image_check.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pylab\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "val_f = open('../dataset/val.txt', 'rb').readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "img_folder = '/home/VOCdevkit'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "vals = [x.split(' ')[1][22:37] for x in val_f]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1449"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(vals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "AssertionError",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-c8cda768b4e4>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      2\u001b[0m     \u001b[0mimg_old\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImage\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_folder\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m'/SegmentationClassAug_old/'\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# old one\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mimg_new\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImage\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_folder\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m'/SegmentationClassAug/'\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# https://www.dropbox.com/s/oeu149j8qtbs1x0/SegmentationClassAug.zip?dl=0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m     \u001b[1;32massert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_old\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg_new\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAssertionError\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for v in vals:\n",
    "    img_old = Image.open(img_folder + '/SegmentationClassAug_old/' + v) # old one\n",
    "    img_new = Image.open(img_folder + '/SegmentationClassAug/' + v) # https://www.dropbox.com/s/oeu149j8qtbs1x0/SegmentationClassAug.zip?dl=0\n",
    "    assert(np.all(np.array(img_old) == np.array(img_new)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAF3CAAAAAB2meYgAAAC6klEQVR4nO3dzXajMAwGUM2crnj/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\nRK5CYII=\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=L size=500x375 at 0x7F9EFDBC6A10>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_old"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAF3CAAAAAB2meYgAAAEMklEQVR4nO3duZajOhQFUNHrZfz/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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=L size=500x375 at 0x7F9EFDBC6990>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0, 10], dtype=uint8), array([183938,   3562]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(np.array(img_old), return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  0,  10, 255], dtype=uint8), array([182433,   2774,   2293]))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(np.array(img_new), return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}