adds an ipynb for testing/rough-drafting

app.ipynb

@@ -0,0 +1,98 @@
+{
+ "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 MaskFormerFeatureExtractor, MaskFormerForInstanceSegmentation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# feature_extractor = MaskFormerFeatureExtractor.from_pretrained(\"facebook/maskformer-swin-tiny-coco\")\n",
+    "# model = MaskFormerForInstanceSegmentation.from_pretrained(\"facebook/maskformer-swin-tiny-coco\")\n",
+    "feature_extractor = MaskFormerFeatureExtractor.from_pretrained(\"facebook/maskformer-swin-large-coco\")\n",
+    "model = MaskFormerForInstanceSegmentation.from_pretrained(\"facebook/maskformer-swin-large-coco\")\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\")\n",
+    "    "
+   ]
+  },
+  {
+   "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": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.8.15 ('hf-gradio')",
+   "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": "3.8.15"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "4888b226c77b860705e4be316b14a092026f41c3585ee0ddb38f3008c0cb495e"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}