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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

Chapter 7

  1. OpenCV code to detect objects with yellow color from a video is as follows: Note that the boilerplate code is not repeated here.
cuda::cvtColor(d_frame, d_frame_hsv, COLOR_BGR2HSV);

//Split HSV 3 channels
cuda::split(d_frame_hsv, d_frame_shsv);

//Threshold HSV channels for Yellow color
cuda::threshold(d_frame_shsv[0], d_thresc[0], 20, 30, THRESH_BINARY);
cuda::threshold(d_frame_shsv[1], d_thresc[1], 100, 255, THRESH_BINARY);
cuda::threshold(d_frame_shsv[2], d_thresc[2], 100, 255, THRESH_BINARY);

//Bitwise AND the channels
cv::cuda::bitwise_and(d_thresc[0], d_thresc[1],d_intermediate);
cv::cuda::bitwise_and(d_intermediate, d_thresc[2], d_result);
d_result.download(h_result);
imshow("Thresholded Image", h_result);
imshow("Original", frame);
  1. When the color of an object is the same as the color of background, then color based object detection will fail. If there...
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