Update readme.md

Author: yjcyxky

readme.md

@@ -2,7 +2,7 @@
 
 ## Description
 
-sc-MTOP is an analysis framework based on deep learning and computational pathology. It consists of two steps: 1) Nuclear segmentation and classification; 2) Feature extraction. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. We have established a [demo](http://101.132.124.14/#/dashboard) website to show the functions.
+sc-MTOP is an analysis framework based on deep learning and computational pathology. It consists of two steps: 1) Nuclear segmentation and classification; 2) Feature extraction. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. We have established a [demo](http://sc-mtop.biosolver.cn/) website to show the functions.
 
 This is the official pytorch implementation of sc-MTOP. Note that only the Nuclear segmentation and classification step supports batch processing.
 
@@ -74,4 +74,4 @@ python main.py feature --json_path='./output/json/Example001.json' --wsi_path='.
 visualization
 ```
 python main.py visual --feature_path='./feature/sample' --wsi_path='./wsi/sample.ndpi' --xml_path='./xml/sample.xml'
-```
+```