Introduction

OpenCV is a powerful library for Computer Vision.  The library is capable of leveraging massively parallel and heterogenous computing platforms simply and easily.  OpenCV contains more than 2500 different algorithms related to Computer Vision, Image Processing and Motion Analysis and more.  There are bindings for many of the popular languages available including C++, Java, Python and MATLAB among others.  OpenCV is also completely cross-platform and is compatible with Linux, Windows, Mac and even the Android mobile platform.   For a detailed description and details of the inner workings of the library, please refer to the Website and the Documentation. In addition, the website has a number of useful Tutorials available to help you get started with OpenCV.

Using OpenCV on RCC Systems

OpenCV is available on the Spear and HPC Systems. It does not require a module to be loaded in order to use on it's own, however, if you wish to use it's parallel capabilities, you will need to load one of the MPI modules we have available. These can be found on our Software Listing. Once your code is set up, it can be compiled and run using the standard work-flow described in the OpenCV Tutorials using CMake and GCC, both of which are available on our systems.

For further information and very detailed tutorials, please see the OpenCV Documentation or the OpenCV Tutorials.