Caractéristiques
Auteur
Joseph Howse
Conditie
Gelezen
Productnummer (ISBN)
9781789531619
Jaar (oorspr.)
2020
Description
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Bestel direct op onze website!
Titel: Learning OpenCV 4 Computer Vision with Python 3
Auteur: Joseph Howse
ISBN: 9781789531619
Conditie: Beetje gebruikt
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.
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 Key Features
Bestel direct op onze website!
Titel: Learning OpenCV 4 Computer Vision with Python 3
Auteur: Joseph Howse
ISBN: 9781789531619
Conditie: Beetje gebruikt
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.
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 Key Features
- Build powerful computer vision applications in concise code with OpenCV 4 and Python 3
- Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking
- Train, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networks
- 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)
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