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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

Technical requirements

This chapter uses Python, OpenCV, and NumPy. As part of OpenCV, it uses the optional opencv_contrib modules, which include functionality for face recognition. Some parts of this chapter use OpenCV's optional support for OpenNI 2 to capture images from depth cameras. Please refer back to Chapter 1, Setting Up OpenCV, for installation instructions.

The complete code for this chapter can be found in this book's GitHub repository, https://github.com/PacktPublishing/Learning-OpenCV-5-Computer-Vision-with-Python-Fourth-Edition, in the chapter05 folder. Sample images are in the repository images folder.

A subset of the chapter’s sample code can be edited and run interactively in Google Colab at https://colab.research.google.com/github/PacktPublishing/Learning-OpenCV-5-Computer-Vision-with-Python-Fourth-Edition/blob/main/chapter05/chapter05.ipynb.

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