Hands-on GPU-accelerated computer vision with OpenCV and CUDA effective techniques for processing complex image data in real time using GPUs
Discover how CUDA computing platform allows OpenCV to handle rapidly growing computer and machine vision complex image data processing by accessing the power of GPU About This Book Practical examples to leverage the GPU processing power with OpenCV and CUDA Maximise the performance of algorithms on...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham ; Mumbai :
Packt
[2018]
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630393006719 |
| Sumario: | Discover how CUDA computing platform allows OpenCV to handle rapidly growing computer and machine vision complex image data processing by accessing the power of GPU About This Book Practical examples to leverage the GPU processing power with OpenCV and CUDA Maximise the performance of algorithms on embedded hardware platforms Work with C++ and Python libraries for GPU acceleration Who This Book Is For This book is a go-to guide for developers working with OpenCV and now want to learn how to process more complex image data by taking advantage of GPU processing. A thorough understanding of computer vision concepts and programming languages like C++ or Python is expected. What You Will Learn How to access GPU device properties and capabilities from CUDA programs know the acceleration of searching and sorting algorithms using CUDA Detect shapes like lines or circles from images using OpenCV and CUDA Object tracking and detection with algorithms using OpenCV and CUDA Process videos using different video analysis techniques on jetson TX1 Know how to access GPU device properties from PyCUDA program Get to know how Kernal execution works In Detail Computer vision is revolutionizing wide range of industries and OpenCV is the most widely chosen tool for computer vision with the ability to work in multiple programming languages. Now a days in Computer vision there is a need to process large images in real time which is difficult to handle for OpenCV on its own. This is where CUDA comes into the picture, allowing OpenCV to leverage powerful NVDIA GPUs. This book provides a detail overview on integrating OpenCV with CUDA for practical applications. It starts with explaining 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. This book covers 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 power of CUDA and GPU for accelerations. This book provides complete guide for developers using OpenCV in C++ or Python in accelerating their computer vision applications by taking hands-on approach. |
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| Descripción Física: | 1 online resource (373 pages) |
| ISBN: | 9781789343687 |
