Wrappers for load methods of EM, LR, SVMSGD and Normal Bayes Classifier

modules/ml/src/em.cpp

@@ -845,6 +845,11 @@ Ptr<EM> EM::create()
     return makePtr<EMImpl>();
 }
 
+Ptr<EM> EM::load(const String& filepath, const String& nodeName)
+{
+    return Algorithm::load<EM>(filepath, nodeName);
+}
+
 }
 } // namespace cv
 

modules/ml/src/lr.cpp

@@ -127,6 +127,12 @@ Ptr<LogisticRegression> LogisticRegression::create()
     return makePtr<LogisticRegressionImpl>();
 }
 
+Ptr<LogisticRegression> LogisticRegression::load(const String& filepath, const String& nodeName)
+{
+    return Algorithm::load<LogisticRegression>(filepath, nodeName);
+}
+
+
 bool LogisticRegressionImpl::train(const Ptr<TrainData>& trainData, int)
 {
     // return value

modules/ml/src/nbayes.cpp

@@ -458,6 +458,11 @@ Ptr<NormalBayesClassifier> NormalBayesClassifier::create()
     return p;
 }
 
+Ptr<NormalBayesClassifier> NormalBayesClassifier::load(const String& filepath, const String& nodeName)
+{
+    return Algorithm::load<NormalBayesClassifier>(filepath, nodeName);
+}
+
 }
 }
 

modules/ml/src/svmsgd.cpp

@@ -134,6 +134,12 @@ Ptr<SVMSGD> SVMSGD::create()
     return makePtr<SVMSGDImpl>();
 }
 
+Ptr<SVMSGD> SVMSGD::load(const String& filepath, const String& nodeName)
+{
+    return Algorithm::load<SVMSGD>(filepath, nodeName);
+}
+
+
 void SVMSGDImpl::normalizeSamples(Mat &samples, Mat &average, float &multiplier)
 {
     int featuresCount = samples.cols;