Visual Genome.ipynb

{
 "cells": [
  {
   "metadata": {
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "%cd ~/src/visual_genome_python_driver/\nfrom src import local as vg\nfrom PIL import Image\nfrom os import path",
   "execution_count": null,
   "outputs": []
  },
  {
   "metadata": {
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "%cd ~/data/VisualGenome\nimages = vg.GetAllImageData('.')\nannotations = vg.GetAllRegionDescriptions('.')",
   "execution_count": null,
   "outputs": []
  },
  {
   "metadata": {
    "scrolled": false,
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "with open('subdescriptions.txt', 'w') as f:\n    for regions in annotations:\n        if len(regions) == 0:\n            continue\n            \n        image_id = regions[0].image.id\n        filename = 'images/{0}.jpg'.format(image_id)\n        if not path.isfile(filename):\n            continue\n        \n        img = Image.open(filename).convert('RGB')\n        for region in regions:\n            if region.image.id != image_id:\n                continue\n                \n            box = (region.x, region.y, region.x + region.width, region.y + region.height)\n            if region.width < 224 or region.height < 224  or box[0] < 0 or box[1] < 0 or box[2] > img.width or box[3] > img.height:\n                continue\n            \n            subimg = img.crop(box)\n            filename = 'subimages/{0}_{1}.jpg'.format(image_id, region.id)\n            subimg.save(filename, quality=100)\n            f.write('{0} | {1}\\n'.format(filename, str(region.phrase)))",
   "execution_count": null,
   "outputs": []
  }
 ],
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