docs/code/merge_csv.ipynb

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   "source": [
    "from pandas import Series, DataFrame\n",
    "from PIL import Image\n",
    "import pandas as pd\n",
    "import csv\n",
    "import glob\n",
    "import os\n",
    "\n",
    "#\n",
    "# ------------------------------\n",
    "#  Real     id        name\n",
    "#   0  ==   1    ==   zero\n",
    "#   1  ==   2    ==   one\n",
    "#   2  ==   3    ==   two\n",
    "#   3  ==   4    ==   three\n",
    "#   4  ==   5    ==   four\n",
    "#   5  ==   6    ==   five\n",
    "#   6  ==   7    ==   six\n",
    "#   7  ==   8    ==   seven\n",
    "#   8  ==   9    ==   eight\n",
    "#   9  ==  10    ==   nine\n",
    "# ------------------------------\n",
    "#\n",
    "\n",
    "os.chdir(\"/home/internship/anaconda3/envs/cyp\\\n",
    "/lib/python3.6/site-packages/tensorflow\\\n",
    "/models/research/object_detection/images\")\n",
    "path = '.'\n",
    "files_in_dir = [f for f in os.listdir(path) if f.endswith('csv')]\n",
    "first = True\n",
    "column_name = [\"class\", \"xmin\", \"ymin\", \"bbox_width\", \"bbox_height\"]\n",
    "for filenames in files_in_dir:\n",
    "    df = pd.read_csv(filenames, names=column_name)\n",
    "    image_name = filenames[:-3] + \"png\"\n",
    "    \n",
    "    im = Image.open(image_name)\n",
    "    im_width, im_height = im.size\n",
    "    \n",
    "    \n",
    "    df['filename'] = image_name  \n",
    "    df['width'] = im_width\n",
    "    df['height'] = im_height\n",
    "    df['xmax'] = df['xmin'] + df['bbox_width']\n",
    "    df['ymax'] = df['ymin'] + df['bbox_height']\n",
    "    df = DataFrame(df, columns = ['filename', 'width', 'height', 'class','xmin','ymin','xmax', 'ymax'])\n",
    "    df['class'] = df['class'].replace({0: 'zero', 1: 'one', 2: 'two', 3: 'three',\n",
    "                                   4: 'four', 5: 'five', 6: 'six', 7: 'seven', 8: 'eight',\n",
    "                                   9: 'nine'})\n",
    "\n",
    "    # train_labels, test_labels\n",
    "    if(first): \n",
    "        df.to_csv('train_labels.csv', mode='a', index=False)\n",
    "        first = False\n",
    "    else:\n",
    "        df.to_csv('train_labels.csv', header=None, mode='a', index=False)\n",
    "        \n",
    "    \n",
    "print(\"Done\")"
   ]
  }
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