| import gradio as gr | |
| from transformers import pipeline | |
| from PIL import Image | |
| import requests | |
| def greet(name): | |
| # load pipe | |
| pipe = pipeline(task="depth-estimation", model="LiheYoung/depth-anything-small-hf") | |
| # load image | |
| url = 'http://images.cocodataset.org/val2017/000000039769.jpg' | |
| image = Image.open(requests.get(url, stream=True).raw) | |
| # inference | |
| depth = pipe(image)["depth"] | |
| return name+": " + depth | |
| iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| iface.launch() |