Learning OpenCV 5 Computer Vision with Python - Fourth Edition

Master computer vision with OpenCV 5 and Python 3 by building practical applications for image processing, object detection, tracking, face recognition, machine learning, 3D vision, and cloud computing.

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Key Features:

- Build powerful computer vision applications in concise code with OpenCV 5 and Python 3

- Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking

- Train, use, and understand machine learning models, and deploy them in the Cloud

Book Description:

Computer vision is a fast-moving field of artificial intelligence, powering applications that need to understand images, video, objects, faces, motion, depth, and 3D environments. Learning OpenCV 5 Computer Vision with Python gives you a practical path to building these systems with OpenCV 5 and Python 3.

You will begin by setting up OpenCV, understanding what is new in OpenCV 5, and working with images, video, camera feeds, files, and graphical interfaces. From there, you will learn essential image-processing techniques, depth estimation and segmentation, face detection and recognition, and image retrieval using visual descriptors. As your skills develop, you will build custom object detectors, classify and track moving objects, and explore camera models, augmented reality, 3D reconstruction, and navigation. You will also work with machine learning and neural networks, applying them to practical vision tasks before learning how computer vision solutions can be deployed to the cloud and scaled beyond local experimentation.

Throughout the book, hands-on Python examples help you connect core concepts with working implementations. By the end, you will have the practical skills to design, build, and extend real-world computer vision applications with OpenCV 5 across desktop and cloud-based workflows.

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What You Will Learn:

- Install and familiarize yourself with OpenCV 5's Python 3 bindings

- Understand image processing and video analysis

- 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 age

- Build augmented reality applications, and navigate the real 3D world

- Train neural networks and deploy them as Cloud-based solutions

Who this book is for:

This book is for Python programmers who want to learn computer vision and machine learning with OpenCV 5. It is also suitable for computer vision developers, AI/ML engineers, and practitioners who want to strengthen or refresh their OpenCV skills. No prior computer vision or machine learning experience is required, but readers should be comfortable with basic Python programming.

Table of Contents

- Setting Up OpenCV

- Handling Files, Cameras, and GUIs

- Processing Images with OpenCV

- Depth Estimation and Segmentation

- Detecting and Recognizing Faces

- Retrieving Images and Searching Using Image Descriptors

- Building Custom Object Detectors

- Tracking Objects

- Camera Models and Augmented Reality

- Introduction to 3D Navigation, Odometry, and Point Clouds

- Introduction to Neural Networks with OpenCV

- OpenCV Applications at Scale