Update app.py

app.py

@@ -33,7 +33,8 @@ model = torch.hub.load('isl-org/ZoeDepth', "ZoeD_N", pretrained=True).to("cpu").
 @spaces.GPU(enable_queue=True)
 def save_raw_16bit(depth, fpath="raw.png"):
     if isinstance(depth, torch.Tensor):
-        depth = depth.squeeze().cpu().numpy()
+        depth
+ = depth.squeeze().cpu().numpy()
     
     assert isinstance(depth, np.ndarray), "Depth must be a torch tensor or numpy array"
     assert depth.ndim == 2, "Depth must be 2D"
@@ -73,7 +74,7 @@ def depth_edges_mask(depth):
     return mask
 
 @spaces.GPU(enable_queue=True)
-def predict_depth(model, image):
+def predict_depth(image):
     global model
     model.to(DEVICE)
     depth = model.infer_pil(image)
@@ -81,10 +82,9 @@ def predict_depth(model, image):
 
 @spaces.GPU(enable_queue=True)
 def get_mesh(image: Image.Image, keep_edges=True):
-    global model
     image.thumbnail((1024,1024))  # limit the size of the input image
 
-    depth = predict_depth(model, image)
+    depth = predict_depth(image)
     pts3d = depth_to_points(depth[None])
     pts3d = pts3d.reshape(-1, 3)