If you already have an installation ensure that the correct workload is installed and that you have updated to the latest version. Install the latest version of Visual Studio, selecting the Desktop development with C++ workload shown in the image below. There are a couple of components you need to download and/or install before you can get started, you first need to: If you already have the OpenCV source and the required dependencies and are just looking for the CMake flags they can be found here. If you have previously built and/or are trying to manually install the Python bindings and are facing errors check out the troubleshooting Python bindings installation issues and manually installing OpenCV Python bindings sections first. If you just need the OpenCV binaries or a Python wheel which includes the CUDA modules, check OpenCV C++ CUDA builds and/or OpenCV Python CUDA wheels first to see if they are available for your desired combination of OpenCV and CUDA. Whilst the instructions can also work on older versions, this is not guaranteed so please update to the latest stable releases before raising any issues. This guide assumes you are building the latest stable release of OpenCV against the most recent CUDA dependencies. Before you begin quickly check which parts of the guide are relevant to you To see if building the OpenCV CUDA modules is suitable for your application you can get an indication of the performance boost of most functions in OpenCV CUDA Performance Comparisson (Nvidia vs Intel). If you just need the Windows libraries or a Python wheele take a look at OpenCV C++ CUDA builds and/or OpenCV Python CUDA wheels to see if there is a pre-built version suitable for your setup. The pre-built Windows libraries available for OpenCV do not include the CUDA modules, support for the Nvidia Video Codec SDK or cuDNN.
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