diff --git a/src/twomartens/masterthesis/ssd.py b/src/twomartens/masterthesis/ssd.py
index 0017891..4c4295f 100644
--- a/src/twomartens/masterthesis/ssd.py
+++ b/src/twomartens/masterthesis/ssd.py
@@ -322,17 +322,23 @@ def _predict_loop(generator: Generator,
             saved_images_prediction = True
         if use_bayesian:
             decoded_predictions = callables.decode_func_dropout(predictions)
+            callables.save_func(decoded_predictions, original_labels, filenames,
+                                batch_nr=batch_counter,
+                                suffix="_prediction",
+                                save_labels=False)
             observations = callables.get_observations_func(decoded_predictions)
             callables.save_func(observations, original_labels, filenames,
                                 batch_nr=batch_counter,
-                                suffix="_prediction")
+                                suffix="_observation",
+                                save_labels=False)
         for entropy_threshold in entropy_thresholds:
             if use_bayesian:
                 decoded_predictions = callables.apply_entropy_threshold_func(observations,
                                                                              entropy_threshold=entropy_threshold)
                 callables.save_func(decoded_predictions, original_labels, filenames,
                                     batch_nr=batch_counter, entropy_threshold=entropy_threshold,
-                                    suffix="_entropy")
+                                    suffix="_entropy",
+                                    save_labels=False)
                 decoded_predictions = callables.apply_top_k_func(decoded_predictions)
             else:
                 decoded_predictions = callables.decode_func(predictions, entropy_threshold=entropy_threshold)
@@ -483,6 +489,7 @@ def _save_predictions(transformed_predictions: Union[np.ndarray, Sequence[np.nda
                       original_labels: np.ndarray, filenames: Sequence[str],
                       output_file: str, label_output_file: str,
                       batch_nr: int, nr_digits: int, suffix: str,
+                      save_labels: Optional[bool] = True,
                       entropy_threshold: Optional[float] = 0) -> None:
     
     counter_str = str(batch_nr).zfill(nr_digits)
@@ -492,7 +499,8 @@ def _save_predictions(transformed_predictions: Union[np.ndarray, Sequence[np.nda
 
     with open(filename, "wb") as file, open(label_filename, "wb") as label_file:
         pickle.dump(transformed_predictions, file)
-        pickle.dump({"labels": original_labels, "filenames": filenames}, label_file)
+        if save_labels:
+            pickle.dump({"labels": original_labels, "filenames": filenames}, label_file)
 
 
 def _predict_save_images(inputs: np.ndarray, predictions: np.ndarray,