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| __all__ = ['temp', 'model', 'learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
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| import numpy as np
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| import pandas as pd
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| from fastai.vision.all import *
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| import gradio as gr
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| def is_cat(x): return x[0].isupper()
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| from pathlib import Path
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| import pathlib
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| temp = pathlib.PosixPath
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| model = Path('model.pkl')
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| learn = load_learner(model, cpu=True)
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| categories = ['dog', 'cat']
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| def classify_image(img):
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| pred,idx,probs = learn.predict(img)
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| return dict(zip(categories, map(float, probs)))
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| image = gr.Image()
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| label = gr.Label()
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| examples = ['dog.jpg', 'cat.jpg']
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| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
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| intf.launch(inline=False, share=True)
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