davidbau/explorefeaturebyclick.ipynb

## explorefeaturebyclick.ipynb
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ExploreFeatureByClick.ipynb",
      "provenance": [],
      "machine_shape": "hm",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/davidbau/347c36c52d07c60f0fb423638fe293a5/explorefeaturebyclick.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7oznU8U60VZ_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!git clone https://github.com/davidbau/gpwidget -b demo gpwidget 2>> install.log\n",
        "!pip install ninja >> install.log\n",
        "!pip install --force https://github.com/chengs/tqdm/archive/colab.zip  >> install.log\n",
        "import sys\n",
        "sys.path.append('/content/gpwidget')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4H7b5n5BLMsY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        },
        "outputId": "3d637fac-3ab2-4ab1-8152-2fca0691d144"
      },
      "source": [
        "from ganpaint import renormalize, imgviz, nethook, pbar, show, parallelfolder\n",
        "import torch, torchvision, os\n",
        "torch.backends.cudnn.benchmark = True\n",
        "torch.set_grad_enabled(False)\n",
        "\n",
        "ds_folder = 'datasets/microimagenet/images'\n",
        "if not os.path.exists(ds_folder):\n",
        "    os.makedirs(ds_folder, exist_ok=True)\n",
        "    torchvision.datasets.utils.download_and_extract_archive(\n",
        "        'http://gandissect.csail.mit.edu/datasets/microimagenet.zip',\n",
        "        'datasets',\n",
        "        md5='b14f5afabd1b03f4062107043fb65af2')\n",
        "    \n",
        "g_transform = torchvision.transforms.Compose([\n",
        "    torchvision.transforms.Resize(256),\n",
        "    torchvision.transforms.CenterCrop(256),\n",
        "    torchvision.transforms.ToTensor(),\n",
        "    torchvision.transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])\n",
        "\n",
        "ds = parallelfolder.ParallelImageFolders(\n",
        "    [ds_folder],\n",
        "    transform=g_transform,\n",
        "    shuffle=True)\n",
        "\n",
        "iv = imgviz.ImageVisualizer(128)\n",
        "iv.image(ds[0][0])"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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0DTddA0BvMODKGmc9XAngQZFC8NkZsLLm2Dx5OLggwdbDIcR7z0wiN5BxEjCH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\nkqaPf7rymAIeZXlMAY+yPKaAR1n+FyydrXRQuiAkAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=128x128 at 0x7F6381880F98>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZoCLsJVO0qs1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "net = nethook.InstrumentedModel(torchvision.models.vgg16(pretrained=True)).cuda()\n",
        "net.eval()\n",
        "#net.retain_layer('features.3')\n",
        "#net.retain_layer('features.8')\n",
        "net.retain_layer('features.15')\n",
        "net.retain_layer('features.22')\n",
        "net.retain_layer('features.29')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zTQ6GzIn0vCS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 969
        },
        "outputId": "9ff43321-47ca-4a26-e5ae-c8a541df11e9"
      },
      "source": [
        "from torch.utils.data import DataLoader\n",
        "from ganpaint import runningstats\n",
        "from collections import defaultdict\n",
        "\n",
        "def load_image_set(dataset, size=1000):\n",
        "    # Equivalent: img_sample = torch.cat([dataset[i][0][None] for i in pbar(range(10000))])\n",
        "    # Batching reads with DataLoader helps us do multithreaded disk access.\n",
        "    load_batch_size = 100\n",
        "    img_sample = torch.cat([batch[0] for batch, i in zip(\n",
        "        DataLoader(dataset, batch_size=load_batch_size, num_workers=20),\n",
        "        pbar(range(-(-size // load_batch_size))))])[:size]\n",
        "    return img_sample\n",
        "\n",
        "def create_feature_set(feature_fn, img_sample):\n",
        "    compute_batch_size = 32\n",
        "    features = defaultdict(list)\n",
        "    for i in pbar(range(0, len(img_sample), compute_batch_size)):\n",
        "        for k, v in feature_fn(img_sample[i:i+compute_batch_size]).items():\n",
        "            features[k].append(v)\n",
        "    features = {k: torch.cat(v) for k, v in features.items()}\n",
        "    return features\n",
        "    \n",
        "def feature_fn(img_batch):\n",
        "    net(img_batch.cuda())\n",
        "    return {k: v.cpu() for k, v in net.retained_features().items()}\n",
        "\n",
        "def feature_unit_heatmap(feature_fn, dataset, image_number=0, unit_number=0):\n",
        "    return show.blocks([[k, iv.heatmap(v[0, unit_number])]\n",
        "        for k, v in feature_fn(dataset[image_number][0][None].cuda()).items() ])\n",
        "\n",
        "print(\"example feature - image 0, unit 0\")\n",
        "display(feature_unit_heatmap(feature_fn, ds))\n",
        "\n",
        "print(\"Loading a sample of images\")\n",
        "img_sample = load_image_set(ds)\n",
        "\n",
        "print(\"Building a tensor of all features over images\")\n",
        "f_sample = create_feature_set(feature_fn, img_sample)\n",
        "\n",
        "print(\"Done.\")"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "example feature - image 0, unit 0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2693: UserWarning: Default grid_sample and affine_grid behavior will be changed to align_corners=False from 1.4.0. See the documentation of grid_sample for details.\n",
            "  warnings.warn(\"Default grid_sample and affine_grid behavior will be changed \"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div>features.15</div><img 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\" style=\"margin:1px\"></div><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div>features.22</div><img src=\"data:image/png;base64,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\" style=\"margin:1px\"></div><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div>features.29</div><img src=\"data:image/png;base64,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\" style=\"margin:1px\"></div></div>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "  0%|          | 0/10 [00:00<?, ?it/s]\u001b[A"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Loading a sample of images\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            " 10%|#         | 1/10 [00:12<01:54, 12.77s/it]\u001b[A\n",
            " 30%|###       | 3/10 [00:13<01:02,  8.98s/it]\u001b[A\n",
            " 40%|####      | 4/10 [00:13<00:38,  6.39s/it]\u001b[A\n",
            " 90%|######### | 9/10 [00:13<00:04,  4.49s/it]\u001b[A\n",
            "100%|##########| 10/10 [00:13<00:00,  1.38s/it]\u001b[A\n",
            "  0%|          | 0/32 [00:00<?, ?it/s]\u001b[A"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Building a tensor of all features over images\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "  3%|3         | 1/32 [00:00<00:16,  1.86it/s]\u001b[A\n",
            "  6%|6         | 2/32 [00:01<00:15,  1.93it/s]\u001b[A\n",
            "  9%|9         | 3/32 [00:01<00:14,  1.96it/s]\u001b[A\n",
            " 12%|#2        | 4/32 [00:01<00:14,  1.98it/s]\u001b[A\n",
            " 16%|#5        | 5/32 [00:02<00:13,  2.03it/s]\u001b[A\n",
            " 19%|#8        | 6/32 [00:02<00:12,  2.14it/s]\u001b[A\n",
            " 22%|##1       | 7/32 [00:03<00:11,  2.21it/s]\u001b[A\n",
            " 25%|##5       | 8/32 [00:03<00:10,  2.26it/s]\u001b[A\n",
            " 28%|##8       | 9/32 [00:04<00:09,  2.31it/s]\u001b[A\n",
            " 31%|###1      | 10/32 [00:04<00:09,  2.33it/s]\u001b[A\n",
            " 34%|###4      | 11/32 [00:04<00:08,  2.34it/s]\u001b[A\n",
            " 38%|###7      | 12/32 [00:05<00:08,  2.36it/s]\u001b[A\n",
            " 41%|####      | 13/32 [00:05<00:08,  2.37it/s]\u001b[A\n",
            " 44%|####3     | 14/32 [00:06<00:07,  2.37it/s]\u001b[A\n",
            " 47%|####6     | 15/32 [00:06<00:07,  2.39it/s]\u001b[A\n",
            " 50%|#####     | 16/32 [00:07<00:06,  2.39it/s]\u001b[A\n",
            " 53%|#####3    | 17/32 [00:07<00:06,  2.40it/s]\u001b[A\n",
            " 56%|#####6    | 18/32 [00:07<00:05,  2.40it/s]\u001b[A\n",
            " 59%|#####9    | 19/32 [00:08<00:05,  2.41it/s]\u001b[A\n",
            " 62%|######2   | 20/32 [00:08<00:05,  2.39it/s]\u001b[A\n",
            " 66%|######5   | 21/32 [00:09<00:04,  2.34it/s]\u001b[A\n",
            " 69%|######8   | 22/32 [00:09<00:04,  2.29it/s]\u001b[A\n",
            " 72%|#######1  | 23/32 [00:10<00:03,  2.25it/s]\u001b[A\n",
            " 75%|#######5  | 24/32 [00:10<00:03,  2.22it/s]\u001b[A\n",
            " 78%|#######8  | 25/32 [00:11<00:03,  2.19it/s]\u001b[A\n",
            " 81%|########1 | 26/32 [00:11<00:02,  2.19it/s]\u001b[A\n",
            " 84%|########4 | 27/32 [00:11<00:02,  2.16it/s]\u001b[A\n",
            " 88%|########7 | 28/32 [00:12<00:01,  2.19it/s]\u001b[A\n",
            " 91%|######### | 29/32 [00:12<00:01,  2.26it/s]\u001b[A\n",
            " 94%|#########3| 30/32 [00:13<00:00,  2.29it/s]\u001b[A\n",
            " 97%|#########6| 31/32 [00:13<00:00,  2.33it/s]\u001b[A\n",
            "100%|##########| 32/32 [00:13<00:00,  2.87it/s]\u001b[A\n",
            "\u001b[A"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vLfrBywVMO6N",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 703
        },
        "outputId": "974e6365-b551-42dc-db7b-fde98c793076"
      },
      "source": [
        "from ganpaint import labwidget\n",
        "from ganpaint import show\n",
        "from ganpaint.labwidget import Div, Model, Property, Button, Textbox, Choice\n",
        "from ganpaint.paintwidget import PaintWidget\n",
        "\n",
        "\n",
        "class ImageFeatureExplorer(Model):\n",
        "    def __init__(self, samplenums, sample_map, img_sample):\n",
        "        self.samplenums = Property(','.join(str(n) for n in samplenums))\n",
        "        self.feature_fn = Property(feature_fn)\n",
        "        self.query_f = Property(None)\n",
        "        self.layername = Property(list(sample_map)[-1])\n",
        "        self.sampleTextbox = Textbox(self.prop('samplenums'), size=40)\n",
        "        self.img_sample = img_sample\n",
        "        self.sample_map = sample_map\n",
        "        self.layerChoice = Choice(list(sample_map.keys()), selection=self.prop('layername'))\n",
        "        self.layerChoice.on('selection', self.recompute_query)\n",
        "        self.f_sample = sample_map[self.layername]\n",
        "        self.on('samplenums', self.redisplay_painters)\n",
        "        self.painters = []\n",
        "        self.resetButton = Button('reset')\n",
        "        self.inputs = Div()\n",
        "        self.results = Div()\n",
        "        self.redisplay_painters()\n",
        "        self.recompute_results()\n",
        "        self.resetButton.on('click', self.reset_painters)\n",
        "        self.on('query_f', self.recompute_results)\n",
        "        \n",
        "    def get_samplenums(self):\n",
        "        result = []\n",
        "        for s in self.samplenums.split(','):\n",
        "            try:\n",
        "                result.append(int(s.strip()))\n",
        "            except:\n",
        "                pass\n",
        "        return result\n",
        "        \n",
        "    def redisplay_painters(self):\n",
        "        samplenums = self.get_samplenums()\n",
        "        self.painters = [\n",
        "            PaintWidget(self.img_sample.shape[3], self.img_sample.shape[2],\n",
        "                        brushsize=5, image=renormalize.as_url(self.img_sample[i]))\n",
        "            for i in samplenums]\n",
        "        for p in self.painters:\n",
        "            p.on('mask', self.recompute_query)\n",
        "        self.inputs.innerHTML = show.html([(\n",
        "                        ['enter image number then paint', self.sampleTextbox, [[p] for p in self.painters]],\n",
        "                         [[self.resetButton, self.layerChoice]]\n",
        "        )])\n",
        "    \n",
        "    def reset_painters(self):\n",
        "        for p in self.painters:\n",
        "            p.mask = ''\n",
        "    \n",
        "    def recompute_query(self):\n",
        "        global feat\n",
        "        total_mask = 0.0\n",
        "        self.f_sample = self.sample_map[self.layername]\n",
        "        total_feat = torch.zeros_like(self.f_sample[0,:,0,0])\n",
        "        for i, p in zip(self.get_samplenums(), self.painters):\n",
        "            a = self.f_sample[i]\n",
        "            if p.mask:\n",
        "                mask = renormalize.from_url(\n",
        "                    p.mask, target='pt', size=a.shape[1:])[0]\n",
        "                total_feat = total_feat + (a * mask[None]).sum((1,2))\n",
        "                total_mask += mask.sum()\n",
        "        feat = total_feat / (total_mask + 1e-20)\n",
        "        self.query_f = feat\n",
        "    \n",
        "    def recompute_results(self):\n",
        "        if self.query_f is None:\n",
        "            return\n",
        "        feat = self.query_f\n",
        "        # Rank the sampled images according to similar to this feature\n",
        "        patch_scores = (self.f_sample * feat[None,:,None,None]).sum(1)\n",
        "        score = patch_scores.view(len(self.f_sample), -1).max(1)[0]\n",
        "        _, ordering = torch.sort(-score)\n",
        "        self.results.innerHTML = show.html([\n",
        "            ['img #%d' % i.item(), \n",
        "             'score %g' % score[i].item(),\n",
        "             [\n",
        "                iv.masked_image(\n",
        "                    self.img_sample[i],\n",
        "                    (self.f_sample[i] * feat[None,:,None,None]).sum(1)[0],\n",
        "                    percent_level=0.9)\n",
        "            ]] for i in ordering[:14]\n",
        "        ])\n",
        "        \n",
        "    def _repr_html_(self):\n",
        "        return self.inputs._repr_html_() + self.results._repr_html_()\n",
        "\n",
        "explorer = ImageFeatureExplorer([664], f_sample, img_sample)\n",
        "display(explorer)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "        \n",
              "          <div id=\"_140065062904832_1\"><table style=\"display:inline-table\"><tr style=\"padding:0\"><td style=\"text-align:left; vertical-align:top; padding:1px\"><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div>enter image number then paint</div>\n",
              "        \n",
              "          <input id=\"_140065062907408_1\" style=\"display:block\"\n",
              "             value=\"664\" size=\"40\">\n",
              "        \n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062907408\", {\"value\": \"664\", \"size\": 40});\n",
              "        var element = document.getElementById(\"_140065062907408_1\");\n",
              "        \n",
              "          element.value = model.get('value');\n",
              "          element.size = model.get('size');\n",
              "          element.addEventListener('keydown', (e) => {\n",
              "            if (e.code == 'Enter') {\n",
              "              model.set('value', element.value);\n",
              "            }\n",
              "          });\n",
              "          model.on('value', (value) => {\n",
              "            element.value = model.get('value');\n",
              "          });\n",
              "          model.on('size', (value) => {\n",
              "            element.size = model.get('size');\n",
              "          });\n",
              "        \n",
              "        })();\n",
              "        </script>\n",
              "        <div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\">\n",
              "        \n",
              "    <style>\n",
              "    #_140065062906232_1 { position: relative; display: inline-block; }\n",
              "    #_140065062906232_1 .paintmask {\n",
              "      position: absolute; top:0; left: 0; z-index: 1;\n",
              "      opacity: 0; transition: opacity .1s ease-in-out; }\n",
              "    #_140065062906232_1 .paintmask:hover { opacity: 0.7; }\n",
              "    </style>\n",
              "    <div id=\"_140065062906232_1\"></div>\n",
              "    \n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062906232\", {\"mask\": \"\", \"image\": 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\", \"brushsize\": 5, \"erase\": false, \"oneshot\": false, \"disabled\": false, \"width\": 256, \"height\": 256});\n",
              "        var element = document.getElementById(\"_140065062906232_1\");\n",
              "        \n",
              "      \n",
              "class PaintWidget {\n",
              "  constructor(el, model) {\n",
              "    this.el = el;\n",
              "    this.model = model;\n",
              "    this.size_changed();\n",
              "    this.model.on('mask', this.mask_changed.bind(this));\n",
              "    this.model.on('image', this.image_changed.bind(this));\n",
              "    this.model.on('width', this.size_changed.bind(this));\n",
              "    this.model.on('height', this.size_changed.bind(this));\n",
              "  }\n",
              "  mouse_stroke(first_event) {\n",
              "    var self = this;\n",
              "    if (self.model.get('disabled')) { return; }\n",
              "    if (self.model.get('oneshot')) {\n",
              "        var canvas = self.mask_canvas;\n",
              "        var ctx = canvas.getContext('2d');\n",
              "        ctx.clearRect(0, 0, canvas.width, canvas.height);\n",
              "    }\n",
              "    function track_mouse(evt) {\n",
              "      if (evt.type == 'keydown' || self.model.get('disabled')) {\n",
              "        if (self.model.get('disabled') || evt.key === \"Escape\") {\n",
              "          window.removeEventListener('mousemove', track_mouse);\n",
              "          window.removeEventListener('mouseup', track_mouse);\n",
              "          window.removeEventListener('keydown', track_mouse, true);\n",
              "          self.mask_changed();\n",
              "        }\n",
              "        return;\n",
              "      }\n",
              "      if (evt.type == 'mouseup' ||\n",
              "        (typeof evt.buttons != 'undefined' && evt.buttons == 0)) {\n",
              "        window.removeEventListener('mousemove', track_mouse);\n",
              "        window.removeEventListener('mouseup', track_mouse);\n",
              "        window.removeEventListener('keydown', track_mouse, true);\n",
              "        self.model.set('mask', self.mask_canvas.toDataURL());\n",
              "        return;\n",
              "      }\n",
              "      var p = self.cursor_position();\n",
              "      self.fill_circle(p.x, p.y,\n",
              "          self.model.get('brushsize'),\n",
              "          self.model.get('erase'));\n",
              "    }\n",
              "    this.mask_canvas.focus();\n",
              "    window.addEventListener('mousemove', track_mouse);\n",
              "    window.addEventListener('mouseup', track_mouse);\n",
              "    window.addEventListener('keydown', track_mouse, true);\n",
              "    track_mouse(first_event);\n",
              "  }\n",
              "  mask_changed(val) {\n",
              "    this.draw_data_url(this.mask_canvas, this.model.get('mask'));\n",
              "  }\n",
              "  image_changed() {\n",
              "    this.draw_data_url(this.image_canvas, this.model.get('image'));\n",
              "  }\n",
              "  size_changed() {\n",
              "    this.mask_canvas = document.createElement('canvas');\n",
              "    this.image_canvas = document.createElement('canvas');\n",
              "    this.mask_canvas.className = \"paintmask\";\n",
              "    this.image_canvas.className = \"paintimage\";\n",
              "    for (var attr of ['width', 'height']) {\n",
              "      this.mask_canvas[attr] = this.model.get(attr);\n",
              "      this.image_canvas[attr] = this.model.get(attr);\n",
              "    }\n",
              "\n",
              "    this.el.innerHTML = '';\n",
              "    this.el.appendChild(this.image_canvas);\n",
              "    this.el.appendChild(this.mask_canvas);\n",
              "    this.mask_canvas.addEventListener('mousedown',\n",
              "        this.mouse_stroke.bind(this));\n",
              "    this.mask_changed();\n",
              "    this.image_changed();\n",
              "  }\n",
              "\n",
              "  cursor_position(evt) {\n",
              "    const rect = this.mask_canvas.getBoundingClientRect();\n",
              "    const x = event.clientX - rect.left;\n",
              "    const y = event.clientY - rect.top;\n",
              "    return {x: x, y: y};\n",
              "  }\n",
              "\n",
              "  fill_circle(x, y, r, erase, blur) {\n",
              "    var ctx = this.mask_canvas.getContext('2d');\n",
              "    ctx.save();\n",
              "    if (blur) {\n",
              "        ctx.filter = 'blur(' + blur + 'px)';\n",
              "    }\n",
              "    ctx.globalCompositeOperation = (\n",
              "        erase ? \"destination-out\" : 'source-over');\n",
              "    ctx.fillStyle = '#fff';\n",
              "    ctx.beginPath();\n",
              "    ctx.arc(x, y, r, 0, 2 * Math.PI);\n",
              "    ctx.fill();\n",
              "    ctx.restore()\n",
              "  }\n",
              "\n",
              "  draw_data_url(canvas, durl) {\n",
              "    var ctx = canvas.getContext('2d');\n",
              "    var img = new Image;\n",
              "    canvas.pendingImg = img;\n",
              "    function imgdone() {\n",
              "      if (canvas.pendingImg == img) {\n",
              "        ctx.clearRect(0, 0, canvas.width, canvas.height);\n",
              "        ctx.drawImage(img, 0, 0);\n",
              "        canvas.pendingImg = null;\n",
              "      }\n",
              "    }\n",
              "    img.addEventListener('load', imgdone);\n",
              "    img.addEventListener('error', imgdone);\n",
              "    img.src = durl;\n",
              "  }\n",
              "}\n",
              "\n",
              "      var pw = new PaintWidget(element, model);\n",
              "    \n",
              "        })();\n",
              "        </script>\n",
              "        </div></div></div></td><td style=\"text-align:left; vertical-align:top; padding:1px\"><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\"><div style=\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\">\n",
              "        \n",
              "          <input id=\"_140065062905000_1\" type=\"button\" style=\"display:block\"\n",
              "            value=\"reset\">\n",
              "        \n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062905000\", {\"label\": \"reset\"});\n",
              "        var element = document.getElementById(\"_140065062905000_1\");\n",
              "        \n",
              "          element.addEventListener('click', (e) => {\n",
              "            model.trigger('click');\n",
              "          })\n",
              "          model.on('label', (v) => {\n",
              "            element.value = v;\n",
              "          })\n",
              "        \n",
              "        })();\n",
              "        </script>\n",
              "        \n",
              "        <form id=\"_140065062904048_1\"><label><input name=\"choice\" type=\"radio\"  value=\"features.15\">features.15</label><br><label><input name=\"choice\" type=\"radio\"  value=\"features.22\">features.22</label><br><label><input name=\"choice\" type=\"radio\" checked value=\"features.29\">features.29</label></form>\n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062904048\", {\"choices\": [\"features.15\", \"features.22\", \"features.29\"], \"horizontal\": false, \"selection\": \"features.29\"});\n",
              "        var element = document.getElementById(\"_140065062904048_1\");\n",
              "        \n",
              "          function esc(unsafe) {\n",
              "            return unsafe.replace(/&/g, \"&amp;\").replace(/</g, \"&lt;\")\n",
              "                   .replace(/>/g, \"&gt;\").replace(/\"/g, \"&quot;\");\n",
              "          }\n",
              "          function render() {\n",
              "            console.log('rendering');\n",
              "            var lines = model.get('choices').map((c) => {\n",
              "              return '<label><input type=\"radio\" name=\"choice\" value=\"' +\n",
              "                 esc(c) + '\">' + esc(c) + '</label>'\n",
              "            });\n",
              "            element.innerHTML = lines.join(model.get('horizontal')?' ':'<br>');\n",
              "          }\n",
              "          model.on('choices horizontal', render);\n",
              "          model.on('selection', (selection) => {\n",
              "            [...element.querySelectorAll('input')].forEach((e) => {\n",
              "              e.checked = (e.value == selection);\n",
              "            })\n",
              "          });\n",
              "          element.addEventListener('change', (e) => {\n",
              "            model.set('selection', element.choice.value);\n",
              "          });\n",
              "        \n",
              "        })();\n",
              "        </script>\n",
              "        </div></div></td></tr></table></div>\n",
              "        \n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062904832\", {\"innerHTML\": \"<table style=\\\"display:inline-table\\\"><tr style=\\\"padding:0\\\"><td style=\\\"text-align:left; vertical-align:top; padding:1px\\\"><div style=\\\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\\\"><div>enter image number then paint<\\/div>\\n        \\n          <input id=\\\"_140065062907408_1\\\" style=\\\"display:block\\\"\\n             value=\\\"664\\\" size=\\\"40\\\">\\n        \\n        <script>\\n        (function() {\\n        \\nfunction recvFromPython(obj_id, fn) {\\n  var recvname = \\\"recv_\\\" + obj_id;\\n  if (window[recvname] === undefined) {\\n    window[recvname] = new BroadcastChannel(\\\"channel_\\\" + obj_id);\\n  }\\n  window[recvname].addEventListener(\\\"message\\\", (ev) => {\\n    if (ev.data == 'ok') {\\n      window[recvname].ok = true;\\n      return;\\n    }\\n    fn.apply(null, ev.data.slice(1));\\n  });\\n}\\nfunction sendToPython(obj_id, ...args) {\\n  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\\n}\\n\\nclass Model {\\n  constructor(obj_id, init) {\\n    this._id = obj_id;\\n    this._listeners = {};\\n    this._data = Object.assign({}, init)\\n    recvFromPython(this._id, (name, value) => {\\n      this._data[name] = value;\\n      if (this._listeners.hasOwnProperty(name)) {\\n        this._listeners[name].forEach((fn) => { fn(value); });\\n      }\\n    })\\n  }\\n  trigger(name, value) {\\n    sendToPython(this._id, name, value);\\n  }\\n  get(name) {\\n    return this._data[name];\\n  }\\n  set(name, value) {\\n    this.trigger(name, value);\\n  }\\n  on(name, fn) {\\n    name.split(/\\\\s+/).forEach((n) => {\\n      if (!this._listeners.hasOwnProperty(n)) {\\n        this._listeners[n] = [];\\n      }\\n      this._listeners[n].push(fn);\\n    });\\n  }\\n  off(name, fn) {\\n    name.split(/\\\\s+/).forEach((n) => {\\n      if (!fn) {\\n        delete this._listeners[n];\\n      } else if (this._listeners.hasOwnProperty(n)) {\\n        this._listeners[n] = this._listeners[n].filter(\\n            (e) => { return e !== fn; });\\n      }\\n    });\\n  }\\n}\\n\\n        var model = new Model(\\\"140065062907408\\\", {\\\"value\\\": \\\"664\\\", \\\"size\\\": 40});\\n        var element = document.getElementById(\\\"_140065062907408_1\\\");\\n        \\n          element.value = model.get('value');\\n          element.size = model.get('size');\\n          element.addEventListener('keydown', (e) => {\\n            if (e.code == 'Enter') {\\n              model.set('value', element.value);\\n            }\\n          });\\n          model.on('value', (value) => {\\n            element.value = model.get('value');\\n          });\\n          model.on('size', (value) => {\\n            element.size = model.get('size');\\n          });\\n        \\n        })();\\n        <\\/script>\\n        <div style=\\\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\\\"><div style=\\\"display:inline-block;text-align:center;line-height:1;vertical-align:top;padding:1px\\\">\\n        \\n    <style>\\n    #_140065062906232_1 { position: relative; display: inline-block; }\\n    #_140065062906232_1 .paintmask {\\n      position: absolute; top:0; left: 0; z-index: 1;\\n      opacity: 0; transition: opacity .1s ease-in-out; }\\n    #_140065062906232_1 .paintmask:hover { opacity: 0.7; }\\n    <\\/style>\\n    <div id=\\\"_140065062906232_1\\\"><\\/div>\\n    \\n        <script>\\n        (function() {\\n        \\nfunction recvFromPython(obj_id, fn) {\\n  var recvname = \\\"recv_\\\" + obj_id;\\n  if (window[recvname] === undefined) {\\n    window[recvname] = new BroadcastChannel(\\\"channel_\\\" + obj_id);\\n  }\\n  window[recvname].addEventListener(\\\"message\\\", (ev) => {\\n    if (ev.data == 'ok') {\\n      window[recvname].ok = true;\\n      return;\\n    }\\n    fn.apply(null, ev.data.slice(1));\\n  });\\n}\\nfunction sendToPython(obj_id, ...args) {\\n  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\\n}\\n\\nclass Model {\\n  constructor(obj_id, init) {\\n    this._id = obj_id;\\n    this._listeners = {};\\n    this._data = Object.assign({}, init)\\n    recvFromPython(this._id, (name, value) => {\\n      this._data[name] = value;\\n      if (this._listeners.hasOwnProperty(name)) {\\n        this._listeners[name].forEach((fn) => { fn(value); });\\n      }\\n    })\\n  }\\n  trigger(name, value) {\\n    sendToPython(this._id, name, value);\\n  }\\n  get(name) {\\n    return this._data[name];\\n  }\\n  set(name, value) {\\n    this.trigger(name, value);\\n  }\\n  on(name, fn) {\\n    name.split(/\\\\s+/).forEach((n) => {\\n      if (!this._listeners.hasOwnProperty(n)) {\\n        this._listeners[n] = [];\\n      }\\n      this._listeners[n].push(fn);\\n    });\\n  }\\n  off(name, fn) {\\n    name.split(/\\\\s+/).forEach((n) => {\\n      if (!fn) {\\n        delete this._listeners[n];\\n      } else if (this._listeners.hasOwnProperty(n)) {\\n        this._listeners[n] = this._listeners[n].filter(\\n            (e) => { return e !== fn; });\\n      }\\n    });\\n  }\\n}\\n\\n        var model = new Model(\\\"140065062906232\\\", {\\\"mask\\\": \\\"\\\", \\\"image\\\": 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\\\", \\\"brushsize\\\": 5, \\\"erase\\\": false, \\\"oneshot\\\": false, \\\"disabled\\\": false, \\\"width\\\": 256, \\\"height\\\": 256});\\n        var element = document.getElementById(\\\"_140065062906232_1\\\");\\n        \\n      \\nclass PaintWidget {\\n  constructor(el, model) {\\n    this.el = el;\\n    this.model = model;\\n    this.size_changed();\\n    this.model.on('mask', this.mask_changed.bind(this));\\n    this.model.on('image', this.image_changed.bind(this));\\n    this.model.on('width', this.size_changed.bind(this));\\n    this.model.on('height', this.size_changed.bind(this));\\n  }\\n  mouse_stroke(first_event) {\\n    var self = this;\\n    if (self.model.get('disabled')) { return; }\\n    if (self.model.get('oneshot')) {\\n        var canvas = self.mask_canvas;\\n        var ctx = canvas.getContext('2d');\\n        ctx.clearRect(0, 0, canvas.width, canvas.height);\\n    }\\n    function track_mouse(evt) {\\n      if (evt.type == 'keydown' || self.model.get('disabled')) 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              "        var element = document.getElementById(\"_140065062904832_1\");\n",
              "        \n",
              "          function updater(attr) {\n",
              "            return (val) => { for (k in val) { element[attr][k] = val[k]; } }\n",
              "          }\n",
              "          model.on('style', updater('style'));\n",
              "          updater('style')();\n",
              "          model.on('data', updater('dataset'));\n",
              "          updater('dataset')();\n",
              "          model.on('innerHTML', (innerHTML) => {\n",
              "            element.innerHTML = innerHTML;\n",
              "            Array.from(element.querySelectorAll(\"script\")).forEach(old=>{\n",
              "              const newScript = document.createElement(\"script\");\n",
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              "                 newScript.setAttribute(attr.name, attr.value));\n",
              "              newScript.appendChild(document.createTextNode(old.innerHTML));\n",
              "              old.parentNode.replaceChild(newScript, old);\n",
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              "        })();\n",
              "        </script>\n",
              "        \n",
              "        \n",
              "          <div id=\"_140065062905224_1\"></div>\n",
              "        \n",
              "        <script>\n",
              "        (function() {\n",
              "        \n",
              "function recvFromPython(obj_id, fn) {\n",
              "  var recvname = \"recv_\" + obj_id;\n",
              "  if (window[recvname] === undefined) {\n",
              "    window[recvname] = new BroadcastChannel(\"channel_\" + obj_id);\n",
              "  }\n",
              "  window[recvname].addEventListener(\"message\", (ev) => {\n",
              "    if (ev.data == 'ok') {\n",
              "      window[recvname].ok = true;\n",
              "      return;\n",
              "    }\n",
              "    fn.apply(null, ev.data.slice(1));\n",
              "  });\n",
              "}\n",
              "function sendToPython(obj_id, ...args) {\n",
              "  google.colab.kernel.invokeFunction('invoke_' + obj_id, args, {})\n",
              "}\n",
              "\n",
              "class Model {\n",
              "  constructor(obj_id, init) {\n",
              "    this._id = obj_id;\n",
              "    this._listeners = {};\n",
              "    this._data = Object.assign({}, init)\n",
              "    recvFromPython(this._id, (name, value) => {\n",
              "      this._data[name] = value;\n",
              "      if (this._listeners.hasOwnProperty(name)) {\n",
              "        this._listeners[name].forEach((fn) => { fn(value); });\n",
              "      }\n",
              "    })\n",
              "  }\n",
              "  trigger(name, value) {\n",
              "    sendToPython(this._id, name, value);\n",
              "  }\n",
              "  get(name) {\n",
              "    return this._data[name];\n",
              "  }\n",
              "  set(name, value) {\n",
              "    this.trigger(name, value);\n",
              "  }\n",
              "  on(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = [];\n",
              "      }\n",
              "      this._listeners[n].push(fn);\n",
              "    });\n",
              "  }\n",
              "  off(name, fn) {\n",
              "    name.split(/\\s+/).forEach((n) => {\n",
              "      if (!fn) {\n",
              "        delete this._listeners[n];\n",
              "      } else if (this._listeners.hasOwnProperty(n)) {\n",
              "        this._listeners[n] = this._listeners[n].filter(\n",
              "            (e) => { return e !== fn; });\n",
              "      }\n",
              "    });\n",
              "  }\n",
              "}\n",
              "\n",
              "        var model = new Model(\"140065062905224\", {\"innerHTML\": \"\", \"style\": {}});\n",
              "        var element = document.getElementById(\"_140065062905224_1\");\n",
              "        \n",
              "          function updater(attr) {\n",
              "            return (val) => { for (k in val) { element[attr][k] = val[k]; } }\n",
              "          }\n",
              "          model.on('style', updater('style'));\n",
              "          updater('style')();\n",
              "          model.on('data', updater('dataset'));\n",
              "          updater('dataset')();\n",
              "          model.on('innerHTML', (innerHTML) => {\n",
              "            element.innerHTML = innerHTML;\n",
              "            Array.from(element.querySelectorAll(\"script\")).forEach(old=>{\n",
              "              const newScript = document.createElement(\"script\");\n",
              "              Array.from(old.attributes).forEach(attr =>\n",
              "                 newScript.setAttribute(attr.name, attr.value));\n",
              "              newScript.appendChild(document.createTextNode(old.innerHTML));\n",
              "              old.parentNode.replaceChild(newScript, old);\n",
              "            });\n",
              "          });\n",
              "        \n",
              "        })();\n",
              "        </script>\n",
              "        "
            ],
            "text/plain": [
              "<__main__.ImageFeatureExplorer at 0x7f637051e240>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2693: UserWarning: Default grid_sample and affine_grid behavior will be changed to align_corners=False from 1.4.0. See the documentation of grid_sample for details.\n",
            "  warnings.warn(\"Default grid_sample and affine_grid behavior will be changed \"\n"
          ],
          "name": "stderr"
        }
      ]
    }
  ]
}