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import gradio as gr |
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from fastai.vision.all import * |
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from huggingface_hub import from_pretrained_fastai |
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learn = from_pretrained_fastai("Pablogps/gradio-test-24") |
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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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title = "Bad castle predictor" |
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description = "A bad model that tries to identify the type of castle." |
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examples = ['spanish.jpg', 'french.jpg', 'japanese.jpg'] |
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gr.Interface( |
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fn=predict, |
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inputs=gr.Image(), |
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outputs=gr.Label(num_top_classes=3), |
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title=title, |
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description=description, |
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examples=examples, |
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).launch() |
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iface.launch() |
