diff --git a/README.md b/README.md
index 74bd956..19da8c2 100644
--- a/README.md
+++ b/README.md
@@ -20,30 +20,20 @@ This operator detects faces in the images by using [RetinaFace](https://arxiv.or
 
 Load an image from path './turing.png' and use the pre-trained RetinaFace model to generate face bounding boxes and confidence scores. 
 
- *Write the pipeline in simplified style:*
+*Write a pipeline with explicit inputs/outputs name specifications:*
 
 ```python
-import towhee
+from towhee.dc2 import pipe, ops, DataCollection
 
-towhee.glob('turing.png') \
-  .image_decode() \
-  .face_detection.retinaface() \
-  .show()
-
-```
-<img src="https://towhee.io/face-detection/retinaface/raw/branch/main/result1.png" alt="result1" style="height:20px;"/>
-
-*Write a same pipeline with explicit inputs/outputs name specifications:*
-
-```python
-import towhee
-
-towhee.glob['path']('turing.png') \
-  .image_decode['path', 'img']() \
-  .face_detection.retinaface['img', ('bbox','score')]() \
-  .image_crop[('img', 'bbox'), 'crop']()\
-  .select('img', 'crop', 'bbox', 'score').show()
+p = (
+    pipe.input('path')
+        .map('path', 'img', ops.image_decode())
+        .map('img', ('bbox','score'), ops.face_detection.retinaface())
+        .map(('img', 'bbox'),'crop', ops.image_crop())
+        .output('img', 'crop', 'bbox', 'score')
+)
 
+DataCollection(p('turing.png')).show()
 ```
 
 <img src="https://towhee.io/face-detection/retinaface/raw/branch/main/result2.jpg" alt="result2" style="height:60px;"/>