From a6b29be55bd45db07acab1394669211c98d90231 Mon Sep 17 00:00:00 2001 From: Dmitriy Anisimov Date: Sat, 13 Sep 2014 15:06:07 +0400 Subject: [PATCH] minor change: moved algorithm type to the end of params --- modules/ml/include/opencv2/ml.hpp | 4 ++-- modules/ml/src/knearest.cpp | 6 +++--- modules/ml/test/test_emknearestkmeans.cpp | 2 +- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/modules/ml/include/opencv2/ml.hpp b/modules/ml/include/opencv2/ml.hpp index 2030f69ac..51d09d13e 100644 --- a/modules/ml/include/opencv2/ml.hpp +++ b/modules/ml/include/opencv2/ml.hpp @@ -230,12 +230,12 @@ public: class CV_EXPORTS_W_MAP Params { public: - Params(int algorithmType_=BRUTE_FORCE, int defaultK=10, bool isclassifier_=true, int Emax_=INT_MAX); + Params(int defaultK=10, bool isclassifier_=true, int Emax_=INT_MAX, int algorithmType_=BRUTE_FORCE); - CV_PROP_RW int algorithmType; CV_PROP_RW int defaultK; CV_PROP_RW bool isclassifier; CV_PROP_RW int Emax; // for implementation with KDTree + CV_PROP_RW int algorithmType; }; virtual void setParams(const Params& p) = 0; virtual Params getParams() const = 0; diff --git a/modules/ml/src/knearest.cpp b/modules/ml/src/knearest.cpp index ac9e95ca0..4bf40758f 100644 --- a/modules/ml/src/knearest.cpp +++ b/modules/ml/src/knearest.cpp @@ -50,11 +50,11 @@ namespace cv { namespace ml { -KNearest::Params::Params(int algorithmType_, int k, bool isclassifier_, int Emax_) : - algorithmType(algorithmType_), +KNearest::Params::Params(int k, bool isclassifier_, int Emax_, int algorithmType_) : defaultK(k), isclassifier(isclassifier_), - Emax(Emax_) + Emax(Emax_), + algorithmType(algorithmType_) { } diff --git a/modules/ml/test/test_emknearestkmeans.cpp b/modules/ml/test/test_emknearestkmeans.cpp index ba0b82b0c..121b34d18 100644 --- a/modules/ml/test/test_emknearestkmeans.cpp +++ b/modules/ml/test/test_emknearestkmeans.cpp @@ -330,7 +330,7 @@ void CV_KNearestTest::run( int /*start_from*/ ) } // KNearest KDTree implementation - Ptr knearestKdt = KNearest::create(ml::KNearest::Params(ml::KNearest::KDTREE)); + Ptr knearestKdt = KNearest::create(ml::KNearest::Params(10, true, INT_MAX, ml::KNearest::KDTREE)); knearestKdt->train(trainData, ml::ROW_SAMPLE, trainLabels); knearestKdt->findNearest(testData, 4, bestLabels); if( !calcErr( bestLabels, testLabels, sizes, err, true ) )