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from fastai.vision.all import * |
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import gradio as gr |
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def is_cat(x): return x[0].isupper() |
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learn = load_learner('model.pkl') |
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categories = ('Dog','Cat','Dunno') |
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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.jpeg','cat.jpeg','dunno.jpeg'] |
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iface = gr.Interface(fn=classify_image, |
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inputs=image, |
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outputs=label, |
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examples=examples, |
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title = 'Simple Image Classifier', |
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description = "A cat vs dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace spaces.") |
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iface.launch(inline=False) |
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