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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

Basic computer vision operations using PyCUDA

This section will demonstrate the use of PyCUDA in developing simple computer vision applications. Images in Python are nothing but two- or three-dimensional numpy arrays, hence working and manipulating images in PyCUDA is similar to working with multidimensional arrays. This section will give you a basic idea of developing a simple application that you can utilize in developing complex computer vision applications using PyCUDA.

Color space conversion in PyCUDA

Most computer vision algorithms work on grayscale images, so there is a need for converting a color image captured from a camera to a grayscale image. Though OpenCV provides an inbuilt function to do this operation, it can...

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