update compute_loss()

utils/utils.py

@@ -437,7 +437,8 @@ def compute_loss(p, targets, model):  # predictions, targets, model
         BCEcls, BCEobj = FocalLoss(BCEcls, g), FocalLoss(BCEobj, g)
 
     # per output
-    nt = 0  # targets
+    nt = 0  # number of targets
+    np = len(p)  # number of outputs
     balance = [1.0, 1.0, 1.0]
     for i, pi in enumerate(p):  # layer index, layer predictions
         b, a, gj, gi = indices[i]  # image, anchor, gridy, gridx
@@ -470,7 +471,7 @@ def compute_loss(p, targets, model):  # predictions, targets, model
 
         lobj += BCEobj(pi[..., 4], tobj) * balance[i]  # obj loss
 
-    s = 3 / (i + 1)  # output count scaling
+    s = 3 / np  # output count scaling
     lbox *= h['giou'] * s
     lobj *= h['obj'] * s
     lcls *= h['cls'] * s
@@ -517,7 +518,6 @@ def build_targets(p, targets, model):
                 j, k = ((gxy % 1. < g) & (gxy > 1.)).T
                 a, t = torch.cat((a, a[j], a[k]), 0), torch.cat((t, t[j], t[k]), 0)
                 offsets = torch.cat((z, z[j] + off[0], z[k] + off[1]), 0) * g
-
             elif style == 'rect4':
                 j, k = ((gxy % 1. < g) & (gxy > 1.)).T
                 l, m = ((gxy % 1. > (1 - g)) & (gxy < (gain[[2, 3]] - 1.))).T