{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gradio as gr\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "from transformers import MaskFormerForInstanceSegmentation, MaskFormerImageProcessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_id = f\"facebook/maskformer-swin-large-coco\"\n",
    "\n",
    "feature_extractor = MaskFormerImageProcessor.from_pretrained(model_id)\n",
    "model = MaskFormerForInstanceSegmentation.from_pretrained(model_id)\n",
    "\n",
    "with Image.open(\"../color-filter-calculator/assets/Artshack_screen.jpg\") as img:\n",
    "    img_size = (img.height, img.width)\n",
    "    inputs = feature_extractor(images=img, return_tensors=\"pt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs = model(**inputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = feature_extractor.post_process_semantic_segmentation(outputs=outputs, target_sizes=[img_size])[0]\n",
    "results = results.numpy()\n",
    "\n",
    "labels = np.unique(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for label_id in labels:\n",
    "    print(model.config.id2label[label_id])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.8.15 ('hf-gradio')",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "4888b226c77b860705e4be316b14a092026f41c3585ee0ddb38f3008c0cb495e"
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