//
// 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
/**
* <p>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.</p>
*
* <p>class DescriptorMatcher <code></p>
*
* <p>// C++ code:</p>
*
*
* <p>public:</p>
*
* <p>virtual ~DescriptorMatcher();</p>
*
* <p>virtual void add(const vector<Mat>& descriptors);</p>
*
* <p>const vector<Mat>& getTrainDescriptors() const;</p>
*
* <p>virtual void clear();</p>
*
* <p>bool empty() const;</p>
*
* <p>virtual bool isMaskSupported() const = 0;</p>
*
* <p>virtual void train();</p>
*
* <p>/ *</p>
* <ul>
* <li> Group of methods to match descriptors from an image pair.
* <li> /
* </ul>
*
* <p>void match(const Mat& queryDescriptors, const Mat& trainDescriptors,</p>
*
* <p>vector<DMatch>& matches, const Mat& mask=Mat()) const;</p>
*
* <p>void knnMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,</p>
*
* <p>vector<vector<DMatch> >& matches, int k,</p>
*
* <p>const Mat& mask=Mat(), bool compactResult=false) const;</p>
*
* <p>void radiusMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,</p>
*
* <p>vector<vector<DMatch> >& matches, float maxDistance,</p>
*
* <p>const Mat& mask=Mat(), bool compactResult=false) const;</p>
*
* <p>/ *</p>
* <ul>
* <li> Group of methods to match descriptors from one image to an image set.
* <li> /
* </ul>
*
* <p>void match(const Mat& queryDescriptors, vector<DMatch>& matches,</p>
*
* <p>const vector<Mat>& masks=vector<Mat>());</p>
*
* <p>void knnMatch(const Mat& queryDescriptors, vector<vector<DMatch> >& matches,</p>
*
* <p>int k, const vector<Mat>& masks=vector<Mat>(),</p>
*
* <p>bool compactResult=false);</p>
*
* <p>void radiusMatch(const Mat& queryDescriptors, vector<vector<DMatch> >&
* matches,</p>
*
* <p>float maxDistance, const vector<Mat>& masks=vector<Mat>(),</p>
*
* <p>bool compactResult=false);</p>
*
* <p>virtual void read(const FileNode&);</p>
*
* <p>virtual void write(FileStorage&) const;</p>
*
* <p>virtual Ptr<DescriptorMatcher> clone(bool emptyTrainData=false) const = 0;</p>
*
* <p>static Ptr<DescriptorMatcher> create(const string& descriptorMatcherType);</p>
*
* <p>protected:</p>
*
* <p>vector<Mat> trainDescCollection;...</p>
*
* <p>};</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher">org.opencv.features2d.DescriptorMatcher : public Algorithm</a>
*/
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)
//
/**
* <p>Adds descriptors to train a descriptor collection. If the collection
* <code>trainDescCollectionis</code> is not empty, the new descriptors are
* added to existing train descriptors.</p>
*
* @param descriptors Descriptors to add. Each <code>descriptors[i]</code> is a
* set of descriptors from the same train image.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-add">org.opencv.features2d.DescriptorMatcher.add</a>
*/
public void add(List<Mat> descriptors)
{
Mat descriptors_mat = Converters.vector_Mat_to_Mat(descriptors);
add_0(nativeObj, descriptors_mat.nativeObj);
return;
}
//
// C++: void javaDescriptorMatcher::clear()
//
/**
* <p>Clears the train descriptor collection.</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-clear">org.opencv.features2d.DescriptorMatcher.clear</a>
*/
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)
//
/**
* <p>Creates a descriptor matcher of a given type with the default parameters
* (using default constructor).</p>
*
* @param matcherType a matcherType
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-create">org.opencv.features2d.DescriptorMatcher.create</a>
*/
public static DescriptorMatcher create(int matcherType)
{
DescriptorMatcher retVal = new DescriptorMatcher(create_0(matcherType));
return retVal;
}
//
// C++: bool javaDescriptorMatcher::empty()
//
/**
* <p>Returns true if there are no train descriptors in the collection.</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-empty">org.opencv.features2d.DescriptorMatcher.empty</a>
*/
public boolean empty()
{
boolean retVal = empty_0(nativeObj);
return retVal;
}
//
// C++: vector_Mat javaDescriptorMatcher::getTrainDescriptors()
//
/**
* <p>Returns a constant link to the train descriptor collection <code>trainDescCollection</code>.</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-gettraindescriptors">org.opencv.features2d.DescriptorMatcher.getTrainDescriptors</a>
*/
public List<Mat> getTrainDescriptors()
{
List<Mat> retVal = new ArrayList<Mat>();
Mat retValMat = new Mat(getTrainDescriptors_0(nativeObj));
Converters.Mat_to_vector_Mat(retValMat, retVal);
return retVal;
}
//
// C++: bool javaDescriptorMatcher::isMaskSupported()
//
/**
* <p>Returns true if the descriptor matcher supports masking permissible matches.</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-ismasksupported">org.opencv.features2d.DescriptorMatcher.isMaskSupported</a>
*/
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)
//
/**
* <p>Finds the k best matches for each descriptor from a query set.</p>
*
* <p>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.</p>
*
* @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 <code>matches[i]</code> 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
* <code>compactResult</code> is false, the <code>matches</code> vector has the
* same size as <code>queryDescriptors</code> rows. If <code>compactResult</code>
* is true, the <code>matches</code> vector does not contain matches for fully
* masked-out query descriptors.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-knnmatch">org.opencv.features2d.DescriptorMatcher.knnMatch</a>
*/
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> 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;
}
/**
* <p>Finds the k best matches for each descriptor from a query set.</p>
*
* <p>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.</p>
*
* @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 <code>matches[i]</code> 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 <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-knnmatch">org.opencv.features2d.DescriptorMatcher.knnMatch</a>
*/
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> 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<Mat>(), bool compactResult = false)
//
/**
* <p>Finds the k best matches for each descriptor from a query set.</p>
*
* <p>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.</p>
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. Each <code>matches[i]</code> 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 <code>masks[i]</code> specifies permissible
* matches between the input query descriptors and stored train descriptors from
* the i-th image <code>trainDescCollection[i]</code>.
* @param compactResult Parameter used when the mask (or masks) is not empty. If
* <code>compactResult</code> is false, the <code>matches</code> vector has the
* same size as <code>queryDescriptors</code> rows. If <code>compactResult</code>
* is true, the <code>matches</code> vector does not contain matches for fully
* masked-out query descriptors.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-knnmatch">org.opencv.features2d.DescriptorMatcher.knnMatch</a>
*/
public void knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> 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;
}
/**
* <p>Finds the k best matches for each descriptor from a query set.</p>
*
* <p>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.</p>
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. Each <code>matches[i]</code> 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 <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-knnmatch">org.opencv.features2d.DescriptorMatcher.knnMatch</a>
*/
public void knnMatch(Mat queryDescriptors, List<MatOfDMatch> 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())
//
/**
* <p>Finds the best match for each descriptor from a query set.</p>
*
* <p>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 <code>DescriptorMatcher.add</code> is used.
* Optional mask (or masks) can be passed to specify which query and training
* descriptors can be matched. Namely, <code>queryDescriptors[i]</code> can be
* matched with <code>trainDescriptors[j]</code> only if <code>mask.at<uchar>(i,j)</code>
* is non-zero.</p>
*
* @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
* <code>mask</code>, no match is added for this descriptor. So,
* <code>matches</code> 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 <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-match">org.opencv.features2d.DescriptorMatcher.match</a>
*/
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;
}
/**
* <p>Finds the best match for each descriptor from a query set.</p>
*
* <p>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 <code>DescriptorMatcher.add</code> is used.
* Optional mask (or masks) can be passed to specify which query and training
* descriptors can be matched. Namely, <code>queryDescriptors[i]</code> can be
* matched with <code>trainDescriptors[j]</code> only if <code>mask.at<uchar>(i,j)</code>
* is non-zero.</p>
*
* @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
* <code>mask</code>, no match is added for this descriptor. So,
* <code>matches</code> size may be smaller than the query descriptors count.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-match">org.opencv.features2d.DescriptorMatcher.match</a>
*/
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<Mat>())
//
/**
* <p>Finds the best match for each descriptor from a query set.</p>
*
* <p>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 <code>DescriptorMatcher.add</code> is used.
* Optional mask (or masks) can be passed to specify which query and training
* descriptors can be matched. Namely, <code>queryDescriptors[i]</code> can be
* matched with <code>trainDescriptors[j]</code> only if <code>mask.at<uchar>(i,j)</code>
* is non-zero.</p>
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. If a query descriptor is masked out in
* <code>mask</code>, no match is added for this descriptor. So,
* <code>matches</code> size may be smaller than the query descriptors count.
* @param masks Set of masks. Each <code>masks[i]</code> specifies permissible
* matches between the input query descriptors and stored train descriptors from
* the i-th image <code>trainDescCollection[i]</code>.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-match">org.opencv.features2d.DescriptorMatcher.match</a>
*/
public void match(Mat queryDescriptors, MatOfDMatch matches, List<Mat> 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;
}
/**
* <p>Finds the best match for each descriptor from a query set.</p>
*
* <p>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 <code>DescriptorMatcher.add</code> is used.
* Optional mask (or masks) can be passed to specify which query and training
* descriptors can be matched. Namely, <code>queryDescriptors[i]</code> can be
* matched with <code>trainDescriptors[j]</code> only if <code>mask.at<uchar>(i,j)</code>
* is non-zero.</p>
*
* @param queryDescriptors Query set of descriptors.
* @param matches Matches. If a query descriptor is masked out in
* <code>mask</code>, no match is added for this descriptor. So,
* <code>matches</code> size may be smaller than the query descriptors count.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-match">org.opencv.features2d.DescriptorMatcher.match</a>
*/
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)
//
/**
* <p>For each query descriptor, finds the training descriptors not farther than
* the specified distance.</p>
*
* <p>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 <code>maxDistance</code>. Found matches are returned in
* the distance increasing order.</p>
*
* @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
* <code>compactResult</code> is false, the <code>matches</code> vector has the
* same size as <code>queryDescriptors</code> rows. If <code>compactResult</code>
* is true, the <code>matches</code> vector does not contain matches for fully
* masked-out query descriptors.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-radiusmatch">org.opencv.features2d.DescriptorMatcher.radiusMatch</a>
*/
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> 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;
}
/**
* <p>For each query descriptor, finds the training descriptors not farther than
* the specified distance.</p>
*
* <p>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 <code>maxDistance</code>. Found matches are returned in
* the distance increasing order.</p>
*
* @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 <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-radiusmatch">org.opencv.features2d.DescriptorMatcher.radiusMatch</a>
*/
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> 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<Mat>(), bool compactResult = false)
//
/**
* <p>For each query descriptor, finds the training descriptors not farther than
* the specified distance.</p>
*
* <p>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 <code>maxDistance</code>. Found matches are returned in
* the distance increasing order.</p>
*
* @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 <code>masks[i]</code> specifies permissible
* matches between the input query descriptors and stored train descriptors from
* the i-th image <code>trainDescCollection[i]</code>.
* @param compactResult Parameter used when the mask (or masks) is not empty. If
* <code>compactResult</code> is false, the <code>matches</code> vector has the
* same size as <code>queryDescriptors</code> rows. If <code>compactResult</code>
* is true, the <code>matches</code> vector does not contain matches for fully
* masked-out query descriptors.
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-radiusmatch">org.opencv.features2d.DescriptorMatcher.radiusMatch</a>
*/
public void radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> 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;
}
/**
* <p>For each query descriptor, finds the training descriptors not farther than
* the specified distance.</p>
*
* <p>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 <code>maxDistance</code>. Found matches are returned in
* the distance increasing order.</p>
*
* @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 <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-radiusmatch">org.opencv.features2d.DescriptorMatcher.radiusMatch</a>
*/
public void radiusMatch(Mat queryDescriptors, List<MatOfDMatch> 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()
//
/**
* <p>Trains a descriptor matcher</p>
*
* <p>Trains a descriptor matcher (for example, the flann index). In all methods to
* match, the method <code>train()</code> is run every time before matching.
* Some descriptor matchers (for example, <code>BruteForceMatcher</code>) have
* an empty implementation of this method. Other matchers really train their
* inner structures (for example, <code>FlannBasedMatcher</code> trains
* <code>flann.Index</code>).</p>
*
* @see <a href="http://docs.opencv.org/modules/features2d/doc/common_interfaces_of_descriptor_matchers.html#descriptormatcher-train">org.opencv.features2d.DescriptorMatcher.train</a>
*/
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<Mat>(), 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<Mat>())
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<Mat>(), 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);
}