data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import sys\n",
    "import os\n",
    "from matplotlib import pyplot as plt\n",
    "from skimage import io"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parsing labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_label(fname):\n",
    "    label = []\n",
    "    with open(fname) as f:\n",
    "        reader = csv.reader(f)\n",
    "        next(reader)\n",
    "        for row in reader:\n",
    "            label.append(row)\n",
    "    return label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2ada1ea3c8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "label = load_label(\"./data/train.csv\")\n",
    "import pandas as pd\n",
    "label = pd.DataFrame(label)\n",
    "num_classes = len(set(label[1]))\n",
    "label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Label's frequency :\n",
    "\n",
    "It is obvious that the classes aren't balanced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'label'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2656\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2657\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2658\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'label'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-16-35405fad1879>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mtable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrosstab\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"count\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mtable1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrosstab\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabel1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"label\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"count\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mlabel1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2925\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2926\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2927\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2928\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2929\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2657\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2658\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2659\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2660\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2661\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'label'"
     ]
    }
   ],
   "source": [
    "label1 = pd.read_csv(\"./data/train.csv\")\n",
    "table1 = pd.crosstab(index = label1[\"label\"], columns = \"count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sampling image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sample_img():\n",
    "    index = np.random.choice(range(len(label)))\n",
    "    img = io.imread(\"./data/train/{}\".format(label[0][index]))\n",
    "    io.imshow(img)\n",
    "    print(\"Class : {}\".format(label[1][index]))\n",
    "    print(img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class : 73\n",
      "(181, 181, 3)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_img()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['count'], dtype='object', name='col_0')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([  0, 109,  11, 111, 114, 116, 117,  12, 120,  13, 130, 134, 137,\n",
       "       139,  14, 140, 142, 143, 145, 152, 165,  17, 170, 171, 177,  18,\n",
       "       181, 183, 190, 193, 198, 200, 203, 205, 206, 213, 214, 215,  22,\n",
       "       224, 228,  23, 230, 239, 240, 246, 249,  25, 252, 270, 271, 277,\n",
       "       284,  29, 295,   3,  30, 303, 308, 309,  31, 312, 313, 317, 318,\n",
       "       325, 329,  33, 330, 336, 337, 339, 340, 344, 348, 350, 351, 355,\n",
       "        36, 362, 367,  37, 370, 371,  38,  39, 395, 397,  40, 403, 407,\n",
       "        41, 410, 413, 415, 417, 421, 422, 427, 429,  43, 432, 441, 442,\n",
       "       447, 450, 452, 455, 458, 461, 462, 467, 470, 477, 478, 479, 486,\n",
       "       488,  49, 499,  50,  51, 520, 521, 524, 527,  53, 535, 537, 543,\n",
       "       544, 546, 550, 551, 556, 559, 560, 568, 569, 577, 579, 580, 591,\n",
       "       598, 599, 601, 603, 605, 613, 616,  62, 624, 633, 634, 635,  64,\n",
       "       640, 644,  65, 653, 655, 658, 660, 663,  67, 676, 677, 678, 679,\n",
       "        68, 680,  69,   7, 700, 704, 710, 712, 713,  72, 732, 737, 745,\n",
       "        75, 750, 752, 754, 769, 770, 776, 785, 786, 787, 791, 794, 798,\n",
       "       800, 804, 805, 808, 809,  81, 814, 817, 818, 825, 833, 836,  84,\n",
       "       842, 857, 858, 859, 860, 864,  88, 890,   9, 900, 903, 905,  91,\n",
       "       911, 912, 913, 915,  92, 922, 924, 927,  93, 931, 933, 936, 937,\n",
       "       939, 944, 947, 949, 962,  97, 973, 974,  98, 980, 982, 989, 990,\n",
       "       997, 999])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "less_than_3 = table[\"count\"] < 3\n",
    "print(table.columns)\n",
    "np.asarray((table[less_than_3].index)).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-3fa52c2ba565>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfile\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0mpath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpath_root\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0mimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m     \u001b[0mheight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mimg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mweight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py\u001b[0m in \u001b[0;36mimread\u001b[0;34m(fname, as_gray, plugin, flatten, **plugin_args)\u001b[0m\n\u001b[1;32m     60\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     61\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mfile_or_url_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfname\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 62\u001b[0;31m         \u001b[0mimg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcall_plugin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'imread'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mplugin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mplugin\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mplugin_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     63\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'ndim'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py\u001b[0m in \u001b[0;36mcall_plugin\u001b[0;34m(kind, *args, **kwargs)\u001b[0m\n\u001b[1;32m    212\u001b[0m                                (plugin, kind))\n\u001b[1;32m    213\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 214\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    215\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    216\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/pil_plugin.py\u001b[0m in \u001b[0;36mimread\u001b[0;34m(fname, dtype, img_num, **kwargs)\u001b[0m\n\u001b[1;32m     34\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstring_types\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     35\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 36\u001b[0;31m             \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     37\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mpil_to_ndarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimg_num\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mimg_num\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     38\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3/dist-packages/PIL/Image.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(fp, mode)\u001b[0m\n\u001b[1;32m   2555\u001b[0m         \u001b[0mexclusive_fp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2556\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2557\u001b[0;31m     \u001b[0mprefix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2558\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2559\u001b[0m     \u001b[0mpreinit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import os\n",
    "from skimage import io\n",
    "\n",
    "height = []\n",
    "weight = []\n",
    "\n",
    "files = os.listdir(\"./data/train\")\n",
    "path_root = \"./data/train/\"\n",
    "for file in files:\n",
    "    path = path_root + file\n",
    "    img = io.imread(path)\n",
    "    height.append( img.shape[1])\n",
    "    weight.append(img.shape[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.hist(height)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.hist(weight)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "<p>1000 rows × 1 columns</p>\n",
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      ],
      "text/plain": [
       "col_0  count\n",
       "1           \n",
       "0          2\n",
       "1          3\n",
       "10         4\n",
       "100        4\n",
       "101        9\n",
       "102        5\n",
       "103       10\n",
       "104        8\n",
       "105        6\n",
       "106        3\n",
       "107        3\n",
       "108        6\n",
       "109        1\n",
       "11         2\n",
       "110        4\n",
       "111        2\n",
       "112        6\n",
       "113        4\n",
       "114        2\n",
       "115        4\n",
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       "123        3\n",
       "124        4\n",
       "..       ...\n",
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       "98         2\n",
       "980        1\n",
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       "982        2\n",
       "983        7\n",
       "984        7\n",
       "985        7\n",
       "986        4\n",
       "987        6\n",
       "988        7\n",
       "989        1\n",
       "99         5\n",
       "990        2\n",
       "991        4\n",
       "992        5\n",
       "993        5\n",
       "994        3\n",
       "995        7\n",
       "996        7\n",
       "997        2\n",
       "998        3\n",
       "999        2\n",
       "\n",
       "[1000 rows x 1 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
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  }
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