Preface

Computer vision is revolutionizing a wide range of industries and OpenCV is the most widely chosen tool for computer vision with the ability to work in multiple programming languages. Nowadays, there is a need to process large images in real time in computer vision which is difficult to handle for OpenCV on its own. In this Graphics Processing Unit (GPU) and CUDA can help. So this book provides a detailed overview on integrating OpenCV with CUDA for practical applications. It starts with explaining the programming of GPU with CUDA which is essential for computer vision developers who have never worked with GPU. Then it explains OpenCV acceleration with GPU and CUDA by taking some practical examples. When computer vision applications are to be used in real life scenarios then it needs to deployed on embedded development boards. This book covers the deployment of OpenCV applications on NVIDIA Jetson Tx1 which is very popular for computer vision and deep learning applications. The last part of the book covers the concept of PyCUDA which can be used by Computer vision developers who are using OpenCV with Python. PyCUDA is a python library which leverages the power of CUDA and GPU for accelerations. This book provides a complete guide for developers using OpenCV in C++ or Python in accelerating their computer vision applications by taking a hands on approach.