Joseph Howse - Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition

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First published: April 2013
Second edition: September 2015
Third edition: February 2020

Production reference: 1190220

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ISBN 978-1-78953-161-9

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Joseph Howse lives in a Canadian fishing village with four cats; the cats like fish, but they prefer chicken.

Joseph provides computer vision expertise through his company, Nummist Media. His books include OpenCV 4 for Secret Agents, Learning OpenCV 4 Computer Vision with Python 3, OpenCV 3 Blueprints, Android Application Programming with OpenCV 3, iOS Application Development with OpenCV 3, and Python Game Programming by Example, published by Packt.

Joe Minichino is an R&D labs engineer at Teamwork. He is a passionate programmer who is immensely curious about programming languages and technologies and constantly experimenting with them. Born and raised in Varese, Lombardy, Italy, and coming from a humanistic background in philosophy (at Milan's Universit Statale), Joe has lived in Cork, Ireland, since 2004. There, he became a computer science graduate at the Cork Institute of Technology.

Sri Manikanta Palakollu is an undergraduate student pursuing his bachelor's degree in computer science and engineering at SICET under JNTUH. He is a founder of the Open Stack Developer Community in his college. He started his journey as a competitive programmer. He loves to solve problems related to the data science field. His interests include data science, app development, web development, cyber security, and technical writing. He has published many articles on data science, machine learning, programming, and cyber security with publications such as Hacker Noon, freeCodeCamp, Towards Data Science, and DDI.

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Now in its third edition, this is the original book on OpenCV's Python bindings. Readers will learn a great range of techniques and algorithms, from the classics to the state-of-the-art, and from geometry to machine learning. All of this is in aid of solving practical computer vision problems in well-built applications. Using OpenCV 4 and Python 3, we adopt an approach that is accessible to computer vision novices, yet also informative for experts who want to expand and update their skills.

We start with an introduction to OpenCV 4 and explain how to set it up with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. You'll learn about image processing and video analysis, along with depth estimation and segmentation, and you'll gain practice by building a simple GUI application. Next, you'll tackle two popular problems: face detection and face recognition.