Learning OpenCV 4 Computer Vision with Python 3 – Third Edition

Learning OpenCV 4 Computer Vision with Python 3, 3rd Edition

eBook Details:

  • Paperback: 372 pages
  • Publisher: WOW! eBook (February 20, 2020)
  • Language: English
  • ISBN-10: 1789531616
  • ISBN-13: 978-1789531619

eBook Description:

Learning OpenCV 4 Computer Vision with Python 3, 3rd Edition: Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code

Computer vision is a rapidly evolving science, encompassing diverse applications 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 4 and Python 3.

You’ll start by understanding OpenCV 4 and 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. From taking you through image processing, video analysis, and 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. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person’s gender and age.

  • Install and familiarize yourself with OpenCV 4’s Python 3 bindings
  • Understand image processing and video analysis basics
  • Use a depth camera to distinguish foreground and background regions
  • Detect and identify objects, and track their motion in videos
  • Train and use your own models to match images and classify objects
  • Detect and recognize faces, and classify their gender and age
  • Build an augmented reality application to track an image in 3D
  • Work with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs)

By the end of this Learning OpenCV 4 Computer Vision with Python 3, Third Edition book, you’ll have the skills you need to execute real-world computer vision projects.

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3 Responses

  1. March 25, 2020

    […] OpenCV 4 with Python Blueprints, 2nd Edition: Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworks. Become proficient in computer vision by designing advanced projects using OpenCV 4 with Python 3.8. […]

  2. July 1, 2020

    […] deep neural networks, AI systems make decisions based on their perceptions of their input data. Deep learning-based computer vision (CV) techniques, which enhance and interpret visual perceptions, makes tasks like image recognition, […]

  3. July 1, 2020

    […] deep neural networks, AI systems make decisions based on their perceptions of their input data. Deep learning-based computer vision (CV) techniques, which enhance and interpret visual perceptions, makes tasks like image recognition, […]

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