// // This file is auto-generated. Please don't modify it! // package org.opencv.ml; import org.opencv.core.Mat; // C++: class NormalBayesClassifier /** * Bayes classifier for normally distributed data. * * SEE: REF: ml_intro_bayes */ public class NormalBayesClassifier extends StatModel { protected NormalBayesClassifier(long addr) { super(addr); } // internal usage only public static NormalBayesClassifier __fromPtr__(long addr) { return new NormalBayesClassifier(addr); } // // C++: float cv::ml::NormalBayesClassifier::predictProb(Mat inputs, Mat& outputs, Mat& outputProbs, int flags = 0) // /** * Predicts the response for sample(s). * * The method estimates the most probable classes for input vectors. Input vectors (one or more) * are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one * output vector outputs. The predicted class for a single input vector is returned by the method. * The vector outputProbs contains the output probabilities corresponding to each element of * result. * @param inputs automatically generated * @param outputs automatically generated * @param outputProbs automatically generated * @param flags automatically generated * @return automatically generated */ public float predictProb(Mat inputs, Mat outputs, Mat outputProbs, int flags) { return predictProb_0(nativeObj, inputs.nativeObj, outputs.nativeObj, outputProbs.nativeObj, flags); } /** * Predicts the response for sample(s). * * The method estimates the most probable classes for input vectors. Input vectors (one or more) * are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one * output vector outputs. The predicted class for a single input vector is returned by the method. * The vector outputProbs contains the output probabilities corresponding to each element of * result. * @param inputs automatically generated * @param outputs automatically generated * @param outputProbs automatically generated * @return automatically generated */ public float predictProb(Mat inputs, Mat outputs, Mat outputProbs) { return predictProb_1(nativeObj, inputs.nativeObj, outputs.nativeObj, outputProbs.nativeObj); } // // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create() // /** * Creates empty model * Use StatModel::train to train the model after creation. * @return automatically generated */ public static NormalBayesClassifier create() { return NormalBayesClassifier.__fromPtr__(create_0()); } // // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::load(String filepath, String nodeName = String()) // /** * Loads and creates a serialized NormalBayesClassifier from a file * * Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk. * Load the NormalBayesClassifier from this file again, by calling this function with the path to the file. * Optionally specify the node for the file containing the classifier * * @param filepath path to serialized NormalBayesClassifier * @param nodeName name of node containing the classifier * @return automatically generated */ public static NormalBayesClassifier load(String filepath, String nodeName) { return NormalBayesClassifier.__fromPtr__(load_0(filepath, nodeName)); } /** * Loads and creates a serialized NormalBayesClassifier from a file * * Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk. * Load the NormalBayesClassifier from this file again, by calling this function with the path to the file. * Optionally specify the node for the file containing the classifier * * @param filepath path to serialized NormalBayesClassifier * @return automatically generated */ public static NormalBayesClassifier load(String filepath) { return NormalBayesClassifier.__fromPtr__(load_1(filepath)); } @Override protected void finalize() throws Throwable { delete(nativeObj); } // C++: float cv::ml::NormalBayesClassifier::predictProb(Mat inputs, Mat& outputs, Mat& outputProbs, int flags = 0) private static native float predictProb_0(long nativeObj, long inputs_nativeObj, long outputs_nativeObj, long outputProbs_nativeObj, int flags); private static native float predictProb_1(long nativeObj, long inputs_nativeObj, long outputs_nativeObj, long outputProbs_nativeObj); // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create() private static native long create_0(); // C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::load(String filepath, String nodeName = String()) private static native long load_0(String filepath, String nodeName); private static native long load_1(String filepath); // native support for java finalize() private static native void delete(long nativeObj); }