{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:00.042481Z",
     "iopub.status.busy": "2024-11-07T16:42:00.042038Z",
     "iopub.status.idle": "2024-11-07T16:42:00.536812Z",
     "shell.execute_reply": "2024-11-07T16:42:00.535349Z",
     "shell.execute_reply.started": "2024-11-07T16:42:00.042436Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/cvd1/pytorch/default/1/model.pkl\n",
      "/kaggle/input/dog-jpeg/dog.jpeg\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:00.539921Z",
     "iopub.status.busy": "2024-11-07T16:42:00.539246Z",
     "iopub.status.idle": "2024-11-07T16:42:00.546035Z",
     "shell.execute_reply": "2024-11-07T16:42:00.544485Z",
     "shell.execute_reply.started": "2024-11-07T16:42:00.539864Z"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "#|default.exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:00.548268Z",
     "iopub.status.busy": "2024-11-07T16:42:00.547765Z",
     "iopub.status.idle": "2024-11-07T16:42:40.346973Z",
     "shell.execute_reply": "2024-11-07T16:42:40.345786Z",
     "shell.execute_reply.started": "2024-11-07T16:42:00.548214Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Installing collected packages: tomlkit, semantic-version, ruff, python-multipart, ffmpy, starlette, huggingface-hub, safehttpx, gradio-client, fastapi, gradio\n",
      "  Attempting uninstall: tomlkit\n",
      "    Found existing installation: tomlkit 0.13.2\n",
      "    Uninstalling tomlkit-0.13.2:\n",
      "      Successfully uninstalled tomlkit-0.13.2\n",
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      "    Found existing installation: python-multipart 0.0.9\n",
      "    Uninstalling python-multipart-0.0.9:\n",
      "      Successfully uninstalled python-multipart-0.0.9\n",
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      "    Found existing installation: starlette 0.37.2\n",
      "    Uninstalling starlette-0.37.2:\n",
      "      Successfully uninstalled starlette-0.37.2\n",
      "  Attempting uninstall: huggingface-hub\n",
      "    Found existing installation: huggingface-hub 0.24.6\n",
      "    Uninstalling huggingface-hub-0.24.6:\n",
      "      Successfully uninstalled huggingface-hub-0.24.6\n",
      "  Attempting uninstall: fastapi\n",
      "    Found existing installation: fastapi 0.111.0\n",
      "    Uninstalling fastapi-0.111.0:\n",
      "      Successfully uninstalled fastapi-0.111.0\n",
      "Successfully installed fastapi-0.115.4 ffmpy-0.4.0 gradio-5.5.0 gradio-client-1.4.2 huggingface-hub-0.26.2 python-multipart-0.0.12 ruff-0.7.2 safehttpx-0.1.1 semantic-version-2.10.0 starlette-0.41.2 tomlkit-0.12.0\n"
     ]
    }
   ],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "!pip install gradio\n",
    "import gradio as gr\n",
    "\n",
    "share = True\n",
    "def is_cat(x): return x[0].isupper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:40.351150Z",
     "iopub.status.busy": "2024-11-07T16:42:40.350198Z",
     "iopub.status.idle": "2024-11-07T16:42:40.780869Z",
     "shell.execute_reply": "2024-11-07T16:42:40.779627Z",
     "shell.execute_reply.started": "2024-11-07T16:42:40.351085Z"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "#|export\n",
    "learn = load_learner('/kaggle/input/cvd1/pytorch/default/1/model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:40.782674Z",
     "iopub.status.busy": "2024-11-07T16:42:40.782252Z",
     "iopub.status.idle": "2024-11-07T16:42:40.789359Z",
     "shell.execute_reply": "2024-11-07T16:42:40.787980Z",
     "shell.execute_reply.started": "2024-11-07T16:42:40.782632Z"
    },
    "trusted": true
   },
   "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": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-07T16:42:40.791441Z",
     "iopub.status.busy": "2024-11-07T16:42:40.791006Z",
     "iopub.status.idle": "2024-11-07T16:42:42.246846Z",
     "shell.execute_reply": "2024-11-07T16:42:42.245632Z",
     "shell.execute_reply.started": "2024-11-07T16:42:40.791400Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7860\n",
      "* Running on public URL: https://f0396da6689b4b4b39.gradio.live\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#|export\n",
    "image = \"image\"\n",
    "label = \"label\"\n",
    "\n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)\n",
    "intf.launch(inline=False, share = True)"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 5660894,
     "sourceId": 9340954,
     "sourceType": "datasetVersion"
    },
    {
     "isSourceIdPinned": true,
     "modelId": 157980,
     "modelInstanceId": 135253,
     "sourceId": 159107,
     "sourceType": "modelInstanceVersion"
    }
   ],
   "dockerImageVersionId": 30761,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}