Class cv::FastFeatureDetector#

Wrapping class for feature detection using the FAST method. View details

#include <opencv2/features.hpp>

Collaboration diagram for cv::FastFeatureDetector:

Public Types#

enum cv::FastFeatureDetector {
    cv::THRESHOLD = 10000,
    cv::NONMAX_SUPPRESSION =10001,
    cv::FAST_N =10002
}

enum DetectorType {
    TYPE_5_8 = 0,
    TYPE_7_12 = 1,
    TYPE_9_16 = 2
}

Public Member Functions#

Public Member Functions inherited from cv::Feature2D

Return	Name	Description
	`~Feature2D()`
`void`	`compute(` `InputArray image,` `std::vector< KeyPoint > & keypoints,` `OutputArray descriptors )`	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
`void`	`compute(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `OutputArrayOfArrays descriptors )`
`int`	`defaultNorm()`
`int`	`descriptorSize()`
`int`	`descriptorType()`
`void`	`detect(` `InputArray image,` `std::vector< KeyPoint > & keypoints,` `InputArray mask = noArray() )`	Detects keypoints in an image (first variant) or image set (second variant).
`void`	`detect(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `InputArrayOfArrays masks = noArray() )`
`void`	`detectAndCompute(` `InputArray image,` `InputArray mask,` `std::vector< KeyPoint > & keypoints,` `OutputArray descriptors,` `bool useProvidedKeypoints = false )`
`bool`	`empty()`	Return true if detector object is empty.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`read(const String & fileName)`
`void`	`write(const String & fileName)`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	`Algorithm()`
	`~Algorithm()`
`void`	`clear()`	Clears the algorithm state.
`bool`	`empty()`	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`save(const String & filename)`
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name = String() )`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
`static Ptr< _Tp >`	`load(` `const String & filename,` `const String & objname = String() )`	Loads algorithm from the file.
`static Ptr< _Tp >`	`loadFromString(` `const String & strModel,` `const String & objname = String() )`	Loads algorithm from a String.
`static Ptr< _Tp >`	`read(const FileNode & fn)`	Reads algorithm from the file node.

Additional Inherited Members#

Detailed Description#

Wrapping class for feature detection using the FAST method.

Check the corresponding tutorial for more details.

Member Enumeration Documentation#

enum FastFeatureDetector

THRESHOLD

NONMAX_SUPPRESSION

FAST_N

enum DetectorType

TYPE_5_8
Python: cv.FastFeatureDetector_TYPE_5_8

TYPE_7_12
Python: cv.FastFeatureDetector_TYPE_7_12

TYPE_9_16
Python: cv.FastFeatureDetector_TYPE_9_16

Member Function Documentation#

create()#

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

Python:

cv.FastFeatureDetector.create([, threshold[, nonmaxSuppression[, type]]]) -> retval

cv.FastFeatureDetector_create([, threshold[, nonmaxSuppression[, type]]]) -> retval

getDefaultName()#

String cv::FastFeatureDetector::getDefaultName()

Python:

cv.FastFeatureDetector.getDefaultName() -> retval

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

getNonmaxSuppression()#

bool cv::FastFeatureDetector::getNonmaxSuppression()

Python:

cv.FastFeatureDetector.getNonmaxSuppression() -> retval

getThreshold()#

int cv::FastFeatureDetector::getThreshold()

Python:

cv.FastFeatureDetector.getThreshold() -> retval

getType()#

FastFeatureDetector::DetectorType cv::FastFeatureDetector::getType()

Python:

cv.FastFeatureDetector.getType() -> retval

setNonmaxSuppression()#

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

Python:

cv.FastFeatureDetector.setNonmaxSuppression(f)

setThreshold()#

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

Python:

cv.FastFeatureDetector.setThreshold(threshold)

setType()#

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

Python:

cv.FastFeatureDetector.setType(type)

Source file#

The documentation for this class was generated from the following file:

opencv2/features.hpp