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| # AUTOGENERATED! DO NOT EDIT! File to edit: GradioImplemetation.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image'] | |
| # %% GradioImplemetation.ipynb 1 | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| # %% GradioImplemetation.ipynb 4 | |
| learn = load_learner('PlaneRecognizer.pkl') | |
| # %% GradioImplemetation.ipynb 6 | |
| categories = ('Airbus A320','Airbus A380','Boeing 737','Boeing 747') | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| # %% GradioImplemetation.ipynb 8 | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = ['A388.jpg','AA320.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label,examples=examples) | |
| intf.launch(inline=False) | |