{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe0521db",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import json\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from IPython.display import display, Image as IPImage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6d7ebbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_dir = Path(\"../data/annotation_results/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75efc15a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_result(folder):\n",
    "    folder = Path(folder)\n",
    "\n",
    "    with open(folder / \"metadata.json\") as f:\n",
    "        metadata = json.load(f)\n",
    "\n",
    "    frame = np.array(Image.open(folder / \"frame.png\"))\n",
    "    mask = np.array(Image.open(folder / \"mask_vis.png\"))\n",
    "    overlay = np.array(Image.open(folder / \"overlay.png\"))\n",
    "\n",
    "    title = \" | \".join(f\"{k}: {v}\" for k, v in metadata.items())\n",
    "    fig, axs = plt.subplots(1, 3, figsize=(15, 5))\n",
    "    axs[0].imshow(frame)\n",
    "    axs[0].set_title(\"Frame\")\n",
    "    axs[0].axis(\"off\")\n",
    "    axs[1].imshow(mask, cmap=\"gray\")\n",
    "    axs[1].set_title(\"Mask\")\n",
    "    axs[1].axis(\"off\")\n",
    "    axs[2].imshow(overlay)\n",
    "    axs[2].set_title(\"Overlay\")\n",
    "    axs[2].axis(\"off\")\n",
    "    plt.suptitle(f\"{folder.name}\\n{title}\", fontsize=9)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "    for gif_name in [\"video_original_lowres.gif\", \"video_overlay_lowres.gif\"]:\n",
    "        gif_path = folder / gif_name\n",
    "        if gif_path.exists():\n",
    "            display(IPImage(filename=str(gif_path)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02ff1ae9",
   "metadata": {},
   "outputs": [],
   "source": [
    "for folder in sorted(out_dir.iterdir()):\n",
    "    if folder.is_dir() and (folder / \"metadata.json\").exists():\n",
    "        show_result(folder)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "river-annotation-tool",
   "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": "3.12.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}