Learning OpenCV

Common Routines in the ML Library

This chapter is written to get you up and running with the machine learning algorithms. As you try out and become comfortable with different methods, you'll also want to reference the …/opencv/docs/ref/opencvref_ml.htm manual that installs with OpenCV and/or the online OpenCV Wiki documentation (http://opencvlibrary.willowgarage.com/). Because this portion of the library is under active development, you will want to know about the latest and greatest available tools.

All the routines in the ML library^[238] are written as C++ classes and all derived from the CvStatModel class, which holds the methods that are universal to all the algorithms. These methods are listed in Table 13-3. Note that in the CvStatModel there are two ways of storing and recalling the model from disk: save() versus write() and load() versus read(). For machine learning models, you should use the much simpler save() and load(), which essentially wrap the more complex write() and read() functions into an interface that writes and reads XML and YAML to and from disk. Beyond that, for learning from data the two most important functions, predict() and train(), vary by algorithm and will be discussed next.

Table 13-3. Base class methods for the machine learning (ML) library

CvStatModel:: Methods	Description
save( const char* filename, const char* name = 0 )	Saves learned model in XML or YMAL. Use this method for storage.
load( const char* filename, const char* name=0 ); ...