Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

By : Joseph Howse, Joe Minichino
5 (2)
Book Image

Learning OpenCV 5 Computer Vision with Python, Fourth Edition - Fourth Edition

5 (2)
By: Joseph Howse, Joe Minichino

Overview of this book

Computer vision is a rapidly evolving science in the field of artificial intelligence, encompassing diverse use cases and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 5 and Python 3. You'll start by setting up OpenCV 5 with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying images, videos, and camera feeds. From taking you through image processing, video analysis, depth estimation, and segmentation, to helping you gain practice by building a GUI app, this book ensures you'll have opportunities for hands-on activities. You'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning, which will enable you to create and use object detectors and even track moving objects in real time. Later, you'll develop your skills in augmented reality and real-world 3D navigation. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age, and you'll deploy your solutions to the Cloud. By the end of this book, you'll have the skills you need to execute real-world computer vision projects.
Table of Contents (12 chapters)
Free Chapter
1
Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning
Appendix A: Bending Color Space with the Curves Filter

Project Cameo (face tracking and image manipulation)

OpenCV is often studied through a cookbook approach that covers a lot of algorithms, but nothing about high-level application development. To an extent, this approach is understandable because OpenCV's potential applications are so diverse. To name just a few examples, OpenCV can be used in photo/video editors, motion-controlled games, medical imaging devices, a robot's AI, or psychology experiments where we log participants' eye movements. Across these varied use cases, can we truly study a useful set of abstractions?

The book's authors believe we can, and the sooner we start creating abstractions, the better. Throughout Chapters 2 to 5, we will structure several of our OpenCV examples around a single application, but, at each step, we will design a component of this application to be extensible and reusable.

We will develop an interactive application that performs face tracking and image manipulations on camera...