Scale up wallpaper image to 4K resolution by google colab and waifu2x-chainer.

upscale4K-waifu2x-chainer-colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "upscale4k.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "lUWpoANv8CBR"
      },
      "source": [
        "# @brief: waifu2x-scaleup4k\n",
        "# @By: github/InfiniteSynthesis\n",
        "# This notebook required GPU runtime, so please activate GPU.\n",
        "\n",
        "import os\n",
        "from google.colab import files\n",
        "from google.colab import drive\n",
        "from PIL import Image\n",
        "!git clone https://github.com/tsurumeso/waifu2x-chainer\n",
        "\n",
        "try:\n",
        "  drive.mount('/content/drive/')\n",
        "except:\n",
        "  exit()\n",
        "\n",
        "%cd /content/waifu2x-chainer\n",
        "\n",
        "SUPPORTED_FORMAT = ['.jpg', '.png', '.jpeg', '.tif', '.tiff' , '.bmp', '.tga']\n",
        "SUITABLE_COUNT = 0\n",
        "PROCESSED_COUNT = 0\n",
        "FAILED_SET = []\n",
        "MARK_COUNT = 0\n",
        "\n",
        "def call_waifu2x(file_path, scale):\n",
        "  global FAILED_SET\n",
        "  fname, ext = os.path.splitext(file_path)\n",
        "  target_name = fname + '_' + str(scale) + 'x.png'\n",
        "\n",
        "  try:\n",
        "    result = !python /content/waifu2x-chainer/waifu2x.py -g 0 -s {scale} -i {file_path} --output {target_name}\n",
        "    print(result)\n",
        "  except:\n",
        "    FAILED_SET.append(file_path)\n",
        "  else:\n",
        "    if os.path.exists(target_name):\n",
        "      os.remove(file_path)\n",
        "    else:\n",
        "      FAILED_SET.append(file_path)\n",
        "\n",
        "\n",
        "def process_image(file_path):\n",
        "  global SUITABLE_COUNT, PROCESSED_COUNT, MARK_COUNT\n",
        "  img = Image.open(file_path)\n",
        "  imgWidth, imgHeight = img.size\n",
        "  img.close()\n",
        "  idealLength = 3840   # 4K resolution\n",
        "  PROCESSED_COUNT += 1\n",
        "  scale = (idealLength / imgWidth) if (imgWidth > imgHeight) else (idealLength / imgHeight)\n",
        "  if (scale <= 1):\n",
        "    SUITABLE_COUNT += 1\n",
        "    PROCESSED_COUNT -= 1\n",
        "    MARK_COUNT += 1\n",
        "    if MARK_COUNT == 80:\n",
        "      print(\">\")\n",
        "      MARK_COUNT = 0\n",
        "    else:\n",
        "      print(\">\", end = \"\")\n",
        "  elif (scale <= 1.5):\n",
        "    call_waifu2x(file_path, 1.5)\n",
        "  elif (scale <= 2):\n",
        "    call_waifu2x(file_path, 2)\n",
        "  elif scale <= 3:\n",
        "    call_waifu2x(file_path, 3)\n",
        "  else:\n",
        "    call_waifu2x(file_path, 4)\n",
        "\n",
        "def main():\n",
        "  for folder in ['vertical/', 'horizontal/']:\n",
        "    for root, dirs, files in os.walk(\"/content/drive/MyDrive/\" + folder):\n",
        "      for file in files:\n",
        "        if (os.path.splitext(file)[1] in SUPPORTED_FORMAT):\n",
        "          process_image(root + file)\n",
        "\n",
        "  print(\"\\nsuitable image count = \\033[1;32m\" + str(SUITABLE_COUNT) + \\\n",
        "        \"\\033[0m, processed image count = \\033[1;34m\" + str(PROCESSED_COUNT) + \"\\033[0m.\")\n",
        "  print('failed image set:', FAILED_SET)\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "  main()\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}