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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))}
examples = ['/kaggle/input/butterfly-images40-species/test/ADONIS/1.jpg',
'/kaggle/input/butterfly-images40-species/test/AFRICAN GIANT SWALLOWTAIL/2.jpg',
'/kaggle/input/butterfly-images40-species/test/AMERICAN SNOOT/3.jpg']
image = gr.Image()
label = gr.Label(num_top_classes = 3)
gr.Interface(fn=predict, inputs=image, outputs=label, examples = examples).launch(share=True)
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