from fastai.vision.all 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 = ('Dog', 'Cat') def classify_images(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)