PyTTI_Tools_FiLM-colab.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cp9wuo2MbKLa"
      },
      "source": [
        "# FiLM: Frame Interpolation for Large Motion\n",
        "\n",
        "This notebook is a convenience wrapper around a pre-trained model released by ML researchers at Google. Learn more about their work here: \n",
        "\n",
        "* https://github.com/google-research/frame-interpolation\n",
        "\n",
        "---\n",
        "\n",
        "Notebook authored by David Marx ([@DigThatData](https://twitter.com/DigThatData)), released under the MIT license.\n",
        "\n",
        "If you experience any issue with or have suggestions regarding this notebook, please report them here:\n",
        "* https://github.com/pytti-tools/pytti-notebook/issues/new \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "-7TD7YZJbsy_"
      },
      "outputs": [],
      "source": [
        "# This top bit only neneds to be run once\n",
        "# ...may as well set up the notebook to \n",
        "# assume the user is only going to run all\n",
        "# of setup once.\n",
        "from pathlib import Path\n",
        "import os\n",
        "\n",
        "drive_mounted = False\n",
        "gdrive_fpath = '.'\n",
        "local_path = '/content/'\n",
        "\n",
        "##############################\n",
        "\n",
        "#@markdown # 1. Setup Workspace\n",
        "\n",
        "#@markdown Run this cell to perform setup.\n",
        "\n",
        "#@markdown Mounting your google drive is optional.\n",
        "#@markdown If you mount your drive, code and models will be downloaded to it.\n",
        "#@markdown This should reduce setup time after your first run.\n",
        "\n",
        "###################\n",
        "\n",
        "# Optionally Mount GDrive\n",
        "\n",
        "mount_gdrive = True # @param{type:\"boolean\"}\n",
        "if mount_gdrive and not drive_mounted:\n",
        "    from google.colab import drive\n",
        "\n",
        "    gdrive_mountpoint = '/content/drive/' #@param{type:\"string\"}\n",
        "    gdrive_subdirectory = 'MyDrive/interpolation' #@param{type:\"string\"}\n",
        "    gdrive_fpath = str(Path(gdrive_mountpoint) / gdrive_subdirectory)\n",
        "    try:\n",
        "        drive.mount(gdrive_mountpoint, force_remount = True)\n",
        "        !mkdir -p {gdrive_fpath}\n",
        "        %cd {gdrive_fpath}\n",
        "        local_path = gdrive_fpath\n",
        "        drive_mounted = True\n",
        "    except OSError:\n",
        "        print(\n",
        "            \"\\n\\n-----[PYTTI-TOOLS]-------\\n\\n\"\n",
        "            \"If you received a scary OSError and your drive\"\n",
        "            \" was already mounted, ignore it.\"\n",
        "            \"\\n\\n-----[PYTTI-TOOLS]-------\\n\\n\"\n",
        "            )\n",
        "        raise\n",
        "\n",
        "#####################\n",
        "\n",
        "# Perform rest of setup\n",
        "\n",
        "if not Path('./frame-interpolation').exists():\n",
        "    !git clone https://github.com/pytti-tools/frame-interpolation\n",
        "\n",
        "try:\n",
        "    import frame_interpolation\n",
        "except ModuleNotFoundError:\n",
        "    %pip install -r ./frame-interpolation/requirements_colab.txt\n",
        "    %pip install ./frame-interpolation\n",
        "\n",
        "#url = \"https://drive.google.com/drive/folders/1GhVNBPq20X7eaMsesydQ774CgGcDGkc6?usp=sharing\"\n",
        "share_id = \"1GhVNBPq20X7eaMsesydQ774CgGcDGkc6\"\n",
        "\n",
        "if not (Path(local_path) / 'saved_model').exists():\n",
        "    !pip install --upgrade gdown\n",
        "    !gdown --folder {share_id}\n",
        "\n",
        "# create default frame\n",
        "!mkdir -p frames"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "cellView": "form",
        "id": "toGdeAXf6NdM"
      },
      "outputs": [],
      "source": [
        "#@markdown # 2. Setup Interpolation\n",
        "\n",
        "#@markdown Specify the directory containing your video frames with the `frames_dir` parameter.\n",
        "\n",
        "frames_dir = \"frames\" #@param{'type':'string'}\n",
        "\n",
        "#@markdown A single pass of the interpolation procedure adds a frame between each contiguous pair of frames in `frames_dir`.\n",
        "\n",
        "#@markdown If you start with $n$ frames in `frames_dir` and set `recursive_interpolation_passes` to $k$, your total number of frames\n",
        "#@markdown after interpolation will be: \n",
        "#@markdown $$2^k (n-1) -1$$\n",
        "\n",
        "recursive_interpolation_passes = 1 #@param{'type':'integer'}\n",
        "\n",
        "#@markdown Check this box to generate a video output. If no output video will be generated, the FPS option can be ignored.\n",
        "output_video = True #@param{'type':'boolean'}\n",
        "output_video_fps = 30 #@param{'type':'number'}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "HBMnARHIuGiq"
      },
      "outputs": [],
      "source": [
        "#@markdown # 3. Interpolate!\n",
        "#@markdown Results will be saved in a subdirectory of `frames_dir` named \"interpolated_frames\"\n",
        "\n",
        "from loguru import logger\n",
        "\n",
        "logger.info(\"Beginning interpolation...\")\n",
        "\n",
        "if output_video:\n",
        "  !python -m frame_interpolation.eval.interpolator_cli \\\n",
        "      --model_path ./saved_model \\\n",
        "      --pattern {frames_dir} \\\n",
        "      --fps {output_video_fps} \\\n",
        "      --output_video\n",
        "      \n",
        "\n",
        "else:\n",
        "    !python -m frame_interpolation.eval.interpolator_cli \\\n",
        "      --model_path ./saved_model \\\n",
        "      --pattern {frames_dir} \\\n",
        "\n",
        "logger.info(\"Interpolation comlpete.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XVYQeaF9askL"
      },
      "source": [
        "```\n",
        "MIT License\n",
        "\n",
        "Copyright (c) 2022 David Marx\n",
        "\n",
        "Permission is hereby granted, free of charge, to any person obtaining a copy\n",
        "of this software and associated documentation files (the \"Software\"), to deal\n",
        "in the Software without restriction, including without limitation the rights\n",
        "to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n",
        "copies of the Software, and to permit persons to whom the Software is\n",
        "furnished to do so, subject to the following conditions:\n",
        "\n",
        "The above copyright notice and this permission notice shall be included in all\n",
        "copies or substantial portions of the Software.\n",
        "\n",
        "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n",
        "IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n",
        "FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n",
        "AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n",
        "LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n",
        "OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n",
        "SOFTWARE.\n",
        "```"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [],
      "name": "PyTTI-Tools: FiLM.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}