diff --git a/README.md b/README.md
index 2946c71..e86a56a 100644
--- a/README.md
+++ b/README.md
@@ -1,17 +1,25 @@
 # MobileFaceNet Face Landmark Detecter
 
-*authors: David Wang*
+*author: David Wang*
 
 
-## Desription
+<br />
+
+
+
+## Description
 
 [MobileFaceNets](https://arxiv.org/pdf/1804.07573) is a class of extremely efficient CNN models to extract 68 landmarks from a facial image, which use less than 1 million parameters and are specifically tailored for high-accuracy real-time face verification on mobile and embedded devices. This repo is an adaptation from [cuijian/pytorch_face_landmark](https://github.com/cunjian/pytorch_face_landmark).
 
+
+<br />
+
+
 ## Code Example
 
 Extract facial landmarks from './img1.jpg'. 
 
-*Write the pipeline in simplified style*:
+*Write the pipeline in simplified style:*
 
 ```python
 import towhee
@@ -31,12 +39,17 @@ import towhee
 towhee.glob['path']('./img1.jpg') \
   .image_decode.cv2['path', 'img']() \
   .face_landmark_detection.mobilefacenet['img', 'landmark']() \
-  .select('img','landmark') \
+  .select['img','landmark']() \
   .show()
 ```
 
 <img src="https://towhee.io/face-landmark-detection/mobilefacenet/raw/branch/main/result.png" alt="result1" style="height:20px;"/>
 
+
+<br />
+
+
+
 ## Factory Constructor
 
 Create the operator via the following factory method
@@ -51,13 +64,18 @@ Create the operator via the following factory method
 
 ​  supported types: `bool`, default is True, using pretrained weights.
 
+
+<br />
+
+
+
 ## Interface
 
 An image embedding operator takes an image as input. it extracts the embedding back to ndarray.
 
 **Parameters:**
 
-​	***img***: *towhee.types.Image (a sub-class of numpy.ndarray)*
+​	***img:*** *towhee.types.Image (a sub-class of numpy.ndarray)*
 
 ​	The input image.