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from icevision.all import *
import gradio as gr

learn = load_learner('fasterRCNNKangaroo.pth')

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))}
   
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128,128)), outputs=gr.outputs.Label(num_top_classes=3),examples=['00001.jpg','00002.jpg']).launch(share=False)