In this chapter, we have covered two advanced modules of OpenCV: machine learning and GPU. Machine learning has the capability to learn computers to make decisions. For this, a classifier is trained and validated. This chapter provides three classification samples: KNN classifier, Random Forest using a .cvs
database, and SVM using an image database. The chapter also addresses the use of OpenCV with CUDA. GPUs have a growing role in intensive tasks because they can offload the CPU and run parallel tasks such as those encountered in computer vision algorithms. Several GPU examples have been provided: GPU module installation, a basic first GPU program, and real-time template matching.
OpenCV Essentials
OpenCV Essentials
Overview of this book
Table of Contents (15 chapters)
OpenCV Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Started
Something We Look At – Graphical User Interfaces
First Things First – Image Processing
What's in the Image? Segmentation
Focusing on the Interesting 2D Features
Where's Wally? Object Detection
What Is He Doing? Motion
Advanced Topics
Index
Customer Reviews