{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "view-in-github" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "663IVxfrpIAb" }, "source": [ "#◢ [ DeOldify-video\n", "\n", "##This Colab notebook colorizes video in four steps\n", "1. Upload source media or specify media URL - YouTube, Twitter, MySpace, etc.\n", "2. Extract single images from media\n", "3. Process images with [DeOldify](https://github.com/jantic/DeOldify) \n", "4. Rebuild the video from **colorized** images\n", "\n", "I'm on twitter [@tradica](https://twitter.com/tradica)\n", "\n", "\n", "---\n", "\n", "\n", "Thanks [@citnaj](https://twitter.com/citnaj) for creating DeOldify and thanks to Matt Robinson for his [notebook](https://colab.research.google.com/github/jantic/DeOldify/blob/master/DeOldify_colab.ipynb). It helped make DeOldify approachable.\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "ZjPqTBNoohK9" }, "source": [ "\n", "\n", "---\n", "\n", "\n", "#◢ [ Set Runtime type to Python 3/GPU\n", "In the Runtime menu above be sure:\n", "* Runtime Type = Python 3\n", "* Hardware Accelerator = GPU **<-------------- IMPORTANT **\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "00_GcC_trpdE" }, "outputs": [], "source": [ "from os import path\n", "import torch\n", "print(torch.__version__)\n", "print(torch.cuda.is_available())" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "gaEJBGDlptEo" }, "source": [ "#◢ Git clone and install DeOldify" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "-T-svuHytJ-8" }, "outputs": [], "source": [ "!git clone -b FastAIv1 --single-branch https://github.com/jantic/DeOldify.git DeOldify\n", "#!git clone https://github.com/jantic/DeOldify.git DeOldify" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "cd DeOldify" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "BDFjbNxaadNJ" }, "source": [ "#◢ Setup" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "Lsx7xCXNSVt6" }, "outputs": [], "source": [ "!pip install PyDrive\n", "!pip install ffmpeg-python\n", "!pip install youtube-dl\n", "!pip install tensorboardX" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "MsJa69CMwj3l" }, "outputs": [], "source": [ "import os\n", "from pydrive.auth import GoogleAuth\n", "from pydrive.drive import GoogleDrive\n", "from google.colab import auth\n", "from oauth2client.client import GoogleCredentials\n", "from google.colab import drive\n", "import fastai\n", "from fasterai.visualize import *\n", "from pathlib import Path\n", "from itertools import repeat\n", "from google.colab import drive\n", "from google.colab import files\n", "torch.backends.cudnn.benchmark=True" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!mkdir 'models'\n", "!wget https://www.dropbox.com/s/zqt6pzcmoztda0l/ColorizeVideos_gen2.pth?dl=0 -O ./models/ColorizeVideos_gen2.pth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#◢ Render Factor" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Determines resolution at which video is rendered. Higher is generally better (not always however!). Default is carefully chosen and should work for most scenarios" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "render_factor = 36 #@param {type: \"slider\", min: 5, max: 45}" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "z5rSDjZbTntY" }, "source": [ "#◢ Specify URL" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "YouTube, Imgur, Twitter, MySpace, Reddit ... most work. NOTE: If this is ommitted, you can just upload the file later in the workflow" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "source_url = '' #@param {type:\"string\"}" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "z5rSDjZbTntY" }, "source": [ "#◢ Additional Parameters" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's not recommended to change the following (not really necessary)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "file_name = 'video.mp4'\n", "source_dir = './video/source/'\n", "source_path = source_dir + file_name\n", "dest_dir = './video/result/'\n", "dest_path = dest_dir + file_name" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!mkdir file_dir" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "sUQrbSYipiJn" }, "source": [ "#◢ DeOldify / Colorize" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", "id": "tzHVnegp21hC" }, "outputs": [], "source": [ "colorizer = get_video_colorizer2(render_factor=render_factor)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "if source_url is not None and source_url !='':\n", " colorizer.colorize_from_url(source_url, file_name)\n", "else:\n", " #UPLOAD File Here\n", " source_media = files.upload()\n", " os.system('ln -s /content/WORKFOLDER/' + list(source_media.keys())[0] + ' ' + source_path)\n", " colorizer.colorize_from_file_name(file_name)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "A5WMS_GgP4fm" }, "source": [ "#◢ Download" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* In the Menu on the left, click **Files**\n", "* Click refresh button if you don't see the 'DeOldify' folder.\n", "* Rendered video should be in /DeOldify/video/result/" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "X7Ycv_Y9xAHp" }, "source": [ "---\n", "#⚙ Some great video and gif sources \n", "* [/r/Nickelodeons/](https://www.reddit.com/r/Nickelodeons/)\n", "* https://twitter.com/silentmoviegifs " ] } ], "metadata": { "accelerator": "GPU", "colab": { "collapsed_sections": [], "name": "DeOldify-video.ipynb", "provenance": [], "toc_visible": true, "version": "0.3.2" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.0" } }, "nbformat": 4, "nbformat_minor": 2 }