Class cv::LightGlueMatcher#

LightGlue feature matcher. View details

#include <opencv2/features.hpp>

Collaboration diagram for cv::LightGlueMatcher:

Public Types#

Public Member Functions#

Public Member Functions inherited from cv::DescriptorMatcher

Return	Name	Description
	`~DescriptorMatcher()`
`void`	`add(InputArrayOfArrays descriptors)`	Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.
`void`	`clear()`	Clears the train descriptor collections.
`CV_NODISCARD_STD Ptr< DescriptorMatcher >`	`clone(bool emptyTrainData = false)`	Clones the matcher.
`bool`	`empty()`	Returns true if there are no train descriptors in the both collections.
`const std::vector< Mat > &`	`getTrainDescriptors()`	Returns a constant link to the train descriptor collection trainDescCollection .
`bool`	`isMaskSupported()`	Returns true if the descriptor matcher supports masking permissible matches.
`void`	`knnMatch(` `InputArray queryDescriptors,` `InputArray trainDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `int k,` `InputArray mask = noArray(),` `bool compactResult = false )`	Finds the k best matches for each descriptor from a query set.
`void`	`knnMatch(` `InputArray queryDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `int k,` `InputArrayOfArrays masks = noArray(),` `bool compactResult = false )`
`void`	`match(` `InputArray queryDescriptors,` `InputArray trainDescriptors,` `std::vector< DMatch > & matches,` `InputArray mask = noArray() )`	Finds the best match for each descriptor from a query set.
`void`	`match(` `InputArray queryDescriptors,` `std::vector< DMatch > & matches,` `InputArrayOfArrays masks = noArray() )`
`void`	`radiusMatch(` `InputArray queryDescriptors,` `InputArray trainDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `float maxDistance,` `InputArray mask = noArray(),` `bool compactResult = false )`	For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	`radiusMatch(` `InputArray queryDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `float maxDistance,` `InputArrayOfArrays masks = noArray(),` `bool compactResult = false )`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`read(const String & fileName)`
`void`	`train()`	Trains a descriptor matcher.
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name )`
`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::DescriptorMatcher

Return	Name	Description
`static Ptr< DescriptorMatcher >`	`create(const DescriptorMatcher::MatcherType & matcherType)`
`static Ptr< DescriptorMatcher >`	`create(const String & descriptorMatcherType)`	Creates a descriptor matcher of a given type with the default parameters (using default constructor).

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#

Protected Member Functions inherited from cv::DescriptorMatcher

Return	Name	Description
`void`	`checkMasks(` `InputArrayOfArrays masks,` `int queryDescriptorsCount )`
`void`	`knnMatchImpl(` `InputArray queryDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `int k,` `InputArrayOfArrays masks = noArray(),` `bool compactResult = false )`
`void`	`radiusMatchImpl(` `InputArray queryDescriptors,` `std::vector< std::vector< DMatch > > & matches,` `float maxDistance,` `InputArrayOfArrays masks = noArray(),` `bool compactResult = false )`

Static Protected Member Functions inherited from cv::DescriptorMatcher

Return	Name	Description
`static CV_NODISCARD_STD Mat`	`clone_op(Mat m)`
`static bool`	`isMaskedOut(` `InputArrayOfArrays masks,` `int queryIdx )`
`static bool`	`isPossibleMatch(` `InputArray mask,` `int queryIdx,` `int trainIdx )`

Protected Attributes inherited from cv::DescriptorMatcher

Return	Name	Description
`std::vector< Mat >`	`trainDescCollection`	Collection of descriptors from train images.
`std::vector< UMat >`	`utrainDescCollection`

Detailed Description#

LightGlue feature matcher.

LightGlue is a CNN-based feature matcher, as described in Lindenberger23 . It takes keypoint locations and descriptors from two images and directly predicts match pairs. Unlike traditional matchers that compute descriptor distances, LightGlue uses attention mechanisms to produce confidence scores for each potential match pair.

The matcher extends DescriptorMatcher and supports the standard match(), knnMatch(), and radiusMatch() interfaces. Context (keypoints and image sizes) must be provided via setPairInfo() before matching.

Examples: samples/cpp/stitching_detailed.cpp.

Constructor & Destructor Documentation#

LightGlueMatcher()#

cv::LightGlueMatcher::LightGlueMatcher()

~LightGlueMatcher()#

cv::LightGlueMatcher::~LightGlueMatcher()

Member Function Documentation#

clearPairInfo()#

void cv::LightGlueMatcher::clearPairInfo()

Python:

cv.LightGlueMatcher.clearPairInfo()

Clears stored pair context information.

setPairInfo()#

void cv::LightGlueMatcher::setPairInfo(
InputArray queryKpts,
InputArray trainKpts,
Size queryImageSize = Size(),
Size trainImageSize = Size() )

Python:

cv.LightGlueMatcher.setPairInfo(queryKpts, trainKpts[, queryImageSize[, trainImageSize]])

Sets the keypoint and image size context for the next match() call.

This provides the spatial context that LightGlue needs in addition to descriptors. Must be called before match()/knnMatch()/radiusMatch() unless using automatic context from in-process ALIKED instances.

Parameters

queryKpts — Query image keypoints (Nx2 float matrix with x,y coordinates).
trainKpts — Train image keypoints (Nx2 float matrix with x,y coordinates).
queryImageSize — Size of the query image (width, height).
trainImageSize — Size of the train image (width, height).

create()#

static Ptr< LightGlueMatcher > cv::LightGlueMatcher::create(
const String & modelPath,
float scoreThreshold = 0.0f,
int backend = 0,
int target = 0 )

Python:

cv.LightGlueMatcher.create(modelPath[, scoreThreshold[, backend[, target]]]) -> retval

cv.LightGlueMatcher.createFromMemory(modelData[, scoreThreshold[, backend[, target]]]) -> retval

cv.LightGlueMatcher_create(modelPath[, scoreThreshold[, backend[, target]]]) -> retval

cv.LightGlueMatcher_createFromMemory(modelData[, scoreThreshold[, backend[, target]]]) -> retval

Creates LightGlueMatcher from a model file path.

Parameters

modelPath — Path to the ONNX model file.
scoreThreshold — Match confidence threshold.
backend — DNN backend
target — DNN target

Source file#

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

opencv2/features.hpp