from fastai.vision.all import * import gradio as gr 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 = "Bears Classifier" description = "A simple bears classifier trained on the dataset created with fastai & bing search." examples = ['grizzly.jpg'] gr.Interface(fn=predict, inputs=gr.Image(shape=(512, 512)), outputs=gr.Label(num_top_classes=3), title=title, description=description, examples=examples, ).launch(enable_queue=True)