这是一个基于CUDA加速的快速立体匹配库，它的核心是SemiglobalMatching（SGM）算法，它不仅在时间效率上要远远优于基于CPU的常规SGM，而且占用明显更少的内存，这意味着它不仅可以在较低分辨率（百万级）图像上达到实时的帧率，且完全具备处理千万级甚至更高量级图像的能力。
I'm coding some stereo matching algorithms. If you are interested in this work, please follow me, I hope my work is helpful to you!
我正在编写一些立体匹配算法，并免费开源。如果你对此工作感兴趣，欢迎关注我，希望它们能够给你的科研或工作提供一些帮助！
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李博您好！看了Readme中您最近研究工作的效果，令我印象深刻。
我有个问题，诸如“数据2”中在Kitti 双目图像上计算得到的结果，其速率“95fps”是在何种硬件设备（CPU&GPU）上得到的呢？
希望我的问题能够得到李博的解答。非常感谢！
博士您好！在尝试测试您代码的时候出现了单像对测试无法显示视差图的问题，恳请指导！
博士您好，我们在调试运行时，如何在#Load all image pairs in specified folder更改vector str_paths所指定测试数据集文件夹
你好，请问你的这个算法库的时效性是你设置的吗？ 续期怎么续期呢？谢谢
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