Cityscapes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cityscapes\n",
    "\n",
    "This notebook is meant as an illustration how to reproduce those tables and figures from our paper that are based on the Cityscapes dataset.  \n",
    "It also contains useful scripts to download and extract the used datasets and load our pretrained models and experimental configurations.  \n",
    "To run the notebook for yourself, please follow the [installation instructions from the readme](https://github.com/ethz-asl/modular_semantic_segmentation/blob/publish/README.md).\n",
    "\n",
    "### *Optional Config and Installation*\n",
    "\n",
    "Simply jump over the steps you already did set up.\n",
    "\n",
    "**1. Configuration**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xview\n",
    "from os import path\n",
    "\n",
    "# PLEASE EDIT THE FOLLOWING PATHS FOR YOUR LOCAL SETTINGS\n",
    "\n",
    "# path where the image data will be/is stored\n",
    "DATA_BASEPATH = '/tmp/test'\n",
    "\n",
    "# path where experiment configs will be stored\n",
    "EXPERIMENT_STORAGE_FOLDER = '/tmp/exp'\n",
    "\n",
    "# only change in case you want to use tensorboard for model training, otherwise not relevant\n",
    "EXP_OUT = '/tmp'\n",
    "\n",
    "print('writing settings to %s' % path.join(path.dirname(xview.__file__), 'settings.py'))\n",
    "with open(path.join(path.dirname(xview.__file__), 'settings.py'), 'w') as settings_file:\n",
    "    settings_file.write(\"DATA_BASEPATH = '%s'\\n\" % DATA_BASEPATH)\n",
    "    settings_file.write(\"EXPERIMENT_STORAGE_FOLDER = '%s'\\n\" % EXPERIMENT_STORAGE_FOLDER)\n",
    "    settings_file.write(\"EXP_OUT = '%s'\\n\" % EXP_OUT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2. Downloading Cityscapes data**  \n",
    "To download the cityscapes data, you have to [register](https://www.cityscapes-dataset.com/login/) with your own account. Please download the files `gtFine_trainvaltest.zip` and `leftImg8bit_trainvaltest.zip`. Afterwards, please place the downloaded archive in the following directory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/test\n"
     ]
    }
   ],
   "source": [
    "from xview.settings import DATA_BASEPATH; print(DATA_BASEPATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once placed in the above directory, the following code extracts and organizes the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from xview.settings import DATA_BASEPATH\n",
    "from os import path, makedirs, remove\n",
    "import zipfile\n",
    "with zipfile.ZipFile(path.join(DATA_BASEPATH, 'gtFine_trainvaltest.zip')) as archive:\n",
    "    archive.extractall(path.join(DATA_BASEPATH, 'cityscapes/gtFine_trainvaltest'))\n",
    "with zipfile.ZipFile(path.join(DATA_BASEPATH, 'leftImg8bit_trainvaltest.zip')) as archive:\n",
    "    archive.extractall(path.join(DATA_BASEPATH, 'cityscapes/leftImg8bit_trainvaltest'))\n",
    "remove(path.join(DATA_BASEPATH, 'gtFine_trainvaltest.zip'))\n",
    "remove(path.join(DATA_BASEPATH, 'leftImg8bit_trainvaltest.zip'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**3. Downloading Experimental Data**  \n",
    "All training and measurement experiments are bundeled into an archive that is downloaded and installed. This gives you access to pre-trained models and all experimental configurations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! wget http://robotics.ethz.ch/~asl-datasets/2018_modular_semantic_segmentation/experimental_data.tar.gz -O /tmp/experimental_data.tar.gz\n",
    "import tarfile\n",
    "from os import path\n",
    "from xview.settings import EXPERIMENT_STORAGE_FOLDER\n",
    "tar = tarfile.open('/tmp/experimental_data.tar.gz')\n",
    "tar.extractall(path=EXPERIMENT_STORAGE_FOLDER)\n",
    "tar.close()\n",
    "! rm /tmp/experimental_data.tar.gz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Single Examples for 'Cityscapes' Fusion\n",
    "The following cells reproduce figure 4 from the paper.\n",
    "\n",
    "The pretrained models for rgb (860) and depth (861) are loaded. Also, confusion matrices and dirichlet parameters fitted on the measure-set of Cityscapes are loaded from experiments 868 and 878."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from xview.datasets import Cityscapes\n",
    "from xview.models import Adapnet, BayesFusion, AverageFusion, DirichletFusion\n",
    "from experiments.utils import ExperimentData\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Load the relevant experiments. If this fails, your config from above is not setup properly.\n",
    "rgb = ExperimentData(860)\n",
    "depth = ExperimentData(861)\n",
    "bayes = ExperimentData(868)\n",
    "dirichlet = ExperimentData(878)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now load example images to do inference of all the different fusion models. 39, 192 and 177 are the images also shown in the paper, you can test any other images by entering random indizes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "data = Cityscapes(resize=True)\n",
    "images = data._get_batch([data.testset[i] for i in [39, 192, 177]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For inference, all configurations are loaded from the referenced experiments. Configurations include e.g. architecture details, which modalities of the data is used as input etc. As an example, this is the config for the bayes fusion:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'evaluation_data': {'batchsize': 4,\n",
       "  'dataset': 'cityscapes_c',\n",
       "  'in_memory': True,\n",
       "  'resize': True},\n",
       " 'net_config': {'expert_model': 'adapnet',\n",
       "  'learning_rate': 0,\n",
       "  'num_channels': {'depth': 1, 'rgb': 3},\n",
       "  'num_classes': 12,\n",
       "  'num_units': 20,\n",
       "  'prefixes': {'depth': 'depth', 'rgb': 'rgb'},\n",
       "  'trainer': 'rmsprop'},\n",
       " 'seed': 453280996,\n",
       " 'starting_weights': {'depth': 861, 'rgb': 860}}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bayes.get_record()['config']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "predictions = {}\n",
    "# rgb and depth prediction\n",
    "for key, exp in {'rgb': rgb, 'depth': depth}.items():\n",
    "    config = exp.get_record()['config']['net_config']\n",
    "    with Adapnet(data_description=data.get_data_description(), **config) as net:\n",
    "        net.import_weights(exp.get_weights(), warnings=False)\n",
    "        predictions[key] = net.predict(images)\n",
    "# fusion predictions\n",
    "config = bayes.get_record()['config']['net_config']\n",
    "config['confusion_matrices'] = {m: np.array(val)\n",
    "                                for m, val in bayes.get_record()['info']['confusion_matrices'].items()}\n",
    "\n",
    "with BayesFusion(data_description=data.get_data_description(), **config) as net:\n",
    "    [net.import_weights(exp.get_weights(), warnings=False) for exp in [rgb, depth]]\n",
    "    predictions['bayes'] = net.predict(images)\n",
    "    \n",
    "with AverageFusion(data_description=data.get_data_description(), **config) as net:\n",
    "    [net.import_weights(exp.get_weights(), warnings=False) for exp in [rgb, depth]]\n",
    "    predictions['average'] = net.predict(images)\n",
    "    \n",
    "config = dirichlet.get_record()['config']['net_config']\n",
    "config['dirichlet_params'] = {key: np.array(val)\n",
    "                              for key, val in dirichlet.get_record()['info']['dirichlet_params'].items()}\n",
    "with DirichletFusion(data_description=data.get_data_description(), **config) as net:\n",
    "    [net.import_weights(exp.get_weights(), warnings=False) for exp in [rgb, depth]]\n",
    "    predictions['dirichlet'] = net.predict(images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 828x1152 with 24 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ncols = images['rgb'].shape[0]\n",
    "label_params = {'fontsize': 16}\n",
    "fig, axs = plt.subplots(8, ncols, figsize=(11.5,16), gridspec_kw = {'wspace':.05, 'hspace':.05})\n",
    "\n",
    "for col in range(ncols):\n",
    "    axs[0][col].imshow(images['rgb'][col].astype('int'))\n",
    "    axs[1][col].imshow(np.squeeze(images['depth'][col]))\n",
    "    axs[2][col].imshow(data.coloured_labels(predictions['rgb'][col]))\n",
    "    axs[3][col].imshow(data.coloured_labels(predictions['depth'][col]))\n",
    "    axs[4][col].imshow(data.coloured_labels(predictions['average'][col]))\n",
    "    axs[5][col].imshow(data.coloured_labels(predictions['bayes'][col]))\n",
    "    axs[6][col].imshow(data.coloured_labels(predictions['dirichlet'][col]))\n",
    "    axs[7][col].imshow(data.coloured_labels(images['labels'][col]))\n",
    "\n",
    "for row, title in {0: 'RGB', 1: 'Depth', 2: 'RGB', 3: 'Depth', 4: 'Average', 5: 'Bayes',\n",
    "                   6: 'Dirichlet', 7: 'Ground Truth'}.items():\n",
    "    axs[row][0].set_ylabel(title, **label_params)\n",
    "    for ax in axs[row]:\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantitative Evaluation of 'Synthia RAND' Fusion\n",
    "\n",
    "In the following, we compare the different fusion methods quantitatively and show how the tables in the paper were produced.  \n",
    "The function `print_tables` simply loads the measurements out of the referenced experiments and displays all results in a table. In particular, these cells do not measure the model's against the Cityscapes test set, but load measurement results that were produced by the authors.  \n",
    "Below the tables we show how to revalidate the measurement results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_tables(data, **experiments):\n",
    "    table_data = {}\n",
    "    for key, experiment_id in experiments.items():\n",
    "        measurements = ExperimentData(experiment_id).get_record()['info']['measurements']\n",
    "        if key == 'bayes':\n",
    "            table_data[key.title()] = measurements['fusion']['IoU']\n",
    "            # with the bayes experiments, we also measure the single baselines\n",
    "            for modality in ('RGB', 'Depth'):\n",
    "                table_data[modality] = measurements[modality.lower()]['IoU']\n",
    "        else:\n",
    "            table_data[key.title()] = measurements['IoU']\n",
    "        \n",
    "    classes = pd.DataFrame(table_data, index=[i['name'] for i in data.labelinfo.values()])\n",
    "    mean = pd.DataFrame({col: classes[col][1:].mean() for col in classes.columns}, index=['mean'])\n",
    "    \n",
    "    # now order the columns\n",
    "    ordered_columns = []\n",
    "    for key in ['Fusion_Fcn', 'Dirichlet', 'Bayes', 'Average', 'Variance', 'RGB', 'Depth']:\n",
    "        if key in classes.columns:\n",
    "            ordered_columns.append(key)\n",
    "    return mean.append(classes)[ordered_columns]\n",
    "pd.set_option('display.precision', 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**1. Both RGB and Depth trained on Cityscapes** (Table III)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "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>Dirichlet</th>\n",
       "      <th>Bayes</th>\n",
       "      <th>Average</th>\n",
       "      <th>RGB</th>\n",
       "      <th>Depth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.6922</td>\n",
       "      <td>0.6877</td>\n",
       "      <td>0.6847</td>\n",
       "      <td>0.6920</td>\n",
       "      <td>0.5412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>void</th>\n",
       "      <td>0.6520</td>\n",
       "      <td>0.6498</td>\n",
       "      <td>0.6814</td>\n",
       "      <td>0.6575</td>\n",
       "      <td>0.6577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sky</th>\n",
       "      <td>0.8697</td>\n",
       "      <td>0.9045</td>\n",
       "      <td>0.8893</td>\n",
       "      <td>0.9054</td>\n",
       "      <td>0.7860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>building</th>\n",
       "      <td>0.8460</td>\n",
       "      <td>0.8359</td>\n",
       "      <td>0.8432</td>\n",
       "      <td>0.8409</td>\n",
       "      <td>0.7283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>road</th>\n",
       "      <td>0.9237</td>\n",
       "      <td>0.9171</td>\n",
       "      <td>0.9259</td>\n",
       "      <td>0.9153</td>\n",
       "      <td>0.9179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sidewalk</th>\n",
       "      <td>0.6766</td>\n",
       "      <td>0.6501</td>\n",
       "      <td>0.6725</td>\n",
       "      <td>0.6642</td>\n",
       "      <td>0.5758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fence</th>\n",
       "      <td>0.4154</td>\n",
       "      <td>0.3792</td>\n",
       "      <td>0.4079</td>\n",
       "      <td>0.3984</td>\n",
       "      <td>0.2362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vegetation</th>\n",
       "      <td>0.8713</td>\n",
       "      <td>0.8804</td>\n",
       "      <td>0.8448</td>\n",
       "      <td>0.8804</td>\n",
       "      <td>0.6656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pole</th>\n",
       "      <td>0.4423</td>\n",
       "      <td>0.4211</td>\n",
       "      <td>0.4377</td>\n",
       "      <td>0.4194</td>\n",
       "      <td>0.3328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vehicle</th>\n",
       "      <td>0.8762</td>\n",
       "      <td>0.8620</td>\n",
       "      <td>0.8702</td>\n",
       "      <td>0.8654</td>\n",
       "      <td>0.7792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>traffic sign</th>\n",
       "      <td>0.5129</td>\n",
       "      <td>0.5137</td>\n",
       "      <td>0.4833</td>\n",
       "      <td>0.5212</td>\n",
       "      <td>0.1885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>person</th>\n",
       "      <td>0.6490</td>\n",
       "      <td>0.6354</td>\n",
       "      <td>0.6475</td>\n",
       "      <td>0.6354</td>\n",
       "      <td>0.5227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bicycle</th>\n",
       "      <td>0.5313</td>\n",
       "      <td>0.5654</td>\n",
       "      <td>0.5098</td>\n",
       "      <td>0.5657</td>\n",
       "      <td>0.2200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Dirichlet   Bayes  Average     RGB   Depth\n",
       "mean             0.6922  0.6877   0.6847  0.6920  0.5412\n",
       "void             0.6520  0.6498   0.6814  0.6575  0.6577\n",
       "sky              0.8697  0.9045   0.8893  0.9054  0.7860\n",
       "building         0.8460  0.8359   0.8432  0.8409  0.7283\n",
       "road             0.9237  0.9171   0.9259  0.9153  0.9179\n",
       "sidewalk         0.6766  0.6501   0.6725  0.6642  0.5758\n",
       "fence            0.4154  0.3792   0.4079  0.3984  0.2362\n",
       "vegetation       0.8713  0.8804   0.8448  0.8804  0.6656\n",
       "pole             0.4423  0.4211   0.4377  0.4194  0.3328\n",
       "vehicle          0.8762  0.8620   0.8702  0.8654  0.7792\n",
       "traffic sign     0.5129  0.5137   0.4833  0.5212  0.1885\n",
       "person           0.6490  0.6354   0.6475  0.6354  0.5227\n",
       "bicycle          0.5313  0.5654   0.5098  0.5657  0.2200"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print_tables(Cityscapes(), bayes=868, average=867, dirichlet=878)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2. With Depth trained on Synthia RAND** (Table IV)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "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>Dirichlet</th>\n",
       "      <th>Bayes</th>\n",
       "      <th>Average</th>\n",
       "      <th>RGB</th>\n",
       "      <th>Depth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.801852</td>\n",
       "      <td>0.799118</td>\n",
       "      <td>0.790490</td>\n",
       "      <td>0.759173</td>\n",
       "      <td>0.637632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>void</th>\n",
       "      <td>0.798663</td>\n",
       "      <td>0.753131</td>\n",
       "      <td>0.798512</td>\n",
       "      <td>0.738616</td>\n",
       "      <td>0.719206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sky</th>\n",
       "      <td>0.973943</td>\n",
       "      <td>0.974090</td>\n",
       "      <td>0.955738</td>\n",
       "      <td>0.955436</td>\n",
       "      <td>0.094735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>building</th>\n",
       "      <td>0.968455</td>\n",
       "      <td>0.967552</td>\n",
       "      <td>0.961995</td>\n",
       "      <td>0.936966</td>\n",
       "      <td>0.798560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>road</th>\n",
       "      <td>0.940887</td>\n",
       "      <td>0.927821</td>\n",
       "      <td>0.931128</td>\n",
       "      <td>0.915791</td>\n",
       "      <td>0.889205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sidewalk</th>\n",
       "      <td>0.950653</td>\n",
       "      <td>0.940441</td>\n",
       "      <td>0.946958</td>\n",
       "      <td>0.917111</td>\n",
       "      <td>0.935961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fence</th>\n",
       "      <td>0.747647</td>\n",
       "      <td>0.729677</td>\n",
       "      <td>0.745399</td>\n",
       "      <td>0.683018</td>\n",
       "      <td>0.718872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vegetation</th>\n",
       "      <td>0.898939</td>\n",
       "      <td>0.906167</td>\n",
       "      <td>0.900205</td>\n",
       "      <td>0.814190</td>\n",
       "      <td>0.903152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pole</th>\n",
       "      <td>0.655285</td>\n",
       "      <td>0.664174</td>\n",
       "      <td>0.647926</td>\n",
       "      <td>0.561722</td>\n",
       "      <td>0.601941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>car</th>\n",
       "      <td>0.931914</td>\n",
       "      <td>0.913920</td>\n",
       "      <td>0.928124</td>\n",
       "      <td>0.878054</td>\n",
       "      <td>0.905565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>traffic sign</th>\n",
       "      <td>0.417546</td>\n",
       "      <td>0.515396</td>\n",
       "      <td>0.483115</td>\n",
       "      <td>0.457722</td>\n",
       "      <td>0.377578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pedestrian</th>\n",
       "      <td>0.799350</td>\n",
       "      <td>0.747336</td>\n",
       "      <td>0.797209</td>\n",
       "      <td>0.737037</td>\n",
       "      <td>0.727711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bicycle</th>\n",
       "      <td>0.654658</td>\n",
       "      <td>0.631115</td>\n",
       "      <td>0.644172</td>\n",
       "      <td>0.585717</td>\n",
       "      <td>0.593955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lanemarking</th>\n",
       "      <td>0.682949</td>\n",
       "      <td>0.671727</td>\n",
       "      <td>0.543910</td>\n",
       "      <td>0.667318</td>\n",
       "      <td>0.104353</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Dirichlet     Bayes   Average       RGB     Depth\n",
       "mean           0.801852  0.799118  0.790490  0.759173  0.637632\n",
       "void           0.798663  0.753131  0.798512  0.738616  0.719206\n",
       "sky            0.973943  0.974090  0.955738  0.955436  0.094735\n",
       "building       0.968455  0.967552  0.961995  0.936966  0.798560\n",
       "road           0.940887  0.927821  0.931128  0.915791  0.889205\n",
       "sidewalk       0.950653  0.940441  0.946958  0.917111  0.935961\n",
       "fence          0.747647  0.729677  0.745399  0.683018  0.718872\n",
       "vegetation     0.898939  0.906167  0.900205  0.814190  0.903152\n",
       "pole           0.655285  0.664174  0.647926  0.561722  0.601941\n",
       "car            0.931914  0.913920  0.928124  0.878054  0.905565\n",
       "traffic sign   0.417546  0.515396  0.483115  0.457722  0.377578\n",
       "pedestrian     0.799350  0.747336  0.797209  0.737037  0.727711\n",
       "bicycle        0.654658  0.631115  0.644172  0.585717  0.593955\n",
       "lanemarking    0.682949  0.671727  0.543910  0.667318  0.104353"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print_tables(SynthiaCityscapes(labels={'lanemarkings': True}), bayes=820, average=819, dirichlet=856)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to reproduce quantitative measurements\n",
    "To reproduce the evaluation experiments listed above, simply run the following cell with the correct `experiment_id`. The command will run the exact same script that was used to produce the measurement results. It will load the pretrained models, measure them on the measurement-set and use the measurements to produce decision functions for the bayes fusion or dirichlet fusion. Again, all the configurations of an experiment_id can be accessed with `ExperimentData(<experiment_id>).get_record()['config']`.  \n",
    "More info on the experiment management can be found [here](http://sacred.readthedocs.io/en/latest/).\n",
    "\n",
    "**There seem to be implementational issues internal to tensorflow. We experienced different results on CPU and GPU. The below example is run on a CPU, the reported results were computed (and validated multiple times) on a GPU. Please note the difference of 2% IoU.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING - root - Added new config entry: \"experiment_id\"\n",
      "INFO - rerun - Running command 'rerun'\n",
      "INFO - rerun - Started\n",
      "Re-Run of experiment \"cityC bayes fusion\"\n",
      "2018-07-23 11:27:20.116544: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
      "2018-07-23 11:27:20.590292: W tensorflow/core/framework/allocator.cc:108] Allocation of 16777216 exceeds 10% of system memory.\n",
      "2018-07-23 11:27:20.596442: W tensorflow/core/framework/allocator.cc:108] Allocation of 16777216 exceeds 10% of system memory.\n",
      "2018-07-23 11:27:20.684443: W tensorflow/core/framework/allocator.cc:108] Allocation of 16777216 exceeds 10% of system memory.\n",
      "2018-07-23 11:27:20.690833: W tensorflow/core/framework/allocator.cc:108] Allocation of 16777216 exceeds 10% of system memory.\n",
      "2018-07-23 11:27:20.802845: W tensorflow/core/framework/allocator.cc:108] Allocation of 16777216 exceeds 10% of system memory.\n",
      "INFO Environment Variable TMPDIR not set, could not unpack data and load into memory\n",
      "Now trying to load every image seperately\n",
      "/home/spadmin/Dropbox/ETH/Masterarbeit/documentation/iros_paper/newdata/860/Adapnet_weights_100000.npz\n",
      "Evaluated network rgb on cityscapes_c train data:\n",
      "INFO now getting test results\n",
      "total accuracy 0.924 IoU 0.691\n",
      "INFO Environment Variable TMPDIR not set, could not unpack data and load into memory\n",
      "Now trying to load every image seperately\n",
      "/home/spadmin/Dropbox/ETH/Masterarbeit/documentation/iros_paper/newdata/861/Adapnet_weights_100000.npz\n",
      "Evaluated network depth on cityscapes_c train data:\n",
      "INFO now getting test results\n",
      "total accuracy 0.873 IoU 0.541\n",
      "INFO Environment Variable TMPDIR not set, could not unpack data and load into memory\n",
      "Now trying to load every image seperately\n",
      "/home/spadmin/Dropbox/ETH/Masterarbeit/documentation/iros_paper/newdata/860/Adapnet_weights_100000.npz\n",
      "WARNING: depth/block_0_1/kernel not found in saved weights\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/spadmin/Dropbox/ETH/Masterarbeit/documentation/iros_paper/newdata/861/Adapnet_weights_100000.npz\r\n",
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      "WARNING: rgb/block_layer_4/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_4/shortcut/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_4/shortcut/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_4/shortcut/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_4/shortcut/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_4/shortcut/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_5/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_6/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_7/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/shortcut/kernel not found in saved weights\r\n",
      "WARNING: rgb/shortcut/bias not found in saved weights\r\n",
      "WARNING: rgb/shortcut/gamma not found in saved weights\r\n",
      "WARNING: rgb/shortcut/beta not found in saved weights\r\n",
      "WARNING: rgb/shortcut/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/shortcut/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/shortcut/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/shortcut/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/shortcut/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/shortcut/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_8/shortcut/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_9/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_10/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_11/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_12/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_13/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/shortcut/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/shortcut/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/shortcut/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/shortcut/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_14/shortcut/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_15/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_1/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_1/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_1/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_1/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_1/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_2/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_2/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_2/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_2/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_2_2/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_3/kernel not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_3/gamma not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_3/beta not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_3/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/block_layer_16/stage_3/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/kernel not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/bias not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/gamma not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/beta not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_conv/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_upconv/kernel not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_upconv/gamma not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_upconv/beta not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_upconv/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/first_deconvolution_upconv/moving_variance not found in saved weights\r\n",
      "WARNING: rgb/second_deconvolution_upconv/kernel not found in saved weights\r\n",
      "WARNING: rgb/second_deconvolution_upconv/gamma not found in saved weights\r\n",
      "WARNING: rgb/second_deconvolution_upconv/beta not found in saved weights\r\n",
      "WARNING: rgb/second_deconvolution_upconv/moving_mean not found in saved weights\r\n",
      "WARNING: rgb/second_deconvolution_upconv/moving_variance not found in saved weights\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Evaluated Bayes Fusion on cityscapes_c data:\n",
      "total accuracy 0.907 IoU 0.666\n",
      "INFO - rerun - Completed after 1:00:11\n"
     ]
    }
   ],
   "source": [
    "! python -m experiments.rerun with experiment_id=868 -u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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