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  {
   "cell_type": "markdown",
   "id": "77fbe5ae",
   "metadata": {},
   "source": [
    "# Film Stars Gradio App"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37d47b60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|default_exp app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96a084dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "from fastai.vision.all import *\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0dd4db80",
   "metadata": {},
   "outputs": [],
   "source": [
    "pic = 'Penelope Cruz.jpg'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf73c204",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "learn50 = load_learner('filmstars50.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18bfac9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "labels = learn50.dls.vocab\n",
    "def classify_image(pic):\n",
    "    pred,pred_idx,probs = learn50.predict(PILImage.create(pic))\n",
    "    #ps, idxs = probs.topk(3)\n",
    "    return  {labels[i]: float(probs[i]) for i in range(len(labels))}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d49e1a0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "classify_image(pic);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "773dab23",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "image = gr.components.Image()\n",
    "examples = ['Angelina Jolie.jpg','Penelope Cruz.jpg','Jack Nicholson.jpg']\n",
    "title = \"Identify film stars similar to your image\"\n",
    "description = \"Try uploading a photograph of yourself\"\n",
    "article = \"<p style='text-align: center'><a href='https://science4performance.com/2023/01/01/eddy-goes-to-hollywood/' target='_blank'>Blog post</a></p>\"\n",
    "intfr = gr.Interface(fn=classify_image, inputs=image, outputs=gr.components.Label(num_top_classes=3), examples=examples, title=title, description=description, article=article)\n",
    "intfr.launch(inline=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "705f241c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import nb_export\n",
    "nb_export('FilmStarsApp.ipynb')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbaa52cc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "toc": {
   "nav_menu": {},
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {},
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