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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
Languages
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Creating modules

Let's revisit the Cameo project that we started in Chapter 2, Handling Files, Cameras, and GUIs. We can modify Cameo so that it applies filters to the captured images in real time. As in the case of our CaptureManager and WindowManager classes, our filters should be reusable outside of Cameo. Thus, we should separate the filters into their own Python module or file.

Let's create a file called filters.py in the same directory as cameo.py. We need the following import statements in filters.py:

import cv2
import numpy
import utils

Let's also create a file called utils.py in the same directory. It should contain the following import statements:

import cv2
import numpy
import scipy.interpolate

We will be adding filter functions and classes to filters.py, while more general-purpose math functions will go in utils.py.

...
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