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__all__ = ['learn', '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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from pathlib import Path |
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project_dir = Path(__file__).parent |
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def is_cat(x) -> bool: |
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return x[0].isupper() |
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learn = load_learner("model.pkl") |
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categories = ("Dog", "Cat") |
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def classify_image(img): |
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img = PILImage.create(img) |
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_, _, probs = learn.predict(img) |
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return dict(zip(categories, [float(p) for p in 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 = str((project_dir / "examples").absolute()) |
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print(examples) |
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intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, |
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title = "Dog/Cat Classifier", |
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description = "A dog/cat classifier.", |
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examples=examples, |
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interpretation="default") |
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intf.launch() |
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