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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

QR code detection

To complete this chapter, we are going to learn how to detect QR codes in images. This way, QR codes can also be used as markers for our augmented reality applications. The cv2.detectAndDecode() function both detects and decodes a QR code in the image containing the QR code. The image can be grayscale or color (BGR).

This function returns the following:

  • An array of vertices of the found QR code is returned. This array can be empty if the QR code is not found.
  • The rectified and binarized QR code is returned.
  • The data associated with this QR code is returned.

In the qr_code_scanner.py script, we make use of the aforementioned function to detect and decode QR codes. The key points are commented next.

First, the image is loaded, as follows:

image = cv2.imread("qrcode_rotate_45_image.png")

Next, we create the QR code detector with the following code...

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