diff --git a/models/common.py b/models/common.py
index 9764d4c3a6c0..689aa0f3ed7c 100644
--- a/models/common.py
+++ b/models/common.py
@@ -223,18 +223,18 @@ def forward(self, x):
         return non_max_suppression(x[0], conf_thres=self.conf, iou_thres=self.iou, classes=self.classes)
 
 
-class autoShape(nn.Module):
+class AutoShape(nn.Module):
     # input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS
     conf = 0.25  # NMS confidence threshold
     iou = 0.45  # NMS IoU threshold
     classes = None  # (optional list) filter by class
 
     def __init__(self, model):
-        super(autoShape, self).__init__()
+        super(AutoShape, self).__init__()
         self.model = model.eval()
 
     def autoshape(self):
-        print('autoShape already enabled, skipping... ')  # model already converted to model.autoshape()
+        print('AutoShape already enabled, skipping... ')  # model already converted to model.autoshape()
         return self
 
     @torch.no_grad()
diff --git a/models/yolo.py b/models/yolo.py
index 314fd806f5e7..06b80032d3d3 100644
--- a/models/yolo.py
+++ b/models/yolo.py
@@ -215,9 +215,9 @@ def nms(self, mode=True):  # add or remove NMS module
             self.model = self.model[:-1]  # remove
         return self
 
-    def autoshape(self):  # add autoShape module
-        logger.info('Adding autoShape... ')
-        m = autoShape(self)  # wrap model
+    def autoshape(self):  # add AutoShape module
+        logger.info('Adding AutoShape... ')
+        m = AutoShape(self)  # wrap model
         copy_attr(m, self, include=('yaml', 'nc', 'hyp', 'names', 'stride'), exclude=())  # copy attributes
         return m