EmbraceLife
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911a563
auto app.py
Browse files- .ipynb_checkpoints/gradiomodel-checkpoint.ipynb +0 -0
- app.py +10 -2
- gradiomodel.ipynb +0 -0
.ipynb_checkpoints/gradiomodel-checkpoint.ipynb
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app.py
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@@ -1,19 +1,27 @@
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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): return x[0].isupper()
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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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image = gr.inputs.Image(shape=(192, 192))
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label = gr.outputs.Label()
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examples = ['../
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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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# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
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__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
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# Cell
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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): return x[0].isupper()
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# Cell
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learn = load_learner('model.pkl')
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# Cell
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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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# Cell
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image = gr.inputs.Image(shape=(192, 192))
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label = gr.outputs.Label()
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examples = ['../input/simplesamples/.jpeg']
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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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gradiomodel.ipynb
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