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Mastering OpenCV 4 with Python

You're reading from  Mastering OpenCV 4 with Python

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344912
Pages 532 pages
Edition 1st Edition
Languages
Author (1):
Alberto Fernández Villán Alberto Fernández Villán
Profile icon Alberto Fernández Villán

Table of Contents (20) Chapters

Preface Section 1: Introduction to OpenCV 4 and Python
Setting Up OpenCV Image Basics in OpenCV Handling Files and Images Constructing Basic Shapes in OpenCV Section 2: Image Processing in OpenCV
Image Processing Techniques Constructing and Building Histograms Thresholding Techniques Contour Detection, Filtering, and Drawing Augmented Reality Section 3: Machine Learning and Deep Learning in OpenCV
Machine Learning with OpenCV Face Detection, Tracking, and Recognition Introduction to Deep Learning Section 4: Mobile and Web Computer Vision
Mobile and Web Computer Vision with Python and OpenCV Assessments Other Books You May Enjoy

Summary

In this chapter, we looked at the key concepts related to images. Images constitute rich information that's necessary to build your computer vision projects. OpenCV uses the BGR color format instead of RGB, but some Python packages (for example, Matplotlib) use the latter format. Therefore, we have covered how to convert the image from one color format into the other.

Additionally, we have summarized the main functions and options to work with images:

  • To access image properties
  • Some OpenCV functions, such as cv2.imread(), cv2.split(), cv2.merge(), cv2.imshow(), cv2.waitKey(), and cv2.destroyAllWindows()
  • How to get and set image pixels in both BGR and grayscale images

Finally, we included two notebooks, which let you play with all these concepts. Remember that once you have loaded the notebook, you can run it step by step by pressing Shift + Enter or run the notebook...

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