Book Image

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

By : Bhaumik Vaidya
Book Image

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

By: Bhaumik Vaidya

Overview of this book

Computer 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.

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Table of Contents (15 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Introducing CUDA and Getting Started with CUDA
Introducing CUDA and Getting Started with CUDA
Technical requirements
Introducing CUDA
CUDA applications
CUDA development environment
Installing the CUDA toolkit on all operating systems
A basic program in CUDA C
Summary
Questions
2
Parallel Programming using CUDA C
Parallel Programming using CUDA C
Technical requirements
CUDA program structure
Executing threads on a device
Accessing GPU device properties from CUDA programs
Vector operations in CUDA
Parallel communication patterns
Summary
Questions
3
Threads, Synchronization, and Memory
Threads, Synchronization, and Memory
Technical requirements
Threads
Memory architecture
Thread synchronization
Constant memory
Texture memory
Dot product and matrix multiplication example
Summary
Questions
4
Advanced Concepts in CUDA
Advanced Concepts in CUDA
Technical requirements
Performance measurement of CUDA programs
Error handling in CUDA
Performance improvement of CUDA programs
CUDA streams
Acceleration of sorting algorithms using CUDA
Image processing using CUDA
Summary
Questions
5
Getting Started with OpenCV with CUDA Support
Getting Started with OpenCV with CUDA Support
Technical requirements
Introduction to image processing and computer vision
Introduction to OpenCV
Installation of OpenCV with CUDA support
Working with images in OpenCV
Working with videos in OpenCV
Basic computer vision applications using the OpenCV CUDA module
Performance comparison of OpenCV applications with and without CUDA support
Summary
Questions
6
Basic Computer Vision Operations Using OpenCV and CUDA
Basic Computer Vision Operations Using OpenCV and CUDA
Technical requirements
Accessing the individual pixel intensities of an image
Histogram calculation and equalization in OpenCV
Geometric transformation on images
Filtering operations on images
Morphological operations on images
Summary
Questions
7
Object Detection and Tracking Using OpenCV and CUDA
Object Detection and Tracking Using OpenCV and CUDA
Technical requirements
Introduction to object detection and tracking
Object detection and tracking based on color
Object detection and tracking based on shape
Key-point detectors and descriptors
Object detection using Haar cascades
Object tracking using background subtraction
Summary
Questions
8
Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1
Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1
Technical requirements
Introduction to Jetson TX1
Installation of JetPack on Jetson TX1
Summary
Questions
9
Deploying Computer Vision Applications on Jetson TX1
Deploying Computer Vision Applications on Jetson TX1
Technical requirements
Device properties of Jetson TX1 GPU
Basic CUDA program on Jetson TX1
Image processing on Jetson TX1
Interfacing cameras with Jetson TX1
Advanced applications on Jetson TX1
Computer vision using Python and OpenCV on Jetson TX1
Summary
Questions
10
Getting Started with PyCUDA
Getting Started with PyCUDA
Technical requirements
Introduction to Python programming language
Introduction to the PyCUDA module
Installing PyCUDA on Windows
Installing PyCUDA on Ubuntu
Summary
Questions
11
Working with PyCUDA
Working with PyCUDA
Technical requirements
Writing the first program in PyCUDA
Accessing GPU device properties from PyCUDA program
Thread and block execution in PyCUDA
Basic programming concepts in PyCUDA
Measuring performance of PyCUDA programs using CUDA events
Complex programs in PyCUDA
Advanced kernel functions in PyCUDA
Summary
Questions
12
Basic Computer Vision Applications Using PyCUDA
Basic Computer Vision Applications Using PyCUDA
Technical requirements
Histogram calculation in PyCUDA
Basic computer vision operations using PyCUDA
Summary
Questions
13
Assessments
Assessments
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
14
Other Books You May Enjoy
Other Books You May Enjoy
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Other Books You May Enjoy

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ISBN: 978-1-78847-239-5

  • Get an introduction to Qt IDE and SDK
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  • Explore the multithreaded application development features...
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