Upload playground.ipynb

playground.ipynb

@@ -0,0 +1,167 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from PIL import Image\n",
+    "\n",
+    "import torch\n",
+    "from transformers import (\n",
+    "    AutoModelForImageClassification,\n",
+    "    AutoImageProcessor,\n",
+    ")\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "MODEL_NAME = \"p1atdev/siglip-tagger-test-2\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = AutoModelForImageClassification.from_pretrained(\n",
+    "    MODEL_NAME, torch_dtype=torch.bfloat16, trust_remote_code=True\n",
+    ")\n",
+    "model.eval()\n",
+    "processor = AutoImageProcessor.from_pretrained(MODEL_NAME)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = Image.open(\"sample.jpg\")\n",
+    "inputs = processor(image, return_tensors=\"pt\").to(model.device, model.dtype)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "logits = model(**inputs).logits.detach().cpu().float()[0]\n",
+    "logits = np.clip(logits, 0.0, 1.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results = {\n",
+    "    model.config.id2label[i]: logit for i, logit in enumerate(logits) if logit > 0\n",
+    "}\n",
+    "results = sorted(results.items(), key=lambda x: x[1], reverse=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1girl: 100.00%\n",
+      "outdoors: 100.00%\n",
+      "sky: 100.00%\n",
+      "solo: 100.00%\n",
+      "school uniform: 96.88%\n",
+      "skirt: 92.97%\n",
+      "day: 89.06%\n",
+      "cloud: 85.94%\n",
+      "scenery: 79.69%\n",
+      "pleated skirt: 72.27%\n",
+      "black hair: 66.80%\n",
+      "standing: 65.62%\n",
+      "sailor collar: 59.38%\n",
+      "sitting: 57.81%\n",
+      "long sleeves: 53.52%\n",
+      "serafuku: 53.12%\n",
+      "holding: 52.34%\n",
+      "tree: 47.46%\n",
+      "dress: 46.48%\n",
+      "shoes: 43.55%\n",
+      "building: 42.77%\n",
+      "neckerchief: 40.82%\n",
+      "short hair: 38.09%\n",
+      "water: 38.09%\n",
+      "cloudy sky: 37.30%\n",
+      "looking at viewer: 32.23%\n",
+      "long hair: 32.03%\n",
+      "brown eyes: 31.45%\n",
+      "plant: 31.05%\n",
+      "bag: 29.30%\n",
+      "railing: 29.10%\n",
+      "sunlight: 28.12%\n",
+      "from side: 27.73%\n",
+      "window: 27.54%\n",
+      "brown hair: 26.37%\n",
+      "white shirt: 25.78%\n",
+      "shirt: 25.39%\n",
+      "blue sky: 23.93%\n",
+      "hairclip: 23.44%\n",
+      "blunt bangs: 21.58%\n",
+      "picture frame: 19.34%\n",
+      "hand up: 18.26%\n",
+      "black skirt: 17.87%\n",
+      "smile: 17.87%\n",
+      "from behind: 13.57%\n",
+      "cowboy shot: 10.99%\n",
+      "indoors: 10.74%\n",
+      "curtains: 10.25%\n",
+      "facing away: 9.23%\n",
+      "white socks: 6.08%\n",
+      "bottle: 6.01%\n",
+      "mountain: 5.66%\n",
+      "blue skirt: 5.13%\n",
+      "drinking straw: 3.37%\n",
+      "kneehighs: 1.71%\n"
+     ]
+    }
+   ],
+   "source": [
+    "for tag, score in results:\n",
+    "    print(f\"{tag}: {score*100:.2f}%\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "py310",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}