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from fastai.vision.all import * |
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import gradio as gr |
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import pathlib |
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plt = platform.system() |
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if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath |
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learn = load_learner('export.pkl') |
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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 = "Bear Classifier" |
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description = "A bear classifier trained on downloaded images of bear dataset with fastai." |
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article="<p style='text-align: center'><a href='https://shuowangphd.github.io' target='_blank'>Back to my personal webpage.</a></p>" |
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exa = [['grizzly.jpg'],['teddy.jpg']] |
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interpretation='default' |
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enable_queue=True |
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gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), |
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outputs=gr.outputs.Label(num_top_classes=3), |
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title=title,description=description,article=article,examples=exa, |
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interpretation=interpretation, |
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enable_queue=enable_queue).launch() |
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