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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 = "Gradio test" | |
description = "Quick Fastai classifier for bird/forest." | |
examples = ['examples/bird.jpg', 'examples/tree.jpg', 'examples/rainforest.jpg'] | |
interpretation='default' | |
enable_queue=True | |
gr.Interface(fn=predict,inputs=gr.Image(),outputs=gr.Label(num_top_classes=2),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch() | |
iface.launch() | |