update

README.md

@@ -72,7 +72,7 @@ yolo predict model=yolov10n/s/m/b/l/x.engine
 
 ## Acknowledgement
 
-The code base is built with [ultralytics](https://github.com/ultralytics/ultralytics) and [RT-DETR](https://github.com/lyuwenyu/RT-DETR)
+The code base is built with [ultralytics](https://github.com/ultralytics/ultralytics) and [RT-DETR](https://github.com/lyuwenyu/RT-DETR).
 
 Thanks for the great implementations! 
 

ultralytics/nn/modules/head.py

@@ -510,6 +510,9 @@ def __init__(self, nc=80, ch=()):
 
     def forward(self, x):
         one2one = self.forward_feat([xi.detach() for xi in x], self.one2one_cv2, self.one2one_cv3)
+        if not self.export:
+            one2many = super().forward(x)
+
         if not self.training:
             one2one = self.inference(one2one)
             if not self.export:
@@ -519,7 +522,6 @@ def forward(self, x):
                 boxes, scores, labels = ops.v10postprocess(one2one.permute(0, 2, 1), self.max_det)
                 return torch.cat([boxes, scores.unsqueeze(-1), labels.unsqueeze(-1)], dim=-1)
         else:
-            one2many = super().forward(x)
             return {"one2many": one2many, "one2one": one2one}
 
     def bias_init(self):