further attempts...

app.py

@@ -97,24 +97,19 @@ except Exception as e:
     raise gr.Error(f"Failed to load model {MODEL_NAME}. Check logs. Error: {e}")
 
 
-# --- Blurnonymizer Instance ---
-try:
-    blurnonymizer_instance = blurnonymize.ImageBlurnonymizer()
-    print("Blurnonymizer initialized successfully.")
-except Exception as e:
-    print(f"Error initializing Blurnonymizer: {e}")
-    print(traceback.format_exc())
-    raise gr.Error(f"Failed to initialize Blurnonymizer. Check logs. Error: {e}")
-
 # --- Core Processing Function ---
 @spaces.GPU(duration=30)
 def anonymise_image(input_image_np: np.ndarray, boxes: list[BoundingBox]):
-    """Calls the blurnonymizer instance to censor the image."""
-    if not blurnonymizer_instance:
-        raise gr.Error("Blurnonymizer not initialized.")
-    return blurnonymizer_instance.censor_image_blur_easy(
-        input_image_np, boxes, method="segmentation", verbose=False # Set verbose as needed
-    )
+    # --- Blurnonymizer Instance ---
+    try:
+        blurnonymizer_instance = blurnonymize.ImageBlurnonymizer()
+        return blurnonymizer_instance.censor_image_blur_easy(
+            input_image_np, boxes, method="segmentation", verbose=False # Set verbose as needed
+        )
+    except Exception as e:
+        print(f"Error initializing Blurnonymizer: {e}")
+        print(traceback.format_exc())
+        raise gr.Error(f"Failed to initialize Blurnonymizer. Check logs. Error: {e}")
 
 
 def run_model_inference(input_image_pil: Image.Image, prompt_text: str):

blurnonymize.py

@@ -163,8 +163,8 @@ class ImageBlurnonymizer:
         torch.cuda.set_device(device)
         self.predictor = SAM2ImagePredictor.from_pretrained(
             "facebook/sam2.1-hiera-small",
-            device=device,
-        )
+            device="cuda",
+        ).to("cuda").eval()
 
     @staticmethod
     def _smoothen_mask(mask: np.ndarray):