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| # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image'] | |
| # %% app.ipynb 1 | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| # %% app.ipynb 3 | |
| learn = load_learner('modelv2.pkl') | |
| # %% app.ipynb 5 | |
| categories = ('blanched hazelnut', "walnut kernel") | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float, probs))) | |
| # %% app.ipynb 7 | |
| image = gr.components.Image(shape=(192,192)) | |
| label = gr.components.Label() | |
| examples = ['walnut.jpg', 'hazelnut.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=False) | |