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from fastai.vision.all import* |
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import gradio as gr |
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__all__= ['learn', 'labels', 'predict', 'image', 'label', 'examples', 'iface'] |
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learn = load_learner('export.pkl') |
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labels = learn.dls.vocab |
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def predict(img): |
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img = PILImage.create(img) |
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pred,pred_idx,probs = learn.predict(img) |
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return {labels[i]: float(probs[i]) for i in range(len(labels))} |
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image = gr.inputs.Image(shape=(192, 192)) |
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label = gr.outputs.Label() |
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examples = ['black-bear.jpg', 'grizzly.jpg', 'teddy-bear.png'] |
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iface = gr.Interface(fn=predict, inputs=image, outputs=label, examples=examples) |
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iface.launch(inline=False) |