001
002//
003// This file is auto-generated. Please don't modify it!
004//
005package org.opencv.ml;
006
007import org.opencv.core.Algorithm;
008import org.opencv.core.Mat;
009
010// C++: class StatModel
011//javadoc: StatModel
012public class StatModel extends Algorithm {
013
014    protected StatModel(long addr) { super(addr); }
015
016
017    public static final int
018            UPDATE_MODEL = 1,
019            RAW_OUTPUT = 1,
020            COMPRESSED_INPUT = 2,
021            PREPROCESSED_INPUT = 4;
022
023
024    //
025    // C++:  bool empty()
026    //
027
028    //javadoc: StatModel::empty()
029    public  boolean empty()
030    {
031        
032        boolean retVal = empty_0(nativeObj);
033        
034        return retVal;
035    }
036
037
038    //
039    // C++:  bool isClassifier()
040    //
041
042    //javadoc: StatModel::isClassifier()
043    public  boolean isClassifier()
044    {
045        
046        boolean retVal = isClassifier_0(nativeObj);
047        
048        return retVal;
049    }
050
051
052    //
053    // C++:  bool isTrained()
054    //
055
056    //javadoc: StatModel::isTrained()
057    public  boolean isTrained()
058    {
059        
060        boolean retVal = isTrained_0(nativeObj);
061        
062        return retVal;
063    }
064
065
066    //
067    // C++:  bool train(Mat samples, int layout, Mat responses)
068    //
069
070    //javadoc: StatModel::train(samples, layout, responses)
071    public  boolean train(Mat samples, int layout, Mat responses)
072    {
073        
074        boolean retVal = train_0(nativeObj, samples.nativeObj, layout, responses.nativeObj);
075        
076        return retVal;
077    }
078
079
080    //
081    // C++:  bool train(Ptr_TrainData trainData, int flags = 0)
082    //
083
084    // Unknown type 'Ptr_TrainData' (I), skipping the function
085
086
087    //
088    // C++:  float calcError(Ptr_TrainData data, bool test, Mat& resp)
089    //
090
091    // Unknown type 'Ptr_TrainData' (I), skipping the function
092
093
094    //
095    // C++:  float predict(Mat samples, Mat& results = Mat(), int flags = 0)
096    //
097
098    //javadoc: StatModel::predict(samples, results, flags)
099    public  float predict(Mat samples, Mat results, int flags)
100    {
101        
102        float retVal = predict_0(nativeObj, samples.nativeObj, results.nativeObj, flags);
103        
104        return retVal;
105    }
106
107    //javadoc: StatModel::predict(samples)
108    public  float predict(Mat samples)
109    {
110        
111        float retVal = predict_1(nativeObj, samples.nativeObj);
112        
113        return retVal;
114    }
115
116
117    //
118    // C++:  int getVarCount()
119    //
120
121    //javadoc: StatModel::getVarCount()
122    public  int getVarCount()
123    {
124        
125        int retVal = getVarCount_0(nativeObj);
126        
127        return retVal;
128    }
129
130
131    @Override
132    protected void finalize() throws Throwable {
133        delete(nativeObj);
134    }
135
136
137
138    // C++:  bool empty()
139    private static native boolean empty_0(long nativeObj);
140
141    // C++:  bool isClassifier()
142    private static native boolean isClassifier_0(long nativeObj);
143
144    // C++:  bool isTrained()
145    private static native boolean isTrained_0(long nativeObj);
146
147    // C++:  bool train(Mat samples, int layout, Mat responses)
148    private static native boolean train_0(long nativeObj, long samples_nativeObj, int layout, long responses_nativeObj);
149
150    // C++:  float predict(Mat samples, Mat& results = Mat(), int flags = 0)
151    private static native float predict_0(long nativeObj, long samples_nativeObj, long results_nativeObj, int flags);
152    private static native float predict_1(long nativeObj, long samples_nativeObj);
153
154    // C++:  int getVarCount()
155    private static native int getVarCount_0(long nativeObj);
156
157    // native support for java finalize()
158    private static native void delete(long nativeObj);
159
160}