class cv::cuda::DescriptorMatcher

Overview

Abstract base class for matching keypoint descriptors. More…

#include <cudafeatures2d.hpp>

class DescriptorMatcher: public cv::Algorithm
{
public:
    // methods

    static
    Ptr<DescriptorMatcher>
    createBFMatcher(int normType = cv::NORM_L2);

    virtual
    void
    add(const std::vector<GpuMat>& descriptors) = 0;

    virtual
    void
    clear() = 0;

    virtual
    bool
    empty() const = 0;

    virtual
    const std::vector<GpuMat>&
    getTrainDescriptors() const = 0;

    virtual
    bool
    isMaskSupported() const = 0;

    virtual
    void
    knnMatch(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        std::vector<std::vector<DMatch>>& matches,
        int k,
        InputArray mask = noArray(),
        bool compactResult = false
        ) = 0;

    virtual
    void
    knnMatch(
        InputArray queryDescriptors,
        std::vector<std::vector<DMatch>>& matches,
        int k,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
        bool compactResult = false
        ) = 0;

    virtual
    void
    knnMatchAsync(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        OutputArray matches,
        int k,
        InputArray mask = noArray(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    knnMatchAsync(
        InputArray queryDescriptors,
        OutputArray matches,
        int k,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    knnMatchConvert(
        InputArray gpu_matches,
        std::vector<std::vector<DMatch>>& matches,
        bool compactResult = false
        ) = 0;

    virtual
    void
    match(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        std::vector<DMatch>& matches,
        InputArray mask = noArray()
        ) = 0;

    virtual
    void
    match(
        InputArray queryDescriptors,
        std::vector<DMatch>& matches,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>()
        ) = 0;

    virtual
    void
    matchAsync(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        OutputArray matches,
        InputArray mask = noArray(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    matchAsync(
        InputArray queryDescriptors,
        OutputArray matches,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    matchConvert(
        InputArray gpu_matches,
        std::vector<DMatch>& matches
        ) = 0;

    virtual
    void
    radiusMatch(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        std::vector<std::vector<DMatch>>& matches,
        float maxDistance,
        InputArray mask = noArray(),
        bool compactResult = false
        ) = 0;

    virtual
    void
    radiusMatch(
        InputArray queryDescriptors,
        std::vector<std::vector<DMatch>>& matches,
        float maxDistance,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
        bool compactResult = false
        ) = 0;

    virtual
    void
    radiusMatchAsync(
        InputArray queryDescriptors,
        InputArray trainDescriptors,
        OutputArray matches,
        float maxDistance,
        InputArray mask = noArray(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    radiusMatchAsync(
        InputArray queryDescriptors,
        OutputArray matches,
        float maxDistance,
        const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
        Stream& stream = Stream::Null()
        ) = 0;

    virtual
    void
    radiusMatchConvert(
        InputArray gpu_matches,
        std::vector<std::vector<DMatch>>& matches,
        bool compactResult = false
        ) = 0;

    virtual
    void
    train() = 0;
};

Inherited Members

public:
    // methods

    virtual
    void
    clear();

    virtual
    bool
    empty() const;

    virtual
    String
    getDefaultName() const;

    virtual
    void
    read(const FileNode& fn);

    virtual
    void
    save(const String& filename) const;

    virtual
    void
    write(FileStorage& fs) const;

    template <typename _Tp>
    static
    Ptr<_Tp>
    load(
        const String& filename,
        const String& objname = String()
        );

    template <typename _Tp>
    static
    Ptr<_Tp>
    loadFromString(
        const String& strModel,
        const String& objname = String()
        );

    template <typename _Tp>
    static
    Ptr<_Tp>
    read(const FileNode& fn);

protected:
    // methods

    void
    writeFormat(FileStorage& fs) const;

Detailed Documentation

Abstract base class for matching keypoint descriptors.

It has two groups of match methods: for matching descriptors of an image with another image or with an image set.

Methods

static
Ptr<DescriptorMatcher>
createBFMatcher(int normType = cv::NORM_L2)

Brute-force descriptor matcher.

For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. This descriptor matcher supports masking permissible matches of descriptor sets.

Parameters:

normType

One of NORM_L1, NORM_L2, NORM_HAMMING. L1 and L2 norms are preferable choices for SIFT and SURF descriptors, NORM_HAMMING should be used with ORB, BRISK and BRIEF).

virtual
void
add(const std::vector<GpuMat>& descriptors) = 0

Adds descriptors to train a descriptor collection.

If the collection is not empty, the new descriptors are added to existing train descriptors.

Parameters:

descriptors

Descriptors to add. Each descriptors[i] is a set of descriptors from the same train image.

virtual
void
clear() = 0

Clears the train descriptor collection.

virtual
bool
empty() const = 0

Returns true if there are no train descriptors in the collection.

virtual
const std::vector<GpuMat>&
getTrainDescriptors() const = 0

Returns a constant link to the train descriptor collection.

virtual
bool
isMaskSupported() const = 0

Returns true if the descriptor matcher supports masking permissible matches.

virtual
void
knnMatch(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    std::vector<std::vector<DMatch>>& matches,
    int k,
    InputArray mask = noArray(),
    bool compactResult = false
    ) = 0

Finds the k best matches for each descriptor from a query set (blocking version).

These extended variants of DescriptorMatcher::match methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See DescriptorMatcher::match for the details about query and train descriptors.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Matches. Each matches[i] is k or less matches for the same query descriptor.
k	Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
compactResult	Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

virtual
void
knnMatch(
    InputArray queryDescriptors,
    std::vector<std::vector<DMatch>>& matches,
    int k,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
    bool compactResult = false
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
knnMatchAsync(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    OutputArray matches,
    int k,
    InputArray mask = noArray(),
    Stream& stream = Stream::Null()
    ) = 0

Finds the k best matches for each descriptor from a query set (asynchronous version).

These extended variants of DescriptorMatcher::matchAsync methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See DescriptorMatcher::matchAsync for the details about query and train descriptors.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Matches array stored in GPU memory. Internal representation is not defined. Use DescriptorMatcher::knnMatchConvert method to retrieve results in standard representation.
k	Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
stream	CUDA stream.

virtual
void
knnMatchAsync(
    InputArray queryDescriptors,
    OutputArray matches,
    int k,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
    Stream& stream = Stream::Null()
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
knnMatchConvert(
    InputArray gpu_matches,
    std::vector<std::vector<DMatch>>& matches,
    bool compactResult = false
    ) = 0

Converts matches array from internal representation to standard matches vector.

The method is supposed to be used with DescriptorMatcher::knnMatchAsync to get final result. Call this method only after DescriptorMatcher::knnMatchAsync is completed (ie. after synchronization).

Parameters:

gpu_matches	Matches, returned from DescriptorMatcher::knnMatchAsync.
matches	Vector of DMatch objects.
compactResult	Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

virtual
void
match(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    std::vector<DMatch>& matches,
    InputArray mask = noArray()
    ) = 0

Finds the best match for each descriptor from a query set (blocking version).

In the first variant of this method, the train descriptors are passed as an input argument. In the second variant of the method, train descriptors collection that was set by DescriptorMatcher::add is used. Optional mask (or masks) can be passed to specify which query and training descriptors can be matched. Namely, queryDescriptors[i] can be matched with trainDescriptors[j] only if mask.at<uchar>(i,j) is non-zero.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Matches. If a query descriptor is masked out in mask , no match is added for this descriptor. So, matches size may be smaller than the query descriptors count.
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.

virtual
void
match(
    InputArray queryDescriptors,
    std::vector<DMatch>& matches,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>()
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
matchAsync(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    OutputArray matches,
    InputArray mask = noArray(),
    Stream& stream = Stream::Null()
    ) = 0

Finds the best match for each descriptor from a query set (asynchronous version).

In the first variant of this method, the train descriptors are passed as an input argument. In the second variant of the method, train descriptors collection that was set by DescriptorMatcher::add is used. Optional mask (or masks) can be passed to specify which query and training descriptors can be matched. Namely, queryDescriptors[i] can be matched with trainDescriptors[j] only if mask.at<uchar>(i,j) is non-zero.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Matches array stored in GPU memory. Internal representation is not defined. Use DescriptorMatcher::matchConvert method to retrieve results in standard representation.
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
stream	CUDA stream.

virtual
void
matchAsync(
    InputArray queryDescriptors,
    OutputArray matches,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
    Stream& stream = Stream::Null()
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
matchConvert(
    InputArray gpu_matches,
    std::vector<DMatch>& matches
    ) = 0

Converts matches array from internal representation to standard matches vector.

The method is supposed to be used with DescriptorMatcher::matchAsync to get final result. Call this method only after DescriptorMatcher::matchAsync is completed (ie. after synchronization).

Parameters:

gpu_matches	Matches, returned from DescriptorMatcher::matchAsync.
matches	Vector of DMatch objects.

virtual
void
radiusMatch(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    std::vector<std::vector<DMatch>>& matches,
    float maxDistance,
    InputArray mask = noArray(),
    bool compactResult = false
    ) = 0

For each query descriptor, finds the training descriptors not farther than the specified distance (blocking version).

For each query descriptor, the methods find such training descriptors that the distance between the query descriptor and the training descriptor is equal or smaller than maxDistance. Found matches are returned in the distance increasing order.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Found matches.
maxDistance	Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
compactResult	Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

virtual
void
radiusMatch(
    InputArray queryDescriptors,
    std::vector<std::vector<DMatch>>& matches,
    float maxDistance,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
    bool compactResult = false
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
radiusMatchAsync(
    InputArray queryDescriptors,
    InputArray trainDescriptors,
    OutputArray matches,
    float maxDistance,
    InputArray mask = noArray(),
    Stream& stream = Stream::Null()
    ) = 0

For each query descriptor, finds the training descriptors not farther than the specified distance (asynchronous version).

For each query descriptor, the methods find such training descriptors that the distance between the query descriptor and the training descriptor is equal or smaller than maxDistance. Found matches are returned in the distance increasing order.

Parameters:

queryDescriptors	Query set of descriptors.
trainDescriptors	Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.
matches	Matches array stored in GPU memory. Internal representation is not defined. Use DescriptorMatcher::radiusMatchConvert method to retrieve results in standard representation.
maxDistance	Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
stream	CUDA stream.

virtual
void
radiusMatchAsync(
    InputArray queryDescriptors,
    OutputArray matches,
    float maxDistance,
    const std::vector<GpuMat>& masks = std::vector<GpuMat>(),
    Stream& stream = Stream::Null()
    ) = 0

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

virtual
void
radiusMatchConvert(
    InputArray gpu_matches,
    std::vector<std::vector<DMatch>>& matches,
    bool compactResult = false
    ) = 0

Converts matches array from internal representation to standard matches vector.

The method is supposed to be used with DescriptorMatcher::radiusMatchAsync to get final result. Call this method only after DescriptorMatcher::radiusMatchAsync is completed (ie. after synchronization).

Parameters:

gpu_matches	Matches, returned from DescriptorMatcher::radiusMatchAsync.
matches	Vector of DMatch objects.
compactResult	Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

virtual
void
train() = 0

Trains a descriptor matcher.

Trains a descriptor matcher (for example, the flann index). In all methods to match, the method train() is run every time before matching.

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class cv::cuda::DescriptorMatcher

Overview

Inherited Members

Detailed Documentation

Methods