MINI FAKRA Automotive Connectors MINI FAKRA 4PIN Male Connector for Cable,Mini Fakra Connector For Pcb,MINI FAKRA 1PIN Female Connector for Cable VersionA Dongguan Zhuoyuexin Automotive Electronics Co.,Ltd , https://www.zyx-fakra.com
OpenCV3.3+VS2017 development environment to build
OpenCV 3.3, released in August, introduced significant performance improvements and new features. A major highlight was the official integration of the Deep Neural Network (DNN) module into the main repository, providing deeper support for machine learning tasks. The library now supports C++11 features through the ENABLE_CXX11 macro, and includes numerous optimizations based on SSE4.x and AVX/AVX2 instruction sets. Additionally, the built-in Intel IPP version was upgraded to 2017.2, resulting in nearly a 15% performance boost according to official tests. If you're using OpenCV 3.x, upgrading is highly recommended for better performance and functionality.
Compiling OpenCV from source is straightforward, especially compared to older projects, and it offers excellent support for Visual Studio. However, if this is your first time compiling, you might find the process and various configuration options a bit confusing. While precompiled binaries are available, they may lack certain modules. Therefore, it's advisable to customize the build as much as possible to include only the components you need.
This guide assumes that you have CMake and Python (either 2.x or 3.x) already installed.
**First, prepare resources**
Download the OpenCV 3.3.0-vc14.exe file from SourceForge, which is often faster and more reliable than GitHub mirrors. You can use third-party downloaders to speed up the process.
**Second, extract the source code**
Run the downloaded executable and choose a directory to extract the files. The folder structure will look something like this:
**Third, generate the project**
Open CMake GUI, select the source directory, and configure for Visual Studio 2017 (Win64). Once the initial configuration completes, some settings may appear in red, indicating that manual adjustments are needed. Check the output for any missing libraries or dependencies. For example, if you see "Could NOT find XXX," you should either add the correct path or disable the corresponding module.
Here are a few tips:
- Since we're using OpenCV as a library, disable unnecessary options like BUILD_DOCS, BUILD_EXAMPLES, and other test-related flags.
- Enable C++11 support by checking the ENABLE_CXX11 option.
- For easier configuration and debugging, consider building the world library (BUILD_opencv_world), which combines all modules into a single .lib or .dll file. In release builds, however, it’s better to include only the modules you need to reduce the final size.
- If you don’t work with video or audio, disable modules like BUILD_opencv_video, BUILD_opencv_videoio, and related options such as WITH_GSTREAMER.