OpenCV is a powerful library for computer vision applications. The library is capable of leveraging massively parallel and heterogeneous computing platforms simply and easily. OpenCV contains more than 2,500 different algorithms related to computer vision, image processing, motion analysis, and more.
There are bindings available for many popular languages, including C++, Java, Python, and MATLAB, among others. For detailed usage information, please refer to the official documentation. In addition, a wealth of official tutorials are available to help you get started with OpenCV.
Using OpenCV on RCC Resources
OpenCV is available on the Spear and HPC systems. It does not require a module to be loaded before using it. However, if you wish to use its parallel capabilities, first you will need to load one of the MPI modules. These can be found in our software catalog.
Once your code is set up, it can be compiled and run using the standard workflow with CMake and GCC. Both are available on RCC resources. A description of the standard workflow can be found on the OpenCV tutorials page.