{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cde69a49-7ab1-4bf5-bb0f-30746827dedb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e3e7300c-9b84-4687-8c72-7914240e9397",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Suppress only UserWarning\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore', category=UserWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5026e71e-78b2-451c-b5f8-20421387a480",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install gradio > /dev/null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "39544176-83a1-4bcb-bdc3-c8acb8a2ba84",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "\n",
    "import pathlib\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "38301e4e-11fc-4f1e-909f-58759b8d9e8d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#|export\n",
    "\n",
    "path = pathlib.Path('.')\n",
    "\n",
    "try:    \n",
    "    path = pathlib.Path(__file__).parent.resolve()\n",
    "except NameError:    \n",
    "    if 'SPACE_ID' in os.environ:         \n",
    "         path = pathlib.Path('nbs')  \n",
    "\n",
    "model_path = path / 'model.pkl'\n",
    "\n",
    "learn = load_learner(model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "905035bc-6dd2-45ba-aee8-b77a5b519a04",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "categories = learn.dls.vocab\n",
    "\n",
    "def classify_image(img):\n",
    "    pred,idx,probs = learn.predict(img)\n",
    "    return dict(zip(categories, map(float,probs)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e77f8a97-e73f-4c3b-a73d-a958689ff1a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7863\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#|export\n",
    "image = gr.Image(type=\"pil\")\n",
    "label = gr.Label()\n",
    "\n",
    "examples = [\n",
    "    path / 'black_bear.jpg',\n",
    "    path / 'grizzly_bear.jpg',\n",
    "    path / 'teddy_bear.jpg'\n",
    "    ]\n",
    "\n",
    "intf = gr.Interface(\n",
    "    fn=classify_image,  \n",
    "    inputs=image,       \n",
    "    outputs=label,      \n",
    "    examples=examples\n",
    ")\n",
    "\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a379ae5-65ff-476a-ba6d-3c1edc6878b3",
   "metadata": {},
   "source": [
    "## export python file from the notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "af0ec285-9e53-49f0-be57-12d4e1fc1a3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nbdev\n",
    "\n",
    "nbdev.export.nb_export('app.ipynb', '.')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (fastai_env)",
   "language": "python",
   "name": "fastai_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}