| from fastai import * | |
| import gradio as gr | |
| __all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] | |
| def is_cat(x): return x[0].issuper() | |
| learn = load_learner('model.pkl') | |
| categories = ('Cat', 'Dog') | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float, probs))) | |
| image = gr.Inputs.Image(shape=(192,192)) | |
| label = gr.outputs.label() | |
| examples = ['dog.jpg', 'cat.jpg', 'random.jpg'] | |
| intf = gr.Interface(fn = classify_image, inputs = image, outputs = label, examples = examples) | |
| intf.launch(inline=False) | |