summary_mydataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2, os, json, math, time, tqdm\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from collections import Counter, OrderedDict, defaultdict\n",
    "from zipfile import ZipFile\n",
    "import skimage.io as io\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import matplotlib.patches as mpatches\n",
    "from matplotlib.patches import Polygon \n",
    "from matplotlib.collections import PatchCollection\n",
    "from IPython.display import display, HTML\n",
    "\n",
    "DIR = './data' #@@@ OVERRIDE: Path of folder with all annotations and images "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DATASETS ANALYSIS\n",
    "**Dataset Folder Structure**  \n",
    "Images and annotations have been organized in a folder with the following structure. 'USER' refers to DeepFashion2 wild images, while 'SHOP' refers to DeepFashion2 street images.\n",
    "\n",
    "- data\n",
    "    - ```shop_df2```\n",
    "        * ```train```\n",
    "            - image: ```df2_train_shop``` (filenames from 0 to 2499)\n",
    "            - annos: coco_df2_ts_2500.json\n",
    "        * ```validation```\n",
    "            - image: ```df2_val_shop``` (filenames from 0 to 499)\n",
    "            - annos: coco_df2_vs_500.json\n",
    "    - ```user_df2```\n",
    "        * ```train```\n",
    "            - image: ```df2_train_user``` (filenames from 0 to 4999)\n",
    "            - annos: coco_df2_tu_5000.json\n",
    "        * ```validation```\n",
    "            - image: ```df2_val_user``` (filenames from 0 to 499)\n",
    "            - annos: coco_df2_vu_500.json\n",
    "    - ```shop_user_df2```\n",
    "        * ```validation``` \n",
    "            - image: ```df2_val_shop_user``` (filenames from 0 to 999)\n",
    "            - annos: coco_df2_vsu_100.json    \n",
    "    - test\n",
    "        - image: ```dlcv_test``` (filenames from 0 to 499)\n",
    "        - annos: coco_test_500.json\n",
    "\n",
    "**Dataset Creation**  \n",
    "Train and Validation Sets - Images are from DeepFashion2 dataset, specifically the validation set. Images are 50% from fashion e-commerce (shop) and 50% from photos of consumers (user). Annotations have been created manually with VGG Image Annotator and converted to COCO format using the function in ```convertes.ipynb```. Categories have been defined considering the catalogs of major fahsion e-commerce ([macy's](#https://www.macys.com/), [zalando](#https://www.zalando.it/), [asos](#https://www.asos.com/women/), [yoox](https://www.yoox.com/)) and trying to do an intersection of Fashionpedia's, ModaNet's and DeepFashion's classes. \n",
    "\n",
    "Test Set - Images are from Instagram. Annotations have been created manually from scratch with VGG Image Annotator and converted to COCO format using the function in ```convertes.ipynb```. Same story for the categories. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_side_by_side(dfs:list, captions:list):\n",
    "    \"\"\"Display tables side by side to save vertical space\n",
    "    Input:\n",
    "        dfs: list of pandas.DataFrame\n",
    "        captions: list of table captions\n",
    "    \"\"\"\n",
    "    output = \"\"\n",
    "    combined = dict(zip(captions, dfs))\n",
    "    for caption, df in combined.items():\n",
    "        output += df.style.set_table_attributes(\"style='display:inline'\").set_caption(caption)._repr_html_()\n",
    "        output += \"\\xa0\\xa0\\xa0\"\n",
    "    display(HTML(output))\n",
    "\n",
    "def plot_annotations(img_path, anns, cats):\n",
    "    plt.rcParams['figure.figsize'] = [10, 8]\n",
    "    plt.subplot(1, 2, 1)\n",
    "    plt.axis('off')\n",
    "    imgArray = io.imread(img_path)\n",
    "    plt.imshow(imgArray)\n",
    "\n",
    "    plt.subplot(1, 2, 2)\n",
    "    plt.imshow(imgArray)\n",
    "    plt.axis('off')\n",
    "\n",
    "    ax = plt.gca()\n",
    "    ax.set_autoscale_on(False)\n",
    "\n",
    "    polygons = []\n",
    "    color = []\n",
    "    maps = []\n",
    "\n",
    "    for ann in anns: #anns = [{annotation1}, {}, {}]\n",
    "        c = (np.random.random((1, 3))*0.6+0.4).tolist()[0] # for each annotation get 3 random numbers [0, 1]\n",
    "        for seg in ann['segmentation']:                    # for each segmentation [list of lists] get vertices      \n",
    "            poly = np.array(seg).reshape((int(len(seg)/2), 2)) # get a matrix len(seg)/2 x 2 (each vertex is an array)\n",
    "            polygons.append(Polygon(poly))\n",
    "            color.append(c) \n",
    "            if (ann['id'], cats[ann['category_id']-1]['name'], mcolors.to_hex(c)) not in maps:\n",
    "                maps.append((ann['id'], cats[ann['category_id']-1]['name'], mcolors.to_hex(c)))\n",
    "\n",
    "    p = PatchCollection(polygons, facecolor=color, linewidths=0, alpha=0.4)\n",
    "    ax.add_collection(p)\n",
    "    p = PatchCollection(polygons, facecolor='none', edgecolors=color, linewidths=2)\n",
    "    ax.add_collection(p)\n",
    "\n",
    "    #  text\n",
    "    for i, ann in enumerate(anns):\n",
    "        print(\"Segmentation {}:\".format(i))\n",
    "        print(\"\\tCategory: {}\".format(cats[ann[\"category_id\"]-1][\"name\"]))\n",
    "\n",
    "    # legend\n",
    "    pops = [mpatches.Patch(color=maps[i][2], label=maps[i][1]) for i in range(len(maps))]\n",
    "    plt.legend(handles=pops, fontsize='large');\n",
    "\n",
    "def categories_frequency(dataset_annos, name_dataset, relative_frequency=False):\n",
    "    counts = []\n",
    "    num_masks = len(dataset_annos['annotations'])\n",
    "    cat_count =  dict(OrderedDict(Counter([d['category_id'] for d in dataset_annos['annotations']]).most_common()))\n",
    "    cats = [i for i in range(1, len(dataset_annos['categories'])+1)]\n",
    "    if len(counts) != len(dataset_annos['categories']):\n",
    "        adding = {i:0 for i in cats if i not in cat_count.keys()}\n",
    "        cat_count_all = cat_count | adding\n",
    "    for k, v in cat_count_all.items():\n",
    "        counts.append([dataset_annos['categories'][k-1]['name'], v, round((v/num_masks)*100, 1)])\n",
    "    df = pd.DataFrame(counts, columns = ['category', '#masks', 'frequency'])\n",
    "    \n",
    "    # Plot\n",
    "    fig, ax = plt.subplots(figsize=(17,5))\n",
    "    fig.suptitle(name_dataset.upper(), fontweight='bold')\n",
    "    x = df['category'].tolist()\n",
    "    if relative_frequency: \n",
    "        y = df['frequency'].tolist()\n",
    "        ax.set_ylabel('Number of masks (%)')\n",
    "    else:\n",
    "        y = df['#masks'].tolist()\n",
    "        ax.set_ylabel('Number of masks')\n",
    "    #clrs = ['grey' if x >  else 'red' for x in y]\n",
    "    ax.bar(x,y, width=0.4)\n",
    "    ax.set_title('Number of masks by CATEGORY')\n",
    "    labels = ax.get_xticklabels()\n",
    "    for label, v in zip(labels, y):\n",
    "        if v == 0:\n",
    "            label.set_color('r')\n",
    "\n",
    "    fig.autofmt_xdate(rotation=45)\n",
    "    plt.show();\n",
    "    return df.round(decimals=2)\n",
    "\n",
    "def category_area(dataset_annos):\n",
    "    a = defaultdict(list)\n",
    "    for d in dataset_annos['annotations']:\n",
    "        img = dataset_annos['images'][d['image_id']]\n",
    "        img_size = img['width']*img['height']*3\n",
    "        a[d['category_id']].append(d['area']/img_size)\n",
    "\n",
    "    avg_area_cat = {k:round(np.average(v)*100,2) for k,v in a.items()}\n",
    "    cats = [i for i in range(1, len(dataset_annos['categories'])+1)]\n",
    "    if len(avg_area_cat) != len(dataset_annos['categories']):\n",
    "        adding = {i:0 for i in cats if i not in avg_area_cat.keys()}\n",
    "        avg_area_cat = avg_area_cat | adding\n",
    "    avg_area_cat = {dataset_annos['categories'][k-1]['name']:round(v,1) for k,v in dict(sorted(avg_area_cat.items(), key = lambda x: x[1], reverse = True)).items()}\n",
    "    df = pd.DataFrame({'category':avg_area_cat.keys(), 'avg(segmentation area) - % of image area':avg_area_cat.values()})\n",
    "    return df.round(decimals=2)\n",
    "\n",
    "def img_resolution(dataset_annos):\n",
    "    return round(np.mean([d['width']*d['height']*3 for d in dataset_annos['images']])/1000000,2)\n",
    "\n",
    "def img_type(dataset_annos):\n",
    "    map = {\"0\" : '1_person', \"1\":'people', \"2\":'no_people', \"0_3\":'1_person_selfie', \"1_3\":'people_selfie'}\n",
    "    num_imgs = len(dataset_annos['images'])\n",
    "    dd = []\n",
    "    for d in dataset_annos['images']:\n",
    "        type = '_'.join([i.strip() for i in d['people']])\n",
    "        if type in map.keys():\n",
    "            dd.append(type)\n",
    "        else:\n",
    "            dd.append('0')\n",
    "\n",
    "    count = {map[k]:round(v/num_imgs*100, 2) for k,v in Counter(dd).items()}\n",
    "    df = pd.DataFrame(count, index=['%images'])\n",
    "    return df.round(decimals=2)\n",
    "\n",
    "def compute_statistics(dataset_annos, index:list):\n",
    "    dict_numb = {\n",
    "        '#categories' : len(dataset_annos['categories']),\n",
    "        '#images' : len(dataset_annos['images']),\n",
    "        '#masks' : len(dataset_annos['annotations'])}\n",
    "    stats = pd.DataFrame(dict_numb, index=index)\n",
    "    stats['avg(#masks) - per image'] = round(stats.iloc[:, 2]/stats.iloc[:, 1], 2)\n",
    "\n",
    "    lens = []\n",
    "    try:\n",
    "        for d in dataset_annos['annotations']:\n",
    "            assert len(d['segmentation']) == 1\n",
    "            lens.append(len(d['segmentation'][0]))\n",
    "        stats['avg(#vertices) - per mask'] = round(np.mean(lens),2)\n",
    "    except:\n",
    "        pass\n",
    "    return stats.round(decimals=2)\n",
    "\n",
    "def show_all(annos_json, name:str):\n",
    "    print('\\nStatistics about annotation')\n",
    "    display(compute_statistics(annos_json, [name]))\n",
    "    print('\\nStatistics about images')\n",
    "    print('\\navg(image size) - Mpx: ', img_resolution(annos_json))\n",
    "    display(img_type(annos_json))\n",
    "    print('\\nStatistics about categories')\n",
    "    freq = categories_frequency(annos_json, name)\n",
    "    area = category_area(annos_json)\n",
    "    display_side_by_side([freq.round(decimals=2), area.round(decimals=2)], ['Satistics by category', ''])   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TRAIN - VALIDATION SETS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. DeepFashion2 - User (WILD)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Train Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Train - User</th>\n",
       "      <td>30</td>\n",
       "      <td>5000</td>\n",
       "      <td>7897</td>\n",
       "      <td>1.58</td>\n",
       "      <td>155.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             #categories  #images  #masks  \\\n",
       "DeepFashion2 - Train - User           30     5000    7897   \n",
       "\n",
       "                             avg(#masks) - per image  \\\n",
       "DeepFashion2 - Train - User                     1.58   \n",
       "\n",
       "                             avg(#vertices) - per mask  \n",
       "DeepFashion2 - Train - User                     155.89  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  0.85\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1_person</th>\n",
       "      <th>1_person_selfie</th>\n",
       "      <th>no_people</th>\n",
       "      <th>people</th>\n",
       "      <th>people_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>40.6</td>\n",
       "      <td>27.24</td>\n",
       "      <td>30.88</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "         1_person  1_person_selfie  no_people  people  people_selfie\n",
       "%images      40.6            27.24      30.88    0.72           0.56"
      ]
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     "metadata": {},
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     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >2212</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >28.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >dress</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >1440</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >18.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >skirt</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >1057</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >13.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >pants</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >580</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >7.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >shirt</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >483</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >6.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >shorts</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >332</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >4.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >jacket</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >288</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >3.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >252</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >3.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >jeans</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >184</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >2.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >180</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >2.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >heels</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >147</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >1.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >bag</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >114</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >1.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >106</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >1.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >95</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >joggers</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >80</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >sweater</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >76</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >coat</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >68</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >0.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >boots</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >49</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >leggings</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >44</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >39</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >hat</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >32</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >slippers</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >26</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >7</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >blazer</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >3</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >2</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >1</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >underwear</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >robe</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2a615466_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >25.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >sweater</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >16.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >15.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >shirt</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >15.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >15.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >jacket</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >14.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >coat</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >12.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >dress</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >12.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >top</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >10.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >10.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >skirt</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >8.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >joggers</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >8.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >8.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >shorts</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >7.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >jeans</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >6.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >blazer</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >6.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >pants</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >5.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >leggings</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >3.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >bag</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >1.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >hat</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >1.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >boots</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >heels</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >underwear</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >robe</td>\n",
       "                        <td id=\"T_2a62d480_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_df2tu = os.path.join(DIR, 'user_df2/train/coco_df2_tu_5000.json')\n",
    "df2tu = json.load(open(path_df2tu))\n",
    "show_all(df2tu, 'DeepFashion2 - Train - User')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Validation Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Validation - User</th>\n",
       "      <td>30</td>\n",
       "      <td>505</td>\n",
       "      <td>925</td>\n",
       "      <td>1.83</td>\n",
       "      <td>144.44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  #categories  #images  #masks  \\\n",
       "DeepFashion2 - Validation - User           30      505     925   \n",
       "\n",
       "                                  avg(#masks) - per image  \\\n",
       "DeepFashion2 - Validation - User                     1.83   \n",
       "\n",
       "                                  avg(#vertices) - per mask  \n",
       "DeepFashion2 - Validation - User                     144.44  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  0.87\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>no_people</th>\n",
       "      <th>1_person</th>\n",
       "      <th>1_person_selfie</th>\n",
       "      <th>people</th>\n",
       "      <th>people_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>8.91</td>\n",
       "      <td>61.58</td>\n",
       "      <td>28.12</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         no_people  1_person  1_person_selfie  people  people_selfie\n",
       "%images       8.91     61.58            28.12    0.79           0.59"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >280</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >30.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >skirt</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >131</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >14.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >dress</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >100</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >10.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >pants</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >66</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >7.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >shorts</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >55</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >5.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >shirt</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >48</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >5.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >40</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >4.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >35</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >3.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >jeans</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >29</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >3.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jacket</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >28</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >3.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >heels</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >25</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >2.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >18</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >1.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >joggers</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >17</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >1.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >sweater</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >15</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >bag</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >11</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >8</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >0.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >boots</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >6</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >hat</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >6</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >2</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >slippers</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >2</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >2</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >blazer</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >1</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >underwear</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >robe</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >coat</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >leggings</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2b44ade2_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >blazer</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >24.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >16.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >jacket</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >14.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >sweater</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >12.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >12.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >shirt</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >11.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >joggers</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >9.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >dress</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >8.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >top</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >7.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jeans</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >6.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >shorts</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >5.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >skirt</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >5.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >pants</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >4.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >0.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >hat</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >bag</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >boots</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >slippers</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >heels</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >underwear</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >robe</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >coat</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >leggings</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2b45ec66_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_df2vu =  os.path.join(DIR, 'user_df2/validation/coco_df2_vu_500.json')\n",
    "df2vu = json.load(open(path_df2vu))\n",
    "show_all(df2vu, 'DeepFashion2 - Validation - User')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. DeepFashion2 - Shop (STREET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Train Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Train - Shop</th>\n",
       "      <td>30</td>\n",
       "      <td>2500</td>\n",
       "      <td>6002</td>\n",
       "      <td>2.4</td>\n",
       "      <td>141.11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             #categories  #images  #masks  \\\n",
       "DeepFashion2 - Train - Shop           30     2500    6002   \n",
       "\n",
       "                             avg(#masks) - per image  \\\n",
       "DeepFashion2 - Train - Shop                      2.4   \n",
       "\n",
       "                             avg(#vertices) - per mask  \n",
       "DeepFashion2 - Train - Shop                     141.11  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  1.63\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1_person</th>\n",
       "      <th>people</th>\n",
       "      <th>no_people</th>\n",
       "      <th>1_person_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>94.88</td>\n",
       "      <td>0.84</td>\n",
       "      <td>1.68</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         1_person  people  no_people  1_person_selfie\n",
       "%images     94.88    0.84       1.68              2.6"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >1431</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >23.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >dress</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >649</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >10.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >pants</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >569</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >9.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >skirt</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >507</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >8.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >497</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >8.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >shorts</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >418</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >7.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >bag</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >381</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >6.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >hat</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >274</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >4.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >256</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >4.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >shirt</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >211</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >heels</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >180</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >3.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >jeans</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >147</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >boots</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >104</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >1.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >94</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >jacket</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >78</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >sweater</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >59</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >44</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >0.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >joggers</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >40</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >leggings</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >17</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >coat</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >15</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >14</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >blazer</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >10</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >7</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >underwear</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >robe</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2c5e6c9a_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >dress</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >5.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >shirt</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >5.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >coat</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >5.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >sweater</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >5.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >joggers</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >4.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >skirt</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >4.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >jacket</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >4.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >leggings</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >4.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >top</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >4.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >4.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >blazer</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >4.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >3.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >jeans</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >3.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >pants</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >shorts</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >3.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >3.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >3.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >bag</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >0.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >hat</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >boots</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >heels</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >underwear</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >robe</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2c5f9cd2_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_df2ts =  os.path.join(DIR, 'shop_df2/train/coco_df2_ts_2500.json')\n",
    "df2ts = json.load(open(path_df2ts))\n",
    "show_all(df2ts, 'DeepFashion2 - Train - Shop')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Validation Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Validation - Shop</th>\n",
       "      <td>30</td>\n",
       "      <td>501</td>\n",
       "      <td>1131</td>\n",
       "      <td>2.26</td>\n",
       "      <td>146.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  #categories  #images  #masks  \\\n",
       "DeepFashion2 - Validation - Shop           30      501    1131   \n",
       "\n",
       "                                  avg(#masks) - per image  \\\n",
       "DeepFashion2 - Validation - Shop                     2.26   \n",
       "\n",
       "                                  avg(#vertices) - per mask  \n",
       "DeepFashion2 - Validation - Shop                     146.89  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  1.64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1_person</th>\n",
       "      <th>1_person_selfie</th>\n",
       "      <th>no_people</th>\n",
       "      <th>people</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>94.41</td>\n",
       "      <td>2.79</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         1_person  1_person_selfie  no_people  people\n",
       "%images     94.41             2.79        2.0     0.8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >288</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >25.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >dress</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >123</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >10.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >skirt</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >115</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >10.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >pants</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >101</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >8.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >shorts</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >88</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >7.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >bag</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >61</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >5.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >58</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >5.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >55</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >4.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >hat</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >41</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >3.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jeans</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >37</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >3.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >shirt</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >34</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >3.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >heels</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >32</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >2.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >jacket</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >21</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >1.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >21</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >boots</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >20</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >sweater</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >18</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >10</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >0.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >joggers</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >4</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >2</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >2</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >slippers</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >underwear</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >robe</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >coat</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >leggings</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >blazer</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2d53de32_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >joggers</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >7.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >shirt</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >6.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >sweater</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >5.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >5.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >dress</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >5.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >skirt</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >4.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >jacket</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >4.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >top</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >4.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >4.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >pants</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >3.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >shorts</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >3.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >3.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >jeans</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >bag</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >hat</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >boots</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >heels</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >slippers</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >underwear</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >robe</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >coat</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >leggings</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >blazer</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2d57563e_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_df2vs =  os.path.join(DIR, 'shop/validation/coco_df2_vs_500.json')\n",
    "df2vs = json.load(open(path_df2vs))\n",
    "show_all(df2vs, 'DeepFashion2 - Validation - Shop')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3. DeepFashion2 - User + Shop (WILD + STREET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Train Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Train - User + Shop</th>\n",
       "      <td>30</td>\n",
       "      <td>7500</td>\n",
       "      <td>13899</td>\n",
       "      <td>1.85</td>\n",
       "      <td>149.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    #categories  #images  #masks  \\\n",
       "DeepFashion2 - Train - User + Shop           30     7500   13899   \n",
       "\n",
       "                                    avg(#masks) - per image  \\\n",
       "DeepFashion2 - Train - User + Shop                     1.85   \n",
       "\n",
       "                                    avg(#vertices) - per mask  \n",
       "DeepFashion2 - Train - User + Shop                     149.51  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  1.11\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1_person</th>\n",
       "      <th>1_person_selfie</th>\n",
       "      <th>no_people</th>\n",
       "      <th>people</th>\n",
       "      <th>people_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>58.69</td>\n",
       "      <td>19.03</td>\n",
       "      <td>21.15</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         1_person  1_person_selfie  no_people  people  people_selfie\n",
       "%images     58.69            19.03      21.15    0.76           0.37"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >3643</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >26.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >dress</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >2089</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >15.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >skirt</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >1564</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >11.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >pants</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >1149</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >8.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >shorts</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >750</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >5.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >749</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >5.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >shirt</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >694</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >5.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >bag</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >495</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >3.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >436</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >3.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jacket</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >366</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >2.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >jeans</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >331</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >heels</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >327</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >hat</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >306</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >2.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >boots</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >153</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >150</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >sweater</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >135</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >133</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >joggers</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >120</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >109</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >coat</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >83</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >leggings</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >61</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >slippers</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >26</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >14</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >blazer</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >13</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >2</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >1</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >underwear</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >robe</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2e7c0320_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >25.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >jacket</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >12.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >shirt</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >12.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >sweater</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >11.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >11.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >coat</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >11.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >dress</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >10.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >9.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >9.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >top</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >8.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >skirt</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >7.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >joggers</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >7.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >5.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >jeans</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >5.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >shorts</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >5.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >blazer</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >4.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >pants</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >4.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >leggings</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >3.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >bag</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >hat</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >boots</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >heels</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >underwear</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >robe</td>\n",
       "                        <td id=\"T_2e7db972_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First need to merge two separate json file of Train - Shop and Train - User \n",
    "ctu = df2tu.copy()\n",
    "cts = df2ts.copy()\n",
    "\n",
    "i = 5000\n",
    "for d in cts['images']:\n",
    "    d['id'] = i\n",
    "    d['file_name'] = str(i).zfill(6)+'.jpg'\n",
    "    ctu['images'].append(d)\n",
    "    i+=1\n",
    "\n",
    "j = 7897\n",
    "for d in cts['annotations']:\n",
    "    d['id'] = j\n",
    "    d['image_id'] += 5000\n",
    "    ctu['annotations'].append(d)\n",
    "    j += 1\n",
    "\n",
    "df2tsu = {\n",
    "    'info':df2ts['info'],\n",
    "    'lincenses': '', \n",
    "    'images': ctu['images'], \n",
    "    'annotations' : ctu['annotations'],\n",
    "    'categories': df2ts['categories']\n",
    "}\n",
    "\n",
    "show_all(df2tsu, 'DeepFashion2 - Train - User + Shop')   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Validation Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DeepFashion2 - Validation - User + Shop</th>\n",
       "      <td>30</td>\n",
       "      <td>1006</td>\n",
       "      <td>2056</td>\n",
       "      <td>2.04</td>\n",
       "      <td>145.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         #categories  #images  #masks  \\\n",
       "DeepFashion2 - Validation - User + Shop           30     1006    2056   \n",
       "\n",
       "                                         avg(#masks) - per image  \\\n",
       "DeepFashion2 - Validation - User + Shop                     2.04   \n",
       "\n",
       "                                         avg(#vertices) - per mask  \n",
       "DeepFashion2 - Validation - User + Shop                     145.79  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  1.26\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1_person</th>\n",
       "      <th>1_person_selfie</th>\n",
       "      <th>no_people</th>\n",
       "      <th>people</th>\n",
       "      <th>people_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>77.93</td>\n",
       "      <td>15.51</td>\n",
       "      <td>5.47</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         1_person  1_person_selfie  no_people  people  people_selfie\n",
       "%images     77.93            15.51       5.47     0.8            0.3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >568</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >27.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >skirt</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >246</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >12.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >dress</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >223</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >10.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >pants</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >167</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >8.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >shorts</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >143</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >7.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >98</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >4.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >90</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >4.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >shirt</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >82</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >4.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >bag</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >72</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jeans</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >66</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >3.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >heels</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >57</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >2.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >jacket</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >49</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >hat</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >47</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >2.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >sweater</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >33</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >29</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >28</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >boots</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >26</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >1.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >joggers</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >21</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >4</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >4</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >slippers</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >2</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >blazer</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >1</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >underwear</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >robe</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >coat</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >leggings</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2f2e29f6_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >blazer</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >24.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >jacket</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >10.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >shirt</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >9.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >9.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >joggers</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >9.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >sweater</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >8.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >dress</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >6.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >6.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >top</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >5.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >jeans</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >5.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >skirt</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >4.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >shorts</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >4.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >pants</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >4.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >3.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >3.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >bag</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >hat</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >boots</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >0.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >slippers</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >heels</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >underwear</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >robe</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >coat</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >leggings</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2f2f4cd2_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_df2vsu =  os.path.join(DIR, 'shop_user_df2/validation/coco_df2_vsu_1000.json')\n",
    "df2vsu = json.load(open(path_df2vsu))\n",
    "show_all(df2vsu, 'DeepFashion2 - Validation - User + Shop')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about annotation\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#categories</th>\n",
       "      <th>#images</th>\n",
       "      <th>#masks</th>\n",
       "      <th>avg(#masks) - per image</th>\n",
       "      <th>avg(#vertices) - per mask</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Test</th>\n",
       "      <td>30</td>\n",
       "      <td>500</td>\n",
       "      <td>1893</td>\n",
       "      <td>3.79</td>\n",
       "      <td>82.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      #categories  #images  #masks  avg(#masks) - per image  \\\n",
       "Test           30      500    1893                     3.79   \n",
       "\n",
       "      avg(#vertices) - per mask  \n",
       "Test                      82.12  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about images\n",
      "\n",
      "avg(image size) - Mpx:  3.21\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>people_selfie</th>\n",
       "      <th>no_people</th>\n",
       "      <th>1_person</th>\n",
       "      <th>people</th>\n",
       "      <th>1_person_selfie</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>%images</th>\n",
       "      <td>3.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>61.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         people_selfie  no_people  1_person  people  1_person_selfie\n",
       "%images            3.8        3.4      61.0    26.0              5.8"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Statistics about categories\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1224x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><caption>Satistics by category</caption><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >#masks</th>        <th class=\"col_heading level0 col2\" >frequency</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >top</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >478</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow0_col2\" class=\"data row0 col2\" >25.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >325</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow1_col2\" class=\"data row1 col2\" >17.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >shorts</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >153</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow2_col2\" class=\"data row2 col2\" >8.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >hat</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >151</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow3_col2\" class=\"data row3 col2\" >8.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >117</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow4_col2\" class=\"data row4 col2\" >6.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >pants</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >117</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow5_col2\" class=\"data row5 col2\" >6.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >jacket</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >92</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow6_col2\" class=\"data row6 col2\" >4.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >jeans</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >66</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow7_col2\" class=\"data row7 col2\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >58</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow8_col2\" class=\"data row8 col2\" >3.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >shirt</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >55</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow9_col2\" class=\"data row9 col2\" >2.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >bag</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >53</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow10_col2\" class=\"data row10 col2\" >2.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >dress</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >45</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow11_col2\" class=\"data row11 col2\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >heels</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >33</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow12_col2\" class=\"data row12 col2\" >1.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >leggings</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >32</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow13_col2\" class=\"data row13 col2\" >1.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >boots</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >29</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow14_col2\" class=\"data row14 col2\" >1.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >joggers</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >26</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow15_col2\" class=\"data row15 col2\" >1.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >blazer</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >22</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow16_col2\" class=\"data row16 col2\" >1.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >skirt</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >12</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow17_col2\" class=\"data row17 col2\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >coat</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >10</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow18_col2\" class=\"data row18 col2\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >sweater</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >9</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow19_col2\" class=\"data row19 col2\" >0.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >7</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow20_col2\" class=\"data row20 col2\" >0.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >2</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow21_col2\" class=\"data row21 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >1</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow22_col2\" class=\"data row22 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow23_col2\" class=\"data row23 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >underwear</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow25_col2\" class=\"data row25 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow26_col2\" class=\"data row26 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >robe</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow27_col2\" class=\"data row27 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow28_col2\" class=\"data row28 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0</td>\n",
       "                        <td id=\"T_2fa1d8b0_9176_11ec_95bc_9801a7d07c4frow29_col2\" class=\"data row29 col2\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   <style  type=\"text/css\" >\n",
       "</style><table id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4f\" style='display:inline'><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >category</th>        <th class=\"col_heading level0 col1\" >avg(segmentation area) - % of image area</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow0_col0\" class=\"data row0 col0\" >sweater</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow0_col1\" class=\"data row0 col1\" >7.800000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow1_col0\" class=\"data row1 col0\" >sweatshirt</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow1_col1\" class=\"data row1 col1\" >6.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow2_col0\" class=\"data row2 col0\" >swimsuit</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow2_col1\" class=\"data row2 col1\" >5.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow3_col0\" class=\"data row3 col0\" >jacket</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow3_col1\" class=\"data row3 col1\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow4_col0\" class=\"data row4 col0\" >blazer</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow4_col1\" class=\"data row4 col1\" >3.500000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow5_col0\" class=\"data row5 col0\" >top</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow5_col1\" class=\"data row5 col1\" >3.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow6_col0\" class=\"data row6 col0\" >bag</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow6_col1\" class=\"data row6 col1\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow7_col0\" class=\"data row7 col0\" >shirt</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow7_col1\" class=\"data row7 col1\" >2.400000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow8_col0\" class=\"data row8 col0\" >dress</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow8_col1\" class=\"data row8 col1\" >2.300000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow9_col0\" class=\"data row9 col0\" >leggings</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow9_col1\" class=\"data row9 col1\" >2.200000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow10_col0\" class=\"data row10 col0\" >coat</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow10_col1\" class=\"data row10 col1\" >2.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow11_col0\" class=\"data row11 col0\" >joggers</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow11_col1\" class=\"data row11 col1\" >2.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow12_col0\" class=\"data row12 col0\" >skirt</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow12_col1\" class=\"data row12 col1\" >2.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow13_col0\" class=\"data row13 col0\" >jeans</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow13_col1\" class=\"data row13 col1\" >2.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow14_col0\" class=\"data row14 col0\" >cardigan</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow14_col1\" class=\"data row14 col1\" >2.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow15_col0\" class=\"data row15 col0\" >jumpsuit</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow15_col1\" class=\"data row15 col1\" >1.900000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow16_col0\" class=\"data row16 col0\" >pants</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow16_col1\" class=\"data row16 col1\" >1.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow17_col0\" class=\"data row17 col0\" >shorts</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow17_col1\" class=\"data row17 col1\" >1.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow18_col0\" class=\"data row18 col0\" >hat</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow18_col1\" class=\"data row18 col1\" >0.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow19_col0\" class=\"data row19 col0\" >boots</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow19_col1\" class=\"data row19 col1\" >0.700000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow20_col0\" class=\"data row20 col0\" >sneakers</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow20_col1\" class=\"data row20 col1\" >0.600000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow21_col0\" class=\"data row21 col0\" >flat_shoes</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow21_col1\" class=\"data row21 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow22_col0\" class=\"data row22 col0\" >heels</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow22_col1\" class=\"data row22 col1\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow23_col0\" class=\"data row23 col0\" >slippers</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow23_col1\" class=\"data row23 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow24_col0\" class=\"data row24 col0\" >bathrobe</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow25_col0\" class=\"data row25 col0\" >underwear</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow25_col1\" class=\"data row25 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow26_col0\" class=\"data row26 col0\" >pyjama</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow26_col1\" class=\"data row26 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow27_col0\" class=\"data row27 col0\" >robe</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow27_col1\" class=\"data row27 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow28_col0\" class=\"data row28 col0\" >cover_ups</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow28_col1\" class=\"data row28 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4flevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow29_col0\" class=\"data row29 col0\" >waistcoat</td>\n",
       "                        <td id=\"T_2fa310c2_9176_11ec_95bc_9801a7d07c4frow29_col1\" class=\"data row29 col1\" >0.000000</td>\n",
       "            </tr>\n",
       "    </tbody></table>   "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path_tst =  os.path.join(DIR, 'test/coco_test_500.json')\n",
    "tst = json.load(open(path_tst))\n",
    "show_all(tst, 'Test')"
   ]
  }
 ],
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