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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "178f75ea",
"metadata": {},
"outputs": [],
"source": [
"from fastai.vision.all import *\n",
"import gradio as gr\n",
"\n",
"def is_cat(x): return x[0].isupper()\n",
"\n",
"learn = load_learner('model.pkl')\n",
"\n",
"categories = ('Dog', 'Cat')\n",
"\n",
"def classify_image(img):\n",
" pred, idx, probs = learn.predict(img)\n",
" return(dict(zip(categories, map(float, probs))))\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "45599222",
"metadata": {},
"outputs": [],
"source": [
"image = gr.Image(shape=(192, 192))\n",
"label = gr.Label()\n",
"examples = ['Dog.jpg', 'Cat.jpg', 'Dunno.jpg']"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "8eda394f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7861\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
"intf.launch(inline=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c4949615",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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