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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

Installing PyCUDA on Ubuntu

This section will describe the steps to install PyCUDA on Linux operating systems. Ubuntu is used for demonstration but the procedure will work on any recent Linux distribution. The steps are described below:

  1. If you have not installed the CUDA toolkit, as described in the first chapter, then download the latest CUDA toolkit from https://developer.nvidia.com/cuda-downloads. It will ask for your operating system, CPU architecture, and whether to install using the internet or to download the entire installer first. As can be seen from the following screenshot, we have chosen Ubuntu with the runfile (local) installer. You can choose values according to your settings:
  1. Run the sudo sh cuda_9.2.148_396.37_linux.run command on Command Prompt to install the CUDA toolkit.

  1. Anaconda distribution will be used as a Python interpreter so it can be downloaded...
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