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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

Creating and training an object detector

Using a pre-trained detector makes it easy to build a quick prototype, and we are all very grateful to the OpenCV developers for making such useful capabilities as face detection and people detection readily available. However, whether you are a hobbyist or a computer vision professional, it is unlikely that you will only deal with people and faces.

Moreover, if you are like the authors of this book, you will wonder how the people detector was created in the first place and whether you can improve it. Furthermore, you may also wonder whether you can apply the same concepts to detect diverse objects, ranging from cars to goblins.

Indeed, in industry, you may have to deal with problems of detecting very specific objects, such as registration plates, book covers, or whatever thing may be most important to your employer or client.

Thus, the question is, how do we come up with our own classifiers?

There are many popular approaches. Throughout the remainder...

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