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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

Chapter 3: Introduction to Python Programming

In the previous chapter, we learned how to remotely access the Command Prompt and the desktop of a Raspberry Pi (RPi) board. We also installed OpenCV for Python 3. Finally, we learned how to overclock the RPi and examined the various heatsinks for the RPi.

Continuing from where we left off at the end of the previous chapter, in this chapter, we will start by looking at Python 3 programming on the RPi. We will have a brief look at the Scientific Python (SciPy) ecosystem and all the libraries in it. Then, we will write basic programs for numerical computation with NumPy N-Dimensional Arrays (ndarrays). We will also learn how to visualize data with Matplotlib. Finally, we will explore the hardware aspects of the RPi with the General Purpose Input Output (GPIO) library of Python for the RPi.

In short, we will cover the following topics:

  • Understanding Python 3
  • The SciPy ecosystem
  • Programming with NumPy and Matplotlib
  • ...
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