OpenCV is the most widely used open source toolkit in computer vision, based on C/C, supports Linux/Windows/MacOS/Android/iOS, and provides interfaces in languages such as Python, Matlab, and Java. OpenCV released version 2.0 in 2010, adding a very complete C-plus interface, and the version from 2.0 is very user-savvy and is still being maintained and updated. OpenCV 3 was officially released in 2015, adding more algorithms, more performance optimization and a cleaner API, as well as enhanced GPU support, which has now been used in many research institutions and commercial companies. OpenCV3 offers more functionality and more convenience than OpenCV2. However, considering the compatibility with the deep learning framework, as well as the difficulty of installing, this part of the OpenCV2 is the main introduction.
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OpenCV是计算机视觉领域应用最广泛的开源工具包，基于C/C++，支持Linux/Windows/MacOS/Android/iOS，并提供了Python，Matlab和Java等语言的接口。2010年OpenCV发布了2.0版本，添加了非常完备的C++接口，从2.0开始的版本非常用户非常庞大，至今仍在维护和更新。2015年OpenCV 3正式发布，除了架构的调整，还加入了更多算法，更多性能的优化和更加简洁的API，另外也加强了对GPU的支持，现在已经在许多研究机构和商业公司中应用开来。相比OpenCV2，OpenCV3提供了更强的功能和更多方便的特性。不过考虑到和深度学习框架的兼容性，以及上手安装的难度，这部分先以OpenCV2为主进行介绍。
CSsaan/Python-OpenCV2
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OpenCV是计算机视觉领域应用最广泛的开源工具包，基于C/C++，支持Linux/Windows/MacOS/Android/iOS，并提供了Python，Matlab和Java等语言的接口。2010年OpenCV发布了2.0版本，添加了非常完备的C++接口，从2.0开始的版本非常用户非常庞大，至今仍在维护和更新。2015年OpenCV 3正式发布，除了架构的调整，还加入了更多算法，更多性能的优化和更加简洁的API，另外也加强了对GPU的支持，现在已经在许多研究机构和商业公司中应用开来。相比OpenCV2，OpenCV3提供了更强的功能和更多方便的特性。不过考虑到和深度学习框架的兼容性，以及上手安装的难度，这部分先以OpenCV2为主进行介绍。
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