Search  for anything...
NA

Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective techniques for processing complex image data in real time using GPUs

  • Based on 18 reviews
Condition: New
Checking for product changes

Buy Now, Pay Later


As low as $7 / mo
  • – 4-month term
  • – No impact on credit
  • – Instant approval decision
  • – Secure and straightforward checkout

Ready to go? Add this product to your cart and select a plan during checkout. Payment plans are offered through our trusted finance partners Klarna, PayTomorrow, Affirm, Afterpay, Apple Pay, and PayPal. No-credit-needed leasing options through Acima may also be available at checkout.

Learn more about financing & leasing here.

Selected Option

Free shipping on this product

This item is eligible for return within 30 days of receipt

To qualify for a full refund, items must be returned in their original, unused condition. If an item is returned in a used, damaged, or materially different state, you may be granted a partial refund.

To initiate a return, please visit our Returns Center.

View our full returns policy here.


Availability: In Stock.
Fulfilled by Amazon

Arrives Friday, Nov 8
Order within 14 hours and 21 minutes
Available payment plans shown during checkout

Format: Kindle


Description

Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPUKey FeaturesExplore examples to leverage the GPU processing power with OpenCV and CUDAEnhance the performance of algorithms on embedded hardware platformsDiscover C++ and Python libraries for GPU accelerationBook DescriptionComputer vision has been revolutionizing a wide range of industries, and OpenCV is the most widely chosen tool for computer vision with its ability to work in multiple programming languages. Nowadays, 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 detailed overview of integrating OpenCV with CUDA for practical applications. To start with, you’ll understand GPU programming with CUDA, an essential aspect for computer vision developers who have never worked with GPUs. You’ll then move on to exploring OpenCV acceleration with GPUs and CUDA by walking through some practical examples.Once you have got to grips with the core concepts, you’ll familiarize yourself with deploying OpenCV applications on NVIDIA Jetson TX1, which is popular for computer vision and deep learning applications. The last chapters of the book explain PyCUDA, a Python library that leverages the power of CUDA and GPUs for accelerations and can be used by computer vision developers who use OpenCV with Python.By the end of this book, you’ll have enhanced computer vision applications with the help of this book's hands-on approach.What you will learnUnderstand how to access GPU device properties and capabilities from CUDA programsLearn how to accelerate searching and sorting algorithmsDetect shapes such as lines and circles in imagesExplore object tracking and detection with algorithmsProcess videos using different video analysis techniques in Jetson TX1Access GPU device properties from the PyCUDA programUnderstand how kernel execution worksWho this book is forThis book is a go-to guide for you if you are a developer working with OpenCV and want to learn how to process more complex image data by exploiting GPU processing. A thorough understanding of computer vision concepts and programming languages such as C++ or Python is expected.Table of ContentsIntroduction to CUDA and Getting Started with CUDA Parallel programming using CUDA CThreads,Synchronization and MemoryAdvanced concepts in CUDA Getting started with OpenCV with CUDA support Basic computer vision Operations using OpenCV and CUDA Object detection and tracking using OpenCV and CUDA Introduction to Jetson Tx1 development board and installing OpenCV on Jetson TX1Deploying computer vision applications on Jetson TX1 Getting started with PyCUDA Working with PyCUDA Basic Computer vision application using PyCUDA Read more

Publisher ‏ : ‎ Packt Publishing; 1st edition (September 26, 2018)


Publication date ‏ : ‎ September 26, 2018


Language ‏ : ‎ English


File size ‏ : ‎ 18174 KB


Text-to-Speech ‏ : ‎ Enabled


Screen Reader ‏ : ‎ Supported


Enhanced typesetting ‏ : ‎ Enabled


X-Ray ‏ : ‎ Not Enabled


Word Wise ‏ : ‎ Not Enabled


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Friday, Nov 8

Yes, absolutely! You may return this product for a full refund within 30 days of receiving it.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

  • Klarna Financing
  • Affirm Pay in 4
  • Affirm Financing
  • Afterpay Financing
  • PayTomorrow Financing
  • Financing through Apple Pay
Leasing options through Acima may also be available during checkout.

Learn more about financing & leasing here.

Top Amazon Reviews


  • A Worthy Introduction
The book delivers a detailed introduction to CUDA and OpenCV on the Jetson Tx1 that is also applicable to other Nvidia GPUs.
Reviewed in the United States on October 24, 2018 by Force Commander

  • Highly effective Introduction to OpenCV supported by CUDA
I was looking for just this kind of concise introduction to Image analysis on several target areas. The documentation for combining these two technologies is sparse to say the least and this book not only had a precise introduction but also several detailed examples. I now know how to proceed with the object recognition that I was looking to apply to silicon disk defect analysis, but I also know how to speed it up by several hundred percent. I have several department managers in mind that I would love to tantalize with this information. This book should make it easier to make better technology for Computer Vision applications an I wish all the readers more success by reading it. ... show more
Reviewed in the United States on February 28, 2020 by Robin T. Wernick

Can't find a product?

Find it on Amazon first, then paste the link below.