update readme format.

Signed-off-by: wxywb <xy.wang@zilliz.com>

README.md

@@ -3,11 +3,18 @@
 *author: David Wang*
 
 
+<br />
 
-## Desription
+
+
+## Description
 
 This operator extracts features for image with [DOLG](https://arxiv.org/abs/2108.02927) which has special design for image retrieval task. It integrates local and global information inside images into compact image representations. This operator is an adaptation from [dongkyuk/DOLG-pytorch](https://github.com/dongkyuk/DOLG-pytorch).
 
+
+<br />
+
+
 ## Code Example
 
 Load an image from path './towhee.jpg' to generate an image embedding. 
@@ -33,11 +40,16 @@ import towhee
 towhee.glob['path']('./towhee.jpg') \
       .image_decode.cv2['path', 'img']() \
       .image_embedding.dolg['img', 'vec'](img_size=512, input_dim=3, hidden_dim=1024, output_dim=2048) \
-      .select('img', 'vec') \
+      .select['img', 'vec']() \
       .show()
 ```
 <img src="https://towhee.io/image-embedding/dolg/raw/branch/main/result2.png" alt="result2" style="height:60px;"/>
 
+
+<br />
+
+
+
 ## Factory Constructor
 
 Create the operator via the following factory method
@@ -46,22 +58,27 @@ Create the operator via the following factory method
 
 **Parameters:**
 
-​   ***img_size***: *int*
+​   ***img_size:*** *int*
 
 ​   Scaled input image size to extract embedding. The higher resolution would generate the more discriminateive feature but cost more time to calculate.  
 
-​   ***input_dim***: *int*
+​   ***input_dim:*** *int*
 
 ​   The input dimension of DOLG module (equals pretrained cnn output dimension). 
 
-​   ***hidden_dim***: *int*
+​   ***hidden_dim:*** *int*
 
 ​   The hidden dimension size, local feature branch output dimension. 
 
-​   ***output_dim***: *int*
+​   ***output_dim:*** *int*
 
 ​   The output dimsion size, same as embedding size.
 
+
+<br />
+
+
+
 ## Interface
 
 An image embedding operator takes a [towhee image](link/to/towhee/image/api/doc) as input.
@@ -70,13 +87,13 @@ It uses the pre-trained model specified by model name to generate an image embed
 
 **Parameters:**
 
-​	***img***: *towhee.types.Image (a sub-class of numpy.ndarray)* 
+​	***img:*** *towhee.types.Image (a sub-class of numpy.ndarray)* 
 
 ​	The decoded image data in towhee.types.Image (numpy.ndarray).
 
 
 
-**Returns**: *numpy.ndarray*
+**Returns:** *numpy.ndarray*
 
 ​   The image embedding extracted by model.