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| from fastai.vision.all import * | |
| import gradio as gr | |
| learner = load_learner('export.pkl') | |
| labels = learner.dls.vocab | |
| examples = ['tiger-lily.jpg'] | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred,pred_idx,probs = learner.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),examples=examples).launch() | |