1KlTqFy5suhowtjY2EgTyOnzKlSogODgYCQmJuL+/ftaC2MSfY6sFsDkpTqiL2dpaSn94mHMxUmhUGDZsmVo1aoVgNTRtWbNmuH+/fuCk5EhSD9vKzAwUGASMjSyKk4ccSLSjbRRJ2MuTgBgYWGBrVu3olatWgCA8PBwNGnSBKGhoYKTkdylv+R5+fJlgUnI0MiqOHHEiUg30uY5GXtxAlIvT+3btw/ly5cHAISEhKBp06bS5rREH+Pt7S0dszhRZsiqOHFyOJFupC9OMtocQG8cHBxw5MgRaW7PzZs30aRJE0RGRooNRrLl4OAAd3d3AMDVq1eRnJwsOBEZClkVp/QjTrxUR5R1acVJpVJ9ds80Y+Ls7Ixjx46hYMGCAFJ/GDZr1swkRt0oa9Iu1yUkJODmzZuC05ChkFVx4ogTkW4Y+1pOn1KiRAn8/fffyJcvHwDg0qVLaN68uV7WNyLDl36eU/qV0ok+R7bFiSNORFlnqsUJAEqVKoUTJ07A0dERAHDu3Dm0atUKsbGxgpOR3KTfg2/YsGEoXrw4WrZsidGjR2PZsmU4efIkQkNDTeJyN2WcrNZx4uRwIt0w5eIEpK4MfezYMTRo0ABRUVHw9/dHs2bNcPDgQa1/GzJtlSpVgoODgzQX7tGjR3j06BEOHTqk9X45c+aEi4sLChcujMKFC0vHzs7OyJs3LxwdHeHo6Ah7e3solbIajyA9kFVx4qU6It0wlUUwP6dSpUo4evQoGjdujOjoaAQEBKBJkyY4cuQI7O3tRccjGbC2tsaRI0ewatUqXLt2Dbdu3froyGRsbCzu3r2Lu3fvfvbjKZVKODg4aBUpa2trnT5YzMSTVXHi5HAi3TD1Eac0VapUwd9//43GjRvj7du3uHjxIho0aICjR48ib968ouORDPj4+EiX7DQaDUJDQxEcHIx79+5Jbx8+fIhnz559dqNlAFCr1YiIiEBERITe8lpaWiJnzpywsbFBzpw5tR7pn7O1tUWePHmkEvfvh6Wlpd4yGjtZFSeOOBHpBovT/1SuXBmnTp1Co0aN8Pr1a1y9ehX169fHsWPHUKBAAdHxSEYUCgUKFSqEQoUKoUGDBlqvaTQaREdH49mzZ3j+/DmeP3+OsLAwqSj9+xEdHa2XjElJSUhKSvripTby5s0LFxcXrUfRokVRqlQplCxZkj+DP0O2xYkjTkRZZwob/WZG+fLl4e/vj4YNGyI0NBQ3b95ErVq1cPToURQrVkx0PDIACoUC9vb2sLe3lxZb/Zzk5GS8f/8e8fHxGX7ExcVl6P1iY2MRFxeH2NhYxMbGQqVSZfrv8+bNG7x58wZXr1796N/Vzc0NpUqVQunSpVG5cmX4+PigePHiUCgUmf5cxkZWxYmTw4l0gyNOHypVqhROnz6NBg0a4OnTp3j48CFq1KiBI0eOoGLFiqLjkZGxsLBAnjx5suVzJSUlaRWp2NhYREdHf3I0LDw8HC9evEBoaChSUlI++HgajeajE+Xz5MkDHx8fVK1aFdWrV0ft2rVhY2OTLX9HOZFVceKIE5FusDh9XPHixREQEIBmzZrh9u3bePXqFerUqYO9e/eifv36ouMRZYmlpSUsLS0zfdODSqXCy5cv8ezZMzx79gwPHjzA3bt3cefOHdy9e/eD9c/evn2LI0eO4MiRI9LnrVmzJho1aoSWLVvC09PTJEakFBoZLVDRvHlz6T/I27dv4eDgIDgRkWG6fPmyNOH166+/xqJFiwQnkpe3b9+idevWOHfuHIDUHwAbN25Ehw4dBCcjkgeNRoMXL17g5s2buHz5Mi5evIhLly4hPDz8k3+mWLFi8PX1Rfv27VG9enWjLVGyKk716tWDv78/gNTRJ446EWXN3bt3Ubp0aQBAr1698OeffwpOJD9xcXHo1KkTDh48CCB1Xsfvv/+OUaNGGe03fKIvodFoEBISggsXLuDUqVM4duwYHj9+/NH3LV68OHr16oWePXvCzc0tm5Pql6yKU7Vq1XDx4kUAqbd18psXUdaEhoaiUKFCAABfX1/s3r1bcCJ5Sk5OxqBBg7B27VrpucGDB2Px4sUwN5fVTAYiWUqbB7Vnzx6cOnXqo3OmmjRpgpEjR6J58+ZGsQ6VrP4GSUlJAFKHzVmaiLKOc5wyxsLCAn5+fpg0aZL03PLly9GyZUu93U5OZEyKFSuGr7/+GsePH8fr16+xdu1aNGrUSOtn+NGjR9GqVSt4eHhg8eLFWvOZDZGsRpzKlSuHW7duIVeuXLyFmugLaDQamJmZQaPRoEqVKrh06ZLoSLK3YcMG9O/fX/oFrmzZsjhw4ACKFi0qNhiRAXr27Bk2bNiAlStXfnA5r0CBAhg7diwGDx5skHfQy3LEycLCQnASIsOmUCikUSeOOGVMjx49cPz4cWlz4Fu3bqFKlSo4deqU2GBEBsjFxQXjx4/H/fv3sXfvXjRs2FB67eXLlxg1ahTc3NywfPnyLK1DJZIsixOXgif6cixOmVe7dm1cuHAB7u7uAFIXCWzUqBEWLlwIGQ3OExkMMzMztGnTBsePH8fVq1fRrl076bVXr15hyJAhqFy5Mo4fPy4wZeawOBEZKRanrClRogQuXryIpk2bAgBSUlLwzTffoE+fPgY/N4NIpIoVK2Lnzp24du0a2rdvLz1/48YNNG7cGO3atUNYWJjAhBnD4kRkpHLnzg0gdWf3j93pQp/m4OCAgwcPYty4cdJz69atQ+3atfHkyROByYgMn6enJ3bs2IGAgAB4e3tLz+/evRulS5eGn5+frEd4ZVWckpOTAbA4EekC96v7MmZmZvjtt9+wbds2aVuJwMBAVKpUCQcOHBCcjsjw1axZExcvXsSff/6JfPnyAQCio6PRv39/NG3aFKGhoYITfpysihNHnIh0h0sS6EbHjh1x4cIFaTPgyMhItG7dGmPGjJF+2SOirFEqlejVqxdu376Nnj17Ss8fO3YMFStWxOHDhwWm+zgWJyIjxREn3SlfvjwCAwPRtm1b6bnff/8ddevWxbNnzwQmIzIOjo6OWLduHQ4fPiwt3hseHo4WLVpgzJgxsrp0J5vilJKSArVaDYDLERDpAkecdMve3h47d+7EggULpO9R58+fR8WKFbkyO5EOvHv3Du/evYOXl5fW87///rusvsZkU5zSRpsAjjgR6QKLk+4pFAqMHDkSZ8+elRbGfPv2Ldq1a4cBAwZ8sJs8EX3e8+fP8ccff6BZs2bImzcvOnfujH379mm9j7m5OfLnzy8o4YdYnIiMFIuT/lSpUuWDNWlWr16NihUr4sKFCwKTEclfaGgo5s6diypVqsDFxQXDhw/HX3/9pTVn0MrKCo0aNcJvv/2G69evo2bNmgITa5PNLpYsTkS6lbYcAcDipA/29vbYsWMH1q5di5EjRyImJgYPHz5ErVq18NNPP2HChAmcdkD0/6Kjo7Fz505s2rQJf//990fnLLm6uqJNmzZo06YNateuDSsrKwFJ/5tsilP6psniRPTlOOKkfwqFAn379kWdOnXQo0cPXLhwASkpKfj1119x4MABrF27FuXKlRMdk0gItVqNU6dOYeXKldi9ezcSExM/eJ+KFSvC19cXX331FSpUqKC1ObBcyaY4ccSJSLdYnLJP8eLFcebMGUyfPh2TJ09GSkoKAgMD4e3tjYULF2LgwIEG8QOBSBdev36NtWvXYuXKlXjw4MEHrxcvXhzdu3dHt27d4OHhISDhl2FxIjJSXI4ge5mbm2PixIlo3rw5evfujTt37iAxMRGDBw/G6dOnsWzZMuTKlUt0TCK90Gg0CAgIwKJFi7Bnz54P1jjLmzcvunTpgh49esDHx8egf5Hg5HAiI8URJzGqVKmCoKAgfP3119JzGzduRLVq1RAZGSkwGZHuJSYmYv369fD29kadOnWwfft2rdLUsGFDbN26Fc+fP8eiRYtQtWpVgy5NgEyLEydUEn05FidxrKyssGjRImzbtk2apH/r1i2MGTNGcDIi3Xj9+jUmT56MokWLolevXggKCpJey5cvH8aNG4cHDx7g+PHj6NSpE3LkyCEwrW7xUh2RkWJxEq9jx47w9PSEj48P3r17h9WrV6Nbt25o0KCB6GhEWXL79m38/vvv2LRp0weTvb28vDBq1Ch07NjRqH+Oy3LEyZj/wYmyC5cjkAcPDw/MnDlTOh80aBDi4uIEJiLKvOvXr6NTp04oV64c1qxZI5UmpVKJDh06ICAgAJcvX0b37t2N/me4bIoTlyMg0i0LCwtpHRQWJ7EGDRqEWrVqAQAePnyIUaNGyWrvLaJPSVvotUKFCti+fbv0/62dnR2+//57PHr0CNu3b0fNmjUNfu5SRsmmOHGOE5HupV2uY3ESS6lUYuXKldIvhStWrMDPP/8sOBXRp12+fBlt2rRB5cqVtfaJy5cvH2bPno1nz55h9uzZKFKkiMCUYsimOKlUKunY3Fw2U6+IDFpaceJyBOKVKlUKq1evls6nTZuGOXPmCExE9KELFy6gRYsW8PHxwf79+6XnCxQogHnz5uHx48f4/vvvtaYCmBrZNBS1Wi0dm5mZCUxCZDzSjzhpNBqTGUqXqx49eiAyMhIjR44EAHz//fewsbHB0KFDBScjUxcQEIDJkyfj2LFjWs8XKlQI48aNQ//+/WFtbS0onbzIpjilpKRIx0qlbAbCiAxaWnFSqVRISEjgNz4ZGDFiBKKiojBx4kQAwLBhw6BUKjF48GDBycgUnTp1CpMnT8bJkye1nnd1dcX48ePRt29fo1pKQBdkWZw44kSkG/9ekoDFSR5++uknxMXFYcaMGQCAIUOGQKlUYuDAgYKTkSnQaDT4+++/MXnyZJw+fVrrNTc3N0yYMAE9e/bkjVqfIJvilP5SHUeciHTj30sS5M+fX2AaSqNQKDB9+nSo1WrMmjULQOqddwqFAgMGDBCcjoyVRqPB0aNHMXnyZJw7d07rtRIlSmDChAno3r07b9D6D7IpThxxItI9LoIpXwqFAjNmzIBarcbvv/8OABg4cCCUSiX69esnOB0ZE41Gg0OHDmHy5Mm4dOmS1mseHh746aef0KVLF96YlUGy+Vfi5HAi3WNxkjeFQoFZs2ZBrVZj7ty5AIABAwZAoVCgb9++gtORodNoNNi3bx8mT56stSUKAJQtWxY//fQTOnbsyJ+5mSSb4sTJ4US6l744cUkCeVIoFPj999+hVqsxf/58aDQa9O/fH0qlEr179xYdjwyQWq3G7t27MWXKFFy7dk3rNU9PT0ycOBFt27blz9oskmVxYvsl0g2OOBkGhUKBuXPnQqPRYMGCBdBoNOjbty+USiV69uwpOh4ZiJSUFGzfvh1Tp07FrVu3tF6rXLkyJk6ciNatW7MwfSHZFCdODifSPRYnw6FQKDBv3jyo1WosWrQIGo0GvXv3hkKhQI8ePUTHIxlTqVTYsmULpk6diuDgYK3XfHx8MHHiRLRo0YLruOmIbIoTR5yIdI/FybAoFAosWLAAarUaS5Ys0SpP3bt3Fx2PZCY5ORmbNm3CtGnTcP/+fa3XqlevjkmTJqFJkyYsTDomm+LEyeFEuvfv5QhI/hQKBRYtWgS1Wo2lS5dCrVajV69eMDMzQ5cuXUTHIxlITEzE2rVrMWPGDISEhGi9Vrt2bUyaNAkNGjRgYdIT2RQnTg4n0j2OOBkmhUKBxYsXQ6PRYNmyZVCr1ejZsyfy5MmDJk2aiI5HgsTGxmLFihX4/fffERoaqvVagwYNMHHiRNStW1dQOtMhm+LEESci3WNxMlxKpRJLlixBSkoKVq5cCZVKhfbt2+PcuXMoX7686HiUjaKjo7F48WLMnz8fb9680XqtadOm+Omnn1CrVi1B6UyPbIoTR5yIdI/LERg2pVKJpUuXIjw8HHv27EFMTAzatWuHoKAgk96d3lSEh4dj/vz5WLx48Qe/+LRt2xY//vgjvL29BaUzXbJpKJwcTqR7HHEyfGZmZti0aRMqV64MAHjw4AFWrVolOBXp0+PHj/Htt9+iaNGimD59uvS1q1Qq0b17d9y8eRO7du1iaRJENsWJl+qIdM/GxkYawWVxMlzW1tYYO3asdH7v3j2BaUhfzp8/j44dO6JEiRJYsGAB4uLiAAAWFhYYMGAAgoODsWHDBpQtW1ZwUtPGS3VERkyhUMDW1hZRUVEsTgbu2bNn0rGnp6fAJKRLKpUKe/bswZw5c3DhwgWt16ysrDBw4ECMGTMGLi4ughLSv8mmOBGRfuTOnZvFyQicOXNGOq5du7bAJKQLUVFRWLt2LRYsWPDBkgL58+fHiBEjMHjwYOTNm1dMQPok2RSn9OtNaDQagUmIjEvaPCcWJ8OlVqsREBAAAHBwcECZMmUEJ6Ksunz5MpYtW4bNmzcjPj5e67Xy5ctj9OjR6Nq1K3LkyCEoIf0XFiciI5dWnOLi4qBSqWBuLpsve8qgGzduICIiAgBQq1YtTmcwMLGxsdi6dSv++OMPBAYGfvB6s2bNMHr0aDRq1IiLVhoA2XwHZXEi0o/0d9bFxMTA3t5eXBjKkkOHDknHTZs2FZiEMkqtVsPf3x9//vknduzYgdjYWK3XbW1t0bt3bwwZMoQjiAaGxYnIyP17SQIWJ8OTvjg1b95cYBL6L8HBwVi/fj3Wr1+Pp0+ffvB65cqVMXToUHTt2hU5c+YUkJC+FIsTkZHjWk6GLTIyEufOnQMAlCpVCsWKFROciNLTaDS4efMmdu7ciZ07d+LmzZsfvI+dnR06d+6M/v37o0qVKrwcZ+BYnIiMHIuTYdu/f7+0zl2LFi0EpyEASE5OxsWLF3Hw4EHs3LkT9+/f/+B9lEolmjZtit69e6NNmzawtrYWkJT0gcWJyMil35qDxcnwbNmyRTpu3769wCSmS6PR4P79+zh69CiOHTuGkydPfnILo2rVqqFDhw7o1q0bChYsmM1JKTuwOBEZOY44Ga6IiAgcO3YMAODi4oJq1aoJTmR6nj17hhYtWnz0EhyQOrJUp04dtGvXDm3btkXhwoWzOSFlNxYnIiPH4mS4du7cCZVKBQDo3LkzlyEQ4PDhwx+UJicnJzRq1AiNGzdGy5YtkS9fPkHpSAQWJyIjl744feryAsmTn5+fdNy5c2eBSUxXgwYNoFAooNFoYGFhgYCAAHh7e7PEmjDZ/JdncSLSD444GaYbN27g4sWLAFL3pvPy8hKcyDSVKFECX331FYDUSeHBwcEsTSZONv/1WZyI9IPFyTCtWrVKOh44cCBvYRfou+++k47nzJnDn1EmjsWJyMixOBme2NhYrFu3DgBgZWWF7t27C05k2mrWrAkfHx8AwLVr1/D3338LTkQisTgRGTkuR2B41qxZg6ioKACpc5scHBzEBjJxCoXig1EnMl2yKU7psTgR6Q5HnAxLSkoK5s2bJ52PHj1aYBpK065dOxQpUgRA6p12d+7cEZyIRJFNcTIzM5OO01bJJaIvxxEnw7J37148evQIANC4cWN4enoKTkQAYG5ujpEjR0rnixYtEpiGRJJNcbKwsJCOk5OTBSYhMi4WFhbSdg9cjkDeNBoNpkyZIp2nvzxE4vXr10/amPfPP/9EZGSk4EQkAosTkQlIu1zHESd527t3L/755x8AgLe3N5o0aSI2EGmxt7dHnz59AABxcXFadz6S6WBxIjIBLE7yp1ar8euvv0rnv/zyC5cgkKH0l+sWL14srexOpoPFicgEpC9OvPlCnrZs2aI12tSiRQuxgeijSpYsKf23efr0Kfbu3Ss4EWU3FiciE5A2QTwlJQXx8fGC09C/xcXFYdy4cdL5tGnTONokY9988410PH/+fHFBSAjZFCdz8/9tm8ehTyLd4pIE8jZv3jw8e/YMANC8eXPObZK5xo0bo3Tp0gCAgIAABAUFCU5E2Uk2xYkjTkT6w+IkX2FhYfjtt98ApC7L8vvvvwtORP9FoVBojTotWLBAYBrKbixORCYgfXHikgTyMmHCBMTGxgIABg8ejDJlyghORBnRs2dPaUX3LVu24OXLl4ITUXZhcSIyARxxkid/f3+sWbMGAGBnZ4dffvlFbCDKMBsbGwwaNAgAkJSUxKUJTAiLE5EJYHGSn4SEBOkHLwBMnToVTk5OAhNRZg0dOlSaxL9ixQqkpKQITkTZQTbFKf3kcBYnIt1icZKfadOm4d69ewCAatWqYejQoYITUWYVKVIELVu2BAA8e/YMBw8eFJyIsoNsilP6ESfeVUekW9yvTl5u3ryJGTNmAEj93rdy5Uqt/TrJcKQvvEuXLhWYhLKLLIsTR5yIdIsjTvKRnJyMvn37Sr8gjh07FuXKlROcirKqadOmKFq0KADgyJEjePjwodhApHeyKU45cuSQjhMTEwUmITI+vKtOPqZMmYIrV64AADw8PDBhwgTBiehLmJmZYfDgwdL58uXLBaah7CCb4mRlZSUdc2VjIt3iiJM8nD9/HtOmTQOQOq9z/fr1Wt/7yDD169dPumri5+eHhIQEwYlIn2RTnKytraVjFici3WJxEi8mJgY9e/aEWq0GAEycOBFVqlQRnEr/NBoN1q9fj+rVq+PXX381yr0S8+XLhw4dOgAAIiIisGPHDsGJSJ9YnIhMAIuTeCNHjpTmv1SrVg3jx48XnEj/IiIi0K1bN/Tq1QsXLlzAL7/8gkmTJomOpRfDhg2TjjlJ3LjJpjjlyJFDWg+DxYlIt1icxPrzzz+lhS5z5syJDRs2aC3BYoz27t2LsmXLYsuWLVrPT5kyxSgXi6xZs6Y0yf/cuXO4ceOG4ESkL7IpTgqFQrrWz+JEpFvW1tZQKlO/3FmcstetW7c+uGW9ePHiAhPpV2RkJHr16gVfX1+8evUKAGBvb4/q1atL7zNkyBAcOXJEVES9UCgUGDJkiHSeVpTJ+MimOAH/u1zH4kSkWwqFQhp1YnHKPjExMejYsaP0Pa1///7o2bOn4FT6odFosGPHDpQtWxbr16+Xnm/VqhVu3bqFc+fO4dtvvwUApKSkoGPHjrh69aqgtPrRtWtX6Q7x9evXIykpSXAi0gcWJyITkVacuBxB9tBoNBg2bBju3LkDAChfvjwWLVokOJV+PHz4EC1atEDHjh0RFhYGIHXvvbVr12Lfvn1wdnYGAPz+++9o164dgNRS2bJlSzx9+lRYbl3LkycP2rZtCwB48+YNDhw4IDgR6YOsipONjQ0AFicifeCIU/by8/OTRl5y5cqF7du3a90EYwwSExMxdepUlCtXTuvSW8uWLXHr1i307t1bmrsKpK55tGHDBumyXVhYGJo3b46oqKjsjq43/fr1k479/PwEJiF9kVVx4ogTkf6kFae4uDhua6RnV69exddffy2dr1y5Eh4eHgIT6ZZGo8H+/fvh6emJn3/+WVq3qHDhwti5cyf279+PQoUKffTPWltbY9++fXB3dwcA3L59G23btjWahY8bNGgAV1dXAMDhw4cRGhoqOBHpmiyLU0JCgrTWCRHpBlcPzx6RkZFo3769VCaGDBmCLl26CE6lO9evX0fjxo3Rpk0baZNiMzMzjB49Grdv30a7du20Rpk+Jm/evDh8+DCcnJwAAKdOnUK/fv2MYo0nMzMz9OnTBwCgVquxbt06sYFI52RZnABw5VUiHeOSBPqnVqvRo0cPPH78GABQpUoVzJ8/X2woHXn16hUGDx6MSpUq4cSJE9LztWrVQmBgIObMmaO1mfR/KV68OPbv3y9939+0aRMmTpyo89wipBUnIPVynTEUQvof2RYnXq4j0q30P9RYnPRj6tSpOHToEADA0dERO3bs0NqH0xAlJCRg5syZcHd3x4oVK6SrAW5ubti+fTtOnz6NChUqZOljV61aFZs3b5aWypg6dSo2bNigs+yiuLm5oX79+gCA+/fvS3sTknFgcSIyERxx0q8jR47gl19+AQAolUps2bJFmutiiFQqFfz8/FCyZEmMGzdOurybO3duzJw5E7dv30aHDh3+87Lcf/nqq68wZ84c6bx///44e/bsF31MOejRo4d0vHHjRoFJSNdkVZzS7qoDgNjYWIFJiIwP5zjpT0hICLp16yZdkpkyZQoaNWokOFXWqNVqbN++HeXKlUP//v3x7NkzAKllcNCgQbh//z5++OEHnW5O/M0332Dw4MEAgKSkJPj6+uLRo0c6+/gitGvXDpaWlgCALVu2ICUlRXAi0hVZFaf0lxL4jZ1ItzjipB8JCQlo3749IiMjAQCtW7fGuHHjBKfKPI1Gg8OHD8Pb2xudOnVCcHCw9FrLli1x9epVLF++HPnz59f551YoFFi0aJFUNt+8eYPWrVsjOjpa558ru9jb26NVq1YAUueHnTx5UnAi0hVZFSf+RkykPyxO+vH1118jKCgIQOqE53Xr1klzdgxFQEAA6tatixYtWmit5l27dm2cOXMGBw4cgKenp14zWFhYYPv27ShVqhSA1GUKOnXqZNBLZ3Tr1k065uU64yGrr26OOBHpD4uT7q1evRqrV68GkDpHc9euXbC3txcbKhOCgoLQsmVLqSClqVSpEg4fPgx/f3/UqlUr2/LY29vjwIEDcHR0BAAcPXpU2qbFELVo0UL6utu5cyfn7hoJFiciE8HipFuBgYEYPny4dL5ixQq9j8royqVLl9C6dWt4eXlJdwECgIeHB7Zv344rV66gWbNmXzzxOyuKFy+OXbt2wcLCAgCwZMkSLF68ONtz6IK1tbW0xcz79+9x8OBBwYlIF2RVnPiNnUh/uByB7kRERKB9+/bSatfDhg3TuotKrs6fP4/mzZujatWqWvuoubq6ws/PDzdv3kSHDh2EX2qsU6cOVqxYIZ1/8803Wlu6GJL0l+t27NghMAnpiqyKE0eciPSHv5joRkpKCrp3744nT54AAKpVq4Z58+YJTvV5AQEBaNKkCWrUqKFVQFxcXPDHH3/g3r176Nu3L8zNzQWm1NanTx9pkr1arUanTp1w8+ZNwakyr169esiTJw8A4ODBg1zc2QiwOBGZCN58oRuTJ0/GX3/9BQBwcnLC9u3bpdvO5cbf3x8NGjRA7dq1cezYMen5IkWKYPny5Xjw4AGGDh0q20U6p02bpnWpq3Xr1ggPDxecKnMsLCzQpk0bAEBMTIzWqutkmGRVnPgbMZH+8Ovryx08eBCTJ08G8L9FLgsXLiw4lTaNRoMTJ06gbt26qFevntZt8MWKFcPq1atx//59DBo0SLaFL41SqcT69evh5eUFIHW9rHbt2hnchsBt27aVjnft2iUwCemCrIoTR5yI9IdznL7Mo0ePtOYxTZ8+HQ0aNBCYSJtGo8HRo0dRu3ZtNGrUCKdPn5ZeK1GiBNauXYu7d++iX79+0sRrQ2BjY4O9e/eiYMGCAFIvOw4ZMsSg9n9r3LgxcubMCQDYt2+fQS+xQCxORCbD3NxcWp2fxSlz4uPj0b59e0RFRQEAfH198cMPP4gN9f80Gg0OHTqE6tWro2nTplrblXh4eGDDhg24c+cOevfubVCFKb1ChQph37590mrla9euxe+//y44VcZZW1ujefPmAFIX9wwICBCciL6ErIoTLyUQ6Vfa1xi/vjJOo9Fg2LBh+OeffwAA7u7uWLt2rZBb9f+da//+/fDx8UHLli1x8eJF6bUyZcpg8+bNuHXrFrp37y6rSd9Z5e3tjT///FM6Hzt2LPbt2ycwUeakzdUCeLnO0MmqOKUfcTLkpfaJ5Crta4zFKeNWrlyJtWvXAki9bLRr1y7Y2dkJy6NWq7F79254eXmhTZs2uHLlivRa+fLlsX37dty4cQNdunSBmZmZsJz60KlTJ/z6668AUotjt27dcP36dcGpMqZly5bSiN+BAwcM6lIjaZNVcTIzM5O+IaXt+0REupN+xInfuP/b5cuXMWLECOl81apVKFeunJAsaZvvVqxYEe3atdPaGqVixYrYtWsX/vnnH1msw6RPP//8M7p06QIgdTP41q1b49WrV4JT/TdbW1vUrl0bAPD48WPcv39fcCLKKtl9daWtd/H27VvBSYiMT1pxUqvV3P7hP0RFRaFDhw5ISkoCAIwYMQJdu3bN9hwpKSnYsmULypcvj06dOuHGjRvSa15eXti7dy+CgoLQtm1boy5MaRQKBfz8/ODj4wMAePr0Kdq2bWsQ6yM1a9ZMOjbUBT1J5sVJrVYLTkNkXDiPMOO++eYbPH36FABQvXr1bJ+MrFKpsGHDBpQtWxZdu3bF7du3pdeqVq2KgwcP4vLly2jTpo3w+VbZzdraGnv27JGWgjh//jwGDhwo+1HUtAniAHD48GGBSehLyLY4qdVq3llHpGMsThmza9curFu3DkDqv9mWLVuybc2j5ORkrF27FqVLl0bPnj0RHBwsvVajRg389ddfOH/+PFq0aGFyhSm9ggULYt++fdKdohs2bMCMGTMEp/q8smXLolChQgCAU6dOcdTXQMmuODk4OEjHvFxHpFssTv/t1atXGDx4sHS+aNEiuLq66v3zJiUlYdWqVfDw8EDfvn3x4MED6bW6devixIkT0tYpplyY0qtUqRI2bNggnf/444+yvmNNoVBIl+sSEhK01toiwyG74pQ24gRwgjiRrrE4fZ5Go8GgQYPw5s0bAKkrPvfs2VOvnzMxMRHLli2Du7s7Bg4ciMePH0uvNWzYEKdOncKpU6fQoEEDFqaPaNu2LaZPny6d9+zZU2vivNxwnpPhk3Vx4ogTkW5x9fDP27Ztm7Q2UL58+bB8+XK9lRWVSgU/Pz94eHhg6NCh0nwqAGjSpAkCAgJw/Phx1K1bVy+f35iMGzdOWtU9Li4Obdq0QVhYmOBUH9eoUSNpmYj0+weS4WBxIjIhHHH6tMjISHzzzTfS+bJly+Dk5KTzz5OSkoJNmzahTJky6N+/P548eSK91qJFC5w/fx5//fUXatasqfPPbawUCgVWrlyJ6tWrAwCeP38OX19fWc4hsre3R+XKlQEAt27dkkY3yXCwOBGZkPTFiTdfaBs/fry0HpCvr6/Wxqy6oNFosGvXLlSoUAHdu3fXWsenefPmuHTpEg4ePIhq1arp9POaCisrK+zevVuaj3bp0iX069dPlnfa1alTRzrm9iuGh8WJyIRwxOnjzp49i+XLlwMAcuXKhYULF+rsY2s0Ghw+fBje3t5o3749bt26Jb1Wr149BAQE4NChQ6hSpYrOPqepyp8/P/bv3y9tqLtlyxZMnTpVcKoPpb/86u/vLzAJZQWLE5EJYXH6UHJystZddFOnToWLi4tOPra/vz9q1aqFFi1aICgoSHq+WrVqOHHiBE6ePMlLcjrm6emJTZs2SXPTJk6ciO3btwtOpa1WrVpSPt5ZZ3hkXZx47ZdIt1icPrRq1SppFMjLywtff/31F3/M27dvo3Xr1qhXrx7OnTsnPV+pUiUcPHgQ586dQ4MGDb7489DHtWnTBjNnzpTOe/furbWnn2gODg4oX748AOCff/7h3qwGRnbFKX/+/NLx69evBSYhMj4sTtrevXuHSZMmSeeLFi36oo1xw8LCMHjwYJQvXx4HDhyQni9Tpgx27tyJK1eumPzCldnl+++/R58+fQAA8fHxaNOmDV68eCE2VDpp85zUarVWuSb5k11xypMnj/SNyxA2biQyJFyOQNuMGTMQHh4OAOjUqZN0V1ZmxcTE4JdffoG7uztWrFghbRdVuHBhrF27FtevX0e7du1MYi85uVAoFFi2bBlq1aoFILXUtmnTBnFxcYKTpUo/z4mX6wyL7L6KlUqldAswR5yIdIsjTv/z9OlTzJs3DwBgaWmJ3377LdMfIyUlBStXroS7uzt+/fVXxMbGAkgtqNOnT8e9e/fQu3fvLxrFoqzLkSMHdu3aBTc3NwBAUFAQevfuLYt9UNOXdDldRqT/JrviBPzvct3r169leSspkaGytraWfoib+nIEP//8MxISEgAAI0aMQLFixTL158+ePYsqVapg0KBBePnyJQDA3NwcI0aMwMOHDzF+/HhYW1vrPDdljpOTE/bv3y+Ntu7YsUPr8qwohQoVQsGCBQGkFif+rDMcsixO+fLlA5C6d1NUVJTYMERGRKFQSKNOpjzidO/ePWmPMwcHB0yYMCHDfzYsLAw9e/ZErVq1tLb2aN++PW7fvo2FCxfqZeFMyrqyZcti69at0qXSqVOnYuXKlYJTAd7e3gCAqKgoPHz4UHAayihZFidOECfSHxYnYNq0adLlmjFjxmhtLv4pSUlJmD17NkqWLKm1sWzFihVx+vRp7NixA+7u7nrLTF+mefPm0qVZABgyZAj2798vMBG01u66fPmywCSUGbIvTpwgTqRbpl6cHjx4gI0bNwJIvRklI8sPXLhwAV5eXvjhhx8QExMj/dk//vgDV65cQe3atfWamXRj5MiR+P777wGk3s3WuXNnXLhwQVietBEngPOcDIksi1PapTqAI05EupZWnOLj45GcnCw4TfabPXs2UlJSAACjRo3SutPw3969e4evv/4aNWrUwM2bNwGkXu4cMmQI7t27h6FDh3Lit4GZOXMmunbtCiD1a6BVq1a4d++ekCzpixNHnAyHLIsTR5yI9Cd9UTC1CeLh4eFYt24dgNR/hxEjRnzyfffu3YsyZcpgyZIl0sTdypUr4/Lly1i6dCkcHR2zJTPpllKpxJo1a6QFSCMiItC0aVNpgn92cnJyQpEiRQCk3vGXVuhJ3liciEyMKS9JsGzZMulOugEDBsDOzu6D94mMjET37t3h6+srLZhoY2ODOXPm4OLFi/Dy8srWzKR7acsUeHp6AgBCQkLQokULIb9IpP3/FBsbi0ePHmX756fMk2Vx4qU6Iv1JX5xMacQpMTERS5YsAZA66jBy5MgP3uf48eMoX748Nm3aJD3XrFkz3Lx5E6NHj4a5uXm25SX9srOzw+HDh+Hq6goAuHr1Ktq1a4fExMRszVG2bFnpOP0G0CRfsixOBQoUkI5DQ0MFJiEyPqY64rRnzx5pBLtdu3YoWrSo9FpcXBxGjhyJxo0bS6NMdnZ2WLduHQ4dOiQtoEjGxdnZGUeOHJHuqjx+/Di6du0KlUqVbRnSF6fbt29n2+elrJNlccqfP7804VJOewsRGQNTLU7p1+0ZNmyYdHzr1i14e3tj0aJF0nMNGzbEjRs30LNnT+4rZ+RKly6NAwcOwMbGBgCwe/du9O3bN9tWFy9Tpox0zBEnwyDL4mRmZgZnZ2cAwPPnzwWnITIuplicHj16hBMnTgAAihcvLu0TtnHjRvj4+ODOnTsAACsrKyxcuBBHjx6Fi4uLsLyUvWrUqIE9e/bA0tISALBhwwZ8/fXX2bKad8mSJaWBAhYnwyDL4gSkbo4JpM5xyu5rzkTGzBSLk5+fn3Q8YMAAJCUlYejQoejRo4e06WuFChVw9epVjBgxgpvxmqDGjRtj69atUolZunQpxo0bp/fylCNHDmnh1Lt37/LOOgMg2+8OacUJ4DwnIl1KvxyBKRQnjUYjLXhpZmaGBg0aoFatWli2bJn0Pv369cP58+dRqlQpUTFJBnx9fbF27Vrp8uysWbMwffp0vX/etMt1iYmJvLPOAMi2OBUqVEg65uU6It0xtRGnS5cuISQkBEBqaWzTpg0CAwMBpF6aW716NVavXs0NeQkA0KNHD/zxxx/S+U8//YTffvtNr5+Td9YZFtneW5t+xInFiUh3TG05gq1bt0rH6TcNL1asGHbt2oUKFSoISEVyNmTIEMTExGDMmDEAgB9//BFqtTpTm0FnhoeHh3TMzX7lT7YjTixORPphSiNOarUa27Zt++D5OnXq4NKlSyxN9Enff/89ZsyYIZ3/9NNPmDp1ql4+V/rlLh4/fqyXz0G6w+JEZGJMqThdvnz5gyVNevfujaNHj3LLFPpPY8eOxaxZs6Tzn3/+GZMnT9b550lfnDjHSf5YnIhMjKkUJ7VajWrVqmk99+OPP2LNmjXIkSOHoFRkaMaMGYPff/9dOp80aRJ++eUXnX6OAgUKwMrKCgBHnAyBbItTwYIFpTsbWJyIdMdU7qr79/yt77//HtOmTeOClpRp3333HebOnSud//rrrxg7dqzOlipQKBTSqFNISEi2Lb5JWSPb4mRpaSlt9sviRKQ7ZmZm0irJxlycbG1tpb3pAGD27NkC05ChGzVqFObNmyedz5o1C4MGDdLZukvFihUDACQkJODly5c6+ZikH7ItTgCklXvDwsK4CCaRDqVdrjPm4qRQKDBs2DDExcVlywrQZPy+/fZbLFu2TBq1XLVqFTp16qSTn0+cIG44ZF2c0jbh1Gg0ePr0qdgwREYkrTiZwnIEXJ+JdGnw4MHYvHkzLCwsAAC7du1Cy5Ytv/hrKW3ECeAEcbmTdXFiAyfSj7SJqKZQnIh0rXPnzti/f790yfvEiRNo1KgRIiIisvwx0++NyN0y5E3WxSl9A2dxItKNuLg4aVPb9L+cEFHGNW3aFMePH4eDgwOA1BXqa9euLa1Sn1kFCxaUjsPCwnQRkfRE1sWJI05Eunf27FkkJycDABo0aCA4DZHhql69Ok6fPi2Vnjt37qBatWq4cuVKpj9WgQIFpGMWJ3ljcSIyIa9fv8batWul8/r164sLQ2QEypUrh7Nnz6JkyZIAgFevXqFu3brYu3dvpj4OR5wMh0Ij49tNEhMTYW1tDY1GgypVquDSpUuiIxHJWmJiIkJDQ/H8+XM8f/4cz549k96GhITg+vXrWmvEvHz5Ulr2g4iyLiIiAm3btsWZM2cApN7VOX/+fIwcOTLDH8POzg7v3r2Du7s77t27p6+o9IVkXZwAwNXVFc+ePUPevHkRHh4uOg6RMImJiVIh+ncxSnu8evUqwx+vW7du2Lhxox4TE5mWxMRE9OvXD5s2bZKe+/rrrzF37lzpLrzPKVWqFIKDg5ErVy7euCFj5qID/Bc3Nzc8e/YMb968wfv377VWPSYyBhqNBpGRkQgLC0NoaCjCwsLw4sWLD8rRl/7iYGZmBnd3d/j6+qJ9+/bw8vLS0d+AiAAgR44c2LBhA4oVKyZtCLx48WLcvn0b27Zt+8/9EQsUKIDg4GDExMQgJiYGuXLlyo7YlEkGUZxOnz4NIHWek6enp+BERBmj0Wjw9u1brUL0qbdfuoCeUqlEwYIFUbhwYbi4uKBw4cIfHDs7O8PcXPZf8kQGTaFQYMqUKShWrBgGDx6M5ORk/P333/Dx8cG+fftQtmzZT/7Zf89zcnd3z47IlEmy/y6afkmChw8fsjiRcAkJCXj9+jVevXolvX358uVHC1FSUtIXfz4zMzM4OztLBehj5ahAgQIsRUQy0rdvX5QsWRLt2rXD69ev8ejRI1SrVg0bN25EmzZtPvpn0t9Z9/r1axYnmZL9d9q0OxUAcLIc6YVGo8H79++1itDnjnW5TUmePHng7OyMggULSm/TjtPKUf78+VmKiAxQzZo1cfnyZfj6+uLq1auIiYmBr68vfvnlF/z0009QKrVvbE9bEwoAIiMjszsuZZDsvxt7eHhIx8HBwQKTkKFISUlBVFQU3rx589lH+lKUkJCg0wyOjo4fFKJ/vy1QoIC0gjcRGSdXV1cEBASgb9++2LZtGzQaDSZNmoQLFy5gw4YNyJMnj/S+LE6GQfbFKf1QJUecTI9KpUJUVBQiIyMRERHxn2XozZs3iIyM1LrlXlfs7OyQL18+5M+fH/nz5//gOH0hypEjh84/PxEZJhsbG2zZsgUVK1bETz/9BLVajcOHD6Ny5crYsWMHvL29AbA4GQrZF6dcuXLB2dkZoaGhLE4GKm0EKDIy8oPH27dvP/p82kOXl8X+TaFQwMnJ6bNlKO1tvnz5ODpERFmmUCgwfvx4VKlSBV27dsWbN2/w5MkT1KxZE4sWLcLAgQNZnAyE7IsTkDrPKTQ0FOHh4YiMjNT6n4v0Kzk5GdHR0Xj37h3evXuXqeO0YqTP8pOera0t8ubNi7x588LR0VE6/tgj7XUzM7NsyUZEBACNGjVCUFAQOnXqhAsXLiApKQmDBw/G2bNn0aNHD+n9WJzkyyCKk4eHB06dOgUg9XJd1apVxQaSqZSUFMTGxiI2NhYxMTHS2/THn3ubvvSkvdX13J+MsLCwgIODwweP/ypClpaW2Z6ViCizXFxc4O/vj++//x6LFi0CAKxbtw6HDh2S3ofFSb4Mojilv7MuODgYCoUCZ8+exYMHD3D//n3ExsYif/78KFCgAAoUKIAaNWqgUaNGAhMDarUaycnJSEpKkh7x8fFISEhAfHy81uNjz2Xkff9dfkSUnE8xNzf/aPlxcHBAnjx5PvuajY0NFAqF6L8CEZHeWFpaYuHChahRowYGDhyImJgYvHnzRnqdxUm+DK44DRs2DLGxsZ99fzMzM8ydOxcpKSnSQ6VSaZ1/7Ll/n6cVn8TERK0ClJGHSqXS9z+LXiiVStjZ2cHW1ha2trZZPraysmL5ISL6D126dIGXlxe6dOmCoKAg6XkWJ/mS/V51QOrlufTLElAqGxsb5MqVC7ly5ULOnDk/+jYzr9na2nK0h4hIgMTERIwdOxYLFiwAALRp0wZ79+4VnIo+xiCKU3JyMgoXLozXr18DAGrUqIGePXvC09MT7u7u6N+/P/bv359teRQKBXLkyAFLS8sMPywsLGBtbS09rKystM4z85y1tTVy5MjBgkNEZGSOHz+Oo0ePYvDgwShevLjoOPQRBlGcAODatWs4duwYmjZtivLly2u9dvToUTx+/BhmZmYwMzODubm5dPyp5zLyPp8qQbwTi4iIyDQZTHEiIiIiEk353+9CRERERACLExEREVGGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEGsTgRERERZRCLExEREVEG/R9W6l2FVvdfhgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Visualizing shapes"
      ],
      "metadata": {
        "id": "XXV-26X2nXBq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Converting polylines to PNG and SVG for further processing\n"
      ],
      "metadata": {
        "id": "WpKW9Wcc4VEf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "!pip install svgwrite\n",
        "import svgwrite\n",
        "\n",
        "!pip install cairosvg\n",
        "import cairosvg\n",
        "\n",
        "def polylines2svg(paths_XYs, svg_path):\n",
        "    W, H = 0, 0\n",
        "    colours = ['black']  # Define color palette\n",
        "\n",
        "    # Calculate the maximum width and height for the canvas\n",
        "    for path_XYs in paths_XYs:\n",
        "        for XY in path_XYs:\n",
        "            W, H = max(W, np.max(XY[:, 0])), max(H, np.max(XY[:, 1]))\n",
        "\n",
        "    padding = 0.1\n",
        "    W, H = int(W + padding * W), int(H + padding * H)\n",
        "\n",
        "    # Create a new SVG drawing\n",
        "    dwg = svgwrite.Drawing(svg_path, profile='tiny', shape_rendering='crispEdges')\n",
        "    group = dwg.g()\n",
        "\n",
        "    # Generate SVG path data\n",
        "    for i, path in enumerate(paths_XYs):\n",
        "        path_data = []\n",
        "        c = colours[i % len(colours)]  # Cycle through colors for each path\n",
        "        for XY in path:\n",
        "            path_data.append((\"M\", (XY[0, 0], XY[0, 1])))  # Move to starting point\n",
        "            for j in range(1, len(XY)):\n",
        "                path_data.append((\"L\", (XY[j, 0], XY[j, 1])))  # Draw line to next point\n",
        "\n",
        "        # Close path if start and end points are the same\n",
        "        if not np.allclose(path[0], path[-1]):\n",
        "            path_data.append((\"Z\", None))  # Close the path\n",
        "\n",
        "        # Add path to group with specified color and no stroke\n",
        "        group.add(dwg.path(d=\" \".join(f\"{cmd} {','.join(map(str, coords))}\" if coords else cmd for cmd, coords in path_data), fill=c, stroke='none', stroke_width=2))\n",
        "\n",
        "    # Add group to drawing and save\n",
        "    dwg.add(group)\n",
        "    dwg.save()\n",
        "\n",
        "    # Convert SVG to PNG using cairosvg\n",
        "    png_path = svg_path.replace('.svg', '.png')\n",
        "    factor = max(1, 1024 // min(H, W))  # Ensure a minimum size for readability\n",
        "    cairosvg.svg2png(url=svg_path, write_to=png_path, parent_width=W, parent_height=H, output_width=factor * W, output_height=factor * H, background_color='white')\n",
        "\n",
        "    return\n",
        "\n",
        "polylines2svg(shapes, '/content/polylines_output.svg')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "qwLRUtnH1WYJ",
        "outputId": "f44dd23b-5f10-49f1-bff0-f2567aab3a32"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting svgwrite\n",
            "  Downloading svgwrite-1.4.3-py3-none-any.whl.metadata (8.8 kB)\n",
            "Downloading svgwrite-1.4.3-py3-none-any.whl (67 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m67.1/67.1 kB\u001b[0m \u001b[31m1.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        },
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'svgwrite'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-34e4a02e7368>\u001b[0m in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pip install svgwrite'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0msvgwrite\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pip install cairosvg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'svgwrite'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Shape Segmentation"
      ],
      "metadata": {
        "id": "tbgyNLBdLdRC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import cv2\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def segment_and_store_isolated_shapes(image_path):\n",
        "    img = cv2.imread(image_path)\n",
        "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
        "    _, threshold = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)\n",
        "    contours, _ = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
        "\n",
        "    isolated_shapes = []  # List to store each isolated shape\n",
        "\n",
        "    for contour in contours[1:]:  # Skip the first contour as it's the entire image\n",
        "        mask = np.zeros_like(gray)\n",
        "        cv2.drawContours(mask, [contour], -1, 255, -1)\n",
        "        segmented_shape = np.zeros_like(gray)\n",
        "        segmented_shape[mask == 255] = gray[mask == 255]\n",
        "        x, y, w, h = cv2.boundingRect(contour)\n",
        "        cropped = segmented_shape[y:y+h, x:x+w]\n",
        "        isolated = np.full((h, w), 255, dtype=np.uint8)\n",
        "        isolated[mask[y:y+h, x:x+w] == 255] = cropped[mask[y:y+h, x:x+w] == 255]\n",
        "        isolated_shapes.append(isolated)  # Append the isolated shape to the list\n",
        "\n",
        "    return isolated_shapes\n",
        "\n",
        "# Example Usage\n",
        "image_path = 'isolated.png'\n",
        "isolated_shapes = segment_and_store_isolated_shapes(image_path)\n",
        "print(isolated_shapes)\n",
        "\n",
        "# You can access any isolated shape like this:\n",
        "for idx, shape in enumerate(isolated_shapes, start=1):\n",
        "    plt.imshow(shape, cmap='gray')\n",
        "    plt.title(f'Shape {idx}')\n",
        "    plt.axis('off')\n",
        "    plt.show()\n"
      ],
      "metadata": {
        "id": "dGfi2JsTLhqC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "32af5e7a-24a5-43d4-b477-90237e9a297d"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[array([[255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       ...,\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8), array([[255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       ...,\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8), array([[255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       ...,\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8), array([[255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       ...,\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8), array([[255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       ...,\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255],\n",
            "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8)]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Shape Identification"
      ],
      "metadata": {
        "id": "XGRDV4bgAaVS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Uses weight file from pretrained CNN model with 99.26& accuracy, refer to Shape_Identification notebook for detailed insights on how the model was trained"
      ],
      "metadata": {
        "id": "Tu0ISeMeBlj7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Download pretained weights (.h5) model file from the public Github repository"
      ],
      "metadata": {
        "id": "awqjNVq-GLbl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget 'https://raw.githubusercontent.com/thejediboySHASHANK/Google-Doodle-Classes/main/keras.h5'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-1D729BeGS1y",
        "outputId": "eae1bc1f-7a83-40f5-f6b5-9c9d0f1c87d2"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-08-12 10:54:12--  https://raw.githubusercontent.com/thejediboySHASHANK/Google-Doodle-Classes/main/keras.h5\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1225792 (1.2M) [application/octet-stream]\n",
            "Saving to: ‘keras.h5.1’\n",
            "\n",
            "\rkeras.h5.1            0%[                    ]       0  --.-KB/s               \rkeras.h5.1          100%[===================>]   1.17M  --.-KB/s    in 0.06s   \n",
            "\n",
            "2024-08-12 10:54:12 (18.4 MB/s) - ‘keras.h5.1’ saved [1225792/1225792]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Load Classes file from public Github repositories"
      ],
      "metadata": {
        "id": "YfN_asR7Hklx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget 'https://raw.githubusercontent.com/thejediboySHASHANK/Google-Doodle-Classes/main/mini_classes.txt'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W6iy9zxEHn_S",
        "outputId": "acb48bcb-24aa-43a8-840e-16031a398a87"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-08-12 10:54:14--  https://raw.githubusercontent.com/thejediboySHASHANK/Google-Doodle-Classes/main/mini_classes.txt\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 66 [text/plain]\n",
            "Saving to: ‘mini_classes.txt.1’\n",
            "\n",
            "\rmini_classes.txt.1    0%[                    ]       0  --.-KB/s               \rmini_classes.txt.1  100%[===================>]      66  --.-KB/s    in 0s      \n",
            "\n",
            "2024-08-12 10:54:14 (1.29 MB/s) - ‘mini_classes.txt.1’ saved [66/66]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Read the Classes Name"
      ],
      "metadata": {
        "id": "z_sMmbb7IBin"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "f = open(\"mini_classes.txt\", \"r\")\n",
        "#And for the purpose of reading\n",
        "classes = f.readlines()\n",
        "f.close()"
      ],
      "metadata": {
        "id": "GVvnqUtfIA4v"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "classes = [c.replace('\\n', '').replace(' ', '_') for c in classes]\n",
        "\n",
        "print(classes)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fG29HgwuHr0s",
        "outputId": "ee5b6cb5-b2ec-46ad-b7db-4e86074d933c"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['circle', 'hexagon', 'line', 'octagon', 'square', 'star', 'triangle', 'suitcase']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from tensorflow import keras\n",
        "\n",
        "class_names = []\n",
        "# Append the new classes\n",
        "class_names.extend(classes)\n",
        "\n",
        "print(class_names)\n",
        "\n",
        "def prepare_custom_image(image_path, image_size=28):\n",
        "    # Load the image\n",
        "    img = Image.open(image_path).convert('L')  # Convert to grayscale\n",
        "\n",
        "    # Resize image\n",
        "    img = img.resize((image_size, image_size), Image.ANTIALIAS)\n",
        "\n",
        "    # Convert to numpy array and normalize\n",
        "    img_array = np.array(img, dtype=np.float32) / 255.0\n",
        "\n",
        "    # Invert the image to match training data style\n",
        "    img_array = 1 - img_array  # Subtract from 1 to invert the grayscale values\n",
        "\n",
        "    # Reshape the array to fit the model input\n",
        "    img_array = img_array.reshape(1, image_size, image_size, 1)\n",
        "\n",
        "    return img_array\n",
        "\n",
        "# Path to your custom image and model\n",
        "image_path = 'star.png'\n",
        "model_path = 'keras.h5'\n",
        "\n",
        "# Load the model\n",
        "model = keras.models.load_model(model_path)\n",
        "\n",
        "# Prepare the image\n",
        "custom_img = prepare_custom_image(image_path)\n",
        "\n",
        "# Display the processed image\n",
        "plt.imshow(custom_img.reshape(28, 28), cmap='gray')\n",
        "plt.title(\"Processed Custom Image\")\n",
        "plt.axis('off')\n",
        "plt.show()\n",
        "\n",
        "# from PIL import Image\n",
        "# import numpy as np\n",
        "# import matplotlib.pyplot as plt\n",
        "# from tensorflow import keras\n",
        "\n",
        "# # Assuming class_names is already defined and populated correctly as shown in previous responses\n",
        "# class_names = []\n",
        "# # Append the new classes\n",
        "# class_names.extend(classes)\n",
        "\n",
        "# def prepare_image_for_model(image, image_size=28):\n",
        "#     # Convert image to grayscale and resize\n",
        "#     img = Image.fromarray(image).convert('L')\n",
        "#     img = img.resize((image_size, image_size), Image.ANTIALIAS)\n",
        "\n",
        "#     # Convert to numpy array and normalize\n",
        "#     img_array = np.array(img, dtype=np.float32) / 255.0\n",
        "\n",
        "#     # Invert the image to match training data style\n",
        "#     img_array = 1 - img_array  # Subtract from 1 to invert the grayscale values\n",
        "\n",
        "#     # Reshape the array to fit the model input\n",
        "#     img_array = img_array.reshape(1, image_size, image_size, 1)\n",
        "\n",
        "#     return img_array\n",
        "\n",
        "# model_path = 'keras.h5'\n",
        "# model = keras.models.load_model(model_path)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wB-YMG8RAdo-",
        "outputId": "9c9e5e71-6e2a-4466-ca82-51a13f323cb0"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Predicting the Custom Image shape"
      ],
      "metadata": {
        "id": "gpPbnF0HCCxG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Corrected prediction call\n",
        "pred = model.predict(custom_img)[0]\n",
        "ind = (-pred).argsort()[:5]\n",
        "latex = [class_names[x] for x in ind]\n",
        "print(latex)\n",
        "\n",
        "\n",
        "# predictions = []\n",
        "# for i, shape in enumerate(isolated_shapes):\n",
        "#     processed_img = prepare_image_for_model(shape)\n",
        "#     pred = model.predict(processed_img)[0]\n",
        "#     ind = (-pred).argsort()[:5]\n",
        "#     predicted_labels = [class_names[x] for x in ind]\n",
        "#     predictions.append(predicted_labels)\n",
        "\n",
        "#     # Plot the image that was input to the model\n",
        "#     plt.imshow(processed_img.reshape(28, 28), cmap='gray')\n",
        "#     plt.title(f\"Shape {i+1}: {', '.join(predicted_labels)}\")\n",
        "#     plt.axis('off')\n",
        "#     plt.show()\n",
        "\n",
        "# # Print out predictions for verification\n",
        "# for idx, pred in enumerate(predictions, 1):\n",
        "#     print(f\"Shape {idx}: {pred}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Df5uUvxtCFjV",
        "outputId": "fa317db9-446c-42a3-e3bb-495a88ab9568"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 112ms/step\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-24-9b654826d131>:59: DeprecationWarning: ANTIALIAS is deprecated and will be removed in Pillow 10 (2023-07-01). Use LANCZOS or Resampling.LANCZOS instead.\n",
            "  img = img.resize((image_size, image_size), Image.ANTIALIAS)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 27ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 29ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaIAAAGbCAYAAACGfpQKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAo80lEQVR4nO3dfZzNdf7/8ecxxhgzY8bVhJkYV80sg3VVu3I1aGnJEglbBhv7RfarUqvtS3IdFSKDtkSq7eaiWEW0O6gNX6Us9R3JDmW6GLlal5F5/f7oN+fmmBGfz87Mu/S4327+mM/5vD4X788553k+5/M5LwEzMwEA4Egp1xsAAPhpI4gAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcKrYgCgQCuvvuu4tr8T86AwYMUFJSUsi0QCCgcePGOdkeFI1x48YpEAjo66+/dr0pP0nt2rVTu3btXG9G0A/lNf3cc88pEAho3759RbK8ffv2KRAI6LnnniuS5V3McxDt3LlTvXr1Us2aNVW2bFklJCTopptu0uzZs4tj+0rc559/rjvuuEPJycmKiYlRXFycrr/+ei1atEh0Q7pyc+fOLbYnLa4+n3/+ucaNG6cPPvjA9abAgdJeZn7nnXeUlpamGjVqaPDgwapatao+++wzbdmyRbNmzdKIESOKaztLzNdff60DBw6oV69eqlGjhs6dO6f169drwIAB2r17tyZPnlxk6zp9+rRKl/Z0CH405s6dq8qVK2vAgAGuNwU/Ap9//rkeeeQRJSUl6ec///kV161bt674NupH7M4771SfPn0UERHhelOuiKd3wUmTJik2Nlbbtm1TXFxcyGO5ublFuV3ONGrUSBs2bAiZdvfdd+uWW27Rk08+qQkTJigsLKxI1lW2bNkiWQ7wU3Pq1CmVK1dOZcqUcb0pP0hhYWGXfZ8yM505c0aRkZEltFWX5umrub1796pBgwYFQkiS4uPjC6159dVXlZqaqoiICDVo0EBr164NeXz//v0aNmyYkpOTFRkZqUqVKum2224r8N1m/neemzZt0u9//3tVqlRJ5cuXV//+/XXkyJEC612zZo1at26tqKgoxcTEqEuXLvrwww+97G6IpKQknTp1SmfPng1OO3XqlLKysnxfH7j4++T86w2ffPKJBgwYoLi4OMXGxmrgwIE6depUgfolS5aoWbNmioyMVMWKFdWnTx999tlnvrZFkk6ePKn77rtP1157rSIiIpScnKzHHnus0K8klyxZouuvv17lypVThQoV1KZNm+Cn06SkJH344YfauHGjAoGAAoFA8Hv8w4cPa9SoUWrYsKGio6NVvnx53XzzzdqxY0eBdezfv1/dunVTVFSU4uPjdc899+iNN95QIBAo8GFh6dKlwbGoXLmy7rjjDuXk5ITMM2DAAEVHRysnJ0fdu3dXdHS0qlSpolGjRun8+fO+x02Sjh49WiTHbOHChQoEAnr22WdD6iZPnqxAIKDXX389OO2xxx5Ty5YtValSJUVGRqpZs2ZatmxZgXWePn1af/jDH1S5cmXFxMSoW7duysnJKfR6xvvvv6+bb75Z5cuXV3R0tDp06KAtW7aEzJP/WvzHP/6he++9V1WqVFFUVJR69OihgwcPeh67DRs2qEWLFpKkgQMHBp8z+V/ttmvXTqmpqXrvvffUpk0blStXTn/605+Cj114jejs2bMaO3asmjVrptjYWEVFRal169bKzMwMWWf+NY/HHntMCxYsUJ06dRQREaEWLVpo27ZtBbZx6dKlql+/vsqWLavU1FS98sorhV73LUxOTo4GDRqka665Jvg+ePHx9SorK0u9e/dWlSpVFBkZqeTkZD300EPBxwu7RpSUlKSuXbvqjTfeUPPmzRUZGan58+dL+u75e8899ygpKUkRERFKTExU//79L/velpWVpV69eqlixYoqW7asmjdvrlWrVnnfIfPgV7/6lcXExNjOnTsvO68ka9y4sVWrVs0mTJhgM2fOtNq1a1u5cuXs66+/Ds63dOlSa9y4sY0dO9YWLFhgf/rTn6xChQpWs2ZNO3nyZHC+hQsXmiRr2LChtW7d2p588kkbPny4lSpVytq0aWN5eXnBeRcvXmyBQMA6d+5ss2fPtkcffdSSkpIsLi7OsrOzr2hfT506ZQcPHrTs7Gx77rnnLCoqylq2bBkyT2Zmpkmyhx9++LLLS09Pt5o1axYYowtrH374YZNkTZo0sVtvvdXmzp1rd911l0myBx54IKR24sSJFggE7Pbbb7e5c+faI488YpUrV7akpCQ7cuTIFe3jhfLy8qx9+/YWCATsrrvusjlz5tgtt9xikmzkyJEh844bN84kWcuWLW369Ok2a9Ys69evn/3xj380M7NXXnnFEhMTLSUlxZ5//nl7/vnnbd26dWZmtm3bNqtTp46NHj3a5s+fb+PHj7eEhASLjY21nJyc4DpOnDhhtWvXtsjISBs9erTNnDnTrr/+emvcuLFJsszMzOC8+c+NFi1a2IwZM2z06NEWGRlZYCzS09OtbNmy1qBBAxs0aJBlZGRYz549TZLNnTvX85iZFc8x69q1q8XGxtqnn35qZmb//Oc/rUyZMva73/0uZHmJiYk2bNgwmzNnjj3xxBN2/fXXmyRbvXp1yHy9e/c2SXbnnXfaU089Zb179w6O44XPv127dllUVFTwNTt16lSrVauWRURE2JYtWwqMd5MmTax9+/Y2e/Zsu++++ywsLMx69+7teQy//PJLGz9+vEmyIUOGBJ8ze/fuNTOztm3bWtWqVa1KlSo2YsQImz9/vr366qvBx9q2bRtc1sGDB61atWp27733WkZGhk2bNs2Sk5MtPDzc3n///eB82dnZwX2oW7euPfroozZt2jSrXLmyJSYm2tmzZ4Pzrl692gKBgDVq1MieeOIJGzNmjFWoUMFSU1Mv+5r+8ssvLTEx0a699lobP368ZWRkWLdu3UySzZgxw/NYmZnt2LHDypcvb5UqVbIHH3zQ5s+fbw888IA1bNgwOE/+Mbrw/a5mzZpWt25dq1Chgo0ePdrmzZtnmZmZdvz4cUtNTbWwsDAbPHiwZWRk2IQJE6xFixbBMcsfr4ULFwaXt2vXLouNjbX69evbo48+anPmzLE2bdpYIBCwFStWeNonT0G0bt06CwsLs7CwMPvlL39pDzzwgL3xxhshBy24YMnKlCljn3zySXDajh07TJLNnj07OO3UqVMFajdv3mySbPHixcFp+QPbrFmzkPVNmzbNJNnKlSvNzOz48eMWFxdngwcPDlnml19+abGxsQWmX8qUKVNMUvBfhw4dgm8M+YoriAYNGhQyX48ePaxSpUrBv/ft22dhYWE2adKkkPl27txppUuXLjD9Srz66qsmySZOnBgyvVevXhYIBILHcc+ePVaqVCnr0aOHnT9/PmTeCz8MNGjQIOQNIt+ZM2cK1GVnZ1tERISNHz8+OO3xxx83ScE3HDOz06dPW0pKSkgQnT171uLj4y01NdVOnz4dnHf16tUmycaOHRuclp6ebpJC1mNm1qRJE2vWrNn3Dc8lFccx++KLL6xixYp200032TfffGNNmjSxGjVq2LFjx0JqL37tnD171lJTU619+/bBae+9916hHyYGDBhQ4PnXvXt3K1OmTDAAzMw+//xzi4mJsTZt2gSn5b8WO3bsGHLM77nnHgsLC7OjR49ecrwuZdu2bQXe6PK1bdvWJNm8efMKfezC59m3335r33zzTcg8R44csWuuuSbkGOW/sVaqVMkOHz4cnL5y5UqTZH/961+D0xo2bGiJiYl2/Pjx4LQNGzaYpMu+pn/3u99ZtWrVQj58m5n16dPHYmNjC33/u5w2bdpYTEyM7d+/P2T6hcfiUkEkydauXRtSN3bsWJNUaHjkL7OwIOrQoYM1bNjQzpw5EzJ/y5YtrV69ep72ydNXczfddJM2b96sbt26aceOHZo2bZo6deqkhISEQk/HOnbsqDp16gT/btSokcqXL69//etfwWkXfj957tw5HTp0SHXr1lVcXJy2b99eYJlDhgxReHh48O+hQ4eqdOnSwa8s1q9fr6NHj6pv3776+uuvg//CwsJ0ww03FDhFv5S+fftq/fr1evHFF9WvXz9J333FcaF27drJzIr8ds3/+q//Cvm7devWOnTokP79739LklasWKG8vDz17t07ZB+rVq2qevXqXfE+Xuj1119XWFiY/vCHP4RMv++++2RmWrNmjaTvvmrNy8vT2LFjVapU6NMnEAhcdj0RERHBuvPnz+vQoUOKjo5WcnJyyPFeu3atEhIS1K1bt+C0smXLavDgwSHLe/fdd5Wbm6thw4aFXHPr0qWLUlJS9NprrxXYhsLG98LnpB9FecyqVq2qp556SuvXr1fr1q31wQcf6Nlnn1X58uVD1nHha+fIkSM6duyYWrduXWAcJWnYsGEhtRffWHT+/HmtW7dO3bt3V+3atYPTq1Wrpn79+untt98O7ku+IUOGhBzz1q1b6/z589q/f//lB8yjiIgIDRw48LLzhYWFBa8b5eXl6fDhw/r222/VvHnzQt9Pbr/9dlWoUCH4d+vWrSUp+Hz4/PPPtXPnTvXv31/R0dHB+dq2bauGDRt+77aYmZYvX65bbrlFZhZy3Dt16qRjx44Vuk3f5+DBg9q0aZMGDRqkGjVqhDx2Ja+/WrVqqVOnTiHTli9frsaNG6tHjx4F5r/UMg8fPqy///3v6t27t44fPx7cr0OHDqlTp07as2dPga/Gv4/nW7ZatGihFStW6OzZs9qxY4deeeUVzZgxQ7169dIHH3yg+vXrB+e9eKAkqUKFCiHXdE6fPq0pU6Zo4cKFysnJCbkecezYsQL19erVC/k7Ojpa1apVC34XumfPHklS+/btC93+i1/Ml1KzZk3VrFlT0nehNGTIEHXs2FG7d+8u9ot7F49b/gvlyJEjKl++vPbs2SMzKzAW+S4M6iu1f/9+Va9eXTExMSHTf/aznwUfl767TliqVKmQ4+xFXl6eZs2apblz5yo7Ozvk2kylSpVCtqdOnToFXgh169YtsN2SlJycXGBdKSkpevvtt0OmlS1bVlWqVAmZdvFz0o+iPmZ9+vTRkiVL9Nprr2nIkCHq0KFDgZrVq1dr4sSJ+uCDD/TNN98Ep184Zvv371epUqVUq1atkNqLx/HgwYM6depUoeP4s5/9THl5efrss8/UoEGDK9rnopaQkHDFNyYsWrRIjz/+uLKysnTu3Lng9IvHQLr8PuQ/vy4er/xp3xckBw8e1NGjR7VgwQItWLCg0Hm83uSVH5Cpqame6vIVNgZ79+5Vz549PS3nk08+kZlpzJgxGjNmTKHz5ObmKiEh4YqW5/ve4TJlyqhFixZq0aKFrrvuOg0cOFBLly7Vww8/HJznUndtXBg2I0aM0MKFCzVy5Ej98pe/VGxsrAKBgPr06aO8vDzP25Vf8/zzz6tq1aoFHvd7u3SvXr309NNPa9OmTQU+URS1y41bXl6eAoGA1qxZU+i8F35y+6GZPHmyxowZo0GDBmnChAmqWLGiSpUqpZEjR/o63l4V1R2PV7pcv8fs0KFDevfddyVJH330kfLy8kLOQN966y1169ZNbdq00dy5c1WtWjWFh4dr4cKFevHFF4tqt77Xlby+i8qVfvhbsmSJBgwYoO7du+v+++9XfHy8wsLCNGXKFO3du7fA/MW5D/nP5zvuuEPp6emFztOoUaP/eD1eFNWH6Px9GzVq1CXfDwsL70spkh+xNG/eXJL0xRdfeK5dtmyZ0tPT9fjjjwennTlzRkePHi10/j179igtLS3494kTJ/TFF1/o17/+tSQFvwqMj49Xx44dPW/PpeR/LVfYWVpJq1OnjsxMtWrV0nXXXVcky6xZs6befPNNHT9+POSsKCsrK/h4/rrz8vL00Ucffe/vPS51Sr9s2TKlpaXpmWeeCZl+9OhRVa5cOWR7PvroI5lZyLI++eSTAtstSbt37y5wFrx79+7g4655PWbDhw/X8ePHNWXKFD344IOaOXOm7r333uDjy5cvV9myZfXGG2+E/FZk4cKFIcupWbOm8vLylJ2dHXI2dvE4VqlSReXKldPu3bsLbEtWVpZKlSqla6+99or316sr+VrpSixbtky1a9fWihUrQpZ54QdkL/KfPxeP16WmXahKlSqKiYnR+fPni+y9KP9r0127dhXJ8qTvnptel5e/HeHh4UWyb56uEWVmZhb6SSH/+kxhp/WXExYWVmCZs2fPvuTttAsWLAg53c7IyNC3336rm2++WZLUqVMnlS9fXpMnTw6ZL9/lbi+91OPPPPOMAoGAmjZtGpz2n96+7dett96qsLAwPfLIIwXGzsx06NAhz8v89a9/rfPnz2vOnDkh02fMmKFAIBAc3+7du6tUqVIaP358gTOYC7clKiqq0A8ThR3vpUuXFvg+uVOnTsrJyQm59njmzBk9/fTTIfM1b95c8fHxmjdvXsjXU2vWrNH//d//qUuXLlew98XPyzFbtmyZXn75ZU2dOlWjR49Wnz599D//8z/6+OOPg/OEhYUpEAiEvE727dunV199NWTZ+Z9W586dGzL94k4oYWFh+tWvfqWVK1eG3PL71Vdf6cUXX1SrVq2u+GttP6KioiTpkh9Ar1T+Gc6FY7x161Zt3rzZ1/KqV6+u1NRULV68WCdOnAhO37hxo3bu3HnZbenZs6eWL19e6Bu9n1vdq1SpojZt2ujZZ5/Vp59+GvKY37O4nj17Bi+zXOxSy4yPj1e7du00f/78Qk9AvO6bpzOiESNG6NSpU+rRo4dSUlJ09uxZvfPOO3r55ZeVlJR0RRcTL9a1a1c9//zzio2NVf369bV582a9+eabIdcLLnT27Fl16NBBvXv31u7duzV37ly1atUqeFG7fPnyysjI0J133qmmTZuqT58+qlKlij799FO99tpruvHGGwu82V5o0qRJ+sc//qHOnTurRo0aOnz4sJYvX65t27ZpxIgRIaeb//u//6u0tDQ9/PDDJdpfqk6dOpo4caIefPBB7du3T927d1dMTIyys7P1yiuvaMiQIRo1apSk736jcSXbeMsttygtLU0PPfSQ9u3bp8aNG2vdunVauXKlRo4cGTzTrFu3rh566CFNmDBBrVu31q233qqIiAht27ZN1atX15QpUyRJzZo1U0ZGhiZOnKi6desqPj5e7du3V9euXTV+/HgNHDhQLVu21M6dO/XCCy+EXCCXpN///veaM2eO+vbtq//+7/9WtWrV9MILLwRvSMj/tBseHq5HH31UAwcOVNu2bdW3b1999dVXmjVrlpKSknTPPff4GuMBAwZo0aJFys7OvqLfilzOlR6z3NxcDR06VGlpacFejXPmzFFmZqYGDBigt99+W6VKlVKXLl30xBNPqHPnzurXr59yc3P11FNPqW7duvrnP/8ZXG+zZs3Us2dPzZw5U4cOHdIvfvELbdy4MRhqF541TJw4UevXr1erVq00bNgwlS5dWvPnz9c333yjadOm+drv5557TgMHDtTChQu/t8tGnTp1FBcXp3nz5ikmJkZRUVG64YYbCr2m8X26du2qFStWqEePHurSpYuys7M1b9481a9fPyRIvJg8ebJ+85vf6MYbb9TAgQN15MgRzZkzR6mpqZdd5tSpU5WZmakbbrhBgwcPVv369XX48GFt375db775pg4fPhyct127dtq4ceNlA+XJJ59Uq1at1LRpUw0ZMkS1atXSvn379Nprr/lqkXT//fdr2bJluu222zRo0CA1a9ZMhw8f1qpVqzRv3jw1bty40LqnnnpKrVq1UsOGDTV48GDVrl1bX331lTZv3qwDBw4U+tvAS/Jyi92aNWts0KBBlpKSYtHR0VamTBmrW7eujRgxwr766quQeSXZ8OHDCyyjZs2alp6eHvz7yJEjNnDgQKtcubJFR0dbp06dLCsrq8B8+bcjbty40YYMGWIVKlSw6Oho++1vf2uHDh0qsJ7MzEzr1KmTxcbGWtmyZa1OnTo2YMAAe/fdd793H9etW2ddu3a16tWrW3h4uMXExNiNN95oCxcuDLk9Mn8dKobbtw8ePBgyX2G3YpqZLV++3Fq1amVRUVEWFRVlKSkpNnz4cNu9e3dwnr/+9a+XvPX1YsePH7d77rknuO/16tWz6dOnF9hvM7Nnn33WmjRpYhEREVahQgVr27atrV+/Pvj4l19+aV26dLGYmBiTFLzF9syZM3bfffdZtWrVLDIy0m688UbbvHlzgdtwzcz+9a9/WZcuXSwyMtKqVKli9913ny1fvtwkhfyuxczs5ZdfDm5PxYoV7be//a0dOHAgZJ709HSLiooqsC/5436hnj17WmRk5GV/k1XUx+zWW2+1mJgY27dvX0hd/m3Fjz76aHDaM888Y/Xq1bOIiAhLSUmxhQsXFrovJ0+etOHDh1vFihUtOjraunfvbrt37zZJNnXq1JB5t2/fbp06dbLo6GgrV66cpaWl2TvvvFPovm3bti1kev7r4cLfeM2ePbvQW4YLs3LlSqtfv76VLl065Fbhtm3bWoMGDQqtufh5k5eXZ5MnT7aaNWtaRESENWnSxFavXl3g9Zd/O/L06dMLLLOw1/Rf/vIXS0lJsYiICEtNTbVVq1ZZz549LSUl5bK1X331lQ0fPtyuvfZaCw8Pt6pVq1qHDh1swYIFIfM1a9bMqlat+v2D9P/t2rXLevToYXFxcVa2bFlLTk62MWPGBB+/1O3bXbp0KXR5hw4dsrvvvtsSEhKsTJkylpiYaOnp6cHbzgu7fdvMbO/evda/f3+rWrWqhYeHW0JCgnXt2tWWLVt2RfuRz1MQuXSpJz++3/3332+JiYkh9/r/mM2YMcMkFQiZohYfH2+jRo0q1nW49P7775skW7JkSbGu57bbbrMWLVoU6zpcady4sXXs2LFIlvXvf//bSpcubXPmzCmS5f3Y8P8RXeUyMzM1ZsyYH03zwwtd/LutM2fOaP78+apXr94V3xbqx4cffqjTp0/rj3/8Y7GtoyRdPI6SNHPmTJUqVUpt2rQptvWamTZs2KCJEycW2zpKwrlz5/Ttt9+GTNuwYYN27NhRZP8FxaZNm5SQkFDgd3I/FVdn62cEFdY368fi1ltvVY0aNfTzn/9cx44d05IlS5SVlaUXXnihWNfboEGDAj/e/DGbNm2a3nvvPaWlpal06dJas2aN1qxZoyFDhhT7nXBXQzPknJwcdezYUXfccYeqV6+urKwszZs3T1WrVi3wQ2a/unTp8oO5scYFggg/WJ06ddKf//xnvfDCCzp//rzq16+vv/zlL7r99ttdb9qPSsuWLbV+/XpNmDBBJ06cUI0aNTRu3LiQJpm4tAoVKqhZs2b685//rIMHDyoqKkpdunTR1KlTL3lTFbwJmPG/vQEA3OEaEQDAKYIIAOBUsV8jKqrWHUBJ8NMwtrAOHpezadMmzzX5HdC9yv+RsRclNQ74cSjuKzicEQEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAU/zHeLhqlVTjzltuucVzzdatWz3XLF682HONXzQwRUnijAgA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnKLpKa5afhp3JiQkeK75xS9+4bnm9ddf91zTv39/zzWSNGXKFM81JdUwFpA4IwIAOEYQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTdN/GD56fTtCSv27Qw4YN81zz9NNPe65JTEz0XBMdHe25Bvgx4IwIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJyi6Sl+8Pw0L5WkhIQEzzW5ubmea/bt2+e55pprrvFcc+LECc81wI8BZ0QAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRNT1GiwsPDPdf4bXo6ePBgzzUvvviir3V5dfLkSc81fhqlAj8GnBEBAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFNXTdNTP800Jf8NNeGPn/FOSkryta74+HjPNR9//LGvdXmVm5tbIusBfgw4IwIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAAp4q96WlCQoLnmpycHM81P/TmpX6bsnpVkuPgZ5/8bN/NN9/suUaSVq1a5auuJBw5csRzTVRUVDFsSeF+6K8nXF04IwIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTxd59+8CBA55rZs2aVSLrkaQtW7Z4rtm6davnmquxm3FJ7VNycrKvusWLFxfxlhQdP2Pnd7z9dO0+efKkr3UBfnBGBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOFXvT0379+nmuiY+P91zjp3mpJKWnp3uuGTZsmOeao0ePeq7ZuXOn55qsrCzPNZKUk5PjuSY3N9dzjd8Gpn74adwZHh5eDFtSkJ8GpmfPnvW1rlq1anmu2b17t691wZ+rsSmyF5wRAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTxd709KWXXvJcM3ToUM81FSpU8Fwj+Wtg6qcxZsOGDT3XpKameq7p2LGj5xrJ3/gdOXLEc42fhrYZGRmea/zy03yypBqlZmdn+6rz89zbtWuXr3Xhh6+knq9ecEYEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4FzMyKcwVlypTxXOOn8eTcuXM910jSW2+95bnGTyNX4D/lpwmuJE2ePNlzzYkTJzzX5OTkeK45fPiw55qUlBTPNZK0fft2zzV+mgEfOHDAc01WVpbnGknaunWr5xo/76/FHBOcEQEA3CKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMCpYu++HQgEinPx/7G77rrLc014eLjnmoyMDM81fvjZth86P92C8Z+Ji4vzXBMVFeW5xs/ztWLFip5r/IqPj/dcU6tWLc81iYmJnmskf/+7wc6dOz3XLFq0yHONF5wRAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTP/mmp3507tzZc02HDh0818ycOdNzTU5OjucaAG75aTIr+WvaPHjwYM811113necaLzgjAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnaHpaQvw0DUxPT/dcM336dM81knT06FFfdUC+8PDwElnPuXPnSmQ9ktS0aVPPNT179vRcExUV5blGktauXVsiNcUcE5wRAQDcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTND31wU9zRz+NGhMSEjzXdOvWzXONJL300kuea2iUChfS0tJ81fXr189zzcmTJz3X+Hktbd261XNNSaLpKQDgqkYQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAAp2h6WkJKqlFq586dPddIUq1atTzXZGRkeK4pqXHAfyYuLs5zTa9evTzXtG7d2nPNkSNHPNdIV2cz0pJC01MAwFWNIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAAp0q73gAUrdTUVF917733XhFvSeHopF3ybrjhBs8106dP91yzatUqzzWTJk3yXPPxxx97rvGLbvElgzMiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKpqc/YFFRUZ5rEhMTfa1r1qxZvupKgp/GkxLNJ/NlZ2d7rnnrrbc81zz22GOea/woyecDz6GSwRkRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhF01Mf/DRd9NM8cdSoUZ5r1q5d67lG8rd9JTUOfhtPJiUlea45deqU55rc3FzPNX74bfbpZ/v81KSlpXmuyczM9FxDI9KrD2dEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAODUT77paUk17vTTEDIiIsJzjd+mp374GYe4uDjPNenp6Z5rJCk5OdlzzcmTJz3XzJw503NNTk6O55qSbPa5Zs0azzXDhg3zXOOn6anf5q80S/3h4owIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJz6yTc99dMIMSEhwXPNb37zG881I0eO9Fzjl59mpH379vVc07RpU881f//73z3XSNKsWbM81/g5tn6O07hx4zzX+GnIKvlrEvrxxx/7WpdX8fHxnmtyc3OLYUvgEmdEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcCpgZlasKwgEinPx/7GoqCjPNZMmTfJc89BDD3mu8dM1eejQoZ5rJCklJcVzzd/+9jfPNS+99JLnGj8d0iV/4+dnXdddd53nmn79+nmu8dOxWyq5cejfv3+JrMfPc0gquXG4GhVzTHBGBABwiyACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABO/eSbnvpp1Jibm+u5Jj4+3nNNt27dPNesXbvWc40kLVq0yHPN1dgQsqQaY6alpXmuadSokecaSZo1a5avOq/8NH8dOXKk55phw4Z5rpFoevqfoOkpAOCqRhABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnSrvegKLip+GiJN1///2ea5YvX+65Zvfu3Z5revXq5bmmJF2NTST9bJ+fccjMzPRcU7VqVc81kjR06FDPNRkZGZ5rsrOzPdf4GTs/NdIP/7n3U8YZEQDAKYIIAOAUQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4VexNT0uqMWZycrLnGknasmWL55rp06d7rjl58qTnGj9KsiEkTSS/U1KNUl966SXPNZK/pqf9+/f3XLN48WLPNX7GLj4+3nONJOXk5PiqQ/HjjAgA4BRBBABwiiACADhFEAEAnCKIAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABOBczMinUFgUBxLh74ySjJzup+Onbn5uZ6rvHTSXvr1q2eayRp+/btvuogFXNMcEYEAHCLIAIAOEUQAQCcIogAAE4RRAAApwgiAIBTBBEAwCmCCADgFEEEAHCKIAIAOEUQAQCcIogAAE795Jue+mkk6aeJJOBKST3HO3fu7Llm0aJFnmv69OnjuUaSMjMzfdWBpqcAgKscQQQAcIogAgA4RRABAJwiiAAAThFEAACnCCIAgFMEEQDAKYIIAOAUQQQAcIogAgA4RRABAJwq9qanAAB8H86IAABOEUQAAKcIIgCAUwQRAMApgggA4BRBBABwiiACADhFEAEAnCKIAABO/T+Ikys6xtX8AAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 27ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 28ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape 1: ['line', 'octagon', 'hexagon', 'triangle', 'circle']\n",
            "Shape 2: ['line', 'octagon', 'hexagon', 'star', 'triangle']\n",
            "Shape 3: ['line', 'octagon', 'hexagon', 'triangle', 'circle']\n",
            "Shape 4: ['octagon', 'line', 'hexagon', 'suitcase', 'triangle']\n",
            "Shape 5: ['line', 'octagon', 'hexagon', 'triangle', 'circle']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Shape Symmetry Identification"
      ],
      "metadata": {
        "id": "zWF0N5EtkhvL"
      }
    }
  ]
}