{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#/default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#/export \n",
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "from PIL import Image\n",
    "import tqdm as notebook_tqdm\n",
    "\n",
    "def is_cat(x): return x[0].isupper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "image/png": 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",
      "text/plain": [
       "PILImage mode=RGB size=192x151"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = PILImage.create('dog2.png')\n",
    "im.thumbnail((192,192))\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#/export\n",
    "learn = load_learner('model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 36.2 ms, sys: 23.3 ms, total: 59.5 ms\n",
      "Wall time: 37.1 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('False', tensor(0), tensor([0.9914, 0.0086]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time learn.predict(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#/export\n",
    "categories = (\"Dog\", \"Cat\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#/export\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": 14,
   "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': 0.99138343334198, 'Cat': 0.008616549894213676}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classify_image(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0l/xypk5csj5hn6q4ftcrgsgx6m0000gn/T/ipykernel_8474/3024765963.py:1: GradioDeprecationWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
      "  image = gr.inputs.Image(shape=(192,192))\n",
      "/var/folders/0l/xypk5csj5hn6q4ftcrgsgx6m0000gn/T/ipykernel_8474/3024765963.py:1: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  image = gr.inputs.Image(shape=(192,192))\n",
      "/var/folders/0l/xypk5csj5hn6q4ftcrgsgx6m0000gn/T/ipykernel_8474/3024765963.py:2: GradioDeprecationWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
      "  label = gr.outputs.Label()\n",
      "/var/folders/0l/xypk5csj5hn6q4ftcrgsgx6m0000gn/T/ipykernel_8474/3024765963.py:2: GradioUnusedKwargWarning: You have unused kwarg parameters in Label, please remove them: {'type': 'auto'}\n",
      "  label = gr.outputs.Label()\n"
     ]
    }
   ],
   "source": [
    "#/export\n",
    "image = gr.inputs.Image(shape=(192,192))\n",
    "label = gr.outputs.Label()\n",
    "examples = [\"dog1.png\", \"cat1.png\", \"dog2.png\", \"cat2.png\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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": 16,
     "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"
    }
   ],
   "source": [
    "#/export\n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = learn.model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
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