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43 // 2004-03-16, Mark Asbach <asbach@ient.rwth-aachen.de>
44 // Institute of Communications Engineering, RWTH Aachen University
46 %module(package="opencv") ml
53 #include "pyhelpers.h"
54 #include "pycvseq.hpp"
57 // include python-specific files
58 %include "./nointpb.i"
59 %include "./pytypemaps.i"
60 %include "exception.i"
62 %import "../general/cv.i"
64 %include "../general/memory.i"
65 %include "../general/typemaps.i"
67 %newobject cvCreateCNNConvolutionLayer;
68 %newobject cvCreateCNNSubSamplingLayer;
69 %newobject cvCreateCNNFullConnectLayer;
70 %newobject cvCreateCNNetwork;
71 %newobject cvTrainCNNClassifier;
73 %newobject cvCreateCrossValidationEstimateModel;
79 __doc__ = """Machine Learning
81 The Machine Learning library (ML) is a set of classes and functions for
82 statistical classification, regression and clustering of data.
84 Most of the classification and regression algorithms are implemented as classes.
85 As the algorithms have different sets of features (like ability to handle missing
86 measurements, or categorical input variables etc.), there is only little common
87 ground between the classes. This common ground is defined by the class CvStatModel
88 that all the other ML classes are derived from.
90 This wrapper was semi-automatically created from the C/C++ headers and therefore
91 contains no Python documentation. Because all identifiers are identical to their
92 C/C++ counterparts, you can consult the standard manuals that come with OpenCV.
101 CvMat ** pointers = const_cast<CvMat **> (self->get_covs());
102 int n = self->get_nclusters();
104 PyObject * result = PyTuple_New(n);
105 for (int i=0; i<n; ++i)
107 PyObject * obj = SWIG_NewPointerObj(pointers[i], $descriptor(CvMat *), 0);
108 PyTuple_SetItem(result, i, obj);
116 %ignore CvEM::get_covs;