org.bytedeco.opencv.opencv_ximgproc

Class SuperpixelLSC

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.opencv.opencv_core.Algorithm

org.bytedeco.opencv.opencv_ximgproc.SuperpixelLSC

All Implemented Interfaces:

AutoCloseable

@Namespace(value="cv::ximgproc")
 @Properties(inherit=opencv_ximgproc.class)
public class SuperpixelLSC
extends Algorithm

\addtogroup ximgproc_superpixel \{

/** \brief Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in \cite LiCVPR2015LSC.

LSC (Linear Spectral Clustering) produces compact and uniform superpixels with low computational costs. Basically, a normalized cuts formulation of the superpixel segmentation is adopted based on a similarity metric that measures the color similarity and space proximity between image pixels. LSC is of linear computational complexity and high memory efficiency and is able to preserve global properties of images

Nested Class Summary

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
SuperpixelLSC(Algorithm pointer) Downcast constructor.
SuperpixelLSC(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
Algorithm	asAlgorithm()
static Algorithm	asAlgorithm(SuperpixelLSC pointer)
void	enforceLabelConnectivity()
void	enforceLabelConnectivity(int min_element_size) \brief Enforce label connectivity.
void	getLabelContourMask(GpuMat image)
void	getLabelContourMask(GpuMat image, boolean thick_line)
void	getLabelContourMask(Mat image)
void	getLabelContourMask(Mat image, boolean thick_line) \brief Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
void	getLabelContourMask(UMat image)
void	getLabelContourMask(UMat image, boolean thick_line)
void	getLabels(GpuMat labels_out)
void	getLabels(Mat labels_out) \brief Returns the segmentation labeling of the image.
void	getLabels(UMat labels_out)
int	getNumberOfSuperpixels() \brief Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelLSC object.
void	iterate()
void	iterate(int num_iterations) \brief Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.

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

clear, empty, getDefaultName, getPointer, 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, getDirectBufferAddress, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

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

Constructor Detail

SuperpixelLSC

public SuperpixelLSC(Pointer p)

Pointer cast constructor. Invokes Pointer(Pointer).

SuperpixelLSC

public SuperpixelLSC(Algorithm pointer)

Downcast constructor.

Method Detail

asAlgorithm

public Algorithm asAlgorithm()

Overrides:

asAlgorithm in class Algorithm

asAlgorithm

@Namespace
 @Name(value="static_cast<cv::Algorithm*>")
public static Algorithm asAlgorithm(SuperpixelLSC pointer)

getNumberOfSuperpixels

public int getNumberOfSuperpixels()

\brief Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelLSC object.

iterate

public void iterate(int num_iterations)

\brief Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelLSC object.

This function can be called again without the need of initializing the algorithm with createSuperpixelLSC(). This save the computational cost of allocating memory for all the structures of the algorithm.

Parameters:

num_iterations - Number of iterations. Higher number improves the result.

The function computes the superpixels segmentation of an image with the parameters initialized with the function createSuperpixelLSC(). The algorithms starts from a grid of superpixels and then refines the boundaries by proposing updates of edges boundaries.

iterate

public void iterate()

getLabels

public void getLabels(@ByVal
                      Mat labels_out)

\brief Returns the segmentation labeling of the image.

Each label represents a superpixel, and each pixel is assigned to one superpixel label.

Parameters:

labels_out - Return: A CV_32SC1 integer array containing the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].

The function returns an image with the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].

getLabels

public void getLabels(@ByVal
                      UMat labels_out)

getLabels

public void getLabels(@ByVal
                      GpuMat labels_out)

getLabelContourMask

public void getLabelContourMask(@ByVal
                                Mat image,
                                @Cast(value="bool")
                                boolean thick_line)

\brief Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.

Parameters:

image - Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border, and 0 otherwise.

thick_line - If false, the border is only one pixel wide, otherwise all pixels at the border are masked.

The function return the boundaries of the superpixel segmentation.

getLabelContourMask

public void getLabelContourMask(@ByVal
                                Mat image)

getLabelContourMask

public void getLabelContourMask(@ByVal
                                UMat image,
                                @Cast(value="bool")
                                boolean thick_line)

getLabelContourMask

public void getLabelContourMask(@ByVal
                                UMat image)

getLabelContourMask

public void getLabelContourMask(@ByVal
                                GpuMat image,
                                @Cast(value="bool")
                                boolean thick_line)

getLabelContourMask

public void getLabelContourMask(@ByVal
                                GpuMat image)

enforceLabelConnectivity

public void enforceLabelConnectivity(int min_element_size)

\brief Enforce label connectivity.

Parameters:

min_element_size - The minimum element size in percents that should be absorbed into a bigger superpixel. Given resulted average superpixel size valid value should be in 0-100 range, 25 means that less then a quarter sized superpixel should be absorbed, this is default.

The function merge component that is too small, assigning the previously found adjacent label to this component. Calling this function may change the final number of superpixels.

enforceLabelConnectivity

public void enforceLabelConnectivity()