{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "df084527",
   "metadata": {},
   "source": [
    "# Transformers image processing examples\n",
    "Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. \n",
    "Credits: Huggingface documentation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b642b2ed",
   "metadata": {},
   "source": [
    "## Image classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "be6c9453",
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import pipeline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7fb58fb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "275e0faa56b9408da0ac037321f4c8e8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading (…)lve/main/config.json:   0%|          | 0.00/69.7k [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "116534ad956e439199abad118e13f5b4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading pytorch_model.bin:   0%|          | 0.00/346M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bbf4d3ccfbf44c55ae9b59722cc2799d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading (…)rocessor_config.json:   0%|          | 0.00/160 [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the image classification pipeline with GPU\n",
    "vision_classifier = pipeline(model=\"google/vit-base-patch16-224\", device=0)  # Specify the GPU device index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9129e663",
   "metadata": {},
   "outputs": [],
   "source": [
    "image_url=\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "982a5b7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(url=image_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6cfc0312",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'score': 0.4335, 'label': 'lynx, catamount'},\n",
       " {'score': 0.0348,\n",
       "  'label': 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor'},\n",
       " {'score': 0.0324, 'label': 'snow leopard, ounce, Panthera uncia'},\n",
       " {'score': 0.0239, 'label': 'Egyptian cat'},\n",
       " {'score': 0.0229, 'label': 'tiger cat'}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds = vision_classifier(image_url)\n",
    "preds = [{\"score\": round(pred[\"score\"], 4), \"label\": pred[\"label\"]} for pred in preds]\n",
    "preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c507a767",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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