VS2017平台，cmake编译的opencv3.2以及contrib库，懒人必备！

编译opencv3.2时，当出现ippicv_windows_20151201报错时，下载并替换。..//自己相应的文件夹下opencv3.2\opencv\sources\3rdparty\ippicv\路径下文件

opencv3.4.3+contrib3.4.3.zip

基于VS2015环境和openCV环境下实现原始影像到目标影像的颜色转换，此操作是在lab颜色空间对两者计算得到

环境opencv3.4.1和vs2017，语言c++,基于人工神经网络ANN的喷码字符识别

Mastering OpenCV 3 - Second Edition by Daniel Lélis Baggio English | 4 May 2017 | ASIN: B01N7G0BKE | 250 Pages | AZW3 | 4.82 MB Key Features Updated for OpenCV 3, this book covers new features that will help you unlock the full potential of OpenCV 3 Written by a team of 7 experts, each chapter explores a new aspect of OpenCV to help you make amazing computer-vision aware applications Each chapter is a tutorial for an entire project from start to finish, showing you how to apply OpenCV to solve complete problems Book Description As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision. This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You’ll learn how to make AI that can remember and use neural networks to help your applications learn. By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3. What you will learn Execute basic image processing operations and cartoonify an image Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video Use OpenCV 3’s new 3D visualization framework to illustrate the 3D scene geometry Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks Train and predict pattern-recognition algorithms to decide whether an image is a number plate Use POSIT for the six degrees of freedom head pose Train a face recognition database using deep learning and recognize faces from that database

Mastering OpenCV 3, Second Edition, Get hands-on with practical Computer Vision using OpenCV 3. Second edition: April 2017

源代码

本代码提供了一个将多个字符图片用SVM进行分类的Demo，另外使用的库为OpenCV3.4.0，在OpenCV3.x的版本上应该都可以使用。其中附带训练数据和测试数据，只需要下载，用vs2015打开并执行即可~

opencv3+python人脸检测和识别 完整项目 识别视频《欢乐颂》中人物