Because the pre-built Windows libraries available for OpenCV 4.4.0 do not include the CUDA modules, or support for the Nvidia Video Codec SDK, Nvidia cuDNN, Intel Media SDK or Intel’s Math Kernel Libraries (MKL) or Intel Threaded Building Blocks (TBB) performance libraries, I have included the build instructions, below for anyone who is interested. If […]
OpenCV 4.4.0 (changelog) which is compatible with CUDA 11.0 and cuDNN 8.0 was released on 18/07/2019, see Accelerate OpenCV 4.4.0 – build with CUDA and python bindings, for the updated guide. Because the pre-built Windows libraries available for OpenCV 4.3.0 do not include the CUDA modules, or support for the Nvidia Video Codec SDK, Nvidia […]
OpenCV 4.4.0 (changelog) which is compatible with CUDA 11.0 and cuDNN 8.0 was released on 18/07/2019, see Accelerate OpenCV 4.4.0 – build with CUDA and python bindings, for the updated guide. Because the pre-built Windows libraries available for OpenCV 4.2.0 do not include the CUDA modules, or support for the Nvidia Video Codec SDK, Nvidia […]
Overview¶ Since Aug 2018 the OpenCV CUDA API has been exposed to python (for details of the API call’s see test_cuda.py). To get the most from this new functionality you need to have a basic understanding of CUDA (most importantly that it is data not task parallel) and its interaction with OpenCV. Below I have […]
OpenCV 4.4.0 (changelog) which is compatible with CUDA 11.0, has a CUDA DNN backend compatible with cuDNN 8.0 and improved python CUDA bindings was released on 18/07/2019, see Accelerate OpenCV 4.4.0 – build with CUDA and python bindings, for the updated guide. Because the pre-built Windows libraries available for OpenCV 4.1.0 do not include the […]
OpenCV 4.4.0 (changelog) which is compatible with CUDA 11.0, has a CUDA DNN backend compatible with cuDNN 8.0 and improved python CUDA bindings was released on 18/07/2019, see Accelerate OpenCV 4.4.0 – build with CUDA and python bindings, for the updated guide. Because the pre-built Windows libraries available for OpenCV 4.0.0 do not include the […]
In this post I am going to use the OpenCV’s performance tests to compare the CUDA and CPU implementations. The idea, is to get an indication of which OpenCV and/or Computer Vision algorithms, in general, benefit the most from GPU acceleration, and therefore, under what circumstances it might be a good idea to invest in […]
OpenCV 4.0 which is compatible with CUDA 10.0 and the latest version of Visual Studio 2017 was released on 18/11/2018, go to Build OpenCV 4.0.0 with CUDA 10.0 and Intel MKL +TBB in Windows, for the updated guide. Because the pre-built Windows libraries available for OpenCV 3.4 do not include the CUDA modules, or the […]
OpenCV 3.4 which is compatible with CUDA 9.1 and Visual Studio 2017 was released on 23/12/2017, go to Building OpenCV 3.4 on Windows with CUDA 9.1, Intel MKL+TBB, for the updated guide. Because the pre-built Windows libraries available for OpenCV v3.3 do not include the CUDA modules, I have included the build […]
The below instructions should have you set up with both Keras 1.2.2 and theano 0.9 on Windows 8.1 in 30 minutes or less, depending on the speed of your internet connection. I can confirm that this set up is suitable for all the lessons in the fantastic Practical Deep Learning For Coders, Part 1, course. […]