diff --git a/utils/utils.py b/utils/utils.py
index 59447312..99eb38be 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -388,10 +388,6 @@ def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
                     dc = dc[1:][iou < nms_thres]  # remove ious > threshold
 
                 # Image      Total          P          R        mAP
-                #    32       5000      0.633      0.579      0.568
-                #    64       5000      0.619      0.579      0.568
-                #    96       5000      0.652      0.622      0.613
-                #   128       5000      0.651      0.625      0.617
                 #  5000       5000      0.627      0.593      0.584
 
             elif nms_style == 'AND':  # requires overlap, single boxes erased
@@ -406,16 +402,15 @@ def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
                     iou = bbox_iou(dc[:1], dc[0:])  # iou with other boxes
                     i = iou > nms_thres
 
-                    weights = (dc[i, 4:5] * dc[i, 5:6]) ** 0.5
+                    weights = (dc[i, 4:5] * dc[i, 5:6]) ** 2
                     dc[0, :4] = (weights * dc[i, :4]).sum(0) / weights.sum()
                     det_max.append(dc[:1])
                     dc = dc[iou < nms_thres]
 
                 # Image      Total          P          R        mAP
-                #    32       5000      0.635      0.581      0.569
-                #    64       5000       0.63      0.591      0.578
-                #    96       5000       0.66       0.63       0.62
-                #   128       5000      0.657      0.631      0.622
+                #  4964       5000      0.632      0.597      0.588  # normal
+                #  4964       5000      0.632      0.597      0.588  # squared
+                #  4964       5000      0.631      0.597      0.588  # sqrt
 
             if len(det_max) > 0:
                 det_max = torch.cat(det_max)