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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

Questions

  1. What packages and libraries were reviewed in this chapter in connection with face processing?
  2. What is the main difference between face identification and face verification?
  3. What does the cv2.face.getFacesHAAR() OpenCV function do?
  4. What does the cv2.dnn.blobFromImage() function do?
  5. What function does the cvlib package provide to detect faces?
  6. What function does face_recognition provide to detect facial landmarks?
  7. What function does dlib provide to initialize the correlation tracker?
  8. What function does dlib provide to start the correlation tracker?
  9. What function does dlib provide to get the position of the tracked object?
  10. Calculate the 128D descriptor to perform face recognition of the image BGR image with dlib.
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