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OpenCV 3 Computer Vision with Python Cookbook

You're reading from   OpenCV 3 Computer Vision with Python Cookbook Leverage the power of OpenCV 3 and Python to build computer vision applications

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788474443
Length 306 pages
Edition 1st Edition
Languages
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Authors (2):
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Aleksei Spizhevoi Aleksei Spizhevoi
Author Profile Icon Aleksei Spizhevoi
Aleksei Spizhevoi
 Rybnikov Rybnikov
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Rybnikov
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Table of Contents (15) Chapters Close

Title Page
Packt Upsell
Contributors
Preface
1. I/O and GUI FREE CHAPTER 2. Matrices, Colors, and Filters 3. Contours and Segmentation 4. Object Detection and Machine Learning 5. Deep Learning 6. Linear Algebra 7. Detectors and Descriptors 8. Image and Video Processing 9. Multiple View Geometry 1. Other Books You May Enjoy Index

Appendix 1. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Computer Vision with OpenCV 3 and Qt5 Amin Ahmadi Tazehkandi

ISBN: 978-1-78847-239-5

  • Get an introduction to Qt IDE and SDK
  • Be introduced to OpenCV and see how to communicate between OpenCV and Qt
  • Understand how to create UI using Qt Widgets
  • Know to develop cross-platform applications using OpenCV 3 and Qt 5
  • Explore the multithreaded application development features of Qt5
  • Improve OpenCV 3 application development using Qt5
  • Build, test, and deploy Qt and OpenCV apps, either dynamically or statically
  • See Computer Vision technologies such as filtering and transformation of images, detecting and matching objects, template matching, object tracking, video and motion analysis, and much more
  • Be introduced to QML and Qt Quick for iOS and Android application development

OpenCV 3.x with Python By Example - Second Edition Gabriel Garrido, Prateek Joshi

ISBN: 978-1-78839-690-5

  • Detect shapes and edges from images and videos
  • How to apply filters on images and videos
  • Use different techniques to manipulate and improve images
  • Extract and manipulate particular parts of images and videos
  • Track objects or colors from videos
  • Recognize specific object or faces from images and videos
  • How to create Augmented Reality applications
  • Apply artificial neural networks and machine learning to improve object recognition
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