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Mastering OpenCV 4 with Python

You're reading from   Mastering OpenCV 4 with Python A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344912
Length 532 pages
Edition 1st Edition
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Author (1):
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Alberto Fernández Villán Alberto Fernández Villán
Author Profile Icon Alberto Fernández Villán
Alberto Fernández Villán
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Introduction to OpenCV 4 and Python
2. Setting Up OpenCV FREE CHAPTER 3. Image Basics in OpenCV 4. Handling Files and Images 5. Constructing Basic Shapes in OpenCV 6. Section 2: Image Processing in OpenCV
7. Image Processing Techniques 8. Constructing and Building Histograms 9. Thresholding Techniques 10. Contour Detection, Filtering, and Drawing 11. Augmented Reality 12. Section 3: Machine Learning and Deep Learning in OpenCV
13. Machine Learning with OpenCV 14. Face Detection, Tracking, and Recognition 15. Introduction to Deep Learning 16. Section 4: Mobile and Web Computer Vision
17. Mobile and Web Computer Vision with Python and OpenCV 18. Assessments 19. Other Books You May Enjoy

Summary

In this chapter, we looked at an introduction to augmented reality. We coded several examples to see how to build both marker and markerless augmented reality applications. Additionally, we saw how to overlay simple models (shapes or images, among others).

As commented previously, to overlay more complex models, PyOpenGL (standard OpenGL bindings for Python) can be used. In this chapter, for the sake of simplification, this library is not tackled.

We have also seen how to create some funny Snapchat-based filters. It should be noted that in Chapter 11, Face Detection, Tracking, and Recognition, more advanced algorithms for both face detection, tracking, and location of facial landmarks will be covered. Therefore, Snapchat-based filters coded in this chapter can be easily modified to include a more robust pipeline to derive the position where both the glasses and the moustache...

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