diff --git a/yolo/tools/data_loader.py b/yolo/tools/data_loader.py
index 5f7245f..794c6f0 100644
--- a/yolo/tools/data_loader.py
+++ b/yolo/tools/data_loader.py
@@ -99,9 +99,6 @@ def filter_data(self, dataset_path: Path, phase_name: str, sort_image: bool = Fa
                     continue
                 annotations = annotations_index.get(image_info["id"], [])
                 image_seg_annotations = scale_segmentation(annotations, image_info)
-                if not image_seg_annotations:
-                    continue
-
             elif data_type == "txt":
                 label_path = labels_path / f"{image_id}.txt"
                 if not label_path.is_file():
diff --git a/yolo/tools/loss_functions.py b/yolo/tools/loss_functions.py
index ec23855..54fd7cf 100644
--- a/yolo/tools/loss_functions.py
+++ b/yolo/tools/loss_functions.py
@@ -93,7 +93,7 @@ def __call__(self, predicts: List[Tensor], targets: Tensor) -> Tuple[Tensor, Ten
         targets_cls, targets_bbox = self.separate_anchor(align_targets)
         predicts_box = predicts_box / self.vec2box.scaler[None, :, None]
 
-        cls_norm = targets_cls.sum()
+        cls_norm = max(targets_cls.sum(), 1)
         box_norm = targets_cls.sum(-1)[valid_masks]
 
         ## -- CLS -- ##