painting_style_classifier.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai2.vision.all import *\n",
    "from fastai2.vision.widgets import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Painting Style Classifier**\n",
    "This is a painting style classifier which distinguishes a painting into 'Surrealism', 'Expressionism', 'Mughal miniature', 'Madhubani', 'Cubism' based on fastai2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = Path()\n",
    "learn_inf = load_learner(path/'export.pkl', cpu=True)\n",
    "btn_upload = widgets.FileUpload()\n",
    "out_pl = widgets.Output()\n",
    "lbl_pred = widgets.Label()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def on_click(change):\n",
    "    img = PILImage.create(btn_upload.data[-1])\n",
    "    out_pl.clear_output()\n",
    "    with out_pl: display(img.to_thumb(128,128))\n",
    "    pred, pred_idx, probs = learn_inf.predict(img)\n",
    "    lbl_pred.value = f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "btn_upload.observe(on_click, names=['data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display(VBox([widgets.Label('Select your painting'), btn_upload, out_pl, lbl_pred]))"
   ]
  }
 ],
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