{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e0bddbd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "! pip install -Uqq fastbook\n",
    "import fastbook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1b46b67e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "from fastai.vision.widgets import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a089247",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib\n",
    "temp = pathlib.PosixPath\n",
    "pathlib.PosixPath = pathlib.WindowsPath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1f07c129",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = Path()\n",
    "learn_inf = load_learner(path/'export.pkl', cpu=True)\n",
    "btn_upload = widgets.FileUpload()\n",
    "out_pl = widgets.Output()\n",
    "lbl_pred = widgets.Label()\n",
    "btn_run = widgets.Button(description='Classify')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b319ee30",
   "metadata": {},
   "outputs": [],
   "source": [
    "def on_click_classify(change):\n",
    "    img = PILImage.create(btn_upload.data[-1])\n",
    "    out_pl.clear_output()\n",
    "    with out_pl: display(img.to_thumb(128,128))\n",
    "    pred, pred_idx, probs = learn_inf.predict(img)\n",
    "    lbl_pred.value = f'Prediction: {str(pred)[10:]}; Probability: {probs[pred_idx]:.04f}'\n",
    "    \n",
    "btn_run.on_click(on_click_classify)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "114b5a71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "476e154bfede489a9560404bca8fff16",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='Select your images'), FileUpload(value={}, description='Upload'), Button(descripti…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "VBox([widgets.Label('Select your images'),\n",
    "     btn_upload, btn_run, out_pl, lbl_pred])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d640937e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "d925690840644bcd766647b280b19c370132b1426b7601e4e2f280a77c18a034"
  },
  "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}