{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'fastai'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn [2], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mfastai\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mvision\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mall\u001b[39;00m \u001b[39mimport\u001b[39;00m \u001b[39m*\u001b[39m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'fastai'"
     ]
    }
   ],
   "source": [
    "from fastai.vision.all import *\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = load_learner('export.pkl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = learn.dls.vocab\n",
    "def predict(img):\n",
    "    img = PILImage.create(img)\n",
    "    pred,pred_idx,probs = learn.predict(img)\n",
    "    return {labels[i]: float(probs[i]) for i in range(len(labels))}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gradio as gr\n",
    "gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)"
   ]
  }
 ],
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   "display_name": "Python 3.9.12 ('base')",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "b781f973879b6653a182b86dce637bbad8607b90046e75a81b5febd27741eaed"
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 },
 "nbformat": 4,
 "nbformat_minor": 2
}