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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from fastai.vision.all import *\n",
"import gradio as gr\n",
"import pathlib\n",
"temp = pathlib.PosixPath\n",
"pathlib.PosixPath = pathlib.WindowsPath\n",
"\n",
"def is_cat(x): return x[0].isupper()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"learn = load_learner('model.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"categories = ('Dog', 'Cat')\n",
"\n",
"def classify_image(img):\n",
" pred,idx,probs = learn.predict(img)\n",
" return dict(zip(categories, map(float,probs)))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:1: 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",
"C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:1: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n",
" image = gr.inputs.Image(shape=(192, 192))\n",
"C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:2: 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",
"C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:2: 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",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/plain": []
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"image = gr.inputs.Image(shape=(192, 192))\n",
"label = gr.outputs.Label()\n",
"examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']\n",
"\n",
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
"intf.launch(inline=False)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import nbdev\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"C:\\Users\\Lenovo\\Desktop\\fastaiTesting\\testai\n"
]
}
],
"source": [
"import os\n",
"print(os.getcwd())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"nbdev.export.nb_export('app.ipynb', r'C:\\Users\\Lenovo\\Desktop\\fastaiTesting\\testai')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"C:\\Users\\Lenovo\\miniconda3\\envs\\pytorch\\python.exe\n"
]
}
],
"source": [
"import sys\n",
"\n",
"print(sys.executable)"
]
}
],
"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": "3.8.17"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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