cv::FastFeatureDetector 类参考

使用 FAST 方法进行特征检测的包装类。: 更多…

#include <opencv2/features2d.hpp>

cv::FastFeatureDetector 的协作图

公共类型
枚举	{   THRESHOLD = 10000 ,   NONMAX_SUPPRESSION =10001 ,   FAST_N =10002 }
枚举	DetectorType {   TYPE_5_8 = 0 ,   TYPE_7_12 = 1 ,   TYPE_9_16 = 2 }

公共成员函数
virtual String	getDefaultName () const CV_OVERRIDE
virtual bool	getNonmaxSuppression () const =0
virtual int	getThreshold () const =0
virtual FastFeatureDetector::DetectorType	getType () const =0
virtual void	setNonmaxSuppression (bool f)=0
virtual void	setThreshold (int threshold)=0
virtual void	setType (FastFeatureDetector::DetectorType type)=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)
	计算在图像（第一种变体）或图像集（第二种变体）中检测到的关键点的描述符。
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())
	检测图像（第一种变体）或图像集（第二种变体）中的关键点。
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
	将算法参数存储在文件存储中。
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< FastFeatureDetector >	create (int threshold=10, bool nonmaxSuppression=true, FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16)
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。

继承的附加成员
从 cv::Algorithm 继承的受保护成员函数
void	writeFormat (FileStorage &fs) const

详细描述

使用FAST方法进行特征检测的包装类。

成员枚举文档

匿名枚举

匿名枚举

枚举器
THRESHOLD
NONMAX_SUPPRESSION
FAST_N

DetectorType

枚举 cv::FastFeatureDetector::DetectorType

枚举器
TYPE_5_8
TYPE_7_12
TYPE_9_16

成员函数文档

create()

static Ptr< FastFeatureDetector > cv::FastFeatureDetector::create ( int threshold = 10, bool nonmaxSuppression = true, FastFeatureDetector::DetectorType type = FastFeatureDetector::TYPE_9_16 )

静态

Python
	cv.FastFeatureDetector.create(	[, threshold[, nonmaxSuppression[, type]]]	) ->	返回值
	cv.FastFeatureDetector_create(	[, threshold[, nonmaxSuppression[, type]]]	) ->	返回值

getDefaultName()

virtual String cv::FastFeatureDetector::getDefaultName ( ) const

虚函数

Python
	cv.FastFeatureDetector.getDefaultName(		) ->	返回值

返回算法字符串标识符。将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。

getNonmaxSuppression()

virtual bool cv::FastFeatureDetector::getNonmaxSuppression ( ) const

纯虚函数

Python
	cv.FastFeatureDetector.getNonmaxSuppression(		) ->	返回值

getThreshold()

virtual int cv::FastFeatureDetector::getThreshold ( ) const

纯虚函数

Python
	cv.FastFeatureDetector.getThreshold(		) ->	返回值

getType()

virtual FastFeatureDetector::DetectorType cv::FastFeatureDetector::getType ( ) const

纯虚函数

Python
	cv.FastFeatureDetector.getType(		) ->	返回值

setNonmaxSuppression()

virtual void cv::FastFeatureDetector::setNonmaxSuppression ( bool f )

纯虚函数

Python
	cv.FastFeatureDetector.setNonmaxSuppression(	f	) ->	None

setThreshold()

virtual void cv::FastFeatureDetector::setThreshold ( int threshold )

纯虚函数

Python
	cv.FastFeatureDetector.setThreshold(	threshold	) ->	None

setType()

virtual void cv::FastFeatureDetector::setType ( FastFeatureDetector::DetectorType type )

纯虚函数

Python
	cv.FastFeatureDetector.setType(	type	) ->	None

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此类的文档是从以下文件生成的：

• opencv2/features2d.hpp