Update head.py

ultralytics/nn/modules/head.py

@@ -48,8 +48,6 @@ class Detect(nn.Module):
             self.one2one_cv2 = copy.deepcopy(self.cv2)
             self.one2one_cv3 = copy.deepcopy(self.cv3)
 
-        self.relu = nn.ReLU()
-
     def forward(self, x):
         """Concatenates and returns predicted bounding boxes and class probabilities."""
         if self.end2end:
@@ -120,11 +118,10 @@ class Detect(nn.Module):
             dbox = self.decode_bboxes(
                 self.dfl(box) * self.strides, self.anchors.unsqueeze(0) * self.strides, xywh=False
             )
-            # NOTE: the relu could be removed in the future.
-            y1 = self.relu(dbox[:, 0, :])
-            x1 = self.relu(dbox[:, 1, :])
-            y2 = self.relu(dbox[:, 2, :])
-            x2 = self.relu(dbox[:, 3, :])
+            y1 = dbox[:, 0, :]
+            x1 = dbox[:, 1, :]
+            y2 = dbox[:, 2, :]
+            x2 = dbox[:, 3, :]
             y_bb = torch.stack((x1, y1, x2, y2), 1).transpose(1, 2)
             return y_bb, cls.sigmoid().permute(0, 2, 1)
         else: