TrackFormer_demo.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NLSO7QwCUytT"
      },
      "source": [
        "論文  \n",
        "https://arxiv.org/abs/2101.02702v2  \n",
        "  \n",
        "GitHub  \n",
        "https://github.com/timmeinhardt/trackformer  \n",
        "  \n",
        "<a href=\"https://colab.research.google.com/github/kaz12tech/ai_demos/blob/master/TrackFormer_demo.ipynb\" target=\"_blank\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gG3eD_UDUytZ"
      },
      "source": [
        "# ランタイムの設定\n",
        "「ランタイム」→「ランタイムのタイプを変更」→「ハードウェアアクセラレータ」をGPUに変更"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yQFJz7b0Uyta"
      },
      "source": [
        "# 実行方法\n",
        "「ランタイム」→「すべてのセルを実行」を選択"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gd1t4-oNUytb"
      },
      "source": [
        "# GPU確認"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ODkoi-eAUytb",
        "outputId": "886495bc-f1ea-4ead-d7ed-f7be21de2c47"
      },
      "outputs": [],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "75fbCZBXdmf1"
      },
      "source": [
        "# 環境セットアップ"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uwvu_hfgVCAS"
      },
      "source": [
        "## GitHubからTrackFormerのソースコードを取得"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1jMHAoNoU5e9",
        "outputId": "7c2db8b3-e13f-49be-9df8-e0e3632fece8"
      },
      "outputs": [],
      "source": [
        "%cd /content/\n",
        "\n",
        "!git clone https://github.com/timmeinhardt/trackformer.git"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JptNThTkVtrn"
      },
      "source": [
        "## ライブラリのインストール"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "xFyFZu8UVu2N",
        "outputId": "108d5ffb-22b7-434b-92c6-646365184993"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer\n",
        "\n",
        "!pip install -r requirements.txt\n",
        "\n",
        "!pip uninstall torch -y\n",
        "!pip install torch==1.5.1+cu101 torchvision==0.6.1+cu101 -f https://download.pytorch.org/whl/torch_stable.html\n",
        "\n",
        "!pip install -U 'git+https://github.com/timmeinhardt/cocoapi.git#subdirectory=PythonAPI'\n",
        "!python src/trackformer/models/ops/setup.py build --build-base=src/trackformer/models/ops/ install"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9L-3HXGpdefO"
      },
      "source": [
        "## バージョン変更したPytorchの動作確認"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2On3LVDSdZK7",
        "outputId": "171fe532-1a89-421b-96ae-d99a77a3e883"
      },
      "outputs": [],
      "source": [
        "!python -c \"import torch; print(torch.__version__); print(torch.cuda.is_available()); print(torch.cuda.device_count());\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hbi6g5-PYOjC"
      },
      "source": [
        "# 事前学習済みモデルのダウンロード"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oLPXxuTFYTdG",
        "outputId": "8f815b4f-1ae5-46ae-9fc4-774229e7e2c7"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer/models\n",
        "\n",
        "!wget https://vision.in.tum.de/webshare/u/meinhard/trackformer_models.zip\n",
        "!unzip trackformer_models.zip"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rHQUaodokT_V"
      },
      "source": [
        "# Multi-object tracking"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cNgjAtuRqBEw",
        "outputId": "3a4c1b08-8a5d-46cc-c4d2-7a26ff41d34d"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer\n",
        "\n",
        "!ffmpeg -i data/snakeboard/snakeboard.mp4 -vf fps=30 data/snakeboard/%06d.png"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aRFyXJEmahkb",
        "outputId": "b3b19753-4379-47e4-f9b0-c7acd65b252f"
      },
      "outputs": [],
      "source": [
        "%%time\n",
        "\n",
        "!python src/track.py with \\\n",
        "  dataset_name=DEMO \\\n",
        "  data_root_dir=data/snakeboard \\\n",
        "  output_dir=data/snakeboard \\\n",
        "  write_images=pretty"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O0TskNYDmIYC"
      },
      "source": [
        "## トラッキング結果を動画に変換\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wy1qzHw6mz1u",
        "outputId": "536de1c6-4feb-4f78-d66a-286f005b191f"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer\n",
        "\n",
        "results_video = \"data/snakeboard/DEMO/snakeboard_result.mp4\"\n",
        "\n",
        "!ffmpeg -i data/snakeboard/DEMO/snakeboard/%06d.png -c:v libx264 -vf \"fps=25,format=yuv420p\" {results_video}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "5Wlztf0WoZiW",
        "outputId": "deae30a0-47a8-4364-9ddd-af12588cb1ef"
      },
      "outputs": [],
      "source": [
        "from IPython.display import HTML\n",
        "from base64 import b64encode\n",
        "\n",
        "mp4 = open(results_video, \"rb\").read()\n",
        "data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "HTML(f\"\"\"\n",
        "<video width=\"60%\" height=\"60%\" controls>\n",
        "      <source src=\"{data_url}\" type=\"video/mp4\">\n",
        "</video>\"\"\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ix9iwZ-qs8wv"
      },
      "source": [
        "# アップロードした動画のMulti-object tracking\n",
        "使用動画  \n",
        "https://www.pexels.com/ja-jp/video/3873059/  \n",
        "https://www.pexels.com/ja-jp/video/853889/  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 133,
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
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",
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "ok": true,
              "status": 200,
              "status_text": ""
            }
          }
        },
        "id": "6RZLFZE3tM-C",
        "outputId": "a89cb4fe-51cc-4c67-eb63-faba13fa2442"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer/data\n",
        "!rm -rf upload\n",
        "!mkdir -p upload\n",
        "%cd upload\n",
        "\n",
        "from google.colab import files\n",
        "\n",
        "uploaded = files.upload()\n",
        "uploaded = list(uploaded.keys())\n",
        "file_name = uploaded[0]\n",
        "\n",
        "print(file_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ewi2Kf3gvrl7"
      },
      "outputs": [],
      "source": [
        "# 半角スペース除去\n",
        "rename = file_name.replace(\" \", \"\")\n",
        "\n",
        "import os\n",
        "os.rename(file_name, rename)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8u3dfBvaxNsI"
      },
      "source": [
        "## 動画をフレーム画像に分割"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rhfHeSEPuj-J",
        "outputId": "4c1edbb4-7848-4fa5-bc32-109e6f8abf8a"
      },
      "outputs": [],
      "source": [
        "!ffmpeg -i {rename} ./%06d.png"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vpF_TowOzxvR"
      },
      "source": [
        "## Multi-object tracking実施"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9AHJ7Q3dxZUr",
        "outputId": "59172121-4189-4c95-c846-fe8aca9b20d4"
      },
      "outputs": [],
      "source": [
        "%%time\n",
        "\n",
        "%cd /content/trackformer\n",
        "\n",
        "!python src/track.py with \\\n",
        "  dataset_name=DEMO \\\n",
        "  data_root_dir=data/upload \\\n",
        "  output_dir=data/upload \\\n",
        "  write_images=pretty"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G-n2X14-z3pb"
      },
      "source": [
        "## トラッキング結果を動画に変換"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "icX5j8mlyu9i",
        "outputId": "f7ede148-fed9-4bb5-ce6a-c105e9d24cfb"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer\n",
        "\n",
        "results_video = \"data/upload/DEMO/upload_result.mp4\"\n",
        "\n",
        "!ffmpeg -i data/upload/DEMO/upload/%06d.png -c:v libx264 -vf \"fps=25,format=yuv420p\" {results_video}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "xaCZxCoTzt79",
        "outputId": "4b697e62-8421-4e35-c975-933f2e5a6cd9"
      },
      "outputs": [],
      "source": [
        "mp4 = open(results_video, \"rb\").read()\n",
        "data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "HTML(f\"\"\"\n",
        "<video width=\"60%\" height=\"60%\" controls>\n",
        "      <source src=\"{data_url}\" type=\"video/mp4\">\n",
        "</video>\"\"\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DECkkjcEFozQ"
      },
      "source": [
        "# Multi-object tracking(Segmentation)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 133,
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "ok": true,
              "status": 200,
              "status_text": ""
            }
          }
        },
        "id": "gQwwmGwRGDE4",
        "outputId": "ecb34830-c4fa-4412-8844-cac58f8d3654"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer/data\n",
        "!rm -rf upload_seg\n",
        "!mkdir -p upload_seg\n",
        "%cd upload_seg\n",
        "\n",
        "from google.colab import files\n",
        "\n",
        "uploaded_seg = files.upload()\n",
        "uploaded_seg = list(uploaded_seg.keys())\n",
        "file_name = uploaded_seg[0]\n",
        "\n",
        "print(file_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BJnR3k4lGQNm"
      },
      "outputs": [],
      "source": [
        "# 半角スペース除去\n",
        "rename = file_name.replace(\" \", \"\")\n",
        "\n",
        "import os\n",
        "os.rename(file_name, rename)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1M5llT2hGUSS",
        "outputId": "40f0f885-0b90-4aec-d227-34c43659aa16"
      },
      "outputs": [],
      "source": [
        "!ffmpeg -i {rename} ./%06d.png"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wD2L0l9CFyo0",
        "outputId": "547b23d1-21da-49c3-cceb-b1a7990d009c"
      },
      "outputs": [],
      "source": [
        "%%time\n",
        "\n",
        "%cd /content/trackformer\n",
        "\n",
        "!python src/track.py with \\\n",
        "  dataset_name=DEMO \\\n",
        "  obj_detect_checkpoint_file=models/mots20_train_masks/checkpoint.pth \\\n",
        "  data_root_dir=data/upload_seg \\\n",
        "  output_dir=data/upload_seg \\\n",
        "  write_images=pretty"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mUtQGcQGKMTA",
        "outputId": "a45e5ae3-9ca3-4781-a398-26134d6e2709"
      },
      "outputs": [],
      "source": [
        "%cd /content/trackformer\n",
        "\n",
        "results_video = \"data/upload_seg/DEMO/upload_seg_result.mp4\"\n",
        "\n",
        "!ffmpeg -i data/upload_seg/DEMO/upload_seg/%06d.png -c:v libx264 -vf \"fps=25,format=yuv420p\" {results_video}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "ICPV1zDpKgpr",
        "outputId": "614d3883-dcbf-4350-ddfc-39096b44d64e"
      },
      "outputs": [],
      "source": [
        "mp4 = open(results_video, \"rb\").read()\n",
        "data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
        "HTML(f\"\"\"\n",
        "<video width=\"60%\" height=\"60%\" controls>\n",
        "      <source src=\"{data_url}\" type=\"video/mp4\">\n",
        "</video>\"\"\")"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [],
      "name": "TrackFormer_demo.ipynb",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "orig_nbformat": 4
  },
  "nbformat": 4,
  "nbformat_minor": 0
}