data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os, time\n",
    "import glob\n",
    "import pickle\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.patches as patches\n",
    "\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# German Traffic Sign Recognition Benchmark dataset\n",
    "training_path = \"./dataset/Final_Training/\"\n",
    "test_path = \"./dataset/Final_Test/\"\n",
    "\n",
    "train_file = training_path + \"train.p\"\n",
    "test_file = test_path + \"test.p\"\n",
    "\n",
    "train_list = []\n",
    "train_list = glob.glob(training_path + \"**/**/*.ppm\")\n",
    "train_label = glob.glob(training_path + \"**/**/*.csv\")\n",
    "\n",
    "test_list = []\n",
    "test_list = glob.glob(test_path + \"**/*.ppm\")\n",
    "test_label = glob.glob(test_path + \"*.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./dataset/Final_Training/Images/00000/00000_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00000_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00001_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00002_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00003_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00004_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00004.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00005.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00006.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00007.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00005_00029.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00000.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00001.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00002.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00003.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00004.ppm',\n",
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       " './dataset/Final_Training/Images/00000/00006_00008.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00009.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00010.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00011.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00012.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00013.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00014.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00015.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00016.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00017.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00018.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00019.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00020.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00021.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00022.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00023.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00024.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00025.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00026.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00027.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00028.ppm',\n",
       " './dataset/Final_Training/Images/00000/00006_00029.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00000_00002.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00001_00018.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00019.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00001_00021.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00022.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00001_00024.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00025.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00026.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00027.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00028.ppm',\n",
       " './dataset/Final_Training/Images/00001/00001_00029.ppm',\n",
       " './dataset/Final_Training/Images/00001/00002_00000.ppm',\n",
       " './dataset/Final_Training/Images/00001/00002_00001.ppm',\n",
       " './dataset/Final_Training/Images/00001/00002_00002.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00002_00020.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00002_00022.ppm',\n",
       " './dataset/Final_Training/Images/00001/00002_00023.ppm',\n",
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       " './dataset/Final_Training/Images/00001/00024_00028.ppm',\n",
       " './dataset/Final_Training/Images/00001/00024_00029.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00000.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00001.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00002.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00003.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00004.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00005.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00006.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00007.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00008.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00009.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00010.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00011.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00012.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00013.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00014.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00015.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00016.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00017.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00018.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00019.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00020.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00021.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00022.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00023.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00024.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00025.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00026.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00027.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00028.ppm',\n",
       " './dataset/Final_Training/Images/00001/00025_00029.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00000.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00001.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00002.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00003.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00004.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00005.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00006.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00007.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00008.ppm',\n",
       " './dataset/Final_Training/Images/00001/00026_00009.ppm',\n",
       " ...]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_list = sorted(train_list)\n",
    "train_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./dataset/Final_Test/Images/00000.ppm',\n",
       " './dataset/Final_Test/Images/00001.ppm',\n",
       " './dataset/Final_Test/Images/00002.ppm',\n",
       " './dataset/Final_Test/Images/00003.ppm',\n",
       " './dataset/Final_Test/Images/00004.ppm',\n",
       " './dataset/Final_Test/Images/00005.ppm',\n",
       " './dataset/Final_Test/Images/00006.ppm',\n",
       " './dataset/Final_Test/Images/00007.ppm',\n",
       " './dataset/Final_Test/Images/00008.ppm',\n",
       " './dataset/Final_Test/Images/00009.ppm',\n",
       " './dataset/Final_Test/Images/00010.ppm',\n",
       " './dataset/Final_Test/Images/00011.ppm',\n",
       " './dataset/Final_Test/Images/00012.ppm',\n",
       " './dataset/Final_Test/Images/00013.ppm',\n",
       " './dataset/Final_Test/Images/00014.ppm',\n",
       " './dataset/Final_Test/Images/00015.ppm',\n",
       " './dataset/Final_Test/Images/00016.ppm',\n",
       " './dataset/Final_Test/Images/00017.ppm',\n",
       " './dataset/Final_Test/Images/00018.ppm',\n",
       " './dataset/Final_Test/Images/00019.ppm',\n",
       " './dataset/Final_Test/Images/00020.ppm',\n",
       " './dataset/Final_Test/Images/00021.ppm',\n",
       " './dataset/Final_Test/Images/00022.ppm',\n",
       " './dataset/Final_Test/Images/00023.ppm',\n",
       " './dataset/Final_Test/Images/00024.ppm',\n",
       " './dataset/Final_Test/Images/00025.ppm',\n",
       " './dataset/Final_Test/Images/00026.ppm',\n",
       " './dataset/Final_Test/Images/00027.ppm',\n",
       " './dataset/Final_Test/Images/00028.ppm',\n",
       " './dataset/Final_Test/Images/00029.ppm',\n",
       " './dataset/Final_Test/Images/00030.ppm',\n",
       " './dataset/Final_Test/Images/00031.ppm',\n",
       " './dataset/Final_Test/Images/00032.ppm',\n",
       " './dataset/Final_Test/Images/00033.ppm',\n",
       " './dataset/Final_Test/Images/00034.ppm',\n",
       " './dataset/Final_Test/Images/00035.ppm',\n",
       " './dataset/Final_Test/Images/00036.ppm',\n",
       " './dataset/Final_Test/Images/00037.ppm',\n",
       " './dataset/Final_Test/Images/00038.ppm',\n",
       " './dataset/Final_Test/Images/00039.ppm',\n",
       " './dataset/Final_Test/Images/00040.ppm',\n",
       " './dataset/Final_Test/Images/00041.ppm',\n",
       " './dataset/Final_Test/Images/00042.ppm',\n",
       " './dataset/Final_Test/Images/00043.ppm',\n",
       " './dataset/Final_Test/Images/00044.ppm',\n",
       " './dataset/Final_Test/Images/00045.ppm',\n",
       " './dataset/Final_Test/Images/00046.ppm',\n",
       " './dataset/Final_Test/Images/00047.ppm',\n",
       " './dataset/Final_Test/Images/00048.ppm',\n",
       " './dataset/Final_Test/Images/00049.ppm',\n",
       " './dataset/Final_Test/Images/00050.ppm',\n",
       " './dataset/Final_Test/Images/00051.ppm',\n",
       " './dataset/Final_Test/Images/00052.ppm',\n",
       " './dataset/Final_Test/Images/00053.ppm',\n",
       " './dataset/Final_Test/Images/00054.ppm',\n",
       " './dataset/Final_Test/Images/00055.ppm',\n",
       " './dataset/Final_Test/Images/00056.ppm',\n",
       " './dataset/Final_Test/Images/00057.ppm',\n",
       " './dataset/Final_Test/Images/00058.ppm',\n",
       " './dataset/Final_Test/Images/00059.ppm',\n",
       " './dataset/Final_Test/Images/00060.ppm',\n",
       " './dataset/Final_Test/Images/00061.ppm',\n",
       " './dataset/Final_Test/Images/00062.ppm',\n",
       " './dataset/Final_Test/Images/00063.ppm',\n",
       " './dataset/Final_Test/Images/00064.ppm',\n",
       " './dataset/Final_Test/Images/00065.ppm',\n",
       " './dataset/Final_Test/Images/00066.ppm',\n",
       " './dataset/Final_Test/Images/00067.ppm',\n",
       " './dataset/Final_Test/Images/00068.ppm',\n",
       " './dataset/Final_Test/Images/00069.ppm',\n",
       " './dataset/Final_Test/Images/00070.ppm',\n",
       " './dataset/Final_Test/Images/00071.ppm',\n",
       " './dataset/Final_Test/Images/00072.ppm',\n",
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       " './dataset/Final_Test/Images/00074.ppm',\n",
       " './dataset/Final_Test/Images/00075.ppm',\n",
       " './dataset/Final_Test/Images/00076.ppm',\n",
       " './dataset/Final_Test/Images/00077.ppm',\n",
       " './dataset/Final_Test/Images/00078.ppm',\n",
       " './dataset/Final_Test/Images/00079.ppm',\n",
       " './dataset/Final_Test/Images/00080.ppm',\n",
       " './dataset/Final_Test/Images/00081.ppm',\n",
       " './dataset/Final_Test/Images/00082.ppm',\n",
       " './dataset/Final_Test/Images/00083.ppm',\n",
       " './dataset/Final_Test/Images/00084.ppm',\n",
       " './dataset/Final_Test/Images/00085.ppm',\n",
       " './dataset/Final_Test/Images/00086.ppm',\n",
       " './dataset/Final_Test/Images/00087.ppm',\n",
       " './dataset/Final_Test/Images/00088.ppm',\n",
       " './dataset/Final_Test/Images/00089.ppm',\n",
       " './dataset/Final_Test/Images/00090.ppm',\n",
       " './dataset/Final_Test/Images/00091.ppm',\n",
       " './dataset/Final_Test/Images/00092.ppm',\n",
       " './dataset/Final_Test/Images/00093.ppm',\n",
       " './dataset/Final_Test/Images/00094.ppm',\n",
       " './dataset/Final_Test/Images/00095.ppm',\n",
       " './dataset/Final_Test/Images/00096.ppm',\n",
       " './dataset/Final_Test/Images/00097.ppm',\n",
       " './dataset/Final_Test/Images/00098.ppm',\n",
       " './dataset/Final_Test/Images/00099.ppm',\n",
       " './dataset/Final_Test/Images/00100.ppm',\n",
       " './dataset/Final_Test/Images/00101.ppm',\n",
       " './dataset/Final_Test/Images/00102.ppm',\n",
       " './dataset/Final_Test/Images/00103.ppm',\n",
       " './dataset/Final_Test/Images/00104.ppm',\n",
       " './dataset/Final_Test/Images/00105.ppm',\n",
       " './dataset/Final_Test/Images/00106.ppm',\n",
       " './dataset/Final_Test/Images/00107.ppm',\n",
       " './dataset/Final_Test/Images/00108.ppm',\n",
       " './dataset/Final_Test/Images/00109.ppm',\n",
       " './dataset/Final_Test/Images/00110.ppm',\n",
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       " './dataset/Final_Test/Images/00113.ppm',\n",
       " './dataset/Final_Test/Images/00114.ppm',\n",
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       " './dataset/Final_Test/Images/00117.ppm',\n",
       " './dataset/Final_Test/Images/00118.ppm',\n",
       " './dataset/Final_Test/Images/00119.ppm',\n",
       " './dataset/Final_Test/Images/00120.ppm',\n",
       " './dataset/Final_Test/Images/00121.ppm',\n",
       " './dataset/Final_Test/Images/00122.ppm',\n",
       " './dataset/Final_Test/Images/00123.ppm',\n",
       " './dataset/Final_Test/Images/00124.ppm',\n",
       " './dataset/Final_Test/Images/00125.ppm',\n",
       " './dataset/Final_Test/Images/00126.ppm',\n",
       " './dataset/Final_Test/Images/00127.ppm',\n",
       " './dataset/Final_Test/Images/00128.ppm',\n",
       " './dataset/Final_Test/Images/00129.ppm',\n",
       " './dataset/Final_Test/Images/00130.ppm',\n",
       " './dataset/Final_Test/Images/00131.ppm',\n",
       " './dataset/Final_Test/Images/00132.ppm',\n",
       " './dataset/Final_Test/Images/00133.ppm',\n",
       " './dataset/Final_Test/Images/00134.ppm',\n",
       " './dataset/Final_Test/Images/00135.ppm',\n",
       " './dataset/Final_Test/Images/00136.ppm',\n",
       " './dataset/Final_Test/Images/00137.ppm',\n",
       " './dataset/Final_Test/Images/00138.ppm',\n",
       " './dataset/Final_Test/Images/00139.ppm',\n",
       " './dataset/Final_Test/Images/00140.ppm',\n",
       " './dataset/Final_Test/Images/00141.ppm',\n",
       " './dataset/Final_Test/Images/00142.ppm',\n",
       " './dataset/Final_Test/Images/00143.ppm',\n",
       " './dataset/Final_Test/Images/00144.ppm',\n",
       " './dataset/Final_Test/Images/00145.ppm',\n",
       " './dataset/Final_Test/Images/00146.ppm',\n",
       " './dataset/Final_Test/Images/00147.ppm',\n",
       " './dataset/Final_Test/Images/00148.ppm',\n",
       " './dataset/Final_Test/Images/00149.ppm',\n",
       " './dataset/Final_Test/Images/00150.ppm',\n",
       " './dataset/Final_Test/Images/00151.ppm',\n",
       " './dataset/Final_Test/Images/00152.ppm',\n",
       " './dataset/Final_Test/Images/00153.ppm',\n",
       " './dataset/Final_Test/Images/00154.ppm',\n",
       " './dataset/Final_Test/Images/00155.ppm',\n",
       " './dataset/Final_Test/Images/00156.ppm',\n",
       " './dataset/Final_Test/Images/00157.ppm',\n",
       " './dataset/Final_Test/Images/00158.ppm',\n",
       " './dataset/Final_Test/Images/00159.ppm',\n",
       " './dataset/Final_Test/Images/00160.ppm',\n",
       " './dataset/Final_Test/Images/00161.ppm',\n",
       " './dataset/Final_Test/Images/00162.ppm',\n",
       " './dataset/Final_Test/Images/00163.ppm',\n",
       " './dataset/Final_Test/Images/00164.ppm',\n",
       " './dataset/Final_Test/Images/00165.ppm',\n",
       " './dataset/Final_Test/Images/00166.ppm',\n",
       " './dataset/Final_Test/Images/00167.ppm',\n",
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       " './dataset/Final_Test/Images/00178.ppm',\n",
       " './dataset/Final_Test/Images/00179.ppm',\n",
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       " './dataset/Final_Test/Images/00187.ppm',\n",
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       " './dataset/Final_Test/Images/00189.ppm',\n",
       " './dataset/Final_Test/Images/00190.ppm',\n",
       " './dataset/Final_Test/Images/00191.ppm',\n",
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       " './dataset/Final_Test/Images/00193.ppm',\n",
       " './dataset/Final_Test/Images/00194.ppm',\n",
       " './dataset/Final_Test/Images/00195.ppm',\n",
       " './dataset/Final_Test/Images/00196.ppm',\n",
       " './dataset/Final_Test/Images/00197.ppm',\n",
       " './dataset/Final_Test/Images/00198.ppm',\n",
       " './dataset/Final_Test/Images/00199.ppm',\n",
       " './dataset/Final_Test/Images/00200.ppm',\n",
       " './dataset/Final_Test/Images/00201.ppm',\n",
       " './dataset/Final_Test/Images/00202.ppm',\n",
       " './dataset/Final_Test/Images/00203.ppm',\n",
       " './dataset/Final_Test/Images/00204.ppm',\n",
       " './dataset/Final_Test/Images/00205.ppm',\n",
       " './dataset/Final_Test/Images/00206.ppm',\n",
       " './dataset/Final_Test/Images/00207.ppm',\n",
       " './dataset/Final_Test/Images/00208.ppm',\n",
       " './dataset/Final_Test/Images/00209.ppm',\n",
       " './dataset/Final_Test/Images/00210.ppm',\n",
       " './dataset/Final_Test/Images/00211.ppm',\n",
       " './dataset/Final_Test/Images/00212.ppm',\n",
       " './dataset/Final_Test/Images/00213.ppm',\n",
       " './dataset/Final_Test/Images/00214.ppm',\n",
       " './dataset/Final_Test/Images/00215.ppm',\n",
       " './dataset/Final_Test/Images/00216.ppm',\n",
       " './dataset/Final_Test/Images/00217.ppm',\n",
       " './dataset/Final_Test/Images/00218.ppm',\n",
       " './dataset/Final_Test/Images/00219.ppm',\n",
       " './dataset/Final_Test/Images/00220.ppm',\n",
       " './dataset/Final_Test/Images/00221.ppm',\n",
       " './dataset/Final_Test/Images/00222.ppm',\n",
       " './dataset/Final_Test/Images/00223.ppm',\n",
       " './dataset/Final_Test/Images/00224.ppm',\n",
       " './dataset/Final_Test/Images/00225.ppm',\n",
       " './dataset/Final_Test/Images/00226.ppm',\n",
       " './dataset/Final_Test/Images/00227.ppm',\n",
       " './dataset/Final_Test/Images/00228.ppm',\n",
       " './dataset/Final_Test/Images/00229.ppm',\n",
       " './dataset/Final_Test/Images/00230.ppm',\n",
       " './dataset/Final_Test/Images/00231.ppm',\n",
       " './dataset/Final_Test/Images/00232.ppm',\n",
       " './dataset/Final_Test/Images/00233.ppm',\n",
       " './dataset/Final_Test/Images/00234.ppm',\n",
       " './dataset/Final_Test/Images/00235.ppm',\n",
       " './dataset/Final_Test/Images/00236.ppm',\n",
       " './dataset/Final_Test/Images/00237.ppm',\n",
       " './dataset/Final_Test/Images/00238.ppm',\n",
       " './dataset/Final_Test/Images/00239.ppm',\n",
       " './dataset/Final_Test/Images/00240.ppm',\n",
       " './dataset/Final_Test/Images/00241.ppm',\n",
       " './dataset/Final_Test/Images/00242.ppm',\n",
       " './dataset/Final_Test/Images/00243.ppm',\n",
       " './dataset/Final_Test/Images/00244.ppm',\n",
       " './dataset/Final_Test/Images/00245.ppm',\n",
       " './dataset/Final_Test/Images/00246.ppm',\n",
       " './dataset/Final_Test/Images/00247.ppm',\n",
       " './dataset/Final_Test/Images/00248.ppm',\n",
       " './dataset/Final_Test/Images/00249.ppm',\n",
       " './dataset/Final_Test/Images/00250.ppm',\n",
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       " './dataset/Final_Test/Images/00252.ppm',\n",
       " './dataset/Final_Test/Images/00253.ppm',\n",
       " './dataset/Final_Test/Images/00254.ppm',\n",
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       " './dataset/Final_Test/Images/00256.ppm',\n",
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       " './dataset/Final_Test/Images/00258.ppm',\n",
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       " './dataset/Final_Test/Images/00262.ppm',\n",
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       " './dataset/Final_Test/Images/00279.ppm',\n",
       " './dataset/Final_Test/Images/00280.ppm',\n",
       " './dataset/Final_Test/Images/00281.ppm',\n",
       " './dataset/Final_Test/Images/00282.ppm',\n",
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       " './dataset/Final_Test/Images/00284.ppm',\n",
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       " './dataset/Final_Test/Images/00288.ppm',\n",
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       " './dataset/Final_Test/Images/00294.ppm',\n",
       " './dataset/Final_Test/Images/00295.ppm',\n",
       " './dataset/Final_Test/Images/00296.ppm',\n",
       " './dataset/Final_Test/Images/00297.ppm',\n",
       " './dataset/Final_Test/Images/00298.ppm',\n",
       " './dataset/Final_Test/Images/00299.ppm',\n",
       " './dataset/Final_Test/Images/00300.ppm',\n",
       " './dataset/Final_Test/Images/00301.ppm',\n",
       " './dataset/Final_Test/Images/00302.ppm',\n",
       " './dataset/Final_Test/Images/00303.ppm',\n",
       " './dataset/Final_Test/Images/00304.ppm',\n",
       " './dataset/Final_Test/Images/00305.ppm',\n",
       " './dataset/Final_Test/Images/00306.ppm',\n",
       " './dataset/Final_Test/Images/00307.ppm',\n",
       " './dataset/Final_Test/Images/00308.ppm',\n",
       " './dataset/Final_Test/Images/00309.ppm',\n",
       " './dataset/Final_Test/Images/00310.ppm',\n",
       " './dataset/Final_Test/Images/00311.ppm',\n",
       " './dataset/Final_Test/Images/00312.ppm',\n",
       " './dataset/Final_Test/Images/00313.ppm',\n",
       " './dataset/Final_Test/Images/00314.ppm',\n",
       " './dataset/Final_Test/Images/00315.ppm',\n",
       " './dataset/Final_Test/Images/00316.ppm',\n",
       " './dataset/Final_Test/Images/00317.ppm',\n",
       " './dataset/Final_Test/Images/00318.ppm',\n",
       " './dataset/Final_Test/Images/00319.ppm',\n",
       " './dataset/Final_Test/Images/00320.ppm',\n",
       " './dataset/Final_Test/Images/00321.ppm',\n",
       " './dataset/Final_Test/Images/00322.ppm',\n",
       " './dataset/Final_Test/Images/00323.ppm',\n",
       " './dataset/Final_Test/Images/00324.ppm',\n",
       " './dataset/Final_Test/Images/00325.ppm',\n",
       " './dataset/Final_Test/Images/00326.ppm',\n",
       " './dataset/Final_Test/Images/00327.ppm',\n",
       " './dataset/Final_Test/Images/00328.ppm',\n",
       " './dataset/Final_Test/Images/00329.ppm',\n",
       " './dataset/Final_Test/Images/00330.ppm',\n",
       " './dataset/Final_Test/Images/00331.ppm',\n",
       " './dataset/Final_Test/Images/00332.ppm',\n",
       " './dataset/Final_Test/Images/00333.ppm',\n",
       " './dataset/Final_Test/Images/00334.ppm',\n",
       " './dataset/Final_Test/Images/00335.ppm',\n",
       " './dataset/Final_Test/Images/00336.ppm',\n",
       " './dataset/Final_Test/Images/00337.ppm',\n",
       " './dataset/Final_Test/Images/00338.ppm',\n",
       " './dataset/Final_Test/Images/00339.ppm',\n",
       " './dataset/Final_Test/Images/00340.ppm',\n",
       " './dataset/Final_Test/Images/00341.ppm',\n",
       " './dataset/Final_Test/Images/00342.ppm',\n",
       " './dataset/Final_Test/Images/00343.ppm',\n",
       " './dataset/Final_Test/Images/00344.ppm',\n",
       " './dataset/Final_Test/Images/00345.ppm',\n",
       " './dataset/Final_Test/Images/00346.ppm',\n",
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       " './dataset/Final_Test/Images/00958.ppm',\n",
       " './dataset/Final_Test/Images/00959.ppm',\n",
       " './dataset/Final_Test/Images/00960.ppm',\n",
       " './dataset/Final_Test/Images/00961.ppm',\n",
       " './dataset/Final_Test/Images/00962.ppm',\n",
       " './dataset/Final_Test/Images/00963.ppm',\n",
       " './dataset/Final_Test/Images/00964.ppm',\n",
       " './dataset/Final_Test/Images/00965.ppm',\n",
       " './dataset/Final_Test/Images/00966.ppm',\n",
       " './dataset/Final_Test/Images/00967.ppm',\n",
       " './dataset/Final_Test/Images/00968.ppm',\n",
       " './dataset/Final_Test/Images/00969.ppm',\n",
       " './dataset/Final_Test/Images/00970.ppm',\n",
       " './dataset/Final_Test/Images/00971.ppm',\n",
       " './dataset/Final_Test/Images/00972.ppm',\n",
       " './dataset/Final_Test/Images/00973.ppm',\n",
       " './dataset/Final_Test/Images/00974.ppm',\n",
       " './dataset/Final_Test/Images/00975.ppm',\n",
       " './dataset/Final_Test/Images/00976.ppm',\n",
       " './dataset/Final_Test/Images/00977.ppm',\n",
       " './dataset/Final_Test/Images/00978.ppm',\n",
       " './dataset/Final_Test/Images/00979.ppm',\n",
       " './dataset/Final_Test/Images/00980.ppm',\n",
       " './dataset/Final_Test/Images/00981.ppm',\n",
       " './dataset/Final_Test/Images/00982.ppm',\n",
       " './dataset/Final_Test/Images/00983.ppm',\n",
       " './dataset/Final_Test/Images/00984.ppm',\n",
       " './dataset/Final_Test/Images/00985.ppm',\n",
       " './dataset/Final_Test/Images/00986.ppm',\n",
       " './dataset/Final_Test/Images/00987.ppm',\n",
       " './dataset/Final_Test/Images/00988.ppm',\n",
       " './dataset/Final_Test/Images/00989.ppm',\n",
       " './dataset/Final_Test/Images/00990.ppm',\n",
       " './dataset/Final_Test/Images/00991.ppm',\n",
       " './dataset/Final_Test/Images/00992.ppm',\n",
       " './dataset/Final_Test/Images/00993.ppm',\n",
       " './dataset/Final_Test/Images/00994.ppm',\n",
       " './dataset/Final_Test/Images/00995.ppm',\n",
       " './dataset/Final_Test/Images/00996.ppm',\n",
       " './dataset/Final_Test/Images/00997.ppm',\n",
       " './dataset/Final_Test/Images/00998.ppm',\n",
       " './dataset/Final_Test/Images/00999.ppm',\n",
       " ...]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(test_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>00000_00018.ppm</td>\n",
       "      <td>50</td>\n",
       "      <td>48</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>00000_00019.ppm</td>\n",
       "      <td>53</td>\n",
       "      <td>51</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>48</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>00000_00020.ppm</td>\n",
       "      <td>57</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>00000_00021.ppm</td>\n",
       "      <td>59</td>\n",
       "      <td>58</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>53</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>00000_00022.ppm</td>\n",
       "      <td>63</td>\n",
       "      <td>61</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>57</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>00000_00023.ppm</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>00000_00024.ppm</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>70</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>00000_00025.ppm</td>\n",
       "      <td>85</td>\n",
       "      <td>86</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>78</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>00000_00026.ppm</td>\n",
       "      <td>97</td>\n",
       "      <td>97</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>89</td>\n",
       "      <td>88</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>00000_00027.ppm</td>\n",
       "      <td>108</td>\n",
       "      <td>110</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>99</td>\n",
       "      <td>101</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>00000_00028.ppm</td>\n",
       "      <td>124</td>\n",
       "      <td>127</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>113</td>\n",
       "      <td>116</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>00000_00029.ppm</td>\n",
       "      <td>144</td>\n",
       "      <td>148</td>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>132</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>00007_00000.ppm</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>23</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>00007_00001.ppm</td>\n",
       "      <td>28</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>22</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>00007_00002.ppm</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>00007_00003.ppm</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>00007_00004.ppm</td>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>00007_00005.ppm</td>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>00007_00006.ppm</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>00007_00007.ppm</td>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>00007_00008.ppm</td>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>00007_00009.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>00007_00010.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>00007_00011.ppm</td>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>00007_00012.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>34</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>00007_00013.ppm</td>\n",
       "      <td>34</td>\n",
       "      <td>36</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>29</td>\n",
       "      <td>31</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>00007_00014.ppm</td>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>00007_00015.ppm</td>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>00007_00016.ppm</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>00007_00017.ppm</td>\n",
       "      <td>38</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>33</td>\n",
       "      <td>35</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>00007_00018.ppm</td>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>00007_00019.ppm</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>00007_00020.ppm</td>\n",
       "      <td>44</td>\n",
       "      <td>46</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>39</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>00007_00021.ppm</td>\n",
       "      <td>44</td>\n",
       "      <td>46</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>39</td>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>00007_00022.ppm</td>\n",
       "      <td>47</td>\n",
       "      <td>50</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>42</td>\n",
       "      <td>45</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>00007_00023.ppm</td>\n",
       "      <td>49</td>\n",
       "      <td>50</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>00007_00024.ppm</td>\n",
       "      <td>51</td>\n",
       "      <td>53</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>46</td>\n",
       "      <td>48</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>00007_00025.ppm</td>\n",
       "      <td>52</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>47</td>\n",
       "      <td>51</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>00007_00026.ppm</td>\n",
       "      <td>56</td>\n",
       "      <td>58</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>53</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>00007_00027.ppm</td>\n",
       "      <td>58</td>\n",
       "      <td>62</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>53</td>\n",
       "      <td>57</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>00007_00028.ppm</td>\n",
       "      <td>63</td>\n",
       "      <td>69</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>58</td>\n",
       "      <td>63</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>00007_00029.ppm</td>\n",
       "      <td>68</td>\n",
       "      <td>69</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>62</td>\n",
       "      <td>63</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>39209 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Filename  Width  Height  Roi.X1  Roi.Y1  Roi.X2  Roi.Y2  ClassId\n",
       "0    00000_00000.ppm     29      30       5       6      24      25        0\n",
       "1    00000_00001.ppm     30      30       5       5      25      25        0\n",
       "2    00000_00002.ppm     30      30       5       5      25      25        0\n",
       "3    00000_00003.ppm     31      31       5       5      26      26        0\n",
       "4    00000_00004.ppm     30      32       5       6      25      26        0\n",
       "5    00000_00005.ppm     31      31       6       6      26      26        0\n",
       "6    00000_00006.ppm     33      34       6       6      28      28        0\n",
       "7    00000_00007.ppm     34      35       6       6      29      30        0\n",
       "8    00000_00008.ppm     33      34       5       5      28      29        0\n",
       "9    00000_00009.ppm     36      36       6       5      30      30        0\n",
       "10   00000_00010.ppm     35      36       5       5      30      31        0\n",
       "11   00000_00011.ppm     37      38       6       6      32      33        0\n",
       "12   00000_00012.ppm     37      38       5       6      32      33        0\n",
       "13   00000_00013.ppm     40      39       6       5      35      34        0\n",
       "14   00000_00014.ppm     41      42       5       6      36      37        0\n",
       "15   00000_00015.ppm     44      44       6       6      39      39        0\n",
       "16   00000_00016.ppm     46      44       6       5      41      39        0\n",
       "17   00000_00017.ppm     47      48       6       6      42      42        0\n",
       "18   00000_00018.ppm     50      48       5       5      45      43        0\n",
       "19   00000_00019.ppm     53      51       5       5      48      46        0\n",
       "20   00000_00020.ppm     57      54       6       5      51      49        0\n",
       "21   00000_00021.ppm     59      58       6       6      53      53        0\n",
       "22   00000_00022.ppm     63      61       6       5      57      56        0\n",
       "23   00000_00023.ppm     70      70       7       7      64      64        0\n",
       "24   00000_00024.ppm     76      76       7       7      70      70        0\n",
       "25   00000_00025.ppm     85      86       7       8      78      79        0\n",
       "26   00000_00026.ppm     97      97       8       8      89      88        0\n",
       "27   00000_00027.ppm    108     110       9      10      99     101        0\n",
       "28   00000_00028.ppm    124     127      10      11     113     116        0\n",
       "29   00000_00029.ppm    144     148      12      13     132     136        0\n",
       "..               ...    ...     ...     ...     ...     ...     ...      ...\n",
       "210  00007_00000.ppm     27      28       5       6      22      23       42\n",
       "211  00007_00001.ppm     28      27       6       5      23      22       42\n",
       "212  00007_00002.ppm     28      29       5       5      23      24       42\n",
       "213  00007_00003.ppm     31      31       6       5      26      26       42\n",
       "214  00007_00004.ppm     30      32       5       6      25      27       42\n",
       "215  00007_00005.ppm     30      32       5       6      25      27       42\n",
       "216  00007_00006.ppm     31      31       6       5      26      26       42\n",
       "217  00007_00007.ppm     30      32       5       6      25      27       42\n",
       "218  00007_00008.ppm     30      32       5       6      25      27       42\n",
       "219  00007_00009.ppm     32      32       6       5      27      27       42\n",
       "220  00007_00010.ppm     32      32       6       5      27      27       42\n",
       "221  00007_00011.ppm     33      34       6       6      28      29       42\n",
       "222  00007_00012.ppm     32      34       5       6      27      29       42\n",
       "223  00007_00013.ppm     34      36       5       6      29      31       42\n",
       "224  00007_00014.ppm     34      35       5       5      29      30       42\n",
       "225  00007_00015.ppm     36      37       5       5      31      32       42\n",
       "226  00007_00016.ppm     38      38       6       5      33      33       42\n",
       "227  00007_00017.ppm     38      40       5       6      33      35       42\n",
       "228  00007_00018.ppm     39      40       5       5      34      35       42\n",
       "229  00007_00019.ppm     41      41       6       5      36      36       42\n",
       "230  00007_00020.ppm     44      46       6       6      39      41       42\n",
       "231  00007_00021.ppm     44      46       5       5      39      41       42\n",
       "232  00007_00022.ppm     47      50       5       6      42      45       42\n",
       "233  00007_00023.ppm     49      50       6       5      44      45       42\n",
       "234  00007_00024.ppm     51      53       6       5      46      48       42\n",
       "235  00007_00025.ppm     52      56       5       6      47      51       42\n",
       "236  00007_00026.ppm     56      58       5       5      51      53       42\n",
       "237  00007_00027.ppm     58      62       5       6      53      57       42\n",
       "238  00007_00028.ppm     63      69       5       7      58      63       42\n",
       "239  00007_00029.ppm     68      69       7       6      62      63       42\n",
       "\n",
       "[39209 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df = pd.concat([pd.read_csv(label, delimiter=\";\") for label in train_label])\n",
    "train_df = train_df.sort_values(['ClassId','Filename'])\n",
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>Width</th>\n",
       "      <th>Height</th>\n",
       "      <th>Roi.X1</th>\n",
       "      <th>Roi.Y1</th>\n",
       "      <th>Roi.X2</th>\n",
       "      <th>Roi.Y2</th>\n",
       "      <th>ClassId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00000.ppm</td>\n",
       "      <td>53</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>48</td>\n",
       "      <td>49</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>00001.ppm</td>\n",
       "      <td>42</td>\n",
       "      <td>45</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>36</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00002.ppm</td>\n",
       "      <td>48</td>\n",
       "      <td>52</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>43</td>\n",
       "      <td>47</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00003.ppm</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00004.ppm</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>55</td>\n",
       "      <td>52</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>00005.ppm</td>\n",
       "      <td>52</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>47</td>\n",
       "      <td>51</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>00006.ppm</td>\n",
       "      <td>147</td>\n",
       "      <td>130</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>135</td>\n",
       "      <td>119</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>00007.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>28</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>00008.ppm</td>\n",
       "      <td>45</td>\n",
       "      <td>50</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>40</td>\n",
       "      <td>45</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>00009.ppm</td>\n",
       "      <td>81</td>\n",
       "      <td>86</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>74</td>\n",
       "      <td>79</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>00010.ppm</td>\n",
       "      <td>38</td>\n",
       "      <td>37</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>32</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>00011.ppm</td>\n",
       "      <td>45</td>\n",
       "      <td>44</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>40</td>\n",
       "      <td>39</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>00012.ppm</td>\n",
       "      <td>79</td>\n",
       "      <td>73</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>72</td>\n",
       "      <td>67</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>00013.ppm</td>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>00014.ppm</td>\n",
       "      <td>43</td>\n",
       "      <td>41</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>36</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>00015.ppm</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>00016.ppm</td>\n",
       "      <td>37</td>\n",
       "      <td>38</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>00017.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>00018.ppm</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>00019.ppm</td>\n",
       "      <td>34</td>\n",
       "      <td>40</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>29</td>\n",
       "      <td>35</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>00020.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>00021.ppm</td>\n",
       "      <td>52</td>\n",
       "      <td>55</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>47</td>\n",
       "      <td>49</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>00022.ppm</td>\n",
       "      <td>116</td>\n",
       "      <td>120</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>106</td>\n",
       "      <td>110</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>00023.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>00024.ppm</td>\n",
       "      <td>59</td>\n",
       "      <td>65</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>54</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>00025.ppm</td>\n",
       "      <td>35</td>\n",
       "      <td>34</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>00026.ppm</td>\n",
       "      <td>56</td>\n",
       "      <td>49</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>51</td>\n",
       "      <td>43</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>00027.ppm</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>00028.ppm</td>\n",
       "      <td>34</td>\n",
       "      <td>36</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>00029.ppm</td>\n",
       "      <td>38</td>\n",
       "      <td>35</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>30</td>\n",
       "      <td>11</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>12600</th>\n",
       "      <td>12600.ppm</td>\n",
       "      <td>45</td>\n",
       "      <td>46</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>40</td>\n",
       "      <td>41</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12601</th>\n",
       "      <td>12601.ppm</td>\n",
       "      <td>48</td>\n",
       "      <td>47</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>43</td>\n",
       "      <td>42</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12602</th>\n",
       "      <td>12602.ppm</td>\n",
       "      <td>48</td>\n",
       "      <td>47</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>43</td>\n",
       "      <td>42</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12603</th>\n",
       "      <td>12603.ppm</td>\n",
       "      <td>69</td>\n",
       "      <td>116</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>63</td>\n",
       "      <td>106</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12604</th>\n",
       "      <td>12604.ppm</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12605</th>\n",
       "      <td>12605.ppm</td>\n",
       "      <td>149</td>\n",
       "      <td>129</td>\n",
       "      <td>13</td>\n",
       "      <td>11</td>\n",
       "      <td>137</td>\n",
       "      <td>118</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12606</th>\n",
       "      <td>12606.ppm</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>59</td>\n",
       "      <td>59</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12607</th>\n",
       "      <td>12607.ppm</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12608</th>\n",
       "      <td>12608.ppm</td>\n",
       "      <td>47</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>41</td>\n",
       "      <td>39</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12609</th>\n",
       "      <td>12609.ppm</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12610</th>\n",
       "      <td>12610.ppm</td>\n",
       "      <td>44</td>\n",
       "      <td>50</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>38</td>\n",
       "      <td>44</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12611</th>\n",
       "      <td>12611.ppm</td>\n",
       "      <td>98</td>\n",
       "      <td>86</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>89</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12612</th>\n",
       "      <td>12612.ppm</td>\n",
       "      <td>74</td>\n",
       "      <td>75</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>68</td>\n",
       "      <td>69</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12613</th>\n",
       "      <td>12613.ppm</td>\n",
       "      <td>35</td>\n",
       "      <td>34</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12614</th>\n",
       "      <td>12614.ppm</td>\n",
       "      <td>31</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12615</th>\n",
       "      <td>12615.ppm</td>\n",
       "      <td>72</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>66</td>\n",
       "      <td>55</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12616</th>\n",
       "      <td>12616.ppm</td>\n",
       "      <td>33</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12617</th>\n",
       "      <td>12617.ppm</td>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>37</td>\n",
       "      <td>37</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12618</th>\n",
       "      <td>12618.ppm</td>\n",
       "      <td>42</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>37</td>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12619</th>\n",
       "      <td>12619.ppm</td>\n",
       "      <td>31</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>24</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12620</th>\n",
       "      <td>12620.ppm</td>\n",
       "      <td>63</td>\n",
       "      <td>57</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>58</td>\n",
       "      <td>52</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12621</th>\n",
       "      <td>12621.ppm</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12622</th>\n",
       "      <td>12622.ppm</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12623</th>\n",
       "      <td>12623.ppm</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12624</th>\n",
       "      <td>12624.ppm</td>\n",
       "      <td>84</td>\n",
       "      <td>91</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>77</td>\n",
       "      <td>83</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12625</th>\n",
       "      <td>12625.ppm</td>\n",
       "      <td>42</td>\n",
       "      <td>41</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>37</td>\n",
       "      <td>36</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12626</th>\n",
       "      <td>12626.ppm</td>\n",
       "      <td>50</td>\n",
       "      <td>51</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "      <td>46</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12627</th>\n",
       "      <td>12627.ppm</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12628</th>\n",
       "      <td>12628.ppm</td>\n",
       "      <td>48</td>\n",
       "      <td>49</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>43</td>\n",
       "      <td>44</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12629</th>\n",
       "      <td>12629.ppm</td>\n",
       "      <td>32</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12630 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Filename  Width  Height  Roi.X1  Roi.Y1  Roi.X2  Roi.Y2  ClassId\n",
       "0      00000.ppm     53      54       6       5      48      49       16\n",
       "1      00001.ppm     42      45       5       5      36      40        1\n",
       "2      00002.ppm     48      52       6       6      43      47       38\n",
       "3      00003.ppm     27      29       5       5      22      24       33\n",
       "4      00004.ppm     60      57       5       5      55      52       11\n",
       "5      00005.ppm     52      56       5       5      47      51       38\n",
       "6      00006.ppm    147     130      12      12     135     119       18\n",
       "7      00007.ppm     32      33       5       5      26      28       12\n",
       "8      00008.ppm     45      50       6       5      40      45       25\n",
       "9      00009.ppm     81      86       7       7      74      79       35\n",
       "10     00010.ppm     38      37       6       5      33      32       12\n",
       "11     00011.ppm     45      44       6       5      40      39        7\n",
       "12     00012.ppm     79      73       7       7      72      67       23\n",
       "13     00013.ppm     36      37       5       6      31      32        7\n",
       "14     00014.ppm     43      41       5       5      37      36        4\n",
       "15     00015.ppm     27      27       6       6      22      22        9\n",
       "16     00016.ppm     37      38       5       6      31      32       21\n",
       "17     00017.ppm     32      33       5       5      27      28       20\n",
       "18     00018.ppm     35      35       5       6      30      29       27\n",
       "19     00019.ppm     34      40       6       6      29      35       38\n",
       "20     00020.ppm     32      33       5       6      27      28        4\n",
       "21     00021.ppm     52      55       5       6      47      49       33\n",
       "22     00022.ppm    116     120      10      11     106     110        9\n",
       "23     00023.ppm     32      33       5       5      27      28        3\n",
       "24     00024.ppm     59      65       5       6      54      60        1\n",
       "25     00025.ppm     35      34       6       5      30      29       11\n",
       "26     00026.ppm     56      49       5       6      51      43       13\n",
       "27     00027.ppm     28      29       5       6      23      24       10\n",
       "28     00028.ppm     34      36       6       6      29      30        9\n",
       "29     00029.ppm     38      35       6       5      33      30       11\n",
       "...          ...    ...     ...     ...     ...     ...     ...      ...\n",
       "12600  12600.ppm     45      46       5       6      40      41       35\n",
       "12601  12601.ppm     48      47       6       6      43      42       38\n",
       "12602  12602.ppm     48      47       6       6      43      42       24\n",
       "12603  12603.ppm     69     116       6      11      63     106       13\n",
       "12604  12604.ppm     35      35       5       5      30      30       35\n",
       "12605  12605.ppm    149     129      13      11     137     118       25\n",
       "12606  12606.ppm     64      64       6       6      59      59       38\n",
       "12607  12607.ppm     34      34       5       5      29      29        1\n",
       "12608  12608.ppm     47      45       6       5      41      39       18\n",
       "12609  12609.ppm     41      41       5       5      36      36        7\n",
       "12610  12610.ppm     44      50       5       6      38      44       35\n",
       "12611  12611.ppm     98      86       9       7      89      78       11\n",
       "12612  12612.ppm     74      75       6       6      68      69       39\n",
       "12613  12613.ppm     35      34       6       5      30      29        8\n",
       "12614  12614.ppm     31      33       5       5      26      28        0\n",
       "12615  12615.ppm     72      60       7       6      66      55       10\n",
       "12616  12616.ppm     33      33       5       6      28      28       18\n",
       "12617  12617.ppm     42      42       5       6      37      37       31\n",
       "12618  12618.ppm     42      45       6       5      37      40        8\n",
       "12619  12619.ppm     31      30       5       5      26      24       31\n",
       "12620  12620.ppm     63      57       6       5      58      52       13\n",
       "12621  12621.ppm     39      39       5       6      34      34        5\n",
       "12622  12622.ppm     35      35       6       5      29      30       12\n",
       "12623  12623.ppm     31      31       6       5      26      26       35\n",
       "12624  12624.ppm     84      91       8       8      77      83       25\n",
       "12625  12625.ppm     42      41       5       6      37      36       12\n",
       "12626  12626.ppm     50      51       6       5      45      46       33\n",
       "12627  12627.ppm     29      29       6       6      24      24        6\n",
       "12628  12628.ppm     48      49       5       6      43      44        7\n",
       "12629  12629.ppm     32      31       6       5      27      26       10\n",
       "\n",
       "[12630 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df = pd.concat([pd.read_csv(label, delimiter=\";\") for label in test_label])\n",
    "test_df = test_df.sort_values(['Filename'])\n",
    "test_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "(x1,y1) = (train_df.iloc[0]['Roi.X1'], train_df.iloc[0]['Roi.Y1'])\n",
    "(x2,y2) = (train_df.iloc[0]['Roi.X2'], train_df.iloc[0]['Roi.Y2'])\n",
    "width = x2-x1\n",
    "height = y2-y1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Rectangle at 0x7fbd24934da0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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z7n5Lbd0XAfwBgHO1l33B3Z9s1laxVMVJYoVVnNsJANDbza0wK/DJ6gY3cSusmrtyu3W5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\nwS1EpPx/+S1Ur5eT/k0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbc926846a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1)\n",
    "ax.imshow(mpimg.imread(train_list[0]))\n",
    "ax.add_patch(patches.Rectangle((x1,y1),width, height, fill=False ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num of train:39209, Num of test:12630, Num of Class:43\n"
     ]
    }
   ],
   "source": [
    "n_train = len(train_list)\n",
    "n_test =  len(test_list)\n",
    "n_class = len(np.bincount(train_df.loc[:,\"ClassId\"]))\n",
    "\n",
    "print(\"Num of train:{}, Num of test:{}, Num of Class:{}\".format(n_train, n_test, n_class))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cpIlL8mXgagZ3JnwBuB34J+BeYAPwLHBzVZ15oLgLSd4D/DvwPd6Yv/0Yg+MA9hGQ5DcZ\nHMRcxeCPx3ur6uNJfpXByRaXAd8B/rCqXp1cSycvydXAn1XV+6a5f1ZkAEiSRluJU0CSpHkwACSp\nUwaAJHXKAJCkThkAktQpA0CSOmUASFKnDABJ6tT/AwUc0bNkkOMwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbd2494b278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = plt.hist(train_df.loc[:,'ClassId'], n_class)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_train(training_path):\n",
    "    X_train = []\n",
    "    y_train = []\n",
    "    train_list = []\n",
    "    \n",
    "    train_list = glob.glob(training_path + \"**/**/*.ppm\")\n",
    "    train_label = glob.glob(training_path + \"**/**/*.csv\")\n",
    "    \n",
    "    train_list = sorted(train_list)\n",
    "    train_df = pd.concat([pd.read_csv(label, delimiter=\";\") for label in train_label])\n",
    "    train_df = train_df.sort_values(['ClassId','Filename'])\n",
    "\n",
    "    for (trainx, trainy) in zip(train_list, train_df['ClassId']):\n",
    "        X_train.append(cv2.resize(mpimg.imread(trainx), (32,32)))\n",
    "        y_train.append(trainy)\n",
    "    \n",
    "    return np.array(X_train), np.array(y_train)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_test(test_path):\n",
    "    X_test = []\n",
    "    y_test = []\n",
    "    \n",
    "    test_list = []\n",
    "    test_list = sorted(glob.glob(test_path + \"**/*.ppm\"))\n",
    "    test_label = glob.glob(test_path + \"*.csv\")\n",
    "    \n",
    "    test_df = pd.concat([pd.read_csv(label, delimiter=\";\") for label in test_label])\n",
    "    test_df = test_df.sort_values(['Filename'])\n",
    "    \n",
    "    for (testx, testy) in zip(test_list, test_df['ClassId']):\n",
    "        X_test.append(cv2.resize(mpimg.imread(testx), (32,32)))\n",
    "        y_test.append(testy)\n",
    "        \n",
    "    return np.array(X_test), np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, y_train = make_train(training_path=training_path)\n",
    "\n",
    "X_test, y_test = make_test(test_path=test_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((39209, 32, 32, 3), (39209,), (12630, 32, 32, 3), (12630,))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, y_train.shape, X_test.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open(train_file, mode='wb') as f:\n",
    "    pickle.dump((X_train, y_train), f)\n",
    "\n",
    "with open(test_file, mode='wb') as f:\n",
    "    pickle.dump((X_test, y_test), f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}