| 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() | |