Block detection Sample generation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from PyPDF2 import PdfFileReader, PdfFileWriter\n",
    "import os\n",
    "from sklearn import preprocessing\n",
    "import subprocess\n",
    "import matplotlib.pyplot as plt\n",
    "from itertools import islice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pdf_file_path = 'parsers/pdfs/West Bengal/2017-18/2017_bp11_Demand Nos.1-5.pdf'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pdf = PdfFileReader(open(pdf_file_path, 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "??pdf.getFormTextFields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_page_image_from_pdf(pdf, page_num, image_file_name):\n",
    "    page_layout = pdf.getPage(page_num)['/MediaBox']\n",
    "    command = \"convert -density 300 '%s'[%s] '%s'\" % (pdf_file_path,\n",
    "                                                      page_num,\n",
    "                                                      image_file_name)\n",
    "    subprocess.check_output(command, shell=True)\n",
    "    return cv2.imread(image_file_name, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "img_page2 = get_page_image_from_pdf(pdf, 2, 'west_bengal_demand_1_5_page_1.png')\n",
    "img_page4 = get_page_image_from_pdf(pdf, 4, 'west_bengal_demand_1_5_page_1.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fc638e0e810>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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L29+2uS07aqheOhwvd96Uzrfe8pSG3JWOc/QYcmVPj2l9XgOUCGSAyzpiXkwryNlarj32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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638f97f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,20))\n",
    "plt.imshow(img_page2, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fc638d15690>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YyiVhazHIxWlLPFs/09E+l0fVr7UfVohfPzrpOYNH1a9H1uW7M7QMgMup3XfRcwNtz48B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\nAQAAuiOQAQAAuiOQAQAAuvP/AUj8B8NCy/F6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638dcc990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,20))\n",
    "plt.imshow(img_page4, cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RLSA Implementation\n",
    "\n",
    "http://crblpocr.blogspot.in/2007/06/run-length-smoothing-algorithm-rlsa.html\n",
    "\n",
    "The Run Length Smoothing Algorithm (RLSA) is a method that can be used for Block segmentation and text discrimination. The method developed for the Document Analysis System consists of two steps. First, a segmentation procedure subdivides the area of a document into regions (blocks), each of which should contain only one type of data (text, graphic, halftone image, etc.). Next, some basic features of these blocks are calculated.\n",
    "\n",
    "The basic RLSA is applied to a binary sequence in which white pixels are represented by 0’s and black pixels by 1’s. The algorithm transforms a binary sequence x into an output sequence y according to the following rules:\n",
    "\n",
    "1. 0’s in x are changed to 1’s in y if the number of adjacent 0’s is less than or equal to a predefined limit C.\n",
    "2. 1’s in x are unchanged in y .\n",
    "\n",
    "For example, with C = 4 the sequence x is mapped into y as follows:\n",
    "\n",
    "x : 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0      \n",
    "y : 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fc638a37e50>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tWcyRAQAApiOQAQAApiOQAQAApiOQAQAApiOQAQAApiOQAQAApuPrl+GBWr80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\nI8gAAADN+f9Z7zqO6DEakAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638dec990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ret,thresh1 = cv2.threshold(img_page2,0,1,cv2.THRESH_BINARY_INV)\n",
    "plt.figure(figsize=(30,20))\n",
    "plt.imshow(thresh1, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def rlsa(img, threshold):\n",
    "    ret,thresh1 = cv2.threshold(img, 0, 1, cv2.THRESH_BINARY_INV)\n",
    "    img_iter = np.nditer(thresh1, flags=['multi_index'])\n",
    "    C_vertical, C_horizontal = threshold\n",
    "    temp_thresh = thresh1.copy()\n",
    "    while not img_iter.finished:\n",
    "        x, y = img_iter.multi_index\n",
    "        x_threshold = x + C_horizontal\n",
    "        y_threshold = y + C_vertical\n",
    "        neg_x_threshold = x - C_horizontal\n",
    "        neg_y_threshold = y - C_vertical\n",
    "        if (thresh1[x:x_threshold, y:y_threshold].any() \n",
    "            or thresh1[x:x_threshold, y:neg_y_threshold].any()\n",
    "            or thresh1[x:neg_x_threshold, y:y_threshold].any()\n",
    "            or thresh1[x:neg_x_threshold, y:neg_y_threshold].any()):\n",
    "            temp_thresh[x, y] = 1\n",
    "        else:\n",
    "            temp_thresh[x, y] = 0\n",
    "        img_iter.iternext()\n",
    "    return temp_thresh\n",
    "\n",
    "def plot_page(img):\n",
    "    plt.figure(figsize=(30,20))\n",
    "    plt.imshow(img, cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "img_page4_rlsa = rlsa(img_page4, (15, 25))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3d/Hw8PDKa1nu61hypOt8ncfMd0it5i5nKeXiPFr4rm6t35zln1q7MXXZo7ZT1mupdbr2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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6389f2ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_page(img_page4_rlsa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n_comp, labels, stats, centroids = cv2.connectedComponentsWithStats(img_page4_rlsa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "167"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_comp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4YuMn2WNU5Tg3vb+xhZlZAaXJADNmswJKkwFmzNwjQ9ZmhbpFujEwRE12cmiX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\n/94pNQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638922f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_page(labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stats definitions http://docs.opencv.org/trunk/d3/dc0/group__imgproc__shape.html#gac7099124c0390051c6970a987e7dc5c5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stats_columns = [\"left\", \"top\", \"width\", \"height\", \"area\"]\n",
    "label_stats = pd.DataFrame(stats, columns=stats_columns)\n",
    "# Ignore the label 0 since it is the background\n",
    "label_stats.drop(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>2178</td>\n",
       "      <td>25</td>\n",
       "      <td>54450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>59</td>\n",
       "      <td>885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>916</td>\n",
       "      <td>100</td>\n",
       "      <td>633</td>\n",
       "      <td>59</td>\n",
       "      <td>36608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>164</td>\n",
       "      <td>15</td>\n",
       "      <td>54</td>\n",
       "      <td>810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   left  top  width  height   area\n",
       "1     0    0     15      25    375\n",
       "2   140    0   2178      25  54450\n",
       "3     0  100     15      59    885\n",
       "4   916  100    633      59  36608\n",
       "5     0  164     15      54    810"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_stats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fc6387fedd0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KiACaPpWWtFHSoKTBkZGRpvZdd+3ipsqr7bj996Yd0jM16sYTw8ysFaY66ua4pIURcSx1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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638df7b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(label_stats.width, label_stats.height)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "166    3041\n",
       "165    2957\n",
       "164    2957\n",
       "163    2686\n",
       "162    2686\n",
       "161    2686\n",
       "160    2686\n",
       "159    2664\n",
       "158    2664\n",
       "157    2630\n",
       "156    2630\n",
       "155    2630\n",
       "154    2630\n",
       "153    2608\n",
       "152    2552\n",
       "151    2496\n",
       "150    2496\n",
       "149    2496\n",
       "148    2496\n",
       "147    2496\n",
       "146    2439\n",
       "145    2383\n",
       "144    2383\n",
       "143    2383\n",
       "142    2383\n",
       "141    2383\n",
       "140    2383\n",
       "139    2383\n",
       "138    2343\n",
       "137    2343\n",
       "       ... \n",
       "30      808\n",
       "29      696\n",
       "28      696\n",
       "27      639\n",
       "26      639\n",
       "25      558\n",
       "24      558\n",
       "23      518\n",
       "22      518\n",
       "21      447\n",
       "20      447\n",
       "19      447\n",
       "18      447\n",
       "17      447\n",
       "16      333\n",
       "15      333\n",
       "14      333\n",
       "13      333\n",
       "12      277\n",
       "11      277\n",
       "10      277\n",
       "9       277\n",
       "8       237\n",
       "7       237\n",
       "6       164\n",
       "5       164\n",
       "4       100\n",
       "3       100\n",
       "2         0\n",
       "1         0\n",
       "Name: top, dtype: int32"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_stats.top.sort_index(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DataConversionWarning: Data with input dtype int32 was converted to float64 by MinMaxScaler. [validation.py:429]\n",
      "DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample. [data.py:321]\n",
      "DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample. [data.py:356]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fc63874aad0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AwDEKGAAAgGMUMAAAAMcoYAAAAI5RwAAAAByjgAEAADhGAQMAAHCMAgYAAOAYBQwAAMAx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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6387a0110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "plt.figure(figsize=(10,20))\n",
    "plt.scatter(label_stats.top, label_stats.left, s=min_max_scaler.fit_transform(label_stats.area) * 200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>25</td>\n",
       "      <td>375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>2178</td>\n",
       "      <td>25</td>\n",
       "      <td>54450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>59</td>\n",
       "      <td>885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>916</td>\n",
       "      <td>100</td>\n",
       "      <td>633</td>\n",
       "      <td>59</td>\n",
       "      <td>36608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>164</td>\n",
       "      <td>15</td>\n",
       "      <td>54</td>\n",
       "      <td>810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>843</td>\n",
       "      <td>164</td>\n",
       "      <td>778</td>\n",
       "      <td>54</td>\n",
       "      <td>38447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>237</td>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>153</td>\n",
       "      <td>237</td>\n",
       "      <td>2158</td>\n",
       "      <td>27</td>\n",
       "      <td>58266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>277</td>\n",
       "      <td>15</td>\n",
       "      <td>163</td>\n",
       "      <td>2445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1589</td>\n",
       "      <td>277</td>\n",
       "      <td>123</td>\n",
       "      <td>59</td>\n",
       "      <td>5898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1866</td>\n",
       "      <td>277</td>\n",
       "      <td>135</td>\n",
       "      <td>51</td>\n",
       "      <td>6236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2167</td>\n",
       "      <td>277</td>\n",
       "      <td>123</td>\n",
       "      <td>59</td>\n",
       "      <td>5898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1276</td>\n",
       "      <td>333</td>\n",
       "      <td>174</td>\n",
       "      <td>107</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1564</td>\n",
       "      <td>333</td>\n",
       "      <td>174</td>\n",
       "      <td>107</td>\n",
       "      <td>15580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1853</td>\n",
       "      <td>333</td>\n",
       "      <td>174</td>\n",
       "      <td>107</td>\n",
       "      <td>15566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2142</td>\n",
       "      <td>333</td>\n",
       "      <td>174</td>\n",
       "      <td>107</td>\n",
       "      <td>15567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>447</td>\n",
       "      <td>15</td>\n",
       "      <td>50</td>\n",
       "      <td>750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1351</td>\n",
       "      <td>447</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "      <td>2663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1639</td>\n",
       "      <td>447</td>\n",
       "      <td>61</td>\n",
       "      <td>50</td>\n",
       "      <td>2692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1928</td>\n",
       "      <td>447</td>\n",
       "      <td>61</td>\n",
       "      <td>50</td>\n",
       "      <td>2692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2217</td>\n",
       "      <td>447</td>\n",
       "      <td>61</td>\n",
       "      <td>50</td>\n",
       "      <td>2692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    left  top  width  height   area\n",
       "1      0    0     15      25    375\n",
       "2    140    0   2178      25  54450\n",
       "3      0  100     15      59    885\n",
       "4    916  100    633      59  36608\n",
       "5      0  164     15      54    810\n",
       "6    843  164    778      54  38447\n",
       "7      0  237     15      27    405\n",
       "8    153  237   2158      27  58266\n",
       "9      0  277     15     163   2445\n",
       "10  1589  277    123      59   5898\n",
       "11  1866  277    135      51   6236\n",
       "12  2167  277    123      59   5898\n",
       "13  1276  333    174     107  14721\n",
       "14  1564  333    174     107  15580\n",
       "15  1853  333    174     107  15566\n",
       "16  2142  333    174     107  15567\n",
       "17     0  447     15      50    750\n",
       "18  1351  447     60      50   2663\n",
       "19  1639  447     61      50   2692\n",
       "20  1928  447     61      50   2692\n",
       "21  2217  447     61      50   2692"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_stats[label_stats.top < 500]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1552</td>\n",
       "      <td>921</td>\n",
       "      <td>188</td>\n",
       "      <td>111</td>\n",
       "      <td>16703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1838</td>\n",
       "      <td>921</td>\n",
       "      <td>191</td>\n",
       "      <td>111</td>\n",
       "      <td>16931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2127</td>\n",
       "      <td>921</td>\n",
       "      <td>191</td>\n",
       "      <td>111</td>\n",
       "      <td>16948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1019</td>\n",
       "      <td>977</td>\n",
       "      <td>144</td>\n",
       "      <td>107</td>\n",
       "      <td>11462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>228</td>\n",
       "      <td>1033</td>\n",
       "      <td>216</td>\n",
       "      <td>59</td>\n",
       "      <td>10137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1411</td>\n",
       "      <td>1055</td>\n",
       "      <td>38</td>\n",
       "      <td>29</td>\n",
       "      <td>1099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1700</td>\n",
       "      <td>1055</td>\n",
       "      <td>38</td>\n",
       "      <td>29</td>\n",
       "      <td>1099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1989</td>\n",
       "      <td>1055</td>\n",
       "      <td>37</td>\n",
       "      <td>29</td>\n",
       "      <td>1070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2278</td>\n",
       "      <td>1055</td>\n",
       "      <td>37</td>\n",
       "      <td>29</td>\n",
       "      <td>1070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1019</td>\n",
       "      <td>1089</td>\n",
       "      <td>144</td>\n",
       "      <td>108</td>\n",
       "      <td>11463</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    left   top  width  height   area\n",
       "37  1552   921    188     111  16703\n",
       "38  1838   921    191     111  16931\n",
       "39  2127   921    191     111  16948\n",
       "40  1019   977    144     107  11462\n",
       "41   228  1033    216      59  10137\n",
       "42  1411  1055     38      29   1099\n",
       "43  1700  1055     38      29   1099\n",
       "44  1989  1055     37      29   1070\n",
       "45  2278  1055     37      29   1070\n",
       "46  1019  1089    144     108  11463"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_stats.iloc[36:46]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1364.20007162,   970.59466396],\n",
       "       [ 1655.14362689,   970.8230258 ],\n",
       "       [ 1942.72647806,   970.54456323],\n",
       "       [ 2231.53345527,   970.77248053],\n",
       "       [ 1098.31722213,  1027.41903682],\n",
       "       [  334.72832199,  1059.75584492],\n",
       "       [ 1429.51683348,  1068.98726115],\n",
       "       [ 1718.51683348,  1068.98726115],\n",
       "       [ 2007.01682243,  1068.98691589],\n",
       "       [ 2296.01682243,  1068.98691589]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centroids[36:46]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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pAIAyN/ufSKnR27tsqUFcem/t9u1R1hGGrS16Gp25ZZZG7N73PNTW2WOvz7vl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\nP+t/T7IMVkQQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc63894c750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page4.copy()\n",
    "for centroid in centroids[36:46]:\n",
    "    x, y = centroid\n",
    "    cv2.circle(waste_copy, (int(x), int(y)), 20, (0,0,255), -1)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label_stats['top_str'] = label_stats.top.apply(lambda x: str(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "top_str\n",
       "1258    5\n",
       "1483    5\n",
       "1596    5\n",
       "1708    5\n",
       "2496    5\n",
       "447     5\n",
       "Name: left, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_top = label_stats.groupby('top_str')['left'].count()\n",
    "count_top[count_top == 5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top_str</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1258</th>\n",
       "      <th>65</th>\n",
       "      <td>1912</td>\n",
       "      <td>1258</td>\n",
       "      <td>117</td>\n",
       "      <td>111</td>\n",
       "      <td>10758</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>1624</td>\n",
       "      <td>1258</td>\n",
       "      <td>116</td>\n",
       "      <td>111</td>\n",
       "      <td>10617</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>1335</td>\n",
       "      <td>1258</td>\n",
       "      <td>116</td>\n",
       "      <td>111</td>\n",
       "      <td>10506</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2201</td>\n",
       "      <td>1258</td>\n",
       "      <td>117</td>\n",
       "      <td>111</td>\n",
       "      <td>10741</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>225</td>\n",
       "      <td>1258</td>\n",
       "      <td>410</td>\n",
       "      <td>51</td>\n",
       "      <td>18614</td>\n",
       "      <td>1258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            left   top  width  height   area top_str\n",
       "top_str                                             \n",
       "1258    65  1912  1258    117     111  10758    1258\n",
       "        64  1624  1258    116     111  10617    1258\n",
       "        63  1335  1258    116     111  10506    1258\n",
       "        66  2201  1258    117     111  10741    1258\n",
       "        62   225  1258    410      51  18614    1258"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_top = label_stats.groupby('top_str').apply(lambda x: x.iloc[0:10]).sort_values('top')\n",
    "grouped_top[grouped_top.top_str == '1258']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1189, 1477, 1766, 2055]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(label_stats.left - (label_stats.width // 2) ).iloc[12:16].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1460, 1748, 2037, 2326]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(label_stats.left + label_stats.width + 10 ).iloc[12:16].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[645, 1461, 1750, 2039, 2328]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(label_stats.left + label_stats.width + 10)[61:66].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rudbrkp71tPRuWyqXINWSpto+xv9y+9ezjaUySvubvt6i9pnn9qG3vrbez5VV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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6386a11d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# draw lines at 1411, 1700, 1989, 2278\n",
    "# left - width [1102, 1390, 1679, 1968]\n",
    "# left - width / 2 [1189, 1477, 1766, 2055]\n",
    "\n",
    "def plot_lines(line_xs, img, y_start, y_end):\n",
    "    waste_copy2 = img.copy()\n",
    "    for line_x in line_xs:\n",
    "        line_starting_points = (line_x, y_start)\n",
    "        line_stopping_points = (line_x, y_end)\n",
    "        cv2.line(waste_copy2, line_starting_points, line_stopping_points, (125,255,0), 3)\n",
    "    plot_page(waste_copy2)\n",
    "\n",
    "plot_lines([1461, 1750, 2039, 2328], img_page4, 333, 3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wfoYjeqmOKKtUts8TAM5HInNB6RXVWmMsnrf1/tp1lKbF01vLtV6X9KynpXfb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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6388e6e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_lines([1000,1200,1461, 1750, 2039, 2328], img_page4, 333, 3000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Try the same for page 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rlsa_page2 = rlsa(img_page2, (20, 25))\n",
    "n_comp, labels, stats, centroids = cv2.connectedComponentsWithStats(rlsa_page2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_label_stats(stats):\n",
    "    stats_columns = [\"left\", \"top\", \"width\", \"height\", \"area\"]\n",
    "    label_stats = pd.DataFrame(stats, columns=stats_columns)\n",
    "    # Ignore the label 0 since it is the background\n",
    "    label_stats.drop(0, inplace=True)\n",
    "    return label_stats\n",
    "\n",
    "page2_label_stats = get_label_stats(stats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top_str</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">0</th>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>2183</td>\n",
       "      <td>25</td>\n",
       "      <td>54575</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">103</th>\n",
       "      <th>4</th>\n",
       "      <td>885</td>\n",
       "      <td>103</td>\n",
       "      <td>690</td>\n",
       "      <td>62</td>\n",
       "      <td>42076</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>20</td>\n",
       "      <td>62</td>\n",
       "      <td>1240</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">177</th>\n",
       "      <th>6</th>\n",
       "      <td>1049</td>\n",
       "      <td>177</td>\n",
       "      <td>360</td>\n",
       "      <td>57</td>\n",
       "      <td>19420</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>20</td>\n",
       "      <td>57</td>\n",
       "      <td>1140</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">246</th>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>246</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>901</td>\n",
       "      <td>246</td>\n",
       "      <td>658</td>\n",
       "      <td>66</td>\n",
       "      <td>34215</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">315</th>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>315</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>827</td>\n",
       "      <td>315</td>\n",
       "      <td>805</td>\n",
       "      <td>66</td>\n",
       "      <td>41069</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">383</th>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>383</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>798</td>\n",
       "      <td>383</td>\n",
       "      <td>864</td>\n",
       "      <td>66</td>\n",
       "      <td>44366</td>\n",
       "      <td>383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">502</th>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>502</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>142</td>\n",
       "      <td>502</td>\n",
       "      <td>462</td>\n",
       "      <td>65</td>\n",
       "      <td>25409</td>\n",
       "      <td>502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1016</td>\n",
       "      <td>502</td>\n",
       "      <td>446</td>\n",
       "      <td>66</td>\n",
       "      <td>24421</td>\n",
       "      <td>502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1869</td>\n",
       "      <td>502</td>\n",
       "      <td>448</td>\n",
       "      <td>65</td>\n",
       "      <td>24894</td>\n",
       "      <td>502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">580</th>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>580</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">620</th>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>620</td>\n",
       "      <td>20</td>\n",
       "      <td>59</td>\n",
       "      <td>1180</td>\n",
       "      <td>620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1833</td>\n",
       "      <td>620</td>\n",
       "      <td>206</td>\n",
       "      <td>59</td>\n",
       "      <td>9843</td>\n",
       "      <td>620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">621</th>\n",
       "      <th>21</th>\n",
       "      <td>1593</td>\n",
       "      <td>621</td>\n",
       "      <td>174</td>\n",
       "      <td>51</td>\n",
       "      <td>8152</td>\n",
       "      <td>621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2154</td>\n",
       "      <td>621</td>\n",
       "      <td>162</td>\n",
       "      <td>51</td>\n",
       "      <td>7692</td>\n",
       "      <td>621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">693</th>\n",
       "      <th>24</th>\n",
       "      <td>1251</td>\n",
       "      <td>693</td>\n",
       "      <td>1065</td>\n",
       "      <td>27</td>\n",
       "      <td>28755</td>\n",
       "      <td>693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>693</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">733</th>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>733</td>\n",
       "      <td>20</td>\n",
       "      <td>113</td>\n",
       "      <td>2260</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>618</td>\n",
       "      <td>733</td>\n",
       "      <td>320</td>\n",
       "      <td>58</td>\n",
       "      <td>14864</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1553</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19317</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1873</td>\n",
       "      <td>733</td>\n",
       "      <td>169</td>\n",
       "      <td>57</td>\n",
       "      <td>8747</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2103</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19346</td>\n",
       "      <td>733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>789</th>\n",
       "      <th>30</th>\n",
       "      <td>570</td>\n",
       "      <td>789</td>\n",
       "      <td>149</td>\n",
       "      <td>51</td>\n",
       "      <td>6448</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312</th>\n",
       "      <th>109</th>\n",
       "      <td>1201</td>\n",
       "      <td>2312</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2352</th>\n",
       "      <th>110</th>\n",
       "      <td>0</td>\n",
       "      <td>2352</td>\n",
       "      <td>20</td>\n",
       "      <td>114</td>\n",
       "      <td>2280</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>1108</td>\n",
       "      <td>2352</td>\n",
       "      <td>110</td>\n",
       "      <td>51</td>\n",
       "      <td>5085</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1277</td>\n",
       "      <td>2352</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19416</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1553</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19639</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1828</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19683</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2103</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19667</td>\n",
       "      <td>2352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2408</th>\n",
       "      <th>116</th>\n",
       "      <td>1070</td>\n",
       "      <td>2408</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>2408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2480</th>\n",
       "      <th>118</th>\n",
       "      <td>1201</td>\n",
       "      <td>2480</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>0</td>\n",
       "      <td>2480</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2521</th>\n",
       "      <th>119</th>\n",
       "      <td>0</td>\n",
       "      <td>2521</td>\n",
       "      <td>20</td>\n",
       "      <td>57</td>\n",
       "      <td>1140</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>1827</td>\n",
       "      <td>2521</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11284</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>969</td>\n",
       "      <td>2521</td>\n",
       "      <td>249</td>\n",
       "      <td>51</td>\n",
       "      <td>11604</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>1277</td>\n",
       "      <td>2521</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11140</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>1553</td>\n",
       "      <td>2521</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2103</td>\n",
       "      <td>2521</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2593</th>\n",
       "      <th>125</th>\n",
       "      <td>0</td>\n",
       "      <td>2593</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1201</td>\n",
       "      <td>2593</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2633</th>\n",
       "      <th>132</th>\n",
       "      <td>2103</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19667</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1828</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19683</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>1553</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19639</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1277</td>\n",
       "      <td>2633</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19416</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1108</td>\n",
       "      <td>2633</td>\n",
       "      <td>110</td>\n",
       "      <td>51</td>\n",
       "      <td>5085</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>0</td>\n",
       "      <td>2633</td>\n",
       "      <td>20</td>\n",
       "      <td>114</td>\n",
       "      <td>2280</td>\n",
       "      <td>2633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2689</th>\n",
       "      <th>133</th>\n",
       "      <td>1070</td>\n",
       "      <td>2689</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>2689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2762</th>\n",
       "      <th>134</th>\n",
       "      <td>0</td>\n",
       "      <td>2762</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>1201</td>\n",
       "      <td>2762</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2957</th>\n",
       "      <th>137</th>\n",
       "      <td>135</td>\n",
       "      <td>2957</td>\n",
       "      <td>2157</td>\n",
       "      <td>86</td>\n",
       "      <td>81564</td>\n",
       "      <td>2957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>0</td>\n",
       "      <td>2957</td>\n",
       "      <td>20</td>\n",
       "      <td>134</td>\n",
       "      <td>2680</td>\n",
       "      <td>2957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3041</th>\n",
       "      <th>138</th>\n",
       "      <td>1234</td>\n",
       "      <td>3041</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>1584</td>\n",
       "      <td>3041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>138 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             left   top  width  height   area top_str\n",
       "top_str                                              \n",
       "0       1       0     0     20      25    500       0\n",
       "        2     135     0   2183      25  54575       0\n",
       "103     4     885   103    690      62  42076     103\n",
       "        3       0   103     20      62   1240     103\n",
       "177     6    1049   177    360      57  19420     177\n",
       "        5       0   177     20      57   1140     177\n",
       "246     7       0   246     20      66   1320     246\n",
       "        8     901   246    658      66  34215     246\n",
       "315     9       0   315     20      66   1320     315\n",
       "        10    827   315    805      66  41069     315\n",
       "383     11      0   383     20      66   1320     383\n",
       "        12    798   383    864      66  44366     383\n",
       "502     13      0   502     20      66   1320     502\n",
       "        14    142   502    462      65  25409     502\n",
       "        15   1016   502    446      66  24421     502\n",
       "        16   1869   502    448      65  24894     502\n",
       "580     17      0   580     20      27    540     580\n",
       "        18    143   580   2164      27  58428     580\n",
       "620     19      0   620     20      59   1180     620\n",
       "        20   1833   620    206      59   9843     620\n",
       "621     21   1593   621    174      51   8152     621\n",
       "        22   2154   621    162      51   7692     621\n",
       "693     24   1251   693   1065      27  28755     693\n",
       "        23      0   693     20      27    540     693\n",
       "733     25      0   733     20     113   2260     733\n",
       "        26    618   733    320      58  14864     733\n",
       "        27   1553   733    214     113  19317     733\n",
       "        28   1873   733    169      57   8747     733\n",
       "        29   2103   733    214     113  19346     733\n",
       "789     30    570   789    149      51   6448     789\n",
       "...           ...   ...    ...     ...    ...     ...\n",
       "2312    109  1201  2312   1115      27  30105    2312\n",
       "2352    110     0  2352     20     114   2280    2352\n",
       "        111  1108  2352    110      51   5085    2352\n",
       "        112  1277  2352    216     111  19416    2352\n",
       "        113  1553  2352    215     111  19639    2352\n",
       "        114  1828  2352    215     111  19683    2352\n",
       "        115  2103  2352    215     111  19667    2352\n",
       "2408    116  1070  2408    149      58   7042    2408\n",
       "2480    118  1201  2480   1115      27  30105    2480\n",
       "        117     0  2480     20      27    540    2480\n",
       "2521    119     0  2521     20      57   1140    2521\n",
       "        123  1827  2521    215      57  11284    2521\n",
       "        120   969  2521    249      51  11604    2521\n",
       "        121  1277  2521    215      57  11140    2521\n",
       "        122  1553  2521    214      57  11232    2521\n",
       "        124  2103  2521    214      57  11232    2521\n",
       "2593    125     0  2593     20      27    540    2593\n",
       "        126  1201  2593   1115      27  30105    2593\n",
       "2633    132  2103  2633    215     111  19667    2633\n",
       "        131  1828  2633    215     111  19683    2633\n",
       "        130  1553  2633    215     111  19639    2633\n",
       "        129  1277  2633    216     111  19416    2633\n",
       "        128  1108  2633    110      51   5085    2633\n",
       "        127     0  2633     20     114   2280    2633\n",
       "2689    133  1070  2689    149      58   7042    2689\n",
       "2762    134     0  2762     20      27    540    2762\n",
       "        135  1201  2762   1115      27  30105    2762\n",
       "2957    137   135  2957   2157      86  81564    2957\n",
       "        136     0  2957     20     134   2680    2957\n",
       "3041    138  1234  3041     34      50   1584    3041\n",
       "\n",
       "[138 rows x 6 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page2_label_stats['top_str'] = page2_label_stats.top.apply(lambda x: str(x))\n",
    "page2_label_stats.groupby('top_str').apply(lambda x: x.iloc[0:10]).sort_values('top')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MMK1SI77VuB9pJK2HIJX2bfU8pI230WPJ5b9Odz1EK81ntEck3fcVGpLp0Kr0vV1vk74u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\nAElEQVQ1rwYeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc63744c250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "line_xs = (page2_label_stats.left + page2_label_stats.width + 20).iloc[125:130].tolist()\n",
    "plot_lines(line_xs, img_page2, 333, 3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2336, 40, 1238, 1513, 1788]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "line_xs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Column Detection\n",
    "\n",
    "Need to figure out column selection that would work on both with and without columnar lines.\n",
    "\n",
    "### Thouhgts/Ideas\n",
    "\n",
    "`Left - Width` will not work as it varies with document pages and needs to be adjusted.     \n",
    "`Left + Width + Buffer` works :D. Since its numbers\n",
    "\n",
    "## TODO\n",
    "\n",
    "- Table Boundaries\n",
    "- Row Boundaries\n",
    "- Table Headers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8Zubkr7lPb+eUXupyqTHqupTanKu3fXVsbi2Djq39hHyu1trv/AEuN8ex1NPxqy3jGHpb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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc63744c590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eroded_image = cv2.erode(img_page2, kernel = np.ones((5,5),np.uint8), iterations=2)\n",
    "rlsa_eroded_image = rlsa(eroded_image, (15, 25))\n",
    "plot_page(rlsa_eroded_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ABjFbAMCSBBkAAKAcQQYAAChHkAEAAMoRZACKca8iABBkAEoSZgDonSADAACU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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6372d0bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eroded_image_page4 = cv2.erode(img_page4, kernel = np.ones((5,5),np.uint8), iterations=2)\n",
    "rlsa_eroded_image_page4 = rlsa(eroded_image_page4, (15, 25))\n",
    "plot_page(rlsa_eroded_image_page4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MzduyrUckMy1Jwp46tvZeei9a7t60krX5SzFLlyl9JqVtjqdLKgCgzM3+Ayk1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\nALojkAEAALojkAEAALrz/wFEMBzJlb8FdAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6372dc190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page4.copy()\n",
    "for index, row in label_stats[(label_stats.width > 1250) & (label_stats.top > 0)].iterrows():\n",
    "    cv2.line(waste_copy, (20, row['top']), (2400, row['top']), (0,255,0), 5)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ob7pn6gnA1sc1er7Vemh609l6jrceRL4KgQxM5uggYetY87RR0pqgm6abG25Q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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc637378110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page2.copy()\n",
    "for index, row in page2_label_stats[(page2_label_stats.width > 1200) & (page2_label_stats.top > 0)].iterrows():\n",
    "    cv2.line(waste_copy, (20, row['top']), (2400, row['top']), (0,255,0), 5)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# the current method\n",
    "def draw_table_bounds(image_gray):\n",
    "        table_bounds = None\n",
    "        temp_image, contours, hierarchy = cv2.findContours(image_gray,\n",
    "                                                           cv2.RETR_LIST,\n",
    "                                                           cv2.CHAIN_APPROX_SIMPLE)\n",
    "        best_match_contour_index = None\n",
    "        max_contour_size = 0\n",
    "        count = 0\n",
    "        for contour in contours:\n",
    "            if cv2.contourArea(contour) > max_contour_size:\n",
    "                contour_size = cv2.contourArea(contour)\n",
    "                x, y, w, h = cv2.boundingRect(contour)\n",
    "                if x > 0 and y > 0 and contour_size > max_contour_size:\n",
    "                    best_match_contour_index = count\n",
    "                    max_contour_size = contour_size\n",
    "            count += 1\n",
    "        if best_match_contour_index:\n",
    "            x, y, w, h = cv2.boundingRect(contours[best_match_contour_index])\n",
    "            x = x - 10\n",
    "            w = w + 10\n",
    "            cv2.rectangle(image_gray, (x, y), (x+w, y+h), (125, 125, 0), 5)\n",
    "            cv2.rectangle(image_gray, (x, y), (x+w, y+h), (125, 125, 0), 5)\n",
    "        return image_gray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# plot_page(draw_table_bounds(img_page4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Detect similarly shaped blocks to merge together. \n",
    "\n",
    "How to detect similar blocks ??\n",
    "    - Vertical\n",
    "        - Similar left most points\n",
    "        - Similar right most points\n",
    "    - Horizontal\n",
    "        - Similar top most points\n",
    "        - Similar bottom most points\n",
    "    - Shorter then the parent or similar width."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "page2_label_stats['right'] = page2_label_stats.left + page2_label_stats.width\n",
    "page2_label_stats['bottom'] = page2_label_stats.top + page2_label_stats.height\n",
    "label_stats['right'] = label_stats.left + label_stats.width\n",
    "label_stats['bottom'] = label_stats.top + label_stats.height"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>2183</td>\n",
       "      <td>25</td>\n",
       "      <td>54575</td>\n",
       "      <td>0</td>\n",
       "      <td>2318</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>20</td>\n",
       "      <td>62</td>\n",
       "      <td>1240</td>\n",
       "      <td>103</td>\n",
       "      <td>20</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>885</td>\n",
       "      <td>103</td>\n",
       "      <td>690</td>\n",
       "      <td>62</td>\n",
       "      <td>42076</td>\n",
       "      <td>103</td>\n",
       "      <td>1575</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>20</td>\n",
       "      <td>57</td>\n",
       "      <td>1140</td>\n",
       "      <td>177</td>\n",
       "      <td>20</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1049</td>\n",
       "      <td>177</td>\n",
       "      <td>360</td>\n",
       "      <td>57</td>\n",
       "      <td>19420</td>\n",
       "      <td>177</td>\n",
       "      <td>1409</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>246</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>246</td>\n",
       "      <td>20</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>901</td>\n",
       "      <td>246</td>\n",
       "      <td>658</td>\n",
       "      <td>66</td>\n",
       "      <td>34215</td>\n",
       "      <td>246</td>\n",
       "      <td>1559</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>315</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>315</td>\n",
       "      <td>20</td>\n",
       "      <td>381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>827</td>\n",
       "      <td>315</td>\n",
       "      <td>805</td>\n",
       "      <td>66</td>\n",
       "      <td>41069</td>\n",
       "      <td>315</td>\n",
       "      <td>1632</td>\n",
       "      <td>381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>383</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>383</td>\n",
       "      <td>20</td>\n",
       "      <td>449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>798</td>\n",
       "      <td>383</td>\n",
       "      <td>864</td>\n",
       "      <td>66</td>\n",
       "      <td>44366</td>\n",
       "      <td>383</td>\n",
       "      <td>1662</td>\n",
       "      <td>449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>502</td>\n",
       "      <td>20</td>\n",
       "      <td>66</td>\n",
       "      <td>1320</td>\n",
       "      <td>502</td>\n",
       "      <td>20</td>\n",
       "      <td>568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>142</td>\n",
       "      <td>502</td>\n",
       "      <td>462</td>\n",
       "      <td>65</td>\n",
       "      <td>25409</td>\n",
       "      <td>502</td>\n",
       "      <td>604</td>\n",
       "      <td>567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1016</td>\n",
       "      <td>502</td>\n",
       "      <td>446</td>\n",
       "      <td>66</td>\n",
       "      <td>24421</td>\n",
       "      <td>502</td>\n",
       "      <td>1462</td>\n",
       "      <td>568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1869</td>\n",
       "      <td>502</td>\n",
       "      <td>448</td>\n",
       "      <td>65</td>\n",
       "      <td>24894</td>\n",
       "      <td>502</td>\n",
       "      <td>2317</td>\n",
       "      <td>567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>580</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>580</td>\n",
       "      <td>20</td>\n",
       "      <td>607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "      <td>2307</td>\n",
       "      <td>607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>620</td>\n",
       "      <td>20</td>\n",
       "      <td>59</td>\n",
       "      <td>1180</td>\n",
       "      <td>620</td>\n",
       "      <td>20</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1833</td>\n",
       "      <td>620</td>\n",
       "      <td>206</td>\n",
       "      <td>59</td>\n",
       "      <td>9843</td>\n",
       "      <td>620</td>\n",
       "      <td>2039</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1593</td>\n",
       "      <td>621</td>\n",
       "      <td>174</td>\n",
       "      <td>51</td>\n",
       "      <td>8152</td>\n",
       "      <td>621</td>\n",
       "      <td>1767</td>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2154</td>\n",
       "      <td>621</td>\n",
       "      <td>162</td>\n",
       "      <td>51</td>\n",
       "      <td>7692</td>\n",
       "      <td>621</td>\n",
       "      <td>2316</td>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>693</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>693</td>\n",
       "      <td>20</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1251</td>\n",
       "      <td>693</td>\n",
       "      <td>1065</td>\n",
       "      <td>27</td>\n",
       "      <td>28755</td>\n",
       "      <td>693</td>\n",
       "      <td>2316</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>733</td>\n",
       "      <td>20</td>\n",
       "      <td>113</td>\n",
       "      <td>2260</td>\n",
       "      <td>733</td>\n",
       "      <td>20</td>\n",
       "      <td>846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>618</td>\n",
       "      <td>733</td>\n",
       "      <td>320</td>\n",
       "      <td>58</td>\n",
       "      <td>14864</td>\n",
       "      <td>733</td>\n",
       "      <td>938</td>\n",
       "      <td>791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1553</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19317</td>\n",
       "      <td>733</td>\n",
       "      <td>1767</td>\n",
       "      <td>846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1873</td>\n",
       "      <td>733</td>\n",
       "      <td>169</td>\n",
       "      <td>57</td>\n",
       "      <td>8747</td>\n",
       "      <td>733</td>\n",
       "      <td>2042</td>\n",
       "      <td>790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2103</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19346</td>\n",
       "      <td>733</td>\n",
       "      <td>2317</td>\n",
       "      <td>846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>570</td>\n",
       "      <td>789</td>\n",
       "      <td>149</td>\n",
       "      <td>51</td>\n",
       "      <td>6448</td>\n",
       "      <td>789</td>\n",
       "      <td>719</td>\n",
       "      <td>840</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>1201</td>\n",
       "      <td>2312</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2312</td>\n",
       "      <td>2316</td>\n",
       "      <td>2339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>0</td>\n",
       "      <td>2352</td>\n",
       "      <td>20</td>\n",
       "      <td>114</td>\n",
       "      <td>2280</td>\n",
       "      <td>2352</td>\n",
       "      <td>20</td>\n",
       "      <td>2466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>1108</td>\n",
       "      <td>2352</td>\n",
       "      <td>110</td>\n",
       "      <td>51</td>\n",
       "      <td>5085</td>\n",
       "      <td>2352</td>\n",
       "      <td>1218</td>\n",
       "      <td>2403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1277</td>\n",
       "      <td>2352</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19416</td>\n",
       "      <td>2352</td>\n",
       "      <td>1493</td>\n",
       "      <td>2463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1553</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19639</td>\n",
       "      <td>2352</td>\n",
       "      <td>1768</td>\n",
       "      <td>2463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1828</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19683</td>\n",
       "      <td>2352</td>\n",
       "      <td>2043</td>\n",
       "      <td>2463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2103</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19667</td>\n",
       "      <td>2352</td>\n",
       "      <td>2318</td>\n",
       "      <td>2463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>1070</td>\n",
       "      <td>2408</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>2408</td>\n",
       "      <td>1219</td>\n",
       "      <td>2466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>0</td>\n",
       "      <td>2480</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2480</td>\n",
       "      <td>20</td>\n",
       "      <td>2507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>1201</td>\n",
       "      <td>2480</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2480</td>\n",
       "      <td>2316</td>\n",
       "      <td>2507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>0</td>\n",
       "      <td>2521</td>\n",
       "      <td>20</td>\n",
       "      <td>57</td>\n",
       "      <td>1140</td>\n",
       "      <td>2521</td>\n",
       "      <td>20</td>\n",
       "      <td>2578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>969</td>\n",
       "      <td>2521</td>\n",
       "      <td>249</td>\n",
       "      <td>51</td>\n",
       "      <td>11604</td>\n",
       "      <td>2521</td>\n",
       "      <td>1218</td>\n",
       "      <td>2572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>1277</td>\n",
       "      <td>2521</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11140</td>\n",
       "      <td>2521</td>\n",
       "      <td>1492</td>\n",
       "      <td>2578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>1553</td>\n",
       "      <td>2521</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2521</td>\n",
       "      <td>1767</td>\n",
       "      <td>2578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>1827</td>\n",
       "      <td>2521</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11284</td>\n",
       "      <td>2521</td>\n",
       "      <td>2042</td>\n",
       "      <td>2578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2103</td>\n",
       "      <td>2521</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2521</td>\n",
       "      <td>2317</td>\n",
       "      <td>2578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>0</td>\n",
       "      <td>2593</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2593</td>\n",
       "      <td>20</td>\n",
       "      <td>2620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1201</td>\n",
       "      <td>2593</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2593</td>\n",
       "      <td>2316</td>\n",
       "      <td>2620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>0</td>\n",
       "      <td>2633</td>\n",
       "      <td>20</td>\n",
       "      <td>114</td>\n",
       "      <td>2280</td>\n",
       "      <td>2633</td>\n",
       "      <td>20</td>\n",
       "      <td>2747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1108</td>\n",
       "      <td>2633</td>\n",
       "      <td>110</td>\n",
       "      <td>51</td>\n",
       "      <td>5085</td>\n",
       "      <td>2633</td>\n",
       "      <td>1218</td>\n",
       "      <td>2684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1277</td>\n",
       "      <td>2633</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19416</td>\n",
       "      <td>2633</td>\n",
       "      <td>1493</td>\n",
       "      <td>2744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>1553</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19639</td>\n",
       "      <td>2633</td>\n",
       "      <td>1768</td>\n",
       "      <td>2744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1828</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19683</td>\n",
       "      <td>2633</td>\n",
       "      <td>2043</td>\n",
       "      <td>2744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2103</td>\n",
       "      <td>2633</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19667</td>\n",
       "      <td>2633</td>\n",
       "      <td>2318</td>\n",
       "      <td>2744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>1070</td>\n",
       "      <td>2689</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>2689</td>\n",
       "      <td>1219</td>\n",
       "      <td>2747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>0</td>\n",
       "      <td>2762</td>\n",
       "      <td>20</td>\n",
       "      <td>27</td>\n",
       "      <td>540</td>\n",
       "      <td>2762</td>\n",
       "      <td>20</td>\n",
       "      <td>2789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>1201</td>\n",
       "      <td>2762</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2762</td>\n",
       "      <td>2316</td>\n",
       "      <td>2789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>0</td>\n",
       "      <td>2957</td>\n",
       "      <td>20</td>\n",
       "      <td>134</td>\n",
       "      <td>2680</td>\n",
       "      <td>2957</td>\n",
       "      <td>20</td>\n",
       "      <td>3091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>135</td>\n",
       "      <td>2957</td>\n",
       "      <td>2157</td>\n",
       "      <td>86</td>\n",
       "      <td>81564</td>\n",
       "      <td>2957</td>\n",
       "      <td>2292</td>\n",
       "      <td>3043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>1234</td>\n",
       "      <td>3041</td>\n",
       "      <td>34</td>\n",
       "      <td>50</td>\n",
       "      <td>1584</td>\n",
       "      <td>3041</td>\n",
       "      <td>1268</td>\n",
       "      <td>3091</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>138 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom\n",
       "1       0     0     20      25    500       0     20      25\n",
       "2     135     0   2183      25  54575       0   2318      25\n",
       "3       0   103     20      62   1240     103     20     165\n",
       "4     885   103    690      62  42076     103   1575     165\n",
       "5       0   177     20      57   1140     177     20     234\n",
       "6    1049   177    360      57  19420     177   1409     234\n",
       "7       0   246     20      66   1320     246     20     312\n",
       "8     901   246    658      66  34215     246   1559     312\n",
       "9       0   315     20      66   1320     315     20     381\n",
       "10    827   315    805      66  41069     315   1632     381\n",
       "11      0   383     20      66   1320     383     20     449\n",
       "12    798   383    864      66  44366     383   1662     449\n",
       "13      0   502     20      66   1320     502     20     568\n",
       "14    142   502    462      65  25409     502    604     567\n",
       "15   1016   502    446      66  24421     502   1462     568\n",
       "16   1869   502    448      65  24894     502   2317     567\n",
       "17      0   580     20      27    540     580     20     607\n",
       "18    143   580   2164      27  58428     580   2307     607\n",
       "19      0   620     20      59   1180     620     20     679\n",
       "20   1833   620    206      59   9843     620   2039     679\n",
       "21   1593   621    174      51   8152     621   1767     672\n",
       "22   2154   621    162      51   7692     621   2316     672\n",
       "23      0   693     20      27    540     693     20     720\n",
       "24   1251   693   1065      27  28755     693   2316     720\n",
       "25      0   733     20     113   2260     733     20     846\n",
       "26    618   733    320      58  14864     733    938     791\n",
       "27   1553   733    214     113  19317     733   1767     846\n",
       "28   1873   733    169      57   8747     733   2042     790\n",
       "29   2103   733    214     113  19346     733   2317     846\n",
       "30    570   789    149      51   6448     789    719     840\n",
       "..    ...   ...    ...     ...    ...     ...    ...     ...\n",
       "109  1201  2312   1115      27  30105    2312   2316    2339\n",
       "110     0  2352     20     114   2280    2352     20    2466\n",
       "111  1108  2352    110      51   5085    2352   1218    2403\n",
       "112  1277  2352    216     111  19416    2352   1493    2463\n",
       "113  1553  2352    215     111  19639    2352   1768    2463\n",
       "114  1828  2352    215     111  19683    2352   2043    2463\n",
       "115  2103  2352    215     111  19667    2352   2318    2463\n",
       "116  1070  2408    149      58   7042    2408   1219    2466\n",
       "117     0  2480     20      27    540    2480     20    2507\n",
       "118  1201  2480   1115      27  30105    2480   2316    2507\n",
       "119     0  2521     20      57   1140    2521     20    2578\n",
       "120   969  2521    249      51  11604    2521   1218    2572\n",
       "121  1277  2521    215      57  11140    2521   1492    2578\n",
       "122  1553  2521    214      57  11232    2521   1767    2578\n",
       "123  1827  2521    215      57  11284    2521   2042    2578\n",
       "124  2103  2521    214      57  11232    2521   2317    2578\n",
       "125     0  2593     20      27    540    2593     20    2620\n",
       "126  1201  2593   1115      27  30105    2593   2316    2620\n",
       "127     0  2633     20     114   2280    2633     20    2747\n",
       "128  1108  2633    110      51   5085    2633   1218    2684\n",
       "129  1277  2633    216     111  19416    2633   1493    2744\n",
       "130  1553  2633    215     111  19639    2633   1768    2744\n",
       "131  1828  2633    215     111  19683    2633   2043    2744\n",
       "132  2103  2633    215     111  19667    2633   2318    2744\n",
       "133  1070  2689    149      58   7042    2689   1219    2747\n",
       "134     0  2762     20      27    540    2762     20    2789\n",
       "135  1201  2762   1115      27  30105    2762   2316    2789\n",
       "136     0  2957     20     134   2680    2957     20    3091\n",
       "137   135  2957   2157      86  81564    2957   2292    3043\n",
       "138  1234  3041     34      50   1584    3041   1268    3091\n",
       "\n",
       "[138 rows x 8 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "page2_label_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "label_2_label_map = np.zeros((page2_label_stats.shape[0], page2_label_stats.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_2_label_map[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "left         142\n",
      "top          502\n",
      "width        462\n",
      "height        65\n",
      "area       25409\n",
      "top_str      502\n",
      "right        604\n",
      "bottom       567\n",
      "Name: 14, dtype: object\n",
      "    left   top  width  height   area top_str  right  bottom\n",
      "85   144  1889    457     108  32860    1889    601    1997\n"
     ]
    }
   ],
   "source": [
    "for index, value in enumerate(label_2_label_map[10]):\n",
    "    base_label = page2_label_stats.iloc[13]\n",
    "    print(base_label)\n",
    "    similarly_aligned = page2_label_stats[(page2_label_stats.top > base_label.top) & \n",
    "                                          (page2_label_stats.right.between(base_label.right - 10, base_label.right + 10)) &\n",
    "                                          (page2_label_stats.width.between(base_label.width - 20, base_label.width + 20))]\n",
    "    print(similarly_aligned)\n",
    "    similarly_aligned = similarly_aligned.append(base_label)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([85, 14], dtype='int64')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarly_aligned.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "page_layout = pdf.getPage(3)['/MediaBox']\n",
    "if '/Rotate' in pdf.getPage(3) and pdf.getPage(3)['/Rotate'] == 90:\n",
    "    page_width = float(page_layout[3])\n",
    "    page_height = float(page_layout[2])\n",
    "else:\n",
    "    page_width = float(page_layout[2])\n",
    "    page_height = float(page_layout[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "image_height, image_width = img_page2.shape\n",
    "horizontal_ratio = page_width/image_width\n",
    "vertical_ratio = page_height/image_height\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(34.082291246470355, 120.49144811858609)\n",
      "(15.601482326111745, 110.8874546187979)\n",
      "(34.5623235175474, 453.403078677309)\n",
      "(25.922462941847208, 109.68737394110529)\n"
     ]
    },
    {
     "data": {
      "image/png": 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aFsL7w7yebVjWMxwDPFLaa9y6po4YDlTqhZil0T2iNZ8lN6y45qiend50z9QT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\nAACA5ggyAABAc/4fm7Sc/P4raL8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6375c78d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page2.copy()\n",
    "for index, row in page2_label_stats[page2_label_stats.index.isin(similarly_aligned.index)].iterrows():\n",
    "    print(row.left * horizontal_ratio, row.top * vertical_ratio)\n",
    "    print(row.height * vertical_ratio, row.width * horizontal_ratio)\n",
    "    cv2.rectangle(waste_copy, (row['left'], row['top']), (row['right'], row['bottom']), (125,125,0), 5)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def find_similar_blocks(row, label_stats, similarity_map):\n",
    "    similarly_aligned = label_stats[(label_stats.top > row.top) & \n",
    "                                    (label_stats.right.between(row.right - 10, row.right + 10)) &\n",
    "                                    (label_stats.width.between(row.width - 20, row.width + 20))]\n",
    "    positions = [[row['pos'] - 1] * len(similarly_aligned), similarly_aligned.index.tolist()]\n",
    "    similarity_map[positions] = 1\n",
    "    return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def add_similarity_map(label_stats):\n",
    "    similarity_map = np.zeros((label_stats.shape[0], label_stats.shape[0]))\n",
    "    label_stats.apply(find_similar_blocks, args=[label_stats, similarity_map], axis=1)\n",
    "    similarity_df = pd.DataFrame(similarity_map, columns=['label_{0}'.format(index) for index in range(label_stats.shape[0])],\n",
    "                                 index=label_stats.index)\n",
    "    similarity_df['count'] = similarity_df.apply(sum, axis=1)\n",
    "    return pd.concat([label_stats, similarity_df], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "page2_label_stats['pos'] = page2_label_stats.index\n",
    "similar_labels = add_similarity_map(page2_label_stats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "      <th>pos</th>\n",
       "      <th>label_0</th>\n",
       "      <th>...</th>\n",
       "      <th>label_129</th>\n",
       "      <th>label_130</th>\n",
       "      <th>label_131</th>\n",
       "      <th>label_132</th>\n",
       "      <th>label_133</th>\n",
       "      <th>label_134</th>\n",
       "      <th>label_135</th>\n",
       "      <th>label_136</th>\n",
       "      <th>label_137</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "      <td>2307</td>\n",
       "      <td>607</td>\n",
       "      <td>18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1833</td>\n",
       "      <td>620</td>\n",
       "      <td>206</td>\n",
       "      <td>59</td>\n",
       "      <td>9843</td>\n",
       "      <td>620</td>\n",
       "      <td>2039</td>\n",
       "      <td>679</td>\n",
       "      <td>20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1553</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19317</td>\n",
       "      <td>733</td>\n",
       "      <td>1767</td>\n",
       "      <td>846</td>\n",
       "      <td>27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1873</td>\n",
       "      <td>733</td>\n",
       "      <td>169</td>\n",
       "      <td>57</td>\n",
       "      <td>8747</td>\n",
       "      <td>733</td>\n",
       "      <td>2042</td>\n",
       "      <td>790</td>\n",
       "      <td>28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2103</td>\n",
       "      <td>733</td>\n",
       "      <td>214</td>\n",
       "      <td>113</td>\n",
       "      <td>19346</td>\n",
       "      <td>733</td>\n",
       "      <td>2317</td>\n",
       "      <td>846</td>\n",
       "      <td>29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1553</td>\n",
       "      <td>902</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11192</td>\n",
       "      <td>902</td>\n",
       "      <td>1767</td>\n",
       "      <td>959</td>\n",
       "      <td>37</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2103</td>\n",
       "      <td>902</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11226</td>\n",
       "      <td>902</td>\n",
       "      <td>2317</td>\n",
       "      <td>959</td>\n",
       "      <td>39</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>1201</td>\n",
       "      <td>1443</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>1443</td>\n",
       "      <td>2316</td>\n",
       "      <td>1470</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1103</td>\n",
       "      <td>1596</td>\n",
       "      <td>114</td>\n",
       "      <td>51</td>\n",
       "      <td>5405</td>\n",
       "      <td>1596</td>\n",
       "      <td>1217</td>\n",
       "      <td>1647</td>\n",
       "      <td>68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1279</td>\n",
       "      <td>1596</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19647</td>\n",
       "      <td>1596</td>\n",
       "      <td>1494</td>\n",
       "      <td>1707</td>\n",
       "      <td>69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1552</td>\n",
       "      <td>1596</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19835</td>\n",
       "      <td>1596</td>\n",
       "      <td>1768</td>\n",
       "      <td>1707</td>\n",
       "      <td>70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1827</td>\n",
       "      <td>1596</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19739</td>\n",
       "      <td>1596</td>\n",
       "      <td>2043</td>\n",
       "      <td>1707</td>\n",
       "      <td>71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2102</td>\n",
       "      <td>1596</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19758</td>\n",
       "      <td>1596</td>\n",
       "      <td>2318</td>\n",
       "      <td>1707</td>\n",
       "      <td>72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>1070</td>\n",
       "      <td>1652</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>1652</td>\n",
       "      <td>1219</td>\n",
       "      <td>1710</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1201</td>\n",
       "      <td>1724</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>1724</td>\n",
       "      <td>2316</td>\n",
       "      <td>1751</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1279</td>\n",
       "      <td>1764</td>\n",
       "      <td>213</td>\n",
       "      <td>57</td>\n",
       "      <td>11128</td>\n",
       "      <td>1764</td>\n",
       "      <td>1492</td>\n",
       "      <td>1821</td>\n",
       "      <td>78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>1552</td>\n",
       "      <td>1764</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11284</td>\n",
       "      <td>1764</td>\n",
       "      <td>1767</td>\n",
       "      <td>1821</td>\n",
       "      <td>79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>1827</td>\n",
       "      <td>1764</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11273</td>\n",
       "      <td>1764</td>\n",
       "      <td>2042</td>\n",
       "      <td>1821</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2102</td>\n",
       "      <td>1764</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11264</td>\n",
       "      <td>1764</td>\n",
       "      <td>2317</td>\n",
       "      <td>1821</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>1201</td>\n",
       "      <td>1837</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>1837</td>\n",
       "      <td>2316</td>\n",
       "      <td>1864</td>\n",
       "      <td>83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>1103</td>\n",
       "      <td>1946</td>\n",
       "      <td>114</td>\n",
       "      <td>51</td>\n",
       "      <td>5405</td>\n",
       "      <td>1946</td>\n",
       "      <td>1217</td>\n",
       "      <td>1997</td>\n",
       "      <td>86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>1277</td>\n",
       "      <td>1946</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>18661</td>\n",
       "      <td>1946</td>\n",
       "      <td>1492</td>\n",
       "      <td>2057</td>\n",
       "      <td>87</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1552</td>\n",
       "      <td>1946</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19758</td>\n",
       "      <td>1946</td>\n",
       "      <td>1768</td>\n",
       "      <td>2057</td>\n",
       "      <td>88</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>1827</td>\n",
       "      <td>1946</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19715</td>\n",
       "      <td>1946</td>\n",
       "      <td>2043</td>\n",
       "      <td>2057</td>\n",
       "      <td>89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2102</td>\n",
       "      <td>1946</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19737</td>\n",
       "      <td>1946</td>\n",
       "      <td>2318</td>\n",
       "      <td>2057</td>\n",
       "      <td>90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>1070</td>\n",
       "      <td>2002</td>\n",
       "      <td>149</td>\n",
       "      <td>58</td>\n",
       "      <td>7042</td>\n",
       "      <td>2002</td>\n",
       "      <td>1219</td>\n",
       "      <td>2060</td>\n",
       "      <td>91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>1201</td>\n",
       "      <td>2074</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2074</td>\n",
       "      <td>2316</td>\n",
       "      <td>2101</td>\n",
       "      <td>93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1277</td>\n",
       "      <td>2114</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11288</td>\n",
       "      <td>2114</td>\n",
       "      <td>1492</td>\n",
       "      <td>2171</td>\n",
       "      <td>96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1552</td>\n",
       "      <td>2114</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11312</td>\n",
       "      <td>2114</td>\n",
       "      <td>1767</td>\n",
       "      <td>2171</td>\n",
       "      <td>97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1827</td>\n",
       "      <td>2114</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11289</td>\n",
       "      <td>2114</td>\n",
       "      <td>2042</td>\n",
       "      <td>2171</td>\n",
       "      <td>98</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2102</td>\n",
       "      <td>2114</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11315</td>\n",
       "      <td>2114</td>\n",
       "      <td>2317</td>\n",
       "      <td>2171</td>\n",
       "      <td>99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>1201</td>\n",
       "      <td>2187</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2187</td>\n",
       "      <td>2316</td>\n",
       "      <td>2214</td>\n",
       "      <td>101</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>1277</td>\n",
       "      <td>2239</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11140</td>\n",
       "      <td>2239</td>\n",
       "      <td>1492</td>\n",
       "      <td>2296</td>\n",
       "      <td>104</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>1553</td>\n",
       "      <td>2239</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2239</td>\n",
       "      <td>1767</td>\n",
       "      <td>2296</td>\n",
       "      <td>105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>1827</td>\n",
       "      <td>2239</td>\n",
       "      <td>215</td>\n",
       "      <td>57</td>\n",
       "      <td>11284</td>\n",
       "      <td>2239</td>\n",
       "      <td>2042</td>\n",
       "      <td>2296</td>\n",
       "      <td>106</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2103</td>\n",
       "      <td>2239</td>\n",
       "      <td>214</td>\n",
       "      <td>57</td>\n",
       "      <td>11232</td>\n",
       "      <td>2239</td>\n",
       "      <td>2317</td>\n",
       "      <td>2296</td>\n",
       "      <td>107</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>1201</td>\n",
       "      <td>2312</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2312</td>\n",
       "      <td>2316</td>\n",
       "      <td>2339</td>\n",
       "      <td>109</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1277</td>\n",
       "      <td>2352</td>\n",
       "      <td>216</td>\n",
       "      <td>111</td>\n",
       "      <td>19416</td>\n",
       "      <td>2352</td>\n",
       "      <td>1493</td>\n",
       "      <td>2463</td>\n",
       "      <td>112</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1553</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19639</td>\n",
       "      <td>2352</td>\n",
       "      <td>1768</td>\n",
       "      <td>2463</td>\n",
       "      <td>113</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1828</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19683</td>\n",
       "      <td>2352</td>\n",
       "      <td>2043</td>\n",
       "      <td>2463</td>\n",
       "      <td>114</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2103</td>\n",
       "      <td>2352</td>\n",
       "      <td>215</td>\n",
       "      <td>111</td>\n",
       "      <td>19667</td>\n",
       "      <td>2352</td>\n",
       "      <td>2318</td>\n",
       "      <td>2463</td>\n",
       "      <td>115</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>1201</td>\n",
       "      <td>2480</td>\n",
       "      <td>1115</td>\n",
       "      <td>27</td>\n",
       "      <td>30105</td>\n",
       "      <td>2480</td>\n",
       "      <td>2316</td>\n",
       "      <td>2507</td>\n",
       "      <td>118</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>42 rows × 148 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom  pos  label_0  \\\n",
       "18    143   580   2164      27  58428     580   2307     607   18      0.0   \n",
       "20   1833   620    206      59   9843     620   2039     679   20      0.0   \n",
       "27   1553   733    214     113  19317     733   1767     846   27      0.0   \n",
       "28   1873   733    169      57   8747     733   2042     790   28      0.0   \n",
       "29   2103   733    214     113  19346     733   2317     846   29      0.0   \n",
       "37   1553   902    214      57  11192     902   1767     959   37      0.0   \n",
       "39   2103   902    214      57  11226     902   2317     959   39      0.0   \n",
       "62   1201  1443   1115      27  30105    1443   2316    1470   62      0.0   \n",
       "68   1103  1596    114      51   5405    1596   1217    1647   68      0.0   \n",
       "69   1279  1596    215     111  19647    1596   1494    1707   69      0.0   \n",
       "70   1552  1596    216     111  19835    1596   1768    1707   70      0.0   \n",
       "71   1827  1596    216     111  19739    1596   2043    1707   71      0.0   \n",
       "72   2102  1596    216     111  19758    1596   2318    1707   72      0.0   \n",
       "73   1070  1652    149      58   7042    1652   1219    1710   73      0.0   \n",
       "75   1201  1724   1115      27  30105    1724   2316    1751   75      0.0   \n",
       "78   1279  1764    213      57  11128    1764   1492    1821   78      0.0   \n",
       "79   1552  1764    215      57  11284    1764   1767    1821   79      0.0   \n",
       "80   1827  1764    215      57  11273    1764   2042    1821   80      0.0   \n",
       "81   2102  1764    215      57  11264    1764   2317    1821   81      0.0   \n",
       "83   1201  1837   1115      27  30105    1837   2316    1864   83      0.0   \n",
       "86   1103  1946    114      51   5405    1946   1217    1997   86      0.0   \n",
       "87   1277  1946    215     111  18661    1946   1492    2057   87      0.0   \n",
       "88   1552  1946    216     111  19758    1946   1768    2057   88      0.0   \n",
       "89   1827  1946    216     111  19715    1946   2043    2057   89      0.0   \n",
       "90   2102  1946    216     111  19737    1946   2318    2057   90      0.0   \n",
       "91   1070  2002    149      58   7042    2002   1219    2060   91      0.0   \n",
       "93   1201  2074   1115      27  30105    2074   2316    2101   93      0.0   \n",
       "96   1277  2114    215      57  11288    2114   1492    2171   96      0.0   \n",
       "97   1552  2114    215      57  11312    2114   1767    2171   97      0.0   \n",
       "98   1827  2114    215      57  11289    2114   2042    2171   98      0.0   \n",
       "99   2102  2114    215      57  11315    2114   2317    2171   99      0.0   \n",
       "101  1201  2187   1115      27  30105    2187   2316    2214  101      0.0   \n",
       "104  1277  2239    215      57  11140    2239   1492    2296  104      0.0   \n",
       "105  1553  2239    214      57  11232    2239   1767    2296  105      0.0   \n",
       "106  1827  2239    215      57  11284    2239   2042    2296  106      0.0   \n",
       "107  2103  2239    214      57  11232    2239   2317    2296  107      0.0   \n",
       "109  1201  2312   1115      27  30105    2312   2316    2339  109      0.0   \n",
       "112  1277  2352    216     111  19416    2352   1493    2463  112      0.0   \n",
       "113  1553  2352    215     111  19639    2352   1768    2463  113      0.0   \n",
       "114  1828  2352    215     111  19683    2352   2043    2463  114      0.0   \n",
       "115  2103  2352    215     111  19667    2352   2318    2463  115      0.0   \n",
       "118  1201  2480   1115      27  30105    2480   2316    2507  118      0.0   \n",
       "\n",
       "     ...    label_129  label_130  label_131  label_132  label_133  label_134  \\\n",
       "18   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "20   ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "27   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "28   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "29   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "37   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "39   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "62   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "68   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "69   ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "70   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "71   ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "72   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "73   ...          0.0        0.0        0.0        0.0        1.0        0.0   \n",
       "75   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "78   ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "79   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "80   ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "81   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "83   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "86   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "87   ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "88   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "89   ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "90   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "91   ...          0.0        0.0        0.0        0.0        1.0        0.0   \n",
       "93   ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "96   ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "97   ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "98   ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "99   ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "101  ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "104  ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "105  ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "106  ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "107  ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "109  ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "112  ...          1.0        0.0        0.0        0.0        0.0        0.0   \n",
       "113  ...          0.0        1.0        0.0        0.0        0.0        0.0   \n",
       "114  ...          0.0        0.0        1.0        0.0        0.0        0.0   \n",
       "115  ...          0.0        0.0        0.0        1.0        0.0        0.0   \n",
       "118  ...          0.0        0.0        0.0        0.0        0.0        0.0   \n",
       "\n",
       "     label_135  label_136  label_137  count  \n",
       "18         0.0        0.0        0.0    2.0  \n",
       "20         0.0        0.0        0.0    8.0  \n",
       "27         0.0        0.0        0.0    9.0  \n",
       "28         0.0        0.0        0.0    2.0  \n",
       "29         0.0        0.0        0.0    9.0  \n",
       "37         0.0        0.0        0.0    8.0  \n",
       "39         0.0        0.0        0.0    8.0  \n",
       "62         1.0        0.0        0.0    8.0  \n",
       "68         0.0        0.0        0.0    3.0  \n",
       "69         0.0        0.0        0.0    7.0  \n",
       "70         0.0        0.0        0.0    7.0  \n",
       "71         0.0        0.0        0.0    7.0  \n",
       "72         0.0        0.0        0.0    7.0  \n",
       "73         0.0        0.0        0.0    3.0  \n",
       "75         1.0        0.0        0.0    7.0  \n",
       "78         0.0        0.0        0.0    6.0  \n",
       "79         0.0        0.0        0.0    6.0  \n",
       "80         0.0        0.0        0.0    6.0  \n",
       "81         0.0        0.0        0.0    6.0  \n",
       "83         1.0        0.0        0.0    6.0  \n",
       "86         0.0        0.0        0.0    2.0  \n",
       "87         0.0        0.0        0.0    5.0  \n",
       "88         0.0        0.0        0.0    5.0  \n",
       "89         0.0        0.0        0.0    5.0  \n",
       "90         0.0        0.0        0.0    5.0  \n",
       "91         0.0        0.0        0.0    2.0  \n",
       "93         1.0        0.0        0.0    5.0  \n",
       "96         0.0        0.0        0.0    4.0  \n",
       "97         0.0        0.0        0.0    4.0  \n",
       "98         0.0        0.0        0.0    4.0  \n",
       "99         0.0        0.0        0.0    4.0  \n",
       "101        1.0        0.0        0.0    4.0  \n",
       "104        0.0        0.0        0.0    3.0  \n",
       "105        0.0        0.0        0.0    3.0  \n",
       "106        0.0        0.0        0.0    3.0  \n",
       "107        0.0        0.0        0.0    3.0  \n",
       "109        1.0        0.0        0.0    3.0  \n",
       "112        0.0        0.0        0.0    2.0  \n",
       "113        0.0        0.0        0.0    2.0  \n",
       "114        0.0        0.0        0.0    2.0  \n",
       "115        0.0        0.0        0.0    2.0  \n",
       "118        1.0        0.0        0.0    2.0  \n",
       "\n",
       "[42 rows x 148 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similar_labels[(similar_labels.left > 0) & (similar_labels['count'] > 1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From these similar labels we need to figure out structure defining labels\n",
    "\n",
    "For each parent label remove child label. \n",
    "\n",
    "    Maybe use Argmax on the label_x columns to get the indices and then generate the sets.   \n",
    "    Also ignore the labels with left == 0\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "similar_label_indices = similar_labels[(similar_labels.left > 0) & (similar_labels['count'] > 1)].index.tolist()\n",
    "parent_label_indices = {}\n",
    "marked_label_indices = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# for index in similar_label_indices:\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sudden Realization, I might not need what I am currently doing for table boudaries and columns!!\n",
    "\n",
    "Stupendo..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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L29+2uS07aqheOhwvd96Uzrfe8pSG3JWOc/QYcmVPj2l9XgOUCGSAyzpiXkwryNlarj32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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6373a5650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page2.copy()\n",
    "for index, row in page2_label_stats[(page2_label_stats.width > 1200) & (page2_label_stats.top > 0)].iterrows():\n",
    "    cv2.line(waste_copy, (row['left'], row['top']), (row['right'] + 50, row['top']), (0,255,0), 5)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FX7u5vXcbriBtTOWSsLUY5OK0JZ6tn+lon8uj6tfaDyvErx+d9JzBo+rXI+vy3RlaBsDl\n1O676LmBtufHANJ17bnheZSGdrrvR9/sXFvX1s90NEfWr5Y4HfGZjmhL/dqabDxzXVenRwaAyyk1\nvtauktZ6BVrKLL131LrOZkuc12LRG+feddWmn9Ej6teW9d01zo/Y72ceN1enRwYAABiORAYAABiO\nRAYAABiORAYAABiORAYAABiORAYAABiORAYAABiORAYAABiORAYAABjOR6/eAAAYzTRNH0y765O1\nHyUX4xDE+Wjq8nOI82PokQGAjeZ5/qwxUmp4s80S1yXGGn2PpS4/hzgfSyIDAA+gkfJ4Yvwc4vx4\n0zSJ8wYSGQDYYWl8xD0G0zSFeZ41TA6Sa+QtMeY46vLjxXU57plZemrEuY9EBgB2yjWoNbSPl8ZT\no+946vJzlOqyOPeRyADATmmD2hj4x4tjLM7HUZcfKxdPdXm7XYnMNE3/YJqmvz1N09+apunTt2m/\nZ5qmr07T9Ctv/3/b2/RpmqYfn6bpa9M0/dI0TX/oiB0AgFcqNfRcWT2OGD+HOD9HGud4aBl9juiR\n+Tfnef6eeZ4/efv7R0MIPz/P8xdDCD//9ncIIfxgCOGLb/++HEL4iQPWDQAvl2uYxFxp7ZfGci3G\npWn0UZfPQZzbPGJo2Q+HEH767fVPhxD+eDT9L8/v/M0Qwu+epunbH7B+AHio3NXTeFruf1db++R+\ndrkU43Qa7dTl52ipy/FrcW6zN5GZQwj/wzRNvzhN05ffpn1hnuffeHv9D0MIX3h7/R0hhF+Plv36\n2zQAAIAuH+1c/t+Y5/kb0zT9iyGEr07T9L/Gb87zPE/T1JVOviVEXw4hhN/3+37fzs0DAACuaFeP\nzDzP33j7/7dCCH8thPC9IYTfXIaMvf3/W2+zfyOE8F3R4t/5Ni0t8yfnef5knudPPv744z2bBwAA\nXNTmRGaapm+dpulfWF6HEL4/hPB3QghfCSF86W22L4UQ/vrb66+EEP7026+XfV8I4R9HQ9AAAACa\n7Rla9oUQwl97+0WFj0II/808z//9NE2/EEL4mWma/mwI4ddCCH/ibf6fDSH8UAjhayGE3wkh/Jkd\n6wYAAG5scyIzz/OvhhD+lcz0/zOE8Ecz0+cQwo9sXd8o/FQeAAAjGu2X0h7x88sAAAAPtfdXy0iM\nlskCAMCI9MgAAADDkcgAAADDkcgAAADDkcgAAADDkcgAAADD8atlADxNz7O25nl+b/69f/cYed3P\nXNeZ1117/+h192yb/bTuR67rbiQyADxN7xdtOv/ev++y7meu68zrrr1/9Lp7ts1+Wvej1nU3hpYB\nAADD0SPzBFu73QEAoNXdemgkMgeTtAAA8Ap726GjJUKGlgEAAMPRI3Ow0TJZAAAYkR4ZAABgOBIZ\nAABgOBIZAABgOBIZAABgOBIZAABgOBIZAABgOBIZuIBpmt57CNba38u09L3S63SZ0vrX1tm6zaX3\n1h70tbZ9revf8ndt2tp+xPudKyu3X2tltW5zTlx2yzbVtqXnc8vVgdZ61FK/e7apZ13p+7ntqL3f\nW+9q5ZW2q7atreeAR9W5te1r2a7W9Ze2J9230t+l+de2H3gMiQxc0PI8o+WLNH2+0TRN703LPf+o\n9EykR305157B1PJ8plqjf63MXJxa3++JR67M3uVay9q7zfM8r85fql+17S6VsXUb4nla7HnW17Ls\nkc8Le9azx3Lx6znua+XuOXZbj9utcWo5j7XGpqf8XL2V2MDxJDJwc62NkEd+Ca81iB9lbX2P2J5a\nTHvX96jPJ92OZ30uteS6ZxviWGxJOI/Usv6ehG9LotG7zj2J6ZHLhZD/LNP3eo7jVz20ei3hA7aR\nyMCN7B3u8IhG4VFlPbsHCUpqx9neRv2e+vyI47Z23LX2/K1N3zKEq2dIW2uv0dbPzjkIHkciAzfS\nOwxn8ciriUeUmzY0aldxz+DInpRH9po94nPvvUcl3Ybe5R+9fTm14yx3D8Za4rOnAb1n+dL2xOXX\n5utNEHI9lKUhni29MK1J0pp4+7YOCT3jeQiuQCIDN/bsq7trV6nvdOXy7PdZxAnEsz6X3E3ke7fh\nGcMWt9zMnja0exrmZ+mVeaSWixFHxeRIZ9kOuAuJDFxQy5XOrV+4r7iyWNvWUq9By/6txWnt/fi9\nFnvviekpq2Wba8Nyau+X1tliaXyu3Thf2oZ0+aO2q6f83HauvX/ksKRaWY8Y0ra3rFId23vctm5T\nbf4jh6RKYuD5Pnr1BgD7lH4Vp+VXc0pDLGpXwtd+hac2f0sZa/uTU2sULY3SXKM8vSKeazS3vr82\nT9wwz5Wb2+fSvrWW1bLNPUpxzG1/br9aGpu9SXZp3bW/W7dpbT2Ltc8wbjTX6mHLMdhyXOemtZTd\nMj233aV1lKT1t7StreerLTGpDS/ruaCx5ZwKHEciA4NrGZKyp5zSlf49Hnl1uHU/tsyzp4zWHoS9\n29nzee3d1j3l1ObrqR89696bxO15v2W+I2O797jYsr/P+Lxr82+NyVHr3zofsJ2hZQAAwHAkMgAA\nwHAkMgAAwHAkMgAAwHAkMgAAwHAkMgCcjmdyALDGzy8/gS9kgH7OnQB97vaz3xKZJ7hbpQIAgEcz\ntAwAABiORAYAABiORAYAABiORAYAABiORAYAABiORAYAABiORAYAABiORAYAABiOB2I+0TRNYZ7n\nz/5fpsV6H565VtYyLX0dL59bb7ytLWWVyll7L/f+1r/Tabn5c/O2bFM6PS5jrfza+7XPpDRPad8A\nAO5Ej8yTpA3gaZo+a5BubYTWkqBcmT3r6V3+yIb0WqKVrqsl2Uhfb93e3Oe1FquWbU+3ubStexNf\nAICrkMi80Fri0Sq9gt+acMTL5RrSa8v3vNeqtYehZV2tvS+tZezdnj1qyZpkBgC4I4nMSbQ2mGNp\nUrK3jC22rrdU1hH2xiUeuvVoa0Pyaj0wR8YeAGA0EpkTqTVmS43WtWFVvevr9aghZSVr8SiVdcYG\n/9o2lXrXRtg3AIBHk8icQO2G/bXlQlgfTlZaNk0GtjaIa/dwbC2rVE7LcLwtcVmWSf+vbcteWz+z\nZVlDygCAO5PIvFjccM4NaVoarI9ouB5d7pYkbM2WBK9XbvjW3rikiVCprNb9e0ZiBQAwEj+//CTL\nz+iWfop3q7V7KOLXpUZzy3yl7V77Fa21BnhLAz2NXWn5+O/azySvvZ/+9HQ8rbTN8S+MpdvQ8pnU\n9qW0jfF0AIC7kcg8UcvP9u4pr/X91u3onb5l3tayXrEtW9fZ+8tuR+4DAMBdGFoGAAAMRyIDAAAM\nRyIDAAAMRyIDAAAMRyIDAAAMRyIDAAAMRyIDAAAMRyIDAAAMxwMxX6D0RPfcww7TeUvlxfY8NHFt\nW7aso1bmFi0xOVppH7bGBACAffTIPMk0TZ/9S6eH8K4RHL+Xm7ckbkA/sjG9JXk52qPK3UryAgDw\nGhKZJ5nnuXg1v7V35hly29kr10N09P6cLaEBAOC5DC27iWU4Vvx/CKHrdS4RW6blEou1deXmWZQS\nn9y8ufWn+5pbX23bS9uyNpTs1YkoAMBd6JG5gdJwtkeU3TPMLU2O1npuWrY7t3wpYUmTkpZtj+db\n2x69RgAAjyORGUjpPpue5Y9crrVB37pM67619ALVynxGgiGJAQB4LInMyRw5JKl0r0quV6HWk7FW\n/tZtTpdLt61ne9buM8r1vjxi+NezfngBAODuJDJPVBqG1fPrZK0N8LUej5Z1Lr0bvT//vDa9Vk6p\nV2ZtHWv38OTWs5dEBQDgddzs/0SlXo+lYZ3rodhadtozsNZ7kktacsvl3k9vwE9vps9tW+nm/NI2\nrsWmtK0tCU7L69o2tuwfAADHksicwDOu7K8lB2v3wayV25uEbRnKtqa1zC3rKe1nzMMxAQCeRyJz\nY3oNAAAYlUTmpvQYHE9MAQCex83+AADAcCQyAADAcCQyAADAcCQyAADAcCQyAADAcCQyAADAcPz8\n8gWUHsQYP4W+54GXuafX56Ydsa25bfQzxgAArNEjcwG5hCP33vJ3a6LwiCfVl8rxcE4AAHrokbmg\naZp2Jx5LD0mprFLPSq6clvXk5JIyPTgAAISgR+ZSaj0zsd7ej3T+NIFIk52exKKUjMTTS4lUvH4A\nAO5Fj8zF1Ho44nlipSFkcVmPShZKSc/auvXCAADcmx4Zql6dMBwxTA4AgOuRyFxQb8N/Gb5V6x15\ntpZfXAMA4L4kMheQG4JVul9muYG/p6y0vPTelJ4b9tNtKS2Tu/+mZz8AALg298hcwFpPSk+PSm3e\n2g39a3/3lr+2PgAA7k2PDAAAMByJDAAAMByJDAAAMByJDAAAMByJDAAAMByJDAAAMByJDAAAMByJ\nDAAAMBwPxHyi+En08QMel+m5hz7GT7ZvKTe29SGSpe1Jp5e2rbY/Z1D6HNJ5erd/rdwj4vKq2Ob2\nrSWOPeXXPouedWz57J5ZXsv6Qlg//nrL2vN5HflZA8BR9Mg8ydIYShuB8fS4sTBNUzFBSS1lLuU8\nqqHRWu7ZGzqPilGtzKMSkFfENq6j8frjevdqrcfKCErx3Brn9HNquTCSxvOR5xUA2Eoi8wK5K9qL\nuMG7p+HQ0qje6wwNmz37UrrifYQrNayf4YheqiPKKpXt8wSA85HIXFB6RbXWGIvnXXu/dx2lafH0\nteXWXpe0rGdN67alcglSLWmq7WP8L7d/LdtYKqO0v+nrLWqfeW4fWuvr2vu5smplt8SlNkywtl2l\neLbWzbXP7cjPKy6ndqEFAM5EInNBvVeka/P3DnPJDT1qXbbWMNtylX3v0KdS8tHawOtJttL1pcMF\nc9uWG6aYW2du3pZtPSKZaUkS9tSxtffSe9Fy96aVrM1film6TOkzKW1zPF1SAQBlbvYfSKnR27ps\nqUFcem/r9h1R1hmGrS1aGp25ZZZG7NH3PNTW2eKoz3vNo37U4Ijt74lVafnS5xtPe2Sc42P3yOM3\nvaBwpmMRAGJ6ZF6olFjU5m9ttMQ/HrB2T85RicfZGjyPuIr9iOE8e8tqHfr0rCv8td6d1gTvyF+T\nyy3Xsv/x8VZLVuJ9e9S9aY+85y29QHLGYxkAciQyTxInFq2Nqt4hTLV7Dtbu0aiN029p1KwNTept\nbKX7UVs+N3xn65Ci0v0UacO1FpdawzYX96Ws2j0Va9uaK29t/lguPi2/bpWut7Z/W/cr937uWCqV\nXfucSkO/tmxbqZy1+lLziGQ5/bzSurcwrA2AszO07Ilyw01qw5Z6hjH1rLdnqFRtm0r3dLTM1/p6\ny7ylbWqdf+v6tpbfu87W/WpZruX9o4fG5ZLMLXWpVGZPLFq2sbaO1u1u2da18lu2q6a1bm4pGwBe\nQSIDPMXW3j4+pJcEAAwtA56kdWge7fb0ED5ifQDwTHpkgKfRED6GOAKAHhkAAGBAEhkAAGA4EhkA\nAGA4EhkAAGA4EhkAAGA4EpkTKD1d/FXllMoGAICzkMi8WPxk8zhZ6E1KSuWU5gUAgJFJZF6ollD0\nPCfiGYmJ51YAAHAmHoj5YkckCEsvTNwrE1sSndK64kQo16OzTIufzJ5uf24aAAA8ih6Zi4gTinSI\nWi7ZiN+Pl0/LzCVFueml+QEA4BEkMgNZkpTSULJScrE2hK3lvpqW9bn3BgCAZ5HIDGRJOmoJRNr7\nEvfI5MRD0rZIe3QkMwAAPINE5sUe1fDvSUx6k5jS/TCGlQEA8Cxu9n+htBcjTQS2JhhpcrH0uKy9\nX1vvMi3e5tL9MwAA8GgSmRPY2/hPk4yj368tszYNAAAewdAyAABgOBIZAABgOBIZAABgOBIZAABg\nOBIZAABgOBIZAABgOBIZAABgOBIZAABgOB6IeRHTNH32On0w5TRNxYdVxsuVlgfOLz2Wl+O4dm7Y\ns56znSda9nNtntK5cu38urbeXNm55Uqf4dnUvlOW9xc9+9by+fQum1vm6GPiaHti1XscxPO1HNs9\n8Rwpzj3njJ5jPjfPluNny/S70CNzAfHBMs9zNjkpiSt9vHxPGcDrpcdy+vrqX3DL+SuE/AWapfFQ\nOk+unfNyy6VltoqXy61nZLl9S7+jSsvF86RxrsWs9F48fSlvz/flM7U2kNN9a62Lab3NxSq33rV1\nbtmWV2he76ZfAAAgAElEQVTZvpbjtCdWtfnX1tk7/U4kMhdx50oMvNPTy5DOM7Ijrkj29Fr3vJ+b\np7SuqyadRzS0ehPFUjLbW9YrtNSDrUlwLS61aS3z1Or12c4xvXUgvsi79fPZst5aotT6WV6dRIaq\n9CpWevDc8aCBs6sdl7ljOl1mOc5HOdZbr0CnV4sXvfvW05vTkkhezZZe/fgKdxyz0nfPWjnUGXmx\nzZZE5OiLK0clSVchkeEz8Ylt+dJPD4y1v4HXqh2j6dXE3NXF2rCsEfSMP2+ZvzYuvnU4W8s21/4e\nSUvv35ar4WcfCvYIPRckWpffMhTyDrbUq63HN8eSyNxQ7mprCB+e4NbGygLnteeK66iNnVrDIjeW\nP3e1v9b4K1lLnNbK7i3zzLaO2U+HffmOeac0hGxteNOo9ecVHhkrn8PjSWQuouek39pIKTUKfNHA\nuR355TnKcd5zpT/tUWlpGC7r6NFTdryOu55jS3HqiUPtPpiR4tpaD47Yl5b7bbbek3NVzzhO1y4k\nl278vxuJzAU8suKuXU0Ezqt083/8f+m90r0KZ5b2Nu+5z6e0bKlHJze9Vnb8unQ/yCiNktbev9y9\nSWufT+uPMOSG/uWMENNcPcjFeEud3Hs/WCq996y0H2eLe+vxW5onnnfr/Vy5bYnLCUGPWwvPkbmI\nuFL33sey9UBxIMF5rV1Bzb1uORec9bgv7W/p6mVLfGoNilos1xrkLa/PLBeLXJzXYt76+azV1aNe\nn8VaXS7N11In98TkiM/kLI6KVa7Mlnqf/r318zl7nJ9BjwxdRrgqCxDCvivBW5c949XnR3tFrO72\nXfSKuhzC/RrHr6iTdzxnHEkiQzcHHTCCPecpDb92r4jV3eIsVs/hnDEeQ8vo4oADAOAM9MgAAADD\nkcgAAADDWU1kpmn6qWmafmuapr8TTfs90zR9dZqmX3n7/9vepk/TNP34NE1fm6bpl6Zp+kPRMl96\nm/9Xpmn60mN2BwAAuIOWHpm/FEL4gWTaj4YQfn6e5y+GEH7+7e8QQvjBEMIX3/59OYTwEyG8S3xC\nCD8WQvjDIYTvDSH82JL8AAAA9FpNZOZ5/hshhN9OJv9wCOGn317/dAjhj0fT//L8zt8MIfzuaZq+\nPYTwx0IIX53n+bfnef5HIYSvhg+TIwAAgCZb75H5wjzPv/H2+h+GEL7w9vo7Qgi/Hs339bdppekA\n7PCq52nc7TkesT3Pi2hZtvfJ4KNZ27fc+z2xa1327nHeulwtnkduxwj27Nta/euN55XjXLP7Zv/5\n3e/xHvabvNM0fXmapk+nafr0m9/85lHFAgwr/oKKv/zu+sX1KK0N7Phn6JfPo6VRMs9zcdl0vpbt\nuaJl/9OY5F6ny4UQsssucS9Nv6La897SOtsS37TcOJ5LGbkY56bfwVqMa/WvVpd7pt/F1kTmN9+G\njIW3/3/rbfo3QgjfFc33nW/TStM/MM/zT87z/Mk8z598/PHHGzcP4BrSBkn6xfeKhtgdH4pbayAs\nDZJSoyQXr7ghk/t8rxrftbqTe68W3y3rSqffqfGXq3et55S1YyA331XrcQj1uhzHOBebo+Jyp7pb\nsjWR+UoIYfnlsS+FEP56NP1Pv/162feFEP7x2xC0nwshfP80Td/2dpP/979NA6Cg9CWVaxSn89au\ntpZ6eNbWf+WhOFuGeLS+X5pnLfZXbgTW9NaxnvmvWn9bpY3q3jqWO/fk3D3OsdKFjNK8rWUs7nqe\nWHy0NsM0TX8lhPBHQgi/d5qmr4d3vz72F0MIPzNN058NIfxaCOFPvM3+syGEHwohfC2E8DshhD8T\nQgjzPP/2NE1/IYTwC2/z/fl5ntMfEADgTeuVu9KQjpbhSel8tdd3GPK0Nsxj+TvXg1JrrOTmiafd\nuYegpKUnpTZ/LgnPuWKsH5EE1+KpgV2WO2/Wzhnx+y1l05DIzPP8pwpv/dHMvHMI4UcK5fxUCOGn\nurYOgKq1JCaXfNQafWlidJckpkdPQ3Ftvty49ruOdY/lkrujGsZnGJ75ao/s8VN/y+5Y1x5t983+\nADzf2r0zOS09DvG8rrS+88iG752GkLU2bnP3FRxxlfoucd6qty7eeZhZ63DSPXXuyOFnVyaRATih\nUg9I670cufthSutpvbn3ig2SEMr3r/S8v9ZjtVbeXZSG0NVe55ZZS1hahurd5XPIHcctDd5SL+6W\nZPGKDew0Jlvv1doazyvGdIvVoWUAvMYyRCPuNaklHfH88ZCwWkM81yNTmpaWfwW1RnMI+c8gXbbW\n2FhrDJamXSW+IazHOJ2vdqW/dE9Bbdm057L1/rPRtMS5JykvraMlnleNc09dLp1L4r9TW+J5xTj3\nkMgAnFjLFc6112tltHy5rm3PqFpuKt9zQ27PsleL7WLrsMfS9FIjcU+ZV/CKurxl+shq+9Rynjz6\nWLhijHtJZABu6i5Da3rtaRxoWLTbGisxbqcuP4c4v45EBuCGfHkCMDo3+wMAAMORyAAAAMORyAAA\nAMORyAAAAMORyAAAAMORyAAAAMPx88sXUnu6a8vTenO2/ERrz1Nmc+v1s7CwzZanzx+xDgB4BT0y\nN7D20Lu4YRL/e4b4yeO5p4wD+60dz445AEYkkbm4tZ6YnnLSv3ONn1KDqLWhlG6rBha0az3W4+Oq\n55h1PAJwJhIZQgj5BlDaQ7IkL0tyNM/zBw2iUiKSzluSKy9OmloaYHB3a8lJfFy1HLOGkwFwRhKZ\nC9vbG5M2htJhZ2tJTPxeLhHJrSsuv1YekBcfn7Xjcu2eubVjFgBezc3+F1XqwUh7RuJGT++wlNZe\nlpZyW3+gIF6nq8PwGIZ4AjACPTIXlbtxP72xfk8iUEo81rQ2iFp/oAD40JFJvmMNgLOSyPDBUJTl\ndU06b2m4WTxvbTx+bT2l7QXqaj2a6fGYHrvpMVv6gQ/2cQ/gc6TfR+l09kvrsuGpj+Gc8T5Dyy6k\n1sBfa/znGjwt7/Wso2eZ3u0F3rd2bJWO8doPf3C8ns+B7Ur3XorzcdTl5xDn90lkGEbu3h4AAO7J\n0DKGsfZrZgAA3IdEhqFIYgAACEEiAwAADEgiAwAADEciAwAADEciAwAADEciAwAADEciAzCwVz3N\n+a5PkQbgPCQyACc2TdMHScPy9yuTGD+FDsCrSWQATmpJVGpJg4QCgLv66NUbAECfNHnJJTxxb808\nzx/03izzpvOVlk+nAcCr6ZEBOKGW3phlvlxiM8/ze9OX12myks7XUyYAvJIeGYABxYlO3FMSJyHp\n60WpRyd+3VIOALySHhmAEyr1fJQSktzwsZYyS7037ssB4OwkMgAnVuptqc0X/72nB+Vsv5Z2RfGv\n0uV6xjhGHGNxfoy0LjtfPIZzxvskMgAnFQ/nSpOYNKGJe1HieXP3xqTzlH4YIHc/Ta4s9hHP5xHr\nx8mdk3gMsf2ce2QATqzlC6uU4LQuW/pFs61l0m7PZ0c7cX6O3MUOMT6Wuvw+iQzADZV6XgBgFBIZ\ngJuSwAAwMvfIAAAAw5HIAAAAw5HIAAAAw5HIAAAAw5HIAAAAw5HIAAAAw/HzyxexPHW79LTuEMo/\ntZrOtzb/2aRPPF+mhfDhw/5G2SfYIvdcmKOfFePZMwCchR6ZC0gb6unfaw2O+Em88fylBOeMakmb\nBhd3t3YMjHSsA8BCInMRuYbKngZ8btlcY6fUAEqntyw7TVPTcun7W/dza+OtdZ97psERWo+FuA7u\nrc8A8CoSGVblhmktSUduWtpIit+vlbf0BqXTerdzy/6ky5cacek+l/Yx3v40JrlpcKS15CSugy3D\nMg0nA+CMJDI0yTW800ZNOkQtnp5rLG3ptUntbVi1JDMt99ik+xg3EOMETQLDo5WOy7X5YuopACNw\ns/8NpFddt9z8nmsc7RnWVSqv1nORS4biZGFvwysuI30dT+sZvtPaqISj7elFUU8BGIEemYuoDSVJ\nb95Pb+pvKS83lOrIX0GKh5bFetdxxFXkWg/N3vtxWu5NgL2OTETUUwDOSiJzAaUhTem9KyWle1xK\nw8Hi8nMN9Bbxunp/Fnp5ryXpWbtXIC1n7dfOWvc5jVH6a3BHJoJQUur5DKHeU5s7Pg03e4zaPXYc\np/R9KM7HSevy1vYBdc4Z7zO07CLi4U/ptNZle95vHXef25618tL5tq6/9/WWefeUDY+0Vl/V23Po\nPd+wTen7RJyPoy4/hzi/T48MAAAwHIkMAAAwHIkMAAAwHIkMAAAwHIkMAAAwHIkMAAAwHIkMAAAw\nHIkMAAAwHIkMwMBe9TTnuz5FGoDzkMgAnNg0TR8kDcvfr0xi7voUaQDOQyIDcFJLolJLGiQUANzV\nR6/eAAD6pMlLLuGJe2vmef6g92aZN52vtHw6DQBeTY8MwAm19MYs8+USm3me35u+vE6TlXS+njIB\n4JUkMgADS3tb4iQkfR0vE8stHydSpXIA4JUkMgAnVOr5iG/0T3tc1pKMXJmlnpZa74teGQDOQCID\ncGKl3pbafPHfe3pQzvZraVcU/ypd+llznDjG4vwYaV12vngM54z3SWQATioezpXrgUnnzQ0py90b\nk85T+mGA3P00ubLYRzyfR6wfJ3dO4jHE9nN+tQzgxFq+sEoJTuuypV8021om7fZ8drQT5+fIXewQ\n42Opy++TyADcUKnnBQBGIZEBuCkJDAAjc48MAAAwHIkMAAAwHIkMAAAwHIkMAAAwHIkMAAAwHIkM\nAAAwHInMRSzPg4gfbLc8DXz5V1s2fX9tmaOl2/rIdefKTtf57P2HIzzjWHZsfC4+767FJPe5pNPj\ncsT4cy0xKcVz+b9l+p21xKT0HV36fNTlD22ty6XpzhkSmUuIK2/6kLvlX03p/Wc/Y6J1e2taD+S1\nJ5nDlazV77t+AR6lN77TNL33BPT0HM7narHKzbP8HSu9J9bv9MQk/Y4ufT4tn9vd7KnLtTp+93rs\ngZgX8eiKnDtolgOrlEil8+7Z1rUyc9NrCVrvSbVl/WnZa7GplXdU3LiXpY6lX3qxUp2Ml2mt76zH\nJXeebLEs47jvEx8DqbXvBj63lhyWpnGcWpshV8fves7QI3NxPV3npWFd6cm/pTcjd8Wm5eAqrb+0\nfG56bV257vCWbYrLLO1/vM6116WrWrVY+tJgi1o9S68Q5uYpTaN8nHMs5z6uQl0+nkTm4noaH7Wh\nXbnGek3uak7POM50PUePA93a6Kg1XNZ6aHrXcfdxr2wT159a3akdA8Zdtyn1YuXeZ5vW+sx2uRir\nt8dTlx/D0LIbKQ0FO1pueEtPMlUbfrVHrlHxiIZG7kr21pOWLxNeoSVJ53O1YzztBXZM99Mr/Xhr\nw8g4hrp8PD0yF9HTy1HreektvzR9T0Mo1yh4xNXhoxoUpauyvY2W3D5uGQoHvRcQUnpjtkuvasfn\n2t7zgaTnc2tDnOP5DNPdrnRvzNoQ8jXq8udydbmnR7dUx+96ztAjcwHpjV89N4rnGt5pI6ZUfumG\ns9INaKUTYu5m49r602VK01pvVKwlH2u9WPF7uflakpJ4HWkvlq5+jlSry/GXY3q87elVvLotcSl9\nDuKc19KgWxva67xa1xKPWjzjeWrT724t2Wipyy3T70QicxFbr5a0Llcqa+/yrfOv/b1m7za1zrtn\nO/de8YLYnmNWXWxTilPL8Niez+futtbZ1mXpG/7duqw4f6jlnNEbz7vH2dAyADjQ3RsWz3D3q9DP\noi4/hzhvJ5EBAIai4QeEIJEBAAAGJJEBAACGI5EBAACGI5EBAACGI5EBAACGI5EBAACG44GYAANI\nn5uRe8r2s7flbj+BW9vvlvfS99em3y2+IfTHKrdsT4xr5V1ZqY611L0tcb5jjEPoi9Xaclum34Ee\nGYATm6YpTNMU5nn+7N8ZnGU7nqmUpMSfT2m5XMNjbfodH/q4xCNt+MWxysWlFrd0etzou2M9LsWq\npe7l5lGX85b9X14vcnU8t1zr53P3OEtkAE6q5SrbHRtirxI3TJa/Q2j7DNYaGHFCxIdqV7HXGt05\npSvkd5BrXLfUvdb6udTlu4tj1Xpc99Zl5wyJDMCp5b6kcg25tFFSeh3PG/+fm682D++rNUDShEfj\no09L3PY2FO+kpRexp6y9n8lVlS5OrNXBu8etl0QG4IR6GlwtV5drw2lKydLyJXzn8dcla2PfF3cd\nvrRVbdjYnnJa7pW5i9JQu0XpM1ibh/fVhkIecU7wGbwjkQEYUKnXJYT+K/+5stJla1/Kd3DEftfK\n6L1qe2W5+2OW6S1D9Pasj/3E83N7YrF2Uap1+tVJZABOaO3XbNJ5Whp5rTejr/Ui3LWhsrbfW97v\nSW5o0/tLT3xu66+WxdNz89+5Lu/Z995he3eMs0QG4MTi+1pqDYL0F3JKw0ZK5fdM0wAs9xqU7kmq\n9W6Vfu3pbtauNJfiHM+X/iJUGuMl4b/jcMnSuaQ01LT2AwtrcY7XeTdpnNP3cvPnpq3d3F86B92N\n58gAnFRrr0jLr+PUGsu1BsvadtxFLS5br46uNQ7vZq3urcW55d6v2vSrazmf1OJdq5/q8uf29Gav\n1WVx/pAeGQA4yJ0bFM9y56vPz3TH3pRXUJf30SMDcEN+jYxRqa/PIc6MQCIDcFMaKgCMzNAyAABg\nOBIZAABgOBIZAABgOBIZAABgOBIZAABgOBIZAABgOBKZi1ieB5E+wGqaps/+1ZZ9xIOv9pQZb3fL\n9uXmaVl/a/kwgtJxcGT9drywplYPt57L15bPfQfG01qmj6QUk1JboLRsy/St62zZljOr7e/avq0t\nu/b55Mou1fHR47yXROYC4sobP+QunlZ7XkTrsyR6D5IjnlERb3tt/bl1ra1/eTr0WnxgdC3HAhyl\ndD5e/m2pb7Vz9XIuj/8ubU/6fTmi+Lsrnb5Yi3O6fOv3YWm5dJ2l6aMpxaMWo1IsS59bbtn479r0\ntW25A4nMRZRO7vH/rXJXq3L/r12VKV2FOOJqWM9Vjdz8V7giB6mWpL92LJTmiafBXj0Nr95zde0Y\nWKaN3vCLtz/dl9aLFqX4rPV4rU27klq7qjat9Bn01ru1cnLrvfpnkiORubDW3oza8unr3LRcMrNW\nZnxlYm2Z0pdP677lroLE+zP6lxrU1K4IpldNc/OUpkGvlgtQqVxd5HNbRkrkvjv3theu6hEXcMT3\nWBKZGzi68VG7onN0YyeXxGzpaTKOlLuIGyO9wzEXjhceYc/3gyS6bEtsjuo1uLq9bZp0SNhS5vIe\n+3306g3g+Y4YW/msk93SY5OeDI7qogU+VBt7D69y16EzJblGMo+xpe7VPh91+Th6ZC6iZ/zqETe4\n9wwn22ttCFvL+p0wuJPcUNAeemOep9T7dYfYtwzbSWOydjW7NgzySlfCS43ktXtftt4zu+UHdbbO\ne0a99Sr9fNK4p3W59LnVftwid8Fp9DhvoUfmAuJei+XvxdrNjS3JQXrA5dYXnyTTv0tavqDSe2m2\nrL9lfriD9Cpg6T6Y9IvV1UNa5c7frTdDr91oXmq4lepnPD1O7kvfl6PIfb/mjt21ONduGs+pxTNd\ntnauGUVp+3NxyC1XO4f29tT0Tr8TicxFbL1asvWKSmnMZ0u5a+tsGbvbu/6e7YMr6BkD33J8OGYe\no3ReGzXePXWnpXHXWo/31PfR9H6/rjW89/asXPV+m63tmN549CQ5vdtyB4aWAQAvsXf4I+v2jDy4\neyO5x55YifN2EhkAYCgafu3EiiuTyAAAAMORyAAAAMORyAAAAMORyAAAAMORyAAAAMORyAAAAMPx\nQEyAAeSevv2qp5OP/FR0xtTywMBcvSwtN/pT5/fqidWeZe9+rtga51LceqffgR4ZgBObpumzB9ot\n/87gLNvB9cX1v2WeXNIfT48bfXetx7mGcEsscnEufT61z+QuajFZ/k6V4tY7/S4kMgAn1XKV7a4N\nMe4rbayVGm+1xnnpCvldLfFo6YlZs1x8oT1BjOc/YvqdSGQATiz3JZi7ypdeoSu9jueN/8/NV5sH\nnqG1zrU2FtXhd3ob2IuenhwXWT609JrUehl743n3OEtkAE6op8HVcnW5Npym9GW6fNneefw1r7X1\nfotar43emLJSYtLaC0bd1gSyVBYSGYAhlXpdQvi8odYz7j19nS5bG9MNj9Qz9n9L/ZSgv3NUI1s8\n38klf/EQvrW6aphZG4kMwAmt/ZpNOk/LF2PpSmvaS7N2E7SGCq/SUvcMwamr3WDeo/TLWUeUzTuG\nma2TyACcWHxfS61BEL+Xu8dlbR25dZam3fXK3yOU4irGn8sl22uN8fRYSK+Erx1Pd5LeB5erj2ns\nc3FO50vLuKNSPNLzdao2xC/3wwx3rsueIwNwUq29IqXXtbJKX6Q9N5+yX+/neEdrsSj94par1nlb\n41T7ZbOeee+iFue1mLfGU5z1yAAAA7nz1ednuntvyrOoy/vokQG4Ib9GxqjU1+cQZ0YgkQG4KQ0V\nAEa2OrRsmqafmqbpt6Zp+jvRtP94mqZ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ykcndFePcUh9rw/da4nHnBvait4Gb3jPU6i7x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\nAADQHYEMAADQnf8PSY0cyTExibcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638d065d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waste_copy = img_page4.copy()\n",
    "for index, row in label_stats[(label_stats.width > 1200) & (label_stats.top > 0)].iterrows():\n",
    "    cv2.line(waste_copy, (row['left'], row['top']), (row['left'] + row['width'] + 50, row['top']), (0,255,0), 5)\n",
    "plot_page(waste_copy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the same process remove lines that are in the range of 100 points vertically   \n",
    "and join the left most and right most points of two independent lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "      <th>pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "      <td>2307</td>\n",
       "      <td>607</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>143</td>\n",
       "      <td>974</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>974</td>\n",
       "      <td>2307</td>\n",
       "      <td>1001</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>148</td>\n",
       "      <td>1162</td>\n",
       "      <td>2163</td>\n",
       "      <td>27</td>\n",
       "      <td>58401</td>\n",
       "      <td>1162</td>\n",
       "      <td>2311</td>\n",
       "      <td>1189</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>135</td>\n",
       "      <td>2957</td>\n",
       "      <td>2157</td>\n",
       "      <td>86</td>\n",
       "      <td>81564</td>\n",
       "      <td>2957</td>\n",
       "      <td>2292</td>\n",
       "      <td>3043</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom  pos\n",
       "18    143   580   2164      27  58428     580   2307     607   18\n",
       "41    143   974   2164      27  58428     974   2307    1001   41\n",
       "47    148  1162   2163      27  58401    1162   2311    1189   47\n",
       "137   135  2957   2157      86  81564    2957   2292    3043  137"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "possible_boundary_lines = page2_label_stats[(page2_label_stats.width > 1200) & (page2_label_stats.top > 0)]\n",
    "possible_boundary_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:1]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:2]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "      <th>pos</th>\n",
       "      <th>dist_from_next_line</th>\n",
       "      <th>dist_from_prev_line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "      <td>2307</td>\n",
       "      <td>607</td>\n",
       "      <td>18</td>\n",
       "      <td>394.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>143</td>\n",
       "      <td>974</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>974</td>\n",
       "      <td>2307</td>\n",
       "      <td>1001</td>\n",
       "      <td>41</td>\n",
       "      <td>188.0</td>\n",
       "      <td>394.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>148</td>\n",
       "      <td>1162</td>\n",
       "      <td>2163</td>\n",
       "      <td>27</td>\n",
       "      <td>58401</td>\n",
       "      <td>1162</td>\n",
       "      <td>2311</td>\n",
       "      <td>1189</td>\n",
       "      <td>47</td>\n",
       "      <td>1795.0</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>135</td>\n",
       "      <td>2957</td>\n",
       "      <td>2157</td>\n",
       "      <td>86</td>\n",
       "      <td>81564</td>\n",
       "      <td>2957</td>\n",
       "      <td>2292</td>\n",
       "      <td>3043</td>\n",
       "      <td>137</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1795.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom  pos  \\\n",
       "18    143   580   2164      27  58428     580   2307     607   18   \n",
       "41    143   974   2164      27  58428     974   2307    1001   41   \n",
       "47    148  1162   2163      27  58401    1162   2311    1189   47   \n",
       "137   135  2957   2157      86  81564    2957   2292    3043  137   \n",
       "\n",
       "     dist_from_next_line  dist_from_prev_line  \n",
       "18                 394.0                  NaN  \n",
       "41                 188.0                394.0  \n",
       "47                1795.0                188.0  \n",
       "137                  NaN               1795.0  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "possible_boundary_lines['dist_from_next_line'] = possible_boundary_lines.top.shift(-1) - possible_boundary_lines.top\n",
    "possible_boundary_lines['dist_from_prev_line'] = possible_boundary_lines.top - possible_boundary_lines.top.shift(1)\n",
    "possible_boundary_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_possible_boundary_lines(label_stats):\n",
    "    possible_boundary_lines = label_stats[(label_stats.width > 1200) & (label_stats.top > 0)]\n",
    "    possible_boundary_lines['dist_from_next_line'] = possible_boundary_lines.top.shift(-1) - possible_boundary_lines.top\n",
    "    possible_boundary_lines['dist_from_prev_line'] = possible_boundary_lines.top - possible_boundary_lines.top.shift(1)\n",
    "    possible_boundary_lines.replace(pd.np.nan, pd.np.inf, inplace=True)\n",
    "    return possible_boundary_lines[(possible_boundary_lines.dist_from_next_line > 100) & (possible_boundary_lines.dist_from_prev_line > 100)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:3]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:4]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:5]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "      <th>pos</th>\n",
       "      <th>dist_from_next_line</th>\n",
       "      <th>dist_from_prev_line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>143</td>\n",
       "      <td>580</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>580</td>\n",
       "      <td>2307</td>\n",
       "      <td>607</td>\n",
       "      <td>18</td>\n",
       "      <td>394.000000</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>143</td>\n",
       "      <td>974</td>\n",
       "      <td>2164</td>\n",
       "      <td>27</td>\n",
       "      <td>58428</td>\n",
       "      <td>974</td>\n",
       "      <td>2307</td>\n",
       "      <td>1001</td>\n",
       "      <td>41</td>\n",
       "      <td>188.000000</td>\n",
       "      <td>394.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>148</td>\n",
       "      <td>1162</td>\n",
       "      <td>2163</td>\n",
       "      <td>27</td>\n",
       "      <td>58401</td>\n",
       "      <td>1162</td>\n",
       "      <td>2311</td>\n",
       "      <td>1189</td>\n",
       "      <td>47</td>\n",
       "      <td>1795.000000</td>\n",
       "      <td>188.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>135</td>\n",
       "      <td>2957</td>\n",
       "      <td>2157</td>\n",
       "      <td>86</td>\n",
       "      <td>81564</td>\n",
       "      <td>2957</td>\n",
       "      <td>2292</td>\n",
       "      <td>3043</td>\n",
       "      <td>137</td>\n",
       "      <td>inf</td>\n",
       "      <td>1795.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom  pos  \\\n",
       "18    143   580   2164      27  58428     580   2307     607   18   \n",
       "41    143   974   2164      27  58428     974   2307    1001   41   \n",
       "47    148  1162   2163      27  58401    1162   2311    1189   47   \n",
       "137   135  2957   2157      86  81564    2957   2292    3043  137   \n",
       "\n",
       "     dist_from_next_line  dist_from_prev_line  \n",
       "18            394.000000                  inf  \n",
       "41            188.000000           394.000000  \n",
       "47           1795.000000           188.000000  \n",
       "137                  inf          1795.000000  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_possible_boundary_lines(page2_label_stats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:3]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:4]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:5]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>area</th>\n",
       "      <th>top_str</th>\n",
       "      <th>right</th>\n",
       "      <th>bottom</th>\n",
       "      <th>dist_from_next_line</th>\n",
       "      <th>dist_from_prev_line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>153</td>\n",
       "      <td>237</td>\n",
       "      <td>2158</td>\n",
       "      <td>27</td>\n",
       "      <td>58266</td>\n",
       "      <td>237</td>\n",
       "      <td>2311</td>\n",
       "      <td>264</td>\n",
       "      <td>281.000000</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>140</td>\n",
       "      <td>2957</td>\n",
       "      <td>2152</td>\n",
       "      <td>86</td>\n",
       "      <td>80811</td>\n",
       "      <td>2957</td>\n",
       "      <td>2292</td>\n",
       "      <td>3043</td>\n",
       "      <td>inf</td>\n",
       "      <td>2399.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     left   top  width  height   area top_str  right  bottom  \\\n",
       "8     153   237   2158      27  58266     237   2311     264   \n",
       "165   140  2957   2152      86  80811    2957   2292    3043   \n",
       "\n",
       "     dist_from_next_line  dist_from_prev_line  \n",
       "8             281.000000                  inf  \n",
       "165                  inf          2399.000000  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_possible_boundary_lines(label_stats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def draw_table_bounding_box(img, label_stats):\n",
    "    possible_boundary_lines = get_possible_boundary_lines(label_stats).reset_index()\n",
    "    waste_copy = img.copy()\n",
    "    tables = []\n",
    "    if len(possible_boundary_lines) % 2 != 0:\n",
    "        raise \"Uneven Probable Bounding Lines\"\n",
    "    for index, row in enumerate(possible_boundary_lines.iterrows()):\n",
    "        if index % 2 != 0:\n",
    "            table_bounds = {}\n",
    "            top_bound = possible_boundary_lines.iloc[index - 1]\n",
    "            bottom_bound = possible_boundary_lines.iloc[index]\n",
    "            cv2.rectangle(waste_copy, (top_bound['left'], top_bound['top']), \n",
    "                          (bottom_bound['right'] + 50, bottom_bound['bottom']), (125,125,0), 5)\n",
    "            table_bounds['left'], table_bounds['top'] = top_bound['left'], top_bound['top']\n",
    "            table_bounds['right'], table_bounds['bottom'] = bottom_bound['right'] + 50, bottom_bound['bottom']\n",
    "            tables.append(table_bounds)\n",
    "    plot_page(waste_copy)\n",
    "    return tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:3]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:4]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:5]\n"
     ]
    },
    {
     "data": {
      "image/png": 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JX5e2v21zW3bUUL10OF7uvCmdb73lKQ25Kx3n6DHkyp4e0/q8BigRyACXdcS8mFaQs7Vc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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc638d065d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tables = draw_table_bounding_box(img_page2, page2_label_stats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:3]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:4]\n",
      "SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy [ipykernel_launcher.py:5]\n"
     ]
    },
    {
     "data": {
      "image/png": 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J2FPH1t5L70XL3ZtWsjZ/KWbpMqXPpLTN8XRJBQCUudl/IKVGb+uypQZx6b2t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\n8k7T9IVpmr46TdNXv/nNbx5VLMCw4i+o+Mvvrl9cj9LawI5/h