{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export\n",
    "from fastai.vision.all import*\n",
    "import gradio as gr\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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2vK5yVIGFHUk9gOa871C4a4vJGyCoJVQpyAo6Yqze3kWp2ru0kcJL7VkI+edVyT+tZg5NMaRb02/uNNuftFswD4wQRkEVq3niDU9Rh8qecCI9Y4xtB+tYqrgZHWr1laS3bjaMJ3bsKoZ7dC7Zyh4q3E4QHC8HqKz7B8J81Xkbc52jg9aoyHrPhmVcE45FBjfdlm4AzSyxRoVlPDjow/r61XguPMzuPHT8qQy6xVIwS2aqXR3R5HNNlmUSLzkjt6U8sJYzj8alopM5jWLeSaBgo4/nXlmr2kiXTF8lgfyr3OW2EiEbc1xniDwwZ0aRQARzxWVmtTRM4/RI2VNx5Oa7qwVZYgcMcdxWJoVhCzFGTlT2rrorUhAsZ2/hRa4myNXMZAaVivo1WIphHKZIycj7y+opj2DuAPNUsP7woltrqBd4XIHccipaaBWOjtpFuYgytkMOtTrbsVOTx2rn9DvTJcywlSpXDY7fhXSzXKxw845rWL5lclqzsZ8ykZJP40LtHzHrVW4vFz6+gFQfaGdSelK6GXZGVJSQeCKa4Mikg81nNc7MOx+U019SWIsMNuCllx/EKakhNEGqXYtYjI/AXqa831Z52unu0kEtz5gCQDlUJHDt+Gf0rpNc8Q6Vqtg1tK8kbSAlvl5VV5OfT/69ca10lmboK7PZ7N0kmMNI7/dA9MAihsSKl5JZ3Ze4gLmSPbCBgBO5JUfnVVBg81YnEEWl2YgiaNZA0hDHJJ6cmpLK33YlkHHYetNFFvTbDz3DS8J6dzXWWltCqhFj2qB0FZNqAxBAHtW9aRkAEHn3obGf/9k=",
      "image/png": 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",
      "text/plain": [
       "PILImage mode=RGB size=192x128"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = PILImage.create('cat.jpg')\n",
    "im.thumbnail((192,192))\n",
    "im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/kr/4q10mcs50sj87zzgqq1tkgzsw_c021/T/ipykernel_17179/3467877335.py:9: GradioDeprecationWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
      "  image = gr.inputs.Image(shape=(192,192))\n",
      "/var/folders/kr/4q10mcs50sj87zzgqq1tkgzsw_c021/T/ipykernel_17179/3467877335.py:9: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  image = gr.inputs.Image(shape=(192,192))\n",
      "/var/folders/kr/4q10mcs50sj87zzgqq1tkgzsw_c021/T/ipykernel_17179/3467877335.py:10: GradioDeprecationWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
      "  label = gr.outputs.Label()\n",
      "/var/folders/kr/4q10mcs50sj87zzgqq1tkgzsw_c021/T/ipykernel_17179/3467877335.py:10: GradioUnusedKwargWarning: You have unused kwarg parameters in Label, please remove them: {'type': 'auto'}\n",
      "  label = gr.outputs.Label()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "Running on public URL: https://a38471020988a67549.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/plain": []
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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     "text": [
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.11/site-packages/gradio/routes.py\", line 534, in predict\n",
      "    output = await route_utils.call_process_api(\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/gradio/route_utils.py\", line 226, in call_process_api\n",
      "    output = await app.get_blocks().process_api(\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/gradio/blocks.py\", line 1550, in process_api\n",
      "    result = await self.call_function(\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/gradio/blocks.py\", line 1185, in call_function\n",
      "    prediction = await anyio.to_thread.run_sync(\n",
      "                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/anyio/to_thread.py\", line 33, in run_sync\n",
      "    return await get_asynclib().run_sync_in_worker_thread(\n",
      "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
      "    return await future\n",
      "           ^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
      "    result = context.run(func, *args)\n",
      "             ^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/gradio/utils.py\", line 661, in wrapper\n",
      "    response = f(*args, **kwargs)\n",
      "               ^^^^^^^^^^^^^^^^^^\n",
      "  File \"/var/folders/kr/4q10mcs50sj87zzgqq1tkgzsw_c021/T/ipykernel_17179/3467877335.py\", line 6, in classify_image\n",
      "    preds,idx,probs = learn.predict(im)\n",
      "                      ^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/fastai/learner.py\", line 320, in predict\n",
      "    dl = self.dls.test_dl([item], rm_type_tfms=rm_type_tfms, num_workers=0)\n",
      "         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/fastai/data/core.py\", line 535, in test_dl\n",
      "    test_ds = test_set(self.valid_ds, test_items, rm_tfms=rm_type_tfms, with_labels=with_labels\n",
      "              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/fastai/data/core.py\", line 514, in test_set\n",
      "    if rm_tfms is None: rm_tfms = [tl.infer_idx(get_first(test_items)) for tl in test_tls]\n",
      "                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/fastai/data/core.py\", line 514, in <listcomp>\n",
      "    if rm_tfms is None: rm_tfms = [tl.infer_idx(get_first(test_items)) for tl in test_tls]\n",
      "                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
      "  File \"/usr/local/lib/python3.11/site-packages/fastai/data/core.py\", line 408, in infer_idx\n",
      "    assert idx < len(self.types), f\"Expected an input of type in \\n{pretty_types}\\n but got {type(x)}\"\n",
      "           ^^^^^^^^^^^^^^^^^^^^^\n",
      "AssertionError: Expected an input of type in \n",
      "  - <class 'pathlib.PosixPath'>\n",
      "  - <class 'pathlib.Path'>\n",
      "  - <class 'str'>\n",
      "  - <class 'torch.Tensor'>\n",
      "  - <class 'numpy.ndarray'>\n",
      "  - <class 'bytes'>\n",
      "  - <class 'PIL.Image.Image'>\n",
      "  - <class 'fastai.vision.core.PILImage'>\n",
      " but got <class 'NoneType'>\n"
     ]
    },
    {
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       "    }\n",
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   ],
   "source": [
    "from fastai.vision.all import *\n",
    "import gradio as gr\n",
    "\n",
    "learn = load_learner('export.pkl')\n",
    "def classify_image(im):\n",
    "    preds,idx,probs = learn.predict(im)\n",
    "    \n",
    "    return (preds)\n",
    "image = gr.inputs.Image(shape=(192,192))\n",
    "label = gr.outputs.Label()\n",
    "examples= ['cat.jpg','cat2.jpg','dog.jpg','dog2.jpg','dog3.jpg' ]\n",
    "\n",
    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
    "intf.launch(inline=False,share=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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