org.opencv.ximgproc.SuperpixelLSC Maven / Gradle / Ivy
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//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.ximgproc;
import org.opencv.core.Algorithm;
import org.opencv.core.Mat;
// C++: class SuperpixelLSC
/**
* 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
*/
public class SuperpixelLSC extends Algorithm {
protected SuperpixelLSC(long addr) { super(addr); }
// internal usage only
public static SuperpixelLSC __fromPtr__(long addr) { return new SuperpixelLSC(addr); }
//
// C++: int cv::ximgproc::SuperpixelLSC::getNumberOfSuperpixels()
//
/**
* Calculates the actual amount of superpixels on a given segmentation computed
* and stored in SuperpixelLSC object.
* @return automatically generated
*/
public int getNumberOfSuperpixels() {
return getNumberOfSuperpixels_0(nativeObj);
}
//
// C++: void cv::ximgproc::SuperpixelLSC::iterate(int num_iterations = 10)
//
/**
* 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.
*
* @param 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.
*/
public void iterate(int num_iterations) {
iterate_0(nativeObj, num_iterations);
}
/**
* 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.
*
*
* 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.
*/
public void iterate() {
iterate_1(nativeObj);
}
//
// C++: void cv::ximgproc::SuperpixelLSC::getLabels(Mat& labels_out)
//
/**
* Returns the segmentation labeling of the image.
*
* Each label represents a superpixel, and each pixel is assigned to one superpixel label.
*
* @param 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()].
*/
public void getLabels(Mat labels_out) {
getLabels_0(nativeObj, labels_out.nativeObj);
}
//
// C++: void cv::ximgproc::SuperpixelLSC::getLabelContourMask(Mat& image, bool thick_line = true)
//
/**
* Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
*
* @param image Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border,
* and 0 otherwise.
*
* @param 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.
*/
public void getLabelContourMask(Mat image, boolean thick_line) {
getLabelContourMask_0(nativeObj, image.nativeObj, thick_line);
}
/**
* Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
*
* @param image Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border,
* and 0 otherwise.
*
* are masked.
*
* The function return the boundaries of the superpixel segmentation.
*/
public void getLabelContourMask(Mat image) {
getLabelContourMask_1(nativeObj, image.nativeObj);
}
//
// C++: void cv::ximgproc::SuperpixelLSC::enforceLabelConnectivity(int min_element_size = 25)
//
/**
* Enforce label connectivity.
*
* @param 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.
*/
public void enforceLabelConnectivity(int min_element_size) {
enforceLabelConnectivity_0(nativeObj, min_element_size);
}
/**
* Enforce label connectivity.
*
* 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.
*/
public void enforceLabelConnectivity() {
enforceLabelConnectivity_1(nativeObj);
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: int cv::ximgproc::SuperpixelLSC::getNumberOfSuperpixels()
private static native int getNumberOfSuperpixels_0(long nativeObj);
// C++: void cv::ximgproc::SuperpixelLSC::iterate(int num_iterations = 10)
private static native void iterate_0(long nativeObj, int num_iterations);
private static native void iterate_1(long nativeObj);
// C++: void cv::ximgproc::SuperpixelLSC::getLabels(Mat& labels_out)
private static native void getLabels_0(long nativeObj, long labels_out_nativeObj);
// C++: void cv::ximgproc::SuperpixelLSC::getLabelContourMask(Mat& image, bool thick_line = true)
private static native void getLabelContourMask_0(long nativeObj, long image_nativeObj, boolean thick_line);
private static native void getLabelContourMask_1(long nativeObj, long image_nativeObj);
// C++: void cv::ximgproc::SuperpixelLSC::enforceLabelConnectivity(int min_element_size = 25)
private static native void enforceLabelConnectivity_0(long nativeObj, int min_element_size);
private static native void enforceLabelConnectivity_1(long nativeObj);
// native support for java finalize()
private static native void delete(long nativeObj);
}