cv::xfeatures2d::HarrisLaplaceFeatureDetector 類參考

實現 Harris-Laplace 特徵檢測器，如 [195] 中所述。 更多...

#include <opencv2/xfeatures2d.hpp>

cv::xfeatures2d::HarrisLaplaceFeatureDetector 的協作圖

公共成員函式
virtual float	getCornThresh () const =0
String	getDefaultName () const CV_OVERRIDE
virtual float	getDOGThresh () const =0
virtual int	getMaxCorners () const =0
virtual int	getNumLayers () const =0
virtual int	getNumOctaves () const =0
virtual void	setCornThresh (float corn_thresh_)=0
virtual void	setDOGThresh (float DOG_thresh_)=0
virtual void	setMaxCorners (int maxCorners_)=0
virtual void	setNumLayers (int num_layers_)=0
virtual void	setNumOctaves (int numOctaves_)=0
從 cv::Feature2D 繼承的公共成員函式
virtual	~Feature2D ()
virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
	計算影像（第一種變體）或影像集（第二種變體）中檢測到的一組關鍵點的描述符。
virtual void	compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
virtual int	defaultNorm () const
virtual int	descriptorSize () const
virtual int	descriptorType () const
virtual void	detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
	在影像（第一種變體）或影像集（第二種變體）中檢測關鍵點。
virtual void	detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
virtual bool	empty () const CV_OVERRIDE
	如果檢測器物件為空，則返回 true。
virtual void	read (const FileNode &) CV_OVERRIDE
	從檔案儲存中讀取演算法引數。
void	read (const String &fileName)
void	write (const Ptr< FileStorage > &fs, const String &name) const
void	write (const String &fileName) const
virtual void	write (FileStorage &) const CV_OVERRIDE
	將演算法引數儲存到檔案儲存中。
void	write (FileStorage &fs, const String &name) const
從 cv::Algorithm 繼承的公共成員函式
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	清除演算法狀態。
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
void	write (FileStorage &fs, const String &name) const

靜態公共成員函式
static Ptr< HarrisLaplaceFeatureDetector >	create (int numOctaves=6, float corn_thresh=0.01f, float DOG_thresh=0.01f, int maxCorners=5000, int num_layers=4)
	建立新的實現例項。
從 cv::Algorithm 繼承的靜態公共成員函式
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	從檔案中載入演算法。
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	從字串載入演算法。
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	從檔案節點讀取演算法。

附加的繼承成員
從 cv::Algorithm 繼承的保護成員函式
void	writeFormat (FileStorage &fs) const

詳細描述

實現 Harris-Laplace 特徵檢測器，如 [195] 中所述。

成員函式文件

create()

static Ptr< HarrisLaplaceFeatureDetector > cv::xfeatures2d::HarrisLaplaceFeatureDetector::create ( int numOctaves = 6, float corn_thresh = 0.01f, float DOG_thresh = 0.01f, int maxCorners = 5000, int num_layers = 4 )

static

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.create(	[, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]]	) ->	retval
	cv.xfeatures2d.HarrisLaplaceFeatureDetector_create(	[, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]]	) ->	retval

建立新的實現例項。

引數

numOctaves	尺度空間金字塔中的八度音階數
corn_thresh	Harris 角點響應的閾值
DOG_thresh	高斯差分尺度選擇的閾值
maxCorners	要考慮的最大角點數
num_layers	每個八度音階的中間尺度數

getCornThresh()

virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getCornThresh ( ) const

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getCornThresh(		) ->	retval

getDefaultName()

String cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDefaultName ( ) const

virtual

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getDefaultName(		) ->	retval

返回演算法字串識別符號。當物件儲存到檔案或字串時，此字串用作頂級 xml/yml 節點標籤。

從 cv::Feature2D 重新實現。

getDOGThresh()

virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDOGThresh ( ) const

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getDOGThresh(		) ->	retval

getMaxCorners()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getMaxCorners ( ) const

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getMaxCorners(		) ->	retval

getNumLayers()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumLayers ( ) const

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumLayers(		) ->	retval

getNumOctaves()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumOctaves ( ) const

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumOctaves(		) ->	retval

setCornThresh()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setCornThresh ( float corn_thresh_ )

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.setCornThresh(	corn_thresh_	) ->	無

setDOGThresh()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setDOGThresh ( float DOG_thresh_ )

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.setDOGThresh(	DOG_thresh_	) ->	無

setMaxCorners()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setMaxCorners ( int maxCorners_ )

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.setMaxCorners(	maxCorners_	) ->	無

setNumLayers()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumLayers ( int num_layers_ )

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumLayers(	num_layers_	) ->	無

setNumOctaves()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumOctaves ( int numOctaves_ )

純虛擬函式

Python
	cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumOctaves(	numOctaves_	) ->	無

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此類文件由以下檔案生成

• opencv2/xfeatures2d.hpp