#__all__ = ["examples", "iface", "learn", "labels", "classify_bear", "bear_image", "outputs"] import gradio as gr from fastai.vision.all import * from fastcore.all import * learn = load_learner("model/export.pkl") labels = learn.dls.vocab examples = [ "examples/black.jpg", "examples/grizzly.jpg", "examples/panda.jpg", "examples/polar.jpg", "examples/teddy.png" ] def classify_bear(img): img = PILImage.create(img) pred,idx,probs = learn.predict(img) return f"Prediction: {pred}; Probability: {probs[idx]:.04f}" bear_image = gr.inputs.Image(shape=(192,192)) outputs = gr.outputs.Label(num_top_classes=5) # App launch iface = gr.Interface( fn=classify_bear, inputs=bear_image, outputs=outputs, examples=examples) iface.launch()