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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 programming concepts in PyCUDA

We will start developing some useful stuff using PyCUDA in this section. The section will also demonstrate some useful functions and directives of PyCUDA, using a simple example of adding two numbers.

Adding two numbers in PyCUDA

Python provides a very fast library for numerical operations which is called numpy (Numeric Python). It is developed in C or C++ and is very useful for array manipulations in Python. It is used frequently in PyCUDA programs as arguments to PyCUDA kernel functions are passed as numpy arrays. This section explains how to add two numbers using PyCUDA. The basic kernel code for adding two numbers is shown as follows:

import pycuda.autoinit
import pycuda.driver as...
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