Adding video colab. Updating image colab

DeOldify-video.ipynb

@@ -0,0 +1,650 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "view-in-github"
+   },
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/jantic/DeOldify/blob/master/DeOldify-video.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "663IVxfrpIAb"
+   },
+   "source": [
+    "#◢ <font color='#FF000'>[ </font> DeOldify-video\n",
+    "\n",
+    "##This colbab 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 **<font color='#CC0000'>c</font><font color='#CC8800'>o</font><font color='#FFBB00'>l</font><font color='#00DD00'>o</font><font color='#0000FF'>r</font>ized** 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",
+    "#◢ <font color='#FF000'>[ </font> Set Runtime type to Python 3/GPU\n",
+    "In the Runtime menu above be sure:\n",
+    "* Runtime Type = Python 3\n",
+    "* Hardware Accelerator = GPU **<font color='#FF000'><-------------- IMPORTANT </font>**\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": [
+    "#◢ <font color='#FF000'>[ </font> 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\n",
+    "!cd DeOldify"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "BDFjbNxaadNJ"
+   },
+   "source": [
+    "#◢ <font color='#FF000'>[ </font> 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",
+    "from IPython.display import Image\n",
+    "import fastai\n",
+    "from fastai import *\n",
+    "from fastai.vision import *\n",
+    "from fastai.callbacks import *\n",
+    "from fastai.vision.gan import *\n",
+    "from fasterai.dataset import *\n",
+    "from fasterai.visualize import *\n",
+    "from fasterai.tensorboard import *\n",
+    "from fasterai.loss import *\n",
+    "from fasterai.filters import *\n",
+    "from fasterai.generators 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\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "uqJcwLG80fVe"
+   },
+   "outputs": [],
+   "source": [
+    "!wget https://www.dropbox.com/s/1ReNu8QCgi4vfyDovgYGMs7tlUGrnz72V/colorize_gen.pth -O ./models/colorize_gen.pth"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "ye5zoAYS2q2q"
+   },
+   "outputs": [],
+   "source": [
+    "!mkdir /content/WORKFOLDER\n",
+    "!mkdir /content/WORKFOLDER/monochromatics\n",
+    "!mkdir /content/WORKFOLDER/colorized\n",
+    "!mkdir /content/WORKFOLDER/ANSWER\n",
+    "\n",
+    "import ffmpeg\n",
+    "\n",
+    "# COLAB PROGRESS BAR\n",
+    "from IPython.display import HTML, display\n",
+    "\n",
+    "def progress(value, max=100):\n",
+    "    return HTML(\"\"\"\n",
+    "        <progress\n",
+    "            value='{value}'\n",
+    "            max='{max}',\n",
+    "            style='width: 40%'\n",
+    "        >\n",
+    "            {value}\n",
+    "        </progress>\n",
+    "    \"\"\".format(value=value, max=max))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_dir=Path('/content/WORKFOLDER/colorized')\n",
+    "\n",
+    "#Adjust this if image doesn't look quite right (max 64 on 11GB GPU).  The default here works for most photos.  \n",
+    "#It literally just is a number multiplied by 16 to get the square render resolution.  \n",
+    "#Note that this doesn't affect the resolution of the final output- the output is the same resolution as the input.\n",
+    "#Example:  render_factor=21 => color is rendered at 16x21 = 336x336 px.  \n",
+    "render_factor=21"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "tzHVnegp21hC"
+   },
+   "outputs": [],
+   "source": [
+    "vis = get_colorize_visualizer(results_dir=results_dir, render_factor=render_factor)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "UQWKTCA43DYZ"
+   },
+   "outputs": [],
+   "source": [
+    "%cd \"/content/WORKFOLDER\"\n",
+    "media_file = \"/content/WORKFOLDER/media_file\"\n",
+    "\n",
+    "def ugly_get_fps():\n",
+    "  media_data = ffmpeg.probe(media_file)\n",
+    "  stream_data = media_data['streams']\n",
+    "  stream_data_zero = str(stream_data).rsplit('avg_frame_rate\\': \\'', 1)[1]\n",
+    "  fps_nums=stream_data_zero.rsplit(\"'\")[0]\n",
+    "  fps_list = fps_nums.rsplit(\"/\")\n",
+    "  return int(fps_list[0])/int(fps_list[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "HhjJhmq8ptZJ"
+   },
+   "source": [
+    "---\n",
+    "#◢ <font color='#FF000'>[ </font>1<font color='#FF000'> ] </font> Upload Source Video or Specify Media URL"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "WkY6IysOc02E"
+   },
+   "source": [
+    "###◢  <font color='#FF000'>[ </font> Upload"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "qmGDdYOK3WqT"
+   },
+   "outputs": [],
+   "source": [
+    "#Run this to make an upload widget appear\n",
+    "source_media = files.upload()\n",
+    "\n",
+    "os.system('ln -s /content/WORKFOLDER/' + list(source_media.keys())[0] + ' /content/WORKFOLDER/media_file')\n",
+    "source_media_name = list(source_media.keys())[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "z5rSDjZbTntY"
+   },
+   "source": [
+    "###◢  <font color='#FF000'>[ </font> Specify URL\n",
+    "YouTube, Imgur, Twitter, MySpace, Reddit ... most work"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "TkGgyI9rR4P3"
+   },
+   "outputs": [],
+   "source": [
+    "#@title Paste media URL or leave blank if uploading\n",
+    "media_url = '' #@param {type:\"string\"}\n",
+    "source_media_name = media_url.rsplit('/', 1)[-1]\n",
+    "os.system('youtube-dl ' + media_url + ' -o ' + source_media_name)\n",
+    "os.system('ln -s /content/WORKFOLDER/' + str(source_media_name) + ' /content/WORKFOLDER/media_file')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "PviCbt7fptco"
+   },
+   "source": [
+    "#◢ <font color='#FF000'>[ </font>2<font color='#FF000'> ] </font> Extract Images from Source Media"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "_6e9pwxw7Ufq"
+   },
+   "outputs": [],
+   "source": [
+    "os.system('ffmpeg -i media_file -qscale:v 2 /content/WORKFOLDER/monochromatics/%5d.jpg')\n",
+    "framecount = len(os.listdir('/content/WORKFOLDER/monochromatics'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "sUQrbSYipiJn"
+   },
+   "source": [
+    "#◢ <font color='#FF000'>[ </font>3<font color='#FF000'> ] </font> DeOldify / Colorize"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "6ZGtxdrnBAgO"
+   },
+   "outputs": [],
+   "source": [
+    "render_factor = 5  #@param {type: \"slider\", min: 5, max: 42}\n",
+    "#progress bar\n",
+    "prog = 0\n",
+    "out = display(progress(0, 100), display_id=True)\n",
+    "for img in os.listdir(\"/content/WORKFOLDER/monochromatics\"):\n",
+    "  img_path = str(\"/content/WORKFOLDER/monochromatics/\") + img\n",
+    "  if os.path.isfile(img_path):\n",
+    "    qqq = vis.get_transformed_image(img_path, render_factor)\n",
+    "    qqq.save(\"/content/WORKFOLDER/colorized/\" + img)\n",
+    "  prog += 1\n",
+    "  out.update(progress(prog, framecount))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "nFI8LVP2B-jE"
+   },
+   "source": [
+    "#◢ <font color='#FF000'>[ </font>4<font color='#FF000'> ] </font> Build Video"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "csaF_PHzB9mM"
+   },
+   "outputs": [],
+   "source": [
+    "answer_file = '/content/WORKFOLDER/ANSWER/' + source_media_name + '-RF' + str(render_factor) + 'FR' + str(round(ugly_get_fps(), 2)) + '.mp4'\n",
+    "os.system('ffmpeg -f image2 -framerate ' + str(ugly_get_fps()) + ' -i /content/WORKFOLDER/colorized/%05d.jpg -c:v libx264 -crf 0 ' + answer_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "A5WMS_GgP4fm"
+   },
+   "source": [
+    "###◢  <font color='#FF000'>[ </font> Download\n",
+    "* In the Menu on the left, click **Files**\n",
+    "* It's in /content/WORKFOLDER/ANSWER/\n",
+    "* ( Or use this with its zero feedback :) )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "-PpnqBCUPw-Z"
+   },
+   "outputs": [],
+   "source": [
+    "#Find your video in Files >  /content/WORKFOLDER/ANSWER/  (It's better than this)\n",
+    "files.download(answer_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "s-6-z0oKjU-l"
+   },
+   "source": [
+    "###◢  <font color='#FF000'>[ </font> Build 50/50 Split Screen original / DeOldified video\n",
+    "(need to complete step four)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "s7yfhaR3fTGx"
+   },
+   "outputs": [],
+   "source": [
+    "os.system('ffmpeg -i ' + str(media_file) + ' -i ' + str(answer_file) + ' -filter_complex  \"[0]crop=iw/2:ih:0:0,  pad=iw*2:ih[left];  [1]crop=iw/2:ih:iw/2:0[right]; [left][right]overlay=w\" -strict -2 /content/WORKFOLDER/ANSWER/split-RF' + str(render_factor) + '.mp4')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "VqIrDA2bDMPv"
+   },
+   "source": [
+    "---\n",
+    "#⚙ <font color='#FF000'>[ </font> Delete Workfiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "btv1Az5ODNjl"
+   },
+   "outputs": [],
+   "source": [
+    "# Delete extracted\n",
+    "!rm /content/WORKFOLDER/monochromatics/*jpg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "6XFxW2vfDNm7"
+   },
+   "outputs": [],
+   "source": [
+    "# Delete Colorized\n",
+    "!rm /content/WORKFOLDER/colorized/*jpg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "h5oY6FjXDNq5"
+   },
+   "outputs": [],
+   "source": [
+    "!rm /content/WORKFOLDER/media_file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 34
+    },
+    "colab_type": "code",
+    "executionInfo": {
+     "elapsed": 768,
+     "status": "ok",
+     "timestamp": 1548878396597,
+     "user": {
+      "displayName": "Robert Bell",
+      "photoUrl": "https://lh6.googleusercontent.com/-HcTrynSPUPc/AAAAAAAAAAI/AAAAAAAAbuk/mDAP2a19CmQ/s64/photo.jpg",
+      "userId": "08010292799749788749"
+     },
+     "user_tz": 420
+    },
+    "id": "YW7rAXBlYDNk",
+    "outputId": "94584eea-8288-47a6-9edf-0198d6a2e62a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {
+      "tags": []
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Delete Source Media \n",
+    "os.system('rm /content/WORKFOLDER/' + source_media_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 34
+    },
+    "colab_type": "code",
+    "executionInfo": {
+     "elapsed": 1139,
+     "status": "ok",
+     "timestamp": 1548878397566,
+     "user": {
+      "displayName": "Robert Bell",
+      "photoUrl": "https://lh6.googleusercontent.com/-HcTrynSPUPc/AAAAAAAAAAI/AAAAAAAAbuk/mDAP2a19CmQ/s64/photo.jpg",
+      "userId": "08010292799749788749"
+     },
+     "user_tz": 420
+    },
+    "id": "6bU6Ov9aYes6",
+    "outputId": "e8634a16-a579-4fc1-a305-b6b7b9ebf88f"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {
+      "tags": []
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Delete Answer\n",
+    "os.system('rm ' + answer_file)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "X7Ycv_Y9xAHp"
+   },
+   "source": [
+    "---\n",
+    "#⚙ <font color='#FF000'>[ </font>  \n",
+    "* [/r/Nickelodeons/](https://www.reddit.com/r/Nickelodeons/)\n",
+    "* https://twitter.com/silentmoviegifs "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "3CUeJf2XF-1X"
+   },
+   "source": [
+    "https://twitter.com/silentmoviegifs/status/1087282910288363522\n",
+    "If you click the date at the top of a tweet you can copy the URL from the browser"
+   ]
+  }
+ ],
+ "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
+}

DeOldify_colab.ipynb

@@ -71,7 +71,7 @@
    },
    "outputs": [],
    "source": [
-    "cd DeOldify"
+    "!cd DeOldify"
    ]
   },
   {
@@ -88,16 +88,7 @@
    },
    "outputs": [],
    "source": [
-    "# Doing work so I can access data from my google drive\n",
-    "!pip install PyDrive"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
+    "!pip install PyDrive\n",
     "!pip install tensorboardX"
    ]
   },
@@ -181,7 +172,6 @@
    },
    "outputs": [],
    "source": [
-    "weights_name = 'colorize_gen'\n",
     "results_dir=Path('/content/drive/My Drive/deOldifyImages/results')\n",
     "\n",
     "#Adjust this if image doesn't look quite right (max 64 on 11GB GPU).  The default here works for most photos.  \n",