removeblankimages.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.image as mpimg\n",
    "from os.path import exists\n",
    "import math\n",
    "import constDirectories as cd\n",
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cd.TRAIN_CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(cd.TRAIN_CSV)\n",
    "df = df_train\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['blank'] =0\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "count = 0 \n",
    "for i in df.index:\n",
    "    filename=cd.TRAIN_IMAGE_DIR + df['id'][i]+ '.png'\n",
    "    img = Image.open(filename)\n",
    "    if not img.getbbox(): \n",
    "        #print (df['id'][i],\"blank image\")\n",
    "        df['blank'][i]=1\n",
    "        count+=1\n",
    "print(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfNotNull = df[df['blank']==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfNotNull.to_csv('D:\\\\_0Luciano\\\\_0PHD\\\\datasets//tgs-salt/trainNOTNULL.csv',index=False)"
   ]
  }
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