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Raspberry Pi Computer Vision Programming. - Second Edition

You're reading from  Raspberry Pi Computer Vision Programming. - Second Edition

Product type Book
Published in Jun 2020
Publisher Packt
ISBN-13 9781800207219
Pages 306 pages
Edition 2nd Edition
Languages
Author (1):
Ashwin Pajankar Ashwin Pajankar
Profile icon Ashwin Pajankar

Table of Contents (15) Chapters

Preface 1. Chapter 1: Introduction to Computer Vision and the Raspberry Pi 2. Chapter 2: Preparing the Raspberry Pi for Computer Vision 3. Chapter 3: Introduction to Python Programming 4. Chapter 4: Getting Started with Computer Vision 5. Chapter 5: Basics of Image Processing 6. Chapter 6: Colorspaces, Transformations, and Thresholding 7. Chapter 7: Let's Make Some Noise 8. Chapter 8: High-Pass Filters and Feature Detection 9. Chapter 9: Image Restoration, Segmentation, and Depth Maps 10. Chapter 10: Histograms, Contours, and Morphological Transformations 11. Chapter 11: Real-Life Applications of Computer Vision 12. Chapter 12: Working with Mahotas and Jupyter 13. Chapter 13: Appendix 14. Other Books You May Enjoy

Implementing the chroma key effect

Chroma keying is also known as chroma key compositing. It is also colloquially known as the green screen or blue screen effect due to the green or blue background that we use while creating this effect. It is a post-production technique and can also be used on still images and live videos. In the chroma key effect, we place an object or a person in the foreground and capture an image or footage. The background is usually a green- or blue-colored fabric or wall. Then, we replace the green or blue color in the captured image or footage with another video or an image. This makes the viewers feel that the person or the object in the foreground is at a different location than the studio where they were filmed. This effect is one of the most used effects in film-making and live weather forecasts in news broadcasts:

  1. Let's start by importing all the needed libraries and initiating a video capture object:
    import numpy as np
    import cv2
    cap = cv2...
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