import gradio as gr
import PIL.Image
from transformers import pipeline

pipe = pipeline('depth-estimation', model='Intel/dpt-large')


def run(image: PIL.Image.Image) -> PIL.Image.Image:
    return pipe(image)['depth']


demo = gr.Interface(fn=run,
                    inputs=gr.Image(type='pil'),
                    outputs='image',
                    title='Depth Estimation',
                    examples=['cats.jpg', 'dogs.jpg'])
demo.queue().launch()