org.bytedeco.opencv.opencv_face

Class FacemarkKazemi

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.opencv.opencv_core.Algorithm

org.bytedeco.opencv.opencv_face.Facemark

org.bytedeco.opencv.opencv_face.FacemarkKazemi

All Implemented Interfaces:

AutoCloseable

@Namespace(value="cv::face")
 @Properties(inherit=opencv_face.class)
public class FacemarkKazemi
extends Facemark

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	FacemarkKazemi.Params

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

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
FacemarkKazemi(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
static FacemarkKazemi	create()
static FacemarkKazemi	create(FacemarkKazemi.Params parameters)
boolean	getFaces(Mat image, RectVector faces) get faces using the custom detector
boolean	setFaceDetector(Pointer f, Pointer userData) set the custom face detector
boolean	training(MatVector images, Point2fVectorVector landmarks, BytePointer configfile, Size scale)
boolean	training(MatVector images, Point2fVectorVector landmarks, BytePointer configfile, Size scale, BytePointer modelFilename) \brief This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape.
boolean	training(MatVector images, Point2fVectorVector landmarks, String configfile, Size scale)
boolean	training(MatVector images, Point2fVectorVector landmarks, String configfile, Size scale, String modelFilename)

Methods inherited from class org.bytedeco.opencv.opencv_face.Facemark

fit, loadModel, loadModel

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

clear, empty, 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, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

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

Constructor Detail

FacemarkKazemi

public FacemarkKazemi(Pointer p)

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

Method Detail

create

@opencv_core.Ptr
public static FacemarkKazemi create(@Const @ByRef(nullValue="cv::face::FacemarkKazemi::Params()")
                                                     FacemarkKazemi.Params parameters)

create

@opencv_core.Ptr
public static FacemarkKazemi create()

training

@Cast(value="bool")
public boolean training(@ByRef
                                            MatVector images,
                                            @ByRef
                                            Point2fVectorVector landmarks,
                                            @StdString
                                            BytePointer configfile,
                                            @ByVal
                                            Size scale,
                                            @StdString
                                            BytePointer modelFilename)

\brief This function is used to train the model using gradient boosting to get a cascade of regressors which can then be used to predict shape.

Parameters:

images - A vector of type cv::Mat which stores the images which are used in training samples.

landmarks - A vector of vectors of type cv::Point2f which stores the landmarks detected in a particular image.

scale - A size of type cv::Size to which all images and landmarks have to be scaled to.

configfile - A variable of type std::string which stores the name of the file storing parameters for training the model.

modelFilename - A variable of type std::string which stores the name of the trained model file that has to be saved.

Returns:

A boolean value. The function returns true if the model is trained properly or false if it is not trained.

training

@Cast(value="bool")
public boolean training(@ByRef
                                            MatVector images,
                                            @ByRef
                                            Point2fVectorVector landmarks,
                                            @StdString
                                            BytePointer configfile,
                                            @ByVal
                                            Size scale)

training

@Cast(value="bool")
public boolean training(@ByRef
                                            MatVector images,
                                            @ByRef
                                            Point2fVectorVector landmarks,
                                            @StdString
                                            String configfile,
                                            @ByVal
                                            Size scale,
                                            @StdString
                                            String modelFilename)

training

@Cast(value="bool")
public boolean training(@ByRef
                                            MatVector images,
                                            @ByRef
                                            Point2fVectorVector landmarks,
                                            @StdString
                                            String configfile,
                                            @ByVal
                                            Size scale)

setFaceDetector

@Cast(value="bool")
public boolean setFaceDetector(@Cast(value="bool (*)(cv::InputArray, cv::OutputArray, void*)")
                                                   Pointer f,
                                                   Pointer userData)

set the custom face detector

getFaces

@Cast(value="bool")
public boolean getFaces(@ByVal
                                            Mat image,
                                            @ByRef
                                            RectVector faces)

get faces using the custom detector