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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

Processing images with Mahotas

Mahotas is a Python library for image processing and computer vision-related tasks. It was developed by Luis Pedro.

It implements many computer vision-related algorithms. It has been implemented in C++ and it operates on NumPy arrays. It also has a clean interface for Python 3.

Mahotas currently has over 100 functions for image processing and computer vision, and that number keeps growing with every release. This project is under active development and there is a new release every few months. Apart from the added functionality, every new release brings improvements in performance.

Note:

You can learn more about Mahotas by referring to https://mahotas.readthedocs.io/en/latest/.

We can install mahotas on Raspberry Pi with the following command:

pip3 install mahotas

A component of Mahotas will be installed in /home/pi/.local/bin. We can add this to the PATH variable permanently, as follows:

  1. Open the ~/.profile file in editing...
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