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from fastai.vision.all import *
import gradio as gr
learn = load_learner("classifier.pkl")
labels = learn.dls.vocab
examples = ['dolphin.jpg', 'shark.jpg', 'whale.jpg']
def predict(img_file):
img = PILImage.create(img_file)
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),
examples=examples).launch(share=True, debug=False)