prepareData.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import cv2\n",
    "import glob\n",
    "import random\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "videos = glob.glob('../deep-dataset/traces/*.mp4')\n",
    "mos = np.loadtxt('../deep-dataset/mos.txt')\n",
    "size = len(videos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scaleDownVideos(videos, path):\n",
    "    for video in videos:\n",
    "        os.system('ffmpeg -i '+video+' -qp 1 -vf scale=120:68 -strict -2 '+path+'/'+video.split('/')[-1])\n",
    "\n",
    "def extractImages(videos, path):\n",
    "    for video in videos:\n",
    "        os.system('ffmpeg -i '+video+' -vf fps=10 '+path+'/'+video.split('/')[-1][:-4]+'_%d.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaleDownVideos(videos, '../deep-dataset/traces/images')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "videos = glob.glob('../deep-dataset/traces/images/*.mp4')\n",
    "extractImages(videos, '../deep-dataset/traces/images')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "videos = glob.glob('../deep-dataset/traces/images/*.mp4')\n",
    "def makeImagesNumpy(videos, mos, path):\n",
    "    mosNumpyArray = np.zeros((size, 5))\n",
    "    for video in videos:\n",
    "        images = glob.glob(path+'/'+video.split('/')[-1][:-4]+'_*.png')\n",
    "        images = images[:200]\n",
    "        frames = []\n",
    "        for image in images:\n",
    "            image = cv2.imread(image)\n",
    "            image = np.array(image)\n",
    "            frames.append(image)\n",
    "        frames = np.array(frames)\n",
    "        np.save('../deep-dataset/numpys/'+video.split('/')[-1][:-4]+'.npy', frames)\n",
    "        mosIndex = int(video.split('/')[-1][:-4].split('_')[1])\n",
    "        m = int(round(mos[mosIndex-1]-1))\n",
    "        mosNumpyArray[mosIndex-1][m] = 1\n",
    "        np.save('../deep-dataset/numpys/'+video.split('/')[-1][:-4]+'_mos.npy', mosNumpyArray[mosIndex-1])\n",
    "makeImagesNumpy(videos, mos, '../deep-dataset/traces/images')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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