from fastai.vision.all import *
learn = load_learner('https://drive.google.com/file/d/1mYN7tOaKpv6sgPt6ekSIoceRQijVGviV/view?usp=share_link')
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 = "Damaged Car Classifier"
description = "This model can identify damaged cars"

intf = gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,interpretation='default',enable_queue=True).launch(share=True)
intf.launch(inline=False)