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from fastai.vision.all import * |
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import gradio as gr |
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import pathlib |
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class GetX(ItemTransform): |
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def encodes(self, x): return (x[0]) |
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class GetY(ItemTransform): |
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def encodes(self, x): return (x[1]) |
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pathlib.WindowsPath = pathlib.PosixPath |
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learn = load_learner("model.pkl") |
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categories = ( |
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'Round Smooth Galaxies', 'Barred Spiral Galaxies', |
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) |
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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.inputs.Image(shape=(192, 192)) |
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label = gr.outputs.Label() |
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intf = gr.Interface(fn=classify_image, inputs=image, outputs=label) |
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intf.launch(inline=False) |