lab9.ipynb

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  "metadata": {
    "colab": {
      "name": "lab9.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "mount_file_id": "1X3JiL_7CXjZ3lRMc71PBY05Dtl54nmnM",
      "authorship_tag": "ABX9TyMXqO7iS+koOFHUkH5KFoYQ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hkbu-kennycheng/comp3925/blob/main/lab9.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Lab9: Image Analysis"
      ],
      "metadata": {
        "id": "XcJ9wTgmVmj5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install requests opencv-python"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p2AY9PdMRVvc",
        "outputId": "f0d4a296-f3af-4788-cd5e-d97e1823482a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (2.23.0)\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (4.1.2.30)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests) (2021.10.8)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests) (1.24.3)\n",
            "Requirement already satisfied: numpy>=1.14.5 in /usr/local/lib/python3.7/dist-packages (from opencv-python) (1.21.5)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "GOMpjRiuRQQ2"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        ""
      ],
      "metadata": {
        "id": "r1OQWlZhA-Mt"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T18CwD_rURUe"
      },
      "source": [
        "## Loading dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eJXrpdqIUSgE",
        "outputId": "d58ea410-0944-482d-fa02-9cc17ee40dad"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\r100 4228k  100 4228k    0     0  23.4M      0 --:--:-- --:--:-- --:--:-- 23.4M\n"
          ]
        }
      ],
      "source": [
        "!curl https://gist.githubusercontent.com/hkbu-kennycheng/b95757c385ac5e49a1abb1434a966f6c/raw/5110cce1df181d67411c949c304655572740d0b9/pnk.csv > pnk.csv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0OIs0TPLUv7W",
        "outputId": "711cbc7f-e2f4-4e0e-bc50-48ff5e4e33fb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                name      id  \\\n",
              "0                   Alkaline Water 9.0 (random Pick)  499585   \n",
              "1     Alkaline Water 9.0 (case) (420ml X 24 Bottles)  378829   \n",
              "2              L Type Interdental Brush 0.6mm - 6pcs  805629   \n",
              "3                L Type Interdental Brush 0.8mm 6pcs  805630   \n",
              "4                I Type Interdental Brush 0.7mm 5pcs  805627   \n",
              "...                                              ...     ...   \n",
              "6722                            Kitchen  Towel 9inch  365593   \n",
              "6723                       Chauzhou Style Fish Balls   51761   \n",
              "6724                              Alkaline Ion Water  483353   \n",
              "6725                              Mushroom Pork Ball   55251   \n",
              "6726                                Cuttle Fish Ball   51759   \n",
              "\n",
              "                                                    url  \\\n",
              "0     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "1     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "2     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "3     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "4     https://www.parknshop.com/en/i-type-interdenta...   \n",
              "...                                                 ...   \n",
              "6722  https://www.parknshop.com/en/kitchen-towel-9in...   \n",
              "6723  https://www.parknshop.com/en/chauzhou-style-fi...   \n",
              "6724  https://www.parknshop.com/en/alkaline-ion-wate...   \n",
              "6725  https://www.parknshop.com/en/mushroom-pork-bal...   \n",
              "6726  https://www.parknshop.com/en/cuttle-fish-ball/...   \n",
              "\n",
              "                                                    pic  price  \\\n",
              "0     https://www.parknshop.com/medias/sys_master/fr...    9.0   \n",
              "1     https://www.parknshop.com/medias/sys_master/fr...  168.0   \n",
              "2     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "3     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "4     https://www.parknshop.com/medias/sys_master/fr...   10.0   \n",
              "...                                                 ...    ...   \n",
              "6722  https://www.parknshop.com/medias/sys_master/fr...   25.9   \n",
              "6723  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "6724  https://www.parknshop.com/medias/sys_master/fr...   19.9   \n",
              "6725  https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "6726  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "\n",
              "                specialoffer                brand  \\\n",
              "0                        NaN              WATSONS   \n",
              "1                        NaN              WATSONS   \n",
              "2               $20.8 / 2pcs              WATSONS   \n",
              "3               $20.8 / 2pcs              WATSONS   \n",
              "4               $15.0 / 2pcs              WATSONS   \n",
              "...                      ...                  ...   \n",
              "6722  MONEYBACK MEMBER OFFER             BEST BUY   \n",
              "6723  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6724  MONEYBACK MEMBER OFFER                KIRIN   \n",
              "6725  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6726  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "\n",
              "                          category  variant variantname  ...  organic  \\\n",
              "0                            Water   499585       420ML  ...    False   \n",
              "1              Water,Bottled Water   378829    24X420ML  ...    False   \n",
              "2     Dental Accessories & Denture   805629          6S  ...    False   \n",
              "3     Dental Accessories & Denture   805630          6S  ...    False   \n",
              "4     Dental Accessories & Denture   805627          5S  ...    False   \n",
              "...                            ...      ...         ...  ...      ...   \n",
              "6722                           NaN   365593          6S  ...    False   \n",
              "6723                 Seafood Balls    51761    170G/PKT  ...    False   \n",
              "6724                         Water   483353          2L  ...    False   \n",
              "6725                    Meat Balls    55251        170G  ...    False   \n",
              "6726                 Seafood Balls    51759    170G/PKT  ...    False   \n",
              "\n",
              "      eshoponly  healthyfat  crustacean  \\\n",
              "0         False       False       False   \n",
              "1         False       False       False   \n",
              "2         False       False       False   \n",
              "3         False       False       False   \n",
              "4         False       False       False   \n",
              "...         ...         ...         ...   \n",
              "6722      False       False       False   \n",
              "6723      False       False       False   \n",
              "6724      False       False       False   \n",
              "6725      False       False       False   \n",
              "6726      False       False       False   \n",
              "\n",
              "                                        Product Details     Origin  \\\n",
              "0     - Smart way to hydrate your body- Helps to neu...  Hong Kong   \n",
              "1     - Helps neutralize acidity-Help the body detox...  Hong Kong   \n",
              "2     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "3     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "4     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "...                                                 ...        ...   \n",
              "6722                                                NaN        NaN   \n",
              "6723                                                NaN        NaN   \n",
              "6724                                                NaN        NaN   \n",
              "6725                                                NaN        NaN   \n",
              "6726                                                NaN        NaN   \n",
              "\n",
              "                                       Product Warnings  \\\n",
              "0     This product contains minerals and is electrol...   \n",
              "1     Keep in a cool dry place away from direct sunl...   \n",
              "2     Do not force the interdental brush between tee...   \n",
              "3     Do not force the interdental brush between tee...   \n",
              "4     Do not force the interdental brush between tee...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                                          Product Usage  \\\n",
              "0                        Consume shortly after opening.   \n",
              "1                                                 drink   \n",
              "2     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "3     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "4     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                                      Storage Condition  \\\n",
              "0     Keep in a cool dry place away from direct sunl...   \n",
              "1     Keep in a cool dry place away from direct sunl...   \n",
              "2     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "3     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "4     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                           Ingredients  \n",
              "0     Water, Ocean Mineral Concentrate  \n",
              "1     Water, Ocean Mineral Concentrate  \n",
              "2                                  NaN  \n",
              "3                                  NaN  \n",
              "4                                  NaN  \n",
              "...                                ...  \n",
              "6722                               NaN  \n",
              "6723                               NaN  \n",
              "6724                               NaN  \n",
              "6725                               NaN  \n",
              "6726                               NaN  \n",
              "\n",
              "[6727 rows x 22 columns]"
            ],
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>url</th>\n",
              "      <th>pic</th>\n",
              "      <th>price</th>\n",
              "      <th>specialoffer</th>\n",
              "      <th>brand</th>\n",
              "      <th>category</th>\n",
              "      <th>variant</th>\n",
              "      <th>variantname</th>\n",
              "      <th>...</th>\n",
              "      <th>organic</th>\n",
              "      <th>eshoponly</th>\n",
              "      <th>healthyfat</th>\n",
              "      <th>crustacean</th>\n",
              "      <th>Product Details</th>\n",
              "      <th>Origin</th>\n",
              "      <th>Product Warnings</th>\n",
              "      <th>Product Usage</th>\n",
              "      <th>Storage Condition</th>\n",
              "      <th>Ingredients</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alkaline Water 9.0 (random Pick)</td>\n",
              "      <td>499585</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water</td>\n",
              "      <td>499585</td>\n",
              "      <td>420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>- Smart way to hydrate your body- Helps to neu...</td>\n",
              "      <td>Hong Kong</td>\n",
              "      <td>This product contains minerals and is electrol...</td>\n",
              "      <td>Consume shortly after opening.</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>Water, Ocean Mineral Concentrate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alkaline Water 9.0 (case) (420ml X 24 Bottles)</td>\n",
              "      <td>378829</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>168.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water,Bottled Water</td>\n",
              "      <td>378829</td>\n",
              "      <td>24X420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>- Helps neutralize acidity-Help the body detox...</td>\n",
              "      <td>Hong Kong</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>drink</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>Water, Ocean Mineral Concentrate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>L Type Interdental Brush 0.6mm - 6pcs</td>\n",
              "      <td>805629</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805629</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>L Type Interdental Brush 0.8mm 6pcs</td>\n",
              "      <td>805630</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805630</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>I Type Interdental Brush 0.7mm 5pcs</td>\n",
              "      <td>805627</td>\n",
              "      <td>https://www.parknshop.com/en/i-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>10.0</td>\n",
              "      <td>$15.0 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805627</td>\n",
              "      <td>5S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6722</th>\n",
              "      <td>Kitchen  Towel 9inch</td>\n",
              "      <td>365593</td>\n",
              "      <td>https://www.parknshop.com/en/kitchen-towel-9in...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>25.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>BEST BUY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>365593</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6723</th>\n",
              "      <td>Chauzhou Style Fish Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>https://www.parknshop.com/en/chauzhou-style-fi...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6724</th>\n",
              "      <td>Alkaline Ion Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-ion-wate...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>19.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>KIRIN</td>\n",
              "      <td>Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>2L</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6725</th>\n",
              "      <td>Mushroom Pork Ball</td>\n",
              "      <td>55251</td>\n",
              "      <td>https://www.parknshop.com/en/mushroom-pork-bal...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Meat Balls</td>\n",
              "      <td>55251</td>\n",
              "      <td>170G</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6726</th>\n",
              "      <td>Cuttle Fish Ball</td>\n",
              "      <td>51759</td>\n",
              "      <td>https://www.parknshop.com/en/cuttle-fish-ball/...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51759</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6727 rows × 22 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-831f3e1a-0556-4b7a-b9ac-d8df726ebbff')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-831f3e1a-0556-4b7a-b9ac-d8df726ebbff button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-831f3e1a-0556-4b7a-b9ac-d8df726ebbff');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "pnkdf = pd.read_csv('pnk.csv', index_col=0)\n",
        "pnkdf"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Fetching image data"
      ],
      "metadata": {
        "id": "GS6VGopKRK8H"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Download image with `requests`"
      ],
      "metadata": {
        "id": "1FFq-XPF63Gg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's download the image data by passing in the URL to `requests.get`."
      ],
      "metadata": {
        "id": "PPJWIgBkddZP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "import shutil\n",
        "import tempfile\n",
        "import cv2\n",
        "\n",
        "img_url = 'https://www.parknshop.com/medias/sys_master/front/prd/9444607229982.jpg'\n",
        "\n",
        "response = requests.get(img_url, headers={'User-Agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36'}, stream=True)\n",
        "if response.status_code == 200:\n",
        "  response.raw.decode_content = True\n",
        "  rawdata = np.frombuffer(response.raw.read(), dtype='uint8')\n",
        "  img = cv2.imdecode(rawdata, cv2.IMREAD_COLOR)"
      ],
      "metadata": {
        "id": "8jBAL92P7Cep"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "In Google Colab, we will need to use `cv2_imshow` from `google.colab.patches` in order to display the image."
      ],
      "metadata": {
        "id": "99eBxIYwdWPv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab.patches import cv2_imshow\n",
        "\n",
        "cv2_imshow(img)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "BddjGkmdDHVM",
        "outputId": "b68424c8-b098-4ab7-a237-9f41061c22e8"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=300x300 at 0x7F1AF9CBED90>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Actuallt it's a 3d array consists of red, grenn and blue value for each pixel ranging from 0 to 255 in each value."
      ],
      "metadata": {
        "id": "3Kf7Ool4c6I-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OdN4uYE8dvGX",
        "outputId": "4775c747-a98f-416e-cdd4-f55b71d38866"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(300, 300, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "img"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MaqXSWKPFjMb",
        "outputId": "2dfdaea0-658a-479f-9734-d048684c6a6d"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]],\n",
              "\n",
              "       [[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]],\n",
              "\n",
              "       [[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]],\n",
              "\n",
              "       [[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]],\n",
              "\n",
              "       [[255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        ...,\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255],\n",
              "        [255, 255, 255]]], dtype=uint8)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fetch image function"
      ],
      "metadata": {
        "id": "7avXeospYTA_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def fetchImage(url):\n",
        "  response = requests.get(url, headers={'User-Agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36'}, stream=True)\n",
        "  if response.status_code == 200:\n",
        "    response.raw.decode_content = True\n",
        "    rawdata = np.frombuffer(response.raw.read(), dtype='uint8')\n",
        "    return cv2.imdecode(rawdata, cv2.IMREAD_COLOR)\n",
        "  return []\n",
        "    "
      ],
      "metadata": {
        "id": "OohtCxyfYW6W"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Fetch all images in data frame"
      ],
      "metadata": {
        "id": "IvwoNuHrFG5H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "picdf = pd.DataFrame(pd.Series(pnkdf['pic'].unique(), name='pic'))\n",
        "picdf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "k3Ehjo7kBD0W",
        "outputId": "892107e8-401b-4606-b315-85e23c892ee4"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    pic\n",
              "0     https://www.parknshop.com/medias/sys_master/fr...\n",
              "1     https://www.parknshop.com/medias/sys_master/fr...\n",
              "2     https://www.parknshop.com/medias/sys_master/fr...\n",
              "3     https://www.parknshop.com/medias/sys_master/fr...\n",
              "4     https://www.parknshop.com/medias/sys_master/fr...\n",
              "...                                                 ...\n",
              "6722  https://www.parknshop.com/medias/sys_master/fr...\n",
              "6723  https://www.parknshop.com/medias/sys_master/fr...\n",
              "6724  https://www.parknshop.com/medias/sys_master/fr...\n",
              "6725  https://www.parknshop.com/medias/sys_master/fr...\n",
              "6726  https://www.parknshop.com/medias/sys_master/fr...\n",
              "\n",
              "[6727 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c2978510-81ef-4401-841d-8e79bebba909\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pic</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6722</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6723</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6724</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6725</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6726</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6727 rows × 1 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c2978510-81ef-4401-841d-8e79bebba909')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c2978510-81ef-4401-841d-8e79bebba909 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c2978510-81ef-4401-841d-8e79bebba909');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "picdf['picdata'] = picdf['pic'].apply(fetchImage)"
      ],
      "metadata": {
        "id": "tkoCrRQzBo8R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "picdf.to_pickle('picdf.pickle')"
      ],
      "metadata": {
        "id": "bN_vMLTKCxLP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "You may use my version of image data to reduce the loading time."
      ],
      "metadata": {
        "id": "EFygHCR7eTI3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!curl -L https://www.comp.hkbu.edu.hk/~kennycheng/cs7113-8000/picdf.pickle > picdf.pickle"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IVX_gu74E9eI",
        "outputId": "7dcbc7aa-3e91-4e61-dab0-0b1b9033d329"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100 1712M  100 1712M    0     0  11.1M      0  0:02:33  0:02:33 --:--:-- 11.0M\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!sha256sum picdf.pickle"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AD8I2DYwLI4R",
        "outputId": "fc255061-2d3b-4f6f-cb36-8ac4da09ce43"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "46a024ac257ebaff56b3e090d0551e341d54dc9a3726bca904b5288fb1a4370b  picdf.pickle\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pickle\n",
        "\n",
        "picdf = pd.DataFrame()\n",
        "\n",
        "with open('picdf.pickle', 'r+b') as f:\n",
        "  picdf = pickle.load(f)\n",
        "\n",
        "picdf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "vQoib9AfDBlv",
        "outputId": "a3442ec6-a3c9-4f39-e322-39be3b3e1007"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    pic  \\\n",
              "0     https://www.parknshop.com/medias/sys_master/fr...   \n",
              "1     https://www.parknshop.com/medias/sys_master/fr...   \n",
              "2     https://www.parknshop.com/medias/sys_master/fr...   \n",
              "3     https://www.parknshop.com/medias/sys_master/fr...   \n",
              "4     https://www.parknshop.com/medias/sys_master/fr...   \n",
              "...                                                 ...   \n",
              "6722  https://www.parknshop.com/medias/sys_master/fr...   \n",
              "6723  https://www.parknshop.com/medias/sys_master/fr...   \n",
              "6724  https://www.parknshop.com/medias/sys_master/fr...   \n",
              "6725  https://www.parknshop.com/medias/sys_master/fr...   \n",
              "6726  https://www.parknshop.com/medias/sys_master/fr...   \n",
              "\n",
              "                                                picdata  \n",
              "0     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "1     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "2     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "3     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "4     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "...                                                 ...  \n",
              "6722  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6723  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6724  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6725  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6726  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "\n",
              "[6727 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fb110fb3-edba-42ef-8c8a-c7904f8089c7\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pic</th>\n",
              "      <th>picdata</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6722</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6723</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6724</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6725</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6726</th>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6727 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fb110fb3-edba-42ef-8c8a-c7904f8089c7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fb110fb3-edba-42ef-8c8a-c7904f8089c7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fb110fb3-edba-42ef-8c8a-c7904f8089c7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Merge `pnkdf` and `picdf` as `df`"
      ],
      "metadata": {
        "id": "K7f_Ex9yN_zy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.merge(pnkdf, picdf, on='pic')"
      ],
      "metadata": {
        "id": "iChnbRPuDi23"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "JV2zJZc3NpXi",
        "outputId": "aa42d717-25d9-4208-e840-ef8c415ddae8"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                name      id  \\\n",
              "0                   Alkaline Water 9.0 (random Pick)  499585   \n",
              "1     Alkaline Water 9.0 (case) (420ml X 24 Bottles)  378829   \n",
              "2              L Type Interdental Brush 0.6mm - 6pcs  805629   \n",
              "3                L Type Interdental Brush 0.8mm 6pcs  805630   \n",
              "4                I Type Interdental Brush 0.7mm 5pcs  805627   \n",
              "...                                              ...     ...   \n",
              "6722                            Kitchen  Towel 9inch  365593   \n",
              "6723                       Chauzhou Style Fish Balls   51761   \n",
              "6724                              Alkaline Ion Water  483353   \n",
              "6725                              Mushroom Pork Ball   55251   \n",
              "6726                                Cuttle Fish Ball   51759   \n",
              "\n",
              "                                                    url  \\\n",
              "0     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "1     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "2     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "3     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "4     https://www.parknshop.com/en/i-type-interdenta...   \n",
              "...                                                 ...   \n",
              "6722  https://www.parknshop.com/en/kitchen-towel-9in...   \n",
              "6723  https://www.parknshop.com/en/chauzhou-style-fi...   \n",
              "6724  https://www.parknshop.com/en/alkaline-ion-wate...   \n",
              "6725  https://www.parknshop.com/en/mushroom-pork-bal...   \n",
              "6726  https://www.parknshop.com/en/cuttle-fish-ball/...   \n",
              "\n",
              "                                                    pic  price  \\\n",
              "0     https://www.parknshop.com/medias/sys_master/fr...    9.0   \n",
              "1     https://www.parknshop.com/medias/sys_master/fr...  168.0   \n",
              "2     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "3     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "4     https://www.parknshop.com/medias/sys_master/fr...   10.0   \n",
              "...                                                 ...    ...   \n",
              "6722  https://www.parknshop.com/medias/sys_master/fr...   25.9   \n",
              "6723  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "6724  https://www.parknshop.com/medias/sys_master/fr...   19.9   \n",
              "6725  https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "6726  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "\n",
              "                specialoffer                brand  \\\n",
              "0                        NaN              WATSONS   \n",
              "1                        NaN              WATSONS   \n",
              "2               $20.8 / 2pcs              WATSONS   \n",
              "3               $20.8 / 2pcs              WATSONS   \n",
              "4               $15.0 / 2pcs              WATSONS   \n",
              "...                      ...                  ...   \n",
              "6722  MONEYBACK MEMBER OFFER             BEST BUY   \n",
              "6723  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6724  MONEYBACK MEMBER OFFER                KIRIN   \n",
              "6725  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6726  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "\n",
              "                          category  variant variantname  ...  eshoponly  \\\n",
              "0                            Water   499585       420ML  ...      False   \n",
              "1              Water,Bottled Water   378829    24X420ML  ...      False   \n",
              "2     Dental Accessories & Denture   805629          6S  ...      False   \n",
              "3     Dental Accessories & Denture   805630          6S  ...      False   \n",
              "4     Dental Accessories & Denture   805627          5S  ...      False   \n",
              "...                            ...      ...         ...  ...        ...   \n",
              "6722                           NaN   365593          6S  ...      False   \n",
              "6723                 Seafood Balls    51761    170G/PKT  ...      False   \n",
              "6724                         Water   483353          2L  ...      False   \n",
              "6725                    Meat Balls    55251        170G  ...      False   \n",
              "6726                 Seafood Balls    51759    170G/PKT  ...      False   \n",
              "\n",
              "      healthyfat  crustacean  \\\n",
              "0          False       False   \n",
              "1          False       False   \n",
              "2          False       False   \n",
              "3          False       False   \n",
              "4          False       False   \n",
              "...          ...         ...   \n",
              "6722       False       False   \n",
              "6723       False       False   \n",
              "6724       False       False   \n",
              "6725       False       False   \n",
              "6726       False       False   \n",
              "\n",
              "                                        Product Details     Origin  \\\n",
              "0     - Smart way to hydrate your body- Helps to neu...  Hong Kong   \n",
              "1     - Helps neutralize acidity-Help the body detox...  Hong Kong   \n",
              "2     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "3     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "4     WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...      China   \n",
              "...                                                 ...        ...   \n",
              "6722                                                NaN        NaN   \n",
              "6723                                                NaN        NaN   \n",
              "6724                                                NaN        NaN   \n",
              "6725                                                NaN        NaN   \n",
              "6726                                                NaN        NaN   \n",
              "\n",
              "                                       Product Warnings  \\\n",
              "0     This product contains minerals and is electrol...   \n",
              "1     Keep in a cool dry place away from direct sunl...   \n",
              "2     Do not force the interdental brush between tee...   \n",
              "3     Do not force the interdental brush between tee...   \n",
              "4     Do not force the interdental brush between tee...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                                          Product Usage  \\\n",
              "0                        Consume shortly after opening.   \n",
              "1                                                 drink   \n",
              "2     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "3     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "4     1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                                      Storage Condition  \\\n",
              "0     Keep in a cool dry place away from direct sunl...   \n",
              "1     Keep in a cool dry place away from direct sunl...   \n",
              "2     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "3     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "4     STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...   \n",
              "...                                                 ...   \n",
              "6722                                                NaN   \n",
              "6723                                                NaN   \n",
              "6724                                                NaN   \n",
              "6725                                                NaN   \n",
              "6726                                                NaN   \n",
              "\n",
              "                           Ingredients  \\\n",
              "0     Water, Ocean Mineral Concentrate   \n",
              "1     Water, Ocean Mineral Concentrate   \n",
              "2                                  NaN   \n",
              "3                                  NaN   \n",
              "4                                  NaN   \n",
              "...                                ...   \n",
              "6722                               NaN   \n",
              "6723                               NaN   \n",
              "6724                               NaN   \n",
              "6725                               NaN   \n",
              "6726                               NaN   \n",
              "\n",
              "                                                picdata  \n",
              "0     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "1     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "2     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "3     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "4     [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "...                                                 ...  \n",
              "6722  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6723  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6724  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6725  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "6726  [[[255, 255, 255], [255, 255, 255], [255, 255,...  \n",
              "\n",
              "[6727 rows x 23 columns]"
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>url</th>\n",
              "      <th>pic</th>\n",
              "      <th>price</th>\n",
              "      <th>specialoffer</th>\n",
              "      <th>brand</th>\n",
              "      <th>category</th>\n",
              "      <th>variant</th>\n",
              "      <th>variantname</th>\n",
              "      <th>...</th>\n",
              "      <th>eshoponly</th>\n",
              "      <th>healthyfat</th>\n",
              "      <th>crustacean</th>\n",
              "      <th>Product Details</th>\n",
              "      <th>Origin</th>\n",
              "      <th>Product Warnings</th>\n",
              "      <th>Product Usage</th>\n",
              "      <th>Storage Condition</th>\n",
              "      <th>Ingredients</th>\n",
              "      <th>picdata</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alkaline Water 9.0 (random Pick)</td>\n",
              "      <td>499585</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water</td>\n",
              "      <td>499585</td>\n",
              "      <td>420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>- Smart way to hydrate your body- Helps to neu...</td>\n",
              "      <td>Hong Kong</td>\n",
              "      <td>This product contains minerals and is electrol...</td>\n",
              "      <td>Consume shortly after opening.</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>Water, Ocean Mineral Concentrate</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alkaline Water 9.0 (case) (420ml X 24 Bottles)</td>\n",
              "      <td>378829</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>168.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water,Bottled Water</td>\n",
              "      <td>378829</td>\n",
              "      <td>24X420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>- Helps neutralize acidity-Help the body detox...</td>\n",
              "      <td>Hong Kong</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>drink</td>\n",
              "      <td>Keep in a cool dry place away from direct sunl...</td>\n",
              "      <td>Water, Ocean Mineral Concentrate</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>L Type Interdental Brush 0.6mm - 6pcs</td>\n",
              "      <td>805629</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805629</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>L Type Interdental Brush 0.8mm 6pcs</td>\n",
              "      <td>805630</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805630</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>I Type Interdental Brush 0.7mm 5pcs</td>\n",
              "      <td>805627</td>\n",
              "      <td>https://www.parknshop.com/en/i-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>10.0</td>\n",
              "      <td>$15.0 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805627</td>\n",
              "      <td>5S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>WATSONS ORAL CARE RANGE IS SPECIALLY DESIGNED ...</td>\n",
              "      <td>China</td>\n",
              "      <td>Do not force the interdental brush between tee...</td>\n",
              "      <td>1. PUT THE INTERDENTAL BRUSH BETWEEN THE TEETH...</td>\n",
              "      <td>STORE IN A COOL, DRY PLACE AWAY FROM DIRECT SU...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6722</th>\n",
              "      <td>Kitchen  Towel 9inch</td>\n",
              "      <td>365593</td>\n",
              "      <td>https://www.parknshop.com/en/kitchen-towel-9in...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>25.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>BEST BUY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>365593</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6723</th>\n",
              "      <td>Chauzhou Style Fish Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>https://www.parknshop.com/en/chauzhou-style-fi...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6724</th>\n",
              "      <td>Alkaline Ion Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-ion-wate...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>19.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>KIRIN</td>\n",
              "      <td>Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>2L</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6725</th>\n",
              "      <td>Mushroom Pork Ball</td>\n",
              "      <td>55251</td>\n",
              "      <td>https://www.parknshop.com/en/mushroom-pork-bal...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Meat Balls</td>\n",
              "      <td>55251</td>\n",
              "      <td>170G</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6726</th>\n",
              "      <td>Cuttle Fish Ball</td>\n",
              "      <td>51759</td>\n",
              "      <td>https://www.parknshop.com/en/cuttle-fish-ball/...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51759</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[[[255, 255, 255], [255, 255, 255], [255, 255,...</td>\n",
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              "  </tbody>\n",
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              "<p>6727 rows × 23 columns</p>\n",
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              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c567d9ff-0c76-4f6f-a59e-2b4db20295d5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c567d9ff-0c76-4f6f-a59e-2b4db20295d5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Color channel and shape"
      ],
      "metadata": {
        "id": "f_DK0uLwJMIj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Shape"
      ],
      "metadata": {
        "id": "ZndbMHpWKmWM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are 3 channels in image for different color (blue, green, red). Thus the data shape for an image would like this."
      ],
      "metadata": {
        "id": "lUo1SfFYJwxT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jcKfVgIuDDtC",
        "outputId": "29b20e67-1de1-484a-e5af-ac109b507f5c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(300, 300, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "img[:,:,0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SBEDGFCdKFX0",
        "outputId": "08d972b0-394f-44ee-c27c-6eb9a8701bbd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[255, 255, 255, ..., 255, 255, 255],\n",
              "       [255, 255, 255, ..., 255, 255, 255],\n",
              "       [255, 255, 255, ..., 255, 255, 255],\n",
              "       ...,\n",
              "       [255, 255, 255, ..., 255, 255, 255],\n",
              "       [255, 255, 255, ..., 255, 255, 255],\n",
              "       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "img[:,:,0].reshape(90000) # flatten"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "92PW-g0OW_mG",
        "outputId": "0d6e57ee-6edb-45a5-a368-f205e6444a6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([255, 255, 255, ..., 255, 255, 255], dtype=uint8)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Blue"
      ],
      "metadata": {
        "id": "3ftxb0lGKhfU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cv2_imshow(img[:,:,0]) # showing only blue channel values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "JcRcieNtKL9T",
        "outputId": "f87cbd9a-abc0-43b9-8a0d-b4c1ffeb11d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=300x300 at 0x7F6530A469D0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Green"
      ],
      "metadata": {
        "id": "lAimFOUEKin8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cv2_imshow(img[:,:,1]) # showing only green channel values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "s5-7wZvoKXil",
        "outputId": "20dd8869-f786-42d0-9945-b72efd5f9ff2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=300x300 at 0x7F6530A4E250>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Red"
      ],
      "metadata": {
        "id": "U9rQU-y3KkKE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cv2_imshow(img[:,:,2]) # showing only red channel values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "aFvYWhvPKY18",
        "outputId": "4b96b349-42bf-4b66-e851-1d5be93c4e1e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=300x300 at 0x7F6530A4EA90>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Color space"
      ],
      "metadata": {
        "id": "CmP0-q4_K_W0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### RGB\n",
        "\n",
        "![](https://upload.wikimedia.org/wikipedia/commons/thumb/8/83/RGB_Cube_Show_lowgamma_cutout_b.png/1280px-RGB_Cube_Show_lowgamma_cutout_b.png)\n",
        "\n",
        "But actullay in OpenCV, the RGB value is arranged in BGR sequence."
      ],
      "metadata": {
        "id": "EDRCTRGrLqVE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### HSL and HSV\n",
        "\n",
        "![](https://upload.wikimedia.org/wikipedia/commons/thumb/a/a0/Hsl-hsv_models.svg/1024px-Hsl-hsv_models.svg.png)"
      ],
      "metadata": {
        "id": "RxOzAAE9LCIk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)\n",
        "cv2_imshow(hsv)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "-DP8oHgCJPLs",
        "outputId": "dcd269ff-168a-4055-a8e8-7403798a0708"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=300x300 at 0x7F6530A5A3D0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### YUV\n",
        "\n",
        "![](https://upload.wikimedia.org/wikipedia/commons/thumb/f/f9/YUV_UV_plane.svg/1024px-YUV_UV_plane.svg.png)\n",
        "\n",
        "When Y = 0.5, Y is the brightness value ranged from 0 to 1."
      ],
      "metadata": {
        "id": "vvnzehK0MLyk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "yuv = cv2.cvtColor(img, cv2.COLOR_BGR2YUV)\n",
        "cv2_imshow(yuv)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "6tDFWjd_MNPT",
        "outputId": "209ed6b1-96e3-4151-857a-4c4afa2f8f4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=300x300 at 0x7F6530A5AC50>"
            ],
            "image/png": 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4uZWqkIMhi5jZL8xFF0ugiC56QEg1IKQDwVFhmuUWZSRFGhHVN6sC0IIKhCsVcQoYzDoPenGzkIUMsMFzqD+tQGyZBun5XtBP6RrFSzPhs5YoIYuwMtk4pu2YL6Y0hg1IRSwx53LEnMgiIB2Kqxa2ZiDNrkCh2nUwKFOpUyf1ig5aMXJGytFldPREGFVhZLOqEcxRDW5SUDStGiqZrvYFmKmwbgnsKvfVRzMYkBwG9u35nvV0LVk4mH0tEJhNksujGx0p+hQ1FaDyuQGJMqv2kKQYneYlhYFWyLDK+PsNdOCeIWQFFUgpEQIL6hZhk/oVH1oEY6Jr1PFUgzrVSwmTWYBicaNbDrdgKE1IDtLkcwpGlZDt9z1A5gE+V5UNAlwqwQk2JRS3UOqoLtSZSgimMBUBYclpzuTovOpsJCG5VvX34JxCUOO3M9ZlRP3fqtPLgxGphI3OyTE5ituoPDhLs0IPQsRgjVXUwL41+CJDpBQ2e1lTJjqLjMkckaZIHIMSFQbkyfqdsFLfw0w1n6mukcTLu+PTxyfw48odrZxk7mkqaZjSrqTBbYg0wSawGd+iAlG9bQT8QFhpNiqB2Pu4rZro7Vm8XsVCEbBkSAk5yYyJAmAVhRIJshoONjFj1mkAQkI4ogWZlswNE4gOkOhRfaI0wIwW9JhtL6u+9jbd5fDxtQ+9jZUzAyAykJycHR774L1VTkfA+qpzvHovGKzQsVFL/1ncJFS2cLoQyapT19qT1EEjAgqKKQzRBSo4U4spc1abXBNMNJqZMVlDCFWUzGH9lnrYQO/iQK63qxTFJFRYQa+QzihnVCmWZI7qr6ygpnfrHElME7OYhRzIUUPytBa+a3MoMDU+jEgRhCLCA8mDIU2BqaTRMRVOoUFIYxrBaspW8BBVOqZDv1rzFBDBrlkrIiYggjElg6UISlAiG8LK9BXCngin3q+RmoUz50g9R0T/acUJX0QWbl5snNJY0ug2qro9IbU0tACiTk1VfQcJ00v6gsBh2atA83QyCFqo5V7I5rwQGFf0/S6pwR9WX4sBCgYoMAEd0MlS5CYGrLlt2NKgrIMhLIk5zMQEGmieIqy5YkCDWUv1oDXeYA0CBBfzCAAlqVg0rNogseZ0RDVcACMyqsOoJT0GWn5chYR1IwIAhDTBLoY0bDntLMDowAyrYq269kU55FazjgivegUykKQxVVTcMl9ZwIBFtX6D5szCYuIwKrizeePanE9TXyecphqWRzK2kLjXNWUCzOmGDKyJMCBCihxMzpqvVFStcghgcE5Mw7z6TcQJgkU1emUhCuZCRAt70mBAFvo+KIuZCZf/ly2FA+HvQHFSYE0dnhMpDGIkVCc5a7wROU1H5t1ZWA5bgTUhsBqdNl+Ye61xGSp+Av24NKGoYmVKZeJUODmLklfHWrQENAn1FQdAas7JvORnB8olFxTBuoHmx6k+6r2AqelQB6blnMRUjRVGS3fCBCQY1XVV5qox4cJXF2EAraLUaMwJT6nu32ZV0tq71s1xjmXxMP+JGQbVFLv6HKkOF8CS2NckZbUDmWyP8GJJfEn7JE9yVHcB7opNO5ZiCqBU0d5QnAQVQ2lxAsqsC8gaFiWZZJbAmjxYrWIzR41BkIHOm8I31Bxr2hIcR8t0sUCF+nB2zVamWWXa5spSIAE0tnzLlt+pXbXMDGoJDJrayBvKaGJjlkktzRAtSUMtdUXVBwuEWFSdN1aQCuYASd1+1eQnNe03zYF+Sq0k7UBFNoEeNcrbsFUXcCEnHz36Qd045VXbn803u3fMfEp/zEKfnQnb/jq0BmtCaNCDxa2EFVj1aClYDfR5a1lUJ0NwkUZXzP3L5n9V9ITmYDT3rzefQd6/NjMjCGAyGpjrkrd3KexaKVO0l2IOzXtqm+lAYrL5I7gwDgibs2HnAEtdwqAZSHrFbS1NuelMVpvBCNRvLgNumdMJtAodDYpZpczJJjMoFIlsvrJJnJwxW9hkrS4S0JIy1TIbiFU6dFMsm222IYyoNRZpvlZaZEnzA8c8D2r6vGWKBghxQrOHalI4GrquEZF5pk1GyBQAa+GLZiu9Wiv7RPaDrQBA4bHXLC04yf3kNbZcdhEFhKBqTy6sMUvqgw0X7RKGObuqCb7K5ZajpqUkVZURCIas9Gka3bemTkhtlg624EvQyzpmqrxf7i3QwcAsithgYEUczYNI289aS2bah33Q/rrClPs71uz1lkYRTeWJoM/f2Mdw2xjrsOALX9Y9X+c7NXef9ndYEp33em0hzebZwuXUpaEyQJt3uMBmzc82mDUAgJZY2YIvQmrJjQD35tDBUIKzatBcSyBxIsNYI6tk0EDX/AkqAbQZxTUzjjOwb9vRqte52tPLfZskwOHyVu6NmH8XPM3CsjIg5wmsnxeQFWqaOdhSeUSVmuLeHIptRmn7Aq15BSVSkmZP2QHEa6v1zL5f0rbaEJZc6/b4syRtV9iHE8mWaVLdKzaPjQoTg4iEoIU8lMYUXenGLfLGU2ILkmiuIlosq89ALxesX8QO5uceqbAysjidFkF5RUQ247XqoTyYhCsq70AtHoDNg7fj4AMHbLdPopt/an7r0ijnDXWw2JcXcg+OFzDZXl90IJa4sEHOvXLcw6eWPglBSDH/VrPy91SrNioveLCrvJWwSG+PujSzywloHNw4QdV0NMrASCjAXHRb4wwLEG76pT1r2jO8DpdDz6ISLhquvWCXp+/gw8+Cr3mo9RGhfSMCLXkGy6Ura8TyxfruPMJDWTdLk/3WOyBd+mcWCjoc6JVQugCIMgWB5nieo8KLS6pV8wgBK0xTwRBmGXY2dit1AaVnfTC1GBL6VPz447EJTbAIi0gh8xkISda0FfZLPeeY7aeWl/bBPE0zgNwTZzF8VSiiPetzcOwsRIn9fOyZ7UVa9yo1mKR593MPjPc76bIyAHi4Tw5Ze8bc7bNBa7o95kUjlFLjeWI25+Y7VH7LWDhWiUigV2VXk0Su3P9wR85g9MCUqW7Rg01c731JuC1PuOglXbn48sn2Tzp8vzEW5p9X5v+FW/XyG3rB75/85cMVv/q+ljrSg89ykeQga+y0ln44OY0pbZjGGAvjjpRUA28HQj4dXu2fGBO2G6ru0bne71AOtaTe/Yfrtvx0TDBf/+oveB7v7d94RjYeTomufvaF99QyxWpO3kOVcElXXL0297/MGPDwrhVZp4NX2RLtDmUHeXg5tqsk1QhHCLVvAbrZqqmZdjWNZnYT1QSXCg7bmmRwf0VgbzhfVmzLRt7Pog5Y6NKjP7sUz5V1fPalF2+ET9K3L/4CL//5ibcgYPs6LR7Ot7X6RgAh0YJyhGeUJ/CL7J8fUWvKNWN3PX+LfSK9FBMebObZkSLMnoB5yTWzIp5FBZf++iyMePkLvHyVTyN2PuFmz/vuoi9wCF15+OcVPXv1brzy6wGyBEDKLvewUUuMgRKeS9yoAg9CSHMrl2CLoxKC1XFbARTqIFiDVax5DABqnFOHw1kg4hXO+SRssrzCg18+mT55CT6ZOa9gnx9Kn3ZvLXlo4MJNDZdYA8pESAG6YQrkEWULXUCr5kE4ePo9I34qqfHj0IRNrl1ltAXKHKp7HXzmUFcdfOEAJb1wDvcw43AfXOLDwwu/OGb6KUApZ8up2VWtEG3pULE8yYLoDnHdJW14Cd6xfidSJ2MtA6cEFag0VnxmB4oIDkqKVVEXkYmUQEMI0SOSlczoTV3QUAvlJIbCC2KiD4iRXiDZYkO28cwltkvnjcN5xQ9ZkBeyxxUsgmf35bMi9fKiUM988ode83mfeRHVp27xoJaCpkCzO6Rm0ipqkqpZch/gpjhCACo1+NTQyyGEaCjkhzPiyzHhAZO0vTS7iZ/ReS+mT/jQs3juh751uF9ehA6f/eKnEajznlBlZ7uySy5hOuLAZdwQ98yc9pybEa0NxOz33HcQ1JJmUy9bgwRUPp76I19vyjqjZ1vAgJfUT0MeLmw6jzgzRI0sYC4DmauGAGYIc8bSUmPc3tTlx30OFx083Iwrn2WPH6rTnvut5/4Z+FHpxTttfvQDkDIDy5q+N/NhyyGWEGE+ufeIG9AGYNMbi9Coz37F6/eJ9CNqQu3/nYvK9upAM7z5RDh+6VpX9um+OOHy7T5pMI0Pr1755aii7CWRfG82xaUPLbqtesSI/VPv12Lx/i1sSgDJB8TCD4BKcySqu6yICBCmSBN6lHUeNyutTTW65+Iu3FMfTCU4ldbwCTDsADYvemgujJ65jsuDWG2HpzkoEjqwfZcdtuCMq0bXFZg6+2CeoRfvzE9Anle+XVnm06yqPvmW++tUiddKYmtJVVRrYY9rSJBUoWr6Qe/W1ZKNA7z0MvTjc8zUvOHGinUFFM2y+RQc8TLD/9Si5lPR80bQdBQPuK5+zPddJJZPXvY8Ac8VBZcDM0JNZCeKQJJS1MziGmeofF1dybX+kTGm8tFm9/EKwlRTMgkPm0YOSpM4kRMZMBTCyRpfJaAlS0lC67y21/NqeoHEHA6aO/7hKssdKo6rD45ZYB3C6WcZ6VlaUMwV9vtk7PMs8Yd94NIlhEtNStr9mxhtosrA2GfuOUAxwnyG87Pee1lh/9l7zPAy5qqpggrIW/OlPVrTrN7EqxN6hQ4Q3RIrXlalXe8KLJn17H5pqP3rOlhUHiIDPWfHXBrGpcWmmB5DCVihFfTNKExx0Frt4HYyYAIyYMAgAOibsMXBPwCWii0QyA1FtE1dVxpthyxoIGC7ASOxpZqLtOo1MRIDdJmLLVuSZMYSomyhAQEm1jzLAhQg6mhVyyzh1lqVNTQ8c9yyRgf+tvoaF9Cc2uvy1jEE2u/m9pUr63iFtZ4Bn8sy7qF5pcN9criIyxU+gWl5+LKW1w5X3nrYCBDoAAcmw6pVPNMjP1K611w3L5ISn5p+jFUUB0x3QJ82peeq+XEoDn8Inrj8+cM/P9Os6JmL1JczKGDJy6nFMNXDGAdf5PzWJHPIgER2s8W4g3oA+1TffTL/tPw9/6z5Jfvs5cMxJj8hAqVmx9cv1Mxs7LuqHST3tb6RLSuHqJlWgLAFk9A1s4fjLEqOoEIUAXOCQWXOw36bs7TSsvD155ygSIfyZbapSv3Z1XxpOPNcDnyZaxyqvTpgArQL2REAYIgamFU0jJ6+pWyRv8Sl7lJ21f33WSrsf6xxwsv/vvADz39rgTjPgpADZP9CMHsFhCx/LrPLHza+/BzOF4RTaDq4x6z9kFpSRd1bDCIEF9dAgQEYSQd6KAP9HL9ZtPTs9VhqZa/uxgnNI8s5p5gkmM7m3M45ca9ey7h/2PrxZsr2QAGnFuFsbcaW2Yk98zBBGbFD7doYaW7wUge4JMBcwQo2cxcurd0lTx0Pfj8MiuLyQuMZqfNcJtXBrniGCQ+H+EIG3yNOtAqcVqjFZVnQAQjsArtIJ2SHElBCGiJ9E/0b6iXOzbioKpYPVYnmWpQfSi+fO3r1LAYBS0uvqxv90wxFz6zKldc/7dCe98U9eH4xxaU9tHwryizgl+GxxeW4z01BtaZANY51pPPIA72nHzc9OSeJztdejHld/ROotqIAzPm18whin+opQM7GQjUXbCnimEclm+una+84mzVYDzngvNQ+0UXVHmYg1MBqHW4c8MkhbndAzZdbx1TRsPLl5Vjm7zB9D5fXa3nlpZXbp98qB3zYZFobX1tMHIsPgtvouuhIiENYuHghe+D9F6I7qvLnUkR38cqxitxP5SP90bqtUZdU0CEWPZQJBOaWJMtOnqt4rjo/BVxeA15ip2f49KqJd5kuR2l+qK6+fK/6Si3LQ2pW08JIyph71dRv1YIIYYJ3QIY2ig7KQoYkjuTMErUjRWU5m8saWx2dzWUZcZCaOitz1eabNVg/JyfKIEKlabkIqNTqEMLMn1IGdFVKzi1DQG5Ri46WBoOs5evdnKjdLEtTap2Fl0lZ9J4A5Hnd1L4ltgdZBMphMs7zdyWft+jPfesQLu3/3g/that7BSLhmb2jOsOzl6GAT6NfldXKN2fma3qv2IHnkU6i/0L0x/NI5hz2/f4iXvCcz6WXZ8Kls02VbAd45Io+wXN2PQ8+fHXenp3Ez2o2XGG8y6v4Q9DygbLCDMOamnKh1LBu0MF1DbLLelhu2WaUq5/DczEXDXtgBE7AWv43ghewHTiABVZLPUZwAOuLI+BzuURzlrSDECTUA1VsLu0DUGumdcPUwbuKOQNmzFCm30NY/VZtjwX1QEfV8iJSDtWQhgkmDDNkTggxXHLExEiYD6XZz6Ewu1UBVWGRWn3Cs0DxhRbFc1Xfi/jwE5DRi16/shX3HzsEtTjMaQXEUQnRH/vmod/4Y/lbnL6WxwwOSF9R90V1bHUwBxUElyoJP7VG//HahM+9p9qAeCiKOGtIfHbA+bzrP3OF5w3l+Z9sRF/kyeHqkL0osFPqwpJSVmYkj64olegG5bNIF0hnsjPPg3cfRR5kZ+BONsEGcCuO4gRT7T0FU2tcC6jqWGawA3ugazWQyGiJHAmohytUjfcEtQdEzR2VQwVy4nFNl69FeqCTtc/FiGgdyhBWu2oyMuMGPadYMTYWx4gbjFPzTR5vo3QWa/ga3nHaWMksiUUsCg9zBwrCWdN6rJbksqFcaA+VgQNPzIIyDv2fh2z5LIu+iGmvrPDy9YNP8tmPHb5yGexcQUjNsCieO1/BT75Tbv09+E9z97bxNpPBvq58R+lCcTw/8v6W3NeD8DJUfCH9GJiwFpPOXvqF5eYhXXq+y/SsypxpD1r3L8zHqxy8fVnBNXzHGVO0mpnLxmsN6ohz/G9uqy47UqpV9kmGMFjr7HUedgY+RXqi9DjSY3WPIz+N1RO3SWkUhZxlvaz3lGN1RznLTsLeFm7CjmEb2Bo4Fs2tk63IDbiRbYQsrAHU2vfa58Far46WCL/vJoRFkLUJCEiy/TmAVow+Z0sFOAETYgsVYmQMKbaIM9cZY5fi/RSDxTl8i3gAvUedp2mXpydWOoSpepvKKo2nHE/S9m2UlcUxyy3ELYubiBOqhzJaOwi3cITXY0VMBfv+ONx3T+fBljjQSVcA3B4pXuHES0m7i/HCA1Z8KVr4cJYYsim6mE7H8fb96fZ3bbiRHz+2chtdV7rXZT14DpzOEkc4KBtegqR/Wu0tLkO9OnUCJoQjiEiGqJIeDijmwznV/puTNZ6dgzaLc90rZn9I07GCWBBH4M5sgI4ESklkbRVCOUAqGasoC4dF1MYOIkO1jWj0AEsydSl1GR1Lp9LFuHrs/SOs3ld3f+weR37E7knk0btdMEFH4Ap2inyT6TXxz7neDhwFTgwnmUeBo4IVYMkSkxXzAEP1tJIEDgwJmkygZYDyKCUg4wB2xkksXovQaUQ9e6g2bUASUHs1qNaoK5NSck0AEhKRprqNBdbKCsgBIQOvkYXsMkUW53Ehg97lTnMjs7LUWUsZjxGjB6SnxMcJT7PuU+/KHyG+A+2oEfGEIfMjK0coR/Qj4kY33um399LwGsptm07SaFaIMBal4pxG+ggriNSK9AHM4gYUWYBqTDY0G3LUQ9xaE0QXJ0JEtmqIUotLas4DiqU/zTMb9qBe8ZIAqA1yrAq9gLWuVDaU1fF4+/cvXvud6fRePr/oujPrOl+fjv2pI8J7WQBkaC4EPrwlP71U+BHb4OtSp4ZLIH4pcI6rHIdnoMThO8sxa4vo3N8tAxPQQRtgAneIjixQAjPQKQC6s4AO64NyuozMCbaRrcUOaSjp3NOH0f0g9e+j+7CsHpXuYlw/VrqJ1W3vbpZ8u+RvoP+c5zcjv+5M5ifE0ew/ESIXKyEDRXhhgUroPOQZBiIsovpI4LJE0pSjVobO5Z5VVoVkuAAKsUpxHCjABBBhbTHR9k+qX44wtga3oUShNtMRJzWxyNoLu/5ObIEIjhM7I2WPHCHkWnZR4UVUZEmRCDsJjB5JuEt+hUpdJGNEZE8jqhCwJ+YfsHxg5RH9IeIpdD9P31pd/LaN59KO9O7iNU5HNt5EeSNPb9n0Vip36MdQoYBw+ggfGW5hjESsqUJM7fFx4KnCCBQgCRshESOwNR41a7m1WbAWUHlhruknWIyE1XO+2NSGmfrkx7873vz98cZuWneYtkhnkSbv+9LVHnZ+5RqHf1Y49ilTSF+qx0zTZZdxt0XrJVEtdX16QXBw7abzMJ8e2Jw/cwiHqt1BowOyYk2brJwaS1gR3GlOA5MykJO6vvSdrwcd3ff1O96/M/Ufl/X7JVPWKZ0wvQ77SeAL4B2lL8FOmDZuvZAKp0hD1IwxTQEYtmSBQVgpnSHm5MomSFIggXkixCmYTNZFJopYpFVogJgsBay2uxKKQKGTjDwxWOI2SYE+YIGyTHFFpMbqcEwAA7uCYcLKUA8T6EUrBOo+qj0XIJO6WAd9myZxIFapNpvACtxFw0xEPQu7on2/MGRgEgpUQJVsQBc2AW4S2BM98ZWEr9OAtHKqsIyapvVAnTufmC668i71MPBu6FvJ/76VbQ7ZZGn8UhrvcvxiGj6fdnexO0k7pkHJz5NjPq5JULTmWnIpI7LozgsBtGzYWE2fUKfWAS4AJ4vwghKwF1JtyuMAMFmK2uWb5eTMb/7OdPzO2HduxxmOXKwLWO1wVwVkjRPGUsf7KfHnFfqR6gkvKeB20Mhc0dsMuM+eAs+Gr+sNqkPHAGAH9cIRZLIzYBROxUB/FsmUe8+bYp3nEvkJ+jN1fxLd/bL6bjn+0Fde1nfVfcFXPzWufjXyDeB18Q50RHG2Wh6DAM8gInqANcCdI0s1EOGEwWvobILWCbWyoTn96ylEtW9RjtXay4knoUuaCnrXUev3waCCVCBNyFu7cI5QL2bjFgAUMcOHzJbDtliGxCQlMSWdHOvmqjy561uBjizVU3WttYciIHQxOvNHdrxLF0GAKQHAtvbLdBFtB7UVFXZgZ3AomYxYRUziFuilNTAFHRxgxZhgRfZBWFdsI/RKq0AX+QZZ3P8sIgcQVogz08c5PrJylna/aeP9NP73Nj60yWx3O13c43jaT79g0w36bfNjuCwG02DF4TsUo2VEsshBQREstfElNBGY67BqdaXjKj3XSXv4pgEFaH37CIaFVuFrlc6VVlUTRJoiD5Gy6oEGPNz+n84N+gL60eEogMXVIZiCTEs9zGe9INvP2ji+ut9StRx06ulCtgM20ok4eg7PK1+/GetzbD729bfK5vu+fs/XH2j1RPmu0pueftntp8f8pbA7hh6kOFBICMfkfFi4KJxTAGIQQ4+njASukrqViqMM1heO0LG11t09MYG152arGapdKqSclPvob03vvDV+uNIK3AJdKo87TYkj4I488sZodx/b7fdXX9gyDZwcTzJ7MEkD0Fs9ja/1JKt8X8dpJjJsJZ2UB29M/8VXx1+75aF4LUBjcqSJSciEBTjh+H5/JPvLH+NW0EEDOmKY1yc0d5Kezys/ASjz7P3GR1MOrp2rwqFG5d0wGohQ0GIgbwEFcOksMIldcG1YyR5VW1wwRSLecHs7MmPzb0QX6fgp8BB6n3rH4h3zD3P5T23IGNc23E7bt9P41fX4lbx7LZ0z7Sb6jr4DSkLtn2WNCZsEhUhY4Dli/4qH53kUVX8kVl+GQWnr3SA7RQA+pnQBFE+D56JEpKYt57Nn7MA58jL0YwpRsKGllm4Aq8L+0GX0aa+0tP0CvQJTgIB3T707mdYnkSO4Voro3itdmda/7usJm0Er+PpmWX8j1n/V+y+Jn6/uRGeMNiEucjwxBdHPnlGFCKya3Y8zIRTHfZze8I1HAnDk51s7Wsf2Ub65Sw9ry5+kIqDmhRpbIklNvDYo4J1w5MPt8je/MPz1W4VujyFkP83yzAJ4gSZ0E48f5aOj+NUf9P/SA94b04eCxB4cahtftSjEnKrcglAERDCrN5S75dHnx+/emzr6e3Wm6oEmQRIoxEh2OP4w//mnfH2XzgLFWpea5TjA+lvzm1EBilpvdHRv+v2NX4Bvjjzd2lGgTLBtPn6atm5b50nH43XAgCmyq0/qCnGRQjZAmXsWUT0aVMbgd5VXzo34FvE54BfnQ9LcpvcwftOGP0y7d7vhv9P0xDDlB7/I3eupfCmNb9l4RHf4gBhTOGuL0cUea/Kk5rh++l0XEOCCEfRqigafQN9HWXXnJ9ItZevGD0yj7Gmku/VosGqvPt/q+4yY9OWPRlvMvmpFyzyswApqA8uDt15AL5qmiova+byoeqBHObk5nj7Z3XjqR/9I3Xe8C/Ue/e1iP6f8NvI3ZJ8P2xSTWxE98DHIhHpclwzISAnJWbml9jtDno/Plk6hLZFulLO3h+8d+yhx7Q97fOdxDtr/9GPbTAyfNdNcB9S0Sa1HCziU4SzobhTeG7b3plvibcqSpqQVeFK1jmssGm/n4Vb8n27Hd/8x//3Hun2Wx9KYeuvouXdQzHciTJkswUkMIOXwfkrr8TbKBWbZ0BsdZD3sxnZPbeziJMcK3Ml6x5SwIba2lPS2qqwaBKod8btb/uiru//XvfE3Ot4Gjka7dc7uEX/6/dVfiXzvjJOBveJ2OTf4wPWkPiuKZXge2sk6dZ0DQBB1FcibAB2SzoACCsrNI5rexOrLefXv2rEmf+TxHnW/vPlfYfqtPP6Nbmf9xVtp+w2OX07D7bS7kQflMVgCHvVAGKtNVuzZTTXvq2fc8k2o1fPxuiLLMgOeonzcn799NG761de0fmDxD1LJ4APY6zWnr5ldz9vT/IzG4Y9PE7KguiX33gTZj4KV57ptZXqP6egPt6/9N7ubp9Pp1yP/G9H/HFb3ZLdCFubgJA3SeWucGzR0lccKa6dhzucj18FVS7rCyADCcUF0OfqNf/PN6f92b/qDVDZZxeAfrW4+yn/pSbpdcAFqdtlZrc8TFDDJnLDmqgkg5+CRdOS5gjgogVRyQIzIYSvZJuyUKeG/3tq9i/W/2QeK7cCVUQ6X9p0MrRUnwWBCB0JgwEwlYYcYUI3Tef9VmzJA4RSYHJk8T5gCp9A2sLUlMrdglTl9FJgSOopvTPjC0K9kwMMxPTnjBw/sY/FnH6zv7biitIrdW8P/9u5Ex2ngtODGw/5r37U/4/mNeXqX5v4CFKxprCFBMEOPqNERrzEps60TniyYnF8Bvl7iV2Se/XEevtdf/GHe/iGH37bxcd6dpuH1fviqla9yei3tcn+2w7Rrnc7nPXTwyxwBvLInuZQuZ8JbBy2NCRfavbk5+4rbz2PzLaX3gbc89UCaa+P8iif2kPHYbvmnEyc8rBc8ICM600SZIUPTHLGwg8ToywO+6tZd3mm+JoOEGjJGdH3p35/yLw+n/8vhhkRXDnQj+AgeApwJsU6acuSVTjuNFDuMzm5iDxtHDqFJ3HhtcARwPhcCoNBOjKG2a71xxx+8NZ32U85Rm7tfvLM+SxCYZAOVAMVcVSDRIIcD7QyGYmbhke5ElU0RgMH6sKePcw9+fNOPLI5Rimk4njav8+JB+q9O+r9Q4vbOdsBKGBLSnKjWAFYTvoBQHKpd68EnwDEMiB7myCns0Xk6Hmx0nDtuFp4/6m5G2rmdmG0zzoMZ4qWOyJeIwLpgyl5OyvdvTh2jB8ompZ5fTekH5+lvb8pPnNmpc9z4xZcuPv78kICPJtPO4vv4uw9X/8ctUmFxiLUFuWDAHK6vezcZ2MHJ5MiOUeiopx02Sdm5DWEghHMq00vBWt1P4eQXx9UuNMK/k8r95P/Y/A9y+Zs2rbrzb2wefG71+Ke687Dx8FmWX56nD0iwZghCCIRLE+LY/HVF7sbHOv+84inO1r7+5VjvcFS8HnK61KsDc7rKy9NLnVl/8HA2xwIZQqyqvAMAdcuxEs98u9KzHLhYg/s5q4YlKNhb6p76Gt4PoQKTNXHfI5B4kSM25cYmtren3z+Kd/r4XlYYbp2nG+/1X32Uvl6SB4d5M+9TG5tuJEwudAXdSkfHcbH2dqrBcdYqdhTm0+1bUkpoXxRYIXjtlIaaHGDp0jPa0/OU7+e/KObgb98u75mtET183JT+xB/dG3/wIN8Dbmh2+ZCYDudv7ldTDW8TCSVFag8xwCaRQ7r9Qfevf7//4pGfrWNbzB9m36abxRw8MQjaOfr63GrTLhx0yyQEpHVse00MNiEC2ySH5zvlW/emf7xLf3Zr242f3Srp7pjqGR5n5k/zDWAdSI4Sc5xzER/18oEjYkjYJawAOiYgpThfxZ1jlU6xs9sG3+JsQhb64BgJJV3AnqCD87b0NcTXqb+YQYvvpekPV4//gcXf6nZf1kX/ybv36mZs1o+AekqpiEBkTm+j+wD4GcQT+cDJrP9jxs/svyigFpDNKu+l+fAlMmYup8PVKEI7f2MNd2rbOqBWhtQyZH3iOA+FVuuOO69fZIlxN8X3iYEckwKeLFKdPGpY6cYq7LXp+28Pv/5m+bs3y3u9XyQFuL7fkfi3bPXmw7wZbD6vcD+Uxo1BBJzsR6wKbhd9IPUMgcEIxKN6PlJtlL5ggSWTrqqVWlpnkEhnV89krj7fCfmJbX53/Svv9V/8lbM7ob92I3ylHipQ3+vhCu8n/bTEgnPiqG99JajWK6Rp3vpfPVI4R+nDc8zYHyshjTp+ZHffyV8fu1XAkOCWz+zOyI8TO8gCAhJQeFjbN8fXqhmetTE8IEdYqmXyNYNnzdObevf18hv39Q3iaK2nGdXjaoQlFODOgPUAn9SAUDqwDYN1y01GJ1aBXhgmOLTpAqvIb0y/cxLvu756kY532DxMN6lpm4/GBEcWOzCQHkMdPAkPi3mKU6S/Ehf/Iqf/M/2IKi/CWM/fdrVJfztpI7VzNNRDXw/+Rjn6TedfDrth9ncpwDeYe388e5crfPjpjcKXtAmbU2IuZGxdZz1ZeD17ABBU4tOGTg8H3MqVMRsplFgilQ3LU8MZsRLYesZDYslxnnD7zvT+l3b/1efH/+HN6eykrCw+B6WwKfD+ScmxyoaiesDT4U2XbtggEIIm6ybciYbXAChJWfdN0U5ka0c4GLE/KGKvuqsJyOzo29M3SZmosvYtBIZCNXVrBI+CEyyDHQBBgUx0wFSZRC0Ntt0iEK3YSaSCc8Fx7cJIRda7r49/7Wj6z0dql7qLPH64/o8edn85cJzUASMgYgBSq97fX7s9LxU5uk4fGQp4JIZgsMmQoHwa5V75jS/s/vwfHf3sOr5jrZdH9RAPwVsFuajMp1M/u8gy7KCV2AcuAi6tUgzHcfzm9PufG/+zm/67Oe4U3NrxtQfp1vurXwn9nOuJ2AVvthqUuEU+FW7Kwm0AHsresQDLJ3ghns8UtaUVUKMUcxcF9ChHWt31zW+OXSAdo3y73/0cpk3M8Gl+Gh4+6KX2o5+aPrtNeHgDAvWMyhA9IUqrtSFYob+6g8NAP5W6np1qs74VLIASNmxsNJYHwJeASYToYkxYJd5K7q/5r705/fdvjhc3/DacsPcm3XTYyFT05g4bj/No0dgZgqKNH0AmAJIuZudrpXmrCViCrfVRVulgRYufssXWllpXtZgeqfBIBT1kUIskZtjN4l8b/voXh795z//wlo+ruAXskIepezjkt7b5jbAEFmElTWWRQfXH3DfJ9r4UUiqY5sNKBY7U8XHcNPCWbUk7x3jfzs+9J/qsM2IAaFjXnhrLQmqu16oO0iwguIoHWfWGNYLYA4J2m/La3eG9nX79W91PrqfHJtSyj6AKi/O2IxFeFWCamwLUCTcAGqEeXElb55m0gdLGz7vo3hp+44vDu3f9OMcIve/2+INuV/rhzP7siNsFBN4Rfpf4VuJtln8bWDvPwbUA4D36HXpHje2R8Bl4oeaXt1pRBSJjGGJ11/svxtHf8HSWhn8pLu6qrJ5TBPIsPDz0dn2KQXw2JtSM7a9cmIBFVYNizVpgzcRLhyfavoCeUep7lm2ZSyzilNN0Yv6+xVcdA+bMUvBpjuOb5eHN6TdvTdsTvw15pLjPL5x1Wbb9qN886tZJ7nBoDfrSxM4O7kehpWeKI++OgLMi/kRYHw8SPEUyWi0jr9ZgOngALT1nFKHk6uZmlQCASEfUnfLN4ONbzlWsoQSz87S73735Qf4L7+Uvujm4TVoDEfUENu7bYDR7k6ptgg3IKMSEhtwzVJ9p24kM9jw24kzTWkPvA4xiT5AwMKrY4YGXfUbW9WTjsopHrd0xieZ7XVOPqbs3x0db/KO704fHcbMP1ROuRmIyFLtTDeX0vI4jlTGBBAwBCccAuvCjuPXl4Zv3yq/fK49vTl+GRuAMxmJ+6medpk5p0CB+S3wE7mAD8XuKX0TUAEtCvJumO3n6zG1KW1uBvRO3GvfCdDtNP0h+y+PPg7TyhVRCNnePvQTdLusXLUXPn5ZePkSh2QFbbVpIqFE0zEFPpmdAsp75/aqcsNlKrm/WYxpNSJOn8Uby75tS1PMvkQh2OtpEd2N8dDJ+/2jKcFyksw/7t/+Hk/9N0Nbp8UX6zv3802fmAnON7xE2H/espfpLgHJRibBz3B6QXO00NkodHqYophytKt6S5lO059Tqpk1Y/bqkulQ7jtU9rGD4bQo4zrGBdsDFBcd3u598p/vlb+U/94h3R56ReQMLZUep7Uf3fre5To913wkpSq+Sq1bmCGTQC6YzrCcMPR6OKFCiMKEvyIaSuCNGoj+oY6hYtvm/AGaw59DhCQjQYSZo5A74cs8zxuNNbG6WH/yZ7W8m2DoAmTg4bbRuTLeVGBYplnTKy5YzOnFEOzmUGb4RO4yv+d+6W94/Lh38AhrETDLj5Mgv1uVixA2jCx7pDvO7iBX4kDToCBoZZtPHafy6jbuDg7yvbLHnM0YQZKR60LiHqs/ZPZUbtutxvk3xlcA9DOf9VmV1kKzGuj91SQ2+lHPmxxInpBGEE06rUrZIRpmZJ9Ao91mzof1Tz53jFSlS2e6AMxsYC6QSqRxbeUTvkOrHovYXs8BKu1VsOxmVHangdKXd43T7Qff1NT7nvLOO3Wi5YLY3qYPzRoGKw5Br/88dNwNrSm/t4ORrP+swUr3m9rk4SPXivh0iWKOjhGj1lXbsVi1sR0dM0Ag52E8sE3/2nfW/9CC9fsaPRGacGgZDibn1rs/TsQ9Bq52smOBd846yLmXYeMF7j9L/ZGtHxmGyaeCTM34haMGPM4/IDTQ13alljue4EACYSZ1PvW8FtD5r1MiTD7tv3B1Lz3985HdP4uJ2+f+BP9m15lFypMHWZ3bqy+nwswOszkPz0LD2EdwYt9Cu161N8M3pO3fK37vpKes14GmwBI8yzi20ige9xkAnXIDngbWBwi+AH4GTcMQQfUrlLI03WOIzc0FzaVi15YHc0hzKI4w/153f4/RbwQ/hP2vllF23bMr9alwx0GpU+k+v29pipFQwqNY4vdpHxWyNdC4DpiPEAIUlbfJ9xma325RSiEyZYQisMHt36uHp0Vw9S4fEmqYeALyeFjAp7e5i+iY0CNHMDaXQGLQwQ7KgkU+OY/XW+N1fjv/dheXRTs/z5x73//Ifb37uIe6OfACtKrAT6zGaTtBb/pEyi+V43N0+H4+cA7SCIeHohm/vTvcf5jsBCjvIFku3YTW1A1cyEtAztsEbUYvlzS0K5OB4nu4BH53GBPWA99rc8//8z10c/Z2Tf6fTeodpEnsOhr4CziXGOrdAhJiAC0cfSKTSPtRioI8YztMbv3P8i99Zfy3RQ6Ywgw+pi4Qkp7qiriZhcs5KbQ3Aq2pEgWxVtr0/kLKwIiYgj/bwg/7tR+nua9PvvqVYxeq16bvAY9MpcMFAijgnPsxv5dhmtz0MRxO2lS09EujGc8IMXAUYen33f78znJ9MJ9AOVkZ7U/jAkBnooxz703H95WJHsMcJG5X/APr/GH4VyAqHb/L4u3m6TSeixYf2uxVzbIQx64BDHqo72Golp5hRWx8wS8A44elt634BfYgbRXLIkWszhAr+Y2nzsrBIZec/1Tb4V8zP2eaRwcBzsx7cSltoAwQ5dfk7iLfIG9AKqp40GUpZYp1XleH82uxBqVxpHvSenuAXzEkkg5IHV4VdsTymY7ctfG2ajh3HikIbcP8sfe9x/EPDX/7m+n8+2D3Xk5gB0qKclxRNo4EoqSu2EqrMFsFVTH0MFIGpdT9+1jhuvw9BuHUTVoEAtlabiDIHN4/ST4PvbPwfZd2DtIrxZkl37de+svviH25+CamM9qjghBhUnUJzoswyXCDEVcgAZE3UBAmqXUP7jNzpW9/Y/T/v+WqbtiM38Pywe/0hfjXjiIJpCATQJ2r2JLXnqDcJ5oS0it3KLxhRBa3DttaNXN1fvZn1xt3ydOWnp74NDBBEYyCgkZ0zC3Zoah4OHe3ADQVOTI+p46z0td1v3pu+faMcZaHYg4Ffe5x/chOPsheo68OP4mwVD56k16hfZvwN6Q9MP0HcAIJi8qM8fZDGDbyXPZbyszf9BJjIWewvHbzmqviqFXvDDdDCbiB8n4VycD0detBevKU/gV4mTrj0O2xqV63qm5qINTnJHEzSBRQ1gXHONC+QQIvqCbmyixfNAuzbB6E9jxDQmp7oD6F7RAENcJBBXtjJlq8P9tvi64wMjAhmpBxdr6OUPtqWX79XvjzaXzgDhwOxhX2bCzRRIhRm8MT4dJ5xGoaNLkglTIYu1TTnCjVnw8MAEMFeKmIeuXL1iBHRQQC3W9v9oP984ZfX/u3bQvZswfXEO/iDL6T/9ml+8337PNLjyYpAAxNbQcnBNED0UG/wuZYnuU4gQAH1ueA1jUfxR2/5zq0UHjvO3uVXPy5/dWf3gK0DhgimYAFatliesw5mfGrHONvovGt5tdgxLlIe0vq99Zfu+M+O099E3LUYTVOYiYkMZxl5c1LvaJ1V6gXtYIWt1sfQduwiPPnNXJ6+7r/2ejw8xUbGj9LFE/vKk+6Lr5e/tXIzIOtJglPrpHPEl8D/GVSSfzHxUQCZkwXT8H0b74RQWMOZuqLugNmBcVWJzA6Zpccd5mQTC1E0Q1obAjGGllz65f8fDz0/1/WT6eAs88WqiMSxt6HPH676J+tVrFdls+q7/tRsQ2wAB0ZJgseS6l4ZuRUf7ju/HNxpnsD6ZnRWeisfM/qKpEgaRreLR/nO4/wXnqajs7QtuSD1SLXJyq4r+eZ0+9b48Fb5LYJdcL7wIq3ZXIAMhwkxYlVwQ7PMM5mhrP1MYEIAyVFljwCJirnrIKHWNV3nSV7VQ/XBgP3OnhSzP1n/1MP02rk9RU2vitWJb96c/uE3hv/viT898lspzoRsaIdP2JLdI7jgIuSmEUCSA95WgQEOEBCrI1/dmk7vjnffGG+86bdvOXuFaQoMgYxaYr8HMbDKh20yisBjPd1o6KO3IAKBMlra2vE2HT/Mv/g0nxY+rW0UDQITjKI7TybrljYSdVZ52ZtIAOihC1Pu3d4Y/uTu9Pu3fAOkwvQkrZ+kr23taMRF4SagLFv7I8GAp4gniNuI0+BHgQJ2ME/adrvHaXsPPjFWz+7Wg5/PeS9mzL+fANXekh1QxAFMVDZN8+L+mDkQn1kTtqwece7tFECCzNBnrfvdkX2/y259semEfs/Khenjyb/IVjfZCxAK4Ysm3OcfXJaaC+0jZGKaNjZ9RCVCgAOZSAXbwU6+3/3SndUfkL+5ifd7HGWsNt6toocuupJuWHdj+t46tlM+mse+NO0Fqp9HUZAyS4fVjje82tbBHtY5Ujyo4NhhcTDq5UCzhh41UEiywuw4FoPsAYPZZP3WPnjY/cqT/Bc2+htHOO+wQqjD+jU9HeNvf3X84u+v/+KRn27VJ+5sRqFxuFeEhMhhhdngYPE0RfQWPSCwLujQUsYtGMmwmtSFEFCQCYJGzPoq1bJ6NBO0RpZO/OlGw1rHiAJYlk9cn6VTiT/o/sznup84Lf/gTrxFGhitytzcedOZgxGsac64hHYISaNCcUw8PvLbt8qDN6a/c7t8sPJbAHd2Uezu99dfPPGnwBSiYcoakn7ACNcaXEMDdQbcE58AAWbqad5u88XN5DWoNHfFXnbVcxhmr/UDxEE5VBUYAgQLJpMjHOzBDHKuHATwvJ36svQy7S1MhLVOFEvLbdKSISdbdZ7wYbIHyS9k31RRYT1j/UL1nDcIKPs88LnBlS032B/twtkPBAKM4Hiax4/MI1TdCiRSsL+wp4/znXdWf9XxMz2+nXXRY3d7/M5bfm6TIOboen90Oj0+y8dqmS61hH8vowMh5ILJsXHcKPWuIYaSLOljRlDJiTholtpKF9j0OuDSKpAFO8vxuHvauwHdmOxxjsf5g8E2v3vyr+r8D2R/79hLCjgvpnx7Zw+d/+VxvDXknyY+Bk5ahjiajRXNPE4BBFNGSbx4nL3TcGGRpISJtTxLopARog+2e2T3AinQNX9YcxrUelugNXRrcsUiU0p6YpggVtEZ9ODpRToptnvQvfYw/dLd/FsnZVrNI6x9jwtvFebCErR2ss3cjKw53UChBCKLSavPjX94r/zOcS0s4eicMn7iQX/veDjrlROmjL6Pm72iWAdugaFWdAJbRwZ35BHjw7RFv11lHwzlcnD8inHGyz/nvYuGi2j73UY6uAJ34iNYAMfEiVUfEw1XfD8/Gk9+Ru9o60MCoIbAUA1YB0tg8m7ymykCioQtOJAroDdmq87I1pkH+0FX2/JQvtQpebYYmIFIabpp47v0EeiAkQxicuYLTBCJLzy1G+f81/oYIqV/8ey/zOVv3NNoMnEEu2Kdt2orLU60dnmZCQGj3JkCx0FgP2YaHnSYslLt19QqeqsPl3PHL0FKIYAXu+Qfru6CyTRBdFs96F67390F9UH/9jr+5Y/jRh/H0Mo5hL12kab7Oc5SP1kXtl5izjbPjDXnQQg2srtg/ACf39p/+GGf1i5iJC4ME6t9CDcM0A4aP85vnSU4z6vkCZohW/UHSr4EhQgT+mDyIm1HcGdpowJ2nop4PKWups7+YPWz9/xrd/291bSqSbcwFHHCaUHnmkK1bzldAJT3HnXAUtaui5NjnL2mf3ArHq7jFAonqM1p2De2v3dv/MGRnx4jEX3E2UrvbnCRuCECmoiVsCtYi4XoEN9P21Pbdubn9Uk03wpzi6IDH+mlLVVBaJWetVFdOzS5vmlF6czTE3ROFZv6FNm0+BDiMle/PL1MnJBzv7BmS1XUpuxAxKCYTMdEZBuQfr74x2CAI7kWAe4AQEbFgQetzhZRoyyH87VYnXAG0nhk4zljIlbkZAgCAQc24O6m/8bN8ntH+reepFsr31JDwn1iBd50jm5UPXjhMEK42IUwq6gRcqYh9WeZR6JZ7KinHbf5nKzt8TzV46YX79IMFNGcmeHUk/z5D1e/+kF/a0IPoCDL+Djf3tLXmt5f/aXv2r+ZVEwx2LrTGEwD18C522PgyOfMsr0HmiBgIiBnGTg+zq/v+G9/r9/0MSxbqq6PoR30G2ErnQ/pLux+0opAkQIzhgQxO0jnTGsJ/Dh733Vn7NYRxjjL46OuK+yK9dD2g/7tzw1fu52/l8LmJHpsjcU2QQO1uDlasf6lGd8Yzldx67Xyzmvlt+74aHGMOAdXOfyEv/Oz2z9UsAuYAjjLoT6Og0bugBVrghx6moMJkvkPON7k2EEDcOOZDK0f6qnkbJQcoFKCqWd+OG3ul1Wv/hZj3Z1bWLQn4xVT90eiz5q2xiU/gLMATUk0GieDGS6SLgzHnaXOAFz4VAAaz8kVuQaC7cC3Axf8cnkACLD2TNLc5r3ab53FkIY73W4wvwB6YAJuAGMOHWG3jlufH//kzfGv5/Ibvd42fHDTz16bOsQpzIs93aafPUs3hAn1zGsRtJlxnBDRG4ZIJ4Sedqf3g2PejtoMdrJNX/+o+7liD4u9DsLUZwXACARCrdLBQEssooLmPHvf/gyEUILQaQzYuWmiRcBoxom1NxR2teVLwhmAhAwMFXamNr7F/EYnAZhYBNvxfDCaLkYyWKz6VFs7+go3QdNg68iPeutyzedlO4qQIGgJJhlbfAuj8XFfvs1/7/3u315re+RnGffH9Ohpft2JkSCiaP1h+vNH+R+W+M46HSWtEh+ed6djukOqYwqWTjmgNMvaxXdUdNHFjT6Ge8Pfvjt+93jsURxaJ3pPy34DUBEgFyZgZRHJP8iagB4YgTVwTmwSJG0ZncU7qfySlceKDebar2bs7GMHV52lC1EFlpJlSO7u7XSlFdIQmzLduLO78X1f/45NP7HR5yPdDJv7wS0+9R+ZPrMmjKawAGAp84cQfuzTrgy3JkeKNJKwD+m/5/GV0PeAm6hwggZlkz+b4je/MguYuXvqLOFHKqUxcTDzD6HXQQsM0pbouuhWsb1bzt8c7bhsu/g9sFtJiFsAt/bhw3TrQf6pXdo4S6rJPfW0XVjAiFyL6MgQdmHpYfcz7+N/9aHu/qD7fEFO9MHW5+m2c6KeAoKMmuMSJOZTUIgEhTEKdcEAtcMIRK8O0miKViyIFqdBqeDNwHVFe23XDAYYK0qqE9eKJzDjD68FHTOeIphaG3KfC1tA5FpUyyZAGwmbOslUTTyqJ9uEbDPIPu76Ph1TGUBGMXjhbkwnwQEoI9P9/qc7/sfnaVjFd7Mi8/6TVB7nW4YSdGgDzBUNXMx8EbRg592b4zuvlW/fKB3iBJhg02CpMHqy0zrVA2fRQbskpRh6Hxm9zCW1zQBSvcVjG4XSc0ELP9xveQliAT3gwBAUmIQMJKSMbvKe09Gvjce/4ZtzG0s+uwltGhptV7qs41+WPnMCd4vtch8xQaAUjCPS7gjbL5Xx7qBdhnVcZYwWt9yfhm6aVoEJMLusxC93UQXa8QWaTa0arCYYVEoju/GE8S71CxCDPuGUSmvlY3+wjg9OoxzH64ge7IEB3J7b4/e64+/0f+X9/Je2TMWm1JpT1L1bPUwBOCkwOeMcLPlLzrsjVsB54SrBJ/MtHxeFAUmdqzUYb0FeimhHPlBV11qBBW1iEgT09XiYVurLuamq36w1SLWJQG1wqBatYa7lSQChRFEMY4g1N6RliADLTrfKZrVtpAxi2A7tcMsWDarcabzQXLJYU+qkBLLTCMipXRoBa1FhhLgCntbkonNuSz4d+l/IUbb4lexlrW2n8UF3cp7WE0a09CFA87mJIAwW6OLk2M/enP7Oa/7311rBEjhtU/8oD4PdTri/1sPjktfR029DRlzkOF/FLuvOFKODUgdMFEwnafh2Hi3FmlpQJZ5Bidz7TgRAi6QTIDlCYWzHvVNiQRrVfez9D0r3fU83S/Kcv6P1TzDeaGL32Zv8CPQS7S0W8wSYC9LgkF9omnzsxumme06yzNOOdzvs5N9HnAQysKvWXf2eXRZc2lsRS/wGrNyiln2dhuB4j+XDOeclAVuQwc5wcWb+OO2g+4nDZDHQtrJH6a0PVn/x25u/8qC/t7MPMzq2Nv2NAmEIYAVNpIRS7LHjyGHQbqSJzEwAvfZ4loOTLIt0MyqbEmVkgDHjQQlwhjNEp7nbWSCAYpykEZjEAoTwNBBQCRShiGWiVz2ba0cplKICOOEGKZLa3EmLvwEAPgdwBhgG9m5roEfcVk32RorIphzoEZl+G0BLkGftg28UwYJWlFwT2grkkgAjIoNC52nYqoCWLIoe0zDGkbDeJp+4FcIwQn3d7gfKt7oPtgkPRvvgaV7/oD/u48nIs6eWH3X/8ff6r7w2fXDkP3idH9wuf+9E982PgESedXrc6QtgQJPDgJxQ6Ku8ey/v1slX3JuCvPzLsw6Z/esEWnJskDCp9klKSu7906n/MOzPIn4p7f6eld8iHiPbHPr8YSr3s7DoZ2ZC27eLnX8SiUjqqEJcSOEBhQsQjgTAb3msoREIYw7Vrh71tOfZ9zAHJZ59lHnOyAAmpPGOxTdNQygZuaon4yY8zbe+u/7Xz9Lnez8DHjlPBhzt+MbOfub+6uu7buPpqVmP6Fo/0+aTZ4IBiRgTCtQ5V8GtrBTURgmb2Qa3PpIAMZB2AYZNsqeyM/Ix9VDxCLyI/EGwAIPhHDgDzxO3QIF9HBTowdro3lFBV0sID0ATImoeGkF0BcqQEEUeiECYJGSgGbNz0X2dNqtGF8QEgpnWkZlYtbJkZUUXsTKsoM7xJpAsVowjxA3hZsGpsKa+DCVTb1oRa2qdypEiu01AzpEUKayEjUXhgKeVYVSIcMPYs5M6ajIVtEZBVazWbv1w65/kN77Lf/9R/tdX/ZOsPzF7OHJ4lP7cB/nt73ZfdeavjX/wc+d/3OHdDe8Gn0badjg3YKUETGIKGJGSI21/kLa3zBNQI586iDnNdMCGB++1bZWQIYNK9WaFTFi7jbHq0H/X8MVu+wanX+mmG73oK5837I+TXjKB+xnrts70CnBgJ6RQICapdgW74d4pfMZi0bqmLr4/HDxXy7Ssf9js2WbN5bOAlWP40+pPszTWAGphXOT1e/rl73f/CgIJXg8DGLEarSd9ShdOUR0wocbRYKCxNbtwxE3nmNRbWOJxUMWceQs8IB8GHgCPgcfgQ/BD4EHo98UQ3TiZRmqABkWhemOLv0GR6q3EuYnx7EwNcE4KI5SgmsMfQAYBmrbzeluPDmJzjtMXHLKoQqGqds7u0TBOtJ1ZgKuoqFs1EVT1wBwxV9BRKzICZrSgAUesp7JwJR6TN9Xdho5cX4ZuGE7A14nXgVOP25xOKA8m0Qw0bEwJ9Naha17b/YEXDLBsU/8RvvZhWhl9Fb8MQ6/dFkcDhqf946O49zSn727WYbhR/hg4fZx3O36cVQp6q84dguhS2ebh47T7MqOeVc7nhQ0+QWU1TCdEaIJ6gxngikhn45GNx/eje5jGn0nbn8nj56z7HV89xbNM/iPTj1TKVJ00ipput5u95LXKSiGjW1EHX83FdxUEUiiohaWoiLOZhc2Aby5gu4xYjZK504/pgh5Bb0YriGaII3Zbg8nCAGSjiZIm51lYBNZQhnbgqWr7ZKSkJAlpLFY8fxt4P/gu0oduH4kPyPvgfdjj4LmjtnKMdsh7FOgEEiOSh0XYhJgyvTOfGJYiIQwlmefOO0YOmSKbd/Q1Y0PfWFkjcmgyMCEDXWgF9RY9IwklWjFfykgmi5oXaVM1kZs524Jvgj2AqR4aaBBZzIawyfuP0FpfRFiRTciTUon+YRgiIbLAUHZPk3IoAxZCkZWShGRd6mS5YOfqHZOhg04Rp4jXtToVXkOcRNwOvZX5Oeo14VSxDj+GLDXBodaIGA5B2m15RgBmk6065R2taJzIYquL1L2Xf+q8+19/mB/cnL517L9/Zk8epdUFz0kL9EHVPB/qkQ1P0nDboiKLFfjCCvJLrNNi0fMuBqO1UBfggVLyxXDyh+Otc3SRz76XH30Rfu7dudsbWi72Cm1CQogaL2tirllvOAGe0IalPVO1eREdJNRWKE1WJbbM4WdkVLWbDyM2mOGMemHnZoxbNvU2nMUmpF4KcQzrgW5ngsZAiDm1JHIIx4wjUaRTp552SI/Ed4nvhn0X/F7wXeih4j5VgAt6yZ6gzOAcGh4USTJGYShpjTimJ0ZOvmI5yn6KcjvKLZSjVG6aZ8bKfI3YpOk4lSOWlaJHgDALozI8JU9yiwgAHZYEE1oYg6EINdbvpIRWLTVXCXPWYUA9sTdlmXtTCNUZ6rISNaZJwBDJZbtIW3Vj5K1yeJo8XdSjF5GeqNspfxQ5hBI2lHShdJb7bdhohmAiYTTaU+AR9IEQsiKYYwQTeITUCSeR7kZ3G7gNfAH6KuJLwJsWN1GOq2wtpuBAhmGadE710i5wUyyTPThTN/L1R/bFVfdTgX/ndvngabo12TrjLGBzulVmXHTDkMYNvAhzpZI+DXvs952DQm4KRQUAtAqceJenzU2sPpDup3VJ5WbwhjQttewHN3oeAP5TtQkhgtFc6ap1LDQLYkpmOQ2WIM+CBTbAGSxDtU3gBKzAZJigHIrqtIb2iZgU2gkthKpkaq30a+O9lTgJ2/7s9ensm1j9/NA9lBM6TrogCwhyw3BiLSVIxVzpDPYdpj8x/nHYB7JvAk+Ijw0XoMSAYNFxCvOUp57F0lg4hk2bNN5K44lNRzHdQDm18ST5bZZ7yW+muA3vzdeINdQhUtSzRVVqizEu5+M21DjU5SJFTYYRtQqx9sHlHnnPYoesnX/VOrW0jJlmCWJJaktooWMR3go96+pARNBAJC6JVh2sAyFu1DyY+/dgiFRzEj04IJ0rnSGdRRpK/ijyoP4JuofRfaTuI/WPvDsvXfIuIq+jE7pJXWHemt2HueiCSxk6hm6PuAUd2fRTiM8LPwN8TeW21AknUBIvAGZ18AlkAZDOA+hivL+6N+aAuccKGi1qstYR/Zv98OVuhwhSfVKNXFOXeWD+tfmzDimAgAmFMGJrTFCnaUjT64jTsCdTd9OPfi/fPDX+fB5PWjMMSK0jmx1cH1dL7D81H352JrwkbVTBBk1mSrYzu7B0orSOsjUbIjJYWgcUZGEKlbnvihHVdd5crHNu5KF92PaZBNgg75USte6H43F4NLiDYrpAbBh3aaRNsIL0kfhQ6ZthH0B/QvwJ7H3DOaMkJ3TMKOZDCkckhNF7K+s0HqXplk1vcXwzTXc53LbhVh6P0vC6TRaeMJlNTIXmyA7GGcOaH16DENURGLRaTcOZqeYIVq2A1+Ipr8tmTa9V/txHTdL87PsQxHJgoaDZvTs7jVDxVVpaf7XtwIrzW/eKw6nVOWZchsXQ0fKh2gXkhng7LClRCergOdRHrEZ1F9Gdez+U1X3vduoeK3+s7iPvPlb/KNI2cpFNsmF2X12IH4gJ/PvVeRu4ge6e8CXh69LbwM8gXmPcYblBIWwauR0pKBHT7Ltz0WBVcZ0jHqRhnQfFlKACDkn2GVvMoB60I/WkocGlABx0WfGU0Q9lfT/vzjGta97tHsQdcNpLnwaDl+q2VpdT0r4RBS1oI9NEKSmFZ2QLMQUt1oqdNMprY7wuIkG+9KbjLD04BwfbLeaHar1LowdABaPQb6X4OCOCx/C7sg81/oH0bqz+CP192R8E/whwoxGZSlbMxmS7aiU9zbtbdvElG9+23VtpuIPhdi430/gF8x7R0xMUFm4eDFAOlHpaWe1Q03ofaj3nsdSIX9u/aW6ocmg8cElnVOMxn30qqXVTqot6aKxc8gAIc51bnQwAc3Hb/D1KLZe1hvXTzLILxx8WrOxvesmlP8eJqumrAZIJ4UrMMcBImSGZ7Fj5GCbwpwMBC9FhU9iIPHguyu97d47+I1/9wNfvq/9AqwelOx9PcumB5JYeIz1C+qasgAJuQ69LX1B8Ef4lxFcRP8nx7WAANJ+oc5jBeuQpNJpvMH2M8ec4HKUykDI6sIaePRrtxVsZAHLLUoDCaExiQmewEKHUSzvw+8AD8IjmB5ru5bnuCr2EY0aa3YuVSJGR7EmXdisMCfehD8U+7DY4oCSPVfFJ9KohWJM5DlXCweNo/qdpesGba6ZDOieQ/CINt/J56c5+F9Gl6T/T9H1NXvop+JvBUTxO2nDqk0/JRyuw4TTt3ub2C3l3N41fTbubaXeLuxPbrdJAm8xKn8tjKITdHKisW5nikpi/RAJ6INWugXvsuGgaxv6x5qgwF2/mTHbASNxPQ/t8m9iDux78JLBXg/MkNb5p0KT24uXBPWdBHbMKXZzT7baL51aqWX1Qam/UI+mBVEM782E4YQYw6aO5DjTVyRG7SIr8JWX3VdFqjPVO/Ta6bVmP48mf+OoHkd9Rflf9Y3VU13um8kXYO+K3K0KWrWF3PN8V/zVOP8HtT9p0w9JN5V52ltSxbFnuc+oZu7AdIwfTHns8h56PDokMeDuBEjmYlVzpCTRRBI+hE3i2AitrcNyDmBde8jPTy7Q8nA8lbP34CSaq56pPu7WNK/sY9oHlE/RfjO5sHMeJP5uwHqetRKkANCVEVAgKzW3kWksZQLC5WGQ5YacyI3Hbpm33VOX43fUH/4euu1jd/1c4fqPYL/jpg8n/937rN+E9djfz0yNe3OsvvpqGb6Txi9zdwbhOkYwjI9soejEfGZMpkoxIqs1S56RYIiAJFGzuu10tvAKVpfhxD+CqOYZ9qXOFhntVN69ZlS+5Ycz24PsS40v/XNpSnM2/Sx+Z+4Accu/yqUP258zze2377BKrh0IIYGps2Y6hri2ubIYsTk2gwB61sUstVwQkJZf4jkryoVPqldZKx8oAFfgppRJ5UHcR/aOy/r6v3/H1h370x2XztGyexrr4SupH5QdmT4P/l6TzXL6Qd18wfl3dv2zxZ8GvYPidNL5hegN8zDDx2LllK+aaJ+0KlsCCFPYLEawVOYS8TSQH4CHKGacdfWR5E7s3cPF5Xhxhva4duy9Lyx+VXi5EsV/u6smkAtiQF8Y+cdORZmcp7hc+Mk0oPxFTTpyK+nkG5vq1+cfCh8vGan/sn7QebzSYn+ftG+v3/w2eFsTrq8crDlbsdjl/UtJX/fHnEf8Ctm/mp19PF6kbsu0SR7C4xQQMSDsiUSLFSFA2AjSBwVYkOd+7qb450XSW96p9Eh2NwbgkDqlegOABUmhWXCsf3e/+ZiPOJ/1eFt+thYgWO3nRki9Y+sP2FPNg5l8ur9nMgXMF9TLjM45utb71IINW31JdHnNBPqAqtnQom2qvcDaWnG62NZsoOFjAgIKxAyBD5OPId6L/yWkF3xRfP/Hj98rRO7F514++H6sfoH8/8ofe3eLuqP/4383nP5P1DyL9Nd/8NdkG07p/8uU0FMNFsAuM0ACsWlv4z0AF6FELZOEQgRW1TuUtTq+Zzqgty21OxzaN3i3rsZ/Q59XdfTZ6mWB97X5W8zrronjI4zwigibcIL+c00U2mNzH3misCDakCIGBnSFDy+Ztei+xbfK9Otmj3kGA6FS2YeimOxhIHndlYGzTuM3l2Mf/RaS78BObisXWIpJ27ZwMCCnEUKxqujbhSCaocBIcWkvyirgEqp7Ia2QiWiImoJAk1rbjy6Ey9SQDKfbek0WkaFaRjd+4lKNV4FQQM+Mu38JiIS42G+frag7P44C79sieC5PUfj5Ay8V9RvVxn0NP7J2ttAIYlJYeiBURgEuycG0oRDFHsJ5rXy18yvYFr+3gdKBK2GrUUkh1y3nywWIbk6UL6HEo31T+RnQ/qZ7Rb5EfIL1XNu+PN37N1w82376Xz34p+c8oX8T6feXvl/z73ZOv9xeey/GUSIxS7RXzItfM/tEPP2HoA6oArc1s7hk30mS5nDjeIY+II9MxFRYnlQM+SRx+dnq5ekJwSVwGFIioMc5VYQTH0Fpw8hH52CybPQU30LFiUkzC+krawaFtU3+LQ21U/yfBDnSxZ5xbSV3JsEfG3tQBhaOlx7cDkj6yyEYYnbWCNxLQzc6RAaiHCHkwAyZ1UgcpBFZ8jbl1Ngtth8hQPZ7MW2CpCvt5ZDU8Hkq18vpAJemAtfa2HOa9jEVTUVcW9fmide5sczh1baoWVci6+RurHm6Wy0Ymn7lLfX/dKjBUD3ozIJEGDUSCEpBb3h8EuNW6P86dj1W1e7s2qVaDKRAJkLgFOipJ2SIMBlEQeAYATLIaKXkT9nash3zzr0K/1z/8Qrr4AfHEdFurtzy/7fbzabqRy3vQScvmjE3zynw27qjnc0zABjJqggYruzSwG+6W6T6jS7rBmumB9WWw/+Ohl2DCpnwpGokAVRDZPZUyFbDucWIymxBfBW4ZNwmFLEQGVsAA9VViBYB6tApQl9CRBBcJ7ohj0BGVKx1ayQowIa0QhdrBT8Sdk2JCLjSaxNKhZmXR5IaoECmac1lp3oEZASiqyKZ5UiLqSe/tpCFIEfVEztIM4X2FlbMeEgRRE9AlrIAdVZ3ARZyAzNbdMxkEFSBLNWEIwQR0xkHowB1YD6x1qgO2QKeFoTCnYAJCrsckAU6bKlcIqr4iEsCINs8jkQmDpnmrCejn3K4qZQyY1OorJ2pDlMXg4azmqWjLAxNGikAPDAmJVrvp9QDVTqfZW2XP2sOM2uPLK7zd42XNzYGjpgDsQKBgFWfEl/IWnJw4Bka6UoLTiScoR6ILCbTW6uBQtrS+uHtQj9lIXyg01nM/iUIlyFJElJO8+1q+2Pa7fwy9m8p9xFeI3BDMvr1FncnZ9p9/fFYOfZmMmZjPV25tWuqzlXVMXpAnuKEYjsmgHklH4B/D7pJv0yiNFDk3n8fcPQVoTawFioN0EyBYiCA7KDEoFkWda8E6ekJ6Ku9RFRgA1TiRsPh1qlu/6e49ZFvUQduKgEVnteE+W3NvgUIC/QD77TsA1LifIKIHEjEAF9XsAQB0wBFZwNK+HSBMiwOdFTjtgI6tJ3zNkEmCQ/mS8T93hqsFvaDICUrUBnBxhLI00ibpGFiRhSiiE2DIGPXAeFVdlAZED9XECGuGLhMU4KTLKOXg95UwzGn3UQvYSaetWzI6KqJbAdwfrLgHyu1B9tqYV2vx2GTNvKMFK9UjXnsts+YfEEARrQO3Yg8mARKNA59/CNgLHqgNqTZjp5rEIMJsQr4475+u9fgr4NNul1MZUHrE8cG++bGpxM/KhIqAtV1ec9ZV2/KZJ5TO4w3XzREXameZvkvcj/4BLmjpKwwZJkQHTYulsMyFo+42KRkUxEiATGYBDfIjcYeSwAw7BwUeQRswhDkZWnPcIyDbW8u1QJ++wDVALSBZhSQBsyCD7ITkQVe4RJZO3QL5dGlT1YsOklMrwI1J2AgDWM+HK8QoQFpJ4ZgYydo659qnjCgQak9kVVQmB0vtJriE19vdqxhgjT6osqLgUK3MWisuGifAYRnsoYr3khBhjoBk8p7Y1EzOtv0wAr2YBOcslQ6s8coti5DvUPspsRMEnAO9YLVbPjgA9VS5bhlzc7+18c9TiX02+4Eiaeb2XnPO5ZU1yb2lxhudAnqDATu5QRvYrhUGXCXON3kuw7DVV7JZQQzj4Jk3I/dan4Q9zmevpZ1x6sNjNkPixwhKXyp39NC8nxujhcbwi8kNsSmRi/LEmx3uJCYvjz1OAgG7AMZaoKODnTyrrfprQSRwBxq1BsdIa5kkomREQEJsYCM4iN1snmjWV7Oyi+daPLzE+AtXEkEZWH0zEc0GtdZubLlo3Yx1tA50ik095ZwQaeQkJCCTBRggQJ2QogJR5oC3jh2aCAtkBlGL32FUzYfqpAwW6PB+i8E8zV6TOraOOAK3wDlUC+sLaJCptnFSAFnooXpKjxEizojUOsWpnow5gYlzquBVaml3LZ5Coh4EAgrqAQIT0NUkTKKDVuDIeb51WFW4RyPNbG3Mrf3r+yWTmn/H6hqxGS8EamMhjFCHqPXSJDthPDCHLy/+VVog5R4OVRlgERxyOl/lR/dkR3nXs9R0kWneQtFSoH4c9Fn7jh4cVFtfqPVwguJ4CkcZohSGpwhTzriXVRB3vIzFJ8GAnkhSBkaggQA72GcBgUaOwCkixItYnXj/IEyYPm9nk+kJplPGceSLmra75+c0D26e2CWLsnLQvnbIDjhXgOBKLghF5qSZ0ioZsJpUW3E0u4JzRTwiAsNU+ySypnv3YIEBWkNgdGplkxW5mVEGJzIUgSmidwVsSnFkGIyACUKoE7e1nbvmwbM2PkRNk6AwUJ20AQQO5EDCsCZdQkiunQfrSRLGiRSZYJPVVjUhRQFr9vi6nmB3qO2WnpOYtZkgaAWMTBNjTSTjBDoYAYijqnVc96id0XvOSama3VjCZbC73GuxGffoaJY5AipGn71N1b+c0AFjwhhx23AW6ZwUOD6n30SzNa+8srShIWjVpqqpoLWPACOl0fU0kGlDQbi4hpVqA1654g8t8f1k+oxMuHhQDu/ZWkScIbwGbOWrcCVMihIeFp3Xrk2WoQvoAgGoIq629DzIdSA7o6DBWSLfHE9YTn6t3Pq2PfwPe/tJOxsRO3jNfE6cC7YxVxfMuTiXRoj5ZV5qMLwP5wlToJNSilXKq3V3sVmde861BKgBtHpcIqmwKFbGzNGLJEzBMInKoIOOCGENBW1K7PtkKRsyaHlCn6fCKe1KDz7NzOwT06YddxtgYfZcvDajaI2WD8iADVAkgYk8M2O2Y0vOVLKKI03Rm08qcgFYkbuUIlmfkoxjKCF691Q8xJ00AN3sW91zwDN7uQdJFmNkRjLWYsyghD7CHIx6Siw2iC0uX4iXr7n82bbz1U188MfcZZMHjNoagdDBbIqSdyg3/ZjgyAHNsHnRc7T7L7+yHh4OuJAJc4pIVM/xOG+FdEx3IJe0eOVwGYv+CPwH4CU6cFcTqh6GLNBCNfxD5A4lEWT1LjLDiKRYuUrt6In8mBqAN6CEUva9sGZAEKqNYxypC25lm2m9Hu58e7z7e+Xeb+bTU2Qz+7I9DsRWEUDUvVDxba3qQJl1Bxta3mdu2n4h0WJzC9smA4NTn3m0eXz35DduvfbNUyWmETJFZmShD3UReSj2BOXi4S8+2b6+HWzyzp3tNHh1UAkICtgukXmVj/sPb6wf9H2HjAiz7e5suPHh+MU+Mo/ya/YnXWfNYHRN4/Rw+qLtME0IIWLegHW6OCGaP5MYjKnL/SpvfZNS9sSSonTDWKaO6Kd4AvU5rfu8S3nrfUqkoRTPq2EQNyg5OB0ctTi3GzgIP897rZDFbA3rUzfkPA39msgSLSIXwDN8DA0Rq32iEw7YYf7z+QmLh3zYnhRo/bTneHJgNvAgm+BdpIS0izgqm6M4/UfESe93WQ7Z+lkO4eVfBSZorIBcAFA7PwwUMGSmNQmZWq+fPfvNEya8gNU/Lb1UxowW03BvP5hIFMISemFHTlQGkhTSQK7AhPxQmCzeAHZgplqiYrOTHDDQM9IuuPa+m9b97s7vn9/9b8a7H8TRn7P8Wx6jp39vnb9sF2shEWYYzIVSm+KCXg8Rl7SfLupwog58swewoqYfGATro/ej/umdG+/d8XWyCVhqqsKBIl6AZkW7X7g/rWM4B2DMhENWo96sDW/NDTcj4Xj1nZs/8V/cKesucrHy1CZ88PNnP7i7taM383vHX/x/n+RhDVDcUk8i8Vv/wYPxC9MMoffl4gSwAUfKwA52bnbCrhzf+vs37v3eifc5Usm7CyvbD37+B2e/jO3N4i6mG0d/tHnjt4/TmAHJzr1//P6fL/G1sB6lbgNHq1C8JBoXfSVkcpuZu/7i1vE/7G98b+0r0Atj6s6n3e3x8V94uL0bY0+YOEo95hW4amYuzVoPuHG2F5aX21sHnh3MwrYyZBcyWikrH9e3xtM/2n31/7r+4Oc5/Ud9UXXnNDeNDi50qItnQ4QGJBdGxEoKmAOJ0TFkLCJgWaopU1n7XXSA2Q+Fzmenl3PMHNRNNYrWmQGlGa/qIKA65TwlL0jH3jvsIw0/kQMJEegKpkCHfCHeVOo4PUneAZySjScnF2/+1va1/3p7+3u7Y5T+I+veuHjr4frov1ud/Av9xes9gjHAb9t0zvFzaVp3U8G46bGLaQy5RHAybaiJqKd39Zx72+xFswDADEBB0FQKMoF15JwJGtRRJk20tcE7dTZNRTxLY4y2G49oJdONGSgRBrLLCXAvG3JX/GTNeCPSa5YETJHWaTToe9an0cdu9baV16wcQyDPBWMMXS9arZMDbREpc5+IVP0ioWQ2oeet1eM3jz+4K0tK8O5s9fSB/Qbfe+sd/ayebq1Lr222r939o1uRVrGe0va+bHz4tQfjTxnPnD1UzXWpemvY/MlR9tqkhGV1kXO/OX/ri3/nTn+2ii6lYZqOxu5iG/lRfOnD6S1MD5KfBtcF0eoqa0OROWN2DoFwmftmEjCAnhBRWGWzaiO+pBrGaqlztXFGKEyrJ1O6tbtxevHGr493/x/l9H1PR2k75V22LQ0ys2BRQL5GALYj8lx93wmCMpDFCUfnwgOd30VxWAeG1JHblFZKmppTKwwCkqjaywecg2MzN8xG1WdTjC9VT/hcDPxceCEQHZmQRnXnZf0Q8g5HiBpj2IaOwoijP/H+LPQ5+tf59KHw5nT8eHv7b23f+PXtnW9v10dj94bbfdhpd7KKvC3516bdkwFuyiiyKXHq03jSj2/Y8Llx+ByHNzRllpNUHlphmhKCUgandmbu5YHP8CID4ercMVBDGuRkaoURpME6qMAjKCmNWnmkks87iFjXvJkmoJaAsICQUUcUerCod5HxNDWQTGrFOGVYRxhPd/EE8ykzixvjwHGog1cWrbUCbih1doQuoOlGObLV0/Hmbzwqb51dnMCw6cvNSJsuIWnl6xvT0NWCFpAHJYiXFnP+cxb9E4Gcyr387t28u2MrrBLQbdIkX+/gsX53w5/eTTfUgqXPbMQD4/CZmwFqpbytVYwNkgm9rIRZyVmWkWpQPhTBYpG+PJ6cbe/+t2dv/e3hzoT1vVg/6J78p/B/b/Xo63n3KMMRa/hIDOoGoAcKUKANIPJM2lAh67R6V9jiYkWcEQDW4AgrSutI4ZGFMaHjEoD+sdLL1BM+g6oPf9nzaE3H6CWlJ746no5vTZsJ00VCKrwQV25dQSiT2pTbv727/dc5/gv44FdRbHfrm9vX/vb29v3t0Y3RTlwrTMcJZ/9/6v4s2JbsPA/Evu9fKzP3cKY7V6FGoApDkQRJAATH5qChSVEttUSpW92eQ9HqkJ/aD/3qCCv85rDDfrA7oiMcHXa4o9vRUsiKpuSWREtsqikJsAhOAEgCIIBCzVV3POPeOzPX+j8/rMx99hnurXsvilJ4xYl99s6de+XKlesf1j98P+yeone7fb+9IgNUwU/MG8tHljM0ZW6sv1K182b1ueb4tenRNg+v8tjRKqLOpx77s8YAFW24AXr6om7tSLydm9BPt3Oo6iXMQcA69CcneeuAOqqW1nVmPlEMRsLlnRBEI5BdKFENHNhjxlmvCVnsnChstUydw0HJsoeBRAfZNA5zvR85teuyQBNkZrAHAHawva18fPPqt7H8w6+ufjJbyOg62SxXYAufOZdeqnpr9FJvPr8S20OgYFEYJEQphFmsT+r5N6rQAbvwdogrYl1hEaev78SD4+oFy3fdY7F4+zol7ewCwuB7LGG6hfIMQwB9cJuAQZYVpeZqao66yf1cHyF2iDmwADGGPm618+8td359cf2OT28FI/zEn/t6O9H0g7/Q3PvMfP8k5BVTg9hiMlcw9ESf6QCyWJEN1IEzr+8qnoT9EuQQwCwLsirHysNdT1coYwl7+hNoT24d1Wm+rdbk9ojzLXq96Lbf7bYm3e5bXKZYLW1x1bFCboxLdwI/ojTtZ9/Ou/9QeNnz/XbvK+3Om+10J8VKug/PQUac0FtZrWbinElZOAG2AFFbwEJMdNLfqfrltP2d7mQrHXy2mf6ZKn7cjp6NbUtf+ljJ9ZxtSwIQqcqVUoqrez9wtLyqndkLW7+3Hd80swJ82vd7+wefP1jEBdrD9prJAy0Qjl50+bQ4JNZxoSDMfLB3jELSdCorjU46SoHDAqksK1jr65kewPrH/e16vjU+AgfgESGhAEizh9U7PF5d//K1xSfu2DMkcug8T80S4FZ61Rhafvq0hn6LR8FGVkUgUF6H3ebBdPfNRgFB8ELzUzJFs3ryYDp5j93zWHgBKS0R34Op8qx/+TTd63Saeg91qptUdbk5UUweD1AdqnkjN3dXk/dTfYwgRgRLQCe8lCyuJgftFN30VcSV+bs5hnxlmuJbbn8fPKzSj9XHPcOhmp2867DfRst4/ImgxiRHBI6kRsbU9B4PWPXWzlG8tUSuYpotc/wK+5dD+rTWnOkSbfNhZtjHak+NtnYqRwqv5yUEKRGpyv0kL/d+vd37Xr9bh8UPVPcOq8U0tASWBrgnjwn5hzJ+fDX7e6uP/V/dqjy1VE2dzvQgsA+akStDAHYolyUDPUMwJzxAYeJsDdfpNyzfc2u6aQjbv2u7vz/Zfn0yf3H+7r83f/BMtZiVuE2euwcUkKUOEBRTxmL14tJfVM2r9Rv19HuTQinqjpc3/2j5ucOjPSSw89x3krsCVMtdSoPLaSiSRxIIqjiAuZSrlgzF0RWv0csyyiLRx6QJbaTqOgbBhWJGXtsxtLbeFxtXBXVgNMy3Zneu73zpRL+IeluWPMlUg6XsKTHQ8Gko+jCA0bdeRjGkNpnQ9Ncnb+5NHtQ2Qcje1a5psJ5swXorrLYnb8z717q2SjkHEOciJk7hGUdxWFgMKENurvXzZbvbrbbe6He/6pO3vXmAuALfzbFtY3abEVtENPaO3v0PHFUOEw8ROmLukKYZu14f+XaMdjuGX49Ifvjz0JYm3+iu/22vj+v3PtekHyAa69ugSu4u5ZDbOcQlm1AtJ9AdwMjG66rbud3Pf69a9Fr+sK2ys3paenlU+74gD8+34u3U6ZaigKFkPOP9D7g+yPFE9SxP6zQNdZ/MBUy8qtL0Xmq+nqp3umYvTbc8GGIEluhP4B1DAk/ASRbgEeioCEzNIVUe+qRnOk6clem5yC7gLdin1bwC3mLziR5/aItuMn0WB9vEMRA2PYjrHRYRYCsC8Km06BOZqroJ/cxgvRRJJLaLuOxO6nwUsrvUlZ09lItvndYR9UbGLAGWNCjD5rQwe8kQIte4LmIJfBjIs2S3a8MIpvEUbBqmRTrhFltgXsImJJEJVs262c6t33tm/wfbZho9Aj0UYW6WR+Z5Sv0FeYNr98B43AUSMUzm8WBr9sdbdMQIX63aWYtPblXfrIKAqlE7335rt71/P9zIdmKoUEyu5zYw623AWhMmVTHN99u93zy+/vbqyrvt7rd8esxQI8yhPWfXhwQEyzC1oHsJadASiuIy6C7zDLoOdkDlddthx/QB0t/ttjrDxxD+fvfMb9Xv/zX4n4WmpgdF0jszYB5yO8teZx50zJndKuRbgBBCP/sgTRfgPapXb+f3Yh9R+z6Tesd2upEfX4uq5JAfE9s1f0Gc5/r/I36tq6/F+c+lFGJCbrp+nlZX31le+1I//26qrvaYCg+YD4Kv0EfDzEP2EJ0xe/A8N68C5oZtk0Mh+3sdP3+MHceDCtu1f6PxjwX8bJ9/ycJvRrwX7U5jWxN6gz5CCYNIwcZwQQiBqgEHa3pyMYmxN2NbAWYGWPAK9JByn9qMAFQRDdGLPSRjAKYjksuGP+T086A7dmCf6NnoogtYL36pJPOORgzXqY2HOBUjXvTZktZHBKrygBjggFY57cBi5H0L9RVrd6uv369vNf3MLIMcMv1AALnY/Ac8b6x3nWv4NTkSEIQ+VlfD7enW+xM2kLxPD9xup1dfxdsVT8DevJpN712LH9wLN00BdooHt950EjhVCUZ3iIypYbv9R0cv/Nrx9rvL3e1+Nle8FXNF78jGeZTRmdwEKgo1GGUnUrYMYgrfJkEeQyl0M6Dp7chni/YmY/f/itYGHdT988F+ommvNqvvRjrStT40TiPp1aKdP/Dt74bub4cK8fCTWLj1N8mlqre8fh7JEO+Lu74OTP9I2/cnCXk2QRJnlQ8AAn07tktLZvpCbm7kyd9NW7/RpU+G6nnTYd+82W29t7zyu6udg9VknmwFPyCWlDlmYBA7Z8h8IduWFEG6bhNvmnpoQjwf8LPQ5+AT2YFj6TwSXxH+JvQv2P/dun2nOf58c/Jn6vaK+W1od4jP2hzs8LkFGrA1LcHkmubCRBDMK5iDnTHAY0bMmEkrDl5hyYu1rQVoCD6CxgmUKNGppFOvSC7xHiaLBSf4jCHSOeaVjPu9sJF8U3J1hujxdVY0RBmwAhpAfb7S52vbvqD122nuW79r/rnGa2M7OLxLPtHFBTWqxevgxELzJEKdp/V7k8k+bA+eWnAB3s7Pvpy2vbptWIHzaTiaVndi7J11ZtIGBQ5KOIb0+41tLWXwCql5NvkL/fy5bv5qbug6Qfoj+tczf0l2LyOSmKCSnGrBBewGtOsQ0QFbUkd0hknwpXiSMenDtTSv+tlBDF2VJlhW1dEDhQfQLtotqXMsMmds1E+WHjzbsea/mXkznvwZ4AV6F1IfVseIr4X+xPoeaYrcn1s047yNIQhP1Z7CRbHm7GfNixr5qzTmxpMkw4JpHhbq05GHT7U7/9Nu/qvLq3+7jT/s4duperuf1O20TXVKoYbuVtohKplli9lSJnN4RnzBNQf/INibxjbgAdVSPxrw2ZqfBV9D7rLu0I7NfpzNM9DKPFbLH5ne/1/O77w8vX0YHxylbhcYs102I/dP7YIJxe2jiuyM0WnynD2YUHLJgszNAjpRQCwg+gPqDmtCjgwkMggNcJI1j9n71ORcowgiyC0F1mlaVblDrRh6o8MqwBzeMyOLQ8A+1zjkxXjoyk5ZKXakmu7uIVtKVKUacJe1OngTP/nyAtWVL0/7vcBqh7+PUI23akJ2VKacS3YlKjBREoIQHctAGWP2YXFVMVSTrrn21Uk3xyQpe+sBBy+ezLaP+fxM361NMtYem+2vNw9+PIWtXjmDATAIdJbKobIAH9GiB9EuyokcjhRvKf46w6dIhvw/YfpXyqmz/YQf7eNVQpmY4Nfr3FA7tFezfZCxALJwj1iZVxUUWRMtcgbvyyphluItYIr6rk3/AXf/jPqf9IWz7ZEbhJy3Znn62+z24+FOff/Hmgd/1pbbbI/QZVvW9cGnvH2+6t+w9graIzSTUx1iWDXF5Pav11m/blxbR8eN9jnD3binnxhO6HXVxsn+UriVm8/227+x3P1/t7Ouq65nO84hC8H1gfl1oiaYmbPVGXuZOxm70FXwNwOniNegN+VB+MHkP0F90nS9UmyErGuwq8CuITCnZvXOdP/nZ3d/aHr3/erBxBZT9yNgTvYbjHi4Ea63sBt4ZECJeivgYgVKrDdmQmSQMs/c/cgNFTDWPxyCrTOT1319DO2AFSxPMmaT2y+nP35g116OvzvPFWqDLaE6e/Ruu/XJULJ4sEyCGEHLAUNDOLUqdGkOUcwVYgWTclrVR+3x5PXVp24tv9XEpRnBCJVs3RrKTteYnlQ0lrVh1MMhvUDhlxCBFGGs6hfCd7bqkxiLaSibx2m1+KT+cId3jEFsaGyyTZuj6+Gtk+o1JA1pGxj5nKBzU19aBnuE1UvV4mP1sef4X2ByU/xx8K85Z+LvZP5ohgVUUoQLvjLdBr4SMJFFR3S8AiTY+66ceD8oQg21pB2DLXyeaF7dytt38/V/kuLJ9PhH4+JGWFJx2V89Stv/vbX79eG/Wz/4QnW4pUWP3HhMYl0tnlG6FnwbaVdowbThyvnI2vdrmCmzfIYP6Myfy4UUqymdcXXSHF/P09fa7W8tm/pk66hrDjMCuxo+E26Ai5UdAXuSuU/FT0AvQVMymt2TfVIBjm+430O6Abxi+WbtE3hf23Gyu1lLx1fRfa1a2mT/J+f3vzK/UzcPbobFEfrWbAu2XEOnrG0SFIzwkkFecl0x2B5pikS0BBpM8CQOFhVgiMY6o9wKUDHQF5unQRmi+/XczxAcoUfs6pRv7LxZTf+ucj2vFpNqOdTcUsox9Qcvrnzq6+GdGk5KLVFAGZ4hSvNERSYCao5gAgLTJKldraZvL1+y1Y9uPfvbW6EHa9gSSGAN5LLtZEkh0GCfGaRkbkp6vmTJG2NoYpXmcXvy3S3raQYzBm4D1e6b1/R2Y8FCi8qAjlbPtJpvfSumT/oxkopFigURZEBxEde4yCXlnQnhWFP20DXpb7L9ofbKd7rpH/fVq7n+HHQ9Ige8FfxPz/Vc9JvRv2r4muH3jbOAK9mqBDmvgtu95p7bgBxQBWTDEp7cS4XTw25n1tbtYu9/mJ78XnP8YnP0WuDH09W/Ay6a/Z+s939ycn8rLvsEet2mrRrVu5av2CoyHMO+karnUNtYb3GDl3wfimhp3wcR6pK/dZom1jqpZ2CSQw5k7A2Lk3y4vZp90Xa/4tMfztXrOXTEs4DJHDwk9+Efh6ZQFfAJ4EWqCaoCXgOuGCPws653wNdlcsjzrxl+mXye/Cb9O5b246Jp9n9o597Ht+7Ppvu36iOy35LcsNzA5j2dOit0OGSulfDJ0ThI0PK4igLUKDeiGYfN07Bw19s9wZFMseTbECB698k+rrWL6+3O202eIewgdNb4VTsUMzmBBaiG5ugeLLzpDj6u3kZgycGNVsKHBRAVscRQ5snJHJjAHPoZmnooukafdMu0qN63L15ffWfWvGUysCl0B5n7WPqKGpEZwdPbdihCjUQwVbHbjQfTne9MQgcLQA1GGibs5S28kU+pAOtgoaHPtt9tlissJukMjhyFdfTdeDHCis030Y4jcB+YMv80dOxXbuUt93iTXASZOaI35h8Q2+JnM09g18BfM94Wdoj3wJRtJr2QvQl6t8JC2A6IBLIawdwW2djHup+wnx9Ptn6n3/5Slch6WZ381frwFyf3UzjZR5oyBI/qd7+uyf+3uf0fso+YrXJ8C/4cONuQhEW8fwQi8SN0UZw1OBYm54AHIKg6AmrTNLZ9sx+meHnL3s1dZzf+3GraiPvOGqGjFJQDXjZMiFRpz7BlMMOE2ZBdvWU877gqWg6HtC3YO8I/dfvz8p9XDlz82uRuv3V3Z+9uu3Xwoq2qoDtZOzLC+jEN9NQzsdY/S7xkiU8r+1mDBph7j2ANenI4ULGLoZFvAHMUg4oPsq9opQYvNhAqt2lycPBz0+ofb08eTJ0IDgqR1DawhDfIyXnvsFod3P6he/0PeGe5pDYAHPzdXG9iQQFTMAkLhJBjCB6HbbmCeY40uoc2P7Br+4dfjM3hXn1c+QSMUA912Sg3jBjEo45YmHwRt1Gi2ypi4rXvxXeqrfdjmsEaoIcv5eiZesQ+LKtcz/sSb6tAn87uvBBf/3Z8zVoD5KOVVChAiaODk+AIfh0E9A1Pguk+vQfvA8+I/8Snv2/2cwSCUqWFae5EG+H2GYTtwK9X3kmvZe126hNbR1Xhp7N+L/vbxorozI4CQITKX4q67bifbdbOpmnSrXZX02Nt3ftCvPcDzUEdlydKU5GInaZ7afeB80FFQKscG1Vktw/MLlhDzlIAz37E2SMPaU+eynRuABummVOky42Ls4Sfe3QENyEjtpwc1lvhZ6D/zuL3In6pq7ZT1bojqAvyoKtBZkgRlUFENhDo4MhaEV3mxO1VqhWbHP+s5f89u39Qrf6jenmlPnhtfne2c+/T84NcdXdit+2aZ0sgpC1gAY8oAR3jUFUskONtjEgjAISM/Xhk9KrvUC07xH062ywv4BRjOoZtJJqpLrsmh8qeMuU+Lu3tyUvVnc+trn11Pr8962PjE2MCshRStlX04zQ9ufep+wc/db+9bl27dmZu4lwWc6kGfG0nTZwAfQrdgqrbHqiXQEdPuco5hK7749Vnw4PX7dZXd/KiKjhFPukBua0rao7ZtmUXX3Eou92SLptaPJzUfxBlQIMs92XbT1fdJ5fdtEsx5Z0mHoXt359UHQI9zSbwpv4O7dOAje6a0bm5vhcf0ZIMAuhQOLa+qo8n0AT2c/Aa3mF3bzX/Q8U+4HliW7aX8C8y3sj8dMAx9O9Tn6FeCKorLOW3AxuiDgzATUfIPDJ+jzwKYEAP3My8nu1YdhwU2b2C9Fw8+GK9v1MtHljunTOYA4L1edI7f8DDDmLXzStU0yq3wHTNCD/CbeFH6qwHzurKIBCQ4cz9REAfOpioXCVsP4i1fb6e/3cn9epk63/Uc0a11LVQyhdDQIQHSQW6kKjASO+I1gzCBKnKllL4Eeafmj/47dn9r8we/MB0//nJ0ZV6cRT7DN/pWCscCo2U4V3JreeGxb8EVdnoICvmcw4xJNSKH7zxpw6nd0OoGB5APFY4XO21SbHkGRQh4gOFjLhXPlisSbl18tTlfLD1re5nbi1fnG1/fTJ/v6lPmiobEuitpePjZ07ufeqw+8G77S0/Yuc5MhjGKksoMwkVF4XM0AM91Vju6rZf9bMDj1nMYdGlycJpqYOjzTkdze6m1+LWB2F6rxEs9M68spRkKOhTGwEyQpYyZDCn1ZYZYtrjB7j2TSh04cCpRWiPF9feO/jC+yfPdV0TLd2YvK+tr+3GE9qBGOCRV75d3emXigmwATYDwGmKvQnIgMMLeAxheZtYhT42xx39RmhztbgZVy/7x3612/6r2X7F8jSFL7v+leeXKItpVuNHK3ycWAXljK1Z3hMNPBY/C3s+UR2Pkl3P2HdkY4LNkp2QR1FVXM0m96/OP3h+/sHN6f60SnCirzqhqtKM/Qp2gHjLm97raXfljxHerxbPQIfQ1YdKwqdtT5VZvzaM8tRhNbz6mLx3+pMKdHovCCGCkDrLYdIz7r/G+SKE/5L66mr2H8k+o4KtBsmSSm3ZgTZ6EkQHEKqRe/AeTKG3uPD66Jfmdz61dX9v9uDW5LiNKzcnfJbDUpbFCNQo+yiFc9UK1otjjf62lvaEcubd5SvV6oVlM6/ZdqGerU5O0g7CnaBTIKOy1RnUxZIpo3gagOnmQL9aIU3emXzC8svNyXKX+xW7odZ90r3+xkm/rZbe9R2X9FkJGd9gtqO2rAyYEKiKiO7Lk7Q1v/MzD04+c78JlR8f8UbVHj3obrlbzmbL/h1+tn6faXqHYVahp+uwX6w6k3PjUZ1h8K4MVEYPWHV5srr72n5oFqH3vLNMy6PMB8fX81FM+chDfD89t/3+57vYICaGPsiWbWcpg4CCl1TZTdzBsZ2ZPfaEw5LlUK8+oK6Ebg/5xRz+Z4vuRZ/+nte/Cv4O+BPGX6bejfpzQQh8QAicBGZTBrKLjpvg9oiCdRPoIQfdQWIVfT5tZ/OD780/OJrdfq4+UFgtCn6fzCQX3a33+L08eTtvdfDX8vTXTI7wS4V/PynE94e2p8iioCOzxBUSMJgIz0PeayZFo2Re7j2XzHcoQJYdYI9KTjjiYjl/9zNh9Tc9/Sav/h/a+WdS/CX4LeGG1GZMHVuwJYwMFrhi2qLuqq+ybntc5cnOdNFd/d7rW3eeCctX4yqFVceegmcGhH4o7y4A3WCHGBfdaHvcsJ9TAHUa228AslJI6MiYT5yokFqx0r5UDcVe1vtzYUOart1HMHg12I6ZcxcWxMpam35QtviGwdOYGXNKAlyVN2AuA9/MG82bngQkwYCUchXb7kG6fqd/thSyZykkkeEpGYIysdD30g/yeEjMAKFMW3XKq8GNN2gAQxk1Qe6xRDWkZIcn147bX36zMhADan+GElLOVKMMLvJ3+58rAHGle2Wi6yGMSJQbFoMzqlKZl+LKdyGUG0Cexq61DOuvhJPnZ3tH7Y1vr/Z+v92+mepfQaDhFuFQlzUBV7CKOKTP4L1xBvRgU6EJ6mpNXSGjzzlCfVCouzA7+J35nQ9m739meg9s5YhGQKiynEgV2kmd6phmX7Zrz7O/B4H9i0BGmMqCwMEDOtzE6BzgCPe3ZmiP155KHd20DQ56GAGTJOUBcZkR1JBcM55mJb2gAHsymffxZGrVj06OrqbJfyX7R9F+M5z8MPKrblNxK9sVhYgg2mHgjDlhNVM+zJZT84Hry7Pj5fbt/9XWBwGekZw5wkdMEpyu39MlwFMrxBg/PbSR/DZnrxjWL3FtrXPKziWXaex30GdBnNpOgwsu9HkDoBoYYFQ3YmSG7KeNhbt5HxwV1HXrHb0DfTeeeGqqJiGFPhPLcz1pE6Jz8ybWwGiDQiB1PdWTy6Qh7rNUYvS1KbVPRDIs1xYLrfvnOLnCmattysRx3rV5nAkhoekRFvuTxday/3Ro/1Ournc7NzU7VNWD1zIW8iVAsiMbyegYuBoT0QRNAjpHEkLGytILsf/W9Oj/Mb+3P739Z6cPduNiWR7D6PsZ3yeExS7wGXYvhu4l+C9U3TX22wgfpRa6bk9DhEUDHT4IPpjwJQZJUk9lIiBGJrPsLojMI0SIl+jIAGdAyLBv0/9pmH5pIq/uvNa8/9eq4yvZDt3uKxy7JZgb7tGvQA38Wg59nn5e819dNr813f9CvbyKvoI7ChJ0GY50msm90dbGI2xYUsrdbDKvDW62ccaFUORL2yZwximFD9M2YL+NoxpeL9I4zvz6XD8PM4rb6SlY63mbAzk1rl8w5J27vEbre+FTa7NN4TlFpR/KH566UjaY19n+nmDhbjBLADDHJIfqMMUUwvGtsNcsr73V3WC//aLHbwOTrAq4QrWwso81hI6KyDTv6C3gCBUsBu9C+/+c3P/q5O7x9INfaA5/ZLJ8n/CEZj2hATDBOoRD8N3/UPFedfwcctNPa6DhMsHCELZ7mh/yEeimT4cxw82nKkIRuepzBesiRSBTpGTq4RE+IC6VLB9jicUo9unI1FuP6ds/SX0unHxxepvhJAp7blcV5DRwBvWWO8jcam92+q3a4zdwcqt58NdtNUEeIKKKMWXclV4CMsAy9nPENAr0kW0DpfzQsFp52XQ/ztSf1pcgMLKgorGesrAL0Tun83rxSme+uKTp7InlxvJFOnyEaYGn111TIEaaHJ/hOFccb/MM8Z+50FOIjjNPJqimTnA0Q7difxh0f1V9pcODXL0i/1kuHR5YdTBXAKwma9MR+8QsSzNY9Mk3VP8LhN+Jq93J0V+Y7r/U7HfNyV2jZ+5Ry3VOZjBQCA6sUN8H7EpcOHDEPnoE0hK+d4EH/psgQmKAVwMHlGsFqfY8a3K7DLnNSw/Z2FWWyMw8FB1iqW/EoSgcBJN3nmM8eg7pVzxOkBtLR9YTaOGgGiibrYAOWcgzx0IhyWq2v95e+U7zzb9s7Q+yO+CwVsZoBkVYBNL5lcCRffDcDa3fnf5bAyMWz+F6y3eqYT1sfoRzy2jjFyMDGINCff2L8SjO/HLz/5n7uKydC6Vfa9e2MexNUrkwE49qmyqwzhLbBnLz6YU2s0fOKSOPJsszIxKQQwBzTEZMwvGsrnYnky+f3Pw74Z1fsvZPhYMluvdJISY1CdaBLyEfhdQzAflIsco73+53fsN334irvbr70Tq/Gp0Ak9XAffkUvmGWIywAQGgDUFky0EKKYKkkEPxDnv/TtKd1UayXiEnRfZLzdp9EhGkV4as+MkukYsF9Ggw5g4maBia4q4H39C4uopCYVrRE1gAg0VtAVBQaiNAyKMgEnzBb89ZPh/2/FPo7oY90DhDNw16IZ3Z8FyWN1mtjXJ86PVxeNlY0R4CvIRNu7P2yx7DOtL0wWTx33unP7cKRhxLJQ+XXaT8PO5/j37o9rKz0wwgzbHy1np7NCcXZ13z2HHzYwr3kuiKzJXpj1cJkdSseXQ3NX6z+8Ki78p3m7iru37LVIeUK8IkUV/ADZljeYXLkY8W6P/7JfPSijv6bfOUbFX+rWr1i6UXwQKrAvYKbXDBxym14qUucItCZEsyDC5k5xtMaq4+aqCduTyEJC2/VaCNArpzMtHcwsTzfTidb4bgKJ11YemgtpmgJcHhBZHfRKaC3LNTRIyEajT0CgT3jMRThweHMhAnWDgyXjXgc/FirV6q3X015HlNrCuO0aHTYCeilzRjRy2TYuf+b2t+mbBx4/RByVYLaLm7jLszRxQ8boCAc7BsY2dLmAr34bNfk5Re+2miXflmcLzz796j28Dvzs+S05mTnRs4zn870eqrffti1hh4kJC3AeeUySVjG1X3tX+Hq39PO/6nqvlx1P299iyxZSAriHOqYGTwzix6ANnZ1PnnGD/4G3+lCy7DaDp3LJwJhHiOGCN+ilBIinMjojfKqCrSgkm2WyXYDZubfHBHidJ8wxDqTSpUjHufJe2F+xOWWndwIi2u22KvbSd156MTO0bk6sVPdlQXYiEsZzSu6w0rKzhEQCxUBgAK8GHQmgAMrqoGD3sAj43csPQNLI+pDmZ1Ce2kY61nlcP1BF45fPqdrVWttueHp62NN1dg2jDDjcxzUT+flRHva/FIxd75dPKXQSdz4iJFs9GFdXhRfmzS8KQryhgA8tzPc7O1J1+54miZgpxDkPdNErnDyAP3Hpn/01zC7bRkh18juGZErYQoPdFItAfMp4KFbWQpazcAZHcwtZVBQaE85MDcsamWwLlqwQIae7N2q1Fhq6GMG50fYnk4dlUlZoWSBZ0SE5E2gRdgK6T12X7Ve1s7j6lq9eimutm11JSyvYWH1SZ4eMrQrQsoVUUDjg5xOgUH0EmavoXyBSQT6AcJoYOs90bO9qtBtYMRvsvk4Jm4X7rtWUMEBoDcA9KE8sgFpdPltcvNN0XlezdzYsvFURYV0iUd6vQ8c5Oyo/Ja/arRiahDm6543etoQcxfVV1xGM5du4TaJxDa+2tQnz0mw87dz7vWUS50ns8tluza+2kB52+BRp6eSRCWCwQxgHOaya0xH8Ne4+hSy++iMZGrIRA+QwAgAIZEAqgB46gavTykZV7ksAkpwySSTYFkotcbA6JmAyczgFnJTr7bfWW7NcnxhHN9mxdfvSyo+jbOeI/cW4NCAQE+hkmLQZAJ35iOmd0L/Ztd9ObRV6KZhcb0+vtEcvDCPr2rVTFLrOfTeKJsyKfeCHj/Qj/sQL4OBcKyXjCraAwVnqfrAIUkXwOlaFYA46qhn12vBsDgvB85pa8KgdF+i5F2Y70I5MsDPRHyeO7Hwj5JdsfHVaXHZc0pj3ny4mzcwvm4u+nMEubk321Qjzx3HhR9uHjnH78+T1mVbo81vHyZp1xR7booiBtjWgfsOMYYl4GgjD5hiqZRFODxLiVbAgiNlpoxh7uTr+rPCgEZdahECgLMUGfBGkiAzL/FLZgTNOQ1V4tStloUH3db3uhvfanc/nusffsh9PX37PpJ6S1hMERMisilJpSYlAqyxWrk66WYN1Vren7TvhEVo9q/fmLx85WiOdD2naetbqzRr+0mbJ0ufdXlibc45wIyiyizJVTLpSA71KNewizbg911UL9flOAebTSgar2vp0IYhZ0yqIc+pmT4C5Wze9Pn3pzJTPuTq2AUzZ+kinxV04+hOd6FDtPMgeC/b45217T5MnT7HdzZJ5eEyafwjLxpsLhLb6RUf9t3m+M+ccyYWYD2HGnG6wbX/g4RgHoWh9BPooFg0pVRDoXicNWSAUnBHFFT22xDcWaLUxRYEJMooWiJogmW4AIuMIVZRFj1UyWJuQrsVD8Psrk/aZb3q9t72Z95N02fUPdyk9bTtacB/NVbqBYZSlwPn8lCiG42908HaLbk5aAaLTfKqr7Daae/d4H3oj7PHpVddrvrc5H6mbt6lWds92+damnWYrnyaVGXF7BUhupgdGcyCBi6X3deP1TcWg7AuRFA+pkEkDMWcOQayEaKogbbLuaeIYNyc8jW5AABsyJIYvhmJZyD+DZLg6VRv9LB+XauFPKsfhk2RcU5rvKxtnrV5iXD2HJze5vnj567wUPXy4W1TJl8iCc/K8/VgTon0PINhqWayAes4Fvkx75w+oKeOOhmYgTjcP2UCoYCCETJDwYAtj41ikNGzWcW+Dm0djpt4WFX7MR7EsKyrNlQdJl3XGOpZ2G7S9rWu3ooZl7Cp7689cSoTXSBkLIt3mDkj2QruTrEWGqIjevrKnKDDQpFFwaYTm85iLuxrQiVfWjrW7C5KmC3gMvfoaZL6aern2We910u82HvVpkmbpm3fdLlxD9mDEkskqsFNMLgESS6HqJLfNwBFqCQgGIpnyNe643kRMQiJUrou2KaaO9DEwIh4fm2SYw3Ls+qWLuOfRfau1cJzP+xxhmjWy/Icbaz7P3cXo+C5RIE8faszxx0YIRXPt4dT4ClfGQXYGXX3Yhc2xlWsb0wjMxptVgPCAZzIQQLRg35aytAgH0poYKjXqIAUAOTYQkaYMUQzEEY3c1TZqhyrVId2GheTsKzCSRVWTXivsg62DGFVx94sKziCB5u4Tdy2FkFtTDJrs7fpDvXRZx49ZS0KaowGBggCNTGFzHTiyiqV0EspFWSpFNZ0MMGcpmBOBFKNoZGZVYBjQKom5FAnLXO+38tc7GVd/FL2KqVJ381Tt5X7ueemz1Xf3swepEaadGx61D0qV4DDYe7mCqXCNwr3GIwxBOADH4XLKpXqS2XXIYEOAxE1hL9u6I2lOUeQi7Pzs2k40RDHLWEjmHnsRxs0dW6Ph+FZj5J2Y0XnM7R5etKlxAk8jAjPn6lxTANfHSXwmNY1WrrO+ktxKeVfdq2LR88Jfx83BRiz/mEGNydggSX/0EwFwFxwK6qlDVsJzzB6DpNgOViquZhw2XAVsTTrbfp+tL6Oy6paxmoRqgVCG0I/5yQaQBmtChVYd4xuAZYzld2jWQikmQNZ3Yd4p56qPXkq06DCSV4S0Yr5ZAZ7BXDHG9JSNGEl9cOemgWhpcTfF8zbPOTHyU9h2gIAG0sBGRFiUJTDHUrQVHRVS69O0vy2QC9GrdBKQR7klXKVvXKPLvN+O3vlatxn7tOMOiG6rNXEPRT1JqFymGvgfgWesBRedFi5hHso7GYskTtkWkBjyLwGegbhbsPxc3Thp+FymwYR4cKZY4c2pDoSI2soDyB4P1Lp6YrnBkTwZo9nhdF4ftHVihPoVPyejuCsuqwLR8aRn3Z7Zv85AtnVuLSdqQFy+itjQf7fuAvC4O4NCNVCEKMPdQKpwFxZV8U+hn5mJxMuG6xiaGP8IIZkaENoY7W0uELoYAndFpmjpUg3EIyZtWxitLI+xyu7q00OsZGQPTkbhmm0HKwN7P8E6sE8nbN+/cgFIBEUJtKLjk7+prAvJOcRuJSyQiE9edHtQTE63OBDkVQVdW+NmRsG7siBgMEIEEwFQdEYh0LSA4hNjSJm1AHdYMUW3N4phaoLLLgDacyKcIUMQGa5kkIW3atRrRkjc0UpuAxiqYMlhaLPFqOOi8RQv0UeoBBkkvUyV4gy9+AK8kCYZAX5u0BsOylZOZ4RBxWuZKLAHAYg8/TRjBkeBJAV1xxhcNgWqKaNcwZsawCFOwDYOLIW/lrXg7E1ba3V4+FpcK2cX1h9GvOWARAylQTIsZy4uvW3Z8QfB5YGlCIbRdwiMpEKTCY3uCGDifDgS7NsobfYhlCIqjVLFpchto31MfQxdNFSoEdLURbpoejVRtBgAWgQewhgXINIVi5ncgsCx6o8dBiHiu4uzABacV+ZB9bkrTUNfITtyYiwLMYxla7MfoStAM+o5VOZKf8K867h9zL/SOFbwAK271YJPWwGM0Nno4+DGFcCyh5tDWA2smet0aPWLH7TD1HkRoB6sAFWoENXoUPjzOgVHN4gGWSqHkjb9F4KGaC1kRHVcVLQUDCN2YNXS+QKdMu14so2KHNEpufaACoqaQjULmUK2tAzTerQItcrS1mhAhRa5hpUEBHbvpt76AMEWe+R9CquQrub48oh8yozd6A8RHrMtVcL5lqxRbvj9DVgYRV6Sw1kXi2VGrfkoHIFmdGDjKFTbtxDsoQ0tWoRUpPp9Gihz918SSnXE5JIScEtBWYUiwYdUAApc9Etc0BlZRJlmbmCLJMEYnUcZAmgDPUxPbiCeYzMAJJleQSdHkDPHnPoAjj1wNC1gFuSQqhOpgohVymusmV4wGDHLBDBIzuBANKjlXrzZVkSpEHN6Z50HTM7hHuWqlsEetCBBNsDlkJw0KwFJh17wCrEiHaFWmXzQhM8YwqQMDKT01EIrHe/w1U1uu42SObD25MR4ZASKmKIhuJ4ecJboIOuETeoq87Pky9KPwW7Df7X1AlgwCGxRzQlv+10fJt+43PtnPJy8RwCyqABGTQwQguwW4b93q47+8r35ynBrxAz2tKNjkwheECcgm6VORSS4B4IMKAOUCleFGEVMMrpEi3hG8MwVNyQ4kD0OWIH20KotrSEEqwGpghLqIEaaNVMAiDkCBCxBedQwCRCNUAEDRgscKiACVQIU9AxOxmMFzLIoYTGYQFMaHogwgG1ZVkODmvehk/BHtwHOmAG9YPaOP9AoGRmCR7hAaEbnDcyMZMaJT8QV8izwapshDpIJayZeTbgJocV0MBK6TKHKhihClggV7AENTAvSZrwiAjAkQHrQYJbQAJaqAIN1oMGr4HLSlKHfMlqOLP817rC2uhVlLIW2AYA9IQF9EQFNBnIaozJsBqNbw7QMclIjhXUEwCyBh/juudw6cJ8/PakRAiBTomiSqkTQqQzWCdfOubACSAyGQVegU5MD6A6aMu0omjuQ5GRS7f0T3Q3hQmghxqoG6YjHt6L22/XP3sYPwPsb+XXn2u/eq3vYt4Fu/uVtXZzkvtpfnuiVc/qQTUljm5ox7CEAhSgOMxvwQM7tR2sa0GcHfNm8wiugG3wEDJgCifYATW4KniEAIaQYU8gQIM5eAwIauAZmsDz8ICZYR3YQRMoDqsfRdGqgB5WrrIYoh5FWAYdbMEIbRds7wEknxVCBBJ8GzqmN0QHTBRqhkK9VlydLFAltBG4cAbroSUYQUAVcgVvaYZQ7JbzYRNhFRSQa3AFW0IRqQF2wQfFrQM1wASxQzyBArxB3ka8BwVwCWQwAh3cgAZoLyyRzTfj9ujMIsUYb6iNHW8AeqABAFVjuimJYPCk6DgBdgQDkWkZ1sGBPiM4NKwKT1KSbLzkmcS4i+N7zPak6igEGFV2RMQ6D7v4x2iYOfYNvVQbM2yHWAhGNEACDKqBDE3B1QiL9H229aQLqmDtUeTt+gu/vf3vP4jXKb+R3g+YBfzmdT9yy69P/8ffmX7mY6s3f2Dxd+QHR+Gn/nD+I9O82PL/dq4T5ML7AWjAXdCGkf9MrPVDuAUTQnc37vTGrVxPcRCVha2DEJa2JEst8dQ4tnKo8jF8Dhyv4uIkNAnVxH03HyDtQIICjLB8GKveFlveNFohzQa/Nrs+1EtzcFX7YoId5A6qwABbeqiXIQF57sfIAmZQDUxgyzaiszb4/tRr9hOgW0R1driDbNqDr/U3DiDGBMwRstvyCEisp3ZUu8e+ZI11Hnhs97IpogeWGfMq13McOeNBFai8xxN4bqtl4o4pNViYL2DpXtyS6qt+aOyBHdjiMKSFXcvsDf3Mt2c6rLJtRFZgw5L0kMZRjOEcHVbAEphDAFtAQgQTbQ6tTDRRjCI7U29o6UlzkwGV4M6QYa4TYQlIsJFLYdxFBz05+ZX2xHtCo6h1cVkV6SBkZy3cAuZEDygguTpAYucGs969FQnWznQmJ3TzAk8q1AfN3IAMGFglLu5Ut741+4UH1fXaW7rfjh/77uQXav/u1fS9FcOJTW5Xz273Byd2kHhwL974+vQLAenjq38436zVVEyeJfzlnMfLxpM4vt8UjJb3w+5X53/1rcnHt3XwhZP/e+Ovr/DK78z/Uo+qC02DVeV97e2t/t0X2r9/q8tuq3eaH7pT/cxR2L2a7nyi/ad7uMdEKCFwWe2+2fx8a/GaDq72v7GjDA8wl+m96hOH4SUwb+dvfqx9t/IeZrDVUdXfrz9zt55H+XOr967ie+ahIMPIDm/Xnz6KV0Nu99Ibt3QXqt6rXluEnT0u9vx72+0CQ1HoTaCOvIwHd6tPv1N9ZmHXp7h3rX/rBf1Bo+mdurpX/en7Ma2sqqEoRWGrv3uj+63ML74+fa3WyUvtP6v05p342n74qZVm19I/v67v9Hz+W9NfMvln9Q+upNsglsHfbD73neYvtGGSLUr84eN/8OrqS5OhouQ5ccdTM8H6W541965/QQwrRAnMQAV6pmXWxp7IBlWYg23iYhm54nylDpxNUMrcy9ll5ASrcLKOBBzDEU5jutd0uOF6+nDCfHI/4cZUjHJQ4Ao4AifAFQyhKkeGmRAdD8ClowEn4FJMYAV2Q4LhWpY/tU4tQBWsBwzoltY+CM+/VX+8Vrud/1707gH/gzeaV272P9qu3uoNh9ESo8N61hFVso5yQq1FFZPaYA0aor6hM9bCjfd+fhjj8VXojsP2nfqWnIfV+9tpteDVN5tPdGxyCODCfBLVd11zK73vNl/awe36xd+f/8RJ2LrS39vNf9zk12fpGiBYdxwnv7P1M/erGx/vv/Xjh1/e4qFhAtoq2v36B//V/E/T/ItH//R6/62KM1gla/frW1/f+ne+O/kUhF/M/23tb++gGJe04s7r0z//R9MfMc8/fvT3b+S/2+vatye//MezH7jOD3768D+fMFXiePuFTboHu1N/4rvTv/y16Y+1nJjyJ1bffLb7P0alo/DMv9j+5YPqSoXelHvWU198+uRr2/nLC7vxW9s/G9FPD+5Gvf52/cVvTH6OSV88/t259pfxh746/+IkL19d/aMrvgCa3pYH1ezN6SeWcQ6h8dUq3MsDTNGmdQyjeokLxLl+RucQAgD0wAwl7JEz8GRpuTUHLWo6yQtyu2O/CNcOwl7LF27HT8z64+f9d8BiIz8BInCVRaHDugxT2RqccfD8yaqjxVKZNQCMlJAU0skF7VjWOxroWVeGFsBzQgO0whycCi4ksAV3YGXjNI56880T3cGw7Q7wFVgDqw52bC85w16690z/P0zyci9/7pvTzx6EVzoLzjazBlCjJRJhmUxWJVWO0W6uAou5NhadYmmdo0JgXBjaGDytQuosAnQaMZn6nuHOrj9YhPk9u564dT0fTrSYYLGtZwzs2T0IN5c2g+MkbB3GZ671mCEDAUzLsFjGeWeNyJ4PgAkEwFu2+wFHccfgJ3birIAZ4AonB/Fjd6ubJ2E7IL8xeWUnY6vPBgPyiu2R7R6EKyDerV57vg/SQW/1kvMHdv3AVjfQVuKpTBGA3Ib0dv3v/tH0R5ZhdrW/s8R8367BIv0EmkdPtbqVTQXWaivvplpMtMr62m7+hTvVrbvxeWH6Vv2plU0/2f/hnn93zsXKrLcqeEoQUCHPAx1KjlCpe6Z7J3p/Pd2s9Q0gAjb4mNe6x4bv9JwPZGNRnds92ojzfNwy7VcvHrMVZrU+vqsvG7qV7b5b/Vv3q+vH3OlRXTNL7MhOnJIIqCvsEWmsFrA2D5wqohtree0X/vD2xIYZH161Ed8koIV9B7YEKX1WCtAJcBO5dr4FZKCHeqACaoMT/ZkRP47MvrQRUBpHFAE5tld4CY69dP9af3vmJh642WG81duESo7kCFkhIBkcDA5rtKLG6m5cV7EdNLGzNqQNReOcRXdQhCwAyUyguQf3WdYU3/uxk//1t6efP4r/c/DGlfSvPr76tY93mud7UN2zOQkvn9g2cJSwtbSbqwLPgQBEZ72y6XjBYptJkCXEtohtsh3cKA50Peqj+NyDeB0A5e/Vz7+8shspGwIQEtFZNGZneGPymc90z9H3T0KI6Cm1NCFu3P6AR7KKerP50cOwdy3f3vP/23PtbKIfqVzBq3l+94cW//x73Hm3/rmlZvP0jVfb7z7b/9ZW3sv45tX0+t3q5r3qpYxP3Kk+DeG57nf3/M7ErkA75m7yzAwl+ILKlBLjtf7Obv7PXlmcXO33qzPkpFHSPA7DPmcoMWgBNMAEfLAMz35n8osum+YHH1Qf/9HFNw3vLXn17frlhLjiuzv5u9O85VgEVYIJmUikwBOgB8NosB3wxDYjjZ60PbFhpuQyDCMYLEQmBCfFu7L3xT+WDqDrRC9bGb/n2oJIGZFZ8kucsEtjKdeWR2xM9GCaHD+eG5ABHfK0WP+ok2QzkVv5aJ7Cjtsq7BvyUdzJmEYdmuLombUAq9Rmxoxog1E0j0y3gvqBBzMNwCPKpfIZ1IyMOQETGMAeDECCFxMhIWQFy5gnN0/P43Bld99sIrV6tvVn2m9ea2dVnoHec3Joz7gssKuc79UvvLBsSmoP0BmaMtGOUHlLGRDhTiVDtCFqIAcRWgHz1hbH/GRGICXaYdw7Dh/P/G5UC0wIdyoz9pZXYXoYfz74f+FhS8agFJEIB+O47QlgB+NxvHI/3oBwo//GC+2Xnl1tX+l+d6JDaOtWPiH+q676xL3qx3tVV9K3Ptb91892200f6dW1/p/E6Rfei8/X/kutTa/1t3fzb+6mPQ8P5MiICTGjBwJQQx1lQTkj7PT3rncPdvqbo3W0rJYxkONM1DvHjxtmUvH8+pEDFRCBNhlOwvT96rlJXgalF7r/chEeENeXtt+GiSMLML8acC/KMLhcUgYcXxbn4o+BBTY80QfXKVVtQKqUsVy0eVzengboaVCCN6wYDgAJrGANLIMnjg/ANw23YS3oYtR6EzVEulxgG+eHe2EeLx9QyRvMg7Jh1lvlsJDTxK2R174CmFg5CATT2nl0mq04vKoDZsAMWKKE96ADtoFiq6hHqUuwHZ9oAlaDJcNKITBkAkYZlemCOZGxnbmbraQUT5W3M5pscCi2LT+1CPMJ3ie+1YcfPwx7S5u7LczrYdNPCqQ7N5SwTSMAig0dE9hyaXYcnk2sJvp20K2e9XG4kfjtZkjY89Khw5c2e6/6xFa60tlSRsseNOY2D4t4CB0VO4MnRse1Ss/v5u9OfA9+AzowNLspTD1QIjTPtpus3NqEupLv3ezeeye+1OFTpN9K39jKy8rrlp4hAAYPIypdpuUwM3qttsONjnPhA2L2kAe/uY3ZUAY3t2pn3hjQAw5WCbMOqr1bWluF3Qqv9rqyCM82+mc7ef9edcPx6YB3KrQVJHggyCX4nnAgPOO8Azxvp9ciVWFDHj5pewzYhAu3PmhhlFNOL25LAwKCkWY9wgzVFprem4nHiUJTCkMn0KGMEjI6bDF5fuCbNuhzOv25OyzIUTYSYYDlVAosUaSCquCCryT2qkGAvQ8GK/YcuCvpNriD4+BeK08LAZoAd+EGD9AhsA8swABOwA7A6H+vkA25hOUhGWGGAJoU5EYYDAZaYhRpdAMy6cYjW53El9swmeJkx78ZkJc2OwrPr0IB8w0SS+hZUFZJ3LehjpRzyGMBlYt/P6RFuHm3+nhiNc1/3GiVQnUcP74aShvK6AYDEJUIvVm/cic+twpHmdEKwMHghCyWJ4cIV53avXzf4O9WL7wbf/FB9YKHFjqBB4CgJVhmEGkllcgJSIp7/Z3n2q9nhEV4YdsPb+R/OYUDclpmhCFYboDiKc0hn8SqC/W79YtvN//JV+b/8fvV835+hXK9/jalzoZUHDcJZWFx/HYwdxdZunDGk7CVSMfB3fgT36s/d2Q7S3YpRLcw1Tcr3K64aMgJOCUnNEMLPgC+I9xWwSkvUUUbC5nrBJFhAI+lnD4xEa5b8QxQDEAtTTIn7tNcNa7gBlSO3gkruZnIQhJyHuSgfdjoLtLhQ07wXJg7MJSjNC4Mnhkz0ZHChPJGq2KJPv3hsHqHj84VOAVLLZpmUE2ZoWuwfC/2b1XX3q8+da+eH9ZHR9XiKG6vYgceAz0kIEEJpUAFSkCwAjJRdN9iLaBzICeDG5kNJ3F+FG+BaPzBzL8XkBzhOHyyo4OFBrjO7RhzIIFCUqMRYhDBVM/U2a2lzRutdvLXdtODzLAIH28ZhoxYEDK6Jurm+e19u3o/vLa0NIQiar3m19NuyDbr08dWX5r78aHtfWv6p99s/vI79Se68ACsMbJAiUYP8FiQxpGJZje3V/Lvz/zEGW6k966mP2hUgebkmLvkVjgyggBHbnwF4Hb17FHc7cObl8FXrVVQu8z0UprG1/VC68G6BBcGoFJfqa80AX61R+0MPd5OzB0aukc/JO4DnSOIPbAcwiCUiZOgB/QgDqWTnVm8bJiP3Z4yN2ptODOqEWLGxDM9JYtdqhF6z5ZCoGUyRHqij9F/pTKIj1D6GzP2ZNff+KHWKTCKsIkfyLiK02VcIXVH4QrAvXSvUU/WA94BFcYS2OVjAmQdizwcMhVYnNT78e63mn/7u81fuVfd/NTy9yb4tQm+ez/+jc8ef+kmfqfJjsELV/YquWSV0hWUKh+SmTBkV1CgKUfIgMy0sunt6lkAjd+d+Z0QcstmwedS2Zi56MNMmbxAKgPFT8yS9mH06AqeIUvMvT3bxklUv5vvrNgBOIy3Ou6AR6CBQU66trw3/92T8PxR+MmlmQEuKzVcTndWBGRw7fT5pdU/S/bs12c/dRiufGXrZ0/YTPsH1/MSVosgbNA+uCaqDE1mKe7278z8uEN9o/vgaveg1jboGSkjwwVXzo7kUGKG5XmL6cSXz7VvXE13d/1jEYenD/1MZMylm5SNkVOnltJhs1YBK4AR06nefqn7vX3bqvStxNyzCgCFaV70qmN+Ofv7rd5bAARaWC9AKbqi91G3R9jAck13hE1+MA7lzBbxEe3psijOzINJU8dcTdVHEMl8GZZL69oqpdAxeA6pIw2MuWyVhnTEkXDOKBEX6PLiRJ+7LxuCeOFQqLPN83vmfre6Oc/XanvwoLoOYsvvhwHDhizZECqLfOgz2TzxbsUIL5F3GZzAEti39vK7zS+/1zxfof+j+ReMn7uePtiPV19dfk22hDs4hQLgUF/2URrhjcc0OQCg4DJSVIkXhzOdxO3bzbMAhXcN7+70+x/Ej+3Hl/qwBVvBpQFvr2jfQ9kaEFbylFUEqgQHQ2txac87bZKXVX478tvEDx2F3ZbPu33dgILXSJfJZ/4Hc/7Cwn7Y7V5UyRWhn2YLrhHmDLKb3X5rf+/YDt5u/syD6vq3J597Zfm1a/4b9AYwk5XEDj/NBSSQkZomtzCQmqTlJBde7EWXE4YEF8DAhjiqlAE8173xTP+fvbLq5nkf3jzk0Z/DyDm/gC7Y8Cqg0NSEWk08zDOkd4C/cmyKSrVubaWJ8KCxlcP28oOp7lOp16T3GupqbyfWVDqmvpeZgEgvwUXnIjDXoxnG86F0+FTOep76KioAjiphnrmT542ngJiszuGwi6uTiveq/eOqiwYw11KdPYosRpRNlf7MBS6+X795yP5RhBy5mqV+O31zp9+/V9/0+s/XunMcX4rs53qdWgrrWJ+heoa8QOXYku+vmCp1oIAIVLBSQe94K9+Q8fPLL9X4+gk//+3pa/fCzRdX3wn+TuMVvB4CQUFwBVZOOM1lEp3KZDTZmO2LjT1KtnwcXz0OO5V3C+7U+ATVSni/ea4Le7APJKVRBXWzTGnwDCus6YQQlVi7tYc2e69+vsmrzh5kNMIHlFY27ezjHb42oTKU3OV02hbeOMYfHsafMe4BJR/d3QgTEgEiqkDSwTntpy/p7bn/2tXkX9r6K8dh56B+4ci50xf7+CBz8hrtygzo4QHyHIKHAKH3ILHsHA0VAsxd5giAZMGslB6TttL9eb+Iea/YEB6yENfrQeePnC6T9e4jD/GSCHBO89WWk5305t34+We6rz2IN4Hd6+mdbf8n4AG5bYhBLR1HRnlr+WQndcEiVGe9nbVYcbvgbGSUAmUai3c8cXvySr0ABDeV5VBYfhAmKc+TzXNfy8EpLCs0i1DP663jcNKHJXhSob2xyo2PaQgfooU+QhiOjRgQPwZ7Z4x5eaX/7s303r14437887W3K5s92791Lf1R5YvEPVsn4xZYDIJSBt+v/gNn90r3tZ30BywGaC2BCXRlmr/+bx3+42X4Jvhmj9+91b4Mfbrxr27l36dPgRlwBBgwKeVNVbL1Sk2kEuMOlDyYgYUZ3Qxkb35cveK0jLC0v9j4F+9VNxP6qLAI8zYwCLJByChwWflxxs5oXFKB9VAxzbLTg4P43Fv1x3vWnX1yYX/9ML7q8IzmONxaBk7KLFEi3ULT39vFN5b5s6s4HfAkkLVe1gWYmhmFZ6oHb07w7hS/Mcu/eBR2lzZ3Dpm7p1si+gAHwwC1QCOmMSlRDpN8iEYlCXf63Wa1rW43I4XaLQbkntVJuHYcbeqpOlNE8fyzH9/owiLh6TcDYXTALriAWmAa9N6ry68s7M3t9PrKqtb+Ysu8k+/u+LaRxDFpGXVSVXma9bi62p7p2sryKvsSRwdh0YatMlcBlLIYcYEG+XjB0U+xJyy60OAeLi4xkAYaOkMV1JuWwREytxCuryYZUdwmPCBNs+aJskyMroFiLC09r6fvvJIKnLnBDfdI2SqUdBtmYHYz8bXF/+W+/a0Du7Ky6dX2zg8v/vEz/duTfG0VuugcyaPO8VhxGpQ6TL42/6WAlI/jp5a/t+tEbuCxOMos37zV/nYmgKvCIuGrwO8ZJrXvwAEtx2ks9kyj+pKYH9ETIYhQ9BCyTUxZ2TK7FKbIXTIdxVcSK5NH7w/D3pYf3os34Yvj8MNH4Wvb2iWzYBmht/6gsUoLcmu73we2MqeEHEblyN4j7sUfdFhibLx9vf6pzJhkNfo3Jq8+m/xKHyJoljxYVqj8xnPpXx6HXzoOO5U6AHCyZOoMcSljVfGQ78aX7jfHRxO9X/1QxwaOrbRfe4ASjJ1FZ0BAsIzQwHo4gYCQeqvqvgNQaxVokEtR6ByVYPdj/Mb0P32/7j978k8z/3mHKivcrW4dxv/NO829Lx7+5y90t6OfM4Se06AurBBiCDzEunwfoBpYjTkimT7d0tsThsTDDlcX3N/Kh1O/aloaJsKyRHQ46jrbjba71k/i4mZvywPq/XjQTb57aLecK3FqQBix9IABV4GmsQbyh5Ph06CtUWcoomyxQNmQbaYARLEWa2dwhsGiDqLY7U9dqQ834XKDJi/dFm7S4fgwCAiTjFs9v3j8v3sQfjxjb56//mz65tUkuE0szfPyhfb1j63emiWvOZ3l1XY+2A9XG7WG7DBqB+jG0gsrqIJEVxyuG6oBuCFdGFUZSIpipT4gk6rlVAdtOY6oLnjuGSoF4lioE565F25lhI91v7/b/+MtnpzET/f2Kz2qY946YZjaEqwCEhXfrn5Q+t++b6uP81s/mH6t50FQa8rBswTnvOfx0uYdmlk+uZJ/azvtt5y+0/xky71j2z6yGz2PnTNy2mjV+Cq676b9Tyy/ecLtzproiZpAy+FGT/+pJX93/pfuN9e3wtE78cWlz3b7B1N/e+JL6Ap1YuogRU+TvIA6YHvIhKRDVVaAVHmK6ogZheBV4wECef1eNTmK3WuLK6bpLFcgWkxWNiO8t/lT2+xwdpVefFKVEAFZU+PeK6vfEFYVW0NlWDm2XL0ASBGqkmpoAmWijnGFVeP7lMB6MJBuQtoVnAMnP9QDMLanMsyIY6WzzcsUANw16u3aZDxGgWGTnz1iejYl4bk3504rdDyaWUvOEYWsGfCS3r0Zfi0DtWMnV8gd1E/y3o8v/s/98sakb2tfEZiFL/1y/+ZJ8Mzp1Osb/Z15PkImFHEKMHFOID9yclVN8mTqJ1t+GJTn+Rr9DtRZnk7StPFVYK5zitmyNzk/d+w7depe6j64lb4yxYMDj+/Fk86uvhte/JiudLgDNA4zx0neeh2fYvQ93N8P+wld7VsCzbP76gR3Em71+JxoO9p/tf3V5/tvnljV25W36x8/DHsrfvKY/2yJxuSUetQTnzX59W18FfixpGjZzY9Oi7etGSS5Mlap+6B57q3QuGwn7b/Sfnk3f8d8DiWq2u53gucMzPompBousIY6eJqkpvZ2kpfBU/AGcCBONZv48lb/Tm91VIre76T9qKbl0SdW35z6AsK2Dq+l/eoS4/+jyesJGgGgCWDEQoiGG4ZMLYB8ut2Gj/6JondVhnu1v115lzkFC1rxhmAast6fwHH/5EBPm7vP00KF60iO4cmNTpwzSNQbPqgPW8qXSMKLP+HQK3GqvpaJypjg2YnvAw7NkA0qFv+TWT8FjpABXQVy4w8+5g+S9aAHmXkFnwARTEMAwCDx1kzEx7+Ay5s3fv9zJ/+gXWk3ayu9DTVQNC238xs/ffjrDr+ZvznJ0ZxNPvrC4b/MFl5uv3E9zyaw7XT3R/Rbd+Izs/5klmcTn+9Y+2L67gLz3ms4+lg3OjHfbsBtX9xIH0zSYjfNG98NfIbUtXT7pf47L68OP9ZPT8zu2f7C7sbcT9OtmHemaiZ5MdPJ1XTnWmc7fajDH76y+sZ71fPXutvbea/WvY3HONj2KnEvvfFs+8xC85lOrvVff6b70l56B74FofZwLb3/Uwf/PQxX+u80TqgfKhdoOsuLz5/8o8zqme47E48UgBx98Vz7r3768FvLcLf2bivlraRKh8Kvbx19qeV+FHZ8sp3uQ9sbc/vEcvFDG7UwhgATGHBACJgAK6CGwAG6IlN55MU0LSf63jw/6GLjhesP2CbrTgfjJR6PW/Bv/a0nu7ECB1gM3RmqpFk+vt6/eav72rV+fyufTLw3rKL6GrnyLngOSoWdhBLRJQB5XR4ea1NrceOfonGNr6cKJzaOrwe0cZvnuCYTNAUAHAM1MAEPgR3gGOqAyUhUEzCC/YjbOwEALMEEzKAVhJGrrNMHH+GcbcCjVazdHky0bd4j7QKG0Mq6+xah7opq8wyHWzyoEhCvpBZZUEQ4OqmuJYZZCpUfwiPCYr+5cWJH9BqI4pVZPr6yuguko/rKIsyC4jy/P82C+Z365Q7LHbet9A77HdjibrO7sOejTrbSg53+DkL/QfWp1ppd39lOf2A9YScfTJ/tGHf76Vb6ruUabhuSkMUNdRTuH8VbKVhEmPnJVkqxj9AWsILJw2LJaaZX7tNeA7AFElKFsDqZeGbe7ivmglVhQA+rFlG9LYm6ybHJEQiwRWLKCAGMEnwKtRuc/Jyf8NIFuvluNImdO38zTYQRQKLEGNgBtWM74yijyghANIhogxY1Fondfuzfr998u/7C+/V/8m7zo4kxsQdiGPagg+0Lo53jcWwz3xeQ6XrTe0pCI+WME6AzJ2/89OGJHh/KFM6KRI2gbBgF9ZmeWiiCDdCDS2AL6oAaaDbqN3XQCiJQqikuB1gHGuRjILVG2uMlYzjTVlA9yQ38JtRAS2AJtPCrlK65AwaPUABay7hSBpobSAXAYi6CDyCH7wBzpLDH1R4B74AT2G1oB/kq5NtcbvsBVMEDvIa3N3DbeWg+Q6qRA9yu4wDh2LGyvAc9i25xA+9lrqqCk5Kuw+Kt7q7YMW3BR58kNnJESLi28bFt9Z5OjAZl5AAP0BGshirLnKMfQtsLbDkL4EgLn89zBxCZY448gArOWRJY8kIInQARyhGzOCzLExTAkY9I+XxISyhAzjJgAmbhUHChBmBwyg3ZVKLtBCD6rPF7E3+91muZodhHsYF2N775E9sTjqB6GwqLNteo1ugIADgA5p8S53D48a92+vrw74dxcRzaaDXFDGjBdQJLDywgAyqgB0/AgigDoBpz1SIQoSVQQQ6soOa8ZB7ePCzijwDgC0DAcrBGYRt6ANXA7Cw91/CRyLka4mA9ghNgB2qh+yCQamALcmAJ24Iy/Bh0uAFzgPAAtFADj4ZdeAcA1gI1coR3xgY6QurBZKkym0OEZ/AYXiNHcmtA0NnARhxuZzA+dHCZ1QNX8gyGEYmuG2yhQ7arYAL3gbqEiMF70KFUXDiAgACpKEZgAhKwNcBDQcARUIEEqjF/4rHX9JMusdPYt4JmYiCFXaDku673hD6UNpcHbU/8cJK/u50OuqpJawvMxl51vXV5zBF8FE0ifETyxUAEG/vBtVTcQK37kB4f+e1Z1UI83yXLYloBAqYlOxYE0AAl4aBGsXgN5AcgACugH7IxJChCEeg28mji+PeIeUtAhKoBOg0RBJiAOdBAPXQCrJMweqjE2RCYgAFsgRUUoX1wBUZgG0rQMbyHZnAfS381QAXZuAEzQMgnyIACMAUT2EEZnqHtcadSA4QfQwdghGWYQWngOAN03kiHm8y9BOW5w4v7wYeC5BSU1nCt66KVwATYBnvgGO7wyTiB1WB5ZoYyRPiIPDS0MMqGS2s+6HGp8Qla4sAvssMcGTgclEmJUJCsgH2W4aqJvmr8g6kfBiU7TZsad41jGLc9nnHmKesTFvkrOF2bYe12qgFrYzu3aZrx0aei096GtjbYjFaW0+O4MPVn1c5LOltfdx29SRSAFnUgRmSaMglFLpXtdQc0Gyp92BjAxcd/cZLjhvciDAtaBEYOxfVVMOrwhhK26Q40IwHU49U6sILKZrodtmrBTyes6NXlEohjTbUOFqCSDRdgS6BBGG+BFQhgCW/ABGtGjDMMgT3aMDufMvS1OSqDYQD2dJ1BmjgzHyejhZmj12d0p7HcNTYCYjIIIA6+jaImnOr/T2DmeMjpG4fOLighCoUPBsGFKJgBgBMKSIZkGpOFJKA33aj0vca/0uiZTk2SEwWpfcNuKZ5Z+w9vT5HKNJRXWR8gMtHamCVYTtrQUU+Hcdl4zllcLhLTY7R1vw8335x2z7Mf1z2clvs99/cn0LgxDD83jMtO08ZHnj2uC9N2TiPAhd9uHrGzS+Cxbv0hX5ymDl0YMy48WI5q4MWB/Ztra2YzsEHBihgUcKpuFZZnVF/p/e10z+DVhjA7U4Hn8W7qaSJmBrhDAAUTT06kMeVGp3uKD1/HunCaLjzGR7ZzD+/cLy79yDGn7NGdfPj0XSqfL3z/oU0brw87sj7OC0fOqQubzR8+ORq/Ha51Wijpchre/EIY7BBr/FvgEvLTud+eHd+a8PTIQf6JNp55e3YiB8IbLRqD9d6EkhzsMCFFf73Wt6mX4KSddwwWiPrHUUifTBLqdOzC6QbPTMHGKkWn15RG/2GJpMFaa31U95ccvJSSx+NPykd54fV0XJf+PWnbmKTNkW5e/eJ4HvbtuR60segvdn6xn/XJD5u/9ZuxhscZnNXyNbFhrcHoutDGk7lsEOdVnLPP8dI7/ZOmuke1U5E9Bpx42QfyDJiXADlyIjPM9EHUd6Z+sgnt9hRB3E8hCQsLdWKoyCCSmkIIQBhqAoLn6fthE3xO+3m0LHvI8Yex0ktl1UV6eJjkeeI2kt8aEPnS8eDsEXs4yT96SGvSsrMHMfa5aZvbJF2Nh4TTLTzPXu/cFmKDs45Ux9PXS9SXjePn7mJzDA97Fv/aVdNzFzQUqwcMPpo8NLJqAeiIHrWhD3q7zndp22NaPTTW7VpXkP3Q9hTWUbOB3A2gIQclgwWUSmWyEva75qyXEdjGk7+ox3xo08abTX58tj3Ogzyvbl3695jt4gp++G8fJhvPi6C1tN8Yz6YwfJiovjij5351epGzwx7+Nn4mnLnomRGejQoZBsjT42cGc3Y+dXZIT9O+z+e12c+ZsXJtcD9vJhhOyQg9UmJ0WfD3TG8HpY0utNH1Y93bExPhyDoLQnoi9oPuEPdOo+yUUWrnPnRSHqaTPRE1anjRhofyUqa72eX6ZIwL7qPx0ZzXvS6+/fAOfOP10SvqYdJVIwScX+jnUSMZBfgZvIiNs33jb02pl3b4UJ1ineC6sRXcfGQXGcrTbQUubY9+CpeHtGwS0unvxyFbz1VCEgS9E/BGUL7468eHHn1yZ73gUKBDFnUyyXem/u4036m9uL1dQwKMk2eDCEa48A0xeG41XTbiS5/05oZ+/RQftibW3T+scVQ0Lj35yUqz6sLHh9zu4/x6s20yqA9dnQ8jhof1zwsfhfVSuqSH8zrq+jRe0tuHts07utjzv942biFGdfrc/ROQZzBx2WFCouc96E4BEzqztKkR+unD21OVy0afFaNYp26Wv7Lb/f5e+pFpboOU4WQ2MQCGFHkazkasa9hubP0LmWqDK54u+o2ldMlSWOtCD1lZuuz2T3WtC2VeNq9xpks9ZOFfSuKXamIXr6LLzni8dulGtxziZlT5msP76a8u/+FZRrNJThgVtMuH8WgqXz84AtwY9mXMTsAAeIdxDp+I9232uSlbL4yEm+esvxtKrxkMZClG5TJTHmuvqqB+GSQE50m2ZRcXnU2dFfDblR+3mmQGjOoCATDx8WLuniafUKhImnrTgzrvT/zuxL9da6+GWHaJ6EyZBXh7/aNNytm0G5wuy8cWhh9V+5Pr+bGu+lB6eujvHkthf4Ru8HjjOtPJR96e6BE/zl086SD5kA8DX9nYGSggQ2UNl2pq2XkiOtj11srcS6CVDqHrMhcKelHZGV8Ef7q8PU3EzMhgVyLFm8IE+Ebgp2tV1YhgZx4FJOQweqA0xM9LGMEtz/JbYJ2ZhTNTzwvTdaadtc6dHv5oKexxtMDH6eT7aI91/U094ukG/DBaf+rbf7qR8MKbi92O357bTGKtTl/47cUnwPOvPkjGkgcbB/xVAMzODiQpcGFcZtSCOY4z3hBe0Vjrj6AkPra94cnsEgRIH/G3l47Y8dMn/JFj213wDxZ8q+dKNJMCVkFtUB7S7VUgxgq4kjY2y5dpmxef/aNX76NVxY+sPWanevjfn9TIHjmSp/7hRzjUc2rqwyZn3dY08WjqvfTbpx62dCZoJpMGrsP0MiCHMi1ZQlgCcEwyGmHh+DYkH512694esz2xJCxIe4SA1GNxjBr8dM9mab+/i+Ndf2OLYYvzqKZGDLJSpdCEoa746VrUsI1B8cmo3Pplg1/vkr+P9pFIsu+3l38z6u/30T6aWXvyrrShiF6YtFMROL67qDuXyGFt9oNTKbnemo4cfoThGxafAQYLcEMPFjh2c4aeseWDlosEOGbCDGBGJ7zn6Igpxx7XQ/+TMczAiEx0Bgh9z8UxY+Zznd1a4Y0Vv93iTo/9bQT3ukY0WQCBdfTM2trNy1jgmIfFsw/iKXY4Z3sdXv910OGj1ac/uXZ+yj7q9rBuH3G/vHDkMS/0yLs4/+Wjt6+67P1GF6fDHI4U2Wcgh9rmBtSO3HG15MmxLRZAp+2MeSlK7jBhHzgyTDGQfjEADpDpH7ronsJFQSIHtCNRtRnLBbqeoQ0vr3TzBG8f4ztb+GDGxZaHXc0ngIQw+D+1AQ8xykOdpca1GnJm+A+JwHgcwvq+aO/iM35S5fjRvX2E7Yno8CM3eFx6iafel45vNtfwOZG2/jDoU+tzzl53mPILFDjaGgqYa8mPOE2C4OD6czCj67HquFhYf6jdI3IpT4AjC1EgcM90kP0WTeurP75C/3SpTBEwoic6Qy7Ah52OBHemPux0+MIR2inf27J3ln5nKlYKlaoasUKoFEzB1tliGqXf5vq8VBO5hDL//0vFu3SsH5Xk/Ggl4Z+cFvo4TGq8hYuetktu7qxSio1puHwyzvHB8TyuEeEFwOEJysg9Fyscrbhasjrg9n1eORI7tFlHwJEPkM4PgBNCRUQB9lj+wbE9hYtCgEmVJKqnvCraKROxTMhLoDMLaKK/Uumlqd2d6HCKd+fa39Fiy32uOFGsURvyiAO5nrAENRsRH9iYr804lwuDOk/EpbcREoYBEpigGkPmGDb6eXQC9MPW0KV6Ds5CYODCXWye/2hBUTCmdJrCNxzcXKabt7yuZcvHI8WHmR/XadnnTticJV44/2I/F29t3c+5qXi0rqEBnuH0eLnBDRQ/YWNCqiEne/T+jd3UYzZmNaSSEkAACtwJVJQ8emZKUMfFEr5ifwwccXrMl4/5/BKhw7LDO723mQxGoBcrx4o6AkD0GtAA7EPNSuv2FM56Qu7sKReCIKDEjjpEMCQgsQdXsBzUH3BW6dmpnpup39b+nHe3dDRV12hZq6vhgYggVZuaStF8AcQRK2G9qgyYAgLymBg6PgCk8Y2d3c3rNDVbeXww+TT34zw5PWwxXWScePiKufjzp27dWPuyG2poQmMG/aVtI739VBA8zngexgvWx59OtF7kPudEFc6esElgdoa6BlqyofrVQH7ruAQ/+9vlUKdvDbcxrKJ+MHUyARwzmHuhyUDHrkeX4D1zb94CK8YV9ha8seDVE0xOOFmy6XhMHEq1dAi5l1oEQ4GsFYChOgFCqf4GGPUwVL7T9uTW0UFNbzIjCAzxoiJ6G4qEEeqJ3gBnFNvE5UrxWOGetqO2KyEADW7XaqdqJ1jNdNKoq3Ey937XJhPvyX6c+lDAhKHjDcizkrNcyGYNW7IpKjnmcZc3Pt7smmjxEELiZWSGC0tKF46fa49Pig/rQRsDTiP52cZPzv1wLQMxagHl48Pk/CYlPOz2n4j8HrbdffQ2+OJ8nr2oSsnkvHF3Bf+iG3++/iu1KQtSRhpPCEAEa6BDieNiqYOShZyYV3ywQFgRJwgn2Fpwa2HzFZsWz3doMmOPIKaeyGaCBUUgEk1A71gWvMN1abRNI34Bj3qcGXxqtLUaqESAEYjCQqiG5aJNKWQZ5uiAVKYEDIAMCLgZ6RPZBD7BaopVjdWWt9v6YOqdoYtQkEVYxCrKA5ogBtE0LsRSLGF8Vmdf19wUkIEZ8qGA4Rm80M2VkTd6wAWqw4Xjl7ZHSJVz7z90lVcjv7ARBg4jx3nYDy/2+WjrwKOF1aWdb367vtyl7OxhbOvStpZs5+5OUAcZUAM2Qo1oqGeOzb2fUIyZ5ZwC4VVQ/OE93WEJi8w+QZk5I2fUidMTu7bi9gq7J9hbcG/JyRLsyIT9vuD9kEO31kCkKkMwTDMOgCxM85DYfkul/uOAvGZ47PK9T4O2RjrgxtpIIrNgVEqOMhdmCAIyugLoGGCG6QANhIwB3fGoAxObE1QV5sROBTO68dNBbYVl1LLBcoKjiQ4nOplgNZUaqREmsohYIRoMvtoQjyPa15AKva79VPhfuLAoz20jNw+e+/YxJuahHy99/+gNIUZF1IEarEaa7KH4kAW93mv5KAk1Qsg9YsCPL/E2z3mYOvBotfbRnW+CLJ97E0EBLYhhxbIDGsCHHH+OXnKudxsOpZapQ1rBV9ASzRJccqfF3opbHerEWeK8JxKrDOsHOj50rsQMzMIwahtTDwTKCk3CgZWzcdbOE+cngE8AIMuZ/vjhMni62FHAqQDsAgE8FBMYXQsborcHGQiOWzs50AesAiNERy/UgGegRyekFs5SMZnunJAhYi/oWg02QkM04gR3GvRTLWocNzqusQhoK6WKrKRAmBBhhkDEIKMWhjnVEf0AsFdm85LiM+fapQz+whw8alt47vjDCPLRrR/w1wbN6lImstk2IxVtJMIPvdyj6efSAT/C6nPprD6CAjfnZ5MJ8nTwp8RIUCjKEENGynCHC54HjDcKBA8yLSF0qDrUK+y2mK3QLPmxJSYtJi3DCkzwjsnZCSHDwVboDWawwCJ1e0NytAAG4MYirhnBBGZwV+wzPhD3nL8CboEocZc8BbDGR18QRkXQKBAUavBZ8UB8P7AFYYqGRPaFB2vgVF4iuYkltWvwgANXF7CdwQwCdBVpVZKhVoARK0AJnoAVIhGBKwFmpfwTFYZC8h7Dnaiu4rLWSY1FrbZWqtXX2q6xV+l+jcUEivIKMCV4cyGQAuPWCxvcd338SXdHF0XiI4nwUcbsCqyBFuhHJMWwAQR40byxVs7CALt2WizoYeO8KP8f1tbnP0ITvtjVo9kcxvnRaHnCxsFyTx2YwJhoPbqO+53ljlqxalF3rDuEHkgIGU2PutVWj4kwy5g4KkfIMAczVxkSjh19BoXoDICI44AaDI4QQEMCWyADjSNIHNUQc9HgmSAroM7YznjfuZX558B/G0RgzuvNjkbyewxF6ikkYSYC2AvB+TFYAzsB3oV59pqilZq1pMs1GNkrDvFA2dEZVsC0ADIH5Aza4LuvgBJeA4Bl+jCUhJfzUIO2EcBABEMggukTpNUIFVEj1WojVg36GstKe7XerPFBrVxjGYBKqv3EBiDoornTRIJhqHjMIpML/qZJNhiBNms1byxE4ZHLVxtL7eLyfbSeVgMn0DFY8MLTYOUb7PUXL7qZxrtZj/RDlV6cOWddz0sbRH3+fFzo9ux5vHDCeMRHcGgNFcYlKEPC4Zi7wHU0oxOZnrhwsOMkcdLzasebLW52vNFi3nHaIfc4TlhmsFfVos+DdyIJLbAas4uCoQcElvIHXbGXlqqRQmdwG+qa2OAf0pojW+nQmcUWNoe52wPxnuzPgn9DnJPyoSuOyyLx8ejriWtRnOFyKmUKU/Bvmv9D6o3oRn+WHswL+XUBgDKV4bQB7roYr4IzAEFIUDHvNkBgoQ4OlpWR8GyE2hyepY2W0rLztoEsSVSGqsSyG3qqMlSGfqT5jsqGZOjLa8Si0lGNRcRhrVwjVSOCfACiMPEYNapCRcpIBgWEAFBrpI8wkHaJzDiTobcpbTSu17WMdWDtaNb4siEriA1KxhmQz+H8MoDNUm2PlkuFQ2/6AzdGOBChn+61TpUrbnQzutEVgSWgAeYYLgQxOLpBXaRneCkr3ZMt+54ho89YddzqYAmLHjst5hnThFnCxLHl2AGaDCTS0QnmmDunpSBtxtzRAa2wzGhdrUZHjqsfsW2H7IdxEgPRjZvPAm1ajRW+y55TYW2OHsDCDYCToMkctGyTHLpsH8D+UFzK/pLsr7vtgA5upqx/qC5wpj0t+G9ht0xCgFXZXob/x/Sv9vx64JvkbWekblDzAEfJumDOg7ncTxknR7ghhRGbeTQlnzp5lkAPzG1Y7uOiH/ZIBsjlRf47stgDEjMQRBdWQHYV21owTEkQRtYRtSnUUpDXCjVShVWNRYVlxNLU1cjRjiIykYgEZEMOSEQOSgE5qC/gsAErKhNOxrEw7WAyL7WrSgzhwOS5gcklGEgV3y4x1MXlaA4dzEpAmSXwVG1eP+kyUQHFLH66COSjtAGwDioe/nFTTz4lQh/drSpi6TQpux9w/6AB/IiQkJCEYr2k0IsCLIPOSYZlVkLMqDNqsUqwhFmH2rGVyB7TxL0Wkx6zhNgjZCCjF9xB0R0po1QUzSN5nBjuQ2EoV1Y2McPKccoDIpBtoMMeyD6supFTgKO7uCT0JKEmDKcTUnT4E9AcBGtZ7eZgr9Dn+IZzCfsx8M9n+wkQ4AqcnCUPrivDPI5Z76kq9Y6PTajABBp8K5uAnw34LPgG+R3Ym6a3qO9Bu+YRqsGGinAHehs8P85SPMR9sGRiKP4N9GN8aRzN0wPK26jV0EDIbLAWDjRJmFSyTgBEIQk9EEzV4J+1FkOK40kGBVuCLFUjZIHRMCf2Brh7EqEaScdG/y8MpfJ6pjoiGROQDIlIQQcGBxKRqGRINgjhE5YfDqB6bnQTovZtAG7tDD3R89ThOUzzICgpqviFMG7PN59LOt1fDscpojM4CZhgDgOCYIIJcSitcObRSpAjQBUQHBTMERzBueWgo3JMnXPH1NE4LGEmVWOd8AxEoBEgZAdFOqIQHUEwCCF11FJoHEk8dFGIjh44FEpmug/43ACQTUnIpzFpIlFDoZTwJvIQiQEBydALCciOPJa48HGihKHT0YRaQqy1DfhQtIccahxYALy4v92SuJB1sN4DZZ+U/Zz44yKNPWjOBqcycD2Tj0N9Q3sKIiyLI2MIBQhAlhm0oM0y97L2YD8StS+9Tr0Ffdn9CPoA3lI1uEPsCDvUEURDhIcyn1SS2sEMxYChIlwaWdrWpuJkWldC7jcUs2L9FOgBFDqgdSRoBhjUgoTWwOxFMyZUysKs9cgOWBU54IDT3AIQHaGIaA1FfI0gLACNYV7sZgQDKgPKt5QRRpgNSqSF8WORhgYGmMlN2VBCFPJIST6cAiODWEgIUy2GUvJDGJCDvo6AP7WLSwCcSJxlsuBRClGoHNEHVV8Yq8AUV4ZLACQDgo+l67w8CWZHFnKGRAou5KzskAYySBvRS4NCWKyXQCe4IwfPEceGQ2ACbQGJVNEvhjstE6uiHXkxiUKBTFA3pIXDABLHAEw+XrRYL3PBNxrDtQsgoJyF23CIxx7ZPRCgDwY1hQFWgdlxInbgJDOLnRMIV9xeFT8teynZKyiPFu5WfJXd2iv4dO2pKvUOz7gT6pGvUJyj3Kp6ok7YAz4HfS7o36G/R30L/m3ibfgdw3epBfUKRbrDgoHwSBFyaAVFkKNWEGzYca02ZNFoVRk4nAbFlWUhsjjlHR3YGTBaFzMUh+IHI5/ygQgNaMbN2FrdjQYzz17qfwNgJ7hA0QA4AoY3AgQGQ8g059jPULJu2KISYbyd028dFcgBRZJGVWQEgtCAJboqkhVQCSZjYiRESipJNCTFklEKEDK5FXwDiFLwzoeVmoWkQcPcVFCBIZQBGLhb2TUVEk1AJ/RA54MqW9gQhDzUmVQqUU0joElhkDqNOqQN/FRJcGE+yrHKlIge6Ig0EmEh4Cz0RLJS3A50bexi5IYKqAiOQbaFWSdDA5QojjW9+YAjChsPZgBgKb8xB3u3JdiJdFIWnFMwZXtZfM35KuxjbvOy/RdIdGJVnmrZ+5yjwCcQggCeShLmUUvcqEYDgJ1UgQY241AE5YQIe4F4nv6nTEfQe67XqQ+oLwErUwc5PVJb8BlEapvDox52NA4AZkOod3kGmdS4vbFRlzUb8AUKAbuBjqK3rGNQiwwv6hnBoVuHAYdDjUOu6dAEgxRUi1EAlITspGQiDVEFyWcQosVsOzKI8vNB5kAa2QcwepnhoFNeIIbKUBXH0Nm1USoCoRAwnOIMTIOaUEBmsZYGGrWvMWlToOIGq4LWLKAMYzPwUiQQtBgVvDKksjXoMRBeMWquRV+mByhxoPMFsDQEYEL0QCIyMLiwgV7qnR+4rhkJZDKypO2hJXqIGqIUMW5HCdSUATABzD64lwxYrLeCG2YYAUfAMOWDV50+at2lPk8CNGyJCec9IcBMnMl2ZbecLwjPePh8ZiCk4puw8oxJdFJNSjgGAzQDALZQ8+SkNLSnk4Tr4AyNugd0AVhKIMraJYod0bUL7BKfNPSu/4XhDvU69F34m9Rt6D79IHhDB9C4toEpZUO6WMHFkFkpVoUhGd/lkpzFLTlGDAFD8UcVd1k73mx2q0CIPj6DU2UWYgAwBDuU51oebB6MiXRB5UlKAeg2INTKJk08tXwOW8mN4AAb2OcwJyHAgvKa5kmDTAwq1qZhL1cU3eKb4ZBHOlQvbYA4qNXl6ZwKc2xYZX1cqWPJLhAFW7oIzMEgVIonHI/3UvRDjP5Gw1CbYbwbFDa4hNyKkClWbsxGU22HQVAY4GRPdSRD6MHip3BDGUBfHqYPsrcosWWENZChEhGZRm9WGAQg22EvKoHl0bXA6RPwgpwGOJdAFDOQQIoGVmKU/ZDzOviC+IJ4QzbJLCskA/CRVgWIbnR5DXZAJWxDAFaED6R4Zov+BALxaTLrDb0PZf2ciLpYvZ0JCpvG2tMyMSIQik8z6yZwE/oJBkE9/MC0r/w94B3ie9A94gPTgspQcM2pimqyJoaaqoAoN3eH+ygAHZANQqAaQ0vLI6wNdC4MU6cIifRBXmEcGVXAy6nRdCZDdCagRKwGHzaERfwVhNXB2sGyWAenxUhspzhX2Qfkchd93MGFEfOKAGwI/StP3rg2sxbaYimHNXMkQ3LQhsEUl0+zrgK9vhENUrq4HHws1UWIJKlRWpIQjSVqIg8TMjyxtba/JkKNzDcARq2tuBlIQiBWwAKjDgyMkZ9yUMRsNHdvGwi0RXclXHDDWunUKHlWY/9FrcgD3gQN6MRU9AtHtnKfRkCig8mZgF6WhCzW4FS86rwKPi++ADwv3nKri5IpElZuOotDXTHAOOj5ZLEdQECl4X4xFFdXP9bVe5r2NC4KH643xNQN6wQ4/ac4Hl7vIS+yhdNKlBKACuG647qHV4eeJNNx1nvUW9Bt6i3iwPQAukP1gyjwmj4FItQAE6KGzAuDV7AyjSranVwZqKFsoA82ZAfKozdAgvsg1cHTZRA2BJqr7CIBMBfKKEJmvBkjXSOW3Eiug2QOCOCgBo/aYyIbjh6tEZc1C+7YEsfYXw78DqiB1Rgmu1H/rgRIDGYUnYKrDK6QDOQxenaMKeXGIxkHa8BpVkrR5U4hYTfVrSLdE8t2FlnF7KEIkCqS8xCD9SNSDphBLncsNITyLr2o/hptmxLgNvpQBqXdxtUCge7D7q7cjoF1kYfFjSFCTCBEAxvxGnjT7ZawJ3wS3BavZKuHW+b4EDguxwEtIpydlfUkSae/0ahwlUUST1nT5m8er31fNevXozsviJ+iB46GAksCiSjRtQPsEJ9CqbKhTHTUEXQXeh+4Q51Qb0Er6AS4Z+oBUAaR2nIRCFCkGqgGGmosB1kUUbiUYT3cgQoqxW0GHdUGYdZBRS0Z73JY4GEDSnbD7zcc42ieGIwUHOqDDFV+1o+ebDemgBx2kgA6DsftVCgxY/BBiadDASDjmMl63gFY0lds3CuqaH2m4ICJjpKYwo0dJjbibzCOdiMYoBj3WZC7HAApycEVBdDGvIdRE///tXc2vXHkRhh+ij2t2bFXtrEwsAsEwd5yySH//9fkkFMQwPHasqQZTfPNoUh292gkS4IdeoF6YAjj/mSz+bKqWOxuOyLqiO5QB3WPzJ45xiGboZRqt127l5TJWBZ3cPSHhgRmV1WHI+xkv8E72eucfpddwnvZe6U3k1U3raqufGDTfJK1mdK8wbmGSbvxtvhxlmdqr/GipyiKf7U4p82rzy88Uz6/5fMO3hXBOBtVE/gLVf2DjQlG4xX8iv7edktk0zV8yvoIH0x/oGv0Tzia9ugm6SO6hQN5Il9WA7IxtsYFGi0Z2vu9TUo+NSzjn6R71S7M5k66Xp6Wv5rVKlsJijmVVEyQ+fhkHY30EQKrtYEQ5em0sbqyqn7gHRyzbYsF1vItdcrF81yKx5I/ZFOH9etwaEok09DmPSzcTtq32utVtCizibC9TN1jjKF8rUEZsuZvpLeSeCekbHWgEu+4kKXi75mPuGbY+5i2Z2hE0nCdbYNdZLZwKdthP2Gj8Td4Be9k7+AS22W7yO62LMyRihOT3V0stW2ptj1z+0dtzyft1BY3eGnr7qcB72fln/IQk/NyS3j+HGet4tN6iPYpqTZ1qgYefoS9bASTpy608VAGMZHQJVzCX2gVJ3do7+B20o3pC9wo35H/hW6wT8anxFXii+UrdDDtvY5z6TDNpZO59Di2jAn7s5BYTUxZfVIk1fZ8W9VYR0mKB9UGPFUHJPJiIt7gLhTyArhCc41FPWHoY3370ptDaTzuuRU30ht6u0WG2me320Coxzl3tZW2MM/LO9a7UL3W0vXs6oXkmg0SSLaVZwhMKMncNpaHM0U2y0Jmk8pY194dS9VZoiUeY6MyYf0ttoOfsTfZdrK/Km3htfgZXst2sgt3LE701hoP4CUUycr8xyTdwcb9kZUTWnd+XDOStfb5zXnZa/AfnYyzXvdQwWvnYuuFWvytkZKnE9jWTT0r4CXJmnu1vDyjmYfnW9jC29LbKWf9Q5KZ+f1BOelgujN9gD1cwWf4LK7gBt2Z/lOHdvbwBd364Dsawb95U2M0b/TZByE2MCSfflEUNcBgqxl5liBroxr951J8L+wGqQ4eppp5y8M0COZZnaoD9GWGp0ePNCMnfKBvWtklMmxBHi5anR1e36DXAqY6PRaDP+ptKx5vtWj/rcc3T/akkhW4gYT5U+0jNsJWZhO/yEbsNbzB3srewGvZBbwXF9gOLjxmzpYgJZvyYuSvNJikkrpa+Iul1y6J/tRe3ESZwHSxbHBmy53PNOfabk+iDOa9H6b6S2dM61lemqx/6fbnPdN5rfkrq3zXVo0Goua+wK2QgRikbOYVnmptZshiQ2m5ak9AlOHqkiX3Iw/SDm2Ny1qAPFcjlOeryHBA+8QeHWCCf6PJ2KNbuIZbtIfJ8gd/UzMcMntjD4f6woGSMUtMvjAjaTtPUi8f9/OxzUvQxGRMqYSdfl2pmsrlY+b+RLnq+HA9IClzLAa5TMimWrPPNi8HkYp/1iwhrCa1eQg5wMZsAyNssCTeYqP4ifJvl3F38RfYYFvYYa9gZ7adbJjKU7nNB2+Oz8EP6LaRcuNMbBbuolS72jIJ8bRxCRvMHZo5kWatnRsT5Vv0PP456/tLnzUT7Vm8yB0Vj5vmZXGXUZ8vWMjszBZiqtO1bHEc38Rz1m2JQANNJJ6ES7XShZX0QJlI4/fdqv+2CD3LJsq+NtWFPvsRAQPsYFe/UiD4fVm0+mf9BQIdU3k9TEbX4B/JOU7cwg12AMQnyDUP5jb2LjMlPlaNHetk5SwdxaHWlxWLaj579lWzUbkocKjzDVIZLHH/vVi2nbml0oiNaMy2EQnbueMtRrjILrZy+SnZBnxOzzhZTVHOcSDVFS9VovYawdJpWnV6fdvl3J1t+aGcrXkzNXKbQ7Hma7c5CZqDgrkYi7uASmYUluk0mfeVzV1fcbaFt3b7mICF2VOjQef5ItRcmhd4yacKfKBIbVgAdz3bbVhVWM0vQ9VYW3v0KOue5+DnnjMruI01T8KXW5VZcxpybECzkbDFzbCTGGWcGGEHoHenR13WXhm5aaXSdOKoe0eiKZdO53zxSo0ZWcmnti27uJZ1Yd2Aypb+FRNbvEpwUULPuzRv9aQ2VPTQUi+i5DnJkEzZu7YymcHbT5veNJe8vh6lvLWCVeGbht1tryn7VZBX0jaai0EVZD5VZjnCee638K+12/kialU/VYcv+z5hO+PXT1M940WZ7u308FFO15wfCjqz9qHrauZvWUdt7GfVqTxaj4YNi/88gXsd1rKjKbHW18g2LOzIAwVbnq5mVmpzXhZifbq2vbWWuiqwzcvvWw4zWzbopR/kLs2QTkr9QLg0x3GlP1vXWtnr/uSQee3iltn6FOncPqc/TzifAnik5c/u1TNM4bfIEz6B7+dPv4yndx/fn3XjmM+5an7Pcjn06N/7512vfbZ38zgnvsGz9vqOJ/iR+D+JMPh2zeS5x/nGogq+OSHCH5Zeov0z25Q/JyHC7jxkqb63GHqdNzglRNidXo0+xPajkL6+SRAE35MQYRB0JkQYBJ0JEQZBZ0KEQdCZEGEQdCZEGASdCREGQWdChEHQmRBhEHQmRBgEnQkRBkFnQoRB0JkQYRB0JkQYBJ0JEQZBZ0KEQdCZEGEQdCZEGASdCREGQWdChEHQmRBhEHQmRBgEnQkRBkFnQoRB0JkQYRB0JkQYBJ0JEQZBZ0KEQdCZEGEQdCZEGASdCREGQWdChEHQmRBhEHQmRBgEnQkRBkFnQoRB0JkQYRB0JkQYBJ0JEQZBZ0KEQdCZEGEQdCZEGASdCREGQWdChEHQmRBhEHQmRBgEnQkRBkFnQoRB0JkQYRB0JkQYBJ0JEQZBZ0KEQdCZEGEQdOZ/islWoxBZW2AAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Image operations"
      ],
      "metadata": {
        "id": "kxT84mMJEt7C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "bluehist = cv2.calcHist([img],[0],None,[256],[0,256])\n",
        "greenhist = cv2.calcHist([img],[1],None,[256],[0,256])\n",
        "redhist = cv2.calcHist([img],[2],None,[256],[0,256])\n",
        "  \n",
        "# plot the above computed histogram\n",
        "plt.plot(bluehist, color='b')\n",
        "plt.plot(greenhist, color='g')\n",
        "plt.plot(redhist, color='r')\n",
        "plt.title('Image Histogram For RGB')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "te6_FgeWEwbT",
        "outputId": "6287bdf7-98ae-4fe3-c61a-2546e74c1344"
      },
      "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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Cropping an image"
      ],
      "metadata": {
        "id": "914vlM0WM8H0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cropimg = img[50:250:,50:250,:]\n",
        "cv2_imshow(cropimg)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 217
        },
        "id": "p9CaRdLJM3fz",
        "outputId": "9f981b32-a9e2-4006-ea66-4a1a544fb3cc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=200x200 at 0x7F6530A5F6D0>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bluehist = cv2.calcHist([cropimg],[0],None,[256],[0,256])\n",
        "greenhist = cv2.calcHist([cropimg],[1],None,[256],[0,256])\n",
        "redhist = cv2.calcHist([cropimg],[2],None,[256],[0,256])\n",
        "  \n",
        "# plot the above computed histogram\n",
        "plt.plot(bluehist, color='b')\n",
        "plt.plot(greenhist, color='g')\n",
        "plt.plot(redhist, color='r')\n",
        "plt.title('Image Histogram For RGB')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "y6FVAtAeNB0E",
        "outputId": "73a5b2b3-a1d1-4bb6-f225-5694cf388483"
      },
      "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"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Resize image with opencv"
      ],
      "metadata": {
        "id": "FANij_zmDLML"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cv2_imshow(cv2.resize(img, (100, 100)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 117
        },
        "id": "el4T24o7C_H6",
        "outputId": "5771056f-4c63-4685-d7e6-3f2996b89d15"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=100x100 at 0x7F65309DE190>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Image feature extraction"
      ],
      "metadata": {
        "id": "nyPqkEq8vgDI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Color names"
      ],
      "metadata": {
        "id": "ZjYSrkw1vkiO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install webcolors"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jcFB1rbFvxpI",
        "outputId": "33906aaa-e1e0-4caa-8d26-7c9b7e1ee18a"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting webcolors\n",
            "  Downloading webcolors-1.11.1-py3-none-any.whl (9.9 kB)\n",
            "Installing collected packages: webcolors\n",
            "Successfully installed webcolors-1.11.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import webcolors"
      ],
      "metadata": {
        "id": "KKOiS8K7wy9S"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### List of color names"
      ],
      "metadata": {
        "id": "I4P06wP1wtzH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "webcolors.CSS3_HEX_TO_NAMES"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7Owsy3pvv0_T",
        "outputId": "45498a1b-a11c-4f98-ad07-4d5dc2f2bf6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'#000000': 'black',\n",
              " '#000080': 'navy',\n",
              " '#00008b': 'darkblue',\n",
              " '#0000cd': 'mediumblue',\n",
              " '#0000ff': 'blue',\n",
              " '#006400': 'darkgreen',\n",
              " '#008000': 'green',\n",
              " '#008080': 'teal',\n",
              " '#008b8b': 'darkcyan',\n",
              " '#00bfff': 'deepskyblue',\n",
              " '#00ced1': 'darkturquoise',\n",
              " '#00fa9a': 'mediumspringgreen',\n",
              " '#00ff00': 'lime',\n",
              " '#00ff7f': 'springgreen',\n",
              " '#00ffff': 'cyan',\n",
              " '#191970': 'midnightblue',\n",
              " '#1e90ff': 'dodgerblue',\n",
              " '#20b2aa': 'lightseagreen',\n",
              " '#228b22': 'forestgreen',\n",
              " '#2e8b57': 'seagreen',\n",
              " '#2f4f4f': 'darkslategray',\n",
              " '#32cd32': 'limegreen',\n",
              " '#3cb371': 'mediumseagreen',\n",
              " '#40e0d0': 'turquoise',\n",
              " '#4169e1': 'royalblue',\n",
              " '#4682b4': 'steelblue',\n",
              " '#483d8b': 'darkslateblue',\n",
              " '#48d1cc': 'mediumturquoise',\n",
              " '#4b0082': 'indigo',\n",
              " '#556b2f': 'darkolivegreen',\n",
              " '#5f9ea0': 'cadetblue',\n",
              " '#6495ed': 'cornflowerblue',\n",
              " '#66cdaa': 'mediumaquamarine',\n",
              " '#696969': 'dimgray',\n",
              " '#6a5acd': 'slateblue',\n",
              " '#6b8e23': 'olivedrab',\n",
              " '#708090': 'slategray',\n",
              " '#778899': 'lightslategray',\n",
              " '#7b68ee': 'mediumslateblue',\n",
              " '#7cfc00': 'lawngreen',\n",
              " '#7fff00': 'chartreuse',\n",
              " '#7fffd4': 'aquamarine',\n",
              " '#800000': 'maroon',\n",
              " '#800080': 'purple',\n",
              " '#808000': 'olive',\n",
              " '#808080': 'gray',\n",
              " '#87ceeb': 'skyblue',\n",
              " '#87cefa': 'lightskyblue',\n",
              " '#8a2be2': 'blueviolet',\n",
              " '#8b0000': 'darkred',\n",
              " '#8b008b': 'darkmagenta',\n",
              " '#8b4513': 'saddlebrown',\n",
              " '#8fbc8f': 'darkseagreen',\n",
              " '#90ee90': 'lightgreen',\n",
              " '#9370db': 'mediumpurple',\n",
              " '#9400d3': 'darkviolet',\n",
              " '#98fb98': 'palegreen',\n",
              " '#9932cc': 'darkorchid',\n",
              " '#9acd32': 'yellowgreen',\n",
              " '#a0522d': 'sienna',\n",
              " '#a52a2a': 'brown',\n",
              " '#a9a9a9': 'darkgray',\n",
              " '#add8e6': 'lightblue',\n",
              " '#adff2f': 'greenyellow',\n",
              " '#afeeee': 'paleturquoise',\n",
              " '#b0c4de': 'lightsteelblue',\n",
              " '#b0e0e6': 'powderblue',\n",
              " '#b22222': 'firebrick',\n",
              " '#b8860b': 'darkgoldenrod',\n",
              " '#ba55d3': 'mediumorchid',\n",
              " '#bc8f8f': 'rosybrown',\n",
              " '#bdb76b': 'darkkhaki',\n",
              " '#c0c0c0': 'silver',\n",
              " '#c71585': 'mediumvioletred',\n",
              " '#cd5c5c': 'indianred',\n",
              " '#cd853f': 'peru',\n",
              " '#d2691e': 'chocolate',\n",
              " '#d2b48c': 'tan',\n",
              " '#d3d3d3': 'lightgray',\n",
              " '#d8bfd8': 'thistle',\n",
              " '#da70d6': 'orchid',\n",
              " '#daa520': 'goldenrod',\n",
              " '#db7093': 'palevioletred',\n",
              " '#dc143c': 'crimson',\n",
              " '#dcdcdc': 'gainsboro',\n",
              " '#dda0dd': 'plum',\n",
              " '#deb887': 'burlywood',\n",
              " '#e0ffff': 'lightcyan',\n",
              " '#e6e6fa': 'lavender',\n",
              " '#e9967a': 'darksalmon',\n",
              " '#ee82ee': 'violet',\n",
              " '#eee8aa': 'palegoldenrod',\n",
              " '#f08080': 'lightcoral',\n",
              " '#f0e68c': 'khaki',\n",
              " '#f0f8ff': 'aliceblue',\n",
              " '#f0fff0': 'honeydew',\n",
              " '#f0ffff': 'azure',\n",
              " '#f4a460': 'sandybrown',\n",
              " '#f5deb3': 'wheat',\n",
              " '#f5f5dc': 'beige',\n",
              " '#f5f5f5': 'whitesmoke',\n",
              " '#f5fffa': 'mintcream',\n",
              " '#f8f8ff': 'ghostwhite',\n",
              " '#fa8072': 'salmon',\n",
              " '#faebd7': 'antiquewhite',\n",
              " '#faf0e6': 'linen',\n",
              " '#fafad2': 'lightgoldenrodyellow',\n",
              " '#fdf5e6': 'oldlace',\n",
              " '#ff0000': 'red',\n",
              " '#ff00ff': 'magenta',\n",
              " '#ff1493': 'deeppink',\n",
              " '#ff4500': 'orangered',\n",
              " '#ff6347': 'tomato',\n",
              " '#ff69b4': 'hotpink',\n",
              " '#ff7f50': 'coral',\n",
              " '#ff8c00': 'darkorange',\n",
              " '#ffa07a': 'lightsalmon',\n",
              " '#ffa500': 'orange',\n",
              " '#ffb6c1': 'lightpink',\n",
              " '#ffc0cb': 'pink',\n",
              " '#ffd700': 'gold',\n",
              " '#ffdab9': 'peachpuff',\n",
              " '#ffdead': 'navajowhite',\n",
              " '#ffe4b5': 'moccasin',\n",
              " '#ffe4c4': 'bisque',\n",
              " '#ffe4e1': 'mistyrose',\n",
              " '#ffebcd': 'blanchedalmond',\n",
              " '#ffefd5': 'papayawhip',\n",
              " '#fff0f5': 'lavenderblush',\n",
              " '#fff5ee': 'seashell',\n",
              " '#fff8dc': 'cornsilk',\n",
              " '#fffacd': 'lemonchiffon',\n",
              " '#fffaf0': 'floralwhite',\n",
              " '#fffafa': 'snow',\n",
              " '#ffff00': 'yellow',\n",
              " '#ffffe0': 'lightyellow',\n",
              " '#fffff0': 'ivory',\n",
              " '#ffffff': 'white'}"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Count colors"
      ],
      "metadata": {
        "id": "wn-fXAiySdOx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "colors = {}\n",
        "for c in webcolors.CSS3_HEX_TO_NAMES.values():\n",
        "  colors[c] = 0\n",
        "\n",
        "img_shape = img.shape\n",
        "flatten_img = img.reshape(img_shape[0] * img_shape[1], 3)\n",
        "for pixel in flatten_img:\n",
        "  try:\n",
        "    colors[webcolors.rgb_to_name(pixel)] += 1\n",
        "  except:\n",
        "    pass\n",
        "\n",
        "colors"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tsSyHsuvVEp2",
        "outputId": "93582338-b829-4f7a-c000-3720d6eeb080"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'aliceblue': 2,\n",
              " 'antiquewhite': 0,\n",
              " 'aquamarine': 0,\n",
              " 'azure': 0,\n",
              " 'beige': 0,\n",
              " 'bisque': 0,\n",
              " 'black': 0,\n",
              " 'blanchedalmond': 0,\n",
              " 'blue': 0,\n",
              " 'blueviolet': 0,\n",
              " 'brown': 0,\n",
              " 'burlywood': 0,\n",
              " 'cadetblue': 0,\n",
              " 'chartreuse': 0,\n",
              " 'chocolate': 0,\n",
              " 'coral': 0,\n",
              " 'cornflowerblue': 0,\n",
              " 'cornsilk': 0,\n",
              " 'crimson': 0,\n",
              " 'cyan': 0,\n",
              " 'darkblue': 0,\n",
              " 'darkcyan': 0,\n",
              " 'darkgoldenrod': 0,\n",
              " 'darkgray': 0,\n",
              " 'darkgreen': 0,\n",
              " 'darkkhaki': 0,\n",
              " 'darkmagenta': 0,\n",
              " 'darkolivegreen': 0,\n",
              " 'darkorange': 0,\n",
              " 'darkorchid': 0,\n",
              " 'darkred': 0,\n",
              " 'darksalmon': 0,\n",
              " 'darkseagreen': 0,\n",
              " 'darkslateblue': 0,\n",
              " 'darkslategray': 0,\n",
              " 'darkturquoise': 0,\n",
              " 'darkviolet': 0,\n",
              " 'deeppink': 0,\n",
              " 'deepskyblue': 0,\n",
              " 'dimgray': 0,\n",
              " 'dodgerblue': 0,\n",
              " 'firebrick': 0,\n",
              " 'floralwhite': 1,\n",
              " 'forestgreen': 0,\n",
              " 'gainsboro': 0,\n",
              " 'ghostwhite': 0,\n",
              " 'gold': 0,\n",
              " 'goldenrod': 0,\n",
              " 'gray': 0,\n",
              " 'green': 0,\n",
              " 'greenyellow': 0,\n",
              " 'honeydew': 0,\n",
              " 'hotpink': 0,\n",
              " 'indianred': 0,\n",
              " 'indigo': 0,\n",
              " 'ivory': 0,\n",
              " 'khaki': 0,\n",
              " 'lavender': 0,\n",
              " 'lavenderblush': 0,\n",
              " 'lawngreen': 0,\n",
              " 'lemonchiffon': 0,\n",
              " 'lightblue': 0,\n",
              " 'lightcoral': 0,\n",
              " 'lightcyan': 0,\n",
              " 'lightgoldenrodyellow': 0,\n",
              " 'lightgray': 0,\n",
              " 'lightgreen': 0,\n",
              " 'lightpink': 0,\n",
              " 'lightsalmon': 0,\n",
              " 'lightseagreen': 0,\n",
              " 'lightskyblue': 0,\n",
              " 'lightslategray': 0,\n",
              " 'lightsteelblue': 0,\n",
              " 'lightyellow': 0,\n",
              " 'lime': 0,\n",
              " 'limegreen': 0,\n",
              " 'linen': 0,\n",
              " 'magenta': 0,\n",
              " 'maroon': 0,\n",
              " 'mediumaquamarine': 0,\n",
              " 'mediumblue': 0,\n",
              " 'mediumorchid': 0,\n",
              " 'mediumpurple': 0,\n",
              " 'mediumseagreen': 0,\n",
              " 'mediumslateblue': 0,\n",
              " 'mediumspringgreen': 0,\n",
              " 'mediumturquoise': 0,\n",
              " 'mediumvioletred': 0,\n",
              " 'midnightblue': 0,\n",
              " 'mintcream': 0,\n",
              " 'mistyrose': 0,\n",
              " 'moccasin': 0,\n",
              " 'navajowhite': 0,\n",
              " 'navy': 0,\n",
              " 'oldlace': 0,\n",
              " 'olive': 0,\n",
              " 'olivedrab': 0,\n",
              " 'orange': 0,\n",
              " 'orangered': 0,\n",
              " 'orchid': 0,\n",
              " 'palegoldenrod': 0,\n",
              " 'palegreen': 0,\n",
              " 'paleturquoise': 0,\n",
              " 'palevioletred': 0,\n",
              " 'papayawhip': 0,\n",
              " 'peachpuff': 0,\n",
              " 'peru': 0,\n",
              " 'pink': 0,\n",
              " 'plum': 0,\n",
              " 'powderblue': 0,\n",
              " 'purple': 0,\n",
              " 'red': 0,\n",
              " 'rosybrown': 0,\n",
              " 'royalblue': 0,\n",
              " 'saddlebrown': 0,\n",
              " 'salmon': 0,\n",
              " 'sandybrown': 0,\n",
              " 'seagreen': 0,\n",
              " 'seashell': 1,\n",
              " 'sienna': 0,\n",
              " 'silver': 0,\n",
              " 'skyblue': 0,\n",
              " 'slateblue': 0,\n",
              " 'slategray': 0,\n",
              " 'snow': 1,\n",
              " 'springgreen': 0,\n",
              " 'steelblue': 0,\n",
              " 'tan': 0,\n",
              " 'teal': 0,\n",
              " 'thistle': 0,\n",
              " 'tomato': 0,\n",
              " 'turquoise': 0,\n",
              " 'violet': 0,\n",
              " 'wheat': 0,\n",
              " 'white': 42803,\n",
              " 'whitesmoke': 2,\n",
              " 'yellow': 0,\n",
              " 'yellowgreen': 0}"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Count colors in df\n",
        "\n",
        "Initialize color count to zero in `df`."
      ],
      "metadata": {
        "id": "OiIHnrnCVBzO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for c in webcolors.CSS3_HEX_TO_NAMES.values():\n",
        "  df[c] = 0\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "_nWZJGxvO2xB",
        "outputId": "cce4b4e0-278e-4202-bd1c-a1067616f107"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                name      id  \\\n",
              "0                   Alkaline Water 9.0 (random Pick)  499585   \n",
              "1     Alkaline Water 9.0 (case) (420ml X 24 Bottles)  378829   \n",
              "2              L Type Interdental Brush 0.6mm - 6pcs  805629   \n",
              "3                L Type Interdental Brush 0.8mm 6pcs  805630   \n",
              "4                I Type Interdental Brush 0.7mm 5pcs  805627   \n",
              "...                                              ...     ...   \n",
              "6722                            Kitchen  Towel 9inch  365593   \n",
              "6723                       Chauzhou Style Fish Balls   51761   \n",
              "6724                              Alkaline Ion Water  483353   \n",
              "6725                              Mushroom Pork Ball   55251   \n",
              "6726                                Cuttle Fish Ball   51759   \n",
              "\n",
              "                                                    url  \\\n",
              "0     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "1     https://www.parknshop.com/en/alkaline-water-9-...   \n",
              "2     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "3     https://www.parknshop.com/en/l-type-interdenta...   \n",
              "4     https://www.parknshop.com/en/i-type-interdenta...   \n",
              "...                                                 ...   \n",
              "6722  https://www.parknshop.com/en/kitchen-towel-9in...   \n",
              "6723  https://www.parknshop.com/en/chauzhou-style-fi...   \n",
              "6724  https://www.parknshop.com/en/alkaline-ion-wate...   \n",
              "6725  https://www.parknshop.com/en/mushroom-pork-bal...   \n",
              "6726  https://www.parknshop.com/en/cuttle-fish-ball/...   \n",
              "\n",
              "                                                    pic  price  \\\n",
              "0     https://www.parknshop.com/medias/sys_master/fr...    9.0   \n",
              "1     https://www.parknshop.com/medias/sys_master/fr...  168.0   \n",
              "2     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "3     https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "4     https://www.parknshop.com/medias/sys_master/fr...   10.0   \n",
              "...                                                 ...    ...   \n",
              "6722  https://www.parknshop.com/medias/sys_master/fr...   25.9   \n",
              "6723  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "6724  https://www.parknshop.com/medias/sys_master/fr...   19.9   \n",
              "6725  https://www.parknshop.com/medias/sys_master/fr...   13.9   \n",
              "6726  https://www.parknshop.com/medias/sys_master/fr...    8.4   \n",
              "\n",
              "                specialoffer                brand  \\\n",
              "0                        NaN              WATSONS   \n",
              "1                        NaN              WATSONS   \n",
              "2               $20.8 / 2pcs              WATSONS   \n",
              "3               $20.8 / 2pcs              WATSONS   \n",
              "4               $15.0 / 2pcs              WATSONS   \n",
              "...                      ...                  ...   \n",
              "6722  MONEYBACK MEMBER OFFER             BEST BUY   \n",
              "6723  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6724  MONEYBACK MEMBER OFFER                KIRIN   \n",
              "6725  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "6726  MONEYBACK MEMBER OFFER  JIU LONG CHENG ZHAI   \n",
              "\n",
              "                          category  variant variantname  ...  teal  thistle  \\\n",
              "0                            Water   499585       420ML  ...     0        0   \n",
              "1              Water,Bottled Water   378829    24X420ML  ...     0        0   \n",
              "2     Dental Accessories & Denture   805629          6S  ...     0        0   \n",
              "3     Dental Accessories & Denture   805630          6S  ...     0        0   \n",
              "4     Dental Accessories & Denture   805627          5S  ...     0        0   \n",
              "...                            ...      ...         ...  ...   ...      ...   \n",
              "6722                           NaN   365593          6S  ...     0        0   \n",
              "6723                 Seafood Balls    51761    170G/PKT  ...     0        0   \n",
              "6724                         Water   483353          2L  ...     0        0   \n",
              "6725                    Meat Balls    55251        170G  ...     0        0   \n",
              "6726                 Seafood Balls    51759    170G/PKT  ...     0        0   \n",
              "\n",
              "      tomato  turquoise  violet  wheat white whitesmoke yellow yellowgreen  \n",
              "0          0          0       0      0     0          0      0           0  \n",
              "1          0          0       0      0     0          0      0           0  \n",
              "2          0          0       0      0     0          0      0           0  \n",
              "3          0          0       0      0     0          0      0           0  \n",
              "4          0          0       0      0     0          0      0           0  \n",
              "...      ...        ...     ...    ...   ...        ...    ...         ...  \n",
              "6722       0          0       0      0     0          0      0           0  \n",
              "6723       0          0       0      0     0          0      0           0  \n",
              "6724       0          0       0      0     0          0      0           0  \n",
              "6725       0          0       0      0     0          0      0           0  \n",
              "6726       0          0       0      0     0          0      0           0  \n",
              "\n",
              "[6727 rows x 161 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fcaf4318-e522-4391-bb1f-40c6cb8f28d6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>url</th>\n",
              "      <th>pic</th>\n",
              "      <th>price</th>\n",
              "      <th>specialoffer</th>\n",
              "      <th>brand</th>\n",
              "      <th>category</th>\n",
              "      <th>variant</th>\n",
              "      <th>variantname</th>\n",
              "      <th>...</th>\n",
              "      <th>teal</th>\n",
              "      <th>thistle</th>\n",
              "      <th>tomato</th>\n",
              "      <th>turquoise</th>\n",
              "      <th>violet</th>\n",
              "      <th>wheat</th>\n",
              "      <th>white</th>\n",
              "      <th>whitesmoke</th>\n",
              "      <th>yellow</th>\n",
              "      <th>yellowgreen</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alkaline Water 9.0 (random Pick)</td>\n",
              "      <td>499585</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water</td>\n",
              "      <td>499585</td>\n",
              "      <td>420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alkaline Water 9.0 (case) (420ml X 24 Bottles)</td>\n",
              "      <td>378829</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-water-9-...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>168.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Water,Bottled Water</td>\n",
              "      <td>378829</td>\n",
              "      <td>24X420ML</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>L Type Interdental Brush 0.6mm - 6pcs</td>\n",
              "      <td>805629</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805629</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>L Type Interdental Brush 0.8mm 6pcs</td>\n",
              "      <td>805630</td>\n",
              "      <td>https://www.parknshop.com/en/l-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>$20.8 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805630</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>I Type Interdental Brush 0.7mm 5pcs</td>\n",
              "      <td>805627</td>\n",
              "      <td>https://www.parknshop.com/en/i-type-interdenta...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>10.0</td>\n",
              "      <td>$15.0 / 2pcs</td>\n",
              "      <td>WATSONS</td>\n",
              "      <td>Dental Accessories &amp; Denture</td>\n",
              "      <td>805627</td>\n",
              "      <td>5S</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6722</th>\n",
              "      <td>Kitchen  Towel 9inch</td>\n",
              "      <td>365593</td>\n",
              "      <td>https://www.parknshop.com/en/kitchen-towel-9in...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>25.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>BEST BUY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>365593</td>\n",
              "      <td>6S</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6723</th>\n",
              "      <td>Chauzhou Style Fish Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>https://www.parknshop.com/en/chauzhou-style-fi...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51761</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6724</th>\n",
              "      <td>Alkaline Ion Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>https://www.parknshop.com/en/alkaline-ion-wate...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>19.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>KIRIN</td>\n",
              "      <td>Water</td>\n",
              "      <td>483353</td>\n",
              "      <td>2L</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6725</th>\n",
              "      <td>Mushroom Pork Ball</td>\n",
              "      <td>55251</td>\n",
              "      <td>https://www.parknshop.com/en/mushroom-pork-bal...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>13.9</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Meat Balls</td>\n",
              "      <td>55251</td>\n",
              "      <td>170G</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6726</th>\n",
              "      <td>Cuttle Fish Ball</td>\n",
              "      <td>51759</td>\n",
              "      <td>https://www.parknshop.com/en/cuttle-fish-ball/...</td>\n",
              "      <td>https://www.parknshop.com/medias/sys_master/fr...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>MONEYBACK MEMBER OFFER</td>\n",
              "      <td>JIU LONG CHENG ZHAI</td>\n",
              "      <td>Seafood Balls</td>\n",
              "      <td>51759</td>\n",
              "      <td>170G/PKT</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6727 rows × 161 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fcaf4318-e522-4391-bb1f-40c6cb8f28d6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fcaf4318-e522-4391-bb1f-40c6cb8f28d6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fcaf4318-e522-4391-bb1f-40c6cb8f28d6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Wrapping code with a function"
      ],
      "metadata": {
        "id": "sNQUu8tIYt-E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def countColors(row):\n",
        "  datashape = row['picdata'].shape\n",
        "  flattendata = row['picdata'].reshape(datashape[0] * datashape[1], 3)\n",
        "  for c in flattendata:\n",
        "    try:\n",
        "      row[webcolors.rgb_to_name(c)] += 1\n",
        "    except:\n",
        "      pass\n",
        "  return row"
      ],
      "metadata": {
        "id": "1H2eHdM_Pya3"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "And then apply it to the `df`, and it will take very long time to process."
      ],
      "metadata": {
        "id": "-6TAPqZAYyqt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.apply(countColors, axis=1)"
      ],
      "metadata": {
        "id": "l7TT-YmQQJcY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Extract text with Optical character recognition (OCR)"
      ],
      "metadata": {
        "id": "yQbuXA0DvplA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!add-apt-repository -y ppa:alex-p/tesseract-ocr5\n",
        "!apt install -y tesseract-ocr tesseract-ocr-all\n",
        "!pip install pytesseract"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c1kvS31msbbz",
        "outputId": "d066d543-0285-4bbf-d756-e22dc5ca6d1f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hit:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease\n",
            "Hit:2 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic InRelease\n",
            "Get:3 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n",
            "Ign:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n",
            "Hit:5 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
            "Ign:6 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n",
            "Hit:7 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release\n",
            "Hit:8 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n",
            "Get:9 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n",
            "Hit:10 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease\n",
            "Hit:11 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
            "Get:12 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n",
            "Hit:13 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
            "Hit:14 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n",
            "Fetched 252 kB in 3s (94.7 kB/s)\n",
            "Reading package lists... Done\n",
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "tesseract-ocr is already the newest version (5.1.0-1ppa1~bionic1).\n",
            "The following additional packages will be installed:\n",
            "  tesseract-ocr-afr tesseract-ocr-amh tesseract-ocr-ara tesseract-ocr-asm\n",
            "  tesseract-ocr-aze tesseract-ocr-aze-cyrl tesseract-ocr-bel tesseract-ocr-ben\n",
            "  tesseract-ocr-bod tesseract-ocr-bos tesseract-ocr-bre tesseract-ocr-bul\n",
            "  tesseract-ocr-cat tesseract-ocr-ceb tesseract-ocr-ces tesseract-ocr-chi-sim\n",
            "  tesseract-ocr-chi-sim-vert tesseract-ocr-chi-tra tesseract-ocr-chi-tra-vert\n",
            "  tesseract-ocr-chr tesseract-ocr-cos tesseract-ocr-cym tesseract-ocr-dan\n",
            "  tesseract-ocr-deu tesseract-ocr-div tesseract-ocr-dzo tesseract-ocr-ell\n",
            "  tesseract-ocr-enm tesseract-ocr-epo tesseract-ocr-est tesseract-ocr-eus\n",
            "  tesseract-ocr-fao tesseract-ocr-fas tesseract-ocr-fil tesseract-ocr-fin\n",
            "  tesseract-ocr-fra tesseract-ocr-frk tesseract-ocr-frm tesseract-ocr-fry\n",
            "  tesseract-ocr-gla tesseract-ocr-gle tesseract-ocr-glg tesseract-ocr-grc\n",
            "  tesseract-ocr-guj tesseract-ocr-hat tesseract-ocr-heb tesseract-ocr-hin\n",
            "  tesseract-ocr-hrv tesseract-ocr-hun tesseract-ocr-hye tesseract-ocr-iku\n",
            "  tesseract-ocr-ind tesseract-ocr-isl tesseract-ocr-ita tesseract-ocr-ita-old\n",
            "  tesseract-ocr-jav tesseract-ocr-jpn tesseract-ocr-jpn-vert tesseract-ocr-kan\n",
            "  tesseract-ocr-kat tesseract-ocr-kat-old tesseract-ocr-kaz tesseract-ocr-khm\n",
            "  tesseract-ocr-kir tesseract-ocr-kmr tesseract-ocr-kor tesseract-ocr-kor-vert\n",
            "  tesseract-ocr-lao tesseract-ocr-lat tesseract-ocr-lav tesseract-ocr-lit\n",
            "  tesseract-ocr-ltz tesseract-ocr-mal tesseract-ocr-mar tesseract-ocr-mkd\n",
            "  tesseract-ocr-mlt tesseract-ocr-mon tesseract-ocr-mri tesseract-ocr-msa\n",
            "  tesseract-ocr-mya tesseract-ocr-nep tesseract-ocr-nld tesseract-ocr-nor\n",
            "  tesseract-ocr-oci tesseract-ocr-ori tesseract-ocr-pan tesseract-ocr-pol\n",
            "  tesseract-ocr-por tesseract-ocr-pus tesseract-ocr-que tesseract-ocr-ron\n",
            "  tesseract-ocr-rus tesseract-ocr-san tesseract-ocr-script-arab\n",
            "  tesseract-ocr-script-armn tesseract-ocr-script-beng\n",
            "  tesseract-ocr-script-cans tesseract-ocr-script-cher\n",
            "  tesseract-ocr-script-cyrl tesseract-ocr-script-deva\n",
            "  tesseract-ocr-script-ethi tesseract-ocr-script-frak\n",
            "  tesseract-ocr-script-geor tesseract-ocr-script-grek\n",
            "  tesseract-ocr-script-gujr tesseract-ocr-script-guru\n",
            "  tesseract-ocr-script-hang tesseract-ocr-script-hang-vert\n",
            "  tesseract-ocr-script-hans tesseract-ocr-script-hans-vert\n",
            "  tesseract-ocr-script-hant tesseract-ocr-script-hant-vert\n",
            "  tesseract-ocr-script-hebr tesseract-ocr-script-jpan\n",
            "  tesseract-ocr-script-jpan-vert tesseract-ocr-script-khmr\n",
            "  tesseract-ocr-script-knda tesseract-ocr-script-laoo\n",
            "  tesseract-ocr-script-latn tesseract-ocr-script-mlym\n",
            "  tesseract-ocr-script-mymr tesseract-ocr-script-orya\n",
            "  tesseract-ocr-script-sinh tesseract-ocr-script-syrc\n",
            "  tesseract-ocr-script-taml tesseract-ocr-script-telu\n",
            "  tesseract-ocr-script-thaa tesseract-ocr-script-thai\n",
            "  tesseract-ocr-script-tibt tesseract-ocr-script-viet tesseract-ocr-sin\n",
            "  tesseract-ocr-slk tesseract-ocr-slv tesseract-ocr-snd tesseract-ocr-spa\n",
            "  tesseract-ocr-spa-old tesseract-ocr-sqi tesseract-ocr-srp\n",
            "  tesseract-ocr-srp-latn tesseract-ocr-sun tesseract-ocr-swa tesseract-ocr-swe\n",
            "  tesseract-ocr-syr tesseract-ocr-tam tesseract-ocr-tat tesseract-ocr-tel\n",
            "  tesseract-ocr-tgk tesseract-ocr-tha tesseract-ocr-tir tesseract-ocr-ton\n",
            "  tesseract-ocr-tur tesseract-ocr-uig tesseract-ocr-ukr tesseract-ocr-urd\n",
            "  tesseract-ocr-uzb tesseract-ocr-uzb-cyrl tesseract-ocr-vie tesseract-ocr-yid\n",
            "  tesseract-ocr-yor\n",
            "The following NEW packages will be installed:\n",
            "  tesseract-ocr-afr tesseract-ocr-all tesseract-ocr-amh tesseract-ocr-ara\n",
            "  tesseract-ocr-asm tesseract-ocr-aze tesseract-ocr-aze-cyrl tesseract-ocr-bel\n",
            "  tesseract-ocr-ben tesseract-ocr-bod tesseract-ocr-bos tesseract-ocr-bre\n",
            "  tesseract-ocr-bul tesseract-ocr-cat tesseract-ocr-ceb tesseract-ocr-ces\n",
            "  tesseract-ocr-chi-sim tesseract-ocr-chi-sim-vert tesseract-ocr-chi-tra\n",
            "  tesseract-ocr-chi-tra-vert tesseract-ocr-chr tesseract-ocr-cos\n",
            "  tesseract-ocr-cym tesseract-ocr-dan tesseract-ocr-deu tesseract-ocr-div\n",
            "  tesseract-ocr-dzo tesseract-ocr-ell tesseract-ocr-enm tesseract-ocr-epo\n",
            "  tesseract-ocr-est tesseract-ocr-eus tesseract-ocr-fao tesseract-ocr-fas\n",
            "  tesseract-ocr-fil tesseract-ocr-fin tesseract-ocr-fra tesseract-ocr-frk\n",
            "  tesseract-ocr-frm tesseract-ocr-fry tesseract-ocr-gla tesseract-ocr-gle\n",
            "  tesseract-ocr-glg tesseract-ocr-grc tesseract-ocr-guj tesseract-ocr-hat\n",
            "  tesseract-ocr-heb tesseract-ocr-hin tesseract-ocr-hrv tesseract-ocr-hun\n",
            "  tesseract-ocr-hye tesseract-ocr-iku tesseract-ocr-ind tesseract-ocr-isl\n",
            "  tesseract-ocr-ita tesseract-ocr-ita-old tesseract-ocr-jav tesseract-ocr-jpn\n",
            "  tesseract-ocr-jpn-vert tesseract-ocr-kan tesseract-ocr-kat\n",
            "  tesseract-ocr-kat-old tesseract-ocr-kaz tesseract-ocr-khm tesseract-ocr-kir\n",
            "  tesseract-ocr-kmr tesseract-ocr-kor tesseract-ocr-kor-vert tesseract-ocr-lao\n",
            "  tesseract-ocr-lat tesseract-ocr-lav tesseract-ocr-lit tesseract-ocr-ltz\n",
            "  tesseract-ocr-mal tesseract-ocr-mar tesseract-ocr-mkd tesseract-ocr-mlt\n",
            "  tesseract-ocr-mon tesseract-ocr-mri tesseract-ocr-msa tesseract-ocr-mya\n",
            "  tesseract-ocr-nep tesseract-ocr-nld tesseract-ocr-nor tesseract-ocr-oci\n",
            "  tesseract-ocr-ori tesseract-ocr-pan tesseract-ocr-pol tesseract-ocr-por\n",
            "  tesseract-ocr-pus tesseract-ocr-que tesseract-ocr-ron tesseract-ocr-rus\n",
            "  tesseract-ocr-san tesseract-ocr-script-arab tesseract-ocr-script-armn\n",
            "  tesseract-ocr-script-beng tesseract-ocr-script-cans\n",
            "  tesseract-ocr-script-cher tesseract-ocr-script-cyrl\n",
            "  tesseract-ocr-script-deva tesseract-ocr-script-ethi\n",
            "  tesseract-ocr-script-frak tesseract-ocr-script-geor\n",
            "  tesseract-ocr-script-grek tesseract-ocr-script-gujr\n",
            "  tesseract-ocr-script-guru tesseract-ocr-script-hang\n",
            "  tesseract-ocr-script-hang-vert tesseract-ocr-script-hans\n",
            "  tesseract-ocr-script-hans-vert tesseract-ocr-script-hant\n",
            "  tesseract-ocr-script-hant-vert tesseract-ocr-script-hebr\n",
            "  tesseract-ocr-script-jpan tesseract-ocr-script-jpan-vert\n",
            "  tesseract-ocr-script-khmr tesseract-ocr-script-knda\n",
            "  tesseract-ocr-script-laoo tesseract-ocr-script-latn\n",
            "  tesseract-ocr-script-mlym tesseract-ocr-script-mymr\n",
            "  tesseract-ocr-script-orya tesseract-ocr-script-sinh\n",
            "  tesseract-ocr-script-syrc tesseract-ocr-script-taml\n",
            "  tesseract-ocr-script-telu tesseract-ocr-script-thaa\n",
            "  tesseract-ocr-script-thai tesseract-ocr-script-tibt\n",
            "  tesseract-ocr-script-viet tesseract-ocr-sin tesseract-ocr-slk\n",
            "  tesseract-ocr-slv tesseract-ocr-snd tesseract-ocr-spa tesseract-ocr-spa-old\n",
            "  tesseract-ocr-sqi tesseract-ocr-srp tesseract-ocr-srp-latn tesseract-ocr-sun\n",
            "  tesseract-ocr-swa tesseract-ocr-swe tesseract-ocr-syr tesseract-ocr-tam\n",
            "  tesseract-ocr-tat tesseract-ocr-tel tesseract-ocr-tgk tesseract-ocr-tha\n",
            "  tesseract-ocr-tir tesseract-ocr-ton tesseract-ocr-tur tesseract-ocr-uig\n",
            "  tesseract-ocr-ukr tesseract-ocr-urd tesseract-ocr-uzb tesseract-ocr-uzb-cyrl\n",
            "  tesseract-ocr-vie tesseract-ocr-yid tesseract-ocr-yor\n",
            "0 upgraded, 160 newly installed, 0 to remove and 80 not upgraded.\n",
            "Need to get 282 MB of archives.\n",
            "After this operation, 686 MB of additional disk space will be used.\n",
            "Get:1 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-afr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,733 kB]\n",
            "Get:2 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-bul all 1:5.0.0~git39-6572757-2ppa1~bionic1 [679 kB]\n",
            "Get:3 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-cat all 1:5.0.0~git39-6572757-2ppa1~bionic1 [580 kB]\n",
            "Get:4 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ces all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,410 kB]\n",
            "Get:5 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-dan all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,028 kB]\n",
            "Get:6 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-deu all 1:5.0.0~git39-6572757-2ppa1~bionic1 [745 kB]\n",
            "Get:7 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ell all 1:5.0.0~git39-6572757-2ppa1~bionic1 [596 kB]\n",
            "Get:8 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fin all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,032 kB]\n",
            "Get:9 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fra all 1:5.0.0~git39-6572757-2ppa1~bionic1 [529 kB]\n",
            "Get:10 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-hun all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,854 kB]\n",
            "Get:11 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ind all 1:5.0.0~git39-6572757-2ppa1~bionic1 [538 kB]\n",
            "Get:12 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ita all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,064 kB]\n",
            "Get:13 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-lav all 1:5.0.0~git39-6572757-2ppa1~bionic1 [982 kB]\n",
            "Get:14 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-lit all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,142 kB]\n",
            "Get:15 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-nld all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,308 kB]\n",
            "Get:16 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-nor all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,750 kB]\n",
            "Get:17 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-pol all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,608 kB]\n",
            "Get:18 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-por all 1:5.0.0~git39-6572757-2ppa1~bionic1 [858 kB]\n",
            "Get:19 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ron all 1:5.0.0~git39-6572757-2ppa1~bionic1 [898 kB]\n",
            "Get:20 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-rus all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,273 kB]\n",
            "Get:21 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-slk all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,503 kB]\n",
            "Get:22 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-slv all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,003 kB]\n",
            "Get:23 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-spa all 1:5.0.0~git39-6572757-2ppa1~bionic1 [953 kB]\n",
            "Get:24 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-srp all 1:5.0.0~git39-6572757-2ppa1~bionic1 [786 kB]\n",
            "Get:25 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-swe all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,235 kB]\n",
            "Get:26 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tur all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,583 kB]\n",
            "Get:27 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ukr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,304 kB]\n",
            "Get:28 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-vie all 1:5.0.0~git39-6572757-2ppa1~bionic1 [419 kB]\n",
            "Get:29 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-chi-sim all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,635 kB]\n",
            "Get:30 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-chi-tra all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,585 kB]\n",
            "Get:31 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-amh all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,857 kB]\n",
            "Get:32 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-asm all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,423 kB]\n",
            "Get:33 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-aze-cyrl all 1:5.0.0~git39-6572757-2ppa1~bionic1 [852 kB]\n",
            "Get:34 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-bod all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,181 kB]\n",
            "Get:35 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-bos all 1:5.0.0~git39-6572757-2ppa1~bionic1 [966 kB]\n",
            "Get:36 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ceb all 1:5.0.0~git39-6572757-2ppa1~bionic1 [471 kB]\n",
            "Get:37 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-cym all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,258 kB]\n",
            "Get:38 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-dzo all 1:5.0.0~git39-6572757-2ppa1~bionic1 [391 kB]\n",
            "Get:39 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fas all 1:5.0.0~git39-6572757-2ppa1~bionic1 [302 kB]\n",
            "Get:40 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-gle all 1:5.0.0~git39-6572757-2ppa1~bionic1 [614 kB]\n",
            "Get:41 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-guj all 1:5.0.0~git39-6572757-2ppa1~bionic1 [662 kB]\n",
            "Get:42 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-hat all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,489 kB]\n",
            "Get:43 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-iku all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,212 kB]\n",
            "Get:44 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-jav all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,444 kB]\n",
            "Get:45 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kat all 1:5.0.0~git39-6572757-2ppa1~bionic1 [885 kB]\n",
            "Get:46 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kat-old all 1:5.0.0~git39-6572757-2ppa1~bionic1 [381 kB]\n",
            "Get:47 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kaz all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,688 kB]\n",
            "Get:48 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-khm all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,034 kB]\n",
            "Get:49 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kir all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,279 kB]\n",
            "Get:50 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-lao all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,412 kB]\n",
            "Get:51 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-lat all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,532 kB]\n",
            "Get:52 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mar all 1:5.0.0~git39-6572757-2ppa1~bionic1 [862 kB]\n",
            "Get:53 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mya all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,360 kB]\n",
            "Get:54 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-nep all 1:5.0.0~git39-6572757-2ppa1~bionic1 [480 kB]\n",
            "Get:55 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ori all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,026 kB]\n",
            "Get:56 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-pan all 1:5.0.0~git39-6572757-2ppa1~bionic1 [324 kB]\n",
            "Get:57 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-pus all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,416 kB]\n",
            "Get:58 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-san all 1:5.0.0~git39-6572757-2ppa1~bionic1 [4,228 kB]\n",
            "Get:59 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-sin all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,087 kB]\n",
            "Get:60 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-srp-latn all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,561 kB]\n",
            "Get:61 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-syr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,559 kB]\n",
            "Get:62 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tgk all 1:5.0.0~git39-6572757-2ppa1~bionic1 [954 kB]\n",
            "Get:63 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tir all 1:5.0.0~git39-6572757-2ppa1~bionic1 [299 kB]\n",
            "Get:64 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-uig all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,744 kB]\n",
            "Get:65 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-urd all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,002 kB]\n",
            "Get:66 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-uzb-cyrl all 1:5.0.0~git39-6572757-2ppa1~bionic1 [731 kB]\n",
            "Get:67 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-uzb all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,537 kB]\n",
            "Get:68 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-yid all 1:5.0.0~git39-6572757-2ppa1~bionic1 [346 kB]\n",
            "Get:69 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ara all 1:5.0.0~git39-6572757-2ppa1~bionic1 [646 kB]\n",
            "Get:70 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-aze all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,349 kB]\n",
            "Get:71 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-bel all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,190 kB]\n",
            "Get:72 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ben all 1:5.0.0~git39-6572757-2ppa1~bionic1 [517 kB]\n",
            "Get:73 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-chr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [289 kB]\n",
            "Get:74 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-enm all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,846 kB]\n",
            "Get:75 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-epo all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,710 kB]\n",
            "Get:76 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-est all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,587 kB]\n",
            "Get:77 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-eus all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,769 kB]\n",
            "Get:78 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-frk all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,726 kB]\n",
            "Get:79 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-frm all 1:5.0.0~git39-6572757-2ppa1~bionic1 [831 kB]\n",
            "Get:80 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-glg all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,657 kB]\n",
            "Get:81 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-heb all 1:5.0.0~git39-6572757-2ppa1~bionic1 [433 kB]\n",
            "Get:82 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-hin all 1:5.0.0~git39-6572757-2ppa1~bionic1 [914 kB]\n",
            "Get:83 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-hrv all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,439 kB]\n",
            "Get:84 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-isl all 1:5.0.0~git39-6572757-2ppa1~bionic1 [914 kB]\n",
            "Get:85 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ita-old all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,568 kB]\n",
            "Get:86 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-jpn all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,391 kB]\n",
            "Get:87 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kan all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,660 kB]\n",
            "Get:88 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kor all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,054 kB]\n",
            "Get:89 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mal all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,680 kB]\n",
            "Get:90 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mkd all 1:5.0.0~git39-6572757-2ppa1~bionic1 [719 kB]\n",
            "Get:91 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mlt all 1:5.0.0~git39-6572757-2ppa1~bionic1 [977 kB]\n",
            "Get:92 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-msa all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,116 kB]\n",
            "Get:93 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-spa-old all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,475 kB]\n",
            "Get:94 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-sqi all 1:5.0.0~git39-6572757-2ppa1~bionic1 [721 kB]\n",
            "Get:95 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-swa all 1:5.0.0~git39-6572757-2ppa1~bionic1 [921 kB]\n",
            "Get:96 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tam all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,072 kB]\n",
            "Get:97 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tel all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,014 kB]\n",
            "Get:98 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tha all 1:5.0.0~git39-6572757-2ppa1~bionic1 [900 kB]\n",
            "Get:99 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-bre all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,863 kB]\n",
            "Get:100 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-chi-sim-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,136 kB]\n",
            "Get:101 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-chi-tra-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,091 kB]\n",
            "Get:102 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-cos all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,267 kB]\n",
            "Get:103 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-div all 1:5.0.0~git39-6572757-2ppa1~bionic1 [764 kB]\n",
            "Get:104 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fao all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,668 kB]\n",
            "Get:105 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fil all 1:5.0.0~git39-6572757-2ppa1~bionic1 [761 kB]\n",
            "Get:106 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-fry all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,179 kB]\n",
            "Get:107 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-gla all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,543 kB]\n",
            "Get:108 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-hye all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,192 kB]\n",
            "Get:109 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-jpn-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,890 kB]\n",
            "Get:110 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kor-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [548 kB]\n",
            "Get:111 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-kmr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,666 kB]\n",
            "Get:112 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ltz all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,721 kB]\n",
            "Get:113 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mon all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,218 kB]\n",
            "Get:114 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-mri all 1:5.0.0~git39-6572757-2ppa1~bionic1 [515 kB]\n",
            "Get:115 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-oci all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,596 kB]\n",
            "Get:116 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-que all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,136 kB]\n",
            "Get:117 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-snd all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,404 kB]\n",
            "Get:118 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-sun all 1:5.0.0~git39-6572757-2ppa1~bionic1 [681 kB]\n",
            "Get:119 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-tat all 1:5.0.0~git39-6572757-2ppa1~bionic1 [904 kB]\n",
            "Get:120 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-ton all 1:5.0.0~git39-6572757-2ppa1~bionic1 [548 kB]\n",
            "Get:121 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-yor all 1:5.0.0~git39-6572757-2ppa1~bionic1 [552 kB]\n",
            "Get:122 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-arab all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,217 kB]\n",
            "Get:123 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-armn all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,095 kB]\n",
            "Get:124 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-beng all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,449 kB]\n",
            "Get:125 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-cans all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,102 kB]\n",
            "Get:126 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-cher all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,639 kB]\n",
            "Get:127 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-cyrl all 1:5.0.0~git39-6572757-2ppa1~bionic1 [9,352 kB]\n",
            "Get:128 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-deva all 1:5.0.0~git39-6572757-2ppa1~bionic1 [6,121 kB]\n",
            "Get:129 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-ethi all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,034 kB]\n",
            "Get:130 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-frak all 1:5.0.0~git39-6572757-2ppa1~bionic1 [4,159 kB]\n",
            "Get:131 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-geor all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,850 kB]\n",
            "Get:132 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-grek all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,075 kB]\n",
            "Get:133 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-gujr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,808 kB]\n",
            "Get:134 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-guru all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,557 kB]\n",
            "Get:135 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hans all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,866 kB]\n",
            "Get:136 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hans-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,375 kB]\n",
            "Get:137 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hant all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,374 kB]\n",
            "Get:138 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hant-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,361 kB]\n",
            "Get:139 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hang all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,857 kB]\n",
            "Get:140 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hang-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,754 kB]\n",
            "Get:141 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-hebr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,751 kB]\n",
            "Get:142 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-jpan all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,587 kB]\n",
            "Get:143 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-jpan-vert all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,085 kB]\n",
            "Get:144 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-knda all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,482 kB]\n",
            "Get:145 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-khmr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,665 kB]\n",
            "Get:146 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-laoo all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,666 kB]\n",
            "Get:147 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-latn all 1:5.0.0~git39-6572757-2ppa1~bionic1 [30.9 MB]\n",
            "Get:148 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-mlym all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,974 kB]\n",
            "Get:149 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-mymr all 1:5.0.0~git39-6572757-2ppa1~bionic1 [3,203 kB]\n",
            "Get:150 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-orya all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,770 kB]\n",
            "Get:151 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-sinh all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,748 kB]\n",
            "Get:152 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-syrc all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,699 kB]\n",
            "Get:153 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-taml all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,488 kB]\n",
            "Get:154 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-telu all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,321 kB]\n",
            "Get:155 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-thaa all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,519 kB]\n",
            "Get:156 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-thai all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,646 kB]\n",
            "Get:157 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-tibt all 1:5.0.0~git39-6572757-2ppa1~bionic1 [2,453 kB]\n",
            "Get:158 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-script-viet all 1:5.0.0~git39-6572757-2ppa1~bionic1 [1,432 kB]\n",
            "Get:159 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-grc all 1:5.0.0~git39-6572757-2ppa1~bionic1 [918 kB]\n",
            "Get:160 http://ppa.launchpad.net/alex-p/tesseract-ocr5/ubuntu bionic/main amd64 tesseract-ocr-all all 5.1.0-1ppa1~bionic1 [60.5 kB]\n",
            "Fetched 282 MB in 2min 9s (2,180 kB/s)\n",
            "Extracting templates from packages: 100%\n",
            "Selecting previously unselected package tesseract-ocr-afr.\n",
            "(Reading database ... 156298 files and directories currently installed.)\n",
            "Preparing to unpack .../000-tesseract-ocr-afr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-afr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-bul.\n",
            "Preparing to unpack .../001-tesseract-ocr-bul_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-bul (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-cat.\n",
            "Preparing to unpack .../002-tesseract-ocr-cat_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-cat (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ces.\n",
            "Preparing to unpack .../003-tesseract-ocr-ces_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ces (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-dan.\n",
            "Preparing to unpack .../004-tesseract-ocr-dan_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-dan (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-deu.\n",
            "Preparing to unpack .../005-tesseract-ocr-deu_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-deu (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ell.\n",
            "Preparing to unpack .../006-tesseract-ocr-ell_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ell (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fin.\n",
            "Preparing to unpack .../007-tesseract-ocr-fin_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fin (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fra.\n",
            "Preparing to unpack .../008-tesseract-ocr-fra_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fra (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-hun.\n",
            "Preparing to unpack .../009-tesseract-ocr-hun_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-hun (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ind.\n",
            "Preparing to unpack .../010-tesseract-ocr-ind_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ind (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ita.\n",
            "Preparing to unpack .../011-tesseract-ocr-ita_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ita (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-lav.\n",
            "Preparing to unpack .../012-tesseract-ocr-lav_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-lav (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-lit.\n",
            "Preparing to unpack .../013-tesseract-ocr-lit_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-lit (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-nld.\n",
            "Preparing to unpack .../014-tesseract-ocr-nld_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-nld (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-nor.\n",
            "Preparing to unpack .../015-tesseract-ocr-nor_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-nor (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-pol.\n",
            "Preparing to unpack .../016-tesseract-ocr-pol_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-pol (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-por.\n",
            "Preparing to unpack .../017-tesseract-ocr-por_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-por (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ron.\n",
            "Preparing to unpack .../018-tesseract-ocr-ron_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ron (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-rus.\n",
            "Preparing to unpack .../019-tesseract-ocr-rus_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-rus (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-slk.\n",
            "Preparing to unpack .../020-tesseract-ocr-slk_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-slk (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-slv.\n",
            "Preparing to unpack .../021-tesseract-ocr-slv_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-slv (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-spa.\n",
            "Preparing to unpack .../022-tesseract-ocr-spa_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-spa (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-srp.\n",
            "Preparing to unpack .../023-tesseract-ocr-srp_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-srp (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-swe.\n",
            "Preparing to unpack .../024-tesseract-ocr-swe_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-swe (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tur.\n",
            "Preparing to unpack .../025-tesseract-ocr-tur_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tur (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ukr.\n",
            "Preparing to unpack .../026-tesseract-ocr-ukr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ukr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-vie.\n",
            "Preparing to unpack .../027-tesseract-ocr-vie_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-vie (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-chi-sim.\n",
            "Preparing to unpack .../028-tesseract-ocr-chi-sim_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-chi-sim (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-chi-tra.\n",
            "Preparing to unpack .../029-tesseract-ocr-chi-tra_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-chi-tra (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-amh.\n",
            "Preparing to unpack .../030-tesseract-ocr-amh_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-amh (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-asm.\n",
            "Preparing to unpack .../031-tesseract-ocr-asm_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-asm (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-aze-cyrl.\n",
            "Preparing to unpack .../032-tesseract-ocr-aze-cyrl_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-aze-cyrl (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-bod.\n",
            "Preparing to unpack .../033-tesseract-ocr-bod_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-bod (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-bos.\n",
            "Preparing to unpack .../034-tesseract-ocr-bos_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-bos (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ceb.\n",
            "Preparing to unpack .../035-tesseract-ocr-ceb_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ceb (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-cym.\n",
            "Preparing to unpack .../036-tesseract-ocr-cym_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-cym (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-dzo.\n",
            "Preparing to unpack .../037-tesseract-ocr-dzo_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-dzo (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fas.\n",
            "Preparing to unpack .../038-tesseract-ocr-fas_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fas (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-gle.\n",
            "Preparing to unpack .../039-tesseract-ocr-gle_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-gle (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-guj.\n",
            "Preparing to unpack .../040-tesseract-ocr-guj_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-guj (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-hat.\n",
            "Preparing to unpack .../041-tesseract-ocr-hat_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-hat (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-iku.\n",
            "Preparing to unpack .../042-tesseract-ocr-iku_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-iku (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-jav.\n",
            "Preparing to unpack .../043-tesseract-ocr-jav_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-jav (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kat.\n",
            "Preparing to unpack .../044-tesseract-ocr-kat_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kat (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kat-old.\n",
            "Preparing to unpack .../045-tesseract-ocr-kat-old_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kat-old (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kaz.\n",
            "Preparing to unpack .../046-tesseract-ocr-kaz_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kaz (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-khm.\n",
            "Preparing to unpack .../047-tesseract-ocr-khm_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-khm (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kir.\n",
            "Preparing to unpack .../048-tesseract-ocr-kir_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kir (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-lao.\n",
            "Preparing to unpack .../049-tesseract-ocr-lao_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-lao (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-lat.\n",
            "Preparing to unpack .../050-tesseract-ocr-lat_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-lat (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mar.\n",
            "Preparing to unpack .../051-tesseract-ocr-mar_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mar (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mya.\n",
            "Preparing to unpack .../052-tesseract-ocr-mya_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mya (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-nep.\n",
            "Preparing to unpack .../053-tesseract-ocr-nep_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-nep (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ori.\n",
            "Preparing to unpack .../054-tesseract-ocr-ori_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ori (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-pan.\n",
            "Preparing to unpack .../055-tesseract-ocr-pan_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-pan (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-pus.\n",
            "Preparing to unpack .../056-tesseract-ocr-pus_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-pus (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-san.\n",
            "Preparing to unpack .../057-tesseract-ocr-san_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-san (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-sin.\n",
            "Preparing to unpack .../058-tesseract-ocr-sin_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-sin (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-srp-latn.\n",
            "Preparing to unpack .../059-tesseract-ocr-srp-latn_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-srp-latn (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-syr.\n",
            "Preparing to unpack .../060-tesseract-ocr-syr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-syr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tgk.\n",
            "Preparing to unpack .../061-tesseract-ocr-tgk_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tgk (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tir.\n",
            "Preparing to unpack .../062-tesseract-ocr-tir_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tir (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-uig.\n",
            "Preparing to unpack .../063-tesseract-ocr-uig_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-uig (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-urd.\n",
            "Preparing to unpack .../064-tesseract-ocr-urd_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-urd (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-uzb-cyrl.\n",
            "Preparing to unpack .../065-tesseract-ocr-uzb-cyrl_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-uzb-cyrl (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-uzb.\n",
            "Preparing to unpack .../066-tesseract-ocr-uzb_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-uzb (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-yid.\n",
            "Preparing to unpack .../067-tesseract-ocr-yid_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-yid (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ara.\n",
            "Preparing to unpack .../068-tesseract-ocr-ara_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ara (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-aze.\n",
            "Preparing to unpack .../069-tesseract-ocr-aze_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-aze (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-bel.\n",
            "Preparing to unpack .../070-tesseract-ocr-bel_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-bel (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ben.\n",
            "Preparing to unpack .../071-tesseract-ocr-ben_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ben (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-chr.\n",
            "Preparing to unpack .../072-tesseract-ocr-chr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-chr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-enm.\n",
            "Preparing to unpack .../073-tesseract-ocr-enm_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-enm (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-epo.\n",
            "Preparing to unpack .../074-tesseract-ocr-epo_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-epo (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-est.\n",
            "Preparing to unpack .../075-tesseract-ocr-est_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-est (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-eus.\n",
            "Preparing to unpack .../076-tesseract-ocr-eus_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-eus (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-frk.\n",
            "Preparing to unpack .../077-tesseract-ocr-frk_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-frk (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-frm.\n",
            "Preparing to unpack .../078-tesseract-ocr-frm_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-frm (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-glg.\n",
            "Preparing to unpack .../079-tesseract-ocr-glg_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-glg (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-heb.\n",
            "Preparing to unpack .../080-tesseract-ocr-heb_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-heb (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-hin.\n",
            "Preparing to unpack .../081-tesseract-ocr-hin_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-hin (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-hrv.\n",
            "Preparing to unpack .../082-tesseract-ocr-hrv_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-hrv (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-isl.\n",
            "Preparing to unpack .../083-tesseract-ocr-isl_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-isl (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ita-old.\n",
            "Preparing to unpack .../084-tesseract-ocr-ita-old_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ita-old (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-jpn.\n",
            "Preparing to unpack .../085-tesseract-ocr-jpn_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-jpn (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kan.\n",
            "Preparing to unpack .../086-tesseract-ocr-kan_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kan (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kor.\n",
            "Preparing to unpack .../087-tesseract-ocr-kor_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kor (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mal.\n",
            "Preparing to unpack .../088-tesseract-ocr-mal_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mal (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mkd.\n",
            "Preparing to unpack .../089-tesseract-ocr-mkd_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mkd (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mlt.\n",
            "Preparing to unpack .../090-tesseract-ocr-mlt_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mlt (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-msa.\n",
            "Preparing to unpack .../091-tesseract-ocr-msa_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-msa (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-spa-old.\n",
            "Preparing to unpack .../092-tesseract-ocr-spa-old_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-spa-old (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-sqi.\n",
            "Preparing to unpack .../093-tesseract-ocr-sqi_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-sqi (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-swa.\n",
            "Preparing to unpack .../094-tesseract-ocr-swa_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-swa (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tam.\n",
            "Preparing to unpack .../095-tesseract-ocr-tam_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tam (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tel.\n",
            "Preparing to unpack .../096-tesseract-ocr-tel_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tel (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tha.\n",
            "Preparing to unpack .../097-tesseract-ocr-tha_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tha (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-bre.\n",
            "Preparing to unpack .../098-tesseract-ocr-bre_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-bre (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-chi-sim-vert.\n",
            "Preparing to unpack .../099-tesseract-ocr-chi-sim-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-chi-sim-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-chi-tra-vert.\n",
            "Preparing to unpack .../100-tesseract-ocr-chi-tra-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-chi-tra-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-cos.\n",
            "Preparing to unpack .../101-tesseract-ocr-cos_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-cos (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-div.\n",
            "Preparing to unpack .../102-tesseract-ocr-div_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-div (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fao.\n",
            "Preparing to unpack .../103-tesseract-ocr-fao_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fao (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fil.\n",
            "Preparing to unpack .../104-tesseract-ocr-fil_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fil (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-fry.\n",
            "Preparing to unpack .../105-tesseract-ocr-fry_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-fry (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-gla.\n",
            "Preparing to unpack .../106-tesseract-ocr-gla_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-gla (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-hye.\n",
            "Preparing to unpack .../107-tesseract-ocr-hye_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-hye (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-jpn-vert.\n",
            "Preparing to unpack .../108-tesseract-ocr-jpn-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-jpn-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kor-vert.\n",
            "Preparing to unpack .../109-tesseract-ocr-kor-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kor-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-kmr.\n",
            "Preparing to unpack .../110-tesseract-ocr-kmr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-kmr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ltz.\n",
            "Preparing to unpack .../111-tesseract-ocr-ltz_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ltz (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mon.\n",
            "Preparing to unpack .../112-tesseract-ocr-mon_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mon (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-mri.\n",
            "Preparing to unpack .../113-tesseract-ocr-mri_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-mri (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-oci.\n",
            "Preparing to unpack .../114-tesseract-ocr-oci_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-oci (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-que.\n",
            "Preparing to unpack .../115-tesseract-ocr-que_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-que (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-snd.\n",
            "Preparing to unpack .../116-tesseract-ocr-snd_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-snd (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-sun.\n",
            "Preparing to unpack .../117-tesseract-ocr-sun_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-sun (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-tat.\n",
            "Preparing to unpack .../118-tesseract-ocr-tat_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-tat (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-ton.\n",
            "Preparing to unpack .../119-tesseract-ocr-ton_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-ton (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-yor.\n",
            "Preparing to unpack .../120-tesseract-ocr-yor_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-yor (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-arab.\n",
            "Preparing to unpack .../121-tesseract-ocr-script-arab_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-arab (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-armn.\n",
            "Preparing to unpack .../122-tesseract-ocr-script-armn_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-armn (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-beng.\n",
            "Preparing to unpack .../123-tesseract-ocr-script-beng_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-beng (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-cans.\n",
            "Preparing to unpack .../124-tesseract-ocr-script-cans_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-cans (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-cher.\n",
            "Preparing to unpack .../125-tesseract-ocr-script-cher_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-cher (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-cyrl.\n",
            "Preparing to unpack .../126-tesseract-ocr-script-cyrl_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-cyrl (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-deva.\n",
            "Preparing to unpack .../127-tesseract-ocr-script-deva_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-deva (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-ethi.\n",
            "Preparing to unpack .../128-tesseract-ocr-script-ethi_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-ethi (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-frak.\n",
            "Preparing to unpack .../129-tesseract-ocr-script-frak_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-frak (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-geor.\n",
            "Preparing to unpack .../130-tesseract-ocr-script-geor_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-geor (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-grek.\n",
            "Preparing to unpack .../131-tesseract-ocr-script-grek_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-grek (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-gujr.\n",
            "Preparing to unpack .../132-tesseract-ocr-script-gujr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-gujr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-guru.\n",
            "Preparing to unpack .../133-tesseract-ocr-script-guru_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-guru (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hans.\n",
            "Preparing to unpack .../134-tesseract-ocr-script-hans_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hans (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hans-vert.\n",
            "Preparing to unpack .../135-tesseract-ocr-script-hans-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hans-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hant.\n",
            "Preparing to unpack .../136-tesseract-ocr-script-hant_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hant (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hant-vert.\n",
            "Preparing to unpack .../137-tesseract-ocr-script-hant-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hant-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hang.\n",
            "Preparing to unpack .../138-tesseract-ocr-script-hang_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hang (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hang-vert.\n",
            "Preparing to unpack .../139-tesseract-ocr-script-hang-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hang-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-hebr.\n",
            "Preparing to unpack .../140-tesseract-ocr-script-hebr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-hebr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-jpan.\n",
            "Preparing to unpack .../141-tesseract-ocr-script-jpan_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-jpan (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-jpan-vert.\n",
            "Preparing to unpack .../142-tesseract-ocr-script-jpan-vert_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-jpan-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-knda.\n",
            "Preparing to unpack .../143-tesseract-ocr-script-knda_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-knda (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-khmr.\n",
            "Preparing to unpack .../144-tesseract-ocr-script-khmr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-khmr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-laoo.\n",
            "Preparing to unpack .../145-tesseract-ocr-script-laoo_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-laoo (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-latn.\n",
            "Preparing to unpack .../146-tesseract-ocr-script-latn_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-latn (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-mlym.\n",
            "Preparing to unpack .../147-tesseract-ocr-script-mlym_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-mlym (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-mymr.\n",
            "Preparing to unpack .../148-tesseract-ocr-script-mymr_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
            "Unpacking tesseract-ocr-script-mymr (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Selecting previously unselected package tesseract-ocr-script-orya.\n",
            "Preparing to unpack .../149-tesseract-ocr-script-orya_1%3a5.0.0~git39-6572757-2ppa1~bionic1_all.deb ...\n",
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            "Setting up tesseract-ocr-jpn-vert (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Setting up tesseract-ocr-script-beng (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Setting up tesseract-ocr-srp-latn (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Setting up tesseract-ocr-uzb (1:5.0.0~git39-6572757-2ppa1~bionic1) ...\n",
            "Setting up tesseract-ocr-all (5.1.0-1ppa1~bionic1) ...\n",
            "Requirement already satisfied: pytesseract in /usr/local/lib/python3.7/dist-packages (0.3.9)\n",
            "Requirement already satisfied: packaging>=21.3 in /usr/local/lib/python3.7/dist-packages (from pytesseract) (21.3)\n",
            "Requirement already satisfied: Pillow>=8.0.0 in /usr/local/lib/python3.7/dist-packages (from pytesseract) (9.0.1)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=21.3->pytesseract) (3.0.7)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Supported languages"
      ],
      "metadata": {
        "id": "NnA2VdKu4jia"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pytesseract\n",
        "\n",
        "pytesseract.get_languages()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SyxdKrRk4ll-",
        "outputId": "4750d6cb-fd5b-48d1-b77e-4a99c622d0ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['afr',\n",
              " 'amh',\n",
              " 'ara',\n",
              " 'asm',\n",
              " 'aze',\n",
              " 'aze_cyrl',\n",
              " 'bel',\n",
              " 'ben',\n",
              " 'bod',\n",
              " 'bos',\n",
              " 'bre',\n",
              " 'bul',\n",
              " 'cat',\n",
              " 'ceb',\n",
              " 'ces',\n",
              " 'chi_sim',\n",
              " 'chi_sim_vert',\n",
              " 'chi_tra',\n",
              " 'chi_tra_vert',\n",
              " 'chr',\n",
              " 'cos',\n",
              " 'cym',\n",
              " 'dan',\n",
              " 'deu',\n",
              " 'div',\n",
              " 'dzo',\n",
              " 'ell',\n",
              " 'eng',\n",
              " 'enm',\n",
              " 'epo',\n",
              " 'est',\n",
              " 'eus',\n",
              " 'fao',\n",
              " 'fas',\n",
              " 'fil',\n",
              " 'fin',\n",
              " 'fra',\n",
              " 'frk',\n",
              " 'frm',\n",
              " 'fry',\n",
              " 'gla',\n",
              " 'gle',\n",
              " 'glg',\n",
              " 'grc',\n",
              " 'guj',\n",
              " 'hat',\n",
              " 'heb',\n",
              " 'hin',\n",
              " 'hrv',\n",
              " 'hun',\n",
              " 'hye',\n",
              " 'iku',\n",
              " 'ind',\n",
              " 'isl',\n",
              " 'ita',\n",
              " 'ita_old',\n",
              " 'jav',\n",
              " 'jpn',\n",
              " 'jpn_vert',\n",
              " 'kan',\n",
              " 'kat',\n",
              " 'kat_old',\n",
              " 'kaz',\n",
              " 'khm',\n",
              " 'kir',\n",
              " 'kmr',\n",
              " 'kor',\n",
              " 'kor_vert',\n",
              " 'lao',\n",
              " 'lat',\n",
              " 'lav',\n",
              " 'lit',\n",
              " 'ltz',\n",
              " 'mal',\n",
              " 'mar',\n",
              " 'mkd',\n",
              " 'mlt',\n",
              " 'mon',\n",
              " 'mri',\n",
              " 'msa',\n",
              " 'mya',\n",
              " 'nep',\n",
              " 'nld',\n",
              " 'nor',\n",
              " 'oci',\n",
              " 'ori',\n",
              " 'osd',\n",
              " 'pan',\n",
              " 'pol',\n",
              " 'por',\n",
              " 'pus',\n",
              " 'que',\n",
              " 'ron',\n",
              " 'rus',\n",
              " 'san',\n",
              " 'sin',\n",
              " 'slk',\n",
              " 'slv',\n",
              " 'snd',\n",
              " 'spa',\n",
              " 'spa_old',\n",
              " 'sqi',\n",
              " 'srp',\n",
              " 'srp_latn',\n",
              " 'sun',\n",
              " 'swa',\n",
              " 'swe',\n",
              " 'syr',\n",
              " 'tam',\n",
              " 'tat',\n",
              " 'tel',\n",
              " 'tgk',\n",
              " 'tha',\n",
              " 'tir',\n",
              " 'ton',\n",
              " 'tur',\n",
              " 'uig',\n",
              " 'ukr',\n",
              " 'urd',\n",
              " 'uzb',\n",
              " 'uzb_cyrl',\n",
              " 'vie',\n",
              " 'yid',\n",
              " 'yor']"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### English"
      ],
      "metadata": {
        "id": "FZrDeJON4OkH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "\n",
        "img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
        "data = pytesseract.image_to_data(Image.fromarray(img_rgb), lang='eng', output_type='data.frame')\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 771
        },
        "id": "D7fidA8M3g3G",
        "outputId": "52687fff-da3b-4335-d3d2-e3c6f62ee91f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    level  page_num  block_num  par_num  line_num  word_num  left  top  width  \\\n",
              "0       1         1          0        0         0         0     0    0    300   \n",
              "1       2         1          1        0         0         0    27  132    236   \n",
              "2       3         1          1        1         0         0    27  132    236   \n",
              "3       4         1          1        1         1         0    27  132    236   \n",
              "4       5         1          1        1         1         1    27  128     55   \n",
              "5       5         1          1        1         1         2    93  142    170   \n",
              "6       5         1          1        1         1         3   217  128     48   \n",
              "7       2         1          2        0         0         0   264   90     11   \n",
              "8       3         1          2        1         0         0   264   90     11   \n",
              "9       4         1          2        1         1         0   264   90     11   \n",
              "10      5         1          2        1         1         1   264   90     11   \n",
              "11      2         1          3        0         0         0    70  178    196   \n",
              "12      3         1          3        1         0         0    70  178    196   \n",
              "13      4         1          3        1         1         0    70  178    196   \n",
              "14      5         1          3        1         1         1    70  178     20   \n",
              "15      5         1          3        1         1         2    98  188      7   \n",
              "16      5         1          3        1         1         3   114  180     61   \n",
              "17      5         1          3        1         1         4   184  180     39   \n",
              "18      5         1          3        1         1         5   254  181     12   \n",
              "19      2         1          4        0         0         0    91  222    132   \n",
              "20      3         1          4        1         0         0    91  222    132   \n",
              "21      4         1          4        1         1         0    91  222    132   \n",
              "22      5         1          4        1         1         1    91  222    132   \n",
              "\n",
              "    height       conf     text  \n",
              "0      300  -1.000000      NaN  \n",
              "1       36  -1.000000      NaN  \n",
              "2       36  -1.000000      NaN  \n",
              "3       36  -1.000000      NaN  \n",
              "4       44  67.336014      Wer  \n",
              "5       26  84.737602     TUNA  \n",
              "6       44  55.951065      sty  \n",
              "7       72  -1.000000      NaN  \n",
              "8       72  -1.000000      NaN  \n",
              "9       72  -1.000000      NaN  \n",
              "10      72  44.130646       ee  \n",
              "11      18  -1.000000      NaN  \n",
              "12      18  -1.000000      NaN  \n",
              "13      18  -1.000000      NaN  \n",
              "14      16  70.457977      OIL  \n",
              "15       3  70.457977        ~  \n",
              "16      16  94.856445  ITALIAN  \n",
              "17      16  69.587341    STYLE  \n",
              "18      11  30.278900       9°  \n",
              "19      12  -1.000000      NaN  \n",
              "20      12  -1.000000      NaN  \n",
              "21      12  -1.000000      NaN  \n",
              "22      12  95.000000           "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d58074fa-6078-459c-9863-54dd085ee8d6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>level</th>\n",
              "      <th>page_num</th>\n",
              "      <th>block_num</th>\n",
              "      <th>par_num</th>\n",
              "      <th>line_num</th>\n",
              "      <th>word_num</th>\n",
              "      <th>left</th>\n",
              "      <th>top</th>\n",
              "      <th>width</th>\n",
              "      <th>height</th>\n",
              "      <th>conf</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>300</td>\n",
              "      <td>300</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>27</td>\n",
              "      <td>132</td>\n",
              "      <td>236</td>\n",
              "      <td>36</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>27</td>\n",
              "      <td>132</td>\n",
              "      <td>236</td>\n",
              "      <td>36</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>27</td>\n",
              "      <td>132</td>\n",
              "      <td>236</td>\n",
              "      <td>36</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>27</td>\n",
              "      <td>128</td>\n",
              "      <td>55</td>\n",
              "      <td>44</td>\n",
              "      <td>67.336014</td>\n",
              "      <td>Wer</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>93</td>\n",
              "      <td>142</td>\n",
              "      <td>170</td>\n",
              "      <td>26</td>\n",
              "      <td>84.737602</td>\n",
              "      <td>TUNA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>217</td>\n",
              "      <td>128</td>\n",
              "      <td>48</td>\n",
              "      <td>44</td>\n",
              "      <td>55.951065</td>\n",
              "      <td>sty</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>264</td>\n",
              "      <td>90</td>\n",
              "      <td>11</td>\n",
              "      <td>72</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>264</td>\n",
              "      <td>90</td>\n",
              "      <td>11</td>\n",
              "      <td>72</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>264</td>\n",
              "      <td>90</td>\n",
              "      <td>11</td>\n",
              "      <td>72</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>264</td>\n",
              "      <td>90</td>\n",
              "      <td>11</td>\n",
              "      <td>72</td>\n",
              "      <td>44.130646</td>\n",
              "      <td>ee</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>70</td>\n",
              "      <td>178</td>\n",
              "      <td>196</td>\n",
              "      <td>18</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>70</td>\n",
              "      <td>178</td>\n",
              "      <td>196</td>\n",
              "      <td>18</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>70</td>\n",
              "      <td>178</td>\n",
              "      <td>196</td>\n",
              "      <td>18</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>70</td>\n",
              "      <td>178</td>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "      <td>70.457977</td>\n",
              "      <td>OIL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>98</td>\n",
              "      <td>188</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>70.457977</td>\n",
              "      <td>~</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>114</td>\n",
              "      <td>180</td>\n",
              "      <td>61</td>\n",
              "      <td>16</td>\n",
              "      <td>94.856445</td>\n",
              "      <td>ITALIAN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>184</td>\n",
              "      <td>180</td>\n",
              "      <td>39</td>\n",
              "      <td>16</td>\n",
              "      <td>69.587341</td>\n",
              "      <td>STYLE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>254</td>\n",
              "      <td>181</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>30.278900</td>\n",
              "      <td>9°</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>91</td>\n",
              "      <td>222</td>\n",
              "      <td>132</td>\n",
              "      <td>12</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>91</td>\n",
              "      <td>222</td>\n",
              "      <td>132</td>\n",
              "      <td>12</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>91</td>\n",
              "      <td>222</td>\n",
              "      <td>132</td>\n",
              "      <td>12</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>91</td>\n",
              "      <td>222</td>\n",
              "      <td>132</td>\n",
              "      <td>12</td>\n",
              "      <td>95.000000</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d58074fa-6078-459c-9863-54dd085ee8d6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d58074fa-6078-459c-9863-54dd085ee8d6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d58074fa-6078-459c-9863-54dd085ee8d6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text = pytesseract.image_to_string(Image.fromarray(img), lang='eng')\n",
        "text"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "n4ZiBB-r8aWM",
        "outputId": "b246afc7-8602-478a-f250-b59bc56db57e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Wer TUNA sth\\n\\nae ae\\n\\nOIL ~ ITALIAN STYLE 9°\\n\\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Chinese"
      ],
      "metadata": {
        "id": "3ZigCy8v4STc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "chineseimg = fetchImage('https://www.parknshop.com/medias/sys_master/front/prd/9346157117470.jpg')\n",
        "cv2_imshow(chineseimg)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "AGqvG4qy4UBX",
        "outputId": "3902de54-224c-4461-ec48-ff62a547ab9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=300x300 at 0x7F65302D0110>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "chineseimg_rgb = cv2.cvtColor(chineseimg, cv2.COLOR_BGR2RGB)\n",
        "data = pytesseract.image_to_data(Image.fromarray(chineseimg_rgb), lang='chi_tra', output_type='data.frame')\n",
        "data"
      ],
      "metadata": {
        "id": "pP1e-YPdyPPe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "outputId": "e27efc17-e1b8-43b7-ec03-ce8cf7b4ab79"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    level  page_num  block_num  par_num  line_num  word_num  left  top  width  \\\n",
              "0       1         1          0        0         0         0     0    0    300   \n",
              "1       2         1          1        0         0         0    51  210    198   \n",
              "2       3         1          1        1         0         0    51  210    198   \n",
              "3       4         1          1        1         1         0    51  210    198   \n",
              "4       5         1          1        1         1         1    51  216     24   \n",
              "5       5         1          1        1         1         2    86  216     38   \n",
              "6       5         1          1        1         1         3   123  206     26   \n",
              "7       5         1          1        1         1         4   148  210     14   \n",
              "8       5         1          1        1         1         5   175  216     15   \n",
              "9       5         1          1        1         1         6   206  216     14   \n",
              "10      5         1          1        1         1         7   233  216     16   \n",
              "11      4         1          1        1         2         0   109  249     80   \n",
              "12      5         1          1        1         2         1   109  249     18   \n",
              "13      5         1          1        1         2         2   136  249     24   \n",
              "14      5         1          1        1         2         3   159  231     13   \n",
              "15      5         1          1        1         2         4   172  249     17   \n",
              "\n",
              "    height       conf text  \n",
              "0      300  -1.000000  NaN  \n",
              "1       58  -1.000000  NaN  \n",
              "2       58  -1.000000  NaN  \n",
              "3       33  -1.000000  NaN  \n",
              "4       27  93.211212    天  \n",
              "5       27  91.862755    然  \n",
              "6       49   0.000000    橄  \n",
              "7       33  53.834908    檻  \n",
              "8       27  84.086998    油  \n",
              "9       27  51.076031    精  \n",
              "10      27  93.247444    華  \n",
              "11      19  -1.000000  NaN  \n",
              "12      19  46.192612    抽  \n",
              "13      19  14.665909    平  \n",
              "14      51  40.189777    所  \n",
              "15      19  43.841522    中  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f214e350-f488-47f3-8d93-6c6e96551f26\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>level</th>\n",
              "      <th>page_num</th>\n",
              "      <th>block_num</th>\n",
              "      <th>par_num</th>\n",
              "      <th>line_num</th>\n",
              "      <th>word_num</th>\n",
              "      <th>left</th>\n",
              "      <th>top</th>\n",
              "      <th>width</th>\n",
              "      <th>height</th>\n",
              "      <th>conf</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>300</td>\n",
              "      <td>300</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>51</td>\n",
              "      <td>210</td>\n",
              "      <td>198</td>\n",
              "      <td>58</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>51</td>\n",
              "      <td>210</td>\n",
              "      <td>198</td>\n",
              "      <td>58</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>51</td>\n",
              "      <td>210</td>\n",
              "      <td>198</td>\n",
              "      <td>33</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>51</td>\n",
              "      <td>216</td>\n",
              "      <td>24</td>\n",
              "      <td>27</td>\n",
              "      <td>93.211212</td>\n",
              "      <td>天</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>86</td>\n",
              "      <td>216</td>\n",
              "      <td>38</td>\n",
              "      <td>27</td>\n",
              "      <td>91.862755</td>\n",
              "      <td>然</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>123</td>\n",
              "      <td>206</td>\n",
              "      <td>26</td>\n",
              "      <td>49</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>橄</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>148</td>\n",
              "      <td>210</td>\n",
              "      <td>14</td>\n",
              "      <td>33</td>\n",
              "      <td>53.834908</td>\n",
              "      <td>檻</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>175</td>\n",
              "      <td>216</td>\n",
              "      <td>15</td>\n",
              "      <td>27</td>\n",
              "      <td>84.086998</td>\n",
              "      <td>油</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>206</td>\n",
              "      <td>216</td>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>51.076031</td>\n",
              "      <td>精</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>233</td>\n",
              "      <td>216</td>\n",
              "      <td>16</td>\n",
              "      <td>27</td>\n",
              "      <td>93.247444</td>\n",
              "      <td>華</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>109</td>\n",
              "      <td>249</td>\n",
              "      <td>80</td>\n",
              "      <td>19</td>\n",
              "      <td>-1.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>109</td>\n",
              "      <td>249</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>46.192612</td>\n",
              "      <td>抽</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>136</td>\n",
              "      <td>249</td>\n",
              "      <td>24</td>\n",
              "      <td>19</td>\n",
              "      <td>14.665909</td>\n",
              "      <td>平</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>159</td>\n",
              "      <td>231</td>\n",
              "      <td>13</td>\n",
              "      <td>51</td>\n",
              "      <td>40.189777</td>\n",
              "      <td>所</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>172</td>\n",
              "      <td>249</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>43.841522</td>\n",
              "      <td>中</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f214e350-f488-47f3-8d93-6c6e96551f26')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f214e350-f488-47f3-8d93-6c6e96551f26 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f214e350-f488-47f3-8d93-6c6e96551f26');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    }
  ]
}