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Raspberry Pi Computer Vision Programming

You're reading from   Raspberry Pi Computer Vision Programming Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781800207219
Length 306 pages
Edition 2nd Edition
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Author (1):
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Ashwin Pajankar Ashwin Pajankar
Author Profile Icon Ashwin Pajankar
Ashwin Pajankar
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Introduction to Computer Vision and the Raspberry Pi 2. Chapter 2: Preparing the Raspberry Pi for Computer Vision FREE CHAPTER 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

Summary

In this chapter, we explored the basics of Mahotas, which is a NumPy-based image processing library. We looked at a few image processing-related functions and learned how to combine Mahotas and OpenCV code for image processing. We also learned the names of other NumPy- and non-NumPy-based image processing libraries. You can explore those libraries further.

The last topic we learned about, the Jupyter Notebook, is very handy for quickly prototyping ideas and sharing code electronically. Many computer vision and data science professionals now use Jupyter notebooks for their Python programming projects.

In the Appendix section of this book, I have explained all the topics that I could not list under this chapter. These topics will be immensely useful to anyone who uses Raspberry Pi for various purposes.

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