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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 FREE CHAPTER
2. Setting Up OpenCV 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

A theoretical introduction to drawing in OpenCV

OpenCV provides many functions to draw basic shapes. Common basic shapes include lines, rectangles, and circles. However, with OpenCV we can draw more basic shapes. As mentioned briefly in the introduction, it is a common approach to draw basic shapes on the image in order to do the following:

  • Show some intermediate results of your algorithm
  • Show the final results of your algorithm
  • Show some debugging information

In the next screenshot, you can see an image modified to include some useful information in connection with the two algorithms mentioned in the introduction (face detection and face recognition). In this way, you can process all the images in a directory and, afterward, you can see where your algorithm has detected wrong faces (false positives) or even missing faces (false negatives):

A false positive is an error where...
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