176 lines
6.0 KiB
Objective-C
176 lines
6.0 KiB
Objective-C
//
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// This file is auto-generated. Please don't modify it!
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//
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#pragma once
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#ifdef __cplusplus
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//#import "opencv.hpp"
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#import "opencv2/ximgproc.hpp"
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#import "opencv2/ximgproc/lsc.hpp"
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#else
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#define CV_EXPORTS
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#endif
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#import <Foundation/Foundation.h>
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#import "Algorithm.h"
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@class Mat;
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NS_ASSUME_NONNULL_BEGIN
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// C++: class SuperpixelLSC
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/**
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* Class implementing the LSC (Linear Spectral Clustering) superpixels
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* algorithm described in CITE: LiCVPR2015LSC.
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*
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* LSC (Linear Spectral Clustering) produces compact and uniform superpixels with low
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* computational costs. Basically, a normalized cuts formulation of the superpixel
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* segmentation is adopted based on a similarity metric that measures the color
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* similarity and space proximity between image pixels. LSC is of linear computational
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* complexity and high memory efficiency and is able to preserve global properties of images
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*
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* Member of `Ximgproc`
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*/
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CV_EXPORTS @interface SuperpixelLSC : Algorithm
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::ximgproc::SuperpixelLSC> nativePtrSuperpixelLSC;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::ximgproc::SuperpixelLSC>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::ximgproc::SuperpixelLSC>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// int cv::ximgproc::SuperpixelLSC::getNumberOfSuperpixels()
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//
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/**
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* Calculates the actual amount of superpixels on a given segmentation computed
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* and stored in SuperpixelLSC object.
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*/
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- (int)getNumberOfSuperpixels NS_SWIFT_NAME(getNumberOfSuperpixels());
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//
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// void cv::ximgproc::SuperpixelLSC::iterate(int num_iterations = 10)
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//
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/**
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* Calculates the superpixel segmentation on a given image with the initialized
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* parameters in the SuperpixelLSC object.
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*
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* This function can be called again without the need of initializing the algorithm with
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* createSuperpixelLSC(). This save the computational cost of allocating memory for all the
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* structures of the algorithm.
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*
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* @param num_iterations Number of iterations. Higher number improves the result.
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*
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* The function computes the superpixels segmentation of an image with the parameters initialized
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* with the function createSuperpixelLSC(). The algorithms starts from a grid of superpixels and
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* then refines the boundaries by proposing updates of edges boundaries.
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*/
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- (void)iterate:(int)num_iterations NS_SWIFT_NAME(iterate(num_iterations:));
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/**
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* Calculates the superpixel segmentation on a given image with the initialized
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* parameters in the SuperpixelLSC object.
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*
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* This function can be called again without the need of initializing the algorithm with
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* createSuperpixelLSC(). This save the computational cost of allocating memory for all the
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* structures of the algorithm.
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*
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*
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* The function computes the superpixels segmentation of an image with the parameters initialized
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* with the function createSuperpixelLSC(). The algorithms starts from a grid of superpixels and
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* then refines the boundaries by proposing updates of edges boundaries.
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*/
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- (void)iterate NS_SWIFT_NAME(iterate());
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//
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// void cv::ximgproc::SuperpixelLSC::getLabels(Mat& labels_out)
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//
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/**
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* Returns the segmentation labeling of the image.
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*
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* Each label represents a superpixel, and each pixel is assigned to one superpixel label.
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*
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* @param labels_out Return: A CV_32SC1 integer array containing the labels of the superpixel
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* segmentation. The labels are in the range [0, getNumberOfSuperpixels()].
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*
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* The function returns an image with the labels of the superpixel segmentation. The labels are in
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* the range [0, getNumberOfSuperpixels()].
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*/
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- (void)getLabels:(Mat*)labels_out NS_SWIFT_NAME(getLabels(labels_out:));
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//
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// void cv::ximgproc::SuperpixelLSC::getLabelContourMask(Mat& image, bool thick_line = true)
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//
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/**
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* Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
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*
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* @param image Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border,
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* and 0 otherwise.
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*
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* @param thick_line If false, the border is only one pixel wide, otherwise all pixels at the border
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* are masked.
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*
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* The function return the boundaries of the superpixel segmentation.
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*/
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- (void)getLabelContourMask:(Mat*)image thick_line:(BOOL)thick_line NS_SWIFT_NAME(getLabelContourMask(image:thick_line:));
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/**
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* Returns the mask of the superpixel segmentation stored in SuperpixelLSC object.
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*
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* @param image Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border,
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* and 0 otherwise.
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*
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* are masked.
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*
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* The function return the boundaries of the superpixel segmentation.
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*/
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- (void)getLabelContourMask:(Mat*)image NS_SWIFT_NAME(getLabelContourMask(image:));
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//
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// void cv::ximgproc::SuperpixelLSC::enforceLabelConnectivity(int min_element_size = 25)
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//
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/**
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* Enforce label connectivity.
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*
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* @param min_element_size The minimum element size in percents that should be absorbed into a bigger
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* superpixel. Given resulted average superpixel size valid value should be in 0-100 range, 25 means
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* that less then a quarter sized superpixel should be absorbed, this is default.
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*
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* The function merge component that is too small, assigning the previously found adjacent label
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* to this component. Calling this function may change the final number of superpixels.
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*/
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- (void)enforceLabelConnectivity:(int)min_element_size NS_SWIFT_NAME(enforceLabelConnectivity(min_element_size:));
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/**
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* Enforce label connectivity.
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*
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* superpixel. Given resulted average superpixel size valid value should be in 0-100 range, 25 means
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* that less then a quarter sized superpixel should be absorbed, this is default.
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*
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* The function merge component that is too small, assigning the previously found adjacent label
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* to this component. Calling this function may change the final number of superpixels.
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*/
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- (void)enforceLabelConnectivity NS_SWIFT_NAME(enforceLabelConnectivity());
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@end
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NS_ASSUME_NONNULL_END
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