Run.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Run.ipynb",
      "provenance": [],
      "mount_file_id": "1W-AAdHkS52r1kupiEeemDvfmIHm8gu_7",
      "authorship_tag": "ABX9TyPYj2+bOtSN+G5KBnEl/J9P",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AARohanAA/pneum/blob/main/Run.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-pDvyzkj4cFr"
      },
      "source": [
        "from fastai.vision.all import *"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "12eH6NGxQxOE"
      },
      "source": [
        "from ipywidgets import *"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wbeRR1kG4krv"
      },
      "source": [
        "from fastai.imports import *"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5326KpOeiOKH"
      },
      "source": [
        "def is_pneumonia(x): return x[0].isupper()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ezRybwA5Zih"
      },
      "source": [
        "path = Path()\r\n",
        "learn_inf = load_learner(path/'export.pkl')\r\n",
        "btn_upload = widgets.FileUpload()\r\n",
        "out_pl = widgets.Output()\r\n",
        "lbl_pred = widgets.Label()\r\n",
        "btn_run = widgets.Button(description='Classify')\r\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kl1Wi-1yQpSJ"
      },
      "source": [
        "def on_click_classify(change):\r\n",
        "    img = PILImage.create(btn_upload.data[-1])\r\n",
        "    out_pl.clear_output()\r\n",
        "    with out_pl: display(img.to_thumb(128,128))\r\n",
        "    pred,pred_idx,probs = learn_inf.predict(img)\r\n",
        "    lbl_pred.value = f'Prediction: {pred}; Probability: {probs[pred_idx]:0.04f}'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1SJGYgprQ2SA"
      },
      "source": [
        "btn_run.on_click(on_click_classify)\r\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eo_226s6zmcV"
      },
      "source": [
        "VBox([widgets.Label('Classify Image! False: Pneumonia Positive  True: Pneumonia Negative'),\r\n",
        "      btn_upload, btn_run,out_pl, lbl_pred])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "txucQ50L0sWQ"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}