Su'S Blog

新特性

最近OpenCV发布了全新的OpenCV4.0 alpha版 （下载地址 ~ https://github.com/opencv/opencv/archive/4.0.0-alpha.zip ）

根据其在官网上的说明，4.0是在3.4之上发布的全新版本，对3.4进行了优化，并修复了其中存在的若干BUG。

1. ONNX parser has been added to OpenCV DNN module. It supports various classification networks, such as AlexNet, Inception v2, Resnet, VGG etc. The tiny YOLO v2 object detection network is also partially supported.
2. A few other notable DNN improvements:
   Mask RCNN support and the example
   Faster object detection when using Intel Inference Engine (a part of Intel OpenVINO)
   Several stability improvements in the OpenCL backend.
3. Fast QR code detector (~80FPS @ 640x480 resolution on Core i5 desktop). By 4.0 gold we plan to add the QR code decoder as well, so that we have a complete solution.
4. Constantly expanding set of SSE4-, AVX2- and NEON-optimized kernels via so called “wide universal intrinsics”.

除此之外，OpenCV4.0 Alpha 还有许多新的特性。

1. OpenCV is C++11 library now and it requires C++11 compliant compiler. Therefore, some nice features like parallel_for with lambda functions, convenient iteration over cv::Mat, initialization of cv::Mat by listing its elements etc. are available by default.
2. The standard std::string and std::shared_ptr replaced hand-crafted cv::String and cv::Ptr. Our parallel_for can now use the pool of std::threads as the backend.
3. The legacy C API from OpenCV 1.x (using CvMat, IplImage, etc.) is partially excluded; the cleanup should mostly be finished by OpenCV 4.0 gold.
4. Added basic FP16 support (the new CV_16F type has been added).
5. CPU- and GPU-accelerated KinFu live 3d dense reconstruction algorithm has been included into opencv_contrib.
6. HPX parallel backend (thanks to Jakub Golinowski)
7. The new chessboard detector (thanks to Alexander Duda)

在OpenCV 4.0 Alpha 中共提供了85个补丁，括来自OpenCV 3.4分支的28个大规模合并请求

编译和安装

Opencv4.0的编译和安装并没有什么变化，和其他版本的OpenCV一样，首先使用cmake配合make对源代码进行完成编译，然后完成安装到所需的目录下面即可。