OpenCV  4.9.0-dev
Open Source Computer Vision
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Classes | Namespaces | Typedefs | Enumerations | Functions
features2d.hpp File Reference
#include "opencv2/opencv_modules.hpp"
#include "opencv2/core.hpp"
Include dependency graph for features2d.hpp:
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Classes

struct  cv::Accumulator< T >
 
struct  cv::Accumulator< char >
 
struct  cv::Accumulator< short >
 
struct  cv::Accumulator< unsigned char >
 
struct  cv::Accumulator< unsigned short >
 
class  cv::AffineFeature
 Class for implementing the wrapper which makes detectors and extractors to be affine invariant, described as ASIFT in [307] . More...
 
class  cv::AgastFeatureDetector
 Wrapping class for feature detection using the AGAST method. : More...
 
class  cv::AKAZE
 Class implementing the AKAZE keypoint detector and descriptor extractor, described in [10]. More...
 
class  cv::BFMatcher
 Brute-force descriptor matcher. More...
 
class  cv::BOWImgDescriptorExtractor
 Class to compute an image descriptor using the bag of visual words. More...
 
class  cv::BOWKMeansTrainer
 kmeans -based class to train visual vocabulary using the bag of visual words approach. : More...
 
class  cv::BOWTrainer
 Abstract base class for training the bag of visual words vocabulary from a set of descriptors. More...
 
class  cv::BRISK
 Class implementing the BRISK keypoint detector and descriptor extractor, described in [154] . More...
 
class  cv::DescriptorMatcher::DescriptorCollection
 
class  cv::DescriptorMatcher
 Abstract base class for matching keypoint descriptors. More...
 
class  cv::FastFeatureDetector
 Wrapping class for feature detection using the FAST method. : More...
 
class  cv::Feature2D
 Abstract base class for 2D image feature detectors and descriptor extractors. More...
 
class  cv::FlannBasedMatcher
 Flann-based descriptor matcher. More...
 
class  cv::GFTTDetector
 Wrapping class for feature detection using the goodFeaturesToTrack function. : More...
 
class  cv::KAZE
 Class implementing the KAZE keypoint detector and descriptor extractor, described in [9] . More...
 
class  cv::KeyPointsFilter
 A class filters a vector of keypoints. More...
 
struct  cv::L1< T >
 
struct  cv::L2< T >
 
class  cv::MSER
 Maximally stable extremal region extractor. More...
 
class  cv::ORB
 Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor. More...
 
struct  cv::SimpleBlobDetector::Params
 
class  cv::SIFT
 Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [169] . More...
 
class  cv::SimpleBlobDetector
 Class for extracting blobs from an image. : More...
 
struct  cv::SL2< T >
 

Namespaces

namespace  cv
 "black box" representation of the file storage associated with a file on disk.
 

Typedefs

typedef AffineFeature cv::AffineDescriptorExtractor
 
typedef AffineFeature cv::AffineFeatureDetector
 
typedef Feature2D cv::DescriptorExtractor
 
typedef Feature2D cv::FeatureDetector
 
typedef SIFT cv::SiftDescriptorExtractor
 
typedef SIFT cv::SiftFeatureDetector
 

Enumerations

enum struct  cv::DrawMatchesFlags {
  cv::DrawMatchesFlags::DEFAULT = 0 ,
  cv::DrawMatchesFlags::DRAW_OVER_OUTIMG = 1 ,
  cv::DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS = 2 ,
  cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS = 4
}
 

Functions

void cv::AGAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression, AgastFeatureDetector::DetectorType type)
 Detects corners using the AGAST algorithm.
 
void cv::AGAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true)
 
void cv::computeRecallPrecisionCurve (const std::vector< std::vector< DMatch > > &matches1to2, const std::vector< std::vector< uchar > > &correctMatches1to2Mask, std::vector< Point2f > &recallPrecisionCurve)
 
void cv::drawKeypoints (InputArray image, const std::vector< KeyPoint > &keypoints, InputOutputArray outImage, const Scalar &color=Scalar::all(-1), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
 Draws keypoints.
 
void cv::drawMatches (InputArray img1, const std::vector< KeyPoint > &keypoints1, InputArray img2, const std::vector< KeyPoint > &keypoints2, const std::vector< DMatch > &matches1to2, InputOutputArray outImg, const int matchesThickness, const Scalar &matchColor=Scalar::all(-1), const Scalar &singlePointColor=Scalar::all(-1), const std::vector< char > &matchesMask=std::vector< char >(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
 
void cv::drawMatches (InputArray img1, const std::vector< KeyPoint > &keypoints1, InputArray img2, const std::vector< KeyPoint > &keypoints2, const std::vector< DMatch > &matches1to2, InputOutputArray outImg, const Scalar &matchColor=Scalar::all(-1), const Scalar &singlePointColor=Scalar::all(-1), const std::vector< char > &matchesMask=std::vector< char >(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
 Draws the found matches of keypoints from two images.
 
void cv::drawMatches (InputArray img1, const std::vector< KeyPoint > &keypoints1, InputArray img2, const std::vector< KeyPoint > &keypoints2, const std::vector< std::vector< DMatch > > &matches1to2, InputOutputArray outImg, const Scalar &matchColor=Scalar::all(-1), const Scalar &singlePointColor=Scalar::all(-1), const std::vector< std::vector< char > > &matchesMask=std::vector< std::vector< char > >(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
 
void cv::evaluateFeatureDetector (const Mat &img1, const Mat &img2, const Mat &H1to2, std::vector< KeyPoint > *keypoints1, std::vector< KeyPoint > *keypoints2, float &repeatability, int &correspCount, const Ptr< FeatureDetector > &fdetector=Ptr< FeatureDetector >())
 
void cv::FAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression, FastFeatureDetector::DetectorType type)
 Detects corners using the FAST algorithm.
 
void cv::FAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true)
 
int cv::getNearestPoint (const std::vector< Point2f > &recallPrecisionCurve, float l_precision)
 
float cv::getRecall (const std::vector< Point2f > &recallPrecisionCurve, float l_precision)