DescriptorMatcher Class Reference
[Descriptor Matchers]

Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) 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.

Reimplemented in FlannBasedMatcher.

Clears the train descriptor collections.

Reimplemented from Algorithm.

Reimplemented in FlannBasedMatcher.

Clones the matcher.

Parameters:

emptyTrainData

If emptyTrainData is false, the method creates a deep copy of the object, that is, copies both parameters and train data. If emptyTrainData is true, the method creates an object copy with the current parameters but with empty train data.

Implemented in BFMatcher, and FlannBasedMatcher.

Creates a descriptor matcher of a given type with the default parameters (using default constructor).

Parameters:

descriptorMatcherType

Descriptor matcher type. Now the following matcher types are supported: `BruteForce` (it uses L2 ) `BruteForce-L1` `BruteForce-Hamming` `BruteForce-Hamming(2)` `FlannBased`

Returns true if there are no train descriptors in the both collections.

Reimplemented from Algorithm.

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.

Returns a constant link to the train descriptor collection trainDescCollection .

Returns true if the descriptor matcher supports masking permissible matches.

Implemented in BFMatcher, and FlannBasedMatcher.

Finds the k best matches for each descriptor from a query set.

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.
mask	Mask specifying permissible matches between an input query and train matrices of descriptors.
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.
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.

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.

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

Parameters:

queryDescriptors	Query set of descriptors.
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.
masks	Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].
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.

In fact the matching is implemented only by the following two methods.

These methods suppose that the class object has been trained already. Public match methods call these methods after calling train().

Implemented in BFMatcher, and FlannBasedMatcher.

Loads algorithm from the file.

Parameters:

filename	Name of the file to read.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

     Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).

Definition at line 3027 of file core.hpp.

Loads algorithm from a String.

Parameters:

strModel	The string variable containing the model you want to load.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

     Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);

Definition at line 3046 of file core.hpp.

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

Parameters:

queryDescriptors	Query set of descriptors.
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.
masks	Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].

Finds the best match for each descriptor from a query set.

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.

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.

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

Parameters:

queryDescriptors	Query set of descriptors.
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)!
masks	Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].
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.

For each query descriptor, finds the training descriptors not farther than the specified distance.

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.
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.
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.

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.

Reads algorithm parameters from a file storage.

Reimplemented from Algorithm.

Reimplemented in FlannBasedMatcher.

Saves the algorithm to a file.

In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

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. Some descriptor matchers (for example, BruteForceMatcher) have an empty implementation of this method. Other matchers really train their inner structures (for example, FlannBasedMatcher trains flann::Index ).

Reimplemented in FlannBasedMatcher.

Stores algorithm parameters in a file storage.

Reimplemented from Algorithm.

Reimplemented in FlannBasedMatcher.

Collection of descriptors from train images.

Definition at line 980 of file features2d.hpp.