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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

Product type Book
Published in Sep 2018
Publisher Packt
ISBN-13 9781789348293
Pages 380 pages
Edition 1st Edition
Languages
Author (1):
Bhaumik Vaidya Bhaumik Vaidya
Profile icon Bhaumik Vaidya
Toc

Table of Contents (15) Chapters close

Preface 1. Introducing CUDA and Getting Started with CUDA 2. Parallel Programming using CUDA C 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

Basic Computer Vision Applications Using PyCUDA

In the previous chapter, we saw important programming concepts related to PyCUDA. We also learned how to develop some programs in PyCUDA using these programming concepts. This chapter will build on this knowledge and we will use PyCUDA for developing basic image processing and computer vision applications. The parallel programming concepts of atomic operations and shared memory will also be explained in detail. The histogram of an image conveys important information related to the contrast of an image and it can also be used as an image feature for computer vision tasks. The program to calculate the histogram using PyCUDA will be explained in detail in this chapter. Other basic computer vision applications, such as the conversion of color spaces, image addition, and image inversion using PyCUDA, will also be described.

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