{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "63c6b04c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "244328b1",
   "metadata": {},
   "outputs": [],
   "source": [
    " #|export\n",
    "\n",
    "import gradio as gr\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "56802218",
   "metadata": {},
   "outputs": [],
   "source": [
    " #|export\n",
    "\n",
    "from fastai.vision.all import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1d010bb0",
   "metadata": {},
   "outputs": [],
   "source": [
    " #|export\n",
    "\n",
    "learn = load_learner('model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7f141ae1",
   "metadata": {},
   "outputs": [],
   "source": [
    " #|export\n",
    "\n",
    "categories = {'Ronaldo', 'messi', 'Michael Jordan', 'Rafael Nadal', 'Roger Federer'}\n",
    "\n",
    "def classify_athlete(img):\n",
    "    pred,idx,probs = learn.predict(img)\n",
    "    return dict(zip(categories, map(float,probs)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43c2073d",
   "metadata": {},
   "outputs": [
    {
     "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"
    },
    {
     "data": {
      "text/plain": [
       "{'Michael Jordan': 0.928728461265564,\n",
       " 'messi': 0.025283606722950935,\n",
       " 'Rafael Nadal': 0.0039277831092476845,\n",
       " 'Ronaldo': 0.038711678236722946,\n",
       " 'Roger Federer': 0.0033483856823295355}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classify_athlete('cr7.jpeg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8453ac29",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/yunijkarki/anaconda3/envs/my-torch/lib/python3.10/site-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
      "  warnings.warn(\n",
      "/home/yunijkarki/anaconda3/envs/my-torch/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  warnings.warn(value)\n",
      "/home/yunijkarki/anaconda3/envs/my-torch/lib/python3.10/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
      "  warnings.warn(\n",
      "/home/yunijkarki/anaconda3/envs/my-torch/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
      "  warnings.warn(value)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " #|export\n",
    "\n",
    "image = gr.inputs.Image(shape = (192,192))\n",
    "label = gr.outputs.Label()\n",
    "examples = ['cr7.jpeg','messi.jpeg','michael_jordan.jpeg']\n",
    "\n",
    "intf = gr.Interface(fn = classify_athlete,inputs = image, outputs = label, examples = examples)\n",
    "intf.launch(inline = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6f64235",
   "metadata": {},
   "source": [
    "# Making and exporting a python script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c83f04dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/yunijkarki/workspace/testproduct\r\n"
     ]
    }
   ],
   "source": [
    "!pwd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "012a77aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import nb_export\n",
    "nb_export('app.ipynb','/home/yunijkarki/workspace/testproduct')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "b3deaf04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<hr/>\n",
       "<h3>nb_export</h3>\n",
       "<blockquote><pre><code>nb_export(nbname, lib_path=None, procs=<function black_format>, debug=False, mod_maker=<class 'nbdev.maker.ModuleMaker'>, name=None)</code></pre></blockquote><p>Create module(s) from notebook</p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "doc(nb_export)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "70d9a1fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/bin/bash: line 1: torch.__version__: command not found\r\n"
     ]
    }
   ],
   "source": [
    "!torch.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bc8f6369",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.1.0+cu121\n"
     ]
    }
   ],
   "source": [
    "print(torch. __version__) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33ab01ba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": 5
}