RAFT.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OWiT2KCJBuqv"
      },
      "source": [
        "This Google Colab demos our method\n",
        "\n",
        "# RAFT-Stereo\n",
        "\n",
        "```\n",
        "@inproceedings{lipson2021raft,\n",
        "  title={RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching},\n",
        "  author={Lipson, Lahav and Teed, Zachary and Deng, Jia},\n",
        "  booktitle={International Conference on 3D Vision (3DV)},\n",
        "  year={2021}\n",
        "}\n",
        "```\n",
        "\n",
        "Github Repo: https://github.com/princeton-vl/RAFT-Stereo\n",
        "\n",
        "Paper: https://arxiv.org/pdf/2109.07547.pdf\n",
        "\n",
        "## Steps\n",
        "\n",
        "1)   Build the Conda Environment [~9 min] (**This will restart the runtime. To run steps 2-5, select the next cell and from the dropdown menu select `Runtime -> Run after`**)\n",
        "\n",
        "2)   Download sample data\n",
        "\n",
        "3)   Run RAFT-Stereo\n",
        "\n",
        "4)   Create Point Cloud From Predicted Disparity\n",
        "\n",
        "5)   Visualize 3D Point Cloud"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aMNH6rW5Hgsb"
      },
      "source": [
        "## 1) Build the Conda Environment [~9 min]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PGHGaUizO6vB",
        "outputId": "ba37d2f6-8c15-4ae7-ee5c-c4faee63b603"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "# Install conda\n",
        "!pip install -q condacolab\n",
        "from shutil import which\n",
        "import condacolab\n",
        "if which(\"conda\") is None:\n",
        "  condacolab.install()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BltypgkLPimu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9fa5ff26-27ba-484c-f7a1-571216766572"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'RAFT-Stereo' already exists and is not an empty directory.\n",
            "/content/RAFT-Stereo\n",
            "Collecting package metadata (repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ WARNING conda.models.version:get_matcher(546): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.6.0.*, but conda is ignoring the .* and treating it as 1.6.0\n",
            "WARNING conda.models.version:get_matcher(546): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.9.0.*, but conda is ignoring the .* and treating it as 1.9.0\n",
            "WARNING conda.models.version:get_matcher(546): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.8.0.*, but conda is ignoring the .* and treating it as 1.8.0\n",
            "WARNING conda.models.version:get_matcher(546): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.7.1.*, but conda is ignoring the .* and treating it as 1.7.1\n",
            "\b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Solving environment: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- 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\b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "\n",
            "\n",
            "==> WARNING: A newer version of conda exists. <==\n",
            "  current version: 23.1.0\n",
            "  latest version: 23.10.0\n",
            "\n",
            "Please update conda by running\n",
            "\n",
            "    $ conda update -n base -c conda-forge conda\n",
            "\n",
            "Or to minimize the number of packages updated during conda update use\n",
            "\n",
            "     conda install conda=23.10.0\n",
            "\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "mkl_random-1.2.2     | 287 KB    | :   0% 0/1 [00:00<?, ?it/s]\n",
            "libedit-3.1.20221030 | 181 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "harfbuzz-1.8.8       | 507 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "zipp-3.11.0          | 19 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "_libgcc_mutex-0.1    | 3 KB      | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libpng-1.6.39        | 304 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cachetools-4.2.2     | 13 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "openssl-1.1.1w       | 3.7 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "tensorboard-data-ser | 3.9 MB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 10.5 MB   | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "matplotlib-3.5.3     | 7 KB      | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
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            "\n",
            "idna-3.4             | 91 KB     | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "dask-core-2021.10.0  | 718 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "werkzeug-2.2.2       | 337 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
            "\n",
            "\n",
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            "\n",
            "libopus-1.3.1        | 491 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "ncurses-6.4          | 914 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "absl-py-1.3.0        | 166 KB    | :   0% 0/1 [00:00<?, ?it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "mkl_random-1.2.2     | 287 KB    | :   6% 0.05574438694443594/1 [00:00<00:02,  2.68s/it]\n",
            "\n",
            "\n",
            "\n",
            "zipp-3.11.0          | 19 KB     | :  84% 0.8424949863732195/1 [00:00<00:00,  5.92it/s]\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "harfbuzz-1.8.8       | 507 KB    | :   3% 0.031560130678666094/1 [00:00<00:04,  4.97s/it]\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "zipp-3.11.0          | 19 KB     | : 100% 1.0/1 [00:00<00:00,  5.92it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "_libgcc_mutex-0.1    | 3 KB      | : 100% 1.0/1 [00:00<00:00,  5.46it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libpng-1.6.39        | 304 KB    | :   5% 0.05264290924046281/1 [00:00<00:03,  3.71s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :   0% 0.000715916889669709/1 [00:00<04:51, 291.32s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "openssl-1.1.1w       | 3.7 MB    | :   0% 0.004187193943698291/1 [00:00<00:49, 49.63s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cachetools-4.2.2     | 13 KB     | : 100% 1.0/1 [00:00<00:00,  4.60it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "libedit-3.1.20221030 | 181 KB    | : 100% 1.0/1 [00:00<00:00,  1.64s/it]                \u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "tensorboard-data-ser | 3.9 MB    | :   0% 0.004002919120950752/1 [00:00<00:56, 57.04s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "_libgcc_mutex-0.1    | 3 KB      | : 100% 1.0/1 [00:00<00:00,  5.46it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "mkl_random-1.2.2     | 287 KB    | : 100% 1.0/1 [00:00<00:00,  3.96it/s]\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :   5% 0.05226193294588876/1 [00:00<00:04,  4.75s/it]  \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "openssl-1.1.1w       | 3.7 MB    | :  25% 0.25123163662189746/1 [00:00<00:00,  1.01it/s] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "tensorboard-data-ser | 3.9 MB    | :  45% 0.4483269415464842/1 [00:00<00:00,  1.72it/s]  \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 10.5 MB   | :  16% 0.16217206772255915/1 [00:00<00:01,  1.71s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  17% 0.16824046907238163/1 [00:00<00:01,  1.80s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "openssl-1.1.1w       | 3.7 MB    | :  88% 0.8751235342329429/1 [00:00<00:00,  2.91it/s] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libpng-1.6.39        | 304 KB    | : 100% 1.0/1 [00:00<00:00,  2.68it/s]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libpng-1.6.39        | 304 KB    | : 100% 1.0/1 [00:00<00:00,  2.68it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "harfbuzz-1.8.8       | 507 KB    | : 100% 1.0/1 [00:00<00:00,  2.39it/s]                 \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "harfbuzz-1.8.8       | 507 KB    | : 100% 1.0/1 [00:00<00:00,  2.39it/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 10.5 MB   | :  40% 0.4046862607388632/1 [00:00<00:00,  1.21it/s] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   0% 2.7165309758836265e-05/1 [00:00<4:40:18, 16819.01s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "matplotlib-3.5.3     | 7 KB      | : 100% 1.0/1 [00:00<00:00,  2.17it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "idna-3.4             | 91 KB     | :  18% 0.17528431278150441/1 [00:00<00:02,  2.62s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "cachetools-4.2.2     | 13 KB     | : 100% 1.0/1 [00:00<00:00,  4.60it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  29% 0.2935259247645807/1 [00:00<00:00,  1.26s/it] \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "werkzeug-2.2.2       | 337 KB    | :   5% 0.04750224696297585/1 [00:00<00:10, 10.65s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "dask-core-2021.10.0  | 718 KB    | :   2% 0.022275366712847085/1 [00:00<00:23, 23.78s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "libopus-1.3.1        | 491 KB    | :   3% 0.0325638248183887/1 [00:00<00:16, 16.57s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 10.5 MB   | :  61% 0.6055415739732255/1 [00:00<00:00,  1.47it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   0% 0.0014669267269771583/1 [00:00<04:49, 289.67s/it]     \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "ncurses-6.4          | 914 KB    | :   2% 0.01750655534161504/1 [00:00<00:33, 33.63s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "absl-py-1.3.0        | 166 KB    | :  10% 0.09635209917491458/1 [00:00<00:05,  6.21s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  42% 0.41523179600843124/1 [00:00<00:00,  1.10s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "icu-58.2             | 10.5 MB   | :  87% 0.8703730240155698/1 [00:00<00:00,  1.85it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   1% 0.005813376288390961/1 [00:00<01:13, 73.75s/it]  \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  54% 0.5419490854799698/1 [00:00<00:00,  1.02it/s] \u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   1% 0.008557072574033424/1 [00:00<00:57, 58.07s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "tensorboard-data-ser | 3.9 MB    | : 100% 1.0/1 [00:00<00:00,  1.26it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "tensorboard-data-ser | 3.9 MB    | : 100% 1.0/1 [00:00<00:00,  1.26it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  65% 0.6507684527097656/1 [00:00<00:00,  1.05s/it]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   1% 0.011626752576781921/1 [00:00<00:47, 47.85s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
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            "\n",
            "\n",
            "\n",
            "matplotlib-3.5.3     | 7 KB      | : 100% 1.0/1 [00:00<00:00,  2.17it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   2% 0.01600036744795456/1 [00:00<00:36, 37.00s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  75% 0.7509968172635247/1 [00:01<00:00,  1.23s/it]\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
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            "\n",
            "idna-3.4             | 91 KB     | : 100% 1.0/1 [00:01<00:00,  1.08it/s]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "idna-3.4             | 91 KB     | : 100% 1.0/1 [00:01<00:00,  1.08it/s]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   2% 0.019260204619014912/1 [00:01<00:34, 35.22s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  84% 0.839054594692899/1 [00:01<00:00,  1.33s/it] \u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "openssl-1.1.1w       | 3.7 MB    | : 100% 1.0/1 [00:01<00:00,  2.91it/s]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   2% 0.022492876480316427/1 [00:01<00:34, 35.24s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "libopencv-3.4.2      | 21.8 MB   | :  95% 0.9464421281433554/1 [00:01<00:00,  1.22s/it]\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "libopus-1.3.1        | 491 KB    | : 100% 1.0/1 [00:01<00:00,  1.11s/it]               \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "libopus-1.3.1        | 491 KB    | : 100% 1.0/1 [00:01<00:00,  1.11s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   3% 0.025698383031859107/1 [00:01<00:33, 34.04s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "werkzeug-2.2.2       | 337 KB    | : 100% 1.0/1 [00:01<00:00,  1.17s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "werkzeug-2.2.2       | 337 KB    | : 100% 1.0/1 [00:01<00:00,  1.17s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   3% 0.02947436108833735/1 [00:01<00:30, 31.46s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :   3% 0.03284285949843305/1 [00:01<00:30, 31.11s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "absl-py-1.3.0        | 166 KB    | : 100% 1.0/1 [00:01<00:00,  1.34s/it]                \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
            "absl-py-1.3.0        | 166 KB    | : 100% 1.0/1 [00:01<00:00,  1.34s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
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            " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  16% 0.15633635766210272/1 [00:08<00:35, 42.19s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  17% 0.1720650720124689/1 [00:10<01:07, 81.33s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "libopencv-3.4.2      | 21.8 MB   | : 100% 1.0/1 [00:14<00:00,  1.22s/it]               \u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  30% 0.302458558854883/1 [00:14<00:28, 41.13s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  56% 0.5622675813883931/1 [00:21<00:08, 18.90s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  57% 0.5676734780304015/1 [00:21<00:08, 19.67s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  57% 0.5728620521943392/1 [00:21<00:08, 19.81s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  58% 0.5779691304290003/1 [00:21<00:08, 20.12s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  58% 0.5829947127343851/1 [00:22<00:08, 20.33s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  59% 0.5894600564569881/1 [00:22<00:07, 18.67s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  60% 0.5954092592941732/1 [00:22<00:07, 18.10s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  60% 0.6009781477947347/1 [00:22<00:07, 18.75s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  61% 0.6063568791269843/1 [00:22<00:07, 19.05s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  61% 0.6123875778934459/1 [00:22<00:07, 18.28s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  62% 0.6179021357744897/1 [00:22<00:06, 18.30s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  62% 0.6245848019751634/1 [00:22<00:06, 17.19s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  63% 0.630452508883072/1 [00:22<00:06, 17.73s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  64% 0.6366461995080868/1 [00:22<00:06, 17.27s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  64% 0.6429757166818956/1 [00:23<00:06, 16.82s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  65% 0.6495225563337751/1 [00:23<00:05, 16.34s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  66% 0.6557705775783075/1 [00:23<00:05, 16.26s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  66% 0.6619371028935632/1 [00:23<00:06, 19.55s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  67% 0.6673701648453305/1 [00:23<00:09, 29.32s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  69% 0.6934216969040545/1 [00:25<00:10, 35.72s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  70% 0.6974421627483622/1 [00:25<00:09, 32.96s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  70% 0.7017886123097761/1 [00:25<00:08, 29.98s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  71% 0.7109976523180216/1 [00:25<00:07, 26.14s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  72% 0.7158330774550944/1 [00:25<00:06, 24.48s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  72% 0.7207771638312026/1 [00:25<00:06, 23.77s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  73% 0.7253681011804459/1 [00:26<00:06, 23.18s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  73% 0.7298775426004128/1 [00:26<00:06, 24.88s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  73% 0.7340610003032736/1 [00:26<00:06, 26.28s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  74% 0.7382716233158931/1 [00:26<00:06, 25.92s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  75% 0.7464755468630617/1 [00:26<00:06, 25.39s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  75% 0.7506046739464048/1 [00:26<00:06, 25.84s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  76% 0.7551412806761305/1 [00:26<00:06, 24.64s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  76% 0.7594605649277855/1 [00:26<00:05, 24.26s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  76% 0.764350320684376/1 [00:27<00:05, 23.02s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  77% 0.7687239355555486/1 [00:27<00:05, 23.55s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  77% 0.7730160544974448/1 [00:27<00:05, 23.57s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  78% 0.7780959674223471/1 [00:27<00:05, 23.26s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  78% 0.7828770619399024/1 [00:27<00:04, 22.54s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
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            "\n",
            "\n",
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            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  79% 0.7914884651334534/1 [00:27<00:05, 25.43s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  80% 0.8009963235490462/1 [00:27<00:04, 23.82s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  81% 0.8052341118714246/1 [00:28<00:04, 24.32s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  81% 0.8096348920523561/1 [00:28<00:04, 23.86s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  81% 0.8140085069235287/1 [00:28<00:04, 24.92s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  82% 0.818436452414219/1 [00:28<00:04, 24.22s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  82% 0.8225927448073209/1 [00:28<00:04, 24.23s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  83% 0.8273738393248762/1 [00:28<00:04, 23.55s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  83% 0.8326167441083315/1 [00:28<00:03, 22.06s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  84% 0.8378596488917869/1 [00:28<00:03, 21.22s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  84% 0.8437273557996956/1 [00:28<00:03, 19.80s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  85% 0.8490789218221862/1 [00:28<00:02, 19.46s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  86% 0.8558974145716542/1 [00:29<00:02, 18.01s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  86% 0.8628245685601574/1 [00:29<00:02, 17.60s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  87% 0.8688552673266191/1 [00:29<00:02, 17.60s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  88% 0.8752934457394633/1 [00:29<00:02, 17.05s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  88% 0.8811611526473719/1 [00:29<00:02, 17.30s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  89% 0.886947363626004/1 [00:29<00:01, 17.37s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  89% 0.8927064092948773/1 [00:29<00:02, 19.15s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  90% 0.8980308100076092/1 [00:29<00:02, 20.18s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  91% 0.9063433947938132/1 [00:29<00:01, 17.07s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  91% 0.9130803916140046/1 [00:30<00:01, 16.39s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  92% 0.9195185700268488/1 [00:30<00:01, 16.35s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  93% 0.9257394259616223/1 [00:30<00:01, 16.39s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  93% 0.931905951276878/1 [00:30<00:01, 17.19s/it] \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  94% 0.9378008234945455/1 [00:30<00:01, 17.22s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  94% 0.9437500263317307/1 [00:30<00:00, 17.10s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  95% 0.9496448985493982/1 [00:30<00:00, 17.80s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  96% 0.9553224482889949/1 [00:30<00:00, 18.29s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  96% 0.9608370061700388/1 [00:30<00:00, 23.13s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  97% 0.9661342415730118/1 [00:31<00:00, 21.94s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  97% 0.9716216341442967/1 [00:31<00:00, 20.91s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  98% 0.9766743817594402/1 [00:31<00:00, 20.83s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  98% 0.9819987824721722/1 [00:31<00:00, 20.23s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | :  99% 0.9875405056629748/1 [00:31<00:00, 19.59s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
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            "\n",
            "\n",
            "pytorch-1.7.0        | 575.2 MB  | :  99% 0.9937341962879894/1 [00:31<00:00, 18.46s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "pytorch-1.7.0        | 575.2 MB  | : 100% 0.9992487541690331/1 [00:31<00:00, 19.08s/it]\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "                                                                        \n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "\n",
            "\n",
            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
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            "                                                                        \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\u001b[A\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "\u001b[A\n",
            "\n",
            "\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "\n",
            "\u001b[A\u001b[A\u001b[A\u001b[A\n",
            "Preparing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Verifying transaction: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Executing transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "#\n",
            "# To activate this environment, use\n",
            "#\n",
            "#     $ conda activate raftstereo\n",
            "#\n",
            "# To deactivate an active environment, use\n",
            "#\n",
            "#     $ conda deactivate\n",
            "\n",
            "\n",
            "The runtime has restarted. To run steps 2-5, select the next cell and from the dropdown select Runtime -> Run after\n"
          ]
        }
      ],
      "source": [
        "!git clone --recursive https://github.com/princeton-vl/RAFT-Stereo.git\n",
        "%cd /content/RAFT-Stereo\n",
        "!conda env create -f environment.yaml\n",
        "print(\"\\nThe runtime has restarted. To run steps 2-5, select the next cell and from the dropdown select Runtime -> Run after\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h3BjTEGMvr6x"
      },
      "source": [
        "## 2) Download sample data [~1 min]\n",
        "\n",
        "### **To run steps 2-5, select this cell and from the dropdown menu select `Runtime -> Run after**`"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "l1x3PYQe61rv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "B2q5jq4SRIta",
        "outputId": "fbed74b9-1d90-48d2-d995-8a6292647fdb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/RAFT-Stereo\n",
            "Collecting imageio\n",
            "  Downloading imageio-2.32.0-py3-none-any.whl (313 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m313.3/313.3 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting numpy\n",
            "  Downloading numpy-1.26.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m18.2/18.2 MB\u001b[0m \u001b[31m58.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pillow<10.1.0,>=8.3.2\n",
            "  Downloading Pillow-10.0.1-cp310-cp310-manylinux_2_28_x86_64.whl (3.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.6/3.6 MB\u001b[0m \u001b[31m89.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: pillow, numpy, imageio\n",
            "Successfully installed imageio-2.32.0 numpy-1.26.1 pillow-10.0.1\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m--2023-11-07 20:25:42--  https://www.dropbox.com/s/fn8siy5muak3of3/official_train.txt\n",
            "Resolving www.dropbox.com (www.dropbox.com)... 162.125.3.18, 2620:100:6018:18::a27d:312\n",
            "Connecting to www.dropbox.com (www.dropbox.com)|162.125.3.18|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: /s/raw/fn8siy5muak3of3/official_train.txt [following]\n",
            "--2023-11-07 20:25:43--  https://www.dropbox.com/s/raw/fn8siy5muak3of3/official_train.txt\n",
            "Reusing existing connection to www.dropbox.com:443.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com/cd/0/inline/CHHZjAMPRaQJICgomgFHDSRSzx93bd6OWcs3tPvyZzRjNXiqk638O9Zlmz6FzIQJTUoWVkW2Bpi2l7W1P50we9X57r2rhBH71ko1BdVZqnud-RT5m5cBeTFLnvnmf3xdo3Z9gOkjI5rQZPJPJ1MBSRCd/file# [following]\n",
            "--2023-11-07 20:25:43--  https://uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com/cd/0/inline/CHHZjAMPRaQJICgomgFHDSRSzx93bd6OWcs3tPvyZzRjNXiqk638O9Zlmz6FzIQJTUoWVkW2Bpi2l7W1P50we9X57r2rhBH71ko1BdVZqnud-RT5m5cBeTFLnvnmf3xdo3Z9gOkjI5rQZPJPJ1MBSRCd/file\n",
            "Resolving uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com (uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com)... 162.125.3.15, 2620:100:6018:15::a27d:30f\n",
            "Connecting to uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com (uc8c270cb4be8e71e99e15725dd9.dl.dropboxusercontent.com)|162.125.3.15|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 87 [text/plain]\n",
            "Saving to: ‘MiddEval3/official_train.txt’\n",
            "\n",
            "official_train.txt  100%[===================>]      87  --.-KB/s    in 0s      \n",
            "\n",
            "2023-11-07 20:25:43 (23.5 MB/s) - ‘MiddEval3/official_train.txt’ saved [87/87]\n",
            "\n",
            "--2023-11-07 20:25:44--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-data-Q.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
            "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 30937533 (30M) [application/zip]\n",
            "Saving to: ‘MiddEval3-data-Q.zip’\n",
            "\n",
            "MiddEval3-data-Q.zi 100%[===================>]  29.50M  32.1MB/s    in 0.9s    \n",
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            "2023-11-07 20:25:45 (32.1 MB/s) - ‘MiddEval3-data-Q.zip’ saved [30937533/30937533]\n",
            "\n",
            "Archive:  MiddEval3-data-Q.zip\n",
            "  inflating: MiddEval3/testQ/Australia/calib.txt  \n",
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            "  inflating: MiddEval3/trainingQ/Teddy/calib.txt  \n",
            "  inflating: MiddEval3/trainingQ/Vintage/calib.txt  \n",
            " extracting: MiddEval3/testQ/Australia/im0.png  \n",
            " extracting: MiddEval3/testQ/Australia/im1.png  \n",
            " extracting: MiddEval3/testQ/AustraliaP/im0.png  \n",
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            " extracting: MiddEval3/testQ/Classroom2/im0.png  \n",
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            " extracting: MiddEval3/testQ/Classroom2E/im0.png  \n",
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            " extracting: MiddEval3/testQ/Computer/im0.png  \n",
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            " extracting: MiddEval3/testQ/Hoops/im0.png  \n",
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            " extracting: MiddEval3/testQ/Livingroom/im0.png  \n",
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            " extracting: MiddEval3/testQ/Newkuba/im0.png  \n",
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            " extracting: MiddEval3/trainingQ/PianoL/im0.png  \n",
            " extracting: MiddEval3/trainingQ/PianoL/im1.png  \n",
            " extracting: MiddEval3/trainingQ/Pipes/im0.png  \n",
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            " extracting: MiddEval3/trainingQ/Playtable/im1.png  \n",
            " extracting: MiddEval3/trainingQ/PlaytableP/im0.png  \n",
            " extracting: MiddEval3/trainingQ/PlaytableP/im1.png  \n",
            " extracting: MiddEval3/trainingQ/Recycle/im0.png  \n",
            " extracting: MiddEval3/trainingQ/Recycle/im1.png  \n",
            " extracting: MiddEval3/trainingQ/Teddy/im0.png  \n",
            " extracting: MiddEval3/trainingQ/Teddy/im1.png  \n",
            " extracting: MiddEval3/trainingQ/Vintage/im0.png  \n",
            " extracting: MiddEval3/trainingQ/Vintage/im1.png  \n",
            "  inflating: MiddEval3/trainingQ/Shelves/calib.txt  \n",
            " extracting: MiddEval3/trainingQ/Shelves/im0.png  \n",
            " extracting: MiddEval3/trainingQ/Shelves/im1.png  \n",
            "--2023-11-07 20:25:45--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-GT0-Q.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
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            "Length: 13555667 (13M) [application/zip]\n",
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            "\n",
            "Archive:  MiddEval3-GT0-Q.zip\n",
            "  inflating: MiddEval3/trainingQ/Adirondack/disp0GT.pfm  \n",
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            " extracting: MiddEval3/trainingQ/Adirondack/mask0nocc.png  \n",
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            " extracting: MiddEval3/trainingQ/Shelves/mask0nocc.png  \n",
            "--2023-11-07 20:25:46--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-data-H.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
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            "2023-11-07 20:25:50 (33.6 MB/s) - ‘MiddEval3-data-H.zip’ saved [109900544/109900544]\n",
            "\n",
            "Archive:  MiddEval3-data-H.zip\n",
            "  inflating: MiddEval3/testH/Australia/calib.txt  \n",
            "  inflating: MiddEval3/testH/AustraliaP/calib.txt  \n",
            "  inflating: MiddEval3/testH/Bicycle2/calib.txt  \n",
            "  inflating: MiddEval3/testH/Classroom2/calib.txt  \n",
            "  inflating: MiddEval3/testH/Classroom2E/calib.txt  \n",
            "  inflating: MiddEval3/testH/Computer/calib.txt  \n",
            "  inflating: MiddEval3/testH/Crusade/calib.txt  \n",
            "  inflating: MiddEval3/testH/CrusadeP/calib.txt  \n",
            "  inflating: MiddEval3/testH/Djembe/calib.txt  \n",
            "  inflating: MiddEval3/testH/DjembeL/calib.txt  \n",
            "  inflating: MiddEval3/testH/Hoops/calib.txt  \n",
            "  inflating: MiddEval3/testH/Livingroom/calib.txt  \n",
            "  inflating: MiddEval3/testH/Newkuba/calib.txt  \n",
            "  inflating: MiddEval3/testH/Plants/calib.txt  \n",
            "  inflating: MiddEval3/testH/Staircase/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Adirondack/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/ArtL/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Jadeplant/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Motorcycle/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/MotorcycleE/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Piano/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/PianoL/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Pipes/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Playroom/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Playtable/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/PlaytableP/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Recycle/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Teddy/calib.txt  \n",
            "  inflating: MiddEval3/trainingH/Vintage/calib.txt  \n",
            " extracting: MiddEval3/testH/Australia/im0.png  \n",
            " extracting: MiddEval3/testH/Australia/im1.png  \n",
            " extracting: MiddEval3/testH/AustraliaP/im0.png  \n",
            " extracting: MiddEval3/testH/AustraliaP/im1.png  \n",
            " extracting: MiddEval3/testH/Bicycle2/im0.png  \n",
            " extracting: MiddEval3/testH/Bicycle2/im1.png  \n",
            " extracting: MiddEval3/testH/Classroom2/im0.png  \n",
            " extracting: MiddEval3/testH/Classroom2/im1.png  \n",
            " extracting: MiddEval3/testH/Classroom2E/im0.png  \n",
            " extracting: MiddEval3/testH/Classroom2E/im1.png  \n",
            " extracting: MiddEval3/testH/Computer/im0.png  \n",
            " extracting: MiddEval3/testH/Computer/im1.png  \n",
            " extracting: MiddEval3/testH/Crusade/im0.png  \n",
            " extracting: MiddEval3/testH/Crusade/im1.png  \n",
            " extracting: MiddEval3/testH/CrusadeP/im0.png  \n",
            " extracting: MiddEval3/testH/CrusadeP/im1.png  \n",
            " extracting: MiddEval3/testH/Djembe/im0.png  \n",
            " extracting: MiddEval3/testH/Djembe/im1.png  \n",
            " extracting: MiddEval3/testH/DjembeL/im0.png  \n",
            " extracting: MiddEval3/testH/DjembeL/im1.png  \n",
            " extracting: MiddEval3/testH/Hoops/im0.png  \n",
            " extracting: MiddEval3/testH/Hoops/im1.png  \n",
            " extracting: MiddEval3/testH/Livingroom/im0.png  \n",
            " extracting: MiddEval3/testH/Livingroom/im1.png  \n",
            " extracting: MiddEval3/testH/Newkuba/im0.png  \n",
            " extracting: MiddEval3/testH/Newkuba/im1.png  \n",
            " extracting: MiddEval3/testH/Plants/im0.png  \n",
            " extracting: MiddEval3/testH/Plants/im1.png  \n",
            " extracting: MiddEval3/testH/Staircase/im0.png  \n",
            " extracting: MiddEval3/testH/Staircase/im1.png  \n",
            " extracting: MiddEval3/trainingH/Adirondack/im0.png  \n",
            " extracting: MiddEval3/trainingH/Adirondack/im1.png  \n",
            " extracting: MiddEval3/trainingH/ArtL/im0.png  \n",
            " extracting: MiddEval3/trainingH/ArtL/im1.png  \n",
            " extracting: MiddEval3/trainingH/Jadeplant/im0.png  \n",
            " extracting: MiddEval3/trainingH/Jadeplant/im1.png  \n",
            " extracting: MiddEval3/trainingH/Motorcycle/im0.png  \n",
            " extracting: MiddEval3/trainingH/Motorcycle/im1.png  \n",
            " extracting: MiddEval3/trainingH/MotorcycleE/im0.png  \n",
            " extracting: MiddEval3/trainingH/MotorcycleE/im1.png  \n",
            " extracting: MiddEval3/trainingH/Piano/im0.png  \n",
            " extracting: MiddEval3/trainingH/Piano/im1.png  \n",
            " extracting: MiddEval3/trainingH/PianoL/im0.png  \n",
            " extracting: MiddEval3/trainingH/PianoL/im1.png  \n",
            " extracting: MiddEval3/trainingH/Pipes/im0.png  \n",
            " extracting: MiddEval3/trainingH/Pipes/im1.png  \n",
            " extracting: MiddEval3/trainingH/Playroom/im0.png  \n",
            " extracting: MiddEval3/trainingH/Playroom/im1.png  \n",
            " extracting: MiddEval3/trainingH/Playtable/im0.png  \n",
            " extracting: MiddEval3/trainingH/Playtable/im1.png  \n",
            " extracting: MiddEval3/trainingH/PlaytableP/im0.png  \n",
            " extracting: MiddEval3/trainingH/PlaytableP/im1.png  \n",
            " extracting: MiddEval3/trainingH/Recycle/im0.png  \n",
            " extracting: MiddEval3/trainingH/Recycle/im1.png  \n",
            " extracting: MiddEval3/trainingH/Teddy/im0.png  \n",
            " extracting: MiddEval3/trainingH/Teddy/im1.png  \n",
            " extracting: MiddEval3/trainingH/Vintage/im0.png  \n",
            " extracting: MiddEval3/trainingH/Vintage/im1.png  \n",
            "  inflating: MiddEval3/trainingH/Shelves/calib.txt  \n",
            " extracting: MiddEval3/trainingH/Shelves/im0.png  \n",
            " extracting: MiddEval3/trainingH/Shelves/im1.png  \n",
            "--2023-11-07 20:25:50--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-GT0-H.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
            "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 53097428 (51M) [application/zip]\n",
            "Saving to: ‘MiddEval3-GT0-H.zip’\n",
            "\n",
            "MiddEval3-GT0-H.zip 100%[===================>]  50.64M  30.6MB/s    in 1.7s    \n",
            "\n",
            "2023-11-07 20:25:52 (30.6 MB/s) - ‘MiddEval3-GT0-H.zip’ saved [53097428/53097428]\n",
            "\n",
            "Archive:  MiddEval3-GT0-H.zip\n",
            "  inflating: MiddEval3/trainingH/Adirondack/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/ArtL/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Jadeplant/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Motorcycle/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/MotorcycleE/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Piano/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/PianoL/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Pipes/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Playroom/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Playtable/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/PlaytableP/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Recycle/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Teddy/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingH/Vintage/disp0GT.pfm  \n",
            " extracting: MiddEval3/trainingH/Adirondack/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/ArtL/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Jadeplant/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Motorcycle/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/MotorcycleE/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Piano/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/PianoL/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Pipes/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Playroom/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Playtable/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/PlaytableP/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Recycle/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Teddy/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingH/Vintage/mask0nocc.png  \n",
            "  inflating: MiddEval3/trainingH/Shelves/disp0GT.pfm  \n",
            " extracting: MiddEval3/trainingH/Shelves/mask0nocc.png  \n",
            "--2023-11-07 20:25:53--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-data-F.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
            "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 357538460 (341M) [application/zip]\n",
            "Saving to: ‘MiddEval3-data-F.zip’\n",
            "\n",
            "MiddEval3-data-F.zi 100%[===================>] 340.97M  52.0MB/s    in 6.9s    \n",
            "\n",
            "2023-11-07 20:26:00 (49.4 MB/s) - ‘MiddEval3-data-F.zip’ saved [357538460/357538460]\n",
            "\n",
            "Archive:  MiddEval3-data-F.zip\n",
            "  inflating: MiddEval3/testF/Australia/calib.txt  \n",
            "  inflating: MiddEval3/testF/AustraliaP/calib.txt  \n",
            "  inflating: MiddEval3/testF/Bicycle2/calib.txt  \n",
            "  inflating: MiddEval3/testF/Classroom2/calib.txt  \n",
            "  inflating: MiddEval3/testF/Classroom2E/calib.txt  \n",
            "  inflating: MiddEval3/testF/Computer/calib.txt  \n",
            "  inflating: MiddEval3/testF/Crusade/calib.txt  \n",
            "  inflating: MiddEval3/testF/CrusadeP/calib.txt  \n",
            "  inflating: MiddEval3/testF/Djembe/calib.txt  \n",
            "  inflating: MiddEval3/testF/DjembeL/calib.txt  \n",
            "  inflating: MiddEval3/testF/Hoops/calib.txt  \n",
            "  inflating: MiddEval3/testF/Livingroom/calib.txt  \n",
            "  inflating: MiddEval3/testF/Newkuba/calib.txt  \n",
            "  inflating: MiddEval3/testF/Plants/calib.txt  \n",
            "  inflating: MiddEval3/testF/Staircase/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Adirondack/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/ArtL/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Jadeplant/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Motorcycle/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/MotorcycleE/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Piano/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/PianoL/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Pipes/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Playroom/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Playtable/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/PlaytableP/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Recycle/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Teddy/calib.txt  \n",
            "  inflating: MiddEval3/trainingF/Vintage/calib.txt  \n",
            " extracting: MiddEval3/testF/Australia/im0.png  \n",
            " extracting: MiddEval3/testF/Australia/im1.png  \n",
            " extracting: MiddEval3/testF/AustraliaP/im0.png  \n",
            " extracting: MiddEval3/testF/AustraliaP/im1.png  \n",
            " extracting: MiddEval3/testF/Bicycle2/im0.png  \n",
            " extracting: MiddEval3/testF/Bicycle2/im1.png  \n",
            " extracting: MiddEval3/testF/Classroom2/im0.png  \n",
            " extracting: MiddEval3/testF/Classroom2/im1.png  \n",
            " extracting: MiddEval3/testF/Classroom2E/im0.png  \n",
            " extracting: MiddEval3/testF/Classroom2E/im1.png  \n",
            " extracting: MiddEval3/testF/Computer/im0.png  \n",
            " extracting: MiddEval3/testF/Computer/im1.png  \n",
            " extracting: MiddEval3/testF/Crusade/im0.png  \n",
            " extracting: MiddEval3/testF/Crusade/im1.png  \n",
            " extracting: MiddEval3/testF/CrusadeP/im0.png  \n",
            " extracting: MiddEval3/testF/CrusadeP/im1.png  \n",
            " extracting: MiddEval3/testF/Djembe/im0.png  \n",
            " extracting: MiddEval3/testF/Djembe/im1.png  \n",
            " extracting: MiddEval3/testF/DjembeL/im0.png  \n",
            " extracting: MiddEval3/testF/DjembeL/im1.png  \n",
            " extracting: MiddEval3/testF/Hoops/im0.png  \n",
            " extracting: MiddEval3/testF/Hoops/im1.png  \n",
            " extracting: MiddEval3/testF/Livingroom/im0.png  \n",
            " extracting: MiddEval3/testF/Livingroom/im1.png  \n",
            " extracting: MiddEval3/testF/Newkuba/im0.png  \n",
            " extracting: MiddEval3/testF/Newkuba/im1.png  \n",
            " extracting: MiddEval3/testF/Plants/im0.png  \n",
            " extracting: MiddEval3/testF/Plants/im1.png  \n",
            " extracting: MiddEval3/testF/Staircase/im0.png  \n",
            " extracting: MiddEval3/testF/Staircase/im1.png  \n",
            " extracting: MiddEval3/trainingF/Adirondack/im0.png  \n",
            " extracting: MiddEval3/trainingF/Adirondack/im1.png  \n",
            " extracting: MiddEval3/trainingF/ArtL/im0.png  \n",
            " extracting: MiddEval3/trainingF/ArtL/im1.png  \n",
            " extracting: MiddEval3/trainingF/Jadeplant/im0.png  \n",
            " extracting: MiddEval3/trainingF/Jadeplant/im1.png  \n",
            " extracting: MiddEval3/trainingF/Motorcycle/im0.png  \n",
            " extracting: MiddEval3/trainingF/Motorcycle/im1.png  \n",
            " extracting: MiddEval3/trainingF/MotorcycleE/im0.png  \n",
            " extracting: MiddEval3/trainingF/MotorcycleE/im1.png  \n",
            " extracting: MiddEval3/trainingF/Piano/im0.png  \n",
            " extracting: MiddEval3/trainingF/Piano/im1.png  \n",
            " extracting: MiddEval3/trainingF/PianoL/im0.png  \n",
            " extracting: MiddEval3/trainingF/PianoL/im1.png  \n",
            " extracting: MiddEval3/trainingF/Pipes/im0.png  \n",
            " extracting: MiddEval3/trainingF/Pipes/im1.png  \n",
            " extracting: MiddEval3/trainingF/Playroom/im0.png  \n",
            " extracting: MiddEval3/trainingF/Playroom/im1.png  \n",
            " extracting: MiddEval3/trainingF/Playtable/im0.png  \n",
            " extracting: MiddEval3/trainingF/Playtable/im1.png  \n",
            " extracting: MiddEval3/trainingF/PlaytableP/im0.png  \n",
            " extracting: MiddEval3/trainingF/PlaytableP/im1.png  \n",
            " extracting: MiddEval3/trainingF/Recycle/im0.png  \n",
            " extracting: MiddEval3/trainingF/Recycle/im1.png  \n",
            " extracting: MiddEval3/trainingF/Teddy/im0.png  \n",
            " extracting: MiddEval3/trainingF/Teddy/im1.png  \n",
            " extracting: MiddEval3/trainingF/Vintage/im0.png  \n",
            " extracting: MiddEval3/trainingF/Vintage/im1.png  \n",
            "  inflating: MiddEval3/trainingF/Shelves/calib.txt  \n",
            " extracting: MiddEval3/trainingF/Shelves/im0.png  \n",
            " extracting: MiddEval3/trainingF/Shelves/im1.png  \n",
            "--2023-11-07 20:26:05--  https://vision.middlebury.edu/stereo/submit3/zip/MiddEval3-GT0-F.zip\n",
            "Resolving vision.middlebury.edu (vision.middlebury.edu)... 140.233.20.14\n",
            "Connecting to vision.middlebury.edu (vision.middlebury.edu)|140.233.20.14|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 202989710 (194M) [application/zip]\n",
            "Saving to: ‘MiddEval3-GT0-F.zip’\n",
            "\n",
            "MiddEval3-GT0-F.zip 100%[===================>] 193.59M  50.7MB/s    in 4.2s    \n",
            "\n",
            "2023-11-07 20:26:09 (46.5 MB/s) - ‘MiddEval3-GT0-F.zip’ saved [202989710/202989710]\n",
            "\n",
            "Archive:  MiddEval3-GT0-F.zip\n",
            "  inflating: MiddEval3/trainingF/Adirondack/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/ArtL/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Jadeplant/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Motorcycle/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/MotorcycleE/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Piano/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/PianoL/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Pipes/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Playroom/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Playtable/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/PlaytableP/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Recycle/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Teddy/disp0GT.pfm  \n",
            "  inflating: MiddEval3/trainingF/Vintage/disp0GT.pfm  \n",
            " extracting: MiddEval3/trainingF/Adirondack/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/ArtL/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Jadeplant/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Motorcycle/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/MotorcycleE/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Piano/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/PianoL/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Pipes/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Playroom/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Playtable/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/PlaytableP/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Recycle/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Teddy/mask0nocc.png  \n",
            " extracting: MiddEval3/trainingF/Vintage/mask0nocc.png  \n",
            "  inflating: MiddEval3/trainingF/Shelves/disp0GT.pfm  \n",
            " extracting: MiddEval3/trainingF/Shelves/mask0nocc.png  \n",
            "--2023-11-07 20:26:13--  https://www.eth3d.net/data/two_view_test.7z\n",
            "Resolving www.eth3d.net (www.eth3d.net)... 129.132.89.155\n",
            "Connecting to www.eth3d.net (www.eth3d.net)|129.132.89.155|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 12419669 (12M) [application/x-7z-compressed]\n",
            "Saving to: ‘two_view_test.7z’\n",
            "\n",
            "two_view_test.7z    100%[===================>]  11.84M  10.8MB/s    in 1.1s    \n",
            "\n",
            "2023-11-07 20:26:15 (10.8 MB/s) - ‘two_view_test.7z’ saved [12419669/12419669]\n",
            "\n",
            "Unzipping two_view_test.7z using p7zip (installed from environment.yaml)\n",
            "\n",
            "7-Zip (a) [64] 16.02 : Copyright (c) 1999-2016 Igor Pavlov : 2016-05-21\n",
            "p7zip Version 16.02 (locale=en_US.UTF-8,Utf16=on,HugeFiles=on,64 bits,2 CPUs Intel(R) Xeon(R) CPU @ 2.30GHz (306F0),ASM,AES-NI)\n",
            "\n",
            "Scanning the drive for archives:\n",
            "  0M Scan\b\b\b\b\b\b\b\b\b         \b\b\b\b\b\b\b\b\b1 file, 12419669 bytes (12 MiB)\n",
            "\n",
            "Extracting archive: two_view_test.7z\n",
            "--\n",
            "Path = two_view_test.7z\n",
            "Type = 7z\n",
            "Physical Size = 12419669\n",
            "Headers Size = 1219\n",
            "Method = LZMA:24 BCJ\n",
            "Solid = +\n",
            "Blocks = 2\n",
            "\n",
            "  0%\b\b\b\b    \b\b\b\b 20% 69 - storage_room_3s/im0.png\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                 \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 45% 79 - tunnel_3s/im0.png\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                           \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 70% 88 - storage_room_2s/im1.png\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                                 \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b 95% 99 - tunnel_3s/im1.png\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b                           \b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\bEverything is Ok\n",
            "\n",
            "Files: 100\n",
            "Size:       12701228\n",
            "Compressed: 12419669\n",
            "--2023-11-07 20:26:16--  https://www.dropbox.com/s/ftveifyqcomiwaq/models.zip\n",
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            "--2023-11-07 20:26:16--  https://www.dropbox.com/s/raw/ftveifyqcomiwaq/models.zip\n",
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            "Length: 201797467 (192M) [application/zip]\n",
            "Saving to: ‘models.zip’\n",
            "\n",
            "models.zip          100%[===================>] 192.45M   104MB/s    in 1.9s    \n",
            "\n",
            "2023-11-07 20:26:19 (104 MB/s) - ‘models.zip’ saved [201797467/201797467]\n",
            "\n",
            "Archive:  models.zip\n",
            "  inflating: iraftstereo_rvc.pth     \n",
            "  inflating: raftstereo-eth3d.pth    \n",
            "  inflating: raftstereo-middlebury.pth  \n",
            "  inflating: raftstereo-realtime.pth  \n",
            "  inflating: raftstereo-sceneflow.pth  \n"
          ]
        }
      ],
      "source": [
        "%cd /content/RAFT-Stereo\n",
        "!pip install imageio # for visualization\n",
        "\n",
        "# Download model weights and sample data\n",
        "!bash download_datasets.sh\n",
        "!bash download_models.sh"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nuf9KPC1q3EI"
      },
      "source": [
        "## 3) Run RAFT-Stereo\n",
        "\n",
        "### You can replace the images and calibration with your own"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VvT9dcR1bxDt",
        "outputId": "77ec6525-7e11-4b8c-af23-86b2980562d8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 1 images. Saving files to demo_output/\n",
            "100% 1/1 [00:05<00:00,  5.90s/it]\n"
          ]
        }
      ],
      "source": [
        "!source activate raftstereo && python demo.py --restore_ckpt models/raftstereo-middlebury.pth \\\n",
        "--corr_implementation alt --mixed_precision \\\n",
        "-l=datasets/suturing/left_image_62.png \\\n",
        "-r=datasets/suturing/right_image_0.png \\\n",
        "--save_numpy\n",
        "\n",
        "# Calibration\n",
        "# fx, fy, cx1, cy = 3997.684, 3997.684, 1176.728, 1011.728\n",
        "# cx2 = 1307.839\n",
        "# baseline=193.001 # in millimeters\n",
        "f = 1688.10117\n",
        "cx = 657.660185\n",
        "cy = 411.400296\n",
        "# Tx = -0.045530\n",
        "# cx_diff = 671.318549 - cx\n",
        "# depth_image = (f * Tx) / abs(disparity_map + cx_diff)\n",
        "fx, fy, cx, cy = f, f, cx, cy"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}