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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

You're reading from   Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA Effective techniques for processing complex image data in real time using GPUs

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789348293
Length 380 pages
Edition 1st Edition
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Author (1):
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Bhaumik Vaidya Bhaumik Vaidya
Author Profile Icon Bhaumik Vaidya
Bhaumik Vaidya
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Table of Contents (15) Chapters Close

Preface 1. Introducing CUDA and Getting Started with CUDA 2. Parallel Programming using CUDA C FREE CHAPTER 3. Threads, Synchronization, and Memory 4. Advanced Concepts in CUDA 5. Getting Started with OpenCV with CUDA Support 6. Basic Computer Vision Operations Using OpenCV and CUDA 7. Object Detection and Tracking Using OpenCV and CUDA 8. Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1 9. Deploying Computer Vision Applications on Jetson TX1 10. Getting Started with PyCUDA 11. Working with PyCUDA 12. Basic Computer Vision Applications Using PyCUDA 13. Assessments 14. Other Books You May Enjoy

Introducing CUDA and Getting Started with CUDA

This chapter gives you a brief introduction to CUDA architecture and how it has redefined the parallel processing capabilities of GPUs. The application of CUDA architecture in real-life scenarios will be demonstrated. This chapter will serve as a starting guide for software developers who want to accelerate their applications by using general-purpose GPUs and CUDA. The chapter describes development environments used for CUDA application development and how the CUDA toolkit can be installed on all operating systems. It covers how basic code can be developed using CUDA C and executed on Windows and Ubuntu operating systems.

The following topics will be covered in this chapter:

  • Introducing CUDA
  • Applications of CUDA
  • CUDA development environments
  • Installing CUDA toolkit on Windows, Linux, and macOS
  • Developing simple code, using CUDA C
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