{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "learn = load_learner('model.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastbook import *\n",
    "urls = search_images_ddg('banjo',1)\n",
    "from fastdownload import download_url\n",
    "dest = 'banjo.jpg'\n",
    "download_url(urls[0], dest, show_progress=False)\n",
    "\n",
    "im = Image.open(dest)\n",
    "im.to_thumb(256,256)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = PILImage.create('banjo.jpg')\n",
    "img.thumbnail((224,224))\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.predict(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "categories = ('didgeridoo','tambourine','xylophone','acordian','alphorn','bagpipes','banjo','bongo drum','casaba','castanets','clarinet','clavichord','concertina','drums','dulcimer','flute','guiro','guitar','harmonica','harp','marakas','ocarina','piano','saxaphone','sitar','steel drum','trombone','trumpet','tuba','violin')\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": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "classify_image(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "image = gr.inputs.Image(shape=(224,224))\n",
    "label=gr.outputs.Label()\n",
    "examples=['banjo.jpg']\n",
    "intf = gr.Interface(fn=classify_image,inputs=image,outputs=label,examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import nb_export\n",
    "nb_export('app.ipynb')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}