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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() |