diff --git a/docs/en/advanced_tutorials/image_augmentation/ImageAugment_en.md b/docs/en/advanced_tutorials/image_augmentation/ImageAugment_en.md
index dbf2fd07bd88186f80d9f463c24bc7ad8d93b3e4..7e2a49a2a551648b2811f3fa86eefb2b593f3ca3 100644
--- a/docs/en/advanced_tutorials/image_augmentation/ImageAugment_en.md
+++ b/docs/en/advanced_tutorials/image_augmentation/ImageAugment_en.md
@@ -27,6 +27,10 @@ Compared with the above standard image augmentation methods, the researchers hav
 3. Aliasing. Perform some transformations on the image after `Batch`, such as Mixup and Cutmix.
 
 
+Visualization results of some images after augmentation are shown as follows.
+
+![](../../../images/image_aug/image_aug_samples_s_en.jpg)
+
 
 The following table shows more detailed information of the transformations.
 
diff --git a/docs/zh_CN/advanced_tutorials/image_augmentation/ImageAugment.md b/docs/zh_CN/advanced_tutorials/image_augmentation/ImageAugment.md
index 2c6fbff70113f229078c4aaee89c46b8c6ee96ba..f42eb47bddf2d53e4bebb78e0dce78bedc875c7e 100644
--- a/docs/zh_CN/advanced_tutorials/image_augmentation/ImageAugment.md
+++ b/docs/zh_CN/advanced_tutorials/image_augmentation/ImageAugment.md
@@ -4,7 +4,6 @@
 
 ![](../../../images/image_aug/main_image_aug.png)
 
-
 # 二、常用数据增广方法
 
 如果没有特殊说明，本章节中所有示例为 ImageNet 分类，并且假设最终输入网络的数据维度为：`[batch-size, 3, 224, 224]`
@@ -24,6 +23,9 @@
 2. 对`Transpose` 后的 224 的图像进行一些裁剪: CutOut，RandErasing，HideAndSeek，GridMask
 3. 对 `Batch` 后的数据进行混合: Mixup，Cutmix
 
+增广后的可视化效果如下所示。
+
+![](../../../images/image_aug/image_aug_samples_s.jpg)
 
 具体如下表所示：