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Machine Learning for OpenCV 4 - Second Edition
book

Machine Learning for OpenCV 4 - Second Edition

by Aditya Sharma, Michael Beyeler (USD), Vishwesh Ravi Shrimali, Michael Beyeler
September 2019
Intermediate to advanced
420 pages
10h 29m
English
Packt Publishing
Content preview from Machine Learning for OpenCV 4 - Second Edition

Having a look at supervised learning in OpenCV

Just knowing how supervised learning works is not going to be of any use if we can't put it into practice. Thankfully, OpenCV provides a pretty straightforward interface for all its statistical learning models, which includes all supervised learning models.

In OpenCV, every machine learning model derives from the cv::ml::StatModel base class. This is fancy talk for saying that if we want to use a machine learning model in OpenCV, we have to provide all of the functionality that StatModel tells us to. This includes a method to train the model (called train) and a method to measure the performance of the model (called calcError).

In Object-Oriented Programming (OOP), we deal primarily with objects ...
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Publisher Resources

ISBN: 9781789536300