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| from fastai.vision.all import * |
| import gradio as gr |
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| def is_cat(x): return x[0].isupper() |
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| learn = load_learner('model.pkl') |
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| categories = ('Dog','Cat','Dunno') |
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| def classify_image(img): |
| pred,idx,probs = learn.predict(img) |
| return dict(zip(categories,map(float,probs))) |
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| image = gr.inputs.Image(shape=(192,192)) |
| label = gr.outputs.Label() |
| examples= ['dog.jpeg','cat.jpeg','dunno.jpg'] |
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| iface = gr.Interface(fn=classify_image, |
| inputs=image, |
| outputs=label, |
| examples=examples, |
| title = 'Simple Image Classifier', |
| description = "A cat vs dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace spaces.") |
| iface.launch(inline=False) |
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