lesson_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2904c251",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f566fe5",
   "metadata": {},
   "source": [
    "# Export instructions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8bd8621-65ae-4cb2-bdac-12c3b97a0de5",
   "metadata": {},
   "source": [
    "As of 24.3.18 the way to export cells to a python script is:\n",
    "1) pip install nbdev\n",
    "2) Add \"#|default_exp [file_name]\" to the top of your notebook\n",
    "3) Add \"#|export\" to the top of each cell you want to export\n",
    "4) run:\n",
    "```python\n",
    "    import nbdev\n",
    "    notebook_name = \"lesson_2.ipynb\"\n",
    "    export_destination = \".\" # the root directory\n",
    "    nbdev.export.nb_export(notebook_name, export_destination)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f087d39-106b-46a2-8623-f4429e2885f1",
   "metadata": {},
   "source": [
    "# Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "746c335b-5825-4032-9ee9-834d947ba01d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: 'dlopen(/Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages/torchvision/image.so, 0x0006): Symbol not found: __ZN3c1017RegisterOperatorsD1Ev\n",
      "  Referenced from: <CC4BC91F-8B6A-3F9A-B9EB-A2B9D578E202> /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages/torchvision/image.so\n",
      "  Expected in:     <B36C132B-E822-3FDA-9BEC-DD9DB8197D06> /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages/torch/lib/libtorch_cpu.dylib'If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?\n",
      "  warn(\n"
     ]
    }
   ],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "from fastai.collab import *\n",
    "\n",
    "if os.path.isfile('export.pkl'):\n",
    "    learn: Learner = load_learner('export.pkl')\n",
    "else:\n",
    "    path = untar_data(URLs.PETS)\n",
    "    dls = ImageDataLoaders.from_name_re(path, get_image_files(path/'images'), pat='(.+)_\\d+.jpg', item_tfms=Resize(460), batch_tfms=aug_transforms(size=224, min_scale=0.75))\n",
    "    learn = vision_learner(dls, models.resnet50, metrics=accuracy)\n",
    "    learn.fine_tune(1)\n",
    "    learn.path = Path('.')\n",
    "    learn.export()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d670bc7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "dls: DataLoaders = learn.dls\n",
    "labels = dls.vocab\n",
    "\n",
    "def predict(image):\n",
    "    image = PILImage.create(image)\n",
    "    prediction, prediction_index, probabilities = learn.predict(image)\n",
    "    return { labels[i]: float(probabilities[i]) for i in range(len(labels))}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5be95314",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages (from requests->huggingface-hub>=0.19.3->gradio) (2.0.4)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages (from requests->huggingface-hub>=0.19.3->gradio) (2.1.0)\n",
      "Requirement already satisfied: mdurl~=0.1 in /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages (from markdown-it-py<3.0.0,>=2.2.0->rich<14.0.0,>=10.11.0->typer[all]<1.0,>=0.9->gradio) (0.1.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install gradio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e7e4c80c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "Running on public URL: https://95de38d55a9ae84b0c.gradio.live\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"https://95de38d55a9ae84b0c.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#|export\n",
    "import gradio\n",
    "interface = gradio.Interface(\n",
    "    fn=predict, \n",
    "    inputs=gradio.Image(height=512, width=512), \n",
    "    outputs=gradio.Label(num_top_classes=3),\n",
    "    title=\"Dog Breed Classifier\",\n",
    "    description=\"Upload a photo of a dog and we'll tell you the likely breeds\",\n",
    "    article=\"This is Roman, he's a Red Nosed Pitbull (aka. American Pit-Bull Terrier) from New Orleans.\\n\\nTo try out the classifier, tap on his image to load him into the input box above and then press submit.\",\n",
    "    examples=['roman.png']\n",
    ")\n",
    "interface.launch(share=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "807e0708",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: jupyterlab-quarto in /Users/charlesfeinn/miniforge-pypy3/envs/default/lib/python3.9/site-packages (0.3.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install jupyterlab-quarto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "342a044e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nbdev\n",
    "\n",
    "notebook_name = \"lesson_2.ipynb\"\n",
    "export_destination = \".\" # the root directory\n",
    "nbdev.export.nb_export(notebook_name, export_destination)"
   ]
  }
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