updates

utils/utils.py

@@ -405,8 +405,15 @@ def compute_loss(p, targets, model):  # predictions, targets, model
             tobj[b, a, gj, gi] = (1.0 - model.gr) + model.gr * giou.detach().clamp(0).type(tobj.dtype)  # giou ratio
 
             if 'default' in arc and model.nc > 1:  # cls loss (only if multiple classes)
-                t = torch.zeros_like(ps[:, 5:])  # targets
-                t[range(nb), tcls[i]] = 1.0
+                smooth = False  # class label smoothing https://arxiv.org/pdf/1902.04103.pdf eqn 3
+                if smooth:
+                    e = 0.1  #  class label smoothing epsilon
+                    cp, cn = 1.0 - e, e / (model.nc - 0.99)  # class positive and negative labels
+                else:
+                    cp, cn = 1.0, 0.0
+
+                t = torch.zeros_like(ps[:, 5:]) + cn  # targets
+                t[range(nb), tcls[i]] = cp
                 lcls += BCEcls(ps[:, 5:], t)  # BCE
                 # lcls += CE(ps[:, 5:], tcls[i])  # CE