| # AUTOGENERATED! DO NOT EDIT! File to edit: ../20220918_dog_cat_classifier_with_gradio.ipynb. | |
| # %% auto 0 | |
| __all__ = ['learner', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image'] | |
| # %% ../20220918_dog_cat_classifier_with_gradio.ipynb 1 | |
| from fastai.vision.all import * | |
| import gradio as gr | |
| def is_cat(x): return x[0].isupper() | |
| # %% ../20220918_dog_cat_classifier_with_gradio.ipynb 4 | |
| learner = load_learner('20220918_dogs_cats_model.pkl') | |
| # %% ../20220918_dog_cat_classifier_with_gradio.ipynb 6 | |
| categories = ('Dog', 'Cat') | |
| def classify_image(img): | |
| pred, idx, probs = learner.predict(img) | |
| return dict(zip(categories, map(float, probs))) | |
| # %% ../20220918_dog_cat_classifier_with_gradio.ipynb 8 | |
| image = gr.inputs.Image(shape=(192, 192)) | |
| label = gr.outputs.Label() | |
| examples = ['dog_01.jpeg', 'cat_01.jpeg', 'dunno_01.jpeg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf.launch(inline=False) | |