org.bytedeco.javacpp

Class opencv_ml.NormalBayesClassifier

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.opencv_core.Algorithm

org.bytedeco.javacpp.helper.opencv_ml.AbstractStatModel

org.bytedeco.javacpp.opencv_ml.StatModel

org.bytedeco.javacpp.opencv_ml.NormalBayesClassifier

All Implemented Interfaces:

AutoCloseable

Enclosing class:

opencv_ml

@Namespace(value="cv::ml")
public static class opencv_ml.NormalBayesClassifier
extends opencv_ml.StatModel

\brief Bayes classifier for normally distributed data.

\sa \ref ml_intro_bayes

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.Pointer.CustomDeallocator, org.bytedeco.javacpp.Pointer.Deallocator, org.bytedeco.javacpp.Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.opencv_ml.StatModel

COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
NormalBayesClassifier(org.bytedeco.javacpp.Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
static opencv_ml.NormalBayesClassifier	create() Creates empty model Use StatModel::train to train the model after creation.
static opencv_ml.NormalBayesClassifier	load(org.bytedeco.javacpp.BytePointer filepath)
static opencv_ml.NormalBayesClassifier	load(org.bytedeco.javacpp.BytePointer filepath, org.bytedeco.javacpp.BytePointer nodeName) \brief Loads and creates a serialized NormalBayesClassifier from a file Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
static opencv_ml.NormalBayesClassifier	load(String filepath)
static opencv_ml.NormalBayesClassifier	load(String filepath, String nodeName)
float	predictProb(opencv_core.GpuMat inputs, opencv_core.GpuMat outputs, opencv_core.GpuMat outputProbs)
float	predictProb(opencv_core.GpuMat inputs, opencv_core.GpuMat outputs, opencv_core.GpuMat outputProbs, int flags)
float	predictProb(opencv_core.Mat inputs, opencv_core.Mat outputs, opencv_core.Mat outputProbs)
float	predictProb(opencv_core.Mat inputs, opencv_core.Mat outputs, opencv_core.Mat outputProbs, int flags) \brief Predicts the response for sample(s).
float	predictProb(opencv_core.UMat inputs, opencv_core.UMat outputs, opencv_core.UMat outputProbs)
float	predictProb(opencv_core.UMat inputs, opencv_core.UMat outputs, opencv_core.UMat outputProbs, int flags)

Methods inherited from class org.bytedeco.javacpp.opencv_ml.StatModel

calcError, calcError, calcError, empty, getVarCount, isClassifier, isTrained, predict, predict, predict, predict, predict, predict, train, train, train, train, train

Methods inherited from class org.bytedeco.javacpp.helper.opencv_ml.AbstractStatModel

loadANN_MLP, loadANN_MLP, loadBoost, loadBoost, loadDTrees, loadDTrees, loadEM, loadEM, loadKNearest, loadKNearest, loadLogisticRegression, loadLogisticRegression, loadNormalBayesClassifier, loadNormalBayesClassifier, loadRTrees, loadRTrees, loadSVM, loadSVM

Methods inherited from class org.bytedeco.javacpp.opencv_core.Algorithm

clear, getDefaultName, position, read, save, save, write, write, write

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

NormalBayesClassifier

public NormalBayesClassifier(org.bytedeco.javacpp.Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

Method Detail

predictProb

public float predictProb(@ByVal
                         opencv_core.Mat inputs,
                         @ByVal
                         opencv_core.Mat outputs,
                         @ByVal
                         opencv_core.Mat outputProbs,
                         int flags)

\brief 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.

predictProb

public float predictProb(@ByVal
                         opencv_core.Mat inputs,
                         @ByVal
                         opencv_core.Mat outputs,
                         @ByVal
                         opencv_core.Mat outputProbs)

predictProb

public float predictProb(@ByVal
                         opencv_core.UMat inputs,
                         @ByVal
                         opencv_core.UMat outputs,
                         @ByVal
                         opencv_core.UMat outputProbs,
                         int flags)

predictProb

public float predictProb(@ByVal
                         opencv_core.UMat inputs,
                         @ByVal
                         opencv_core.UMat outputs,
                         @ByVal
                         opencv_core.UMat outputProbs)

predictProb

public float predictProb(@ByVal
                         opencv_core.GpuMat inputs,
                         @ByVal
                         opencv_core.GpuMat outputs,
                         @ByVal
                         opencv_core.GpuMat outputProbs,
                         int flags)

predictProb

public float predictProb(@ByVal
                         opencv_core.GpuMat inputs,
                         @ByVal
                         opencv_core.GpuMat outputs,
                         @ByVal
                         opencv_core.GpuMat outputProbs)

create

@opencv_core.Ptr
public static opencv_ml.NormalBayesClassifier create()

Creates empty model Use StatModel::train to train the model after creation.

load

@opencv_core.Ptr
public static opencv_ml.NormalBayesClassifier load(@opencv_core.Str
                                                                    org.bytedeco.javacpp.BytePointer filepath,
                                                                    @opencv_core.Str
                                                                    org.bytedeco.javacpp.BytePointer nodeName)

\brief 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

Parameters:

filepath - path to serialized NormalBayesClassifier

nodeName - name of node containing the classifier

load

@opencv_core.Ptr
public static opencv_ml.NormalBayesClassifier load(@opencv_core.Str
                                                                    org.bytedeco.javacpp.BytePointer filepath)

load

@opencv_core.Ptr
public static opencv_ml.NormalBayesClassifier load(@opencv_core.Str
                                                                    String filepath,
                                                                    @opencv_core.Str
                                                                    String nodeName)

load

@opencv_core.Ptr
public static opencv_ml.NormalBayesClassifier load(@opencv_core.Str
                                                                    String filepath)