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foo.py
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# AUTOGENERATED! DO NOT EDIT! File to edit: knnccb.ipynb.
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# %% auto 0
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__all__ = ['categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
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# %% knnccb.ipynb 1
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from fastai.vision.all import *
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import gradio as gr
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def is_cat(x):
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return x[0].isupper()
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# %% knnccb.ipynb 8
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categories = ('Dog', 'Cat')
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def classify_image(img):
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pred, idx, probs = learn.predict(img)
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return dict(zip(categories, map(float, probs)))
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# %% knnccb.ipynb 11
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image = gr.components.Image(height = 192, width = 192)
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label = gr.components.Label()
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examples = ['example-dog.jpg', 'example-cat.jpg']
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# %% knnccb.ipynb 12
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intf = gr.Interface(fn = classify_image, inputs = image, outputs = label, examples = examples)
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# %% knnccb.ipynb 13
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intf.launch(inline = False, share=True)
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__all__ = ['categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
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from fastai.vision.all import *
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import gradio as gr
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def is_cat(x):
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return x[0].isupper()
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categories = ('Dog', 'Cat')
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learn = load_learner('model.pkl')
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def classify_image(img):
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pred, idx, probs = learn.predict(img)
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return dict(zip(categories, map(float, probs)))
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image = gr.components.Image(height = 192, width = 192)
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label = gr.components.Label()
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examples = ['example-dog.jpg', 'example-cat.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, share=True)
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