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import gradio as gr |
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from huggingface_hub import from_pretrained_fastai |
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from fastai.learner import load_learner |
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from PIL import Image |
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from fastai.vision.all import load_learner |
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repo_id = "JuncalG/Practica1" |
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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 {str(learner.dls.vocab[i]): float(probs[i]) for i in range(len(probs))} |
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demo = gr.Interface( |
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fn=predict, |
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inputs=gr.Image(type="pil"), |
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outputs=gr.Label(num_top_classes=5), |
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examples=['af3b0115aad1.png', 'b191ba0a2b12.png'] |
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) |
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demo.launch(share=True) |
