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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)