Hi,
I'm dealing with machine learning / deep learning and read a lot about it (how it works, kinds of net structures, kinds of learnings, etc) and read the paper from Paul Viola and Michael Jones whose method is used in OpenCV. But I just couldn't find out what the purpose of the *.xml file is, produced by the OpenCV training.
It contains a lot of training information in the header and, it seems so to me, a lot of random points.
The xml file contains a lot of weak classifiers which are combined to become a strong classifier.
My question, however, is: How does OpenCV use this *.xml file to detect objects?
What are the internal leafs and what's meant by "leaf values"?
I'd appreciate any helpful answer :)