Book Image

OpenCV Computer Vision with Python

By : Joseph Howse
Book Image

OpenCV Computer Vision with Python

By: Joseph Howse

Overview of this book

<p>OpenCV Computer Vision with Python shows you how to use the Python bindings for OpenCV. By following clear and concise examples, you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers, and how to efficiently process image data with NumPy and SciPy, then this book is for you.</p> <p>This book has practical, project-based tutorials for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python. It is a hands-on guide that covers the fundamental tasks of computer vision, capturing, filtering, and analyzing images, with step-by-step instructions for writing both an application and reusable library classes.</p>
Table of Contents (14 chapters)
OpenCV Computer Vision with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Creating modules


Like our CaptureManager and WindowManager classes, our filters should be reusable outside 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.