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| __all__ = ['ategories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image'] |
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| import gradio as gr |
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| def is_cat(x): return x[0].isupper() |
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| ategories = ('Dog', 'Cat') |
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| def classify_image(img): |
| pred, idx, probs = learn.predict(img) |
| print(map(float, probs)) |
| return dict(zip(categories, map(float, probs))) |
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| image = gr.inputs.Image(shape=(192,192)) |
| label = gr.outputs.Label() |
| examples = ['dog.webp', 'cat.png', 'dunno.jpeg'] |
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| intf = gr.Interface(fn=classify_image,inputs=image, outputs=label, examples=examples) |
| intf.launch(inline=False) |
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