cv::xfeatures2d::HarrisLaplaceFeatureDetector 类参考

实现 Harris-Laplace 特征检测器，如 [195] 中所述。 更多...

#include <opencv2/xfeatures2d.hpp>

cv::xfeatures2d::HarrisLaplaceFeatureDetector 的协作图

公共成员函数
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
从 cv::Feature2D 继承的公共成员函数
virtual	~Feature2D ()
virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
	计算图像（第一种变体）或图像集（第二种变体）中检测到的一组关键点的描述符。
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())
	在图像（第一种变体）或图像集（第二种变体）中检测关键点。
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
	如果检测器对象为空，则返回 true。
virtual void	read (const FileNode &) CV_OVERRIDE
	从文件存储中读取算法参数。
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
	将算法参数存储到文件存储中。
void	write (FileStorage &fs, const String &name) const
从 cv::Algorithm 继承的公共成员函数
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	清除算法状态。
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

静态公共成员函数
static Ptr< HarrisLaplaceFeatureDetector >	create (int numOctaves=6, float corn_thresh=0.01f, float DOG_thresh=0.01f, int maxCorners=5000, int num_layers=4)
	创建新的实现实例。
从 cv::Algorithm 继承的静态公共成员函数
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	从文件中加载算法。
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	从字符串加载算法。
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	从文件节点读取算法。

附加的继承成员
从 cv::Algorithm 继承的保护成员函数
void	writeFormat (FileStorage &fs) const

详细描述

实现 Harris-Laplace 特征检测器，如 [195] 中所述。

成员函数文档

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

创建新的实现实例。

参数

numOctaves	尺度空间金字塔中的八度音阶数
corn_thresh	Harris 角点响应的阈值
DOG_thresh	高斯差分尺度选择的阈值
maxCorners	要考虑的最大角点数
num_layers	每个八度音阶的中间尺度数

getCornThresh()

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

纯虚函数

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

getDefaultName()

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

virtual

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

返回算法字符串标识符。当对象保存到文件或字符串时，此字符串用作顶级 xml/yml 节点标签。

从 cv::Feature2D 重新实现。

getDOGThresh()

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

纯虚函数

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

getMaxCorners()

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

纯虚函数

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

getNumLayers()

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

纯虚函数

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

getNumOctaves()

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

纯虚函数

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

setCornThresh()

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

纯虚函数

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

setDOGThresh()

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

纯虚函数

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

setMaxCorners()

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

纯虚函数

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

setNumLayers()

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

纯虚函数

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

setNumOctaves()

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

纯虚函数

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

---

此类文档由以下文件生成

• opencv2/xfeatures2d.hpp