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from fastai.vision.all import * |
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import gradio as gr |
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__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] |
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def is_cat(x): return x[0].issuper() |
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learn = load_learner('model.pkl') |
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categories = ('Cat', 'Dog') |
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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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examples = ['dog.jpg', 'cat.jpg', 'random.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) |
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