From 5dbcba94ca8ee9b5103ed0aa5be13b23520444b2 Mon Sep 17 00:00:00 2001
From: yangco-le <yanglily@sjtu.edu.cn>
Date: Mon, 15 Apr 2024 22:34:41 +0800
Subject: [PATCH] update: readme

---
 README.md | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index 66022fe..a258ec2 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 <img src="docs/assets/ml4co-kit-logo.png" alt="ML4CO-Kit" width="800"/>
 
-
+[![PyPi version](https://badgen.net/pypi/v/data4co/)](https://pypi.org/pypi/data4co/)[![PyPI pyversions](https://img.shields.io/badge/dynamic/json?color=blue&label=python&query=info.requires_python&url=https%3A%2F%2Fpypi.org%2Fpypi%2Fdata4co%2Fjson)](https://pypi.python.org/pypi/data4co/)[![Downloads](https://static.pepy.tech/badge/data4co)](https://pepy.tech/project/data4co)[![GitHub stars](https://img.shields.io/github/stars/Thinklab-SJTU/ML4CO-Kit.svg?style=social&label=Star&maxAge=8640)](https://GitHub.com/Thinklab-SJTU/ML4CO-Kit/stargazers/) 
 
 `ML4CO-Kit` is a in-development toolkit for machine learning practices on combinatorial optimization problems, which is a by-product of our research for a unified modular framework that integrates existing ML4CO practices, minimizing disparities among methods and supporting the investigations via in-depth analysis and transparent ablation. 
 
@@ -172,11 +172,12 @@ draw_tsp_solution(
 )
 ```
 
-<details>
-<summary>Click to view the drawing results</summary>
+Visualization Results:
+
+<p>
 <img src="docs/assets/kroA150_problem.png" width="35%" alt="" />
 <img src="docs/assets/kroA150_solution.png" width="35%" alt="" />
-</details>
+</p>
 
 #### MIS
 
@@ -200,11 +201,12 @@ draw_mis_solution(
 )
 ```
 
-<details>
-<summary>Click to view the drawing results</summary>
+Visualization Results:
+
+<p>
 <img src="docs/assets/mis_problem.png" width="35%" alt="" />
 <img src="docs/assets/mis_solution.png" width="35%" alt="" />
-</details>
+</p>
 
 ### Develop ML4CO Algorithms