diff --git a/models.py b/models.py
index 25ac4dcf..ca5f07d2 100755
--- a/models.py
+++ b/models.py
@@ -182,7 +182,7 @@ class YOLOLayer(nn.Module):
             loss = lx + ly + lw + lh + lconf + lcls
 
             # Sum False Positives from unassigned anchors
-            i = torch.sigmoid(pred_conf[~mask]) > 0.9
+            i = torch.sigmoid(pred_conf[~mask]) > 0.5
             if i.sum() > 0:
                 FP_classes = torch.argmax(pred_cls[~mask][i], 1)
                 FPe = torch.bincount(FP_classes, minlength=self.nC).float().cpu()  # extra FPs
diff --git a/utils/utils.py b/utils/utils.py
index 95abacce..08692c5f 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -282,9 +282,9 @@ def build_targets(pred_boxes, pred_conf, pred_cls, target, anchor_wh, nA, nC, nG
             pconf = torch.sigmoid(pred_conf[b, a, gj, gi]).cpu()
             iou_pred = bbox_iou(tb, pred_boxes[b, a, gj, gi].cpu())
 
-            TP[b, i] = (pconf > 0.9) & (iou_pred > 0.5) & (pcls == tc)
-            FP[b, i] = (pconf > 0.9) & (TP[b, i] == 0)  # coordinates or class are wrong
-            FN[b, i] = pconf <= 0.9  # confidence score is too low (set to zero)
+            TP[b, i] = (pconf > 0.5) & (iou_pred > 0.5) & (pcls == tc)
+            FP[b, i] = (pconf > 0.5) & (TP[b, i] == 0)  # coordinates or class are wrong
+            FN[b, i] = pconf <= 0.5  # confidence score is too low (set to zero)
 
     return tx, ty, tw, th, tconf, tcls, TP, FP, FN, TC