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Learning OpenCV 3 Computer Vision with Python (Update)

You're reading from   Learning OpenCV 3 Computer Vision with Python (Update) Unleash the power of computer vision with Python using OpenCV

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Product type Hardcover
Published in Jun 2026
Publisher
ISBN-13 9781803230221
Length
Edition 1st Edition
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Authors (2):
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Joe Minichino Joe Minichino
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Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (12) Chapters Close

1. Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning FREE CHAPTER
2. Setting Up OpenCV 3. Handling Files, Cameras, and GUIs 4. Processing Images with OpenCV 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. OpenCV Applications at Scale Appendix A: Bending Color Space with the Curves Filter

What's new in OpenCV 5

If you are an OpenCV veteran, you might want to know more about OpenCV 5's changes before you decide to install it. Here are some of the highlights:

  • The C++ implementation of OpenCV has been updated to C++14. OpenCV's Python bindings wrap the C++ implementation, so as Python users, we may gain some performance advantages from this update, even though we are not using C++ directly.
  • Support for Python 2 has been dropped because this Python version is obsolete and no longer maintained. If you have any old Python 2 projects, you should upgrade them to Python 3.
  • For many algorithms, support for named parameters has been added in order to make the initialization code more concise and readable.
  • For the pip package installer, the opencv-python and opencv-contrib-python packages are now maintained by the core OpenCV team rather than a third party. The opencv-contrib-python-nonfree package has been discontinued due to patent restrictions.
  • The SIFT algorithm...
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