diff --git a/ultralytics/models/yolo/obb/val.py b/ultralytics/models/yolo/obb/val.py
index e16d75f2..c9f70b13 100644
--- a/ultralytics/models/yolo/obb/val.py
+++ b/ultralytics/models/yolo/obb/val.py
@@ -61,7 +61,7 @@ class OBBValidator(DetectionValidator):
         Returns:
             (torch.Tensor): Correct prediction matrix of shape [N, 10] for 10 IoU levels.
         """
-        iou = batch_probiou(gt_bboxes, torch.cat([detections[:, :4], detections[:, -2:-1]], dim=-1))
+        iou = batch_probiou(gt_bboxes, torch.cat([detections[:, :4], detections[:, -1:]], dim=-1))
         return self.match_predictions(detections[:, 5], gt_cls, iou)
 
     def _prepare_batch(self, si, batch):
diff --git a/ultralytics/utils/ops.py b/ultralytics/utils/ops.py
index 12ac0461..d589436d 100644
--- a/ultralytics/utils/ops.py
+++ b/ultralytics/utils/ops.py
@@ -263,7 +263,7 @@ def non_max_suppression(
         c = x[:, 5:6] * (0 if agnostic else max_wh)  # classes
         scores = x[:, 4]  # scores
         if rotated:
-            boxes = torch.cat((x[:, :2] + c, x[:, 2:4], x[:, -2:-1]), dim=-1)  # xywhr
+            boxes = torch.cat((x[:, :2] + c, x[:, 2:4], x[:, -1:]), dim=-1)  # xywhr
             i = nms_rotated(boxes, scores, iou_thres)
         else:
             boxes = x[:, :4] + c  # boxes (offset by class)