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import gradio as gr |
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from fastai.vision.all import * |
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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('model.pkl') |
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categories = ('Flower','Sunflower') |
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def classify(img): |
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pred,_,probs = learn.predict(img) |
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return dict(zip(categories, map(float,probs))) |
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image = gr.inputs.Image(shape=(192,192)) |
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label = gr.outputs.Label() |
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examples = ['0.PNG','1.PNG','2.PNG','3.PNG','4.PNG','5.PNG','6.PNG','7.PNG','8.PNG','9.PNG'] |
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iface = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples) |
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iface.launch() |
