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from huggingface_hub import from_pretrained_fastai |
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import gradio as gr |
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from fastai.vision.all import * |
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repo_id = "valintea/modelo_p1" |
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learner = from_pretrained_fastai(repo_id) |
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labels = learner.dls.vocab |
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def predict(img): |
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pred,pred_idx,probs = learner.predict(img) |
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return {labels[i]: float(probs[i]) for i in range(len(labels))} |
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gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['0000029906.jpg','0000043910.jpg']).launch(share=False) |
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