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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0586c32f-2c84-42eb-97a1-e52da6637451",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f9533a95-acfb-4d5b-a508-e96b9eff63b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: gradio in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (5.10.0)\n",
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      "Requirement already satisfied: packaging in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (24.1)\n",
      "Requirement already satisfied: pandas<3.0,>=1.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (2.2.3)\n",
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      "Requirement already satisfied: semantic-version~=2.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (2.10.0)\n",
      "Requirement already satisfied: starlette<1.0,>=0.40.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (0.41.3)\n",
      "Requirement already satisfied: tomlkit<0.14.0,>=0.12.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (0.13.2)\n",
      "Requirement already satisfied: typer<1.0,>=0.12 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio) (0.15.1)\n",
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      "Requirement already satisfied: fsspec in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio-client==1.5.3->gradio) (2024.2.0)\n",
      "Requirement already satisfied: websockets<15.0,>=10.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from gradio-client==1.5.3->gradio) (14.1)\n",
      "Requirement already satisfied: idna>=2.8 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from anyio<5.0,>=3.0->gradio) (3.7)\n",
      "Requirement already satisfied: sniffio>=1.1 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from anyio<5.0,>=3.0->gradio) (1.3.1)\n",
      "Requirement already satisfied: certifi in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from httpx>=0.24.1->gradio) (2024.7.4)\n",
      "Requirement already satisfied: httpcore==1.* in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from httpx>=0.24.1->gradio) (1.0.7)\n",
      "Requirement already satisfied: h11<0.15,>=0.13 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from httpcore==1.*->httpx>=0.24.1->gradio) (0.14.0)\n",
      "Requirement already satisfied: filelock in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface-hub>=0.25.1->gradio) (3.13.1)\n",
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      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas<3.0,>=1.0->gradio) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas<3.0,>=1.0->gradio) (2024.2)\n",
      "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas<3.0,>=1.0->gradio) (2024.1)\n",
      "Requirement already satisfied: annotated-types>=0.6.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pydantic>=2.0->gradio) (0.7.0)\n",
      "Requirement already satisfied: pydantic-core==2.27.2 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pydantic>=2.0->gradio) (2.27.2)\n",
      "Requirement already satisfied: click>=8.0.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from typer<1.0,>=0.12->gradio) (8.1.8)\n",
      "Requirement already satisfied: shellingham>=1.3.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from typer<1.0,>=0.12->gradio) (1.5.4)\n",
      "Requirement already satisfied: rich>=10.11.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from typer<1.0,>=0.12->gradio) (13.9.4)\n",
      "Requirement already satisfied: colorama in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from click>=8.0.0->typer<1.0,>=0.12->gradio) (0.4.6)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from python-dateutil>=2.8.2->pandas<3.0,>=1.0->gradio) (1.16.0)\n",
      "Requirement already satisfied: markdown-it-py>=2.2.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio) (3.0.0)\n",
      "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio) (2.19.1)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface-hub>=0.25.1->gradio) (3.3.2)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface-hub>=0.25.1->gradio) (2.2.2)\n",
      "Requirement already satisfied: mdurl~=0.1 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio) (0.1.2)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install gradio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "897c4423-1979-46c3-8e19-26badbda959c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "\n",
    "\n",
    "def whichBear(x): return x[0].isBear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f5ffbd98-7060-40ea-8050-8b4eeec0b403",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
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",
      "text/plain": [
       "PILImage mode=RGB size=192x127"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = PILImage.create('brown_bear.jpg')\n",
    "im.thumbnail((192,192))\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2e701c46-d338-4ba5-a14f-1a5bc0b8e7a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "\n",
    "if platform.system().lower() == \"windows\":\n",
    "    import pathlib\n",
    "    posix_path = pathlib.PosixPath\n",
    "    pathlib.PosixPath = pathlib.WindowsPath\n",
    "learn = load_learner(\"model.pkl\")\n",
    "if platform.system().lower() == \"windows\":\n",
    "    pathlib.PosixPath = posix_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bfe7a659-51eb-4a95-8b75-b3c6dc191601",
   "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": [
       "('grizzly', tensor(1), tensor([2.7394e-04, 9.9953e-01, 1.9707e-04]))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.predict(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7028b04f-5c3a-4758-95a4-1454e5256b23",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "options = (\"grizzly\", \"black\", \"teddy\")\n",
    "\n",
    "def classify_img(img):\n",
    "    pred,idx,probs = learn.predict(img)\n",
    "    return dict(zip(options, map(float, probs)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b4f60813-7fdc-4d53-8650-91fd7f2a8d0e",
   "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": [
       "{'grizzly': 0.0002739447227213532,\n",
       " 'black': 0.9995290040969849,\n",
       " 'teddy': 0.000197066183318384}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classify_img(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "23f6d95e-4046-4a99-84b8-195c3e8ec8dd",
   "metadata": {},
   "outputs": [
    {
     "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": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#|export\n",
    "image = gr.Image()\n",
    "label = gr.Label()\n",
    "examples = [\"brown_bear.jpg\", \"grizzly_bear.jpg\", \"teddy_bear.jpg\"]\n",
    "\n",
    "intf = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ed4b0be0-a71a-4e48-8427-266642d34891",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: nbdev in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (2.3.34)\n",
      "Requirement already satisfied: packaging in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (24.1)\n",
      "Requirement already satisfied: fastcore>=1.5.27 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (1.7.28)\n",
      "Requirement already satisfied: execnb>=0.1.4 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (0.1.11)\n",
      "Requirement already satisfied: astunparse in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (1.6.3)\n",
      "Requirement already satisfied: ghapi>=1.0.3 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (1.0.6)\n",
      "Requirement already satisfied: watchdog in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (6.0.0)\n",
      "Requirement already satisfied: asttokens in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (3.0.0)\n",
      "Requirement already satisfied: setuptools in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (65.5.0)\n",
      "Requirement already satisfied: PyYAML in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from nbdev) (6.0.2)\n",
      "Requirement already satisfied: ipython in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from execnb>=0.1.4->nbdev) (8.31.0)\n",
      "Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from astunparse->nbdev) (0.45.1)\n",
      "Requirement already satisfied: six<2.0,>=1.6.1 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from astunparse->nbdev) (1.16.0)\n",
      "Requirement already satisfied: colorama in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (0.4.6)\n",
      "Requirement already satisfied: decorator in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (5.1.1)\n",
      "Requirement already satisfied: jedi>=0.16 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (0.19.2)\n",
      "Requirement already satisfied: matplotlib-inline in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (0.1.7)\n",
      "Requirement already satisfied: prompt_toolkit<3.1.0,>=3.0.41 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (3.0.48)\n",
      "Requirement already satisfied: pygments>=2.4.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (2.19.1)\n",
      "Requirement already satisfied: stack_data in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (0.6.3)\n",
      "Requirement already satisfied: traitlets>=5.13.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (5.14.3)\n",
      "Requirement already satisfied: typing_extensions>=4.6 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from ipython->execnb>=0.1.4->nbdev) (4.12.2)\n",
      "Requirement already satisfied: parso<0.9.0,>=0.8.4 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jedi>=0.16->ipython->execnb>=0.1.4->nbdev) (0.8.4)\n",
      "Requirement already satisfied: wcwidth in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from prompt_toolkit<3.1.0,>=3.0.41->ipython->execnb>=0.1.4->nbdev) (0.2.13)\n",
      "Requirement already satisfied: executing>=1.2.0 in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from stack_data->ipython->execnb>=0.1.4->nbdev) (2.1.0)\n",
      "Requirement already satisfied: pure-eval in c:\\users\\colpe\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from stack_data->ipython->execnb>=0.1.4->nbdev) (0.2.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install nbdev\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6d7a6c33-604f-492e-b52b-4b165edb23d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib\n",
    "plt = platform.system()\n",
    "if plt == 'Windows': pathlib.PosixPath = pathlib.WindowsPath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "81e467bf-74d0-4173-9773-b1c8151cd419",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import nb_export\n",
    "\n",
    "nb_export('app.ipynb')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d1e42e5-db46-4a6e-b0b6-88841d7210ad",
   "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}