Desktop

该demo展示了使用opencv和face_recognition库，对图片中出现的人脸识别记录并框出的过程，可实际应用(This is a demo which implements face recognition with opencv and face_recognition libraries)

说明：  采用生成对抗网络（GAN）实现图像去模糊，用于图像的清晰化处理(The generated countermeasure network (GAN) is used to remove the blur of the image, which is used to clear the image)

C++实现OpenGL的下雨效果，非常适合学习参考！(C++ implementation of OpenGL rain effect, very suitable for study reference!)

OpenGL控件。-OpenGL controls.

说明：  PYTHON IMPLEMENTATION FOR FORD-FULKERSON ALGORITH

遗传算法解决处理路径问题 挺好的一个算法(vrp problem solved by GA)

用OpenGL画的一个苹果树林~~可当作业用-with OpenGL painting an apple trees ~ ~ can be used when operating

说明：  周志华 机器学习 机器学习是计算机科学与人工智能的重要分支领域. 本书作为该领域的入门教材，在内容上尽可能涵盖机器学习基础知识的各方面。 为了使尽可能多的读者通过本书对机器学习有所了解。 作者试图尽可能少地使用数学知识. 然而, 少量的概率、统计、代数、优化、逻辑知识似乎不可避免. 因此, 本书更适合大学三年级以上的理工科本科生和研究生, 以及具有类似背景的对机器学 习感兴趣的人士. 为方便读者, 本书附录给出了一些相关数学基础知识简介(machine learningMachine learning is an important branch of computer science and artificial intelligence. As an introductory textbook in this field, this book covers all aspects of basic knowledge of machine learning as far as possible. In order to make as many readers as possible understand machine learning through this book. The author tries to use mathematical knowledge as little as possible. However, a small amount of knowledge about probability, statistics, algebra, optimization and logic seems inevitable. Therefore, this book is more suitable for undergraduates and postgraduates of science and engineering over the third year of the University, as well as people with similar background who are interested in machine learning. For the convenience of readers, the appendix of this book gives some basic mathematical knowledge)

逆透视变换，能把有一定倾角的同一场景转换为从90度获取的场景(Inverse perspective transform, can send the same scene with a certain angle from 90 degree to get into the scene )

使用百度地图api，进行批量实现坐标的拾取(Use Baidu map API to batch realize coordinate pickup.)