Update app.py

app.py

@@ -9,21 +9,21 @@ import os
 import spaces
 import json
 
-dpt_beit = pipeline(task = "depth-estimation", model="Intel/dpt-beit-base-384")
-depth_anything = pipeline(task = "depth-estimation", model="nielsr/depth-anything-small")
-dpt_large = pipeline(task = "depth-estimation", model="intel/dpt-large")
-@spaces.GPU
+dpt_beit = pipeline(task = "depth-estimation", model="Intel/dpt-beit-base-384", device=0)
+depth_anything = pipeline(task = "depth-estimation", model="nielsr/depth-anything-small", device=0)
+dpt_large = pipeline(task = "depth-estimation", model="intel/dpt-large", device=0)
+
 def depth_anything_inference(img):
   return depth_anything(img)["depth"]
-@spaces.GPU
+
 def dpt_beit_inference(img):
   return dpt_beit(img)["depth"]
 
-@spaces.GPU
+
 def dpt_large_inference(img):
   return dpt_large(img)["depth"]
     
-
+@spaces.GPU
 def infer(img):
   return dpt_large_inference(img), dpt_beit_inference(img), depth_anything_inference(img)
 
@@ -37,6 +37,9 @@ css = """
 """
 with gr.Blocks(css=css) as demo:
   gr.HTML("<h1><center>Compare Depth Estimation Models<center><h1>")
+  gr.HTML("<h2><center>In this Space, you can compare different depth estimation models: [DPT-Large](https://huggingface.co/Intel/dpt-large), [DPT with BeiT backbone](https://huggingface.co/Intel/dpt-beit-large-512) and the recent [Depth Anything Model's small checkpoint](https://huggingface.co/LiheYoung/depth-anything-small-hf).<center><h2>")
+  gr.HTML("<h1><center>Simply upload an image or try the example to see the outputs.<center><h1>")
+
   with gr.Column():
       with gr.Row():
         input_img = gr.Image(label="Input Image", type="pil")