{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ['CUDA_VISIBLE_DEVICES']='3' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import fastai\n",
    "import ffmpeg\n",
    "from fastai import *\n",
    "from fastai.vision import *\n",
    "from fastai.callbacks.tensorboard import *\n",
    "from fastai.vision.gan import *\n",
    "from fasterai.dataset import *\n",
    "from fasterai.visualize 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 IPython.display import HTML, display\n",
    "plt.style.use('dark_background')\n",
    "torch.backends.cudnn.benchmark=True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Adjust render_factor (int) 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\n",
    "root_folder =  Path('data/imagenet/ILSVRC/Data/CLS-LOC/bandw')\n",
    "#weights_name = 'ColorizeNew50_gen192_10'\n",
    "weights_name = 'ColorizeNew68_gen192_01_5'\n",
    "nf_factor = 1.25\n",
    "\n",
    "workfolder = Path('./video')\n",
    "source_folder = workfolder/\"source\"\n",
    "bwframes_root = workfolder/\"bwframes\"\n",
    "colorframes_root = workfolder/\"colorframes\"\n",
    "result_folder = workfolder/\"result\"\n",
    "#Make source_url None to just read from source_path directly without modification\n",
    "source_url = 'https://twitter.com/silentmoviegifs/status/1092793719173115905'\n",
    "#source_url=None\n",
    "source_name = 'video8.mp4'\n",
    "source_path =  source_folder/source_name\n",
    "bwframes_folder = bwframes_root/(source_path.stem)\n",
    "colorframes_folder = colorframes_root/(source_path.stem)\n",
    "result_path = result_folder/source_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "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": [
    "def get_fps():\n",
    "    probe = ffmpeg.probe(str(source_path))\n",
    "    stream_data = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None)\n",
    "    avg_frame_rate = stream_data['avg_frame_rate']\n",
    "    print(avg_frame_rate)\n",
    "    fps_num=avg_frame_rate.split(\"/\")[0]\n",
    "    fps_den = avg_frame_rate.rsplit(\"/\")[1]\n",
    "    return round(float(fps_num)/float(fps_den))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def purge_images(dir):\n",
    "    for f in os.listdir(dir):\n",
    "        if re.search('.*?\\.jpg', f):\n",
    "            os.remove(os.path.join(dir, f))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download Video (optional via setting source_url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Specify media_url.  Many sources will work (YouTube, Imgur, Twitter, Reddit, etc). Complete list here:  https://rg3.github.io/youtube-dl/supportedsites.html .  The resulting file path can be used later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if source_url is not None:\n",
    "    if source_path.exists(): source_path.unlink()\n",
    "    youtubdl_command = 'youtube-dl \"' + source_url + '\" -o \"' + str(source_path) + '\"'\n",
    "    print(youtubdl_command)\n",
    "    print('\\n')\n",
    "    output = Path(os.popen(youtubdl_command).read())\n",
    "    print(str(output))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract Raw Frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bwframe_path_template = str(bwframes_folder/'%5d.jpg')\n",
    "bwframes_folder.mkdir(parents=True, exist_ok=True)\n",
    "purge_images(bwframes_folder)\n",
    "ffmpeg.input(str(source_path)).output(str(bwframe_path_template), format='image2', vcodec='mjpeg', qscale=0).run(capture_stdout=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "framecount = len(os.listdir(str(bwframes_folder)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DeOldify / Colorize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vis = get_colorize_visualizer(root_folder=root_folder, weights_name=weights_name, nf_factor=nf_factor, render_factor=render_factor)\n",
    "#vis = get_colorize_visualizer(render_factor=render_factor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "prog = 0\n",
    "out = display(progress(0, 100), display_id=True)\n",
    "colorframes_folder.mkdir(parents=True, exist_ok=True)\n",
    "purge_images(colorframes_folder)\n",
    "\n",
    "for img in os.listdir(str(bwframes_folder)):\n",
    "    img_path = bwframes_folder/img\n",
    "    if os.path.isfile(str(img_path)):\n",
    "        color_image = vis.get_transformed_image(str(img_path), render_factor)\n",
    "        color_image.save(str(colorframes_folder/img))\n",
    "    prog += 1\n",
    "    out.update(progress(prog, framecount))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build Video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "colorframes_path_template = str(colorframes_folder/'%5d.jpg')\n",
    "result_path.parent.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "if result_path.exists(): result_path.unlink()\n",
    "\n",
    "fps = get_fps()\n",
    "print(fps)\n",
    "ffmpeg.input(str(colorframes_path_template), format='image2', vcodec='mjpeg', framerate=str(fps)).output(str(result_path), crf=17, vcodec='libx264').run(capture_stdout=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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