diff --git a/utils/utils.py b/utils/utils.py
index a4c331a2..f21e2285 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -669,7 +669,7 @@ def coco_single_class_labels(path='../coco/labels/train2014/', label_class=43):
             shutil.copyfile(src=img_file, dst='new/images/' + Path(file).name.replace('txt', 'jpg'))  # copy images
 
 
-def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=416):  # from utils.utils import *; kmeans_targets()
+def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=512):  # from utils.utils import *; kmeans_targets()
     # Produces a list of target kmeans suitable for use in *.cfg files
     from utils.datasets import LoadImagesAndLabels
     from scipy import cluster
@@ -679,7 +679,7 @@ def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=416):  # from
     for s, l in zip(dataset.shapes, dataset.labels):
         l[:, [1, 3]] *= s[0]  # normalized to pixels
         l[:, [2, 4]] *= s[1]
-        l[:, 1:] *= img_size / max(s)  # nominal img_size for training
+        l[:, 1:] *= img_size / max(s) * random.uniform(0.99, 1.01)  # nominal img_size for training
     wh = np.concatenate(dataset.labels, 0)[:, 3:5]  # wh from cxywh
 
     # Kmeans calculation