OpenCV 4.11.0
开源计算机视觉
加载中…
搜索中…
无匹配项
cv::xfeatures2d::HarrisLaplaceFeatureDetector 类参考抽象类

实现Harris-Laplace特征检测器的类,如[192]中所述。 更多…

#include <opencv2/xfeatures2d.hpp>

cv::xfeatures2d::HarrisLaplaceFeatureDetector 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
 
- 继承自 cv::Feature2D 的公共成员函数
virtual ~Feature2D ()
 
virtual void compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
 计算在一幅图像(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
 将算法参数存储到文件存储中。
 
void write (FileStorage &fs, const String &name) const
 
- 继承自 cv::Algorithm 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

静态 Ptr< HarrisLaplaceFeatureDetector >create (int numOctaves=6, float corn_thresh=0.01f, float DOG_thresh=0.01f, int maxCorners=5000, int num_layers=4)
 创建一个新的实例。
 
- 继承自 cv::Algorithm 的静态公有成员函数
模板<typename _Tp >
静态 Ptr< _Tp >load (const String &filename, const String &objname=String())
 从文件中加载算法。
 
模板<typename _Tp >
静态 Ptr< _Tp >loadFromString (const String &strModel, const String &objname=String())
 从字符串加载算法。
 
模板<typename _Tp >
静态 Ptr< _Tp >read (const FileNode &fn)
 从文件节点读取算法。
 

其他继承成员

- 继承自 cv::Algorithm 的保护成员函数
void writeFormat (FileStorage &fs) const
 

详细描述

实现Harris-Laplace特征检测器的类,如[192]中所述。

成员函数文档

◆ create()

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

创建一个新的实例。

参数
numOctaves尺度空间金字塔中的octave数量
corn_threshHarris角点性度量的阈值
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octave的中间尺度数量

◆ getCornThresh()

虚函数 float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getCornThresh ( ) const
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.getCornThresh() -> 返回值

◆ getDefaultName()

String cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDefaultName ( ) const
虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.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。

重载自 cv::Feature2D.

◆ getDOGThresh()

虚函数 float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDOGThresh ( ) const
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.getDOGThresh() -> 返回值

◆ getMaxCorners()

虚函数 int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getMaxCorners ( ) const
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.getMaxCorners() -> 返回值

◆ getNumLayers()

虚函数 int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumLayers ( ) const
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumLayers() -> 返回值

◆ getNumOctaves()

虚函数 int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumOctaves ( ) const
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumOctaves() -> 返回值

◆ setCornThresh()

虚函数 void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setCornThresh ( float corn_thresh_)
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.setCornThresh(corn_thresh_) ->

◆ setDOGThresh()

虚函数 void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setDOGThresh ( float DOG_thresh_)
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.setDOGThresh(DOG_thresh_) ->

◆ setMaxCorners()

虚函数 void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setMaxCorners ( int maxCorners_)
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.setMaxCorners(maxCorners_) ->

◆ setNumLayers()

虚函数 void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumLayers ( int num_layers_)
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumLayers(num_layers_) ->

◆ setNumOctaves()

虚函数 void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumOctaves ( int numOctaves_)
纯虚函数
Python
cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumOctaves(numOctaves_) ->

此类的文档是从以下文件生成的: