diff --git a/models/yolo.py b/models/yolo.py
index 9179c85..e491e64 100644
--- a/models/yolo.py
+++ b/models/yolo.py
@@ -61,8 +61,9 @@ class Model(nn.Module):
 
         # Build strides, anchors
         m = self.model[-1]  # Detect()
-        m.stride = torch.tensor([64 / x.shape[-2] for x in self.forward(torch.zeros(1, ch, 64, 64))])  # forward
+        m.stride = torch.tensor([128 / x.shape[-2] for x in self.forward(torch.zeros(1, ch, 128, 128))])  # forward
         m.anchors /= m.stride.view(-1, 1, 1)
+        check_anchor_order(m)
         self.stride = m.stride
 
         # Init weights, biases
diff --git a/utils/utils.py b/utils/utils.py
index 8457643..f1f5db5 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -58,7 +58,8 @@ def check_anchors(dataset, model, thr=4.0, imgsz=640):
     print('\nAnalyzing anchors... ', end='')
     m = model.module.model[-1] if hasattr(model, 'module') else model.model[-1]  # Detect()
     shapes = imgsz * dataset.shapes / dataset.shapes.max(1, keepdims=True)
-    wh = torch.tensor(np.concatenate([l[:, 3:5] * s for s, l in zip(shapes, dataset.labels)])).float()  # wh
+    scale = np.random.uniform(0.9, 1.1, size=(shapes.shape[0], 1))  # augment scale
+    wh = torch.tensor(np.concatenate([l[:, 3:5] * s for s, l in zip(shapes * scale, dataset.labels)])).float()  # wh
 
     def metric(k):  # compute metric
         r = wh[:, None] / k[None]
@@ -77,12 +78,23 @@ def check_anchors(dataset, model, thr=4.0, imgsz=640):
             new_anchors = torch.tensor(new_anchors, device=m.anchors.device).type_as(m.anchors)
             m.anchor_grid[:] = new_anchors.clone().view_as(m.anchor_grid)  # for inference
             m.anchors[:] = new_anchors.clone().view_as(m.anchors) / m.stride.to(m.anchors.device).view(-1, 1, 1)  # loss
+            check_anchor_order(m)
             print('New anchors saved to model. Update model *.yaml to use these anchors in the future.')
         else:
             print('Original anchors better than new anchors. Proceeding with original anchors.')
     print('')  # newline
 
 
+def check_anchor_order(m):
+    # Check anchor order against stride order for YOLOv5 Detect() module m, and correct if necessary
+    a = m.anchor_grid.prod(-1).view(-1)  # anchor area
+    da = a[-1] - a[0]  # delta a
+    ds = m.stride[-1] - m.stride[0]  # delta s
+    if da.sign() != ds.sign():  # same order
+        m.anchors[:] = m.anchors.flip(0)
+        m.anchor_grid[:] = m.anchor_grid.flip(0)
+
+
 def check_file(file):
     # Searches for file if not found locally
     if os.path.isfile(file):