init

app.py

@@ -126,7 +126,7 @@ def get_depth_image(
         feature_extractor: AutoImageProcessor,
         depth_estimator: AutoModelForDepthEstimation
 ) -> Image:
-    image_to_depth = feature_extractor(images=image, return_tensors="pt")#.to(device)
+    image_to_depth = feature_extractor(images=image, return_tensors="pt").to(device)
     with torch.no_grad():
         depth_map = depth_estimator(**image_to_depth).predicted_depth
 
@@ -178,6 +178,7 @@ def flush():
     
 class ControlNetDepthDesignModelMulti:
     """ Produces random noise images """
+    @spaces.GPU
     def __init__(self):
         """ Initialize your model(s) here """
         #os.environ['HF_HUB_OFFLINE'] = "True"