app.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fb0b148e",
   "metadata": {},
   "source": [
    "# This notebook is the .ipynb file for the model. \n",
    "The code has been commmented in order to explain various parts, including the unused commented out parts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e39e2ed1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "435a6f23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# On my computer, I use Anaconda, where these packages are already installed, so there is no need to install them on the notebook\n",
    "# On HuggingFaceSpaces, these packages have been put into requirements.txt so that the website installs them\n",
    "# Therefore there is no need to install them \n",
    "\n",
    "#%pip install -q gradio\n",
    "#%pip install fastbook\n",
    "#%pip install -Uqq fastai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a89a7628",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "# Importing neccesary modules\n",
    "import fastbook\n",
    "fastbook.setup_book()\n",
    "from fastbook import *\n",
    "from fastai.vision.widgets import *\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8c95d6bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# There was an error with the module Pillow, it was not updated and I attempted to update it within the notebook\n",
    "# This was not neccesary as I updated Pillow on my anaconda app and it fixed it.\n",
    "\n",
    "#!pip uninstall Pillow\n",
    "#!pip install Pillow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fe4889a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# There was an error the first time I ran this code on the notebook: \"NotImplementedError: cannot instantiate 'PosixPath' on your system\"\n",
    "# this code fixed it, but as it is suited for windows,\n",
    "# this causes an error on HuggingSpaceFaces, which likely uses linux. \n",
    "# Strangely, simply commenting this code out does not cause the initial error on HuggingFaceSpaces and works for it\n",
    "\n",
    "import pathlib\n",
    "temp = pathlib.PosixPath\n",
    "pathlib.PosixPath = pathlib.WindowsPath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d1d0d596",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Adnan\\anaconda3\\lib\\site-packages\\gradio\\inputs.py:256: 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\\Adnan\\anaconda3\\lib\\site-packages\\gradio\\deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  warnings.warn(value)\n",
      "C:\\Users\\Adnan\\anaconda3\\lib\\site-packages\\gradio\\outputs.py:196: 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\\Adnan\\anaconda3\\lib\\site-packages\\gradio\\deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
      "  warnings.warn(value)\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": [
       "(<gradio.routes.App at 0x2b1d5af4640>, 'http://127.0.0.1:7861/', None)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#|export\n",
    "learn_inf = load_learner('NovaOrToastModel.pkl') # Loading the model\n",
    "learn_inf.dls.vocab # Returns a list of the categories\n",
    "categories = learn_inf.dls.vocab\n",
    "\n",
    "# Gradio code:\n",
    "\n",
    "# Function for Gradio to use to classify images\n",
    "def classify_image(img):\n",
    "    pred, idx, probs = learn_inf.predict(img)\n",
    "    return dict(zip(categories, map(float,probs)))\n",
    "\n",
    "image = gr.inputs.Image(shape=(192,192)) \n",
    "label = gr.outputs.Label()\n",
    "examples = [\"ToastTest.jpeg\"]\n",
    "\n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "300585db",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import notebook2script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "72d6a182",
   "metadata": {},
   "outputs": [],
   "source": [
    "#from nbdev import get_config\n",
    "#get_config (cfg_name='settings.ini', path=None)\n",
    "#get_config (cfg_name='settings.ini')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fad6e0cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "notebook2script('NovaOrToast.ipynb')"
   ]
  }
 ],
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