Chapter12/Chapter12_cocojson_AWSJSON_train.ipynb

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   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "#Chapter 12 - coco-combine json to individual json files convert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import logging\n",
    "\n",
    "def get_coco_mapper():\n",
    "    original_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20,\n",
    "                    21, 22, 23, 24, 25, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,\n",
    "                    41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,\n",
    "                    61, 62, 63, 64, 65, 67, 70, 72, 73, 74, 75, 76, 77, 78, 79, 80,\n",
    "                    81, 82, 84, 85, 86, 87, 88, 89, 90]\n",
    "    iter_counter = 0\n",
    "    COCO = {}\n",
    "    for orig in original_list:\n",
    "        COCO[orig] = iter_counter\n",
    "        iter_counter += 1\n",
    "    return COCO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_mapper_fn(map):  \n",
    "    def mapper(in_category):\n",
    "        return map[in_category]\n",
    "    return mapper\n",
    "\n",
    "fix_index_mapping = get_mapper_fn(get_coco_mapper())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%bash\n",
    "#Create folders to store the data and annotation files\n",
    "mkdir generated train train_annotation validation validation_annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "file_name = 'test_cocoformat.json'\n",
    "with open(file_name) as f:\n",
    "    js = json.load(f)\n",
    "    images = js['images']\n",
    "    categories = js['categories']\n",
    "    annotations = js['annotations']\n",
    "    for i in images:\n",
    "        jsonFile = i['file_name']\n",
    "        jsonFile = jsonFile.split('.')[0]+'.json'\n",
    "        \n",
    "        line = {}\n",
    "        line['file'] = i['file_name']\n",
    "        line['image_size'] = [{\n",
    "            'width':int(i['width']),\n",
    "            'height':int(i['height']),\n",
    "            'depth':3\n",
    "        }]\n",
    "        line['annotations'] = []\n",
    "        line['categories'] = []\n",
    "        for j in annotations:\n",
    "            if j['image_id'] == i['id'] and len(j['bbox']) > 0:\n",
    "                line['annotations'].append({\n",
    "                    'class_id':int(fix_index_mapping(j['category_id'])),\n",
    "                    'top':int(j['bbox'][1]),\n",
    "                    'left':int(j['bbox'][0]),\n",
    "                    'width':int(j['bbox'][2]),\n",
    "                    'height':int(j['bbox'][3])\n",
    "                })\n",
    "                class_name = ''\n",
    "                for k in categories:\n",
    "                    if int(j['category_id']) == k['id']:\n",
    "                        class_name = str(k['name'])\n",
    "                assert class_name is not ''\n",
    "                line['categories'].append({\n",
    "                    'class_id':int(j['category_id']),\n",
    "                    'name':class_name\n",
    "                })\n",
    "        if line['annotations']:\n",
    "            with open(os.path.join('generated', jsonFile),'w') as p:\n",
    "                json.dump(line,p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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