{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3fe8177c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import fiftyone as fo\n",
    "from PIL import Image\n",
    "from detection import detect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32f0f8ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = \"dataset-small\"\n",
    "dataset_dir = \"/home/zenon/Documents/master-thesis/evaluation/dataset-small\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6343aa55",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 100% |█████████████████| 401/401 [633.3ms elapsed, 0s remaining, 633.2 samples/s]      \n"
     ]
    }
   ],
   "source": [
    "# The splits to load\n",
    "splits = [\"val\"]\n",
    "\n",
    "# Load the dataset, using tags to mark the samples in each split\n",
    "dataset = fo.Dataset(name)\n",
    "for split in splits:\n",
    "    dataset.add_dir(\n",
    "        dataset_dir=dataset_dir,\n",
    "        dataset_type=fo.types.YOLOv5Dataset,\n",
    "        split=split,\n",
    "        tags=split,\n",
    "    )\n",
    "\n",
    "classes = dataset.default_classes\n",
    "predictions_view = dataset.view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "29827e3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 100% |█████████████████| 401/401 [5.4m elapsed, 0s remaining, 1.4 samples/s]      \n"
     ]
    }
   ],
   "source": [
    "# Do detections with model and save bounding boxes\n",
    "with fo.ProgressBar() as pb:\n",
    "    for sample in pb(predictions_view):\n",
    "        image = Image.open(sample.filepath)\n",
    "        w, h = image.size\n",
    "        pred = detect(sample.filepath, 'yolo.onnx', 'resnet.onnx')\n",
    "\n",
    "        detections = []\n",
    "        for _, row in pred.iterrows():\n",
    "            xmin, xmax = int(row['xmin']), int(row['xmax'])\n",
    "            ymin, ymax = int(row['ymin']), int(row['ymax'])\n",
    "            rel_box = [\n",
    "                xmin / w, ymin / h, (xmax - xmin) / w, (ymax - ymin) / h\n",
    "            ]\n",
    "            detections.append(\n",
    "                fo.Detection(label=classes[int(row['cls'])],\n",
    "                             bounding_box=rel_box,\n",
    "                             confidence=int(row['cls_conf'])))\n",
    "\n",
    "        sample[\"yolo_resnet\"] = fo.Detections(detections=detections)\n",
    "        sample.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8ad67806",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluating detections...\n",
      " 100% |█████████████████| 401/401 [1.2s elapsed, 0s remaining, 339.9 samples/s]         \n",
      "Performing IoU sweep...\n",
      " 100% |█████████████████| 401/401 [1.4s elapsed, 0s remaining, 288.5 samples/s]         \n"
     ]
    }
   ],
   "source": [
    "results = predictions_view.evaluate_detections(\n",
    "    \"yolo_resnet\",\n",
    "    gt_field=\"ground_truth\",\n",
    "    eval_key=\"eval\",\n",
    "    compute_mAP=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b180420b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "     Healthy       0.80      0.81      0.81       430\n",
      "    Stressed       0.77      0.72      0.75       315\n",
      "\n",
      "   micro avg       0.79      0.77      0.78       745\n",
      "   macro avg       0.79      0.77      0.78       745\n",
      "weighted avg       0.79      0.77      0.78       745\n",
      "\n",
      "0.6336217415940075\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8e819dea581e48d69877fb551a949e49",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FigureWidget({\n",
       "    'data': [{'mode': 'markers',\n",
       "              'opacity': 0.1,\n",
       "              'type': 'scatter',\n",
       "              'uid': '918e4315-b093-4d2b-8af4-789b5a5d5152',\n",
       "              'x': array([0, 1, 2, 0, 1, 2, 0, 1, 2]),\n",
       "              'y': array([0, 0, 0, 1, 1, 1, 2, 2, 2])},\n",
       "             {'colorscale': [[0.0, 'rgb(255,245,235)'], [0.125,\n",
       "                             'rgb(254,230,206)'], [0.25, 'rgb(253,208,162)'],\n",
       "                             [0.375, 'rgb(253,174,107)'], [0.5, 'rgb(253,141,60)'],\n",
       "                             [0.625, 'rgb(241,105,19)'], [0.75, 'rgb(217,72,1)'],\n",
       "                             [0.875, 'rgb(166,54,3)'], [1.0, 'rgb(127,39,4)']],\n",
       "              'hoverinfo': 'skip',\n",
       "              'showscale': False,\n",
       "              'type': 'heatmap',\n",
       "              'uid': 'c2b76e66-be9d-4ca2-9060-d350e1d5e030',\n",
       "              'z': array([[ 86,  68,   0],\n",
       "                          [  0, 228,  87],\n",
       "                          [348,   0,  82]]),\n",
       "              'zmax': 348,\n",
       "              'zmin': 0},\n",
       "             {'colorbar': {'len': 1, 'lenmode': 'fraction'},\n",
       "              'colorscale': [[0.0, 'rgb(255,245,235)'], [0.125,\n",
       "                             'rgb(254,230,206)'], [0.25, 'rgb(253,208,162)'],\n",
       "                             [0.375, 'rgb(253,174,107)'], [0.5, 'rgb(253,141,60)'],\n",
       "                             [0.625, 'rgb(241,105,19)'], [0.75, 'rgb(217,72,1)'],\n",
       "                             [0.875, 'rgb(166,54,3)'], [1.0, 'rgb(127,39,4)']],\n",
       "              'hovertemplate': '<b>count: %{z}</b><br>truth: %{y}<br>predicted: %{x}<extra></extra>',\n",
       "              'opacity': 0.25,\n",
       "              'type': 'heatmap',\n",
       "              'uid': 'faa2cc05-e7dd-41df-8b22-533e4ae70f67',\n",
       "              'z': array([[ 86,  68,   0],\n",
       "                          [  0, 228,  87],\n",
       "                          [348,   0,  82]]),\n",
       "              'zmax': 348,\n",
       "              'zmin': 0}],\n",
       "    'layout': {'clickmode': 'event',\n",
       "               'margin': {'b': 0, 'l': 0, 'r': 0, 't': 30},\n",
       "               'template': '...',\n",
       "               'title': {},\n",
       "               'xaxis': {'constrain': 'domain',\n",
       "                         'range': [-0.5, 2.5],\n",
       "                         'tickmode': 'array',\n",
       "                         'ticktext': [Healthy, Stressed, (none)],\n",
       "                         'tickvals': array([0, 1, 2])},\n",
       "               'yaxis': {'constrain': 'domain',\n",
       "                         'range': [-0.5, 2.5],\n",
       "                         'scaleanchor': 'x',\n",
       "                         'scaleratio': 1,\n",
       "                         'tickmode': 'array',\n",
       "                         'ticktext': array(['(none)', 'Stressed', 'Healthy'], dtype=object),\n",
       "                         'tickvals': array([0, 1, 2])}}\n",
       "})"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "34fe31e66ebc452aba7202b9d206dee8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "FigureWidget({\n",
       "    'data': [{'customdata': array([99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 98. ,\n",
       "                                   98. , 98. , 97. , 97. , 97. , 97. , 97. , 96. , 96. , 95. , 94.2, 94. ,\n",
       "                                   93.2, 93. , 92.9, 91.9, 91.2, 91. , 91. , 90.8, 89.8, 88.8, 88. , 87.9,\n",
       "                                   87. , 86.9, 86. , 85.9, 85.8, 85. , 84.8, 84.6, 83.1, 81.9, 81.8, 81.1,\n",
       "                                   80.1, 79.9, 79.7, 78.9, 78.6, 77.9, 77.7, 76.8, 76. , 75.6, 74.6, 74.2,\n",
       "                                   73.3, 71.9, 70.7, 69.5, 68.3, 67.1, 66.2, 65.1, 64. , 62.9, 61.2, 60.6,\n",
       "                                   59.7, 58.9, 52.6, 51.1, 49.4, 47.2, 46.4, 40.7, 30.5,  0. ,  0. ,  0. ,\n",
       "                                    0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,\n",
       "                                    0. ,  0. ,  0. ,  0. ,  0. ]),\n",
       "              'hovertemplate': ('<b>class: %{text}</b><br>recal' ... 'customdata:.3f}<extra></extra>'),\n",
       "              'line': {'color': '#3366CC'},\n",
       "              'mode': 'lines',\n",
       "              'name': 'Healthy (AP = 0.674)',\n",
       "              'text': array(['Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy',\n",
       "                             'Healthy', 'Healthy', 'Healthy', 'Healthy', 'Healthy'], dtype='<U7'),\n",
       "              'type': 'scatter',\n",
       "              'uid': 'd6dc6ac2-c3a1-43b9-b14d-01413e1e7632',\n",
       "              'x': array([0.  , 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1 , 0.11,\n",
       "                          0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2 , 0.21, 0.22, 0.23,\n",
       "                          0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.3 , 0.31, 0.32, 0.33, 0.34, 0.35,\n",
       "                          0.36, 0.37, 0.38, 0.39, 0.4 , 0.41, 0.42, 0.43, 0.44, 0.45, 0.46, 0.47,\n",
       "                          0.48, 0.49, 0.5 , 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59,\n",
       "                          0.6 , 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.7 , 0.71,\n",
       "                          0.72, 0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.8 , 0.81, 0.82, 0.83,\n",
       "                          0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9 , 0.91, 0.92, 0.93, 0.94, 0.95,\n",
       "                          0.96, 0.97, 0.98, 0.99, 1.  ]),\n",
       "              'y': array([1.        , 1.        , 1.        , 1.        , 1.        , 1.        ,\n",
       "                          1.        , 1.        , 1.        , 1.        , 1.        , 0.85754476,\n",
       "                          0.85754476, 0.85754476, 0.85652174, 0.85652174, 0.85652174, 0.85652174,\n",
       "                          0.85652174, 0.8552381 , 0.8552381 , 0.84579977, 0.84120361, 0.84120361,\n",
       "                          0.84117934, 0.84088811, 0.84055957, 0.8403906 , 0.8403906 , 0.8403906 ,\n",
       "                          0.8403906 , 0.83984171, 0.83723176, 0.83723176, 0.83723176, 0.83723176,\n",
       "                          0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176,\n",
       "                          0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176,\n",
       "                          0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176, 0.83723176,\n",
       "                          0.83582796, 0.83582796, 0.82701581, 0.82393714, 0.82266455, 0.82228338,\n",
       "                          0.82013382, 0.81047308, 0.80513656, 0.79904708, 0.7964512 , 0.79508638,\n",
       "                          0.79508638, 0.79508638, 0.79508638, 0.79484633, 0.79432749, 0.79432749,\n",
       "                          0.79432749, 0.79432749, 0.72013715, 0.71985239, 0.7197879 , 0.71911422,\n",
       "                          0.71911422, 0.64047365, 0.48219373, 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        ])},\n",
       "             {'customdata': array([99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 99. , 98.7, 98. ,\n",
       "                                   98. , 98. , 97.9, 97.7, 97. , 96.9, 96.7, 96.5, 95.9, 95.6, 94.9, 94.5,\n",
       "                                   94. , 93. , 91.6, 91. , 90.1, 89.3, 89. , 88.2, 87.6, 87.2, 86.5, 86.1,\n",
       "                                   85.4, 84.8, 84.2, 83.1, 82.4, 81.7, 80.6, 79.5, 78.9, 77.4, 76.5, 74.7,\n",
       "                                   74. , 73.3, 72.3, 71.7, 71. , 70.2, 69.3, 68.6, 67.8, 67.4, 66.2, 65.3,\n",
       "                                   64.3, 62.7, 61.6, 60.5, 54.3, 53.1, 51.9, 45.1, 38.9, 38.2, 32. , 20.8,\n",
       "                                   10.1,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,\n",
       "                                    0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,\n",
       "                                    0. ,  0. ,  0. ,  0. ,  0. ]),\n",
       "              'hovertemplate': ('<b>class: %{text}</b><br>recal' ... 'customdata:.3f}<extra></extra>'),\n",
       "              'line': {'color': '#DC3912'},\n",
       "              'mode': 'lines',\n",
       "              'name': 'Stressed (AP = 0.593)',\n",
       "              'text': array(['Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed',\n",
       "                             'Stressed', 'Stressed', 'Stressed', 'Stressed', 'Stressed'], dtype='<U8'),\n",
       "              'type': 'scatter',\n",
       "              'uid': '01082c55-ea56-426c-8cfb-a433926eed03',\n",
       "              'x': array([0.  , 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1 , 0.11,\n",
       "                          0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2 , 0.21, 0.22, 0.23,\n",
       "                          0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.3 , 0.31, 0.32, 0.33, 0.34, 0.35,\n",
       "                          0.36, 0.37, 0.38, 0.39, 0.4 , 0.41, 0.42, 0.43, 0.44, 0.45, 0.46, 0.47,\n",
       "                          0.48, 0.49, 0.5 , 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59,\n",
       "                          0.6 , 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.7 , 0.71,\n",
       "                          0.72, 0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.8 , 0.81, 0.82, 0.83,\n",
       "                          0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9 , 0.91, 0.92, 0.93, 0.94, 0.95,\n",
       "                          0.96, 0.97, 0.98, 0.99, 1.  ]),\n",
       "              'y': array([1.        , 1.        , 1.        , 1.        , 1.        , 1.        ,\n",
       "                          1.        , 1.        , 1.        , 1.        , 0.97379592, 0.94476123,\n",
       "                          0.94476123, 0.94476123, 0.93427565, 0.91445476, 0.85844913, 0.85844913,\n",
       "                          0.85790639, 0.85788924, 0.85788924, 0.85747126, 0.85663314, 0.85452586,\n",
       "                          0.85298487, 0.84306319, 0.8375    , 0.8375    , 0.8375    , 0.8375    ,\n",
       "                          0.8375    , 0.8375    , 0.8375    , 0.8375    , 0.8375    , 0.8375    ,\n",
       "                          0.83717347, 0.83658868, 0.83565817, 0.8336283 , 0.82847628, 0.82488659,\n",
       "                          0.82126275, 0.8175916 , 0.81473127, 0.80427951, 0.8016311 , 0.80115198,\n",
       "                          0.8008129 , 0.80053685, 0.79883857, 0.79853619, 0.79853619, 0.79782171,\n",
       "                          0.79757033, 0.79595576, 0.79417872, 0.79338307, 0.79116989, 0.78813658,\n",
       "                          0.78474129, 0.78273994, 0.77996131, 0.77679573, 0.70534431, 0.70114991,\n",
       "                          0.69945778, 0.62345091, 0.54988677, 0.54689953, 0.46774707, 0.31001791,\n",
       "                          0.1547619 , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        , 0.        ,\n",
       "                          0.        , 0.        , 0.        , 0.        , 0.        ])}],\n",
       "    'layout': {'margin': {'b': 0, 'l': 0, 'r': 0, 't': 30},\n",
       "               'shapes': [{'line': {'dash': 'dash'}, 'type': 'line', 'x0': 0, 'x1': 1, 'y0': 1, 'y1': 0}],\n",
       "               'template': '...',\n",
       "               'xaxis': {'constrain': 'domain', 'range': [0, 1], 'title': {'text': 'Recall'}},\n",
       "               'yaxis': {'constrain': 'domain',\n",
       "                         'range': [0, 1],\n",
       "                         'scaleanchor': 'x',\n",
       "                         'scaleratio': 1,\n",
       "                         'title': {'text': 'Precision'}}}\n",
       "})"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the 10 most common classes in the dataset\n",
    "counts = dataset.count_values(\"ground_truth.detections.label\")\n",
    "classes_top10 = sorted(counts, key=counts.get, reverse=True)\n",
    "\n",
    "# Print a classification report for the top-10 classes\n",
    "results.print_report(classes=classes_top10)\n",
    "\n",
    "print(results.mAP())\n",
    "\n",
    "# Plot confusion matrix\n",
    "matrix = results.plot_confusion_matrix(classes=classes)\n",
    "matrix.show()\n",
    "\n",
    "pr_curves = results.plot_pr_curves(classes=[\"Healthy\", \"Stressed\"])\n",
    "pr_curves.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d1137788",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Session launched. Run `session.show()` to open the App in a cell output.\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "window.open('http://localhost:5151/');"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "session = fo.launch_app(dataset, auto=False)\n",
    "session.view = predictions_view\n",
    "session.open_tab()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "535003f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "session.plots.attach(matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3ba32f0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}