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import gradio as gr |
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from fastai.learner import load_learner |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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learn = load_learner('edureyyy/MamographyClassifier/ModelSuperKek.pkl') |
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label = ['Cancer', 'No Cancer'] |
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def classificador(im): |
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pred,idx,probs = learn.predict(im) |
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return dict(zip(label, map(float, probs))) |
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imatge = gr.inputs.Image(shape=(192,192)) |
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label = gr.outputs.Label() |
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example = ['/kaggle/input/rsna22-bal/rsna22_bal/rsna22_bal/images_png/12305_1995339680_L.png', '/kaggle/input/rsna22-bal/rsna22_bal/rsna22_bal/images_png/10234_173054723_L.png' ] |
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intf = gr.Interface(fn=classificador, inputs = imatge, outputs = label) |
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intf.launch(inline=False) |
