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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

Computer vision using Python and OpenCV on Jetson TX1

Up till now, we have developed all computer vision applications using C/C++, OpenCV, and CUDA. Jetson TX1 also supports the Python programming language for computer vision applications. When OpenCV is compiled on Jetson TX1, it also installs Python binaries for OpenCV. So programmers who are comfortable in Python programming language can use a Python interface for OpenCV in developing computer vision applications and deploying them on Jetson TX1. Python also comes preinstalled with Jetson TX1 as is the case for all Linux operating systems. Windows users can install Python separately. The installation procedure and advantages of Python are explained in the next chapter.

One disadvantage of using Python is that OpenCV Python interface is still not greatly benefited by CUDA acceleration. Still, the ease of learning Python and...

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