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//
// This file is auto-generated. Please don't modify it!
//
package org.opencv.features2d;
import java.lang.String;
import java.util.ArrayList;
import java.util.List;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDMatch;
import org.opencv.utils.Converters;
// C++: class javaDescriptorMatcher
/**
* 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.
*
* class DescriptorMatcher
*
* // C++ code:
*
*
* public:
*
* virtual ~DescriptorMatcher();
*
* virtual void add(const vector& descriptors);
*
* const vector& getTrainDescriptors() const;
*
* virtual void clear();
*
* bool empty() const;
*
* virtual bool isMaskSupported() const = 0;
*
* virtual void train();
*
* / *
*
* - Group of methods to match descriptors from an image pair.
*
- /
*
*
* void match(const Mat& queryDescriptors, const Mat& trainDescriptors,
*
* vector& matches, const Mat& mask=Mat()) const;
*
* void knnMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,
*
* vector >& matches, int k,
*
* const Mat& mask=Mat(), bool compactResult=false) const;
*
* void radiusMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,
*
* vector >& matches, float maxDistance,
*
* const Mat& mask=Mat(), bool compactResult=false) const;
*
* / *
*
* - Group of methods to match descriptors from one image to an image set.
*
- /
*
*
* void match(const Mat& queryDescriptors, vector& matches,
*
* const vector& masks=vector());
*
* void knnMatch(const Mat& queryDescriptors, vector >& matches,
*
* int k, const vector& masks=vector(),
*
* bool compactResult=false);
*
* void radiusMatch(const Mat& queryDescriptors, vector >&
* matches,
*
* float maxDistance, const vector& masks=vector(),
*
* bool compactResult=false);
*
* virtual void read(const FileNode&);
*
* virtual void write(FileStorage&) const;
*
* virtual Ptr clone(bool emptyTrainData=false) const = 0;
*
* static Ptr create(const string& descriptorMatcherType);
*
* protected:
*
* vector trainDescCollection;...
*
* };
*
* @see org.opencv.features2d.DescriptorMatcher : public Algorithm
*/
public class DescriptorMatcher {
protected final long nativeObj;
protected DescriptorMatcher(long addr) { nativeObj = addr; }
public static final int
FLANNBASED = 1,
BRUTEFORCE = 2,
BRUTEFORCE_L1 = 3,
BRUTEFORCE_HAMMING = 4,
BRUTEFORCE_HAMMINGLUT = 5,
BRUTEFORCE_SL2 = 6;
//
// C++: void javaDescriptorMatcher::add(vector_Mat descriptors)
//
/**
* Adds descriptors to train a descriptor collection. If the collection
* trainDescCollectionis is not empty, the new descriptors are
* added to existing train descriptors.
*
* @param descriptors Descriptors to add. Each descriptors[i] is a
* set of descriptors from the same train image.
*
* @see org.opencv.features2d.DescriptorMatcher.add
*/
public void add(List descriptors)
{
Mat descriptors_mat = Converters.vector_Mat_to_Mat(descriptors);
add_0(nativeObj, descriptors_mat.nativeObj);
return;
}
//
// C++: void javaDescriptorMatcher::clear()
//
/**
* Clears the train descriptor collection.
*
* @see org.opencv.features2d.DescriptorMatcher.clear
*/
public void clear()
{
clear_0(nativeObj);
return;
}
//
// C++: javaDescriptorMatcher* javaDescriptorMatcher::jclone(bool emptyTrainData = false)
//
public DescriptorMatcher clone(boolean emptyTrainData)
{
DescriptorMatcher retVal = new DescriptorMatcher(clone_0(nativeObj, emptyTrainData));
return retVal;
}
public DescriptorMatcher clone()
{
DescriptorMatcher retVal = new DescriptorMatcher(clone_1(nativeObj));
return retVal;
}
//
// C++: static javaDescriptorMatcher* javaDescriptorMatcher::create(int matcherType)
//
/**
* Creates a descriptor matcher of a given type with the default parameters
* (using default constructor).
*
* @param matcherType a matcherType
*
* @see org.opencv.features2d.DescriptorMatcher.create
*/
public static DescriptorMatcher create(int matcherType)
{
DescriptorMatcher retVal = new DescriptorMatcher(create_0(matcherType));
return retVal;
}
//
// C++: bool javaDescriptorMatcher::empty()
//
/**
* Returns true if there are no train descriptors in the collection.
*
* @see org.opencv.features2d.DescriptorMatcher.empty
*/
public boolean empty()
{
boolean retVal = empty_0(nativeObj);
return retVal;
}
//
// C++: vector_Mat javaDescriptorMatcher::getTrainDescriptors()
//
/**
* Returns a constant link to the train descriptor collection trainDescCollection.
*
* @see org.opencv.features2d.DescriptorMatcher.getTrainDescriptors
*/
public List getTrainDescriptors()
{
List retVal = new ArrayList();
Mat retValMat = new Mat(getTrainDescriptors_0(nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return retVal;
}
//
// C++: bool javaDescriptorMatcher::isMaskSupported()
//
/**
* Returns true if the descriptor matcher supports masking permissible matches.
*
* @see org.opencv.features2d.DescriptorMatcher.isMaskSupported
*/
public boolean isMaskSupported()
{
boolean retVal = isMaskSupported_0(nativeObj);
return retVal;
}
//
// C++: void javaDescriptorMatcher::knnMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, int k, Mat mask = Mat(), bool compactResult = false)
//
/**
* Finds the k best matches for each descriptor from a query set.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param matches Matches. Each matches[i] is k or less matches for
* the same query descriptor.
* @param k Count of best matches found per each query descriptor or less if a
* query descriptor has less than k possible matches in total.
* @param mask Mask specifying permissible matches between an input query and
* train matrices of descriptors.
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.knnMatch
*/
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, int k, Mat mask, boolean compactResult)
{
Mat matches_mat = new Mat();
knnMatch_0(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, k, mask.nativeObj, compactResult);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
/**
* Finds the k best matches for each descriptor from a query set.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param matches Matches. Each matches[i] is k or less matches for
* the same query descriptor.
* @param k Count of best matches found per each query descriptor or less if a
* query descriptor has less than k possible matches in total.
*
* @see org.opencv.features2d.DescriptorMatcher.knnMatch
*/
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, int k)
{
Mat matches_mat = new Mat();
knnMatch_1(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, k);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
//
// C++: void javaDescriptorMatcher::knnMatch(Mat queryDescriptors, vector_vector_DMatch& matches, int k, vector_Mat masks = vector(), bool compactResult = false)
//
/**
* Finds the k best matches for each descriptor from a query set.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. Each matches[i] is k or less matches for
* the same query descriptor.
* @param k Count of best matches found per each query descriptor or less if a
* query descriptor has less than k possible matches in total.
* @param 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].
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.knnMatch
*/
public void knnMatch(Mat queryDescriptors, List matches, int k, List masks, boolean compactResult)
{
Mat matches_mat = new Mat();
Mat masks_mat = Converters.vector_Mat_to_Mat(masks);
knnMatch_2(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, k, masks_mat.nativeObj, compactResult);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
/**
* Finds the k best matches for each descriptor from a query set.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. Each matches[i] is k or less matches for
* the same query descriptor.
* @param k Count of best matches found per each query descriptor or less if a
* query descriptor has less than k possible matches in total.
*
* @see org.opencv.features2d.DescriptorMatcher.knnMatch
*/
public void knnMatch(Mat queryDescriptors, List matches, int k)
{
Mat matches_mat = new Mat();
knnMatch_3(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, k);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
//
// C++: void javaDescriptorMatcher::match(Mat queryDescriptors, Mat trainDescriptors, vector_DMatch& matches, Mat mask = Mat())
//
/**
* Finds the best match for each descriptor from a query set.
*
* 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(i,j)
* is non-zero.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param 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.
* @param mask Mask specifying permissible matches between an input query and
* train matrices of descriptors.
*
* @see org.opencv.features2d.DescriptorMatcher.match
*/
public void match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask)
{
Mat matches_mat = matches;
match_0(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, mask.nativeObj);
return;
}
/**
* Finds the best match for each descriptor from a query set.
*
* 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(i,j)
* is non-zero.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.match
*/
public void match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches)
{
Mat matches_mat = matches;
match_1(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj);
return;
}
//
// C++: void javaDescriptorMatcher::match(Mat queryDescriptors, vector_DMatch& matches, vector_Mat masks = vector())
//
/**
* Finds the best match for each descriptor from a query set.
*
* 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(i,j)
* is non-zero.
*
* @param queryDescriptors Query set of descriptors.
* @param 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.
* @param 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].
*
* @see org.opencv.features2d.DescriptorMatcher.match
*/
public void match(Mat queryDescriptors, MatOfDMatch matches, List masks)
{
Mat matches_mat = matches;
Mat masks_mat = Converters.vector_Mat_to_Mat(masks);
match_2(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, masks_mat.nativeObj);
return;
}
/**
* Finds the best match for each descriptor from a query set.
*
* 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(i,j)
* is non-zero.
*
* @param queryDescriptors Query set of descriptors.
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.match
*/
public void match(Mat queryDescriptors, MatOfDMatch matches)
{
Mat matches_mat = matches;
match_3(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj);
return;
}
//
// C++: void javaDescriptorMatcher::radiusMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, float maxDistance, Mat mask = Mat(), bool compactResult = false)
//
/**
* For each query descriptor, finds the training descriptors not farther than
* the specified distance.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param matches Found matches.
* @param 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)!
* @param mask Mask specifying permissible matches between an input query and
* train matrices of descriptors.
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.radiusMatch
*/
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, float maxDistance, Mat mask, boolean compactResult)
{
Mat matches_mat = new Mat();
radiusMatch_0(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, mask.nativeObj, compactResult);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
/**
* For each query descriptor, finds the training descriptors not farther than
* the specified distance.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param trainDescriptors Train set of descriptors. This set is not added to
* the train descriptors collection stored in the class object.
* @param matches Found matches.
* @param 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)!
*
* @see org.opencv.features2d.DescriptorMatcher.radiusMatch
*/
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, float maxDistance)
{
Mat matches_mat = new Mat();
radiusMatch_1(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
//
// C++: void javaDescriptorMatcher::radiusMatch(Mat queryDescriptors, vector_vector_DMatch& matches, float maxDistance, vector_Mat masks = vector(), bool compactResult = false)
//
/**
* For each query descriptor, finds the training descriptors not farther than
* the specified distance.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param matches Found matches.
* @param 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)!
* @param 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].
* @param 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.
*
* @see org.opencv.features2d.DescriptorMatcher.radiusMatch
*/
public void radiusMatch(Mat queryDescriptors, List matches, float maxDistance, List masks, boolean compactResult)
{
Mat matches_mat = new Mat();
Mat masks_mat = Converters.vector_Mat_to_Mat(masks);
radiusMatch_2(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, masks_mat.nativeObj, compactResult);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
/**
* For each query descriptor, finds the training descriptors not farther than
* the specified distance.
*
* 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.
*
* @param queryDescriptors Query set of descriptors.
* @param matches Found matches.
* @param 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)!
*
* @see org.opencv.features2d.DescriptorMatcher.radiusMatch
*/
public void radiusMatch(Mat queryDescriptors, List matches, float maxDistance)
{
Mat matches_mat = new Mat();
radiusMatch_3(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, maxDistance);
Converters.Mat_to_vector_vector_DMatch(matches_mat, matches);
return;
}
//
// C++: void javaDescriptorMatcher::read(string fileName)
//
public void read(String fileName)
{
read_0(nativeObj, fileName);
return;
}
//
// C++: void javaDescriptorMatcher::train()
//
/**
* 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).
*
* @see org.opencv.features2d.DescriptorMatcher.train
*/
public void train()
{
train_0(nativeObj);
return;
}
//
// C++: void javaDescriptorMatcher::write(string fileName)
//
public void write(String fileName)
{
write_0(nativeObj, fileName);
return;
}
@Override
protected void finalize() throws Throwable {
delete(nativeObj);
}
// C++: void javaDescriptorMatcher::add(vector_Mat descriptors)
private static native void add_0(long nativeObj, long descriptors_mat_nativeObj);
// C++: void javaDescriptorMatcher::clear()
private static native void clear_0(long nativeObj);
// C++: javaDescriptorMatcher* javaDescriptorMatcher::jclone(bool emptyTrainData = false)
private static native long clone_0(long nativeObj, boolean emptyTrainData);
private static native long clone_1(long nativeObj);
// C++: static javaDescriptorMatcher* javaDescriptorMatcher::create(int matcherType)
private static native long create_0(int matcherType);
// C++: bool javaDescriptorMatcher::empty()
private static native boolean empty_0(long nativeObj);
// C++: vector_Mat javaDescriptorMatcher::getTrainDescriptors()
private static native long getTrainDescriptors_0(long nativeObj);
// C++: bool javaDescriptorMatcher::isMaskSupported()
private static native boolean isMaskSupported_0(long nativeObj);
// C++: void javaDescriptorMatcher::knnMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, int k, Mat mask = Mat(), bool compactResult = false)
private static native void knnMatch_0(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj, int k, long mask_nativeObj, boolean compactResult);
private static native void knnMatch_1(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj, int k);
// C++: void javaDescriptorMatcher::knnMatch(Mat queryDescriptors, vector_vector_DMatch& matches, int k, vector_Mat masks = vector(), bool compactResult = false)
private static native void knnMatch_2(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj, int k, long masks_mat_nativeObj, boolean compactResult);
private static native void knnMatch_3(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj, int k);
// C++: void javaDescriptorMatcher::match(Mat queryDescriptors, Mat trainDescriptors, vector_DMatch& matches, Mat mask = Mat())
private static native void match_0(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj, long mask_nativeObj);
private static native void match_1(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj);
// C++: void javaDescriptorMatcher::match(Mat queryDescriptors, vector_DMatch& matches, vector_Mat masks = vector())
private static native void match_2(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj, long masks_mat_nativeObj);
private static native void match_3(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj);
// C++: void javaDescriptorMatcher::radiusMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, float maxDistance, Mat mask = Mat(), bool compactResult = false)
private static native void radiusMatch_0(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj, float maxDistance, long mask_nativeObj, boolean compactResult);
private static native void radiusMatch_1(long nativeObj, long queryDescriptors_nativeObj, long trainDescriptors_nativeObj, long matches_mat_nativeObj, float maxDistance);
// C++: void javaDescriptorMatcher::radiusMatch(Mat queryDescriptors, vector_vector_DMatch& matches, float maxDistance, vector_Mat masks = vector(), bool compactResult = false)
private static native void radiusMatch_2(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj, float maxDistance, long masks_mat_nativeObj, boolean compactResult);
private static native void radiusMatch_3(long nativeObj, long queryDescriptors_nativeObj, long matches_mat_nativeObj, float maxDistance);
// C++: void javaDescriptorMatcher::read(string fileName)
private static native void read_0(long nativeObj, String fileName);
// C++: void javaDescriptorMatcher::train()
private static native void train_0(long nativeObj);
// C++: void javaDescriptorMatcher::write(string fileName)
private static native void write_0(long nativeObj, String fileName);
// native support for java finalize()
private static native void delete(long nativeObj);
}