more debugging for CUDA being initialized outside of hugging space domain

app.py

@@ -22,7 +22,7 @@ subprocess.run(["bash", "get_pretrained_models.sh"])
 
 @spaces.GPU(duration=30)
 def load_model_and_predict(image_path):
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     model, transform = depth_pro.create_model_and_transforms()
     model = model.to(device)
     model.eval()
@@ -219,6 +219,7 @@ def predict_depth(input_image):
         print(f"Resized image path: {temp_file}")
         
         depth, focallength_px = load_model_and_predict(temp_file)
+        print(f"Raw depth type: {type(depth)}, focallength_px type: {type(focallength_px)}")
 
         if depth.ndim != 2:
             depth = depth.squeeze()
@@ -236,9 +237,14 @@ def predict_depth(input_image):
         plt.close()
 
         raw_depth_path = "raw_depth_map.csv"
-        np.savetxt(raw_depth_path, depth, delimiter=',')
+        np.savetxt(raw_depth_path, depth.cpu().numpy() if isinstance(depth, torch.Tensor) else depth, delimiter=',')
+        print(f"Saved raw depth map to {raw_depth_path}")
+
+        focallength_px = float(focallength_px)
+        print(f"Converted focallength_px to float: {focallength_px}")
 
         print("Depth map created!")
+        print(f"Returning - output_path: {output_path}, focallength_px: {focallength_px}, raw_depth_path: {raw_depth_path}, temp_file: {temp_file}")
         return output_path, f"Focal length: {focallength_px:.2f} pixels", raw_depth_path, temp_file, focallength_px
     except Exception as e:
         import traceback
@@ -248,6 +254,7 @@ def predict_depth(input_image):
     finally:
         if temp_file and os.path.exists(temp_file):
             os.remove(temp_file)
+            print(f"Removed temporary file: {temp_file}")
 
 @spaces.GPU(duration=30)
 def create_3d_model(depth_csv, image_path, focallength_px, simplification_factor, smoothing_iterations, thin_threshold):