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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 1. Section 1: Introduction to OpenCV 4 and Python
2. Setting Up OpenCV 3. Image Basics in OpenCV 4. Handling Files and Images 5. Constructing Basic Shapes in OpenCV 6. Section 2: Image Processing in OpenCV
7. Image Processing Techniques 8. Constructing and Building Histograms 9. Thresholding Techniques 10. Contour Detection, Filtering, and Drawing 11. Augmented Reality 12. Section 3: Machine Learning and Deep Learning in OpenCV
13. Machine Learning with OpenCV 14. Face Detection, Tracking, and Recognition 15. Introduction to Deep Learning 16. Section 4: Mobile and Web Computer Vision
17. Mobile and Web Computer Vision with Python and OpenCV 18. Assessments 19. Other Books You May Enjoy

The OpenCV and Python project structure

The project structure is the way you organize all the files inside a folder in a way that the project best accomplishes the objectives. We are going to start with a .py script (sampleproject.py) that should be with other files in order to complete the information about this script dependencies, license, how to install it, or how to test it. A common approach for structuring this basic project is as follows:

sampleproject/

├── .gitignore
├── sampleproject.py
├── LICENSE
├── README.rst
├── requirements.txt
├── setup.py
└── tests.py

sampleproject.py—if your project is only a single Python source file, then put it into the directory and name it something related to your project.

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