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import platform |
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import pathlib |
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plt = platform.system() |
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pathlib.WindowsPath = pathlib.PosixPath |
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import requests |
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__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'interface', 'classify_image'] |
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from fastai.vision.all import * |
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import PIL.Image |
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PIL.Image.MAX_IMAGE_PIXELS = None |
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from PIL import Image |
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import gradio as gr |
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learn = load_learner('ChestXRayfine.pkl') |
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categories=('COVID19','Normal','Pneumonia','Turberculosis') |
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def classify_image(img): |
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pred,indx,probs=learn.predict(img) |
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return dict(zip(categories,map(float,probs))) |
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image=gr.Image() |
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label=gr.Label() |
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examples=['1.jpeg','10.png','11.png','12.jpeg','13.jpeg','14.jpeg','15.jpeg','16.jpeg','17.jpeg', |
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'18.jpeg','19.jpeg','2.jpeg','20.jpeg','21.jpg','22.jpg','23.jpg','3.jpeg','4.jpeg','5.jpeg', |
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'6.png','7.png','8.png','9.png'] |
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interface=gr.Interface(fn=classify_image, inputs=image ,outputs=label,examples=examples) |
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interface.launch(inline=False) |
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