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| __all__ = ['learn', 'clasify_image', 'categories', 'image', 'label', 'examples', 'intf'] | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| # Cell | |
| learn = load_learner('export.pkl') | |
| # Cell | |
| categories = ('Beagle', 'Bulldog', 'Dachshund', 'French Bulldog', 'German Shepherd', 'German Shorthaired Pointer', 'Golden Retriever', 'Labrador Retriever', 'Poodle', 'Rottweiler') | |
| # Cell | |
| def classify_image(img): | |
| pred,idx,probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| # Cell | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = ['Beagle.jpg', 'Bulldog.jpg', 'Dachshund.jpg', 'French Bulldog.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outpus=label, examples=examples) | |
| intf.launch(inline=False) |