Learning OpenCV 5 Computer Vision with Python: Build practical computer vision and machine learning applications with OpenCV 5 and Python 3

by Joseph Howse, Joe Minichino

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 FeaturesBuild powerful computer vision applications in concise code with OpenCV 5 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learning models, and deploy them in the CloudBook DescriptionComputer 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 learnInstall and familiarize yourself with OpenCV 5's Python 3 bindingsUnderstand image processing and video analysisUse a depth camera to distinguish foreground and background regionsDetect and identify objects, and track their motion in videosTrain and use your own models to match images and classify objectsDetect and recognize faces, and classify their ageBuild augmented reality applications, and navigate the real 3D worldTrain neural networks and deploy them as Cloud-based solutionsWho this book is forThis 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 ContentsSetting Up OpenCVHandling Files, Cameras, and GUIsProcessing Images with OpenCVDepth Estimation and SegmentationDetecting and Recognizing FacesRetrieving Images and Searching Using Image DescriptorsBuilding Custom Object DetectorsTracking ObjectsCamera Models and Augmented RealityIntroduction to 3D Navigation, Odometry, and Point CloudsIntroduction to Neural Networks with OpenCVOpenCV Applications at Scale

765 pages, Kindle Edition

Published October 28, 2026

About the author

Joseph Howse writes fiction, as well as technical books on computer programming and image analysis. He lives in a Nova Scotian fishing village, where he chats with his cats and nurtures an orchard of hardy fruit trees. His debut novel, The Girl in the Water, has won the 2023 Independent Press Award for Literary Fiction, the 2023 IAN Awards for Outstanding Multicultural Fiction, and the 2023 IPPY Awards Bronze Medal for Best Regional Ebook (Fiction). He is currently working on a sequel.