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Face Recognition Using Eigen Faces

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{
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  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "Used the approach mentioned in the research paper by Matthew Turk and Alex Pentland, for face recognition using Eigenfaces. The algorithm was implemented using basic matrix algebra and numpy. <br>\n",
        "Link to the research paper: https://ieeexplore.ieee.org/document/139758 <br>\n",
        "Google Colab Notebook: https://colab.research.google.com/drive/1InXv7hbjSBRkuLZgpf9SCFQcxu2m924B#scrollTo=Hj2uRB2ke4Vy"
      ],
      "metadata": {
        "id": "92bQUTh4CPXg"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vHxEROwMLXOM",
        "outputId": "7c9599a0-aefb-449e-c482-dee75bed4570"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (4.6.0.66)\n",
            "Requirement already satisfied: numpy>=1.14.5 in /usr/local/lib/python3.7/dist-packages (from opencv-python) (1.21.6)\n"
          ]
        }
      ],
      "source": [
        "!pip install opencv-python"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# taken from this StackOverflow answer: https://stackoverflow.com/a/39225039\n",
        "import requests\n",
        "\n",
        "def download_file_from_google_drive(id, destination):\n",
        "    URL = \"https://docs.google.com/uc?export=download\"\n",
        "\n",
        "    session = requests.Session()\n",
        "\n",
        "    response = session.get(URL, params = { 'id' : id }, stream = True)\n",
        "    token = get_confirm_token(response)\n",
        "\n",
        "    if token:\n",
        "        params = { 'id' : id, 'confirm' : token }\n",
        "        response = session.get(URL, params = params, stream = True)\n",
        "\n",
        "    save_response_content(response, destination)    \n",
        "\n",
        "def get_confirm_token(response):\n",
        "    for key, value in response.cookies.items():\n",
        "        if key.startswith('download_warning'):\n",
        "            return value\n",
        "\n",
        "    return None\n",
        "\n",
        "def save_response_content(response, destination):\n",
        "    CHUNK_SIZE = 32768\n",
        "\n",
        "    with open(destination, \"wb\") as f:\n",
        "        for chunk in response.iter_content(CHUNK_SIZE):\n",
        "            if chunk: # filter out keep-alive new chunks\n",
        "                f.write(chunk)"
      ],
      "metadata": {
        "id": "RV2ZZg9aLbBA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "The dataset used was the AT&T dataset, where 10 different images of 40 distinct subjects were given. The 10 images of the same person were taken under varying circumstances, like different lighting, facial expressions and facial accessories. <br>\n",
        "\n",
        "We took two images of each of the 40 people for testing. The model was trained on 8 images of the first 20 people. We did this so that we can calculate the accuracy for people both inside and outside our training set. <br>\n",
        "\n",
        "On running the code, train_small.zip, test1.zip and test2.zip will appear in the contents folder. These signify the following:\n",
        "<ol>\n",
        "<li>train_small: training dataset, contains 8 images of 20 different people.</li><li>test1.zip: testing dataset, contains 2 images all people from the training dataset.</li>\n",
        "<li>test2.zip: testing dataset, consisting of 2 images of 20 new people whose images weren't present in the training dataset.</li>\n"
      ],
      "metadata": {
        "id": "NqQ4B8X5DoeI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Downloading training dataset\n",
        "file_id = '1Z9evWwUK4nTpARz67ZWraNe5sX2MNcFx'\n",
        "destination = '/content/dataset.zip'\n",
        "download_file_from_google_drive(file_id, destination)\n",
        "\n",
        "!unzip -q dataset.zip\n",
        "!rm -rf dataset.zip"
      ],
      "metadata": {
        "id": "Ktar_dpcWBHa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Downloading test1 dataset\n",
        "test_file_id_1 = '1bIr_ikTxGuuZnJulykXeZz04pyb27S3f'\n",
        "test_destination_1 = '/content/test1.zip'\n",
        "download_file_from_google_drive(test_file_id_1, test_destination_1)\n",
        "\n",
        "!unzip -q test1.zip\n",
        "!rm -rf test1.zip"
      ],
      "metadata": {
        "id": "yM27R6wHV_iu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Downloading test2 dataset\n",
        "test_file_id_2 = '1Kj0QsxJ1m0n0UCPiaFskskUhM7fvxqS4'\n",
        "test_destination_2 = '/content/test2.zip'\n",
        "download_file_from_google_drive(test_file_id_2, test_destination_2)\n",
        "\n",
        "!unzip -q test2.zip\n",
        "!rm -rf test2.zip"
      ],
      "metadata": {
        "id": "Tz7GFtJqHe4M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# All images are supposed to be the same size, say, N*L\n",
        "IMAGE_DIR = \"/content/train_small\""
      ],
      "metadata": {
        "id": "0XTxubQAL-dq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# importing necessary libraries\n",
        "\n",
        "import os\n",
        "import numpy as np\n",
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "import fnmatch\n",
        "import re"
      ],
      "metadata": {
        "id": "sSAMwOfmMIfW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def getClassFromName(fileName,lastSubdir=True):\n",
        "        if lastSubdir:\n",
        "            name = os.path.basename(os.path.dirname(fileName))\n",
        "        else:\n",
        "            name = os.path.basename(fileName)\n",
        "        mat = re.match(\".*(\\d+).*\", name)\n",
        "        if mat != None:\n",
        "            return int(mat.group(1))\n",
        "        else:\n",
        "            return name.__hash__()"
      ],
      "metadata": {
        "id": "IeBCGIscNHwz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "image_names = []\n",
        "image_dictionary = []\n",
        "\n",
        "image_1D = []\n",
        "for root, dirnames, filenames in os.walk(IMAGE_DIR):\n",
        "    for filename in fnmatch.filter(filenames, \"*.*\"):\n",
        "        image_names.append(os.path.join(root, filename))\n",
        "for idx,image_name in enumerate(image_names):\n",
        "    img = cv2.imread(image_name, cv2.IMREAD_GRAYSCALE).astype(np.float64)\n",
        "    if idx == 0:\n",
        "        imgShape = img.shape\n",
        "        vector_matrix = np.zeros((imgShape[0]*imgShape[1], len(image_names)),dtype=np.float64)\n",
        "    image_dictionary.append((image_name,img,getClassFromName(image_name)))\n",
        "    image_1D.append(img.flatten())"
      ],
      "metadata": {
        "id": "PWqng3a_YB9P"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# print(image_1D)\n",
        "print(len(image_1D))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OH9-dPHwMkM6",
        "outputId": "2bcfed51-a8de-496b-d60b-66988c834bb7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Training Methodology:\n",
        "<ol>\n",
        "<li>We start by grayscaling the images and converting them into matrices of shape 112x92.</li><li>\n",
        "Now each of these matrices was flattened and converted into a matrix of shape 10304x1. (Here 10304 comes from 112*92). All these vectors were stacked row wise into a single matrix (image_1D in our code).</li><li>\n",
        "Now we normalize each row of this matrix by subtracting the row wise mean from each element of the corresponding row. This new matrix will be called AT, and the transpose of this matrix will be called A.</li><li>\n",
        "Next we calculate the covariance matrix by doing ATxA.</li><li>\n",
        "Next we calculate the eigenvalues and eigenvectors of the covariance matrix using the linalg.eig of numpy. </li><li>\n",
        "Next step is dimensionality reduction. We choose a number K, and choose K eigen vectors corresponding to the K largest eigenvalues. </li><li>\n",
        "Now we calculated the normalized training faces (face-average face) and represented each normalized face as a linear combination of the eigenvectors obtained in step 6. These w vectors were calculated using the np.linalg.lstsq function of numpy.\n",
        "</li><li>\n",
        "After calculating the weights (w vectors), we stacked those vectors </li>\n"
      ],
      "metadata": {
        "id": "S8sblmfPFuIC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Calculating the normalized image vectors."
      ],
      "metadata": {
        "id": "_fTlX3dsZ5AG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# We normalize each row of this matrix by subtracting the row wise mean from each element of the corresponding row. \n",
        "# This new matrix will be called AT\n",
        "mean = []\n",
        "a_transpose_norm = []\n",
        "for i in range(len(image_1D[0])):\n",
        "  mean.append(0)\n",
        "\n",
        "  for j in range(len(image_1D)):\n",
        "    mean[i] += image_1D[j][i]/len(image_1D)\n",
        "    # print(sum)\n",
        "\n",
        "for i in range(len(image_1D)):\n",
        "  a_transpose_norm.append([])\n",
        "  for j in range(len(mean)):\n",
        "    a_transpose_norm[i].append(image_1D[i][j] - mean[j])\n",
        "    # print(a_transpose_norm)\n",
        "\n",
        "# print(len(a_transpose_norm))"
      ],
      "metadata": {
        "id": "2S6cKxQQNZoj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# The transpose of the matrix computed above will be called A.\n",
        "a_norm = np.transpose(a_transpose_norm)  #A\n",
        "len(a_norm)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ddx33GkhZX8j",
        "outputId": "16765a4f-d120-4079-cbe9-ebf60aabce41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10304"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Calculating eigenvectors and eigenvalues of the covariance matrix formed by the image vectors."
      ],
      "metadata": {
        "id": "t0rjkbbTaQi9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# We calculate the covariance matrix by doing ATxA.\n",
        "cov_matrix = np.cov(a_transpose_norm) # At*A\n",
        "# print(cov_matrix)\n",
        "len(cov_matrix[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6yWV1oy4R6ZO",
        "outputId": "b3d9a20e-009e-4fb0-f16d-fa11f73b168c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "160"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "eigen = np.linalg.eig(cov_matrix) # returns eigen values and then all eigen vectors\n",
        "# for i in range(len(eigen)):\n",
        "#   print(eigen[i])\n",
        "v_eigenvalues=eigen[0]\n",
        "v=np.transpose(eigen[1])\n",
        "# print(v_eigenvalues)\n",
        "# print(v)\n",
        "# print(len(v), len(v[0]))\n"
      ],
      "metadata": {
        "id": "s4jQdXEbXq2B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "u_transpose = []\n",
        "for i in range(len(v)):\n",
        "  array = np.matmul(a_norm,v[i])\n",
        "  u_transpose.append(array)\n",
        "u=np.transpose(u_transpose)\n",
        "# print(len(u),len(u[0]))\n",
        "print(len(u), len(u[0]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iOa48rbZcr9n",
        "outputId": "71bcb11d-0695-44e1-b331-ed69cee814c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10304 160\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "eigen_values = eigen[0]\n",
        "eigen_vectors=eigen[1]\n",
        "# print(eigen_values)\n",
        "eigen_d = {}\n",
        "for i in range(len(eigen_values)):\n",
        "  eigen_d[eigen_values[i]]=i\n",
        "# eigen_d"
      ],
      "metadata": {
        "id": "TH1PFX1ysqDl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Selecting the K eigenvectors of covariance matrix corresponding to the K largest eigenvalues. "
      ],
      "metadata": {
        "id": "iEraN5okaqkv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "k=12"
      ],
      "metadata": {
        "id": "nEP902JtbGHS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# sorting the dictionary of eigenvalues to get the corresponding eigenvectors.\n",
        "from collections import OrderedDict\n",
        "dict1 = OrderedDict(sorted(eigen_d.items(),reverse=True))\n",
        "dict2=dict(dict1)\n",
        "print(dict2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nFrNOHuRvpqK",
        "outputId": "88b6fe0e-f8cb-4e00-80db-c52a7b5d881b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{43219.953977553596: 0, 18749.895990890815: 1, 17942.155464146246: 2, 12061.802455045403: 3, 10489.25912953686: 4, 8066.724722559026: 5, 7297.85172164008: 6, 6261.016588366359: 7, 5873.753178029104: 8, 4420.5004066534: 9, 3826.304473465676: 10, 3579.8886501814827: 11, 3112.701941552233: 12, 2932.3449009364517: 13, 2747.3196034473535: 14, 2487.396345846331: 15, 2411.0446487988524: 16, 2252.6641238208167: 17, 2074.7096367875374: 18, 1989.9475765463246: 19, 1928.8795510110008: 20, 1773.305425328178: 21, 1676.8247434736688: 22, 1640.8845693566923: 23, 1586.0134088610828: 24, 1384.3119343572707: 25, 1360.5249845839646: 26, 1272.8354997100732: 27, 1171.4911399813118: 28, 1150.5295704016391: 29, 1117.2277311946657: 30, 1066.7345849297926: 31, 1027.8242127649535: 32, 1000.5604997800493: 33, 957.4881339639342: 34, 932.1908536264845: 35, 890.6505933876211: 36, 867.9216091629972: 38, 833.6071838643115: 39, 806.8325487486294: 40, 774.5620675914377: 41, 758.6272156532845: 42, 738.4342113595159: 43, 714.5399164439951: 44, 682.7055539009281: 46, 680.9252271100078: 47, 673.9283018815898: 48, 658.4301569913085: 45, 625.0816864277112: 49, 617.5582835272636: 50, 606.4179117332367: 51, 574.3310372756353: 53, 569.9325407493129: 52, 556.968211979823: 54, 548.371195855361: 55, 541.394394333996: 56, 517.6264019518915: 58, 516.5821198500923: 57, 500.04350432768587: 59, 482.81038227024146: 60, 474.40612112126905: 61, 472.91907873668464: 62, 463.37362069900644: 63, 448.87411947393264: 64, 445.1195525159666: 65, 433.8822394567646: 66, 424.9545193027636: 67, 414.34625398368985: 73, 410.44103052260715: 72, 399.7720057166255: 74, 392.1543734446897: 75, 387.79362525258114: 76, 374.2368664887361: 79, 371.49945348490684: 80, 366.1104550707202: 81, 362.76582599959437: 83, 362.07916777129213: 82, 352.7149467318006: 86, 347.6629266571733: 87, 344.4517149718263: 88, 338.56891140470464: 89, 326.7105220744234: 94, 326.25054239097585: 95, 317.973905297458: 99, 315.61948544607054: 100, 312.15439105645754: 109, 308.5046455356127: 101, 302.55416730618424: 110, 298.5400400481408: 111, 292.27487160513783: 112, 288.8823139316889: 113, 285.0435271976845: 114, 282.9772519873982: 115, 277.64467614646475: 117, 273.7020381676069: 118, 269.5357634357952: 142, 265.9471151508216: 119, 261.3862164259361: 120, 259.8671420930868: 126, 257.6130828977115: 125, 254.21906797290566: 131, 250.616479699577: 128, 246.06438730855305: 127, 240.00699924404051: 129, 234.8180913874552: 130, 232.7549425732958: 141, 230.7956380602637: 143, 226.5311551599993: 159, 223.75397178988626: 153, 221.54950660799236: 152, 219.43463583127505: 158, 217.41411147378702: 151, 215.48480958242658: 150, 211.49682062225486: 154, 209.55479232153124: 157, 208.1694532219256: 156, 206.43451832745535: 155, 200.65013822053376: 144, 199.90465610231152: 145, 197.0978066449791: 140, 195.18560080202585: 147, 190.91520321768897: 146, 189.6685050111701: 137, 185.6900961024561: 139, 182.2508248568398: 136, 178.73701239142918: 135, 174.5908773381799: 132, 169.827660924428: 124, 166.7766873707503: 134, 165.7343487334624: 138, 163.50086445520705: 133, 161.8161444605663: 149, 159.93509949384642: 123, 157.84439541824133: 121, 155.2947155213594: 148, 154.80023084350475: 122, 150.43467043710345: 116, 147.1590447262029: 108, 140.48035960506212: 107, 138.73007592494284: 106, 137.8886194586964: 105, 133.96609468111802: 104, 133.32671443969662: 103, 131.35871093197667: 102, 126.39832659543461: 98, 123.8572162371065: 97, 120.39979904790052: 96, 119.33111585528107: 93, 117.61534130912757: 92, 115.93856715938144: 91, 109.54104484025125: 90, 108.20582883113228: 85, 101.43665329843098: 84, 89.47901931450252: 78, 84.06012945411771: 77, 70.50578026422139: 71, 65.59787544247587: 70, 62.77453678940503: 69, 59.32778617838623: 68, -5.107739735450283e-13: 37}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# indexes of of k maximum eigenvalues\n",
        "index_list=[]\n",
        "for e in dict2:\n",
        "  if(len(index_list)>=k):\n",
        "    break\n",
        "  index_list.append(dict2[e])\n",
        "print(index_list)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cbg1ul5QxPI0",
        "outputId": "d7a6ecaf-b420-40ae-ca61-f486f94abc75"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# eigenvectors of k maximum eigenvalues\n",
        "u_k=[]\n",
        "for i in index_list:\n",
        "  u_k.append(u_transpose[i])\n",
        "print(u_k)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qieh14Bw0eFk",
        "outputId": "db0bc194-6afe-47ef-be65-057354b46ccc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[array([-250.34987268, -246.96739775, -251.03150872, ...,   62.66394197,\n",
            "         42.95102603,   -7.43283506]), array([-293.03400587, -296.61765524, -294.39034777, ...,  -50.55568765,\n",
            "        -45.94985846,  -50.66399445]), array([ 69.73691919,  64.22732671,  68.583571  , ..., -41.61421501,\n",
            "       -40.95085605, -38.69027747]), array([ 15.24047245,  19.31637724,  22.9986019 , ..., -81.3522821 ,\n",
            "       -68.21885398, -73.1093675 ]), array([   7.04373461,    4.56640216,    2.24472334, ..., -102.02376868,\n",
            "        -80.93066914,  -59.14922928]), array([-64.63035609, -68.56599373, -60.92922784, ...,  97.30812891,\n",
            "        83.50398642,  56.29972771]), array([-73.39842816, -75.85858873, -75.10925541, ..., -21.30720511,\n",
            "       -25.49241544,   5.10502217]), array([  76.33460672,   78.27079323,   83.86525799, ..., -100.27234286,\n",
            "        -77.988847  ,  -61.0207666 ]), array([-103.25654954, -100.23979122,  -96.30983044, ...,  -37.3388256 ,\n",
            "        -49.91948021,  -28.46092446]), array([-62.26684061, -59.45034204, -62.54270953, ..., 151.8902004 ,\n",
            "       121.29818377, 111.59794073]), array([ -92.97767444,  -95.5290902 ,  -91.18621931, ..., -113.1381992 ,\n",
            "        -91.31555489,  -88.30228713]), array([-74.61218527, -70.83391408, -71.92315934, ...,  52.7331185 ,\n",
            "        48.02889301,  55.92254778])]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Plotting the mean vector."
      ],
      "metadata": {
        "id": "HvDlF6TucQzE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axarr = plt.subplots()\n",
        "axarr.set_title(\" plot_mean_vector\")\n",
        "avg_image = np.reshape(mean, (imgShape))\n",
        "axarr.imshow(avg_image, cmap=plt.cm.gray)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "p0SBuyof3aiw",
        "outputId": "0b25ab2f-107b-459d-a33e-9665fe76249b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f3182920b10>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Plotting the k eigenfaces."
      ],
      "metadata": {
        "id": "mFsvoKGpce9C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(k):\n",
        "  fig,axarr = plt.subplots()\n",
        "  axarr.set_title(\" plot_eigen_face_\"+str(i+1))\n",
        "  avg_image = np.reshape(u_k[i], (imgShape))\n",
        "  axarr.imshow(avg_image, cmap=plt.cm.gray)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "iL9YmhBp51Vk",
        "outputId": "0067fde8-2220-4363-e4bc-42a9b836ddfd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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Ec5zwTLVXWbUK7ubk8s4EGh8KoqQ1I8J6yAdf6/pyOSL5QrhWeS8bKio923P/Da39MZz1GGykso80svaqyT/3xXPfWtPFxcUoGeRxEI5vo2flOhoFkwIi1RnCTJ0nlMy6e++Dtc/dFwmlUhATjro9ei4Lm+vLMZmmliBcP/c6so0Ucgf0HhPjvyxLJZvNZkOsxD2cVDR+Z1Yt4avPp/ck7+fz+QDXiBDIE+nag3Lvonfwuy+M9zhOLsuk4aLyGmKaDg8PB5lhvZ7DmyrSNtoZRUuoVwlgtQ5Exk5ZfGmVavdkJN6nEqdHy/ooaPQWVg4LGzOg2VbGPxnbuBzbpCHJDCb74npZP1Pm6SVdroo/pqw626T1dxw0RZnNY5Ilvefe3t4AtzkmGjR6SyZiqIDuIyEsY7apvtF7bkrlP+sWrClI0jhbZsZUUKoSyCQrGdea6DWsYPYOU0kN1pXkGxotCFXKnf00VEqjUfWfAkS+TMUIjHt4TQW1fY7ZuFTIVNyEY0QBuXbnchyL+cilEioeF6jpmbiJm/PhBIdjVCq/PXcqmufb7VlR2U/ymvyh4j2rFC3jCVN6uvz4WlNCIC4CG5JRUHyMaXsKNZWebSRk9G0juX3I1zPoZxtZd2VhLVSGihmDZLo613aokDy3WCzW4iC2XS1FZF+r2GwKBWTck32xh7FC2Ei5f3knust54dlK4Sylr2PYwDveOQ82tnkLE/s/hZamjB1p5xStOlZl2VgmvwmtuCOe2N9lfd47Qgj7qHD0SBlb8TEIVXl7uoxfqvhtCsqk52M9VOBMOFBhyBd6koztLNRpGNLDUdHSeyY0rj4ZA+Xam+cn18OYEeV40zCRn4zbmUlNVDSlSPTanB96+00Kt1OKRmHy4KptTBnX5I2QnGgrGDNzhnX0ZLnlinVzchNCSeO9dgn9MimSe/x8jAJJS82+eKJT8JiYMYRKq2wF4WMVkl80FJkMyZS3lbbKMjIuzDnNTdg0EK7fG7upyIZ1LM/YLMswHLBC+zt3ikjX3tPLBzQCTuBwDjl3Htc2CLkTijZlRTj5nFRakCloY0HyDnxaYtfJ5Ag37Pq63vsoppPGOx3SIibUZJ894dnP9DC8hluGNsVvhlz2yNztkbGYvcDBwcEINlVJGCpceonMTnI8WY7H6FU5t/Q8no/Dw8O1On1vm8fNewMZg9FAZz84F+43Yb+VlpB8iqpxV7QTipawg8xmvMUyxNW5eZiL0efn5yPIaIttqMibKSt4w1iNwjEF3zgmwsUqNqElzjLS2BtSWTIu4rhdr69PK5yJoxQQp/1TgHgbDWHYTZMBnDsbK1/nOtPDm8+8zYeKasNio+I6eRuOUQv76nadNCFPiXIYy+XCeiKcbbQTimZKj0DImFbRZViOlt9w0R9OngPjXHC2ANHzZeySRsH9MXxMOEXIlcd4R4DrSc9n4thSIPPuZBIhq9PllSKR+MQuCzKVmlnCqTqSaESr9TYKbkLyKaRgb2jP5xtFCQtpgOiF6cWNCKjQ5EMFo91HxribaCcUrfJSZCxhGyEULaE9mGMy1kFG+IZOf1y2WjqQ1u8hS6hTGQBaXUmj3QaMRSi0tPIJx6p+WTAMA8lLewFnQtmfvLeNXoZ1eHM1lyAY1+XtMOk5MwuZbU0pkMeWnp684v5KSaOYzjfl8jovSrtvNjiO7W14iRiIYgxj2Tblo5KFpJ1QNGkc1E/FIoyDUvB8Pvf6SRopIpWLsRrXqFIApOmnJpmYzKisHuEchbBSwISbVcbLira3tzckP5jO3tvb09HR0dqSg4XMyQTz0v3L2DOFNnmeSuh+cBy5HOK+cx2NUK2KU5nkYDuu332t0EDeEeCkSd4FYc/GuTUaqpZiKA9T50w7o2gW9ikFysRHBu9ejLZHS+jJNH/ehiKtP1eDCpMfZrqY0TIxYUJoyGwihcq3h7B+KqopLWY+ro1wzDdXZpyZMSyNlueBHs7fVsr0ZLnm5X5Wz/YgOuD4sw8cZxomj4/l6NkkDQ9fpffJOTw6OtLh4aEuLi6GhxpNxbAVVKYcsE9TtDOKJtV7HKditupawqHcYpWwNOM8eqGEA7RwKdhpedOiVx/eL0VFY/3pLX2OlPEILTcVjYbKQpjwm17FHpHE5AOPGZbxUXepHN6v6HlJz8X2qwQN4y3PdXXDJY0IeZhe0se4V5TE+c9wwN9UysooJu2EoqUwpGdLKMlB8pqEgYSD9Hb0Wtx9YKrgD2OLvb29tWft+3jCl9ns+rFpxviOPVyecUUmR1KxMsVexXQUKgpbGhmPm8kR84leJw0XjZ1hq+unkbLw5e1FCX99rorVuA4maW0jOHdxsI9++C2XOWjYaPBM5oP7xbG6POGnx0nYvol2QtGk9XuLpPo5HNL0cgDrSCjkWIUwit/pQQgJCRlSAaXxvUxkvPtv78IyVjRJOj4+HoSWClIpWsIq94uemQLkury9iDGZhSVvFaGQptGioOfaFfnuevLG2pzTnGtSrm0mP6b+06hwTtMAmVf0/ByLv1NWGG6Qb5toJxWt+k/B46RdXl7q/Px8lG3M2Ozq6mpYTyNUSuGS1rfxuF1m+Krkhj0SX+DgCT08PByUzd7Qv+3xmJnkSxs83ky+VJk79sdkYbfnocCkAtHD2zMTcmcSJGG16+ccEZa5L/zv70wo9H6d+WR5ekhplQGmYaKC37t3b0AL5KXbXCyubzI9PT3VZz7zmbUxso9EPlxz8xqtEcsU7ZyiVZQTmdnHaneDNN5lYG82FQ/wd5UAoSLQG/mcrTu9G7OC/t7f3x89L8OBOaENYSYpM3DMumW/pVW2lcc4fmn1jA/zw//tgTORkUo/Zcld1k+7ctupaKn4HI9jLZfx+NML0rOzfa7DVZ6H8C9vvckYjdvF0mvnfWwV7YSiJROqgJwW8t69e4M1YfbMadi9vb3BGl5cXAwpfab1qTjZF2mcaKDH4rYg99fHrVz0VrPZ9a31BwcHo2/GZL6WMRwVicel8YNxaHAYxHMdjetFjDMYxE9lG30d393mPvhc5d08F163yxiPqITelR704OBgdL202pNIo2olqF4eQs+WCplG6ejoaJCTRBRuO/ehuh0/r2SKdkLRTGRAplql8c2ZTFGnJcnYLRMl0nq8k/3IeCwVkzjfMItJDqbeDw4Oho8hJBXN3iOD9uwHH2JDRakSDaw3LbH7TyhuPla3idDTsXzFM/bXRq9CEh4H58tzakG3Al1cXIwMTcLVKguZMRa9eMa2zB7ym78zxOBG8PR+Fe2EojGAp1X2f8dVl5eXQ/aQm4Wl8WTZ6p2fn+vs7GyI4ygc2Q77QeWyQjAGc1kqFxMcViZ7sOPjYx0cHAyxmj2apFFyxIrBW/4ljRSRlOll8sL10RgxI5gW22UIW6skCLewuf9TkJuoIzcRVEkGx9BGI1zUttL5m7vtKyiZ3tWxVMbW3KrH44SeHgtRA3ldyVLSTiiaNPYiaX0JLaqYjBbWilml+4mtfR3b93flyfxNIa0UzErmz/Hx8aBY9mRWOBOVlZlLW0t6TPY9LXEqGrOMGZNWirZYLIYnSPlcZg0JvTlvyUP3x8rBpYKEqzk3jIdseDhf5oOVeFOcmPJDuM00vXniuWa9RFfsbxX3TdGTVrTW2ssk/ZCkF0nqkh7tvb+9tfYCST8i6RWSfkXS63vvn9pWH2GMtHo3sxXn8vJSZ2dnuri4GN03ZAbQ09naMRPJBEIKAj8UdiY4+D+VxplDK5d/pydjTEao4/8nJycjhfaHGc9Nk8rJp2XOpE8mNMj3hNTp0awA3L7k+au8FOfJkJ/KT7h1eHioxWKhk5MTzedzPf7448OTqubzue7duzfESby9aep1VTTATFIxSeJxHB4e6uTkZJAZGoaMBzlel6vifdL9eLQrSd/Ue/+51tqDkt7XWvu7kt4k6ad6729rrb1V0lslfcumiqaEJ+OxzH75t70WNwszdqOgpQVOa0aPRiFPr2Vl4wvMDQupbP7PxWjX4/anXoJeKRr5lZ55m6IxVqviEPLEx6YUjYJaQc1EET5GGJZLMW7PXo1LA4Z5nC8bHtaXsNFyZCVg5jNjXB8jbK/irpS/hO4VPWlF670/Jumx5e/PtNZ+SdLDkl4r6VXLYu+Q9B5tUTRplYrmxNiTOcvIRUhmtBaL65fTeT2NcMd1o9+SVjvqK3iWqXifp5cyHPR/JjqsaEdHR4OiUXmsWPy2V3QfUtnpjSuYnROd5z1eCpXLUTDJs8qzcW6y3cwuOkbzWNJwOsPnOeS+SSc4nDV0zMaYysr32c9+dsgwc76rZQUbCPfDfaPB8JIE+ZzejVlu8nOKnpIYrbX2Ckm/W9J7Jb1oqYSS9FFdQ8vqmkckPSJJz3nOc9Zij4zFKmvBwWdqONpai88yVrEnyXS+PU8qkmHj0dHRSDEJKzO76ImzIiX8pLJnnOgJZ5+3KRrHnR7OlApVHbeHpPWm1acH48IuYSWXXjgWJzZyzqgcznjmFrRUnip9n/xhv7KcPWJlmEnb6qvovhWttfaApP9Z0n/ce/+twP29tVaqe+/9UUmPStKLX/ziTqYQe1PJKsvLNTJbu6kA2ZPBc/YqVhgr2snJifb394e4yUkCe6iTk5My/rKX87YqKpzbZkzmOtgvx4lUeno48yIXcBOqpUJZIH29j9Nbpkej0SPkzH2B+UgIX+MnT+3trZ6p4uyxDaORiA0n++n57b3r6OhoUFaXvbi4GPadZvyUd3FUdzO4Lns4G1LKTI7V46XxTEORdF+K1lo70LWS/XDv/ceWhz/WWnuo9/5Ya+0hSR+/QT2j7xQYk497gqiY1ToNrycMYBxGT1bFYFyo5vYpejImTahcuWOEsZavzcVtejxPJJW0UjQK5pSHcxvJc1rw9EL0PI6XfB2zjoZZ9GRWCNbDOTJPmDLPrDLRhLT+tGgiicqjuY8cYxpg8ym9H8vTAGUdU8eT7ifr2CR9v6Rf6r3/tzj145LeKOlty+9336Q+WmvCQA7EFnPThxiaSYBKiO2hqDD2ZHfu3Bltlzo9PR2tpdnTUUm8S9+xGZU2FYyJE/eRm4qllWdj4gT8HxkLaV3JaGUz3jPRKhP6pbJ7Vz+VkgkB3qJEz8akCJWMO00ODw8H78cbcxkDubxvznT7Lu/YnGOu0vRpsBIxue+eNx/nY9qTj4TUU3Q/Hu3LJb1B0j9qrf3C8tif0bWCvau19hZJH5T0+ptWSAGpMof8mCovJq3fw2UmU4AqT2aPZUiYG4KZsmccxSxkJkfcBhWN3zQGVWyWxsLE8xWxfMaiySf/tnd03fSqNFyVoHL+LLSMC+m9LJi+lgqUMNAezRDR/eBuFsNA1+XxcAyMD7PP5EnFR8qovzPG20T3k3X8aUlTvvLVT7Q+wgrvtGcWiZOV0JIBOF0/GWTol4vDVjx7Lr8M3h7Mx6tvKgR3g9izERo6zqPXctuSSoFIyMjzyTtaeXsD18tPruGl4eLOCf4nPM22OX/pwZgpzmNGIS7POyy411FaQderqyvdvXt35L1s9LyWyjumEylQ0eylLi8vR3shyRMrMdESDUR1TUU7sTPEyjIFA4mfeQ0h5lTSJGOyCs5RgXIXh6FlrpfRM9LzET66HrbNdbIq7pryXjxPa1pNblVf1mkBIcTmtdnHCjWYCKncJxq7VDwLesZuRDD0WFYkpvRtiGw8JA3fVo5EChlv0XtL4wcvpTL54z6x35tiM9POKJp3gngHiHG6NI4HpDGWzq1WabmYuWutDV5F0ijzZ0/m2MyKdefOnaEcPQJjO6+vEX7aozG+ygVpU5WgqZTkptYzA/kUNlMqpLTa3kThkuq3bTJDyf+su0pYVSGCDabH73Ip4HyKl7SCnH6kwv7+/miHEPmbyZdM6FiBHdvN5/MREnL7ljOv83HOpmgnFE3SKBDOND3XyabuK5PGgkWYlZ6IENIKwkVmejJ6psqzMaaj4nE3SGVVSRn3mKpYNM9Xkzt1nHVW65LZp22U3tiCvqktxnk+Z2X0tT5mpXf9Thx5N7+F3ArlhWbCwBxPZl5txNk/K3waeBttyp2V91mhaLYU3p9IrM7BeVe347d8fiOFOZMcVijDkFwny9jM3z5vRReeFVMAACAASURBVPN6mut2uUoB0zPQc0nj3fepiITL/k8Lzes3KTB5TDjl83ldlfCgIct5o1fItkyEhuybP47Fc13Qex8NI+11eI8dd4nYu52cnAy8YnKmijPJS8aOhqHue3p4t5+Z4SnaGUXLfYqmhCC5Gz+TAxY6ei7GUIzNcisVU+72aK7HikQPSc+Va2Xue6UAnDjygGPisYwt8lzlnao+VP3JxErGUpuUjfFieqosZ2NJYbfHMDQkzKVhYB1Mu/u8PR3ho42A+VAlnVpro5tic474nbzNPZ12ClO0M4rGe83yVgxi/MxcMSiWVoKV6fV8ElUq2Onp6Vq2kcmS09PTURyTex492Z7ECs6SqgRCLpxmAsLlmXH18cpSW7Cp0JmgoIeVxu+sZto7608PZrIiZb+Zhmf8RcNCxfP8U/FsJG30XNbzSk9IL1iNl8rPNUDyjvOQY/Vx7+WcysqadkLRSCmYibWrgDtxN6EYvZoVbjZb30pFz0TvxFhLWj0iIHfkux9TsVYqXzVul01rSs+VHqxS1AoKun+pBNxYy7qzzfRUOYbMYuZccW7YN/YnjZPP0XjZsHoufN7fNn72OsxmMtayjHD8FZLKjRO8PYi8ssJN0c4oGie0wv0uU8UlVeCbSmblSIiYipbp+6lbXKpbWtwvUiYmNimbz+VWI9ZDwaRBsWVmLEKeWmk8huS7x0tLzmsJdVNhqBjcF8h+p7LnbTRZnplM897XGcFw07G/e+9DXM2EWuXBDUVT0ZjcsNdi6EKl9bF8CGvSTihaMsGMcJq1yrjRsiV0oYLkzg7/rhSMMVimbN2Gz9GCp+BmUoPXG+5kWZbZtEGVk0wo6QmfUoaES5XwJyxlGcM+1se2KKScI/avCgGqNVDOpYWd/SG0ZNxnI+PNwwwpEgKyr1x34zJGQurq1iCX4dO9KtoZRaO1zd0JvGdJWllhWm7Xw4DZn1yEZoxVbQqmABFSUclSiNgv973yZGnFeU0KYsK0NDoZb1Hps39V5pNCW93xQLiW/7kli96AvDA/KyVLD1HBTHoaxlr85py4LStatdsjFVwab7hmltK0t7c3vIUoFc3KnPF00k4oGieenkqqsz5cUMx66LX4oFJOCHd1EF5SGFNRpOnnRRCWuRz/Zx9zbKmEacF9LmFLxmwpsFMwk962Whyv4slK8dNrJ+TLOUpFq2LN/J1Ih4pGebAHkzTcmnN4eDiCfVSGTXLFOawM41RyZBPthKJJ48lLT5XWYgrPU3iqhIWVmP8TLk4lNNweJ439yE9CC/ab1+Rvj7cqX1n/9IrS+uMHLJxp0GggfD3hGv/nLoupOG3KSKawpwBXdZEyXkwYS+/pMnzUgY/bW1V10LtT9syjKoTx2LbRTiias4BnZ2cjqGYGGR/zwTskBq8JASlAidnzUx2nwEkrLJ6L6UwCMG7IhETlNfKmypw496WKA9JjMU7zeQtKemoqnseXt+q4nK/hEkR6MMZ6FaXypwxkrJjJGfYnITL55Pqs9AcHB6M9ipXnd53c+sdY0m1VsaqkkXJWtBOK1tpqD2HiY0IQDzo3f1KZqjhEWlm9KTiY/wnLMoZy5stCnQqVk5leIOMGKhoV8CbfhLDpjWmFGcOwDSZUGGt5XtIzkxeEcFV8mFT1m/1k/fk7y1MRswz5zJjfWdn0yGk0PJfkXzW/2cdNtDOK5mzRbDYbUqVcA6FLr4Q4U/mMuahgU4xO+OXjPC+tP/++wvyMzyphZQBNb5iUY61S5xWkzrapRFXsyXMeK7cg9T5+Xke2RRiaN5tWiaMKKlcKMxX/cExTH/eR8Z2zlB6jlwASvVSGNWFu9omKWtFOKJq0eogoLRUFMTNutF7SOlP5mx7ElFY3Jz+PV4pY9UMap8uruIKp5CpmIRypYGxCzBxXemhCR65JZXl6Jfc/M6DZHg1deuNsM6GYr2eYsGkueK6ay8rjVGX8n0YnDXf2w78rZbqJd9sZRTP+7X1823qVtZJWkNLxmI95Iv3NeMlEi5fMpPdhewklDUMIKZjKTqVnGxlrpSLZyuYd5vwm39I7E2ZXCkIlYNvMujlzl1Ay+8E7LBIWM6apjJ2v90ZhzvOUYWF/qyRZxnpVm6w3PZ37zF0lVRIk53UbhNwpRavilym4wWObLBApLTOPV79ZD5MAxOzSCiJVu9PZR3qOVA5+cnJzknNybaBIjGXTALjPFQSiocosJ2OYiqfkrZWrSs7kHLCv0uYFe/IrFc2Unos8yzL80MjmneJTc1eNvaKdUDR3PDedmjzp/p2Wjs+IyDoze8YAuTqXAbJ/pxLQKzjDZcElVMydJJVwezwJJaeyWCmsuV8x+5ExCw0GFZDCbo+9qV333crMOaAibzMUTNQQnk0pevbB43TSI+ctwwTTbDYbPYLO12TsTM/PY5z3fK1V0k4ominTytI6XEyqIKE0HZxWKe6EX1PkSai8V05qBSkqqMrvXP/a1hcKFD3stnGwDio148ib3CbDflRKyHNTySb2mW1UPNo0RzmfFXF8lo2M46lklRes6qRhnaKdUTQOwskPW8pKgWixpfHLAPl/sbjeFOptWLmelgvWfPQA2yOs6b1+XxgFhRk8UjUhrp/WkpTp+SpmcN/yuuwDHw5qg0E45GxjLjl4XFOQifEl56qCpvz2b/5P6Joxt8tmbO7/5pVjL66h+Rzni/cs+hVfVB7PN+fA7TKr/azxaFN4Wqp3WFgQqCxcqKZQU2EIKzd5tioVnl6Awk+Ik8rnSeH1U+PbxqNtFjTboOew0nIMVDT+pvDyeHqNjF+q/rBfLjtFCWupaOTbJu+2CaVU0DK9GjOlktbOc66n0BNppxTNA3esxompYqje++jWFwuGrbLjDG4ctsfKPY4UTjKOcYuv4wQS1qYVJOVk8rwtr7S+Fcj10osR9rD9CmJnPxgL+Zr0hLlEwnHTK5DHvM2GyaFsK5NICbvNU2b88h1tlWz03ke7Osj3/f39wVNxLrJ/OX7yIefHfWIbm2hnFC3XPjK2cRmmoS3wueODE0aXz7Yqq5fwhUQ4SMHIBdoUmmo8/k/rnpk5f7M+Kh2JAsjrE8742kr4TZmAyMX+7A/3DnKO3I8U5tzVQ565DT4mgApX8aWCnFPENtjHrIdzxfF4nir4/KzxaJWV2t/fH2UUU0GkFb6mtaRwWMmIpUm0kBREnvNxM5PbetwGrR+FkZOQ/WAsQq9gytdPpSCxLD1TNUbGF1x/TCEmzyz05Hk+YSq3NdETeo3Mc0J+Eqry0XA0Du5bvkI5jQXlo/fV82fcz3wzqOvwQ4F8LJV2sVgMt1LlrVrmE+VsE+2Eok3FLZWl8MC4i2RTzJKeK3E746z0Mu6bv5lxrKyahSgVzf3MBAMFnIJimoJeJnppbmqdiqF4nF6fvE9lmFJA9skKmel3K3+m+rMfvJ2mUjSOjYpW/c85S2J58jLjy6wjQwXyM3la0U4omrS6g5XPZOCt6FwnkcYxkQXZWcWEkVN7HV3PfD5fu6WCt4UQerpdPjiTY5gK2N0P768juT98ATuzZcya8ZrcTcHb6XmnMQXePEqBz/5wB7uPcbwJdfPl8RyD5zYNhdvnjZ2cFz7fMxWEimBvQ3jKbXv0rr7eXi4NVI6L3pE7ZTYl1iraGUXLOMPHTMkEZoZMhG+pbFNCNRXDpIWjIGRsRXjJhc/KK7Ct/O1v18E3snh81djcl2rnfcZu6WVzTC7Dcbu+9GA+Tw/u80zouN5MhlRelV49H4STiuY+VRvP0xNyvlmflS7vUeSTsTbBw0QvU7RziibVi448VllFP7LAzKcFzt9sj4y0BSODDSv9lCOuQ9kL+TutLYXaeJ+eMYWA0Kv3PrwqyX1x20wzS+t3nFdW39/MvLpOx8IZf7ANx48XFxfDfVvSat2MPDff7EWyL2mA/J1oxApEb8gsJG9/mc/nw8sM+U3Fcl3n5+cjBMXHfEsaYrJ8Z7a/Oc6MOadoZxStyvJl53Ndg4Os1jNSwRLHM8ajR6VwZ/xYxWf+nfCGk5GxH3/7XEKnTCFnXzNOyb4nAiBf/ZsJkewnjRYzbyR6E/aRiYxNBoiGrkIRqWj0YOkR6cV4LCFrhiZTeyvZ38wuV/L5tCpaa21P0s9K+kjv/TWttVdKeqekF0p6n6Q39N4vNtWRE+U1MT9L3URBY1lb2xyolcz1URDpDbguwkmsIB/XjQiNUkGYjassNtfbfD4fJkOjItWCyO9KSH2cSpkxou9AZlxIj0fLTb7SGKSnYv8t1DnnrI/8qGQj26IhI2y/uroaPBmVnXGeyzJOM+XyRvLY7frZkRm/T9FT4dG+UdIvSXrO8v+fl/Tdvfd3tta+T9JbJH3vtkpoZSs3nJ7Kx/gxUcBIU4zgZKaXSfxNAclA2sRnw1drdraQOZm5vy4hcnqTFILkUcZXJi6Q83afjH/cT0JaPksxvS7bIh+paAnZ+UlFq3jBefFvbnBgmyxD8niYvGL9mxSGfaMsbKP7fYf1SyX9W5K+S9J/2q5b/QOSvn5Z5B2Svl1bFM0QhhlEabX+wWyjPVmuRzk5YobZ4kjjW9OTiYaCtJq+hpbz6OhoVJeFLhdgpfGLFxzX5e52SWsxI7Nk2UdemxDP62LOMpJXGZOaRxREv53FlAJOtJAKk2n5CoYlpLPnIaTndVQYaaUYftQ3x5TJHLdnT+brWVfGyZ4rKv2UEnEOpiBnRffr0f6SpG+W9ODy/wsl/Wbv3Tjhw5Ieri5srT0i6RFJevDBBwcGVJi6uHb0nR7N5wjDTJ5U7uHLWIZCT8iUE1BBIh+nd7Iysi16DrfFRxxwfGkc0vpScaq4ofLG6cEZT7JstfbnPnCeqDD0CjSE5heVzal3Cm6Ol/zOeaa3ZYKjWoOs6iRPM/zgOLJdji+35VV0Py+Lf42kj/fe39dae9UTvb73/qikRyXpxS9+cd/b2xu8xqc//em1l13QCtIT8A5reptlH9eY7DIXFxej5AqfCWhraMFwTEbldV207Al7WX9a6VQ696HyLKlwOS63c+/evcGzZZ8z0UL4m7smTIzN0kAw9e7rqGhV7GplygVoZ/jSYCQiOTk5GXkkl+H7xOfzuc7OzkZ9m/I85CPHWsW6zgOk4Ul5nKL7fVn8v91a+2pJx7qO0d4u6Xmttf2lV3uppI/cpLKMsTxZnJicQN9yTujHZEqFtXk9LTInhRbYCkFhZD8pHElUwFQStsnvmyoar8s63GduQzKPK2+Tns6UMZT5w3GnEBO2VeuOvM710KiRl9mnXPAnzPO82yDTm+XCvstUGwEquUnjXZ3bFtfdz8viv1XSty4be5Wk/6z3/sdaaz8q6XW6zjy+UdK7t9VF67usW4vF9YsHF4vxnjRp9UxF9GVg3vHx8VCGHtBUBfuuQxp7NF5j4c2sYELH3Cni6wkxfH3CNfMif6fgsV8V1KSXsrdLPmQcXAmSeeRxW2ipKLmX0QLMnTUUeno27/xIw8YPvZt5lsbA71c4Pj4e5IZtcY4sK97Nzwxqtsu59hj9n4adcjRFT8c62rdIemdr7Tsl/byk7992gSfIk8QdH5W3oIVLKy1pWIQ1ExM6sQ56yt5Xi8S+pcLEFDT7Rg9ZLTG4rfRoniRu6+EOkKSpmJVBvOvnpDPudWKJ8QgVbUrJLcyShnUxe/5MjlhxfHzK8FBY2Sa9LAWeyp1xU/LPdVXxfrbHOXHfMsa2khHZ8FPJYNJTomi99/dIes/y9wckfekTvF7n5+fDq3O9Nmaq4Ek+MdZW1DtEDg8Ph/vUqGw5wRY0vqZ3sVjo7t27Iy/G1zjRgrPMlKBScFprgzAeHR2txTWOSTlW15N3L3PXSxWMU5n94c4QSSPjtgke+cWM7rs9v9P/uQ5p6Mi4h+fT+LCsx51eLcfI53XM5/PR3BCaGhFVSy1MppgfvFsg78OjseW1Ff9JO7EzhPFYCrekUcxFmJQxAK+rUricdMZkXLTMBUxfQ8hDhpsybuI1/rgMYxLXQ8/NtDeVlA+AsZfZNMFpJHxTbBXb8Zqsk0pOj8U5cb8YX1NY6ZVYL+c0IVrydoqq+LJaX82kD6EhYWDWnYqZ3v4mtBOKJq2e72dFcxaS91BxjctxXeJpZ91swanEhABmWN4xYAGhleUE2mtSOKTx7o2EIbzfSlp5UVPCmXwVkPnimNUe/fj4eGTBbQQoEPkugpOTkyGWoXDlvXAek+fDcQ+3VJkIFQmNXY73DDJuppLSa/kesLOzs7UYtiLOlWVAGr/TLWG+vTiP08jQw+abhnLuyasp2hlFs4JwTcmLzlYWY2RJI8GgYpApjFcSIqQF5jkz1+0mTMuEiPvA+ujJuGGXymzKND83Lktai3sY0zIWYVxkY5UW9+rqaniZiDR+uyh3sPtcGhK+BinHuolSmcznTQLqzc40onk9jSfJc++5JL9omAlN+TtR0qZlJM7dFO2EopkZh4eHms/nww5xv5XTKV17IGld0fiEK3otaSVMman0d0IAKpoZmk9BIqQj7HTMQ0VLxSI8pXGwEBsSmliH65nNZjo7OxvBMmcA3d+806C16/VDe2XzdT6fDy9mTGiUiuad8T5f7WGkkttQst9TiubjLMMsY94LZ2+b649JnjPOuxWUIQV5xd9ug8/upMzcBD7ujKL5UV/SKlPmCWOsZibnRmKeo5VNWJaehDGY2+b1hKvuj9sw3DUxc5oZr4Rarq/KquXyRS4OeyzmC+NMJmrcT15rZMBYym323odbjUyV96quowDbINLwsT8J1cjz5BUVjZ4nicKfkI7KUiWnzOsqCUV+03NmprbKFJN2QtFms+vVfafUPUlmsrNJTJjYYhNHmxlkJANdabUgnRNiYvbJXkLSaL2I0IrvarM3ppItFuMXj3MCCYWYuUvP6z4QKnGsXNsizGIdlRCnEjmrSqHxuU1pfCZ7ptYKMznkLCGfxen+uQ0+WStjOcsN55GQjvEUY7bclZIxmOtKA2J55D1wacQ30U4omrTa7JlrJbQ4R0dHw8TSg2WGiRNPiCBpxEgKf06mFYZpYrflNqwEZrIXQZ0i9nUUCNbjT96KwrWuxWKVnvYkU9icJElhk8aQiZ7ZfE3BkjT030QPRmXlovB8Ph8Wf73e5jGen58Pno1KZgOaj2lL7+VxOz7n3HLrFcduXqcC2TD5PBXW0NDtc0mAn4x7/b/a80raGUWTxvc5JaYnHmaKvUrJSuu7KQzpTBY0wi4KDj1VxiKEP/QQFxcXunfvni4vL0eejf3PuC8tqo0Nk0DcGePjFhYLubT+7jYruwWBnj5jOFtox8ccG6Giv80fz8fdu3dHikteuS1ue5JWTzDj2DiXLnt6ejqKpzIWpZFxm4xdCdEZ72dm0UsfqexEHoTsyfMKIZl2QtEo3IRaVDozwpuNabmk9R390iquYkDu68xQBvfS+pOXKk9QxSq9Xy+63717VxcXF2vKwfiRuwyYDMhEASGQlZ11eZnAbVWwyWNwooZxpvlDosWv+OMy5JNvtvQ5ej7Pp2F+BQ2d8KKxmc1mI1RRZZLv3r07MlJUNEmjR0FYaey9zBcmWOh5/dDVyqPRc9PwbaKdUDRplbGjcpAh9Ar0NgkDqoxZehOe564CH0/hpIfNrCPhzNnZmc7OzgZF88RW6Wf2fVMgnYaD3sx9pFJzBwiTLh6LYSrHSiNAr27PRSF1PzxXXtvjgra/XY/7Qz7S4HgHjz380dHRAJn97eMJd72e6HmhkTCRv5YrypS9FHnnaxh+0BhkXJlzlbQzikacm2lmxkMHBwc6PT1dUwIzJx8+wzSzYYOtKSfFbRPyESKaqIApDBcXF0OMY6G2peXku8+GQLSs9g6tteFGTsdDtuyHh4cDP9jPi4uLwfPbU1gJaBz8OzOQkgYY6gQMjRr77mUCj38KWlNguXDv5I/nl17t3r17Iw9Fz+zxc+4ef/zxwWsm9KSBcLt8kQdlg+uIzr765Sj0aIz5q3i4op1QtIxhmCVihs+Ccnh4OIo5CAnIFNctraABd2XQklOZKYwkC5CTHU7vX15e6uzsbHSc2S56ClPGArb89j6ShsnOfYVWDmYjmfG0ENsrZZKoGh8TOvRYXL6QtGZg/ESpNCLuh+fQSsYd82yfIYP7Z8Xh1jMuxpsnXk+kHLnONLauIzcg0LvZyDF+rqC8DbxlaecVzWRLbYbQ+nkiPHmGS574w8PD4XYJxifSOMPGrJEnYjabjSZTGmeTCKfsXbhe5j4npJDG++tc1p6Om2C55Yy7XzxGxlYeE+GyLbrHbsE2T9xH7gNNhcidD+6rj9nIZMaSRMhK3hIp2Jj4eitzPvrO/LEcGGKmAtgDOqbyDcSeb+4JpaExvzx+zwnHkjGaZcrxn+vmeCraCUXLGCDhDJMF0spN85mKucexegMjrZHPedKZdpbqe78IVzPtT4tHYzHlxSrIwjjBZVwXLT6zZSZmwzKGYXnWn/w1P2gYKqPHZJT7w0RNehVmRrNe89K7UwhLaTg4bu4O4jgcWtBg0LhWsRp5wjVYaXyTcBroNCbbaCcUjRZZ0rAVi4JsoUzlsRU7OTnRnTt31upmciMfHS2tJsMCQstraGgF4/oY9wi6LLdWWfAdJ1H5rIxWcB/npmoLgvuYMFbSmofzGLhA7v75mJU5k0zcJGDjlVaaXpTLJWk0bDjJdyaH6NmolISlhL2MMb3Iba9F70gE4nrt0cmv5EVur3O9hs6cE5M9mstuo51QNGmcAidss1umt7CVshA7AcBnzZtpDLg5IdL6nbLMiFFxGLMwBjFlooOWPuMOafr299yaxEDbdfObXoFeMMv7eKbC09uy7SquZN/T+1dxDnnl+NLXpmL7uMtyvqqMJjOrTFjNZrPheTCphDkHNGgZg9EA+frcUJHrsomCSDujaA5ApdVk2xJZgVJQW7veHWAcbsWr8DJjB/+3tdzb2xslEqTVnkDGN550B/Vuy323B2OgzMDafSJEzMnhUgNjM046qYoLLYSGXkwkUHmdPSMsZAzERJL7b29neMdHulHxue+T/LO34lIO++R55TKK0/dWzMxOpxwlTzwey4r5Y7nhbhbeteHwJNP3HB8Xzzd5tp1RNKneNW3K5AbPe2I40Qxguf5BD8bzWZ/J1p/3Nkmr20WYkJBWz8H3tfxY4C0g3FqUywiMB5i543j9u9qa5duMKOgUQI+XEJiekm34mD0noTYNV9bpen19bq+b+k6vSnjH4wmnEzqTH+Q3YzL/T77nOFIu2IdUxIp2RtGYdidWJpQwlHQZZoiMxWkp7Un8m3VS+BnDeB3M60ecZMOt8/PzITZMJWZsmV6LsVouRTiIb63p9PR0FMv4Wp/3A4gkjcZGhT0+PtadO3d0cXEx9FVaKSChTho4fxOSJgz12B0r0Wsw+eEEhT3RxcXFaJ2PO0ayP55394XxFsl8scc6PT0dGZzj42MdHR3pgQceGMbC9UYaahuMu3fv6vLycoQMGL543rbtcTTthKJl9iutHndfSONF0LRi9HZWKAsMvU3GE1Nun3XTuzHWyd+Z7XKfub7GWCDXDQlr/e066cFcL99RYC+TMQz7QS/uHe3pnZMv9C4cs/+noDLRw3oMyQ3bCBEroifmxt+MpwwFrbxUNEJpj8PHzX96N6IjGtNEOjSGm7yZtCOKZmKaVhrvCKDyzefztR0QDF6lccwwm11v8zk8PNS9e/dGcZAn24KRuN/bfizAXnDNPksrq+5+M6ZML03BNlEBLVhXV1e6e/fu4A3oJS14NEIWKu6UYYKGbVlBCanpHaTxfX/Owu7t7enxxx9f4wF37dAwuT3zjp6Bc0thT0jPuNF98tx5zqy8d+7cGbygPdrx8bEeeOCBwfAwTuMY3bYV1nJCaGyecRlhU3wm7YiiMciUxg8DTUH2pHjQtHKMHUxmjB+TwEnxeZIVItdY7JGsyPmQG1pJrvVUXihT0IxNaGnZ/yoeSc/Otqi0jOfSa6UHSmSQ9RhhcG8ooTKVwTwhtM5NCJxjKiEViAaTima4zaQTt+C5fX649kUPRg+e56a2ck154Yp2QtGk+kGbDP5p4R2r2YIdHx8PxxnHEUtb2AizvE5Cq0pP4LapcFbYXBD3xEqr2zsYc1IQGEeS8qlWVtjT09NRzMf1QsI3L/IyS0fBpQL6+4EHHhgJvbOpKXzcasSs6Gc+85nh2oODgyFmOz4+HtADvedznvOcUaaTPCSEpSLZu/qak5MTHR4e6uTkZC184HxbufiYBnp5pu0zq819opYbG9sqmebrpmhnFI1umcpGolDR+qXVs9KazBhptVSQ6Xu365iFsIAeydafbVAxGKe5r7awDuZzDKbcWW9FtXIbKlshaZ1pwVNhCTOlcRqd/TEfql0e5p/rMKR28sNwnnPh1Dy9ISFiegSPgYrGb9fhjb6E+Tkefjx2JnYyg52yRr5O/TdftsVn0o4omhnkdDRfiWqitfLuAF5rIZNWt6xzo63LnpycDILlMty0y5v/7PEkrUHOCjZ4fanqu60648GEZ67b5/20qgcffFC9rzbZ5nM9pJViHh0d6cEHHxzWeI6OjtYgGJXQvLSgMTmSa5Kz2Uynp6dDBtBrkJeXl7p3797gTR3bXF5eDt7YvHa/Es621gZ0YaXI22eogDZcNnzko/eM2rP7P6GveZFZYxow131xcTH0xUSYnx6xop1QNGk9eVEJcgURMkNmHE5vk7se0qKb+YQMXFbwcSpDUnpQtsmMnP9zrc3HSRmrSOP1N8YMhEEM4C20/k9emTKjZu9vHjATTAGshD0TDBRWw8VqnOwPY2NuAqB82LMnZKuyh+nhMq6uDJakkbGtFCh5meNI2glF84RJqz10udhIpjsOkMYPy6S3mM1W6fG9vdUOCDPNdXi7DuOmxWIx3Nvl6/3KIBqDtGLc3e4yLO+x0mPQE5v84FALjdvmbo2pSXXMDdv/iwAAIABJREFUmtkzj4/CaL4za2u+OL6yEfJeRWZ6mUixp/NcOCPomNTrk76thp4y1wvNF4/jzp07g6eVNKAS8l0aP3rA3pVxGeWGa46ZG1gsrl+B5Rt5804Nw1/OQ7W+R9oJRZPGKXDGXlJtqTI+SkvJQJUM5fmpGM9tMpvGcsT1Fbb39ekBXZZQgyl1t+eYzILBJAYVjF6InoaTzlR/eh0nGpjlJLyygHFeaHxo9Xkdx07jYN5WyzVEAa7XMa3HZF6yzzRY3E9ZQeUqnjJyMR+pbLnDJb18IqxNtDOKZmydlltarfn4IS0Mag0Nj46OdHR0NDxKwDDHFtg7JGh1CTWlsWX17fSEfYRr0jjT6BiqCsK5HpiCSM/IneK9dz3/+c9fiwsT7jDO415PnzMxLe/4hTtraEA4flvye/fuDV7GQuzjvt47QtKz2MORD/T8Cc9SkLmWmf9JVmDv6Eilc58Yw9tzsT1p/SG3juUdR1Jmp8IJ0k4oWmZ2bJE5YYxjmNzItCwtmYlMtuC4vJWCATWzX9lPt8E6qrbcf47B59ND21q6Xv+3QNGw5Le9jI0K4avHxfL2DNV2JvKNd0YQzjFWTaVmDEQvm/ObY6rWCclLri3Sg/gax9k5TzaUJsoKkx+kjMvIk6oNj2lTIkS6/5fFP0/SX5H0OyV1SX9c0i9L+hFJr5D0K5Je33v/1La6iKWPj48HgaHll8YvGOTzEJf9GcpTWegte1+9A202m61lrjxpLCNp5Ok2Bb2eTMdEvsuZz8TIHQkJmexNLGhMc5sHrnt/f38UP9ryemx+lgn5ywyohYW71CUNMTPhLRXN/TZP3TaTUf54HPzv8TL2mYJkFHYaYu+ndNnj4+PBczuu9HkuvTBxxBjfyIcbCrizP/vHOqobjUn369HeLulv9d5f11o7lHQq6c9I+qne+9taa2+V9FZdv5xwI9G92zJLq8VDegd6sPQePE4PwRiQAkUPI41fEUVPYGEj3PI5/s71mbTiFpRsN6/lWCzcfCgPF8OtMBRILin4PxXN19Diky+Edfau9oj0GJ4btk8PyLiJnns2mw2eN7PE/ib8IyXiIK95jIviOZcsTyPINUG2mxnYdAApV0n387L450r61yW9adnQhaSL1tprJb1qWewdun5B4UZFS6bao929e1fSOEBPmGhm8Twhoa2TBYwWSxp70r291W50rtO5D6SEGPaKXBpgwsHZP3oyCjs9sy02lYlxztnZ2bB2lULmbJsFan9/f9jNzmyhx+DryFuOm89kMb94PBM7fpo0M5ZTQs741IaMCQyiDSuopHJXDj+Eu/b89MCUH/M04TAfo8C48vHHHx/Fuu6zH8s3Rffj0V4p6dcl/Q+ttX9J0vskfaOkF/XeH1uW+aikF1UXt9YekfSIJL3gBS8YWUammz3IxNf0ZLkATEZK4+e5m3zDXlpjKhahAi2Xy6XnYbtMiqSSEbLxOsZxtKaEwiaW8dgZ/Kc3oScjfHIdhIDVODFva78rz+I6Eh2EDIzGxZ0lVEbefUADR0/O63Is6VHZNxtCH6On4lgpA4laTE+Xou1L+j2S/mTv/b2ttbfrGiay4d5aK1vvvT8q6VFJeuUrX9mPj4+HWMK/PSivK3mgjG1oSRnv2EsZaiX5icLMdJoIV90PW24+BSrhmq2fJ8ATxq1XKchuz+NK5SNxn52FxLEIx2A+0ML7TuL0Kib3y8KbGdDsqwXX5yj09nT2yJlC9zHykKiG9695HPSOTP8TEaSnZrxYJSzs8Q8ODoZYlorH/rpfhL9TSaqK7kfRPizpw7339y7//zVdK9rHWmsP9d4fa609JOnjN62w2iFhjyaNt8uYwcbUTp4kTmY5Wmnuwp/C++6T++E+ZDlaUZ5Lz0YPZJqKK6V1z83rOakub0jlPnKJweiAxoEwm0pcwbq8JzChM2Mvj8fCyWe/sN1N3pFIwwqT6200TPSOGWvSQxGyU9ZyHhhj2qPmfFfx4xQ9aUXrvX+0tfah1trv6L3/sqRXS/ony88bJb1t+f3um9bpjB6Vwmsz0mrxNZ/Eu1gshoeY5uKhGZvw0v+5M8LlpbHg25MxIUHmM+7i5BOmMbOWsZ375f/cTFx5nSX/B8GiIDNDyd0Z7jP3W7a2uiuZu/ZzGcSePbekSeO3zTj+s1KYH94d4nvq0qsT+lUGy2jCXtY84ROLkwjvck6Y6Mi5cX9ovH1XBOeISa1N8Nh0v1nHPynph9t1xvEDkt4saSbpXa21t0j6oKTXb6ukws60tmQKr2Fm0p4vhZbHMyiXNBIKCyutnetK3J7ZOu7jS2HN7T4mChWVNyeMwuw+VXCO5ekB6KnSm2aMSWNAnlk4eVMuv90/Lub6PGE8s7oeRxVvUkForCovaMqnZbkMlcxzTH7kDhBufiZCyLCESraN7kvReu+/IOn3Fqde/QTrGVlQZpnskSoBdZLEiYvz8/PRJFnYmaXKb3oPaTVJCUuoWO4XlZhblaSVktsbcCcEM6wp/Ald3UcqmoU1y5ncLwupvU0+nyOFlnFv7jnl/ViZvnebkkZ3gTOeoTfmXEtjw8TdGI5taQSceidfUoZs9Kio9mSeYyId1+P1ML/nzjH8po0OlKVNMHIndoZI413jXieyQHE7UCYfzCjCNFo/Kxq9HTG2BcPHLaDeRJsKV+FyW2bGi9ytwDfWMPNIr7pYLEZCZe/hb/OF0FJaFzbzhPCYSk8Fo6JX+w3TqxmSmqeJEngt2+Rxlq+8WGYdyXPeOMs5ZpZVGj92IHlksuHJJRnurDFcpOGxgrp8Kt8U7YyiSSuL4JjMsdjJycngyjNVa9zvJ0MxeCeD/IJAM4q7Ahgo00IzPUxlZDvui5XUikuBsZLnrgx6Q8ISk9vwGJwBtQDQw1DZq4SGY6cM4hnjkeixCJ/cR8d0roN9lsavnuUYM6HCfjNxxKye+e41zrOzs5HRtVGrMsLcYeQ2mfFk//xhVtH849OWzcu8M38T7YyibcLpDzzwgC4uLnT37t3BctCq+5pqwZjZK1o4W3x70moNJ61yJkoYSGecSevtCbEnsAI4wWDvQAtNSGmP6IfbWLA4VpdnbESBMW+YAvdYKHiEqRQmZn6l1QNpHbORB+Qh54fWn3xiOXpdJ2cI8zPMYD2cK34TAmd5y15CYlMuKWTszn5sop1QNEIEaSwE3sPm3RDS+Nn1idEJJWntKXDSKhYz8/gU20rY3S6XFjihnLhkPuMe9t+xG4WZcJXZNt/LZX64XsY10koRfM7eM2OzFHwmOzIG47XODHsHfO7SYPLFdadiJCpIpaEnoTIkvynsWYcRAGEvZc19Yl9pNDl3nqP0hDdNhEg7omimDDK9adaxAV/HI40XQv2br2OlMpAoYD7vpQFPoC0/t2JZOZgFy6RATlL1n33meXoVabUu5pslmVVzf9KrEo5ZiPhC+8oozGbjlwJauQlJ6ZXJQ/LS5RJyGy5XHoeZ1Iwp7altBAilybvKKGQ8KtUvJqwgM5GBYTvLM1vMudtEO6Vo0sq62pIQKzMpYstnRhFW+Om4Pp7CkMIvaaRAFrxc6ExrPaVgVIBMJbP/qWi0tozNHA9ZeGjNEyK5HhoraZXZo3B7/Dkm8z4zfIvFYrRThuNORSP89vyl96UyUeBdF8uR/x5T8tEfZi5zTJSZ/HZZGnjOF0MQetvsf0U7o2iEj7z1norBCbRwMFYyxKJw87rMGFYegKlhSaNbTPhJaDMFhzguewr3nall9sXHmG20sDFu4iukkk/+Zl9clomdKZ7QO0irLVaMa1k3oRuXVnJdjZQbks0v1zsVC/NDfmQ9Ho+VhXPiDQ5sg/zjdUyyuM5Kbjcp284pmj2aYVridFp1KpoZkul1X7Mp9SqtB+b0NlQ8l81rqkB7SjmtzPTC5APLJVyj0FQ7xq0M2R9SLofQg1Re1zxwfSno5Ivr8a54psTJO7fF8WaCwdcww1gpXMLhVOpq6cJhBpdaEu3QC3v+ydfk+yb4uDOKZsjX2ur2CFscEi1IbnHiXse0xhZWJguoKInprQxWVjLRnsX9oSKZUrhdlsJReQ9aWGmsKBYIQ0lackM0Jijcd64Ful7zjhCJfSYfW2vDIwrcb8Z0pqrPmbDix0mo3PRNo5uxJfvAtqhk1TVM85PXPsZkx/7+/hDrcwtW7mqRxu9Z30Q7oWiJoS0wU+6Yikam0pK73rzedVIYCTdyIZl18XgKQwqy66v6n+2mkNP7VpDQ6X5CRvKqykImJX+Z/KDhSe+aULEyKDQm9OTphbjcwli34ltC5Gpuq37Q2yXSMCSsoKP7lUqc6GObJzPthKJJ1xN29+5d7e/v68EHH1yLI7iYyL1stopc0E34RkplcHkKKZlJmOV+EJ65/lQO9iPX/BgzZj/cJv9b+Q2lMwmwWCyG2zsyZuDCPKGxy/hRC17Tyz2dXA5xvChpDUoxDlwsVm/c8XgrmEdlzu/KS1XwjmOpvDIRA8me38Q59rW5iZnj5TIP+TRFO6VoU50l8/kEJTOGTEoMz1iOkM+UmNyMzXIJNW0INllWJjAINa0YabnpWfO/vUrGT2lUKAiug0/H4nnGnnxndSadpJV1t3CmNc+YNpcBUoHoUSvDV/HDx/J41lEpdTXvUwZw6rypgraVASDtjKI5jT2fz4fHSJuBxsvetsTJ5oIpJ8RCxcXatKacEAbrFmoy0RuWCTtSyU0ux8nmRDDdLa28RRXvmCzkHn96EK4ZWlm4jkUeUQnt0Rxr2GsmPKd3Zt+mdpqwj+RNKlsqlcdKquJWGhrC2oTjGfumt/a1fvye6+Zj5Xgdt4Wlp61g9MCnyTPPAHlgGRznFpqEdlMWMa28z1VBP2GLj6cX9GTx+vSShk1TcYnrYZ8zPc1yLE+vQqFLaMRMX96f5/8WQO735PMOrbhsP5MLlec3D3g+Y6D0OFOeYcpbJJ/o2av6LQdEESxjY0NlJXox/yhHuR63yZtJO6Joi8UqVX11daXf+q3fGq2n3bt3b9j1nlk13lDI7UOEgISUpozF2Bdp/KTirMflCLNM7lNFU8Jl2MaNuIQmtrSuw32n16CSeD9l3ozqcTELu1gsBmjpF1cQIk7FIu4b0QW9K2Gk+UdjQmGnAUulqZYgPP+pWJXBSYV0neaTl4S8m99y5LlIJaPhoiHIrHPSTigamdTadSrZd+YShphBVCb+T+XhWpXbYZtVP9xOnqeyJXSRNj+eII9TwKRV/MMUs/vf2mqnDPuR8ZKhru+nskfKXeXZd7fF1DfPe04qvlVIggpc7dyoPGDlZZKvuY5HpaSSs0x6JpL5zSSb+ZAGj8Y055Rj2EQ7oWj2aGQU7z367Gc/q9lsNryk3d6PgutNtyQKIHc2bMLS7k/CQ0Iul0nYmALjxVATBXNTAG9htSfiliIrDxXNHoQ76y30VcYvl0Yck7huK3cFiWgcEo5xAd5rfUxSpZD6nI+bx3wwEz1eGqb0eqmo/F0tZ7gdt2Ul46MzMgvr/7nUQN5UtBOKJo2ZZ+Za6JiYYHaMAzSjMinhbyYoXH+VhTRl3RQWlsnrCTmTLLibsD3jnoRMHMuUp2Q/0wtuEozqXMUfZhnZH9ZnweYmbQp6zkten/1xn6rNBuRjKllS8pPK7z5z00P2N8fLfm6jnVC0xWIx7DwgjLx3794Qfy0Wi+EF5fZgvsnSK/lcxKXFllbPaTQz83HcFZGJuROiUhImFnKtzH2iIvp6PtrABqOCaLT8BwcHay8/50M9XY//845vSUNZPqWXbZnyEXgZ61p4jT5o+RPS2WC5DAWZypYKldCfMTrLEa2kAlQKTYjOe/6YiTXZe7PuNALPCo9GK+UP7wNi/GULyewbvaHLZFqZVn4b5eSmZfa5tKxW3mzb502ZzaRyWmiyDxScXFyl0HIR3eUqL+tzleU2bfI6hG/Zt+RlxlxV/fSIeX1VH/mSMVp13VR9mYjhfKWyZj3bYjfTziiaNJ6E+fz68QNUMr604Pz8fHj1rOM3psmd/XJ5e7/MQKXlmxJuxgr2ThnLuV0Lbi5LMFa0hbR3TljjWIUClFnVrDMV1OcJrRjvzefz4YZXH2P55CF54XbyMQFpYFIZSHzKFGPZjHurpAfH4nNcn2S7vFWICmFjx3rcH/cj+59yMWWEknZG0aqYIC1mdY6ehhaJuxMYm2VdqUh5jHQTLJ5l6N02TchU7EIeZJxVTTzHRqX2+DKzSA9YWeVM+liQCdO8kcDlOSa3UfFuyiP6P40mz6f34djy2srbbTOubqOKhzm26nuKdkLRCJ16Xz2GO60zJ/Pi4mIU1xF2sl5TbhUitmbZKQE2UfASImU9/O8xUugyjcxyPF7dd5Z79XI9j4vVVjivn7HvjD1I9Fjkk1PiXFqo1iTtGXh3d8YxjC/Tm9Lw5Z7DTIYk3zLryGy0eedx0HPnbp7FYjE8ICpT/FXS61nj0fJ3CqG0vrUmmU5GJ0TINLDLJyyaggj+zvjPRC/Ba9Mr+Jt7CxMScVy5ResmSxTuKxUqIeVUAiRhmfvcWlu7R24qvjNfvUPEPOacUEEt7PTihHCJZvjN8W3y9JUSmhfsN70Zz2+Cic8KjyatsoKttbV1IG+PkVZ7/viqXO5J4zMeWls9C9AMzoyey5lRfGgPhSI9DrOEvp4ZTV9PJaYCUkjoLTw+93WxWAyvCjJNQaaKEv6kdWZ8yLrtRXJNL4U0vbSNCtf6ctzOgvKhRPYQbMN1MpvMD42I+0oj4P74m3siudWMBod3MeQDWJmAMm9p1Hfeo7mTZDbPJSzKBAQVh+tuVIq0iqyryhBSOaZgYl7DOivLSuXkNTzO+IdCUcUVU32nYNOjVG1XClPFNsk7KoXrZb8qz155HCuehZsJD1+fO0wSrk0paFKGDawj4748n+gg+/CsUDRpvO5ixvJZi17zIUNywFYyP5aNQshYLOOACpaYWCbhD+tIq8Y4wGXzbTkJ3bgzwYKXQuYx0NuQL+aV41iPnTFwelvGchwz+ZSxmqmKmyiQ5FXyh3NpRGA+UHHzSVQ0DpznhLvJ59yDyj2gjjvp6dgG3y/HfjCRtMkY74yiSes7J6oANBeDaYkpuLSIJuJ+WuzE6FVfzFRaXJZjfxlnVQKSHjs9CCGTy7AdH8vF38zgMS7NvtIKV6jBx/iw1spIuL3KqpvfVbyU46aiJSJIj05FS9TAPuW5KU+X11b8IY9onCtZrWhnFC1jIGnsXfb2Vg8O9e50WrKETfnbGN1exd6DKXBpet0shY1xocvb6nFjak42DUQ+0qzyppuym8wmVkJGoSA6YJbNVppZN9ffex/iY3sZ7h017z0/0vgJUmmUcmwJkwkfPWeMrXLdjI/C8zfXJ5mVrfjkvtKgmdfcUZNrnzYKvAviaVW01tp/IukbJHVJ/0jXr216SNI7Jb1Q16/bfUO/fr/1VqKAuPPLdgZGefB5HXf/ExJUCrTpe1Pf2FaFyakw9Ez5zeyhJ41jqPC/f5PSyvI4r8231xAJECXQK1oI0+jlmuA2qpSMnssf84Lzb56lkpGfWT8zvIkAGG+m8SKEpZwlPE0EUeUVKrqfl8U/LOlPSfri3vu91tq7JH2tpK+W9N2993e21r5P0lskfe+2+sgYdz5x/WKxGF6G7gm6vLzU4eGhzs7Ohpdd2GN58nIhk21NpcnZpq/1t+vPNSj3x3i/ylD5N3fWZ+LD7dAj0XqS6NkT2qXnZLzr8TH2cFsJ6Tg+1j+VHq+MFut1O8wE08BkLDtlgOg1pXH21vV6/u0Z3Zd8o4/77lzA0dHR8Dri3MVv4+U2thlp6f6h476kk9bapaRTSY9J+gOSvn55/h2Svl03UDQybCqYnc/nwzuHyfjE75yYxNk3pcqy5u8UNE8+H/5KC5jxUU6SoVSur/HJvOQXs6mV12M/M8ZjnETIVnlNtselC48ry1dtVb9Teejp6XWqTKmNFfuX8ViOpYrD2C69GeF0FcPmeLfR/bxa9yOttb8o6Vcl3ZP0d3QNFX+z9+70zoclPfwk6h6+OUg/5tvP4JdWTxK2JZLWYzZac9Z/k35knMEAnLEIy1FQGBu4XQoQx2UvnGtbfDKxr68SFRUEJE3FoTQC9LK8hrELlZvlyIfK+/L4bDZ+5ZQVh9nTVLSsm0pAMtpIJJOQ2nVbhuyp7MnszejROBZC66cTOj5f0mslvVLSb0r6UUlf9QSuf0TSI5L03Oc+18ck1esu0jgd6+NUMEnDu5uTEbRQ0rQlrhISSRkn5O9MdTP+cJ95nNnKDNYrb8QYiwJTJU0o8HzFksmw1G2kcDKemuIBz1fxUVIKbEWMhal8OTbGdVMeK88x5ucjyx2XJdTOEIDf1Zgquh/o+G9K+me9919fNvxjkr5c0vNaa/tLr/ZSSR+pLu69PyrpUUl6yUte0is3T4jAe6fIfJMZlfsjh4EuGZheJfF9Qr6sixNOQ0AFo5InNGJ8sOTb0B8KKD1xQuBc92IblQGwl3USifv0GPs5BqbS8w6EKQPI88y2ks/sO+vg2JLHGRokVOcd5qkYGTJ4LPSChIOWL34IIRMqZ7z4dN6P9quSfl9r7VTX0PHVkn5W0t+T9DpdZx7fKOnd2ypKRiemnwp6PSH2aPYWViqmzA0LLMxTMHJKwTjxqVBpLbeNNeuncmdG0NfQ83ijq8eTnrFqw8JoJTdPpyBWGo5q0zBT72yPQjj1yGwe28Sz5G+eq3iZ26WYIaRSeKyO+w8PD0c3wpKXKaPJ46cNOvbe39ta+2uSfk7SlaSf17WH+huS3tla+87lse+/SX05iJw0ezYLizR+irDJTy3OfYNUPlrHqX4kA9N6ZzayqmMT8wm1uBbFrKANiAXe4z86OhrKMXabIisUBdBxzFQf05tUeyLJ3wpaUtCZ4av4w9+p+NV42EcbjjRWzAjTaBGqm5+Hh4c6Ojoa9samJ6v6SI+f55PuK+vYe/82Sd8Whz8g6UufaF108f6fuLeaAJczo22d+Cg2ZqfoDSuFZmIgPRVhVoX56QkSEoJnaxm1qh4KiQXn4OBAs9lsdOtGFcO5Lo+XySLXz2evZNvs61QsZk/KjboUYMLgmxqjVHzy1EpUCT6VJ2NxyhEVMb0eoeK25Bm9YfZlinZmZ0jGItK0xcs4iLsSnLnzmzozK2hhSyhEz5lW23XTSme2jdk4jyUFJ+O5JD7jg2QF8zd3lbudCuoyxjAsMvmO9CqmnYo5ecywPKGj+cAMYsLHTC6kwrgtxpIpA1U9/mYoUSlalezYlARJY1T1JfuTtDOKllCMTPd/UsYzHqTTsxRkpnutFHyUtSeVyldZs/SelSGgx6sSJy5LZfZxCq8FwoKbSQWOuRJWjyEVnZ6WgpzKREXh2iAVbT5fvcCeSIFxo/lPo+h4iVT1lQkv9js9eD5oaJNSW6E28YeyknypkljpwSvaGUWT1oPxhJMmClsKHdeWTKlkxN++XyozXVz5r9p2fzdlIamUm+AHJ5LlGY9yOxB3lyecokd0HRQ298PHHPdxvyD7wl0W/E+jwMRBKoj7YFhfCTeNZcJvCnKVTaTh5Nt0yBuOP5NnLuf/7Adlb1u8WK0bknZK0aT1tQ8OzlbSgpSpYtZBHE4rl6lxZqQscBQWQhmXT4xuZUwoxljN/eRvCgFjHteX7+y2Unh7l9cL0xNXj0mzJU9Pyt0o9GR+MJBv2cnHKeT6mm/JSaXhXDI7SmNCQ5ixYqVg6aUcs1bQrkIyBwcHA695Tfa9MqqJZGiwnjUezVTBxHTdhD3pvahoXDvjce6L8zm2wx3dtLBTisNdHUlTEIVrgq21QclcB+80oLf1fz7Rl21Viua1oYS//uazQHrvQ7Lk7t27w3F6W8ao7IMF++joaM0QprBW3of/bVjIMxpal8tnTybfqWR81DzbrZTM53MMVciQbSftlKLRskjjvW+mynO57JRCZL08npCFijKVvCAcSi9FYp/YHmGaFY11MbPnTdMcmz0QYVzlITYF+9xTSc+WyQ6+gKNK4BApcE44D0QX+QJDzmHOG9c9eT69W4Uycn6rXR+JVG7ymlxCSY57G+2UokkaMcFERm9yz1V2KmFBHudkJB6fUjTWkYxnn3kdvVju0M82c1mCClYZF6+jUbgtWP5tL2hB89Of3W8qGT0PIWOOvfrN8dMjeQ6qzNyUV2OcW7VD+M85mFK2jBGrJFOVBKvGlgY/b91K2hlF44BTyBO+8QY/xlG01qa0hrTWGfyyH4yv6IUIu1jeRMvuGICeirtVzs7ORtdcXFyMHoGegpCp/FR+WndJI0HPzJ/56SWDVF56SEJpJkGmyH2vEjcZX6VnmTKSGTYQenP81W+2ZT6al1RAqY6jfY3Hb774OHeSTNHOKJq0brGqTE9lTSpo4bJV/bTaibHNcAojkycuw/Q1j3Ny0kNK41tDmGXMGM1l9vb2hhR6Nakcb5X9IzTkWMgLCmF1g6XXwuhZqtg4l2h4z11FyacpQaVSVZ+c38pLUak5juSHKWEoecIEDcvuvKIldMvJZoKCFrBihMmWyt7BVouCl5bUE8r6UvHSotEScgMurW720Z+zs7PRzYj5uXfvniStvTwi/xsickE6BSo9mPtJb1X1M9fROGdcJkkFd9/Yl7x/jJ7U/fFj6EjbDMs2Qedc5f5Xt51jr37Ts1Xzuol2QtGk9XT+1GBTeDbVl3W6rqm4ytdVywa04hSsXPRNAUyr73ozmVEJiQXOHo3xWm6MTQORa1kV0Tpvs+CpZFPeg/UkLCf/Kp54TPSO2V56sJSDTQkvEw0iKZU+x+IxUH48J88aRZPGAkLL73P+tmByXa2aIGk9UzWVaGF62m0k2Wv03ocH/XCHSQXtaG2pLBYs7jn0upm9sL9Nvp6ea39/X8fHx2qtDdvOpqCqpGErFvvL/llhaflpeDwubnhOD57eh7s2mIr3Zl56Qc6BvSg9V87uiUNpAAAZW0lEQVSp/5tSQV3fpiTMJg82ddz8uUmmUtoxRUsLPOXSqYQVRmeZtGYsVzG4mhBeRy9lqJOQN8sT5tHLGgLymYmZRODanK9nhos7Xaq+0zD5Wnvhas0ohdp1Zvzpa5gkskKZCNmYXmf55B9jZ7bNecvfN4nxkieb/t+EmKi6Ce2MolWLoVS8XE/heZZhfbS2FrhkTr4UfUpYK0V07DJ1rRWAi6TpLb1fMD32fD4fPBrvjGY7/u340/GXx8zgn96Fys5xWRFtsXncXjAhs3la7X6nR0nP6WuotPSyOb8eLxGBz+emA7bPMTtOzGUSzon5ad64rgxB3IdNckPaGUWroGLCOhMnhsqZyjC1/pLX8rpkKMtPWUwKR6aYPXFUNE+6hToTBZmCd/tp6V2WnohKRshnPrhPCSnJ24TauYTiNqjAVhouCJvyjgQah5yrqi/8n3NSwc7KQ7uNKp7y+HL5ZBsxxq36T9oZRSMl5k5PxliugjqGJ/SSU3DRWJvWkoLO17hmLGPLXyUT+N/Wm17W0NCxGndqcDy55se6GfN5vBbeKqNHZaTwsW72z4rFux2qVHjlwXgrT8ZK2T/W4/5WsD+NMNe2LB887htkrQi8R5FKYqPBRI3b5bJIFQvy/CavthOKllbpptdI9aLtVKxWXc+2CbW2rfRXiruNKOAUKv5O6+qyPD7loa10/Ob4yQdCyE0ZPhoXXscy/DZRqfM3DZm0nsDIxEMaRyKYnL/qGl+XG38TCvr7iXi3So4q2glFS0oMLk2n5TOgJ9OJr30dIR73DDKeM/SqkjPMdKZHdL3uB70Db5B03f7PmMDE8dgbmqaSLqkEVazr84xXq1gq48BULkNF9sH8qOIxQs6My7JvFS9SUWaz2SiGba0Nt8nwGmdvK4NC3viYeUtU5PbScJl676O1zYp2StE2ddRUWSpa6xT6yvpWLt4KxEnOSUsFv4k383VTywWsn8fyPCc6DYDLTHk6f9NKT22GnYpFqQT0dJs8WXX9FG2KgU3VNrhNa1gMMap5nWo7DX3lBStDsUkedk7R3OFKiCism6wi71B2WVLFeGawpiyXr+WxhKo8buKzA6uyvJuZY6RXpEWvFJTjrKx6xjtMrRPC5T1aJnoL95N7GAkFUyHpKXNs0jgMqIwa62S7WSZDAHpA18lYqjK4TKA51sxdQdL4FqabGNydUbRNmRueq/A3qZqgzODx3FQdUxPt80yg3KTOqnylGNzdX7VPD75t7FNjyXO5LCLVN7iSKKTsPz9T3m1TPJP95XgrIzzVLsfCLX3sf8UXGu8MVxIuTnnIinZG0UiV8E6l3il8VRlOtC0Q4wjHahlbVUsDFBDGdIw/ql0UVEz2iR6OD3h1doxrNdybycln3/J3FfewTxTOrLu6mZJLCZnBdH3cYc8lhlSs7C/5Q0hoT8I1MIYJkoY7rKs1vLwZdzablbtR8lqfd3vcASStkE/GnFO0M4q2CWtPEYVjm9UzUbk4odtgja9l2y7LiUkB5nXVdwqyFYvGI5Wy4kP+nrK47Hem033cx2igkgdTY3T5bf2dMhLuQ84l5YPp9E08qjy2FTShNJcIKuNKflV93kY7o2gmDsCQr4Iatjb0RFS2DJaNpf1ap09+8pM6Pz8fXg6ez9PILBKVIOMm9vXy8nLYJeHrbqosCX1yNwnvv8uMbPKOdUrjOPeJCAm9kuvJ7V6VsOfShPtDhZmCbhTuRBFUtqOjo5ExSNiXxtJKlo+G8PW+LjPTLMMYj21su9N65xStsr6k9Fi5hlKV5V4/luNkTrXNyfP/XDJwXZ7s6jfr4v9UhMqTcAtRxqpVrLPNo1fepPJeyZNsI+PNTXHSTfpWlaOy+H/eSHqTGJCK5POVkZ6Kvcn3nN+ct4p2RtFo0W258yUGti58Oi6vz138VrLer3fGc20kLWtCIXvLnAzeAMn2+ZrehCHOXknrL9kz/qdBYHxTeTK+SIJ8Si/L/9z7WMEjeimep2L4m4aLc8bxus8JZVPRqPhTHokxmvtaPf8jwwFmn9Mrcq2U2V3Hgdw32lobeUHPZ/LzWaFoVSdpJTIlT+vDOioB8eQ7GUKMz7aqWG1K8aQ6U+o6Ki/JOrPf0gp+sh56NfeD1jdvZMyF6BR+lvHvTXCQSQLCwfTSbCeVMBWL48v5uom3y2wmeU2EwaUAEp/FQniaaIfjYp8T0rpPm2hnFC2pwvG2NsxASeMdDbw+d9anxZKkxx9/vGQ2rXfWJdVQyxOd0KyKNzJhQDia62XVC9sdD+ZmZD9zJDOD5lEKiL2pLbjH4Tr5TBEqXqVUmZWUNFquSKPp6xJ9pIFNeJ8GL5UieZ3xt6S19S9CS5+3Acp59n2E9OT5KuWknVG0DJpNVg4e25ShJLOqoJUK5cVIBryVpbViSxp5A/evMgpTfXP/LRDuZ445jQbPuc8ul89xtBGplIBekn1PQ+Xy3ExM5c1HGFR995wmjzfxbBO8pEdN78UxpDFMdFPxlZCbPMjkU2YwCZ2reNm0E4o2BSEq2GiLbso4Ku8M9v+Li4tBaaXV653y2YH+9v1XfhmEyySUM6U3TCHMCeL4aHFpRXPpgd8UOq7x8HqT+52eJuEfaZsHq3bx09vYe9pjpsfIuc7/lbKlZ6URpFFgX6XxM1d8bc4JY2waQYYo9Fyeb8pExUfTVkVrrf2ApNdI+njv/Xcuj71A0o9IeoWkX5H0+t77p9p1S2+X9NWS7kp6U+/957a1kVRNBiEE4xdm4nitGUPFi3GNLHTGRukZraBVNiutnctPbRVy+6ncqYDJA47L/c+6q/iIik/FSW+U8Wd+qvbz+oTSvIZjrOIxHif8o2Fh2WrJx/1IBFQdT15XMpAGJs+7/mreSDfxaD8o6Xsk/RCOvVXST/Xe39Zae+vy/7dI+sOSvnD5+TJJ37v8vjFxsMTujMsMRzxY76QgZPIuDT87nlYvLXPGERXU8DFicTLbv5n6laYtKOusEi2ctOybJ5+PJGCd7kPGZGlcKujIfptfWc510YuwX/zPtVB698obcv497vl8PqyXpXA7zuLyR/aJdbPdKTg5tSyQ/PN4mK3cRFsVrff+91trr4jDr5X0quXvd0h6j64V7bWSfqhf9+wftNae11p7qPf+2LZ2NrQ/SsFmypeezkkOZuh8nHAq1034X1qtlVR9yVs1UkFcfzWJCTGq4DnLG35VfeCygMtT0XOhmX1Ob0qYyPL58Jm06oTtPF95ivzt/wkRk8dEL7yO7yhg3ZW3ZjsVtE6ZoMFIXpEqA1HRk43RXgTl+aikFy1/PyzpQyj34eWxNUVrrT0i6RFJet7znsfjo3LE4Vw/47c03pZzeHg4PPU3n6RkopdMi1/0degL0+v0iBb6ZHzCtMprTE0SIZrLMzZwPfQyGVMwOcIx5rjtFTL24ovtzTfzm31LZay86RRcrDx9bjJI6On1w9basNuHCpJ9IF8IJRnPsy/sdxoRGnz3b9OTm6WnIBnSe++ttSe28ev6ukd1/c5rPfzww51Wg8rFGzMzDUzIlUJMaCGtJxC8udgCR4iU3s39cp0J1TIOam21wJnpdwoODUAKecaPrN/tWlD4osWEaVz85vV8+hTLJXHh1vxIj14J48Scr8VnCeXy3JSHZCY4lTVjpvROl5eXo9CjqoNt5f+qL9voySraxwwJW2sPSfr48vhHJL0M5V66PLaVMvNnRUpFo7JdXl6OYi5aM3orCyXjJdfLV/E6ViPzUtgTwlpZLJCMm6jo9HhUKMeWzh5S2RMSmTKmqKCiyePm3QFU2ozRiBB672vP5nd/0jhUiuj/aaw4jy6fdydwzqjovpZxN4WfMZMND1EADXAqDBWTXjDHzrHdxMBIT17RflzSGyW9bfn9bhz/E621d+o6CfLpJxqfJSOrWIy/TVS0fK8yLQ53R5yfnw/XmhKeUcHYHj0bLXx6Kf630FioUondl4SMaTEzZsvHDyR0tKJlVjG9E/tib0FD5j5v8jipqPlJPnJs5Av7yvip8oZOzeeYsm+p9JnAMC9NVF4eSyN1E7pJev9/0nXi459rrX1Y0rfpWsHe1Vp7i6QPSnr9svhP6jq1/35dp/fffOOeaOzJrq6uhidQ5TvL6Klooas7YTkxtJCu38dNPC+t1uZYT2ZDrTxetPSkX1xc6ODgYBS0W8nZJ9btYxQK09S9TxZOt89tVS6fsVbGrAnhbKz4bBALIq1/9QriVKzKMLpcIhnzr0IXnHOSEU8ak6m4kW1lf2iwKsq2q5tKK7pJ1vHrJk69uijbJf1H2+qsiMkJPhYsM02ZgZxK2eZukkyzGzKmlcvJMePZtsuyT27TC+D5FC0aEQuEhcrW0UsH3CybkJj9q1LtCQ0J8Vje35Xw977KdOYjzzPeTA/osky2ZNKJqIXoxX2aUpZUMvP6/PxcrTU98MAD5Txyrqr59jgsFylTJMvMJmWsaCd2htALZTbQ1ppWkZPLjJrrquIAxjAuww24tKakCt6lZ/Mx99NegIpp4h3IbIPtp7eRxgJIy0uF5OO2cwyss4KkHJO0UrDczMxxpNdyPyuYn7xKJUsISw9UeUP27e7/1961hEpyleHvv7f7PgUzoy6iETNiUGajkSwSdCE+MARx5UJx6VIwiiAMrlwK4mMhgiguRFSMQWUWisasRxMUiZmMUSIaQZ2Aj5nuuX277z0uqr+ar74+1XNzYarK4fzQdFd1Pf7zn//7X+dUnem0IU+Vj/czedQ2e/7nMnTgUj5atcz1WeP41n96IPdCJO2oxWJRL+BHIth0aSF6Rvdkbk3b8iEqWm6Na+dTQxztIA1VyD+tsI7t8Tz+57mekudK2gbud0BoGAncVDBV5LbcRiOEXMFCJzrn+ks9Be/tBS5tG4/RfMn7iimF3of9zaEWvb8CgqDR/sp5MD1O5cLrePX5VjQYoLm30P0KkMVigdlsVodCWunTNzhR8Ds7O3XlTENGfnxCLq2fLzLvHcFQR5WB2674/N9DFg/FqFz87bNY1DJTHlqc0HaQImIlz/KQ0Sf98jwe7x5I+dVilUcbJALLtzXMVd7V2Gl7ta88HAVQA1Ajl5zhVqC5vPQ8Pc7nn/L3ScE2CKCpRTo6OqpfL8BcjeDgdCo20IsbVETNWYBmSHB4eNhYKklJr6sPW6rX8zDIByoVUPRaBA35dy+jYQh51lxAq4p+jIZoel/KdTQaNXJRVz4vNGjpm8aA+SOVW706PZN6dff6DjQOq7QVfVQvNKQkUen5AlW2dzqdYnt7G7u7uwBQD2jzXBa/eG1tP/tdjUUOiDxmXZiYo0EADbgJNgWcjqPp/pyVAlbzCLXK6vKpNDmLqmGTg0xnRbgHUEvsHeQJtwJLPZ92ouZrnmfqMIGXwXk/VSTlx3NGykfzVrXUGkkQWN5nKg8PFdkvvk0+cmN/zpuDUb24AtvDbW5rPkn5KHn47fdu2345YBsE0I6PjzGZTHDjxo3ao2kuNZ/P65ARaM7bWywWmEwmDUHqQnuqfMD6uXZeXNCO0cfheV7Oy6nSUol8gFQfsSeoqNhaGaQCEJjMP5S0oug5GuXjoWQuB2MbaIQUaCmllddqK6ByOZoOj3gomVN4NUp+HPVAU4CIaiHDzc1NTKfTWk+AyrMx/Nfzte8pNxpz3t8LRxox6LnkL1dYytEggJZS9dzXwcHBSvzuoaQWN5i3EIDr3L/OIlDSkIvXzG3z2sqzX4ffXskkn3quVwB1BjrbyLI199GAqCJolY+86serpi4/zzlz5W3K3hXu+Hj1vfbqGT2U1PY6rfMOGqrrcbrqKAFDuW1tba28v7HNI+VA5IZmXfTDa6+jQQDt6OgI165da1QT2TmM591C8jcVh0vGzmYzzGazlZCCs/qpfJ647+3trczw1w4g0OjZtGIF3AQ9ZynoQ6feQWwLX/xJMFBR6PH4Gu6DgwNsbGzU08RoWDTXU2C6YVBQ6jfl7N7WPbfmYrqPuZsrs4aYGlloxJALGX3w170tB91pkPnwLg0G78nIyPtTjd3m5mZjMoHy6AP9WoxzQ6aGah3YBgE0dhg9GYHgYYl2gD6LxDCNvzXR9qqY31dDwFyepeSKqpbfq3TsNN4z9xCo5xVafPCwSiuPDHW4nyGl5qg6QK1tdB54P5eXF1Y0hFJg5TxdDmien56kANLGo3o3Hz/T/tfJ1m2eyaMPz6v1ng4yv++68HEQQDs6OsJkMlkZp8nF9eo12Gmj0Qjz+bzO7VJKtQdTQI7H4/rxGfUEuZhcSS0xLZzG90AzqddkX8NZoOlNdEENKrl6Ip2dERErL4Thsdvb27WMVC5t93VSA6Z8e/io3140cM/uMlSl5fVzPOSKTyoP5yuXIkwmEywWi8YLVjWf1H5VcLkXVLlR7mq0tK3/NzkaK4rcVqD5GAYtt3Yuw0u1WG791uUzvL57lNxxqgxtVTyvCJJUUbxy6f+TT/LjnaxhDu85Go1WHm05aR8ogFzhtJzP4/X6ClBXPA9hc4UPP17BpHL3drknBVDn8vRomjfyHAL5VrmV8pSLYE5KgwGaz7gHmh2i8bp6NKAS7MHBAabTKcbjMcbjcS1UvjhV43h6Bp2+xX2eOOfGehi700DweA2R3ChobrIubHLivdT66nVGo1Gd22rRpE1ZldxQ6P2dz5zlbgtHyZcaKA6aO1DWKawWOPQ+zG01H9SZJjzPl9ZVI8FXt2u+yONy444aeubk6M/3OQ0CaMCqkuUSdm+oKtJ8Pq+fT+M+WiAKVEGg5wLIeiC9n4KFgtW3K6khcF5z4WFOwdzDeS5BBWBIzJxU28B9bhycPN9xz+yvMMiVuduKGjlPrqA8CWlfqaFkrqYeyUNfyolTsnJAYzu0AqvgzfHT9h/PXyfvQQAt1wkaA7NQoo+ub21tNbwKXxxKj8Zr7OzsYH9/vx4GoOVbN6VGedHZBFRyrU55Eux5g3YM+afitL1ExkkrY2wXvwn6nOw8mddzVWmd1KCsy6X8aQAFHq/NSqHzrNsOck0BeAxzY81RmW9r9KCgu379eqMopEZwY2OjfgVhRGB3dxd7e3t1e2gQtS/VELpcb0WDABrQFLhbfLXY/s51hgneWTxfS+3egby2egBVLC9Zkzct//L4dWBz4nn0SpqLquXO8eH3Iti1zR7yqmx1vI4GR2WtIaoaFeeFRk6rpnoNBzr3t1FbccXzOQ3p1ch52qHXcLnlrs+hApWn86TX8KryrWgwQGOIp/kav2mpmJdxRgCtEnMUTiCmFdVc5fDwELPZrLZmKjDei14mF49riZnXVI+0WCzqEjunjHm4oXlOLl/LdSzvrZQLaUlaKMl5o1wYRmNES56LMByozjuBpRO99WFTtju3PBZ/a5FIj3XPMh6PV0CjoSFlwP25IRteT0M+jqdqmz0n5vUY6ejsnnU0KKApqQC5DaxOkQGaSqD/qRDV9ee8hhcM2pRerTM7wquYPMevocrCzvFz2nhT8oKNkxoSXl9zU/dG/J0b6ztpXqXtUCCeJLzKtS8XTiswPDdeRzmAeXVZIyPVPW2/9o2eexIe4qSu73ZSRFwFMAHwUt+8tNCrUXg7DQ2Vt9vJ1xtSSq/xnYMAGgBExFMppQf65iNHhbfT0VB564Ovl/fig0KFCp2KCtAKFeqAhgS0r/fNwBoqvJ2Ohspb53wNJkcrVOhOpiF5tEKF7lgqQCtUqAMaBNAi4uGIuBIRf4xqYcO++Hh9RDwZEc9GxO8j4tHl/rMR8fOIeH75faZHHjcj4jcRcXG5fS4iLi1l9/2I2OqJr7si4rGIeC4iLkfEQ0ORW0R8atmfz0TEdyNip2u59Q60iNgE8FVUq4WeB/CRiDjfEzsLAJ9OKZ0H8CCAjy954Qqn9wF4YrndFz0K4LJsfx7Al1JKbwLwLwAf64Wraknln6aU3gLgrah47F1uEfE6AJ8A8ECqlobeBPBhdC03nVLSxwfAQwB+JtsXAFzom68lLz8G8D4AVwDcvdx3N4ArPfFzDyqFfTeAiwAC1QyHUU6WHfL1SgAvYFlck/29yw03F8c8i2rK4UUA7+9abr17NLSvEtorRcS9AO4HcAntK5x2TV8G8BkAnLz3KgD/TinxXW99ye4cgKsAvrUMa78REfsYgNxSSn8D8AUAf0G18ux/ADyNjuU2BKANjiLiFQB+COCTKaX/6n+pMoGdj4lExAcA/DOl9HTX9z4BjQC8HcDXUkr3o5q32ggTe5TbGVRrq58D8FoA+wAe7pqPIQDt1KuE3g6KiDEqkH0npfT4cvc/olrZFNFc4bRLegeAD0bEnwF8D1X4+BUAd0UEn8LoS3YvAngxpXRpuf0YKuANQW7vBfBCSulqSmkO4HFUsuxUbkMA2q8B3LesAm2hSlR/0gcjUT338E0Al1NKX5S/uMIp0FzhtDNKKV1IKd2TUroXlYx+mVL6KIAnAXyoZ97+DuCvEfHm5a73AHgWA5AbqpDxwYjYW/YveetWbl0npy0J6yMA/gDgTwA+2yMf70QV3vwOwG+Xn0dQ5UJPAHgewC8AnO1ZXu8CcHH5+40AfoVqldUfANjuiae3AXhqKbsfATgzFLkB+ByA5wA8A+DbALa7lluZglWoUAc0hNCxUKE7ngrQChXqgArQChXqgArQChXqgArQChXqgArQChXqgArQChXqgP4HDJ99pduqxEsAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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7CnWiCUmTRdTpbXKMeK4ypuxrFdpUylfRwSgaGcpjeZ5rAjmnlSvHrUCXl5eTxapUNCpDCqDXD5KBhDtUNMaJFmbWwespxKlsKRwsM+vnt+vi/ZWCEkray1fjwOychc8GKOe80rtUypoGqSL2jU9cMI422RtmH6mAu+BcQmdfQ3li//i9S5leEjEaKQfS35mSlzaeJydO8zpp6mUM0yiYFhgKDuGKM2BsZxUnVLEP25NeNfualjgVMC2xf2fZqcRMygzD5pGXXQLCzOYuQXaZXBOahir7k+Xxw8xsztVJm2VzrJu8ZtsT5ZhXhLm+jmNEyvgwaZcCSgekaLSC6TVSefzb3x5cflKBuOLdMQKJsV7CTHqiHCxi9119Swucz1hVXiO9lolZOLadbXQdPWHPPridGQeld8oyCMEtpDZWlWflN/vF+JGGxG1iXelxWBd5wrjTsRoNTc9LV+OZ0HPfmCcdhKJRGXJwONh5PVPi9moexF6q3bDE13G1fkKgtL60fj2llrYtKC1upuT53ZugZjyaUNLf7BO9RXoJl+FrnVSppgYqD+nrquul7YSOr2Xd7DONQ8Ze+VAt5WM2m02eEWSfyHeijkQCGZrs8uxJFWrZRQehaNLGmlbUg2dUNCrWfD6fZKQsSPyQ2RRiCiKFywG64VbGfYyD0nrvmxyl1+SA5UByqiG9XcYoWTazZ1RWzp/RQFXw1fzkfyq/vSg9JHnpWNplsq5cLF0RFS09U2Ys2Ud/Z7o/46+Ksi3pQfdBStPBKBoFsccAzqHlYNqj5TyYr8sA20LL5IrPebColEw1U7i4RMv/M5YweZBt9QmFKrjb40PCWcadPJ8CR+ibT4rT2ttbmG/0Qs4eJoSv4rfkgRWRHoc8cHuNTHwPx5jy4eVyfoSpyqJSDq6uribem141s7C7oGF6ZbazRwenaP4t1a69Su1X8FKawhKWy3szg9mDY1RytscCQGjUYzgXGBMquT35PydYySu3IRWZvPSaT95HY0OBSSX3NUQZs9lmro4LBrJNOZY2gumt6OkYT/m3DYfbk/w4Ojqa8D49MYmykv1l/Tye5RjOVvEnvys6CEXrwaoMbvkoC1eEMEWfDLAFY+wwm80mE9hsg+ej/E2IRGFiTOL2+X4PfA8mVr9drsvKuKxnMWlIKkGjkvp8xkLZJ/MthZJe00RFpNdJxUu4xnKprAmX09i21ibbSZjnw7BJimWyhcrrh3KPj491cnIyQQeOVylLJHrmbFcF20kHoWjSNCuVnoqBLwUwH7mooAOhlVQLFq83xCTDK29JyERlIMNT2SqDsgvjM8aohLcqY5dVvbm52ZqeyD4R1qWHl6Yxnf8njEzYSkRgSj5VcKx3LPdWcVx4cXExuZ5xMo2Y50iJLGy4yecqy1kZ29vQQSoaB86Whk9Ac9AquEYm+lGVDJpzEOkZfLxius/tWhFPqix6wq5csuXymNCpYAyzkpVnqKBlWvCsM+tJKMUkisu0IbShIl92KXNmhpNfOcY5VoRs9MKZtk8D4LovLi62MqKWM5Z5fHw8jlEPkexTuoNStMriU7EyTvP57ORyudkTMXe7qhhSDVqer+6R9j8QWglbZv54bfVJooX2ffm7glw9aE5rnx6sB+WquCSnP6o6kwj1uGNWZSx4XVJCRF9XxejMVtIomweWH9+TEDT5mvyu6CAUrcLw0sbS89EOZgnZaQuJP8fHx1txGQUrd/flYHJCm0pOr2shyGSA+8DrbSk5mLwnl/5USZ2eBc/yOPC5o5cTDDxW7fplPnBsUoEzMZHLvypFzN/mNT1QxcvsfypUog7LQLXsaz6fa7FYjGtgGZ7QS3vhwunpaZm8qvq0iw5C0aTtzJo0taDpzdK6cr4qlUXaXhia805ccpVpZ9IuSLkvvZz98r35KE7Cs2x3xaf8XcFp15Fwl8cyQcT2JKxnn5m27wlf5VkIZXvXpyepkI+PU2Eqb1N5vgoFZHxMQ8L2vKQUzXBBmlritOKmhBL0VpyU5nGXwb30sw2SJvf6OO9PaJTLnKqAmvFN5bkqo+F7SZlAoJesYsBKuZ1E4JpExmu+h8+8kffVPv/uW2b7su4KEfg82+pHm3IMaIAqT+gQgWVLmsToaWCz70yEMaFDQ54yR7716CAUTdKkI/vwLpUwA2MyqSqLj2DQsvu63gsW+JtKscuipaJQWCor2itrl7e3Z7QCsZ7Ku2WiicpfxYS5rwbHyN8V7CclZExldBkZ/2Xf87z/J3+shFTuVATH7/neAvaN/SJ/KQ/7FMx0EIqWLplW1t/54KaziTlwucRKWgnXycmJjo6OxrfKUPCGYbPRaQqNH5f3tT0IyMHMLKGtaQV7pf6i1sqj8JpKAc2v1trkzS1MJHDhtNvilLfr6j2Kku2xF+FGOTkevJ9KwnlKp9iXy6UWi0W5htGrVNxWjw2zjTa0bpO/2TfKkPlj8iS4r2OczzJyofM+CHkQitYjWl1pO+hPqGK3T0WSpkufMgtpIizxoFXCnPexDgpF1Y/0nj0PkFMJ/L3L29N4ZCaNQtZrD+Ffei7/ZrlW3DRc5Hnlpdgfwv+Mh1geeUxhT+/C+3dlmiueetxdrz9UpkQxGSL06CAULYUvMXsuGvWMvgc+1w4SOjimuHv3ro6Pj8e0P+MYxhAULtfHuNGWmzElrbevpzemoWA/fL3XZ3Kuht6AWVffyziOwuA2LZeb9wWYH76OGwmlYeg9w0VFolGzgDEZwuuur68nxi2NCDPFCWcT4fhee9s0govFYuLJvA7SE9nZJ2aoOX/GsmlEkhekCl2QDkLRTLexQIy/8lge50AyyVEFslUc0aOM2/htod53P8thPFnFMFkW73P/87r0Vu4nYVDP2/De9IpemGtjxXvyO71j7+mMXp/dx0QK6dn422PN8UhvUyl7ZVC48DrbyzpvQwejaLREjMWS6AlyPWLif1/D2KxSkMxg+f70rPamLlOaPoHsfqQQ56AzDrKH8XfWyQwpDUR6XfebbaV3df15nX/7nD13tVjY3+nVhmEY92thH+g97dns/ej9q4RCJidohE5OTiZoxO00bzmewzDo9PRUNzc3ury83MpGE5nQQPrVW1ZKI6OesajWRpIORtESNpCJZgzXH9Jy8ZNewYOaad2EhvviIiqzl+X0MntJ9D70KumJGS/kvbTuVczaI57rCQn7lY+iVH2isqfScuwyeZRGKMup+p7fbmfGhHkdeZoxe3VtejWWz88uB/C8KFpr7VWSvkfSU5IGSc8Mw/D21tqnSfo+Sa+W9EuS3jAMw8d2lbVcbt4NnfGN4ywmMpx9Mg6n4mXH7cmYGaQyStMgOD1RegnX5/VvLjMfykw4x2Osx78TRmYfEhbe3Kxe88tyEx6dnJyMyQryuoJ8acxS+BMGsjzDyFxbKGmS0aOhIL/pGbMfpFyh4Uy09w6pPPxsNtNisdDl5eXkVVDJN48pX0RpqOxyrq6utFgsJrJoet4UTdK1pD82DMNPt9aekPTe1tpfk/RmST82DMPbWmtvlfRWSd+0r7BkfhU/0CtZ6Cuv4POJ+3sZQ1+fWD+FKuM8t5VtzqCY9SV0yywqlY1973miqs+sqxeg92JB30evREVjW5Kv9NgJN9NIVJ/eBHnyh+fNq9wjMseYcXqv/5Qh94ce2p4+vXTV3oo+aUUbhuFDkj60/v2PWmvvk/QKSa+X9Jr1Ze+U9B7dQtHM7B4Es2JJm337OI/Sg4bMYFEA0mNxkFNp6Gk4d+dB9iBQSPPJ7RRGfqcQZz+qp8Yz8ZO8tIU2uT2E3LmChMqZz3axbVVM5fPp0alsjO+yvcwo8lpJY/9zrBz/me9cu+jr/N/y4jlZn3ffGEtybJjBNB+tcGwv+1rRcxKjtdZeLel3SPoJSU+tlVCSPqwVtKzueVrS05L0xBNPlIO3i2iBUujomSqX3vMCPNeLlaqMJy0dvdVtoQU9U0LM7B89aLWW01QtI6OCJnRjW3yc11PRrGxpKHpUjVEavWq+ap9MuFwmTtj2rM8KySwv68u1pZQBGs/MYj6vHg2V3Jf0P0r694Zh+Ich8ENrrVTzYRiekfSMJH3mZ37mwA7Y0lbkgXYmEeVtBdoU3IQbtOJSf0GwiUu3etdxMDKxUPUnny5IwXVbM0PHtX3uq++l8CS0pIK4juS1f1dbdrNOrvonLzLrOJvNxr09CPM5Jj0jwXjd5ONVvzxXR4/lPvHahKu+z+M2n8/Hl6LY0zkONUpYLBaT8d+nbI+kaK21Y62U7HuHYfjB9eFfa629fBiGD7XWXi7pI7ctryeQ6aGYeWQsUQXT6b3oBfO8/7MMCgwHxZRxVyV8KSyMvVJgErJm+63AGa8yrmJf2U4LC/lGHlftr+IdfveI0Nrf7BNjvWq8ki/VGPo+9ikNKcv0cSZlEkmwXnptG02+3y492y56lKxjk/Rdkt43DMN/jVM/JOlrJL1t/f3u25bJhaCmnodKi9hLoKC943cOWnVdCmyu+k+44vZLmqT/uU4ziTDM92Ubst22xBbWhEzZFwuL4xzzKlfG+H4mAKq40lS1NZMHzs5x3lHSOBdJMhTm2DLLyH5yzmoYhkm2mueZXSU8XSwW45hkmRcXFxNPyE2FlsvN83yey6MX30WP4tG+VNKbJP2d1trPro/9Ca0U7Ptba2+R9MuS3nDbAiuBcQfTqkvbS5NMlcDxXMYlvKey2PSCKWCEIukpWT8Fm3VU3jUNRRqQnHivJtez7bw34yLykImaXhxSCZXHiAbRSQbCRh5nefl4UdX2jMkJy8mjnOyWpo/9VEYykRIRA5XYiuepAk817fPwj5J1/HFJPWD62ocpy1bBVpTr7XwsLZy0vSoDbdvyjL6XTxCTkRwoC0IOuj0b6/bAZnra7aRQOoNVKZPbIW2/VSbnvXJQM3mSZfeUhB4ooTeNGONCxpEU8t6L6emlzFfGnYazvScxSL4nPTm3naOh4N4sGadlUsex2cnJyZh9tLd0WYwDZ7PVvJrnODPZk3QwK0MqYcggmIPGQaZAmDLrlJ6vBy8tDCnsVEz/531sF69Jb1zFI5nuz+U8CRkrA+LfFWVZpGGYLjrOOilcVbnVuKWyUNHyfzWe6dnTk6enS+/l63Ke0v0geiFM9jGPPxWMfXTCxYbb97wkFK3nXfjbqzzMMFpipl4Z7PuefBAwB8fHF4vFWAfPJ6TMhEjCQNefMIaf7DNjDAb8XHlfxW30oJxcJVX/U2HJU2fXnMHjvBHbmkbEgperdbiqhzCNySS/YjgVyuVXS+4qmZE2KCCzqt4rJBXP3/P5fHwKoDJAHk8jo/Pz8/Ha6v12poNRtFScylKmyzeDDMl6sRmFmkpWCSpT0W5XejOWVwm9B6xqk8s0GTq5zy47lbbKcKWnqoSwR71rUpn5SEpOIdD78H4qCZWmihdTOHlvjlXeX/WJS7nM/+SLl1qRGD8T5hqW0jvyu4eokg5G0fgEchIVjXDD1sl7r1MYOSDOutHCmiwI3u3o9PS0zEQSZiQMpWVmmyu4Skhj4ooGnsv9KCtomB6Zx3oGi54920hPaoNR9St3C06lqI7nNZ4LpeLRA6XBybYk5PZ1hnE+zr1VuEaRXtnGmtllP7/Ix2Uq6M14sEcHoWjEyRSGFAIKYiolLSiTGWYYoQyZZQW0gnG5k8uVtueqUjhZbm+Oitfn/fTkuVEOYWEOdkIotjl57O+0yhbKSlESknEc0gtQKdi2bGNeJ20vP6sMVHo0Llh2QsbxE1GIlYWKVXlGo6M0FEdHR6MiJg/42UUHoWjS9uJcqS+wmSwhPLFi2XJ5zoZxDwfu5ORk3IedHs8CweeVqOgpCLS2tG4cTGZQ2U+m5wkhq3nFFJD0TCncFXztKVtPMaR6LShj0Jz2qMqsYil7TSqrr8uV//xk+wjXM9adzVavWDbyqeApFYdPA9hop3xaDhxTZvIt6WAULa1IDooZ72PVI/d09/ZsVDBfTwh6eno62egnBab6TohXeZCK6W4HPRb7SQPS85xVPfSk2dZdg19RhSIqj8f5OApsr309yOVPJj5s5CpYm+iBnlfaeDBONnNZF9uW0DbblYammlLaBRlNB6FoZERmeHxe0iTpQVzO++2hMq5E9zsAACAASURBVKVsotcjZMwNQHtPULuNabmlPnRLi15BDnoZwmMe78GqXZQ8rdrE/+kBfU1CQitaZmMrSq/mvhmquY3VkjRpgxA8ph4rKwbjRbaHx6loKTvuD8eEssYxr+LEfbBROhBFS0rvkZ/0JswQMTXvMmgFHYMRTvKeHtShkKfXvS2zCYm4nVoG8yyXwpyWkwreO5e/yVcqeUI6KvsuRe/102Wx7rzPZef8YHpH8zqnUZg8IXR2PX4sxtM+JycnI+8ThjIWc3usYBW6YJ/46dHBKFoVi/jbnWAwS0ZZ0ejJSFQsDxavJcMZo/UohYeKts9ISJq8gkqq99rPmC29T1VHkvnA8tOzVv2yZ6vqT2FmmaQqFstzFfx3WRX8tSejR+OKlWybIakVqwdFKS+Espn8SBn18ZecRyMkMZRgwM3rpOnELhlGr2MFrNbdcUlQPsCXXqrKOFVeiQJCZWIcxgWtGWNRwdKr0AgwOZF193hbKWXC07wmeZBtTgFMr1QZiFTYnPzmMieGBfmby74y1rMXTJhLhXMiwzGd++h+sgw+v1cZlt5yQNPBKFoGo7TGPWtNYctMlM9VsJLJkIzjKjhIJfG3lcxxQGWFr6+vtyZGpc2cIeEqFSw9TmXpzYP0Vmxnjyj4NGSVF2abzc9UNLYxP2xXtiHhayIRGz8mtyr0QejJ9pifTNxY0apsaQVj09BkG9mPXYbuYBRtPp+Xj6LTYuc5ZhYzLuN8Gj2XByu3ejNZgXISOQXQwXK10Y003T3JbWIdlRfIWCAhKhV618BmbESFZPmpUOxrzuW5XMYvpOwPvUH2JT2b6+kpR7Yxy8nlcq7f8bizj9yGwApLr+cEij2qeec6OEYsY994SAeiaNXASXWGj/fk5HQKFy1geq5MgkgbT5XpXR+np0vI6PulOj3PtlHoaSWzvErRquO7BnhXOaSeJ09vzfHoearqOpfB34TGjqXs2RKe9VCDVG8ga2gpafLtupjlpgf2fvx5LudTWc9tkkQHoWjSNDDNQUoLkzDQ1yV0TFiQA2MFIoRy/MTNXP0/FfG2sMuUx9hfnk+jke3O8lg3eZCwJ5e59WIxnqugoXmb7WRbfV22mXG3PUompKp2uI0ZVjBs8PlMwXuZl8f08vJyzEJmfY7pfS2nC3LusBqrHh2EormxTtemkPkcByXnx3pej/CAg5JKUSkUFYtQkRArA2cKcSp/KprvMfkaJhKyP/soPVwKaRV75nW99roNqXQV5XkrAA1LjklSevuEkunhs22+1oaa6IWxGmXOCImZx4SZt1Uu0kEoGnFyYu1hmO72lFCvN0hUkspL+hoPuq/NbyuYPV3lfYZhmCQ9EsNTmaWN9+bKBfKh8nwVJazOOIZlMfZMWOt7+D8hbH7yXA/6M0OY17vOzB4TqdC4uczkTYVUfM5ZRWn1gkO+cplleYH6fD6fbLzjR3doFNmfrK9HB6FoOVgVbJK2H76srjHR69Dz8HpCUipYxmK9mIwKUj0V7muyLb6usshsf9Wn21zD35VHyy0gDLuynCr+6yGHnH+8refztTmX5nrYXipnxZO8lzB3uVyOE9I5b0a5ImLiqhX2w4qXsnnwiiZNszoJcXqDQEo4YQh4eXk5CbqZZcx7+J2Qsid4lSegZ+IjFlJf8UiVZWZc1Au+Kyjo31yNQt5mPFN5U/aZW0FYQfntc2wjFcR957yUPUmuzjE5OXF5eTnOgTHRZX67TZkJdnme5vHzaEZLrTWdn5+PyMT32BO6fyzL/MunPXp0MIomTdepUbB7SpbQKTOA9Eb0OCYyLLE/76eikCpFyf+3VdL0PiyLXpKKUXmhqo2+Ng2YtFl9nm3uJSYyUyhtey8SPQKVjHy2l/D1Jnq1StlzoruXLPI1mYFmH7jviMsnxN1l5F8yimZrY+GuMG8FSaTtBaeMjwhpjLUdF/mxGJfrZItjmIuLi/E74Qktcyobz/MYs6qkVOjMqnGgfe1tBjxhNj0Q25bZQ/KOx/NBT5fp+xNe5ULuSnGzHzSIbBuJj6XYQ+X0SIYePu8NUe2pOJ9pj8onRHpJmxxD9r1HB6FoUj8uI/WgVmUxXY4HhlbUxxPOuQ4PeA48FdMCy/OM2bJvHKjK61WxkzS12qnwWUfGHql45FO2LcutYqUKYrveRAYsn54r0YopY8asx20wT6zc19fXkzfA9trADz3bPrTSSwrR+N2GDkbRpO25F66yTg9SQa5UElsqPjVrK+ljuUeIY5nLy8utvSKoCFQOQhEKeE6IM3PJQeRLzTmwzmy5jMy4+psxCHnJl8SbEkLmpqUpOPZMma1kXOW+SdP40t6DRjCzsGw/+0VZYPzub2cJuZyKi4YzDmRdhol5zvVyaVcavlTAfUmQcSz3XvECERnuwajmkypFY0Cewp4xiTT1DjmlwJguLS8HJS0hlU/SlneRtLW0i0JL2MwymOVimcmDak6O80ApDClcuzwlvfGuJWdZvg1Z8jF5yPZVPK28NY1vemp6nexTeurkZfatOld5wX2e7WAUTZqmlK04mdIdhlUm0eepFIaIVBLiecdh0mbDFpdv3O6XG6QyZBulaWzJewhLlsvVSgQ+GuP7M4uYwu/jXJ+ZgkLvYqGmN0+h4nxWTl1Q2ag4rttUJWGsgJnUcFneRsDX07OfnJyMG5fyeNVuriwxzx88eDA5799WQGYoGQ5YXtLLM6yoMrUcq3x5Zo8OTtGk3VkcwgcqQj7mkB4ql/6wnBS6ymr3lE3aDuLTuxnmZPazmouhgDGWyDgj72NZlcXOc/SAaTySqPRV0F95NsJFH0vh9Xm+m6yClEwSeZxYPpW88szp6XZlJ1OuKmPrdiT/dsntwSgavYJxOS19fvsRFWmz8j9XZxA+JMQ00z3ozi6mVeIKEWkqaMvlcpLNdBaMwkJM72NMLVPpHc/4ww2DaD3dp5xkrTxdldSwJ66yevSibpM9GseIkNttpaEyX3w+4SHXkkobY0T+e/Nbowzyg09kuMzz8/Nxzxj3wUY4V5dUUDXDjfSwLpOQfJcXIx2Mokn1Cu1d+NlkRvQyhCw7y+VA+1zGZBl7EX5yETLrYrBdxQNc8MyMID8UKgp5LglKnnBeKik9G3leKSzhLb1MFdexXho4JjR6ZdAw5RglNLPnIophKEGPWMlP8uy2ykLKjGWvDtNBKVp22JafQsxA2gNra+gsW8/SeNBbaxOYIm0UzevcXK9XDKRAGAractu7UegsSFYWwioKdqWMLqOaXOXLMiyE9FDM0uWclsnXX1xc6ObmZtxAlnXugqC5w7DjHZPb4e3+mBTJGJY8I6XXsVdK5JNtePDgwYQPRBgeVyKV3IjH40WDRlmhHNGzv2RitH1UeTIrGuOf9Eoc4MTdmenLOKIqMy0n76Mg8b6Mi3pewZQxTgVxGMP0PEwKL6Ghn71iZi/f9sL2chVJtecijYHrIMxzX/g/Y6B9noFjmrEaY7bbpN1z/DLhwTGi1892Mpbu0XPxat25pJ+S9MFhGF7XWvscSe+S9OmS3ivpTcMwXO4qwwLfC+ZNjC8kjZti+kUDy+VSp6enE2/hjN/9+/dHT8bkiO9dLBaazWajdXv22WdHL0VLbi9q70Xv6euOj491enpKHo3tyVXftI7MnkqbzGgaAT4dLml8lRS9EB9w9TkaGr78w+fn8/m4zyVjWLeRW/BdXl5u8YWr8N1fr5bnixmtaO7P1dXVuJ7R40wFdFu4nTeRjj0cH860AabxoMfl/Y7xc+kVnz/jluGSdHZ2NhoNZ3yfV0WT9A2S3ifpyfX/Py3p24dheFdr7TslvUXSd9ymoMqqp2fiNYSNtHL8XWWYGENlbMAsFq15tosClURBSmGkl6Bg+jwVL/nCuip4V1ldttMQ1NfR2xA29gxdtpFKUGVHqXzpCar4MuMztrXKqlZlVh6R3s/93hVikHpjzDaw/z161HdYv1LSH5D0pyT9B23Fid8j6avXl7xT0rdqj6LRAkvTgFnSFryjV7FX47VModuiutzMJHFgEqbNZqvXOA3DML5y1WXlym7GZ4vFQqenp2N5br+9iCn3K2H/yAeurqBHlzZKfXNzo/Pz84kC8nzGRVau09PTsS+EQIRiySeOF7cJ6EGrFEobQAq+d6LifUzls5zq4zoTmrsc8uv09FQ3NzdjppSGh0Tvaw/o/tmQ0qA8n69t+rOSvlHSE+v/ny7p48MwGMB/QNIrqhtba09LelqSnnzyyS2Bt9WkxalwN2EVr6U36aVzpe13MVNA/V0NBoXFcM/3OgHgNnmgcjCoaBRuLgGyotGD0HAwIXB6ejoxEm5/Jknc/symui/06BlDJT+TqpiTxyqPk0Y2IWOeSwVirJbey/exLVSMRBW8jmOa5zke9Nw9epSXxb9O0keGYXhva+01D3v/MAzPSHpGkl7+8pcPVJhcN+ffDKgpUKlstNzSZiATelKI0xJ7oapxOrORbBOhQ8ZsjA0y3W5v6wF3HDAMw2R1eWttjB/pBTKIt7e8urrS2dnZ2D+W749jESIBG4Kc5nBf2KcYx7FMCm0P3rFseyx6NGYFyU8bABsut42ZQcZUHDuunHH7uGuxM8ecQkio7fHif44x9wWt6FFfFv+vtNa+XNJCqxjt7ZJe1lo7Wnu1V0r64MMUmp2QNrGMv7lI2KltD0TPqtAqM/tHi0+iR+MgpqLlMioKmdubEMiDnYPE4Lz6n3Wkx0lv5t95n9tkXqdy7PMG9LrkXcUP30eiN/D45dIw9pHtqbwiE2lUvvSUCVndzio2ZUIqxzzjbt9bTaOYHuVl8d8s6ZvXnX+NpP9wGIY/2Fr7AUlfoVXm8WskvXtfWe6wM3xuvDNgGcekENDSVQEuYzNmtqQpzJM2SsBVGi4jkyj0FrZ+bgc9ZcYNuWI+FcttdGavSiCQGE9Jm/hR6idmXB774OvdZiY9TG5bxZ9MfpDnqXitNV1cXOjq6kqLxULHx8fjf8bkqWQcO7eNr1mSNO7NaOV13VwDy75ziwMbvvRobo/HNefynk+P1qNvkvSu1tq3SfoZSd912xtpee3q2VnO90jbK/4JMSrcTRxthUlr6rIyuJe2n+Am9LTHG4ZhUmbPW6RVtQKyfGZA3X6edz9SEGn1Exa7D+YxBTLjEveZyl55f8aZGT96zJghTUNJYbehIo+zHnpjt9u8skdk+dnePE6vxpjd/wlj+emVV9FzomjDMLxH0nvWv39B0hc9bBmEWs4ULhaLsZPX19c6OzsbBdJCQ+Wxpbm+vh694bpNk70gpY0A8X1qmQmjZzNVsCyFNZ8U4PyPNH2yl2Un/CHUcbaMbXdZnNNibEJPxOuljdJ65bwp0/G5e3T1kCWF0HEM1zJSOHOFCA2qx5rJJU6Mm8dEPuybnxBw+fnMHHmRyR23I8fk4uJi5AvRiNvJPWleaI/2SREHy4PpAcuHMKWpsBG2+RyDVjObLp6Tw8lkC4ThK70OrzFloO3BoDFIRdtFnrz11IIV9c6dO+P99tw3NzflM1+um16McMltcnrfvOQ+9xYmetZq01EaSRpBKlpC8PSS+ZAoDQI9mOWCsuCyCevNx/R8GcumsXTd7EMVp9pbG7bum487GEVjEM25q8vLSz377LNb7pnM9lIiHqeQ22pT0Sw89mheGS6tBuDu3bujV7XiJcxzGUdHR5PyLaieUE/FNNlbMPBfLpc6Ozsb53laW2Udj46OdO/evfE+e7J88oDe0L/5VIPb6riIUweSRiTAjKi0WgkxDMNoeNKjUdF4ntb+8vJy0lZ6E/PV8ZXnsDw/aD6TTxnT5sIFKw6zrqyb3pt8MG/N59z5y+Nrj8ZVKD06CEWr4pTlcrUxzvn5uc7PzyVNH+nnfUxLu7OZTdzllViOtBFGzrMkWQh9X/UIRz6ewf5KGj2J22kF8X308PaaJvfFcMvW1QpGYbfAOpifz1ebhLqP7J89nK/j8i4KbQ86Mu6pFIoGiLGtyzI68TgYvnOKhmO2y5OYhwwxKjSS5dCrcvyITmiUEzlUdBCKJmnSAXfy7OxMZ2dnevDgwWh1MhinYnEuxwE2GVIpHmEl44U7d+5MhIeZP2arFovFBHpKGmNMehUmLTIDx3iE8zpuA7OUbsMwDOMbLekBrq6utp71ojC4bXfu3Jms2Hdb7ty5M/HQ9mBeReHxqTKpjovcVsZiTnZ4XSM9hp83Y3yZCY/lcrm1vpJKU8VJ3AA1ExgcSxoi98fj4LGgQaFHo2PYRQejaNJ2hoyZwbSaifOl6bIbeihpOr8ibe9MTJye6Xd+rFSGm/kObHpOKnBm76TtxAOTJy6TSmyrSWOU6WfGF4wFKUhcHJxJoPT8VMIKHfBaKzI9G4nXu7+9qZiMpfjt8yyH31VZrN8GiRCSMkfjaOPh+n2cMjKbzbbm25IOStFoXckkzlX1cHAKRpbFyV9JE0iQipaek2X7vGMcx3AUogy2mfFjDElI5HZIGjN3HkzDNydJmCBgHwhhqHQ85j64Pe4fYfkuRTNPquRHluP77B0qRaugtc/RIybkY1toUKyA5IdjcY4fve/x8fEYB3KFCBVP2t6enFD3JePRiKPNLKbYpW1YkEtnGFgzuUKvwQycvznQDKwruEGImwNf9SkVgHUxze+Bp5cx0SJTAAmXWD8Vi/1KQSOlB05IacW5uLiYKB3rslKZf9keK5wXgtsL5NKr3NouvVIqkutw3ZViZgaR5VCG3D7zzogiN2xKr+5QoUcHoWgM2u2eM7Hg6zhoHhRben8y8KV36ilaDgCTBzxOBU5Y6fJYF72YiZbYAur/uYyM3qJSKMcZ7Bf5lMkKe1Gel7Yzar3khjOYzN66rxljsT3Sxjha0cgfj2WuOaxgsCnrYH/SGKSSpKJRpgwrLZOuKyFqZch7dBCKZsqlL8wCmhwUWwEpwBSSKtlBprvsjJGorI5nGC+5fAfvhF/0Ejn4hJDpRU3VvA+/fW+lwPQA6WXYz4w/XFc+uMh62H7Gm65juVyOmWHXYY/G8fG1VqiEvexXGkAb4Dye17JMQmQmpPifSua2UdE4me8+MdSoYHZFB6VozOYwfmEwzLQ3La7vleqkCAUt66QgEwrQwjN939pmF2ALCX+b/J91WBhojWlZif/ZdypyBUVTyVLwXBYhqhUnjQQpvSmvp9IyI2iBZT/dB2m6UDehNflSJT16nrtSNt5D6EgFy4/P+V5nX90fjlmFaHp0EIrGINxC5uDZg0ZhJDlZ4NiDWSGWmXEVs4Quh1lHtyknbq04TpPzHrePSRErofvC7KeFhjGJpC0v7DZnAsRJEab0KZjmLQ0TBY3t5cQ6lYuPC5nXy+VyfBSHD09aiWk0KkU10WO6P+4nvQz7b3lIL0ThlzYJsAw7qHjptTMuba3p9PR07CNRjcsyXwl3KzoIRZOmAWxmpwiBEid7cHIBMsuksPFceg4ey5gl4xrC3ISxmVlLa8dYIfvDtuS6uizLipYTq7wmIQ7rT0vOGMvlJFLg+50tzISvaflzjKloTma57DRQVljKQfXJjHJeX3m4/Pb9KRPe/4U7LefYEpL36KAUjXMTmZ7ndYZuxuGeVDX+pmWrBsJlVnDC8R+ViNbL3suQgu3N1feEiRZKbnXGdZd87IKGwX1ZLpeT7cqtBJlM4R4qeb8tPPlKQbm+vh5jNXsSTti6jkyBWyBp2Z09rR6sddvp/bP9HBsiGvMhM4XsCxeJu0wqIXMACUvpdemFnRSjIaGM7aODUTQmLwiXGIhnFs3nq0W1PpdwLq0RIR0tspnNmCC9WOUxLaT0GhQ+CwWTPUxqVF7JxNgq+UDDkdeYqpiHBirbYn5QoTO+Ma8Mr1gnPT8fg+nFM8kr8pG8yWfWaHwoQ8n/5G0mL4h2TJwXpNFOhLWPDkLRPCB8nOT4+Fj379+feBx20nEYIWMOIoXPcQwtqJWMVvPs7GwUHCZjGK9J06e+vZSJlpDewIujz87OxqmI1tqYQHCq2+X5P5Xi+vp6tORWBHtgl39+fq6rqyudn59vwe8UTJdhL2kjUT32bz75es51+foUXnphe3p7K7fZSuA5NZbJeDTjKbfZY0wvY6Ps1TvL5eYFG0xqEOplQszlZGy5XC7HMvP6nvEwHYyi0SNIGyhJT8ZUMy0XFScVjfBNmu59yPvs9awcnJtyW6TN3E1CLKeBM9awUHru6OrqarTy3E7cwiFN3xNN/J9rGDn3ZEF1etpGq4pXKCguk16AVjxjYe+DmUp7eXk5icEyA0gYx1X8FaRmzFnFkkYG5E3GvBn/+h4ioCqmpkySJ4S7pAxrenQQiiZt5l9oQe7duzcyyBvJmCHEzXwMxOc8gLaWCfNoZc18xhO08vZaHiA/luO2nJ6ejpab8QE9ja2wPZPbTTjpBb1WdGf8LIC2zPYW5suzzz6rq6ur0dtIU0H39fRqGfT7WmcTJY0JHh8fhmFri3TXd3Z2puPjY929e3cLIrvNbtf5+fn4KBA9k8eKzx9SkNPQWOnpsWz0bMgcs/E69rdS4IuLi3FBN89ViRsbtn10EIrGOIxxA5MFtBYetMT99FAuh5aRgkX4NpvNJvNATHLQc9ry27NaCFy/pxdchhXNnoxLxqRtRXPZTjC4XMIdt98QyuXSK1CI3E4KlXnN2Nfkuqgo9giGgr5XmsZNTqbYyDE+Il1cXEwgqMeOfOK99pI+7jqpHB4HoiC3x5QZWsaA7GPGhxkr0mgw2bUrKXIQimbKjiU09OoDaTPXZAGTNgrkrcRSCdO123MNw6CPf/zjYwbTcRKhlOfq7HW8/Zw9nB+XyXkiDpy9mgfbC1nd7ouLi8lmpnfu3BkVTdIE8lxdXenBgwejh3Q9jCeYkib8oqJcXl5u9dvt43SI+2pFyySL4apfMJHnLfhcA2lD4XF/8OBBmUbnNcvlcuSb++17rGT5UkPCeBu56+vryYazTEbZ69p4sDwaBZfjtuxKjByUoknTeTJ6uky15z30OGYGrbo9BOM9DgYhJuek6BmtRJwzsxXlzkuENzQc3OXp5mb11hPf7/5xT0t7HyuQy3Rb+X4At6WKN3yOikaIyb4xq0jiFEBCOsM+exzGapzrM9Q1YuACXvPHO0LTMDImZBszqcFxdr9oXDOxkrCWvPI3F0GYD5TTlKMeHYSiZdzAhavSJoV/9+7d0RJJm0was47MNiWM8j0mWjKvSieul6Zbm83n8/GxGFtPewdOXFNQrSBWCD51YKF1TPGxj31skvGr9i2xRXcs4fopmISLhNPsh70LvQY3MWUmlPebp3ylbBLbbh5XsbafnqeXphKZLwnx/J+vzPJYEXq6fbn1HyfKLX8e22effVaSxv7nQggadZefsWNFB6FoPbLVMIPsLShIFVUpfv5PAUlF9ODyHDOAzMjRY1pJLCxpYVPR0vIytW6l9SBb4Ak5ncbn/B49MaFOlQRiWpwCT2HMDC2Nhj2cx8jnmUyiEbQSeIxS0ZhBJd8ZC3PMUsCJVtxHxr00eqm4mWXkdT3ZzOteMtDRlplZQwsShd1EiOf7fdzM9+C5bA5CDwqZqJCZtk8PSWWjcFLIDfkYVM9ms1FhCJcdD87n8zFW86D6lUGeS/R5CjUHfhiGSVbVHo3TA5eXl5MV/Ey3M6ZLRWPGz213zMLMsMt0tpbJjwpaExHkPiU5RswcW7G8eocejatRzD8iqd5SNfef5xhyVFvYJx2UoknbD/ZV2UZpat2SMb3j/E9FqbweA/ism9fQM1LRcsmPBYtZtlRKt53LzwxRqWj2Am4DhTwhTAonoRwNDecP7ZEIv8l3eh8Kmftkb+s4zP2r4CoTJHzKmX2wx+kRk0AcK8bL9Ir8VJnoarwzMZfx3q72SQeiaMvlcswguTMefMYs7iy9EK224wbOgRlr5+QtU7m2piQLnre64wBQyQgRpe3FyVQgpqvttZhVNDk2sbBWAb3bcnR0NHoVKz29P6/h0jGT++95MsNQCqiVOyEsFXW5XI7ZS3tIz4ll3MwPlTzbZJ57Ciazx76HK3jYN9fn+92/jNsNMS0jJycnE0/WWhuzsuy3782kS0UHoWjS9tbTPtaDDJlCpsLlNZwvotD7+rRMVlYLSqVohpU0DtK2ZWT7KJA2JvZ0rIMCnYqR/eVCZvbJ7eBjIq6fQutjhImG2OQNH+93G5m48IJlJgicuDJkJN8MoV02jQ2FPPtToRpC+ipW4n9eQ5lhXxPy04imh8/ye3QQiuaB4tyNB4DZPzPB1ocwiFieZEYxwK6gkD1qJi6cgjdV6+JycC3gOW+UbbIX9XwYrSeVpNqynPzhDsap8N6pK+9nAoUezB7KCkLvYUiYiQDHKq7PZEVLiGuemRybSVPIRhjOb+6K5rJ4X6IL9jkTIikHzFS7DCIBJnSyjF3w8SAUTZrOR6SnYsJBqp8z832V1UvBIPm/z1sxCG0Y4yVcyeSIGc+1h0wkMOHBxEMuE2Ns5nszRshHWFLZOe9oCE4Pb75xmoNzXiw70/7JU89/EdZWima+cRxs1DjG7k9lOBmz0jBn/3lvohuOaaUglKVMgrntmSc4eEXzQHmOxSsgLNRMM1tAnf5mEkCa7uBLWJMWi0pLJcm4IWGF7/W3A257TMK3ZDwFSqoftSB0tdex96LBMc/m8/mYtUyrTo/lnYn9ZLjL4ZZ29rJWkJzUdsxq6Ef+8eWHrtsvRTTvOGbse46J+Zxtk7SFWmiYnWhJT+Z2Mn1vY5KLr12/6/P+nZZDzwW67mqcKzoIRZOm69A4HyRtY2Azk/EHlz6ll9nFEFosDkKF9RmnZduq2COF34rme7I9vp4exu2XNqv6HZTbGFSC5esc6NOIMPFgIXa99MS8jtDSMZfjTRoaJmI4V0eDlRAyM7ccN3omC38a12qseDyRULaHCRKOA1EH4SY9WyULFT3qy+JfJukvSPrtkgZJf0jSz0n6PkmvlvRLHSHF1wAAIABJREFUkt4wDMPHdpXjhnN1OmELNw51Z22JvEKCqzIYyNs70RKmckmbFf/E3ekhLIw+R+VyjJeQkan3s7OzrVcLgZeT5/GcdUyix7YgElZSOAhTff7+/fu6e/fu2E8/d+espD2nPZrhpvnqeOoTn/iEJE2Mnc9XfMo4t0q99wxGFVNmdtEKTEVw1tpl+LfPMyeQ83eZzs9QwskdtztDkqRH9Whvl/Q/D8PwFa21E0l3Jf0JST82DMPbWmtvlfRWrV5OuJOM6QnHaPVo5agwFLD87WuIy1keBZLfrofZyMz8VXHZrhiQsDWhUlpwf1IRDRktvFlHrsFMMsykZ/Bxf2fqnfCd8Nj93xUPW7jz2kw6JCpIz0Oe5xwb+1Z5dPKP5fA3x5nKw/sYeuzicY8e5WXxnyLpX5D05nWDLyVdttZeL+k168veqdULCncqmhl0dnY2wf5mnhlAiJHWO5WMAsvHacworjbhwJt4vVS/RMGCwHsZS/h+KhjjP3tZPn/l/tID+zizZrPZbPJiQhoNvpKXcNwe//LycvRk5rEVkI8mMRbj+sxMgtCYOQXu5AinHzweLic9ExMiLJOrSyRNYnnXwW+X4af2aXipvB57vnCDMsZ7DdWJWsyD2yjco3i0z5H0UUn/bWvtn5b0XknfIOmpYRg+tL7mw5Keqm5urT0t6WlJevLJJ0ehdKcIe8xwepn0MKZM7fJjeJEej0uF8j1Z0m7LVXkwWvW0/sy8VV5X2jwTRtjpb2nzBlEG97dpGz0vDYm9DoU0vVVCqCw3P2kkaAjIH5afsRTvM1XjzrR/5dl6MRy9Jj0VyyKvMuPYCzMqehRFO5L0OyX9kWEYfqK19natYCI7OLTWSikYhuEZSc9I0lNPPTVwcphbfHOhLlPLzMityxuPcw6Ley5K2+9B5sAw9exnkCiQfHKAdTJWs1UehmHy3+WzfvaFZdkb8JVQVDYuOqZ3cD35QGyuimEMaU9QCSs9jmF9WnDGqi7fx91PztURMvoY418iGe4jQ4NJ4nV+siKTJFQIH7csECZzOwbzlwsXmCTydyZQevQoivYBSR8YhuEn1v//slaK9muttZcPw/Ch1trLJX3kNoUxOE1YkfEIH6NJKFB5gbSQGbP5Xg8Y4yAPHLfrZpYtLXzGHfSeuYaRc4f2Aq7D0IjzX4RIaRxcl7QRfsM2ZvoqT+97SBR6t1fS6Pk5z0f4TI9mgWT/9ll+85BJFCOdKlbuxeRZj9tIL+nyzHPyUpoawwq5WF5dfg9ZSI+gaMMwfLi19v7W2m8bhuHnJL1W0t9ff75G0tvW3+++RVljZlCq3xvmjl5fX092yXWq2fNDxOpplaXpRqu0fLTuJCvSgwcPJG0eJ6GiES5SOOx9pGnmzM+X9fbG4PVevU94S0EhTPM5Jol8HY2QtHmFbqbWyTfGOOa9x4nZOceF6cHtnV2eV6lUkLRKUORqIRrW9IC58oVjbiUlwkme0eBRaXLPGVNOf+yjR806/hFJ39tWGcdfkPS1kmaSvr+19hZJvyzpDfsKseBy7wwzcDbb7BbF6wlD0nqll7DAcjC5Sj09G5MkHmTfz3R3D/fbcjKOssBSmC3oCXHcH7fbc100AowZKHhuQxLrtNLy8RPWSXiasSsX15qP5guXJtmLerxYdqKL9PipBBnTVdlEerJ9npPXMKbnPVUmMomx9z56JEUbhuFnJf0zxanXPmQ5o+Wje/cgc37N13PC1sfIGHsixiAum9YxFS0FgBk7Sbp79+7k6WIPmJXSyuN7KNSZqMnECZMgvk7S5AlraZMssfdwljInutknKxnfUZ0QStJEwTwGVmJ7X8aELMNxHPvjZ8I4F5oftpECT2OWGWAqVY6b25UKVSUu6MF5nE97E3pTZqvpgB4dzMqQ5XK1kJWw0e7Z266ZWR5EbgXtMshY7+UhaSI0Pr9cbvaEMKU1tIBZIHztnTt3Jul7ehfHJh4cb+xD71PBHO8MxWxiwizOb1mpMs6iArNPFnQuUmb/6YXz5R70SjYsrLO1Ni64NQ/4yA3nxzy+VDSWxf+ZsCK/6Al7bcp4lPE2eU05pLdmOzzGHPNdD6WSDkLRCB2Jtx27ec6HuxE5C8nkBi0zkwbS9HESn68manOClfd7MLmCQ9KWknGwpM3L470EK+GkoeGDBw8mAbYtevUEgOt1X2iRKQzsI+MuKrMF0Nfx3dwJ//g+bWkKw8xHGpuK79UYsI5UGF5Pg8G4s7U2ea7MY0ZE4/K4b0kmMZjFZbaa4Qrn0dymREZJB6Fo0tQKc9HmcrnUgwcPRsgjTS23NH3WipjZ3xyYdPUpSLTuvo4CmXUn/KvmWuihK4hBxWZ97Ac9oeus4gvCTgvY0dHR5OX2Fn7yxWQ+U0hNhFEJbxnXUij5hHVFjJ19TT5M6eOEte6Tr0nPx+RWwkKXySRIQm7yxMbOUwBESTT0LwlFM9G1u3NePX337l1JU3hnBhG+VQGyrVMytJqPo2dkfMOUua9ljJj157waLWTCFVO2vbLu9D4ZX7itJgumFS13dUqPY0VkUoRK7H4yA2rkkd6JipYwLL2Xy2qtjU8jkNwWIgCOnQ1RQkx6vaRUtGpsGKoYdXH1EuHxLjooRWMKnwLkiWxpuh6O1jAhpKETB5l1WJEMP60EfuQ+mU6FYlImvRlXgrCNPlfFD1kevQQznh5Qf3PjUFt438cYaDabjS/UsxAy2yltoKU3iE2PlvfYoJBvjsto/PhOgvyu4Jv7W61AcVLI3+wPQ4X00pU3S7mjvDhEoIJ5MTX7nZ7zJePRqGiOFaxoDrSZzeM96cIJBzIuYGbPDKZA0fNReUlUjipI5ofHOM9EmEiLbAvMx2L8bS9kY2TBc0bRSCBXVRAyZvskjQkb7richoJttVB6vSU39yGcTsNTQTtmTw1Nuc7SZE9mRcskSc6l9ShRAJXcfM4VIJZB31ctAHjJKJqJaXlpY+mdlTw9PZ0EvunJUvgZJzEWkrRl+RKSpqIRVvqeTIL0FM5Cm16Y/a5gFeMzK9IwDLp379448CcnJ1osFltCZ+IGOS6D6XMrpifHK0G0oaDB8NboTlRx4W16fHpwwi7233CTZZjP9CL5n2PpsnNahZCbcsXkDSG7l17xEZqc472NYksHpmiJdckgrkpIC5JeKAPyTGT4nmqQ0lOa0uqxDHtIKhpfEpHxkAeXS6mkzfwYPUIKKcuhFz4+PtZisRgFjAbDMRUFLB9Cdfxjj8b7qWiGhs7cGRq6nZ5H5PNaCaWpKOQBX/pBpfb4pIFjdjHlyN6c2VWPL5EPecwEDA1Sbh5Uec99ynZwiiZtsk45GW3L462wl8ulTk9PR8hkbC1tZwNzZQgZbwZVjEsvlFQFzrksi8pGRaJ1Zz+9eNr9TyNQTSYzG8e4iGl+xqpe/mVhdllcmEtPbQXLHYyZ7vdxK1DyhXylweScHvmXKXQqTQXnyaf5fK67d+9uwVV/e+sMemgqE5MgfC0TE0PmCeW0RwejaAlVGD/4GDE/MbyZl6/o8X38ruqld8xsYxULkgjrUsmzL5nhyjpYnoVa0gQizeebtY9cecKYh0mCXKlvHnN7cisSM3sU8owzE76x3YSiHDfyP7OBrttGjfOH5JOV2vwjamC5vraa8/O3DRrlKpMvNJwJxc37ffNn4/V7r3gBKDM9ZgiX3FARCLX8ulp7QVszzu5bcHx/ZeU8WAkpqbw8TqOQsCEFi4mQXFYkaQKfhmHz2iH3gdm0o6Mj3bt3b/xNj0DPQJ4aEs1mm8dCLET2UF4UQN4y5qpe62v+sp/mB3mZfKF35X8aJ3p+Ig7yk56SY0vvnu2iUvHJgouLi8nKJN9HuaIxS5iY3jXpIBTNlJaHHoJkS0IcTavHVd4mChwFoRe79eaomOlie5PxPGcBpaISSuakKtdhSpp4rOPj41HRUsF8jG20UPp+ezi3j4pGvvEVTLT2hnemNDycL2N/yRe30TzYlXypKBWPbWH8lBlTtiERhmPDJCIrlp192ufVDkbRbClsRQjFEn44FvCKcT4wytUQhFyV4nGQTbTqlaLRqtk6sg8ZsLuum5ubSdaPECmzaYRM0hQ6Hh0d6e7duxPoyE1LOS1iHlLJma5eLpfj5qsZ/3g5mOuXNvOb9Ir06FQUx6BEBEyKmF+MVdOA0WB43H09IX01Bi6T4+62c9LZ/21Y3L6Mr6tyqYD76GAUTZqmZ3PQKNRpRfn0r72W53dyApqUxypF4UDTStsikyrF5H00FBYYx0f0llkeBY7zY1wpIW2ygvSAtMiEj+ZbptgJ72wEyPuMJyvIXWUKK+jP/8lr11UpMNuY40hj2IOuVEwmfLL8lJuqjTz3kkiGWHArj2BmOKXMwSK8bK1NXlLolLa9H8slZq8URtKWkFPwaVEJ3ypFy4GrFM6K5usljZ7JRDhEwaWBSkUgMbYhH+g9uXFsGojkESFels3jKZjsa/bB/znO5h2hLb0miZC611bLkz2ZISO9ei61ynrY1iqrnXQQikbBJvOq4FjaTGi7k+nmmUVjAP+wbcoP4YPb6msTWlRWr2oLFa2CVO4jz1dWN+us6iGPyFsqg6FlWvgej9JLpAfoKSn5V/EzkxJOcKVxIF9ynJKyz8ykuh0+72RJKnMa0exXjw5C0aRNutRKRKuf8xuc2DXD0tvYKvlFEt4S2/ebqCAu38epZNW+Hb6OcVImSxLyEs6lAaGgMRaiILhc88iJIUNJ15fC10tDp/LzZYmMI518SiX1/TnXRMXlJDHHMZMXjJvp0TLWkqb7fbDeRBeO+V3n1dXV+KZRv4qKZbA/nBfk+GSmlWPTo4NRNAo1hcLW1kxkIE4G0srRElJYeQ2/UwDYHrYvPRo90a5Yg16pVx/7auL0hq81Dyj8Tj/72oybqLTZxtz7gkkBKhqnBNKj8uP+OhRw3VWc5TamHGTbeYxj3EMOKfQ0ZikTFdylvOxTIJffa4vpYBQtYxsLkhe6cr3ZbDYbMTTjgJyPkjS+fuj+/fvjgJO5hAWMt3J+Jq1sJcwuIzN4LoMrXiphpjBK208M2LJ6C3Sm0ullTQk/mSnkcV9L5bVw0ujZI7Csan2iEQDn+qggLH8220yS9yhDCypOKhTHxMfI88vLy3H9Ipd4uU183a+0eWwoY3WilMq4Jh2MokmaBPqGEIzHCAsYJGeALE0tJ+MOwipJWwrle1mGKRmZUKyqm56ZUJfCVmVFCTndtoQ4/E84Q0NDCEivlHCOAkwFr+K59GQ0EuZvxj1sY8Wnh4mje96QZVLR3M6UAxoZjg09MJUo40b2aZ/XOyhFkzartCsrzywcB9IMorU1mWnn5+fjshxmpjiXZUvPQU8hYP0cKKa/My6wMHqg0yuwHEJfThIzo0hPmEkUUyYYsszKMPE+C2Ku5yNffL3bwHWB9mx8tImLnc0r94fxL8eOPKfRSrhGHnIDXk/Qu23psXgPV79U86v0aiknbGdFB6loFPiEA9U0gCkF1mSB86C7HF/LOCdjN1pcHq8sveuh1a+EOT1ZDnoKVgVNeta8OldZ+ap9vXKz7krAGKuyn1SE9NrZPo4r25X8SCPBcmgAXS+9GGNSyljG8lX/ejzf582kA1G07EglBBxM7o9PWMCB4jpAW1ZO5jLeY3yY0MDlGsa6TXwVLCFpZhVdB+Gc+0glt3Eh/vcgcnW++0Yv6nK8bUDWRz5W6/wM09ObsE3OaPqp7t44+jpnGzNjZ+LkfKITH6NXrWSDMbrvcYKHHs288auozNejo6PxKQafp0F3m7ikK5WKEPIl5dGkbQtGxSC8olBbGSzYTqTkUp3KcmbcwYQJBdTlMOjnerpK0dyfxPy+LpW+sqZsY2XdPdgZz7L+jKsyRvF3BcUywZTjxOs47ZAJroS4aVwTRqcxTE9Mw0fUkbGXz1d9dl99bSaYctw+WTooRcsYhV7D1tRW01m26+vrcdV1buxJq8Q6JE3WU5qBvp6xAb2DFdmrVOxdOcjS9JF8zhW5fi98ppKy/yZbcguUPZavdUaQWUwaId/vOMuW3TEL40qm/sknJk0onFQWelcaEl/nsXCMnIbJ/zkmbmsF83y917hmNjUTG4SNye+E9R4rP27EMXwUZTsYRaMy9DpjQaS7Tpfuc4RgGVOYqYQsHjAKDuNFl8U0NidaWS9jInoT1p1eLQc9vQW9qNuec1u5csI8ygl+CqG9/y7oY6NRxXI0VpxiYB/So1femArENlKR0jvlfCr5xWuqlS40BtkvJsv8Scrx26eEB6FohBzSdAlSMoaw5/T0dBJvSNsp+YxNnPRgtlGarpXkvA/bRihBIc1BzPkjxo+ZGbTHoYLkag3X6SfLKyjJvtKruS0JGRmruc2pBC7Lbcx2p/eSpin89EBp8Bj/UhGpYOxnKqifQKCRs7Lf3GxeD3xxcbE1P+h4nSthfK89L7PUlpFc6NzbeSvpIBQtiYPM/+5ItYQqPUcvlvF3teqC1xjG0MPR+1jRqGCs316wsnJUVtZNI0HB2heTJASlopGn9orpOXhvEpXKvxnLsL40mD7HeLUXJ9K4sV3sZ8/75eQxy64MVuWB3HZ6s4qPvD6NzcF7tIRNZjLncGaz2fiaJs5RzedzLRaL8TgVLAeGFtyUK7SdVbPnk7afUWObErbe3NxM9ld0ORxAl8uVIqlkvn8YNi8yz52l3IZ8XoyW3bDQ5XJ/fPeTgk1h9Le9DJ91y7bmqpTcQo4bqdKbXl9fT56GpkykEcj+51YG/G2jQiVnfzhuliPvP8N3E9CQJSRnmdn+pEdStNbavy/p6yQNkv6OVq9termkd0n6dK1et/umYfV+671Eq+fvikmVlbEAp1dJy0Xr5zpodbPuyvvwWl/DRImhC/g0frsuWu4KBvr6qr70nm4XjVV6APajMmxJ6QmYHaUyJqxLT8wPkx1ECWkg2Qa2o1rNUaEYJj/YfkJpU8pUPs9XZUh5L+t9XqBja+0Vkv6opC8YhuGstfb9kt4o6cslffswDO9qrX2npLdI+o595ZnxSRREabM1tDG1iRksChMHcBiGMVvozTirQZI2K0qsQMxIenA5GIyDcrGzr2VfM7s2DMNkgN0WetAeZKLisD+Md5IP/LBt5LXvpyBx0p9Kl2NGb8M4mplhz19VRiNlQ9J4bfIhjQLrbW3zLKJjrjt37ox1M+lhdMQn1hmasC0Zpz7fMdqRpDuttStJdyV9SNLvkfTV6/PvlPStuoWiSduxWRVAExpRuUj0bMkAeix+J5SgEFngpO0V9SbCNvYnIYePUwF8T849ue58SykV2nBuGOrHf1IJK8/Bdrlsel/yh0kb9pG8cv2Epf5wrrNCLvT0VWIllYtj5bGx0SN/7cVy0x5D+twCg0aIfUqUdVt6lFfrfrC19mck/YqkM0n/q1ZQ8ePDMHjEPyDpFbcpLxlDaJHQyhbk+Ph4srPUzc1mk5mxg9g7hALHe6Rty0XYwTiH3sQDwwHO9XwcFBuIar9CezTHMG6TNDUcjE282mWxWEz4Zcr7UkhSOaysjE/Ztxwv30PjR4ufyuHyCNc8/eA6ze/lcrmVjc3+VygkkQOVzHNji8ViXNfo/+a9XwTC5Jf7kyFAju8uehTo+KmSXi/pcyR9XNIPSPqyh7j/aUlPS9ITTzwxWjppOwPI2MTn12VI0kR4yWx6vXT/vQxR5X2okNV5tyXjNgsT+rxVl48zc8UdiHmdB5+P8Rwdrfbcp/FgmTQMNDYu17xJBWXCZhiGiaGpeOa63F/WQzicsWEqhuugZ02FTSVwm9KD28iSn3xw178dRhi657jlGFUxdcpF0qNAx39R0i8Ow/DRdUN+UNKXSnpZa+1o7dVeKemD1c3DMDwj6RlJeuqppwam0onZExLlIFCgmJJnpq1are9zrjNjGNYnTacU0IfJtRQAv8gvBazydmnhbdkZB9CSW/EtLH77KJ9yZrbQ8UgVO3r1Q64V5QtGbLw4JtmHFDwKo/nBzKk9GK9j3+jVuaaRRrdK63uMjXi4oaykCTS0kSI6obeyd/W1VuTKmFQGiPQoivYrkn5Xa+2uVtDxtZJ+StJfl/QVWmUev0bSu29bIOMQUg5yL9vkgaysJK/j78wqVVDVg0pLR8NAIuxlLMkBzIHKwJqWtfJCVJhdAXhFKaycV0t4bsvPZVi5jClhW87TJQqxItDAVcaNnitXhnCKxvfbI+UYV4+35HhldtHylgmoHOOHoUeJ0X6itfaXJf20pGtJP6OVh/oRSe9qrX3b+th33boxR9MXKEjTxaipbGaEYxGu+ki46bJIOeka/Ru/XR8zVBUMZbs4b2TIQkUjJGLCxlDGmVX2m/A6jQz7mjCOsUwluPYMbi/hdr4/PBXz4uJiohRuY4UAkiqj6XYSHWQIkfteut1+sw0TTTYWRAhJNHKMG8nT5DeVLa+p6JGyjsMwfIukb4nDvyDpix6lXA8q19dZeJg88P+EXBwEwxBuk71u+yQwT8VO5pnpvXSvg3dDjCpL5va6rLSKFvJ8AJIKaiEk9QY8jQ1juyp7xnYxdssx4Idex3Wy/oT4/JAMcz1maUzZPrcpDUnlkQnLq+vJd2Y5K49lQ5LHaCR7dBArQ0y0Qu6UjzELyLWK0ibYtuXKIJuWhsLjQUv4WBGVml42YZfnbFLJqNQ9y8cVJJxuoGLZW+xSEnooUipPwi+WacFLhXR/+Ppjrm4hH30+PXZ6MPaBhi2ziyYrd7X5q8koolocnJCcnjyhNctOuPswdDCK1htsnqPi2Xtkap2MqgTOQuzznGiWtueF2D5ps31aWsWegpLSkxHS+ZuKlErN7BqVMZWygjfMyLHeKka1YaOnqhIpbA8NEY0P73E9ea7ykBWkrOB9pXDMNubGOr1xYF3Zr0qpGBvmOFZ0MIqWlMkGWyQLihnsTpqpXN+WMJJCywwePWbP/VeQ0/9ZdqbKfU1P6KTpg4dUNEJJkv9zLabrvrm5Gddr9gSFRqMyEPZE5H8vPmaZNoBUSt7LulLR7BVTyVhvFauz7jTCfONneqFd8LBKfPSULfvVo4NRNHamEvYqjmKWyZPX1X2pDKbKAuUxDq4FmxAwoRG9qJXS9fpcPvuV57m3IqcpUnD5iIZ5SIid8WAqXSX4ye/KOxLeZzk8xus49ZCKyjiP3o3t9n1V1jD7UMVk5HEqdM8QMou6qx7G0D06GEUj0Vv0BCODUlsw35+WKVPoPUpvQ49Z3Uuh78ViHHjD1VwBwuurrBoVh3WaFxk/EMbRO1jAmbRhP3xvj1c8zvsNx2ns2GYrWqX0XKXDc6l0FVqoiJA75yStaKnUCSsrmTCfMlFFY9ejg1G0XcFlQgQmB8xMLjT21mIerHwwlGTFSGuUAkdGssz0ktwYhuXaqlM5sh/+uAyvWMg2uG1cJkXBZ9vT056cnEwELSeqK6ju+60MnHgmvxgbMz1+eXk5vnzEvKDCpDFIo5BL1qqEFI1LpvQ5Bm6bP66X8LJSpl2xuGXyJefRelRlGyWN8Yxn/KVNWt8DT0oLlUpVedKMd/i7B9P4HJNjBytnxh/uHwfNA07FSiFzWwylaaGpbBkbOi5Nr8lEQFp5wjvGtBm/Mc60olAxPTYU7lTU6j89di+1bz4nv1iHM6VVEmwXVZ6ugs0VHYyiZcxCRlNYmHZOBZKmGbkq2E/GEtLQEnKXK2n6IGPF8GyLkzW5brG1Nnoqt8FCkxOrjkH9nzCIbSWPGDdy0juJCkF4lopHxbJ3csKlyizaY5ydnU14nAkaGgN6cmkas1EBqti2+m3ecHMj98EP0XKZl+vMOJhGjf2sYsV9dDCKJvVXZzB9zE8VjPv6CjenBZI2O225Dm4uw3jIxyrltkd1W+hNKyuX6/xsea3cbj/3acx4g4pGHlhA5/P5VmaVMJTepVI0X5s7TXFzIno2Kpr3SKQHvLy8nMxV0QPlRHEmRqiQbHsSeWN+uY82ABmfkX8JacnXrDPRxj46GEWjMknTFRoVY6tjHIjT09OJMJvBTPeyLL84gul/aXuP9bSyhK1uNy2o66Mlt0LlxKvrTsvtc/aEbme+XNHC4hiPK2gyGcS4pQcr2V9/25P5mwrnONTfKdQZx2QI4GNVzEUif5j08NI1buVHuOgXXFxcXEy2c7DM5LxrKl3yicf3KdvBKFqvobssGOODTDdbEL1zVMZU/Obg8qFA30eMn57Kisayc62ly6RXsDCzDgpWBuCM2bhTM/nkrCYTMhRa84n1VHwhZb8zFW8vYQWjB2RSJD0APUj2N6FiGsY8RmXLpXgZN3LPlFS0XXJIfqTs3Oa+g1A0wwcKPAPf3j1kNJnLhIMHnVuE83krP+T34MGDsSxp+rYWl79cLscXG9Ir2FoSlg3DdFtsKjDjQFpR9olEaEmPllMOfF83oaa0iS3c98qAuC7ew7k9xjZ+cNKeLLd+60FRnvP9hMC8ltCS40noPJ/Px1cr5fjSOFxfX0+2nWP7qPzud45DejD3g3Jw8FnHtFC97E0liLT00vbCUgpj9aHVJ6yjR3O5hkTS9J3b+zxCFUel57MSVMT+UcGY1s+APWEoDZDLYflVksfnbDQSGqZH4/27MnD0Mg9rVPnfCsWlVjQw6c0SaeT4ZBuzDT6e53rtJh2EolVJAypBMrqaP0mGnZ6eqrU2WjG+7C4H2N6FForCLGl8cNKKxslmwteMKY6OjiYvuWcsmsLJLdCTB4SEOUeUC2dtzW9uNo/qZ6zqOnI1jT12jg9fQ0uISIWjpee4pnciv6o4jOPksaUCESpyw9PFYjFZrub63We3uepfUqV8lVcj7TIuB6FoSZX12tdxaboImXNSPLeLeha2Z6kZZ9gj+ZjrpBfJPvXKrvrMODMhqu9lrOh7em2nseJxW/30eDQKGftYmCteuuzc4q3KJiaPel4llY1QOqFvKtttqIrDsn1p4Hue0XQQika/q/9+AAAYw0lEQVTLTQhVJTe4DpBwh7Ah4z0OJNcrSpttqReLxZgWJ8PyUREqM2MYtpXQhYPrNjK54Hs5UISELo+eM5+t431so70gXyPr+5K3TH9T8TgWmRXO+l13QmoqQ5WgMbEOjhuTKS7PmxLZoxF28xVTjqudccxsbAWtKyXvwUMa1V0Q8iAUTdoMVs+6Sbtn5mnRqByEJWkJfcz3VqlnCmLVtl3UG6xdMSi//ZvegMF3Bad73p/nqLQsxwkXKmx6sV4sxfrpsRhb0lPvEsoqrmU9hMhU4Ooexpc0vr16yZP8X/2u2lzRwSiatO0tSI4HmKXj/Enux5fzXr7n3r17kzjh7t27Wi6XY/bRL0bI2KWCc/TEVCIucE4oRw9nb5X9d9s8b8aMJdvA/icMY6KA822EdBQ+ZyzZDmkD+bj63uXQK3IekeWwfwnpOFaVgaCRJKJgXFbFq0Q89Ogun0aGhiQhc3r+XhiTHryig1E0Wr9scFpgXs8H/Ag/KXC5O5Y9H73erkC2aostmBMPOYh53P1K/O8yq4GkoGaywNe5P7yH1j4ffGRM5b6kYmQsxzb3hCnbl5D9Npk519GDpfReue6T11OJ3df0OD1vlcrmazMOq2K2XXQwipZxDS0YvZM0HYyTk5Otl8gz1vIKEZ83nn/iiSd0fX2tBw8e6ObmZpyLefbZZycwiXjedbstGc+RGF9UyuVjOcfHviXs8lbV9mzeKo7P5VHJMhtJQ5Zem8kWv86ostQUuF0QNR9WJU+p3Dmu9IBc4eGxOz4+1r1797aWn/FeywARUI5djgcpPXsqmYlGd1+i5SAUjVaJA56WPueZKKDSxvJk2jifxKYgMHjfFTtVykLK+3fh/eqarK+ysglbe1CGRAORMCnbUvUx59cqtMF6em3IWI+Cy3p7fZSme6r0kILry2TZrmuTaBBsaHbx+DZ0MIpma20mcIEtP7ZUtPJ+xooQ0d+np6djHbPZTIvFQrPZTA8ePFBrbXzlk1ebV4JLwbRSe96Ij4vQ+nO7ucxwucxcN8m6EqIkbGHdzBSm9zfRO3AC13zKJVZepe+60ztw4p5tqhZT28NUwkoDlQkVpu1ns5nu3r275b1TIcwXr9axTLgO951yknCf/E6+Zg4gYWaPDkLRkgibpM3Tu7SEic19X2YLTRa0DJ4zY0UvaqoydLvanhk6TuDyO9vMRbd5jZXBlDGR29kL7jltYsXhmkh6ASoi21Z5RAs421YpWo4dqReD+1xmGHNss87Km+0atx6yqLwuy6riuR4djKIxJZyDkWnmjF0yWPd/Ds79+/fHjWMcF0kbZjkm8cOZLifnyagIqYBsMy1jxiQug1CYWD8H133IOS6fY1bR/5nwoCGxdzg/P9fl5eWY2czFwl4JkkLrcjKL5+fN/B4ArzChF2U70runYWU2OedIq0lpfvJxmEpZKC/V1E1eWyGGDHl20cEoGqmH02lh9lkSM4Bza3wCOxmbGS1acFLGFzzu9vo8M3u8Lg0KhSSvc5mcyKXgU5DstQgDmQSZzTYLk/moiMtP6EgDkYJWQUMrLLN8+7xFGtQe2kh+mQjveg/nVmNWKVWFjnroI73aPqRzUIpGr5Yp7CqAJ6aXNoNHiHHnzh3duXNnvOb09FTDMOjs7GyyPs+Zy/RoJrfBK1M4Z1d5mczYVdfZu1g4aTwM36RNvEeYZstty09vSH4lQjBfLi8vdXV1tfW0N1fjs01uOzOf7ivjY0JPxt4epxRQZhVtFD0/xlfcZrLM1zNWdeyezwBy+z6PhduTsS+JitWTPZ/LLGvSQShaZal4XNrOFuW5TL9nitvnEnZyQBiAJyMpRNlGei16EtfjMnLQqKi0zNkn10PLbQEz7KJwc9K2FxNxkTQV022qFuBSWdOjMVOc53ZRohQqFXlIo0XvzjoSAqaCEs24bl5fed+Uy/TUFbqp6CAUTaqXvFhRTFwaRAZVnsKr1nMfDltYJkekDexYLBaaz+eT9YEVNLA3yZUICbFILsseqUp8kBeEgO53xk1WFnpA1sffFApn5tJTuE0JnX3cT0Vke7KsHrzO48MwTMbCxo6Qn54o22UDtFxuXkh/dXU1vkLX17DN3J2aXrWCkJkQoVGkMdincAejaCRCxh5WZqfozXI76LSKpl1xAJmfaXJ6P9fds3iMn3yODx5m+2klpe3X+FKokyrFzHM2DhZGeoAUsizD9/nbHiaTQ/TSGUeTv1Us1huP5IvLIt8ynlwul+PbZbwYnRCR9WecmEiioqp/uxIiB6NoGYha2KXtdXUcKFrq2Ww2zqstFouJ9eVTzsbrjgOchbOiDsMwztcwe0gY6nYZrjmjyYC8gm+tbfbjYCKCc2rch5KUisb4yGQPZ6Vw/Mf1fk6KOPtKi55rRHN5l+t1+bnLV6b5c4wz5nJMZqSR8N1jwDF2G7n+MhM5p6enunfvnlpr40shyVPO/1H2eryn0tOYEKXsor2K1lr7bkmvk/SRYRh++/rYp0n6PkmvlvRLkt4wDMPH2qrFb5f05ZIeSHrzMAw/va8OdoYJkcqb+TpTxlwZm7kc7g6cHpCQMq2uoSFjP2ma7ZN2P8NUxQAcqEyYpIejZ6Oi8b/5ZMWjAvvbHqzyPpkAyniIlp//6XHSQ1BB04vk8jDzlufcjpSBlIfkob+985aXqnE3aXrMlC0qIeskSqlQ0KNCx78o6R2SvgfH3irpx4ZheFtr7a3r/98k6fdL+rz154slfcf6+1ZkIbAVIwRjoE0G5TySPZpho7997MGDB2MZtsxHR0ejdffqfSoUBZ57KfbmvOjJ2LdUICsJU+KVsnGDm4SOjk1o0StDRUUjEsgEC9tLfhMy8rykiQKl8vh37umRMRgVzCjDfamgMH/34PjZ2ZlOTk7GdayLxWJcLeK25dhkIibrND+rvj+Sog3D8Ddaa6+Ow6+X9Jr173dKeo9WivZ6Sd8zrFr1t1prL2utvXwYhg/tq8eNZqfS6rCDaRlNPJZLeFwGB8oPCfrbSmfm2wq6PRQCtquX0cq2SdOYS9KWkhH2PQxV/Ov9J18zJknFqjxQKpS0eSAzlTCzv7sWPdPjVt6eRJ7xt4lJEhvb5XK6FC6VrfJy5B155Pt695A+2RjtKSjPhyU9tf79Cknvx3UfWB/bUrTW2tOSnpakl73sZWOjGcxnbEM3zRUC7KQHm3MyyQwqjufPbOUca3nQrYBp/WlpmXUjWck94BZCepPMVrpdPaoGNQ1TZsr8n7EYkyC8n5A5FY1KlMrn/i0Wi60x87U+7qywxyvLS54w00eigmUSyPy9urrSxcWFFovFmIXsrTFlezhGjA/ZhjQ0u+iRkyHDMAyttds9bDS97xmt3nmtV77ylcP62JZVqgSEypRCIq0UwVCRwmdoRcHLLduYIJnP5xOYYUjLJAAhh/vg3/nUttvJ711kr0Y4ynsrL8pvKgr4Pp6j8FLQDKcJo8xvTyITmrOvafyoRCyLxi9jMi5MpkLklAljU49pQjzCZmdd79y5M3kfAD08DRUN8z6Fyrgx6ZNVtF8zJGytvVzSR9bHPyjpVbjuletjnzRR0Qzp+ByWPQuDXa4sp0BlvCdN998gzOH8WsZxvs/nLTxuY2a0MoDmqhKpntSll2Byw4NOBachythsH6xJ5cw4yXVYwZzB41Pd9Fr0emnAUumS54zJmLQy/zy+7n/v1bs01izT82v379/XxcWFzs7OttCE72X7jbR4zW0MJemTVbQfkvQ1kt62/n43jn99a+1dWiVBPnGb+IzKJE1xs8kKwjmyk5OTCWSrMmQmD5yTDxYKww0u/akW49Lqsl2c1O4NgD1TxgVUeg4mvR4HmF47vZrL87FEBskTlsV76dFoMMhzIgGWRw9KXmU8lte6n724jMmo2Ww28UTJA/fBfeJvGkHDXHs2xsu7+OT62IfbKN1t0vv/g1aJj3+itfYBSd+ilYJ9f2vtLZJ+WdIb1pf/qFap/Z/XKr3/tXtbsCYLI+MHQgUPghXCH84ledfbCrJZyfzxHJuZ7LoYqDNwpoBzdQK3l06IwVQy18JxcOy1pG3vkpY2Y1F6tqybEMztZhsyQcEYVdqs/UwU4ef5uFqD9Vdey2OWQlvNSxI2ZtbRRjWfAezFTTa85oWXm7H/fG7NyIHjwOt9jEmT28Zpt8k6flXn1GuLawdJ/+7eWoMYfDOotbCb+Z7YvHPnzmhVucLBMQRT8KYq8WAvkl6D99LC+3guRk6h4GCkxWN86PITllB4rYhUHFppxkkmJhQY21IguGCX9fo699djYcjI+NX3Je98ndvC65kUobFhLEVeVM/E+ZEcr/xIoqKxb3zGjlCUBj2TRRw/wvSEzfS8FR3EyhB2mmlzQgomL2hVec4DXL0EwmXn/oZS/VCff1fBPMtmoO17XH4ucs04qFJ0l0li0sflpBV3H+mN09NS0XKHLRIVw/UQMlZW3ALoNuQaU3q7jJu5dCy9uNtAGOkY3BlOCjo9OxXNY+91oZnt9HWZxKFCMb6mkknb85BJB6Fo0nQVQR7zIJ+enk7StNLmJRUWqsx6eRW6mc7kAj0LB8rXmWjh+d/3kclc5iRNN/FJa5kW3eTUN+M/C0cqEJMe5hnL7yVF7P3ZR/KdbW6tTRTz/2vvakLuuMrw8+bGfjffF7CJumiN2EhLJZv+0EWLLkprsRRx5UJx2aVglEIhdOWyIP1ZlIJUXIio2BYtWSjaZh1tUaQ2jbVUbAT1K1gLH+R+TTguZp57n3m+d25CNDNDOA9c7p1zZ855z3vO+ztn5rg2d+itF29D++DJD3onvJYWyF1FnRvkXwZXImyT6X66tPo/6/YYUsc+m2fuQe2hpfefgaGMy/x4rsbe2NhYPlPGLKBm8TyJob65azBtyzcz90FVrafuHgeZwuaupyc7MreD9ahLo1rfXUFdgqXfyjd/R4hPUM0q6sRRviudPN9dYcZyWSKHwky63dqqkKmgUalQyGjhVaG6O842NSmlyRyed/Hixc6T5apAs1jPrTfP9VtHmWeimISgcfKQeGoZ1yzz+XwZg2mWTBmhWlOTH2QQz1dtTTfPV8Vr5kwtmLanbp5uXqhuYxa0O+3usnKi8JPFaD659Vivc8Whk949AaXBM4Wq3VmuFsH7wbFg31041KL524QzN1Jvtfi4sz1VTqTHBYYWjf9rppltuYBlysx5rv1zTELQgFXnZrNZZ9WAMpYBPMvJULdQqmU0UeHBrcJTy+4uqHbkoKjroRMEWKWJdcKqQOi9GqVZ22abqqVLKXvuw6nlIhgnkSbyThMsKvwuaKTJb+iTPr1B7dew/+z3Ok3vSSSNyVXweG7mzildvI58dkFTK+qxlnsd3ielwbFOyICJCNq+ffuwtbW1XM1BN4UTxRkMdBMo2YN83NSAAsxB81Q6f2vGSweZE0rPV01P+j0A17q1nyxzqwNc+sWeKnheN9tWd1SFQCd9FrNlsQi9i8xNo2DydX5Ou9albjQnOh/b8acpqEyUj+7aMVzItsf1trUO8kOTL8xkkybdEVS9KHcNqYD6LJ1jMoI2n887fjPdklLKchcQ1/yqqVR7cfJqJlD9aA9cdQJ4mScFlGagGydxMmf3xfx6pd8D6j5BygRI62cdmcZXi6X1qkbPztd7km4xXRmyPv12GvUJA/cieF1WptaObevKECrTPo9F+6rCrH3kPNLbSyqgygP3UHxMHJMRtIMHD3buhwGrjKEHm+pDK4OAVcYLQMdl0scjyDxlOK9n2zpZsw/P0brp9ur6RAq831JgW6wjIvbEiMofghODfFC4e6fwpJGfp33SY+WTXuMTS+M9RSZgmgDx5+VU+Ni2lqtVVvePwqFKWG8xACuryyw25xE3MQRW2ySrl6Njp7d5WFdm+R2TETRaL9VOykgi08a8Rq8H9rpSWqYJBZ0gmeX0trQM2LsCXf/XODGbzCpoqrmzNvk7E7TMVdNy5XGfddU+6fWeyNF+Zvc9HcpjFaQsjlbFp+6u/8d6VQg03sz6pAqax+yfhixKM+lSAXNFy1h98oKmk1wFg4zxV5a5e0CGqZvD+26ueXUNH6/NBlf/Y7tuzYBVcKyZ0tls1nkYUevgtd4HakWHW991sdW6FQ7sl6bPVQFlysXHKFMGjI89ruI1qjD1N7C69eJuvK8fdbeYdehbwIgsm6r308jnbDkay5VPzCRvbm52xsw9okthEoJGuBDpBPIgXrWUTii9JsuYUQu5VnX0TTjWoZNStSLh2ThNevTFEW59WeaP5GgGVC1WFhtmWTrWqTT4TXXCYy9NLCkNmuljucY7/M9DgD53U10254cmM7S8b9Jn/cwsusddbMPvxzk/180VYhKCRi3jaWr6v+oCUIB2d3eXrx3gxNGJvrW1hfl8jp2dHSwWiyUzuESL13JA6TYwE8Z2s2ySWgSnza2UxhAezOtAMT7V2MQtvMcJ2p7Gpgrvg2p69lfT/f5QpAq5CwnL3e3zCch7mrpcTa2W3kOLiOVSKdLPvpEfvqE9r3OLTiHJtiJmufaZyooLInTJ1ubm5pIfOjas01f9OyYjaOquaRzlWltjGh0czYCxzv37m3eA9LUFdFdkZBrd4fGN/1aLScFRFygTIHWnnNYsRlNe+ORxeEyi5fx2T0H76N8uiDpmWXkWl2mG14VSLQn75BZcXUanz8eqLxOZhSDkhyo67ZOOWxa+rMNkBI2r4IGVy8M79vrOB0KtAF/AQgvIGImrTVgXJ5evR1wXrGsgTJ89sx4qvP64j0MnOdBdva4JHF2tQD5l2rTPDc2ER90f9p3I4knlhcZUaqF5nn7zt2cY1Yvw+Ngtno610u9ZXM+mkj+adeaxxqyM11XY1dopaFG5RjLj2TpMQtCAvTf8NLPl757Xj2o9uo/qgroL6HEVy/piBf8vi0UUbuFms9VLdrL4039ruxTuPoFy68rjrNzhKxyyvvI8FSgVMI+JnDcqkHqNt6fH2gbr9FhNU/1Z//RcHXu3SB7X67GHBVqfCqc/hNqHSQgatRIFiRpvsVh0BlTdDfWnDxw4sHxhKi3b9vY2dnZ2lhlBTkBqZXch+1w019q0krrEiv8B3XcTAqungrM1gbyWm1Toq719QFmXZgvJD/ZPrYDSoILHScFJpdYkO8+FI3u1G+Hna+yl55BPGrepNXPXcXd3d5l+Zz/VWilP1WLpawfZNueNf1jP+fPnsVgs9ngEFy5cwGKxWGYfubiCtGgeIMPlvcJnALjvq/GSWxOeD+x9vRwZx+t5jicfMncrgzOvLxbJ+uJlfZbJLZr3tY8etSB9Fin7z2OqPpd5Xdml+OXffbximQt0Vl8m/OvgMW5W3hfz+rnOWz2/L0To1HM5BF9tRMQ2gB0A741NSw8+jkrblWCqtF1Nuj5dSvmEF05C0AAgIl4tpdw1Nh0ZKm1XhqnSNgZdk3EdKyquZVRBq6gYAFMStO+NTcAaVNquDFOlbXC6JhOjVVRcy5iSRauouGZRBa2iYgBMQtAi4sGIOBsRf4lmY8Ox6PhURJyKiDci4k8RcbwtPxwRv46It9rvQyPSOIuI30fEyfb4aEScbnn304i47lJ1XCW6ro+I5yPizYg4ExH3TIVvEfHtdjxfj4gfR8R8aL6NLmgRMQPwDJrdQo8B+FpEHBuJnAsAHimlHANwN4BvtLRwh9NbALzcHo+F4wDOyPHjAJ4spdwM4N8AHh6FqmZL5V+WUj4L4DY0NI7Ot4j4JIBvArirNFtDzwB8FUPzrW+JzlAfAPcA+JUcnwBwYmy6Wlp+AeABAGcB3NCW3QDg7Ej0HEEzYe8DcBJAoFnhsD/j5YB0fRTAO2iTa1I+Ot+w2hzzMJq1vScBfHFovo1u0dC/S+ioiIibANwB4DT6dzgdGk8BeBQAFxt+DMD7pRSuJh6Ld0cBbAP4QevWPhcRW5gA30opfwfwXQB/Q7Pz7H8AvIaB+TYFQZscIuIggBcAfKuU8oH+VxoVOPg9kYj4EoB/lVJeG7rty8B+AHcCeLaUcgeadasdN3FEvh1Cs7f6UQA3AtgC8ODQdExB0P7vu4T+L4iIj6ARsh+VUl5si/8Zzc6miO4Op0PicwC+HBF/BfATNO7j0wCujwg+7jQW784BOFdKOd0eP49G8KbAty8AeKeUsl1K+RDAi2h4OSjfpiBovwNwS5sFug5NoPrSGIRE86zD9wGcKaU8IX9xh1Ogu8PpYCilnCilHCml3ISGR6+UUr4O4BSAr4xM2z8AvBsRt7ZF9wN4AxPgGxqX8e6I2GzHl7QNy7ehg9OegPUhAH8G8DaAx0ak4/No3Js/AvhD+3kITSz0MoC3APwGwOGR+XUvgJPt788A+C2aXVZ/BmBjJJpuB/Bqy7ufAzg0Fb4B+A6ANwG8DuCHADaG5ltdglVRMQCm4DpWVFzzqIJWUTEAqqBVVAyAKmgVFQOgClpFxQCoglZRMQCqoFVUDID/AjlcKPp09I/zAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Projecting the image vector onto the eigenvector space for the training images."
      ],
      "metadata": {
        "id": "Hg8aa-AKdPQQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#storing the weights of each training image in an array.\n",
        "w_array=[]\n",
        "for i in range(len(cov_matrix[0])):\n",
        "  w=np.linalg.lstsq(np.transpose(u_k),np.transpose(a_transpose_norm[i]))\n",
        "  w_array.append(w[0])\n",
        "print(len(w_array), len(w_array[0]))\n",
        "# w_array"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gnVhNr3ED62j",
        "outputId": "548970bc-943c-43f1-ce3e-7f04f10631fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
            "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
            "  after removing the cwd from sys.path.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "160 12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Testing the algorithm.**\n",
        "<ol>\n",
        "<li>\n",
        "We start by gray scaling and resizing the test image to fit our algorithm.\n",
        "Next, we normalize the test image by subtracting the mean face from our unknown face. </li><li>\n",
        "This normalized vector is projected into the eigenspace to obtain the linear combination of the eigenfaces.\n",
        "</li><li>\n",
        "We stack the w vectors obtained as follows:\n",
        "</li><li>\n",
        "We take the stacked w this vector and subtract it from the training images to get the minimum distance between the training vectors and testing vectors.\n",
        "</li><li>\n",
        "If this error comes out to be lower than the set threshold, then we find which face it is most similar to in the training images, else we report that the test image does not match with any image in the training set.\n",
        "</li>"
      ],
      "metadata": {
        "id": "zy3kFuSheBcb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Run this after uploading a suitable PGM file to the colab runtime."
      ],
      "metadata": {
        "id": "kdmdpVkeeafN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# calculating the k weights of the testing image.\n",
        "test_input_dir = '/content/test1/2.10.pgm'\n",
        "\n",
        "img = (cv2.imread(test_input_dir, cv2.IMREAD_GRAYSCALE).astype(np.float64))\n",
        "img2 = cv2.resize(img, (92,112)).flatten()\n",
        "test_norm = []\n",
        "for j in range(len(mean)):\n",
        "    test_norm.append(img2[j] - mean[j])\n",
        "    \n",
        "w_test = np.linalg.lstsq(np.transpose(u_k),np.transpose(test_norm))\n",
        "# w[0]\n",
        "w_test[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v7sytPPUHcxG",
        "outputId": "afc8290b-deea-4d1e-ace1-bdb5fa32ebec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:10: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
            "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
            "  # Remove the CWD from sys.path while we load stuff.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.06458022,  0.03106545, -0.00325797, -0.05024619,  0.07550252,\n",
              "       -0.03153704,  0.07448419,  0.07458258,  0.11583648,  0.18621974,\n",
              "        0.04560699,  0.08938435])"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Generating the output image by the weigted average of all eigenvectors. "
      ],
      "metadata": {
        "id": "7TGiEstKesrP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "test_out = np.zeros([10304,1])\n",
        "# print(len(test_out),len(test_out[0]) )\n",
        "# print(len(eigen_vectors) , len(eigen_vectors[1]))\n",
        "\n",
        "for i in range(10304):\n",
        "  for j in range(k):\n",
        "    test_out[i]+=u_k[j][i]*w_test[0][j]\n",
        "  # temp = np.multiply(eigen_vectors[i], w[0][i])\n",
        "  # test_out = np.add(test_out,temp)\n",
        "\n",
        "test_out\n",
        "# print(len(test_out) , len(test_out[1]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hj2uRB2ke4Vy",
        "outputId": "cc43eb03-917e-4e39-8efa-01106529b1f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-57.93336317],\n",
              "       [-57.019568  ],\n",
              "       [-57.37504091],\n",
              "       ...,\n",
              "       [ 10.37543204],\n",
              "       [  5.38218141],\n",
              "       [  9.78964487]])"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axarr = plt.subplots()\n",
        "axarr.set_title(\" plot_input_test_vector\")\n",
        "avg_image = np.reshape(img2, (imgShape))\n",
        "axarr.imshow(avg_image, cmap=plt.cm.gray)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "Hniwm1aO3HFG",
        "outputId": "36ca6488-c6e8-42da-93e5-23926e5cbc7b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f3181ee8090>"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axarr = plt.subplots()\n",
        "axarr.set_title(\" plot_generated_output_vector\")\n",
        "avg_image = np.reshape(test_out, (imgShape))\n",
        "axarr.imshow(avg_image, cmap=plt.cm.gray)"
      ],
      "metadata": {
        "id": "1GzhX1NCaVa_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "e288cc3f-ece6-4978-efc2-bae1c5376ac5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f3181e4b090>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Calculating error and finding out the most similar face in the training dataset that matches the given test image."
      ],
      "metadata": {
        "id": "dDLZZEzBgTcL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "err_list=[]\n",
        "err_ind=-1\n",
        "for i in range(len(w_array)):\n",
        "  err_list.append(np.linalg.norm(w_array[i]-w_test[0]))\n",
        "print(err_list)\n",
        "for i in range(len(err_list)):\n",
        "  if err_list[i]==min(err_list):\n",
        "    err_ind = i\n",
        "    print(err_ind)\n",
        "print(min(err_list), max(err_list))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nl3S2qqY6V6V",
        "outputId": "4ac6401a-fda2-4fe1-a05c-26417ffaefc2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.34400506725215224, 0.4086184422732713, 0.3390396914525325, 0.350996578240961, 0.46533988720905706, 0.40559758059022627, 0.40332782853805116, 0.34467609524318865, 0.3906116427405409, 0.3895738260219576, 0.3937433501993539, 0.36858183633802327, 0.33446009159634316, 0.3884317531589484, 0.46741174253482987, 0.27276878051150066, 0.41437676904625514, 0.41752461395158635, 0.37899779987721455, 0.36645818899995364, 0.42218206735391794, 0.4199528332673603, 0.36639903445709926, 0.3656055229202129, 0.4448957885345691, 0.4222783902336476, 0.42861125064883526, 0.40875255589734005, 0.42037840448647307, 0.40784167486554596, 0.43398920031944094, 0.4312729186122849, 0.5232602383766208, 0.3537590324318279, 0.4308698066419294, 0.39521233250606214, 0.43628524862401236, 0.43416682148755276, 0.505902166362936, 0.42811646500508965, 0.37338280645889427, 0.3947756834885681, 0.37322236000409437, 0.4155734597445805, 0.39082251644399596, 0.40310836355944707, 0.395961815698299, 0.36159694026553113, 0.36532594638921256, 0.44712499881230566, 0.4208554876537378, 0.4114800331217359, 0.4338686733356697, 0.4229507413730558, 0.38538448141004994, 0.42881931543037827, 0.4175263817989803, 0.39217791741320907, 0.37660163315333717, 0.400062620334388, 0.35754424680352526, 0.4056026029981082, 0.4209321667290099, 0.3687529127879699, 0.3125710563524516, 0.33678824323839535, 0.2719258857732553, 0.3338110480772194, 0.32966477135052963, 0.3405858034666539, 0.30861276306978497, 0.317720253184521, 0.4525747989761004, 0.39815505628734293, 0.41626242928244794, 0.40992508482261997, 0.40766776112702013, 0.43606672053666873, 0.4067910024681659, 0.37631792372467765, 0.0992980550988829, 0.1139481265159695, 0.0869197349324357, 0.16785741683355368, 0.11573238390738243, 0.07871307828956393, 0.12684164990258412, 0.0856959486230288, 0.40767810332431037, 0.3928237124646254, 0.3528535021441879, 0.39181972602287896, 0.4001778501042579, 0.3827569260765583, 0.3911005729186368, 0.4144097236604698, 0.46258514531579936, 0.4459577009618693, 0.40228363457786787, 0.3956984985246744, 0.4499004792074212, 0.415825801438534, 0.44442844365190226, 0.4327409238742284, 0.48335183580498775, 0.4723646156584728, 0.5138396551901641, 0.502954163151842, 0.46852032140007677, 0.4922786613802512, 0.514951294471292, 0.45335194216578906, 0.39601917239414547, 0.4198749098489404, 0.45754566535154634, 0.4672451346091814, 0.41709926026621946, 0.4746096879821277, 0.3946809567633838, 0.4333913749765745, 0.4546763606889827, 0.46744409927173086, 0.45255817505824747, 0.49712151757976636, 0.47030647061901676, 0.4633823863841151, 0.4428747163779644, 0.47049145156514965, 0.4511750044794822, 0.414157569311347, 0.41595183556824417, 0.4141599624378249, 0.39711150045615307, 0.4345892359688866, 0.4498955436300706, 0.42824207501660755, 0.3726885502659128, 0.35225022887673674, 0.4172810770270656, 0.3959925881186866, 0.36421232786459773, 0.41424664336409567, 0.37590248609429644, 0.3870082358694778, 0.32907408140309324, 0.36020515929015234, 0.3640522685344629, 0.3360098666091143, 0.32237406882981834, 0.30866331029805877, 0.3121758865823208, 0.3597574078365001, 0.5631304735149948, 0.41172691776002196, 0.3994565503365075, 0.43301719061078414, 0.4560264985828077, 0.3966641598681113, 0.5632570738264885, 0.41593650420206035]\n",
            "85\n",
            "0.07871307828956393 0.5632570738264885\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "r=0\n",
        "for idx,image_name in enumerate(image_names):\n",
        "    \n",
        "    if r==err_ind:\n",
        "      print(image_name)\n",
        "      similar_image = image_name\n",
        "      name = image_name[18:20]\n",
        "      if name[-1] == '/':\n",
        "       name = name[0]\n",
        "      # print(int(name))\n",
        "    r=r+1 "
      ],
      "metadata": {
        "id": "n12pGgN7W9tT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "20543eaa-2bb8-419f-a12c-12905056b6e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/train_small/s2/7.pgm\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "img_sim = (cv2.imread(similar_image, cv2.IMREAD_GRAYSCALE).astype(np.float64))\n",
        "img_similar = cv2.resize(img_sim, (92,112)).flatten()"
      ],
      "metadata": {
        "id": "yaFcbz1phGgK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axarr = plt.subplots()\n",
        "axarr.set_title(\" plot_most_similar_vector\")\n",
        "avg_image = np.reshape(img_similar, (imgShape))\n",
        "axarr.imshow(avg_image, cmap=plt.cm.gray)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "JEqxjd_vhzLB",
        "outputId": "8663d75c-9830-44b3-ffd2-77b3171baee2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f3181e59f90>"
            ]
          },
          "metadata": {},
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Accuracy calculation on the test dataset.\n"
      ],
      "metadata": {
        "id": "9VPEK34E1fA2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "IMAGE_DIR_TEST = '/content/test1'\n",
        "image_names_test = []\n",
        "image_dictionary_test = []\n",
        "\n",
        "image_1D_test = []\n",
        "for root, dirnames, filenames in os.walk(IMAGE_DIR_TEST):\n",
        "    for filename in fnmatch.filter(filenames, \"*.*\"):\n",
        "        image_names_test.append(os.path.join(root, filename))\n",
        "for idx,image_name in enumerate(image_names_test):\n",
        "    img = cv2.imread(image_name, cv2.IMREAD_GRAYSCALE).astype(np.float64)\n",
        "    if idx == 0:\n",
        "        imgShape = img.shape\n",
        "    image_dictionary_test.append((image_name,img,getClassFromName(image_name)))\n",
        "    image_1D_test.append(img.flatten())\n",
        "a_transpose_norm_test = []\n",
        "\n",
        "for i in range(len(image_1D_test)):\n",
        "  a_transpose_norm_test.append([])\n",
        "  for j in range(len(mean)):\n",
        "    a_transpose_norm_test[i].append(image_1D_test[i][j] - mean[j])\n",
        "w_array_test=[]\n",
        "for i in range(len(image_1D_test)):\n",
        "  w=np.linalg.lstsq(np.transpose(u_k),np.transpose(a_transpose_norm_test[i]))\n",
        "  w_array_test.append(w[0])\n",
        "print(len(w_array_test), len(w_array_test[0]))\n",
        "err_ind_test=[]\n",
        "errors=[]\n",
        "for i in range(len(image_1D_test)):\n",
        "  err_list_test=[]\n",
        "  for j in range(len(image_1D)):\n",
        "    err_list_test.append(np.linalg.norm(w_array[j]-w_array_test[i]))\n",
        "  for k in range(len(err_list_test)):\n",
        "    if err_list_test[k]==min(err_list_test):\n",
        "      err_ind_test.append(k)\n",
        "  errors.append(min(err_list_test))\n",
        "  # print(min(err_list_test))\n",
        "print(err_ind_test)\n",
        "print(errors)\n",
        "print(min(errors), max(errors))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4ujYnKaKNhOP",
        "outputId": "7887a311-328f-4914-865e-aecc9da1bca4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40 12\n",
            "[93, 30, 18, 99, 83, 132, 69, 10, 55, 36, 37, 110, 123, 99, 153, 85, 44, 3, 44, 99, 154, 123, 74, 146, 7, 21, 56, 8, 88, 136, 65, 24, 112, 136, 55, 110, 5, 76, 57, 127]\n",
            "[0.0757127465319844, 0.10885643270758318, 0.09982672432289147, 0.22965267358321398, 0.09663999294457895, 0.10747999023965292, 0.055989675997151954, 0.16283310445990043, 0.14024121457987115, 0.08898125784699758, 0.1091917765266306, 0.0421484701167536, 0.13195768691294044, 0.10475370669325086, 0.10345169369490421, 0.07871307828956393, 0.12175428724950767, 0.11715511620447168, 0.11937662312615109, 0.11984501287376065, 0.1837596768150345, 0.20196556808851845, 0.0657074177531883, 0.06459352913082324, 0.11651594954608181, 0.0658201048666385, 0.10880310269229757, 0.16724841426724457, 0.09996120926750159, 0.03269611984829349, 0.05048778170214982, 0.08773380517183153, 0.18297053305111705, 0.12392150772000826, 0.12214481272783141, 0.0843174151116105, 0.09381321355844549, 0.06815983554787529, 0.08350351134064858, 0.11261886054143717]\n",
            "0.03269611984829349 0.22965267358321398\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:23: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
            "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "IMAGE_DIR_TEST = '/content/test2'"
      ],
      "metadata": {
        "id": "MB2bRSHA4kAR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "image_names_test = []\n",
        "image_dictionary_test = []\n",
        "\n",
        "image_1D_test = []\n",
        "for root, dirnames, filenames in os.walk(IMAGE_DIR_TEST):\n",
        "    for filename in fnmatch.filter(filenames, \"*.*\"):\n",
        "        image_names_test.append(os.path.join(root, filename))\n",
        "for idx,image_name in enumerate(image_names_test):\n",
        "    img = cv2.imread(image_name, cv2.IMREAD_GRAYSCALE).astype(np.float64)\n",
        "    if idx == 0:\n",
        "        # the shape of the image. They are sopposed to be the same\n",
        "        imgShape = img.shape\n",
        "        # the normalized image matrix. it will be normalized by subtracting from the average image later\n",
        "    #img = cv2.pyrDown(img)\n",
        "    image_dictionary_test.append((image_name,img,getClassFromName(image_name)))\n",
        "    image_1D_test.append(img.flatten())\n",
        "\n",
        "# print(image_dictionary_test)"
      ],
      "metadata": {
        "id": "BFLudewz1h8-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# print(image_1D)  # 92x112\n",
        "print(len(image_1D_test))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B-or36Qx4quc",
        "outputId": "f662794d-535a-46c8-b3da-d48da144191c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a_transpose_norm_test = []\n",
        "\n",
        "for i in range(len(image_1D_test)):\n",
        "  a_transpose_norm_test.append([])\n",
        "  for j in range(len(mean)):\n",
        "    a_transpose_norm_test[i].append(image_1D_test[i][j] - mean[j])\n",
        "    # print(a_transpose_norm)\n",
        "\n",
        "# print(len(a_transpose_norm))"
      ],
      "metadata": {
        "id": "-ifHHsLd7CQ8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#storing the weights of each training image in an array.\n",
        "w_array_test=[]\n",
        "for i in range(len(image_1D_test)):\n",
        "  w=np.linalg.lstsq(np.transpose(u_k),np.transpose(a_transpose_norm_test[i]))\n",
        "  w_array_test.append(w[0])\n",
        "print(len(w_array_test), len(w_array_test[0]))\n",
        "# w_array_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-gHiREMt4-mk",
        "outputId": "6752a94f-3313-4454-9782-76c5f3263b47"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40 12\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
            "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
            "  after removing the cwd from sys.path.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "err_ind_test2=[]\n",
        "errors2=[]\n",
        "for i in range(len(image_1D_test)):\n",
        "  err_list_test=[]\n",
        "  for j in range(len(image_1D)):\n",
        "    err_list_test.append(np.linalg.norm(w_array[j]-w_array_test[i]))\n",
        "  for k in range(len(err_list_test)):\n",
        "    if err_list_test[k]==min(err_list_test):\n",
        "      err_ind_test2.append(k)\n",
        "  errors2.append(min(err_list_test))\n",
        "  # print(min(err_list_test))\n",
        "print(err_ind_test2)\n",
        "print(errors2)\n",
        "print(min(errors2), max(errors2))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-O5R9H1sKl6t",
        "outputId": "62368bad-2026-48b7-88d9-38b8d593b2eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[70, 80, 64, 64, 142, 139, 98, 67, 74, 70, 136, 24, 94, 53, 23, 78, 3, 65, 74, 64, 18, 29, 26, 64, 148, 136, 43, 29, 64, 19, 64, 26, 69, 145, 157, 67, 98, 65, 66, 25]\n",
            "[0.24455933614674108, 0.21225727440574949, 0.21483738113923947, 0.2264812212568616, 0.19503708762652225, 0.21052439930504327, 0.21937298516722972, 0.20007678390656794, 0.18103627681490483, 0.25375188437646584, 0.1898239623952792, 0.2095789084573638, 0.16793299966164493, 0.15377921146663465, 0.21237820988615969, 0.15129736285049772, 0.19429071916624643, 0.22181699853680736, 0.2172953972464706, 0.1851673660516963, 0.18568749015993063, 0.16346036514447684, 0.17130978526360258, 0.25363554542627026, 0.14079092639207766, 0.18591898763766568, 0.20677666448000173, 0.17019033105945425, 0.24572292568018825, 0.22270775040965246, 0.20489410866428956, 0.20714207572106164, 0.14314830244653792, 0.15424412868661652, 0.21356987051130216, 0.17955444373324905, 0.21084554196768995, 0.18143765852048863, 0.21813505783692944, 0.15510790948049472]\n",
            "0.14079092639207766 0.25375188437646584\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tp=0  # true positive\n",
        "tn=0  # true negative\n",
        "fp=0  # false poaitive\n",
        "fn=0  # false negative\n",
        "threshold = (min(errors) + max(errors))/2\n",
        "\n",
        "for i in range(len(errors)):\n",
        "  if errors[i] > threshold :\n",
        "    fn+=1\n",
        "  elif errors[i] <= threshold:\n",
        "    tp+=1 \n",
        "\n",
        "for i in range(len(errors2)):\n",
        "  if errors2[i] > threshold :\n",
        "    tn+=1\n",
        "  elif errors2[i] <= threshold:\n",
        "    fp+=1 \n",
        "\n",
        "incorrect_classifications = fp+fn\n",
        "print(incorrect_classifications)"
      ],
      "metadata": {
        "id": "JW03DY0OAT63",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "efc9514d-31b3-4f51-91d3-b7157087d18f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "8\n"
          ]
        }
      ]
    }
  ]
}
关于这个算法

Used the approach mentioned in the research paper by Matthew Turk and Alex Pentland, for face recognition using Eigenfaces. The algorithm was implemented using basic matrix algebra and numpy.
Link to the research paper: https://ieeexplore.ieee.org/document/139758
Google Colab Notebook: https://colab.research.google.com/drive/1InXv7hbjSBRkuLZgpf9SCFQcxu2m924B#scrollTo=Hj2uRB2ke4Vy

!pip install opencv-python
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (4.6.0.66)
Requirement already satisfied: numpy&amp;gt;=1.14.5 in /usr/local/lib/python3.7/dist-packages (from opencv-python) (1.21.6)
# taken from this StackOverflow answer: https://stackoverflow.com/a/39225039
import requests

def download_file_from_google_drive(id, destination):
    URL = "https://docs.google.com/uc?export=download"

    session = requests.Session()

    response = session.get(URL, params = { 'id' : id }, stream = True)
    token = get_confirm_token(response)

    if token:
        params = { 'id' : id, 'confirm' : token }
        response = session.get(URL, params = params, stream = True)

    save_response_content(response, destination)    

def get_confirm_token(response):
    for key, value in response.cookies.items():
        if key.startswith('download_warning'):
            return value

    return None

def save_response_content(response, destination):
    CHUNK_SIZE = 32768

    with open(destination, "wb") as f:
        for chunk in response.iter_content(CHUNK_SIZE):
            if chunk: # filter out keep-alive new chunks
                f.write(chunk)

The dataset used was the AT&T dataset, where 10 different images of 40 distinct subjects were given. The 10 images of the same person were taken under varying circumstances, like different lighting, facial expressions and facial accessories.

We took two images of each of the 40 people for testing. The model was trained on 8 images of the first 20 people. We did this so that we can calculate the accuracy for people both inside and outside our training set.

On running the code, train_small.zip, test1.zip and test2.zip will appear in the contents folder. These signify the following:

  1. train_small: training dataset, contains 8 images of 20 different people.
  2. test1.zip: testing dataset, contains 2 images all people from the training dataset.
  3. test2.zip: testing dataset, consisting of 2 images of 20 new people whose images weren't present in the training dataset.
# Downloading training dataset
file_id = '1Z9evWwUK4nTpARz67ZWraNe5sX2MNcFx'
destination = '/content/dataset.zip'
download_file_from_google_drive(file_id, destination)

!unzip -q dataset.zip
!rm -rf dataset.zip
# Downloading test1 dataset
test_file_id_1 = '1bIr_ikTxGuuZnJulykXeZz04pyb27S3f'
test_destination_1 = '/content/test1.zip'
download_file_from_google_drive(test_file_id_1, test_destination_1)

!unzip -q test1.zip
!rm -rf test1.zip
# Downloading test2 dataset
test_file_id_2 = '1Kj0QsxJ1m0n0UCPiaFskskUhM7fvxqS4'
test_destination_2 = '/content/test2.zip'
download_file_from_google_drive(test_file_id_2, test_destination_2)

!unzip -q test2.zip
!rm -rf test2.zip
# All images are supposed to be the same size, say, N*L
IMAGE_DIR = "/content/train_small"
# importing necessary libraries

import os
import numpy as np
import cv2
import matplotlib.pyplot as plt
import fnmatch
import re
def getClassFromName(fileName,lastSubdir=True):
        if lastSubdir:
            name = os.path.basename(os.path.dirname(fileName))
        else:
            name = os.path.basename(fileName)
        mat = re.match(".*(\d+).*", name)
        if mat != None:
            return int(mat.group(1))
        else:
            return name.__hash__()
image_names = []
image_dictionary = []

image_1D = []
for root, dirnames, filenames in os.walk(IMAGE_DIR):
    for filename in fnmatch.filter(filenames, "*.*"):
        image_names.append(os.path.join(root, filename))
for idx,image_name in enumerate(image_names):
    img = cv2.imread(image_name, cv2.IMREAD_GRAYSCALE).astype(np.float64)
    if idx == 0:
        imgShape = img.shape
        vector_matrix = np.zeros((imgShape[0]*imgShape[1], len(image_names)),dtype=np.float64)
    image_dictionary.append((image_name,img,getClassFromName(image_name)))
    image_1D.append(img.flatten())
# print(image_1D)
print(len(image_1D))
160

Training Methodology:

  1. We start by grayscaling the images and converting them into matrices of shape 112x92.
  2. Now each of these matrices was flattened and converted into a matrix of shape 10304x1. (Here 10304 comes from 112*92). All these vectors were stacked row wise into a single matrix (image_1D in our code).
  3. Now we normalize each row of this matrix by subtracting the row wise mean from each element of the corresponding row. This new matrix will be called AT, and the transpose of this matrix will be called A.
  4. Next we calculate the covariance matrix by doing ATxA.
  5. Next we calculate the eigenvalues and eigenvectors of the covariance matrix using the linalg.eig of numpy.
  6. Next step is dimensionality reduction. We choose a number K, and choose K eigen vectors corresponding to the K largest eigenvalues.
  7. Now we calculated the normalized training faces (face-average face) and represented each normalized face as a linear combination of the eigenvectors obtained in step 6. These w vectors were calculated using the np.linalg.lstsq function of numpy.
  8. After calculating the weights (w vectors), we stacked those vectors

Calculating the normalized image vectors.

# We normalize each row of this matrix by subtracting the row wise mean from each element of the corresponding row. 
# This new matrix will be called AT
mean = []
a_transpose_norm = []
for i in range(len(image_1D[0])):
  mean.append(0)

  for j in range(len(image_1D)):
    mean[i] += image_1D[j][i]/len(image_1D)
    # print(sum)

for i in range(len(image_1D)):
  a_transpose_norm.append([])
  for j in range(len(mean)):
    a_transpose_norm[i].append(image_1D[i][j] - mean[j])
    # print(a_transpose_norm)

# print(len(a_transpose_norm))
# The transpose of the matrix computed above will be called A.
a_norm = np.transpose(a_transpose_norm)  #A
len(a_norm)
10304

Calculating eigenvectors and eigenvalues of the covariance matrix formed by the image vectors.

# We calculate the covariance matrix by doing ATxA.
cov_matrix = np.cov(a_transpose_norm) # At*A
# print(cov_matrix)
len(cov_matrix[0])
160
eigen = np.linalg.eig(cov_matrix) # returns eigen values and then all eigen vectors
# for i in range(len(eigen)):
#   print(eigen[i])
v_eigenvalues=eigen[0]
v=np.transpose(eigen[1])
# print(v_eigenvalues)
# print(v)
# print(len(v), len(v[0]))
u_transpose = []
for i in range(len(v)):
  array = np.matmul(a_norm,v[i])
  u_transpose.append(array)
u=np.transpose(u_transpose)
# print(len(u),len(u[0]))
print(len(u), len(u[0]))
10304 160
eigen_values = eigen[0]
eigen_vectors=eigen[1]
# print(eigen_values)
eigen_d = {}
for i in range(len(eigen_values)):
  eigen_d[eigen_values[i]]=i
# eigen_d

Selecting the K eigenvectors of covariance matrix corresponding to the K largest eigenvalues.

k=12
# sorting the dictionary of eigenvalues to get the corresponding eigenvectors.
from collections import OrderedDict
dict1 = OrderedDict(sorted(eigen_d.items(),reverse=True))
dict2=dict(dict1)
print(dict2)
{43219.953977553596: 0, 18749.895990890815: 1, 17942.155464146246: 2, 12061.802455045403: 3, 10489.25912953686: 4, 8066.724722559026: 5, 7297.85172164008: 6, 6261.016588366359: 7, 5873.753178029104: 8, 4420.5004066534: 9, 3826.304473465676: 10, 3579.8886501814827: 11, 3112.701941552233: 12, 2932.3449009364517: 13, 2747.3196034473535: 14, 2487.396345846331: 15, 2411.0446487988524: 16, 2252.6641238208167: 17, 2074.7096367875374: 18, 1989.9475765463246: 19, 1928.8795510110008: 20, 1773.305425328178: 21, 1676.8247434736688: 22, 1640.8845693566923: 23, 1586.0134088610828: 24, 1384.3119343572707: 25, 1360.5249845839646: 26, 1272.8354997100732: 27, 1171.4911399813118: 28, 1150.5295704016391: 29, 1117.2277311946657: 30, 1066.7345849297926: 31, 1027.8242127649535: 32, 1000.5604997800493: 33, 957.4881339639342: 34, 932.1908536264845: 35, 890.6505933876211: 36, 867.9216091629972: 38, 833.6071838643115: 39, 806.8325487486294: 40, 774.5620675914377: 41, 758.6272156532845: 42, 738.4342113595159: 43, 714.5399164439951: 44, 682.7055539009281: 46, 680.9252271100078: 47, 673.9283018815898: 48, 658.4301569913085: 45, 625.0816864277112: 49, 617.5582835272636: 50, 606.4179117332367: 51, 574.3310372756353: 53, 569.9325407493129: 52, 556.968211979823: 54, 548.371195855361: 55, 541.394394333996: 56, 517.6264019518915: 58, 516.5821198500923: 57, 500.04350432768587: 59, 482.81038227024146: 60, 474.40612112126905: 61, 472.91907873668464: 62, 463.37362069900644: 63, 448.87411947393264: 64, 445.1195525159666: 65, 433.8822394567646: 66, 424.9545193027636: 67, 414.34625398368985: 73, 410.44103052260715: 72, 399.7720057166255: 74, 392.1543734446897: 75, 387.79362525258114: 76, 374.2368664887361: 79, 371.49945348490684: 80, 366.1104550707202: 81, 362.76582599959437: 83, 362.07916777129213: 82, 352.7149467318006: 86, 347.6629266571733: 87, 344.4517149718263: 88, 338.56891140470464: 89, 326.7105220744234: 94, 326.25054239097585: 95, 317.973905297458: 99, 315.61948544607054: 100, 312.15439105645754: 109, 308.5046455356127: 101, 302.55416730618424: 110, 298.5400400481408: 111, 292.27487160513783: 112, 288.8823139316889: 113, 285.0435271976845: 114, 282.9772519873982: 115, 277.64467614646475: 117, 273.7020381676069: 118, 269.5357634357952: 142, 265.9471151508216: 119, 261.3862164259361: 120, 259.8671420930868: 126, 257.6130828977115: 125, 254.21906797290566: 131, 250.616479699577: 128, 246.06438730855305: 127, 240.00699924404051: 129, 234.8180913874552: 130, 232.7549425732958: 141, 230.7956380602637: 143, 226.5311551599993: 159, 223.75397178988626: 153, 221.54950660799236: 152, 219.43463583127505: 158, 217.41411147378702: 151, 215.48480958242658: 150, 211.49682062225486: 154, 209.55479232153124: 157, 208.1694532219256: 156, 206.43451832745535: 155, 200.65013822053376: 144, 199.90465610231152: 145, 197.0978066449791: 140, 195.18560080202585: 147, 190.91520321768897: 146, 189.6685050111701: 137, 185.6900961024561: 139, 182.2508248568398: 136, 178.73701239142918: 135, 174.5908773381799: 132, 169.827660924428: 124, 166.7766873707503: 134, 165.7343487334624: 138, 163.50086445520705: 133, 161.8161444605663: 149, 159.93509949384642: 123, 157.84439541824133: 121, 155.2947155213594: 148, 154.80023084350475: 122, 150.43467043710345: 116, 147.1590447262029: 108, 140.48035960506212: 107, 138.73007592494284: 106, 137.8886194586964: 105, 133.96609468111802: 104, 133.32671443969662: 103, 131.35871093197667: 102, 126.39832659543461: 98, 123.8572162371065: 97, 120.39979904790052: 96, 119.33111585528107: 93, 117.61534130912757: 92, 115.93856715938144: 91, 109.54104484025125: 90, 108.20582883113228: 85, 101.43665329843098: 84, 89.47901931450252: 78, 84.06012945411771: 77, 70.50578026422139: 71, 65.59787544247587: 70, 62.77453678940503: 69, 59.32778617838623: 68, -5.107739735450283e-13: 37}
# indexes of of k maximum eigenvalues
index_list=[]
for e in dict2:
  if(len(index_list)&gt;=k):
    break
  index_list.append(dict2[e])
print(index_list)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
# eigenvectors of k maximum eigenvalues
u_k=[]
for i in index_list:
  u_k.append(u_transpose[i])
print(u_k)
[array([-250.34987268, -246.96739775, -251.03150872, ...,   62.66394197,
         42.95102603,   -7.43283506]), array([-293.03400587, -296.61765524, -294.39034777, ...,  -50.55568765,
        -45.94985846,  -50.66399445]), array([ 69.73691919,  64.22732671,  68.583571  , ..., -41.61421501,
       -40.95085605, -38.69027747]), array([ 15.24047245,  19.31637724,  22.9986019 , ..., -81.3522821 ,
       -68.21885398, -73.1093675 ]), array([   7.04373461,    4.56640216,    2.24472334, ..., -102.02376868,
        -80.93066914,  -59.14922928]), array([-64.63035609, -68.56599373, -60.92922784, ...,  97.30812891,
        83.50398642,  56.29972771]), array([-73.39842816, -75.85858873, -75.10925541, ..., -21.30720511,
       -25.49241544,   5.10502217]), array([  76.33460672,   78.27079323,   83.86525799, ..., -100.27234286,
        -77.988847  ,  -61.0207666 ]), array([-103.25654954, -100.23979122,  -96.30983044, ...,  -37.3388256 ,
        -49.91948021,  -28.46092446]), array([-62.26684061, -59.45034204, -62.54270953, ..., 151.8902004 ,
       121.29818377, 111.59794073]), array([ -92.97767444,  -95.5290902 ,  -91.18621931, ..., -113.1381992 ,
        -91.31555489,  -88.30228713]), array([-74.61218527, -70.83391408, -71.92315934, ...,  52.7331185 ,
        48.02889301,  55.92254778])]

Plotting the mean vector.

fig,axarr = plt.subplots()
axarr.set_title(" plot_mean_vector")
avg_image = np.reshape(mean, (imgShape))
axarr.imshow(avg_image, cmap=plt.cm.gray)
&lt;matplotlib.image.AxesImage at 0x7f3182920b10&gt;

Plotting the k eigenfaces.

for i in range(k):
  fig,axarr = plt.subplots()
  axarr.set_title(" plot_eigen_face_"+str(i+1))
  avg_image = np.reshape(u_k[i], (imgShape))
  axarr.imshow(avg_image, cmap=plt.cm.gray)