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from fastai.vision.all import * |
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import gradio as gr |
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learn = load_learner('model.pkl') |
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categories = ('person bench pressing','person overhead pressing', 'person deadlifting', 'person lateral raising', 'person bent over row', 'person barbell squatting') |
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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 = ['bench_press.jpg', 'deadlift.jpg', 'lateral_raise.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) |
