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692 Bytes
| __all__ = ['is_makeup', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] | |
| # Cell | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_makeup(x): return x[0].isupper() | |
| # Cell | |
| learn = load_learner('model.pkl') | |
| # Cell | |
| categories = ('makeup', 'no makeup') | |
| 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 = ['no makeup.jpg', 'no makeup2.jpg', 'makeup.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title="Makeup? OR No Makeup?") | |
| intf.launch(inline=False) | |