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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fce9d938-61fa-4459-8cfe-645d8704ecdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "\n",
    "def is_cat(x):\n",
    "    return x[0].isupper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "680879b3-ca39-4235-9ed3-03e023d05e82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PILImage mode=RGB size=192x192"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = PILImage.create('dog.jpg')\n",
    "im.thumbnail((192, 192))\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "db742d46-1d18-4e7c-a51c-4905a21e5830",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib\n",
    "temp = pathlib.PosixPath\n",
    "pathlib.PosixPath = pathlib.WindowsPath\n",
    "\n",
    "learn = load_learner('model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8e79a65e",
   "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([9.9963e-01, 3.7140e-04]))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.predict(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1c6d68ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "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": 10,
   "id": "3913a471",
   "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': 0.9996285438537598, 'Cat': 0.00037139744381420314}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classify_image(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec48f44f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Nifdi Guliyev\\anaconda3\\lib\\site-packages\\gradio\\inputs.py:259: 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",
      "c:\\Users\\Nifdi Guliyev\\anaconda3\\lib\\site-packages\\gradio\\inputs.py:262: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  super().__init__(\n",
      "c:\\Users\\Nifdi Guliyev\\anaconda3\\lib\\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",
      "c:\\Users\\Nifdi Guliyev\\anaconda3\\lib\\site-packages\\gradio\\outputs.py:200: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
      "  super().__init__(num_top_classes=num_top_classes, type=type, label=label)\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": 12,
     "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>"
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    {
     "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>"
      ]
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     "output_type": "display_data"
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    {
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      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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    {
     "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>"
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "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": [
    "image = gr.inputs.Image(shape=(192, 192))\n",
    "label = gr.outputs.Label()\n",
    "examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg'] \n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d6c196e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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