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公共成员函数 | 静态公共成员函数 | 所有成员列表
cv::GFTTDetector 类参考抽象
2D 特征框架 » 特征检测与描述

goodFeaturesToTrack 函数的特征检测封装类。： 更多...

#include <opencv2/features2d.hpp>

cv::GFTTDetector 关联图

公共成员函数

virtual int getBlockSize () const =0
 
virtual String getDefaultName () const CV_OVERRIDE
 
virtual int getGradientSize ()=0
 
virtual bool getHarrisDetector () const =0
 
virtual double getK () const =0
 
virtual int getMaxFeatures () const =0
 
virtual double getMinDistance () const =0
 
virtual double getQualityLevel () const =0
 
virtual void setBlockSize (int blockSize)=0
 
virtual void setGradientSize (int gradientSize_)=0
 
virtual void setHarrisDetector (bool val)=0
 
virtual void setK (double k)=0
 
virtual void setMaxFeatures (int maxFeatures)=0
 
virtual void setMinDistance (double minDistance)=0
 
virtual void setQualityLevel (double qlevel)=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)
 计算图像中检测到的关键点的描述符（第一种变体）或图像集（第二种变体）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 检测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 继承的公有成员函数
 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
 

静态公有成员函数

静态 Ptr< GFTTDetector > create (int maxCorners, double qualityLevel, double minDistance, int blockSize, int gradiantSize, bool useHarrisDetector=false, double k=0.04)
 
静态 Ptr< GFTTDetector > create (int maxCorners=1000, double qualityLevel=0.01, double minDistance=1, int blockSize=3, bool useHarrisDetector=false, double k=0.04)
 
- 从 cv::Algorithm 继承的静态公共成员函数
template<typename _Tp >
静态 Ptr< _Tp > load (const String &filename, const String &objname=String())
 从文件加载算法。
 
template<typename _Tp >
静态 Ptr< _Tp > loadFromString (const String &strModel, const String &objname=String())
 从字符串加载算法。
 
template<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

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

详细描述

使用 goodFeaturesToTrack 函数进行特征检测的包装类。

成员函数文档

◆ create() [1/2]

静态 Ptr< GFTTDetector > cv::GFTTDetector::create ( int  maxCorners,
double  qualityLevel,
double  minDistance,
int  blockSize,
int  gradiantSize,
bool  useHarrisDetector = false,
double  k = 0.04 
)
static
Python
cv.GFTTDetector.create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval
cv.GFTTDetector.create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval
cv.GFTTDetector_create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval
cv.GFTTDetector_create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval

◆ create() [2/2]

静态 Ptr< GFTTDetector > cv::GFTTDetector::create ( int  maxCorners = 1000,
double  qualityLevel = 0.01,
double  minDistance = 1,
int  blockSize = 3,
bool  useHarrisDetector = false,
double  k = 0.04 
)
static
Python
cv.GFTTDetector.create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval
cv.GFTTDetector.create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval
cv.GFTTDetector_create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval
cv.GFTTDetector_create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval

◆ getBlockSize()

virtual int cv::GFTTDetector::getBlockSize ( ) const
纯虚
Python
cv.GFTTDetector.getBlockSize() -> retval

◆ getDefaultName()

virtual String cv::GFTTDetector::getDefaultName ( ) const
virtual
Python
cv.GFTTDetector.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 继承重写。

◆ getGradientSize()

virtual int cv::GFTTDetector::getGradientSize ( )
纯虚
Python
cv.GFTTDetector.getGradientSize() -> retval

◆ getHarrisDetector()

virtual bool cv::GFTTDetector::getHarrisDetector ( ) const
纯虚
Python
cv.GFTTDetector.getHarrisDetector() -> retval

◆ getK()

virtual double cv::GFTTDetector::getK ( ) const
纯虚
Python
cv.GFTTDetector.getK() -> retval

◆ getMaxFeatures()

virtual int cv::GFTTDetector::getMaxFeatures ( ) const
纯虚
Python
cv.GFTTDetector.getMaxFeatures() -> retval

◆ getMinDistance()

virtual double cv::GFTTDetector::getMinDistance ( ) const
纯虚
Python
cv.GFTTDetector.getMinDistance() -> retval

◆ getQualityLevel()

virtual double cv::GFTTDetector::getQualityLevel ( ) const
纯虚
Python
cv.GFTTDetector.getQualityLevel() -> retval

◆ setBlockSize()

virtual void cv::GFTTDetector::setBlockSize ( int  blockSize)
纯虚
Python
cv.GFTTDetector.setBlockSize(blockSize) -> None

◆ setGradientSize()

virtual void cv::GFTTDetector::setGradientSize ( int  gradientSize_)
纯虚
Python
cv.GFTTDetector.setGradientSize(gradientSize_) -> None

◆ setHarrisDetector()

virtual void cv::GFTTDetector::setHarrisDetector ( bool  val)
纯虚
Python
cv.GFTTDetector.setHarrisDetector(val) -> None

◆ setK()

virtual void cv::GFTTDetector::setK ( double  k)
纯虚
Python
cv.GFTTDetector.setK(k) -> None

◆ setMaxFeatures()

virtual void cv::GFTTDetector::setMaxFeatures ( int  maxFeatures)
纯虚
Python
cv.GFTTDetector.setMaxFeatures(maxFeatures) -> None

◆ setMinDistance()

virtual void cv::GFTTDetector::setMinDistance ( double  minDistance)
纯虚
Python
cv.GFTTDetector.setMinDistance(minDistance) -> None

◆ setQualityLevel()

virtual void cv::GFTTDetector::setQualityLevel ( double  qlevel)
纯虚
Python
cv.GFTTDetector.setQualityLevel(qlevel) -> None
本类的文档是从以下文件生成的：
2024年6月2日星期日 21:52:15 为 OpenCV 生成
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