from fastai.vision.all import * import gradio as gr import skimage learn = load_learner('export.pkl') labels = learn.dls.vocab def predict(img): img = PILImage.create(img) pred,pred_idx,probs = learn.predict(img) return {labels[i]: float(probs[i]) for i in range(len(labels))} title = "Guitar Classifier" examples = ['classical.jpg', 'bass.jpeg', 'electric.jpeg'] interpretation='default' enable_queue=True gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)