{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def copy(src, dest):\n",
    "    for sub in os.listdir(src):\n",
    "        for file in os.listdir(os.path.join(src, sub)):\n",
    "            image = Image.open(os.path.join(src, sub, file))\n",
    "\n",
    "            # resize image, min(height, width) = 512\n",
    "            if image.size[0] < image.size[1]:\n",
    "                image = image.resize((512, int(512 * image.size[1] / image.size[0])))\n",
    "            else:\n",
    "                image = image.resize((int(512 * image.size[0] / image.size[1]), 512))\n",
    "\n",
    "            image.save(os.path.join(dest, file))\n",
    "\n",
    "datasets = '/home/qninh/Downloads/rgb_anon'\n",
    "\n",
    "# build cyclegan dataset\n",
    "for type in ['fog', 'rain', 'snow', 'night']:\n",
    "    path = os.path.join(datasets, type)\n",
    "\n",
    "    os.makedirs(f'./datasets/{type}/trainA', exist_ok=True)\n",
    "    os.makedirs(f'./datasets/{type}/trainB', exist_ok=True)\n",
    "    os.makedirs(f'./datasets/{type}/testA', exist_ok=True)\n",
    "    os.makedirs(f'./datasets/{type}/testB', exist_ok=True)\n",
    "\n",
    "    copy(os.path.join(path, \"train_ref\"), f\"./datasets/{type}/trainA\")\n",
    "    copy(os.path.join(path, \"test_ref\"), f\"./datasets/{type}/trainA\")\n",
    "\n",
    "    copy(os.path.join(path, \"train\"), f\"./datasets/{type}/trainB\")\n",
    "    copy(os.path.join(path, \"test\"), f\"./datasets/{type}/testB\")\n",
    "\n",
    "    copy(os.path.join(path, \"val_ref\"), f\"./datasets/{type}/testA\")\n",
    "    copy(os.path.join(path, \"val\"), f\"./datasets/{type}/testB\")"
   ]
  }
 ],
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