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Learning OpenCV 5 Computer Vision with Python

You're reading from   Learning OpenCV 5 Computer Vision with Python Tackle computer vision and machine learning with the newest tools, techniques and algorithms

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781803230221
Length
Edition 4th Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
Author Profile Icon Joseph Howse
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, NumPy, and SciPy. Please refer to Chapter 1, Setting Up OpenCV, for installation instructions.

The completed 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 chapter03 folder. The sample images are also in this book's GitHub repository, in the 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/chapter03/chapter03.ipynb.

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