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from fastai.vision import *
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from fastai.learner import load_learner
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from PIL import Image
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import gradio as gr
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import pathlib, platform
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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 = list(learn.dls.vocab)
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def classify_image(img):
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pred, ix, 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 = ["examples/kairi.jpg", "examples/riku.jpg", "examples/sora.jpg"]
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intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
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intf.launch(inline=False)
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