{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "79101a84",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "41630a70",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "\n",
    "def is_cat(x): return x[0].is_upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dba3efcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PILImage mode=RGB size=192x145"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = PILImage.create('dog.jpeg')\n",
    "im.thumbnail((192, 192))\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e03b8495",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "learn = load_learner('model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "78341676",
   "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": [
       "('False', tensor(0), tensor([9.9999e-01, 1.4925e-05]))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.predict(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6f8c22ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "categories = ('Dog', 'Cat')\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": 20,
   "id": "bb174570",
   "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": [
       "{'Dog': 0.9999850988388062, 'Cat': 1.4925380128261168e-05}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classify_image(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1b75b041",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/tarikrahmatallah/mambaforge/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",
      "/Users/tarikrahmatallah/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  warnings.warn(value)\n",
      "/Users/tarikrahmatallah/mambaforge/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",
      "/Users/tarikrahmatallah/mambaforge/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://127.0.0.1:7861\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 21,
     "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"
    },
    {
     "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/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/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.inputs.Image(shape=(192, 192))\n",
    "label = gr.outputs.Label()\n",
    "examples = ['dog.jpeg', 'cat.jpeg', 'dunno.jpeg']\n",
    "\n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bd2d6de6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nbdev\n",
    "nbdev.export.nb_export('minimal.ipynb', 'app')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d889a69d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
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 },
 "nbformat": 4,
 "nbformat_minor": 5
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