| from fastai.learner import load_learner | |
| import gradio as gr | |
| learn = load_learner('./export.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| pred,pred_idx,probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| gr.Interface(fn=predict, | |
| inputs=gr.inputs.Image(shape=(512, 512)), | |
| outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True) |