using OpenCVForUnity.CoreModule; using OpenCVForUnity.UtilsModule; using System; using System.Collections.Generic; using System.Runtime.InteropServices; namespace OpenCVForUnity.Features2dModule { // C++: class DescriptorMatcher /** * 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. */ public class DescriptorMatcher : Algorithm { protected override void Dispose(bool disposing) { try { if (disposing) { } if (IsEnabledDispose) { if (nativeObj != IntPtr.Zero) features2d_DescriptorMatcher_delete(nativeObj); nativeObj = IntPtr.Zero; } } finally { base.Dispose(disposing); } } protected internal DescriptorMatcher(IntPtr addr) : base(addr) { } // internal usage only public static new DescriptorMatcher __fromPtr__(IntPtr addr) { return new DescriptorMatcher(addr); } // C++: enum cv.DescriptorMatcher.MatcherType public const int FLANNBASED = 1; public const int BRUTEFORCE = 2; public const int BRUTEFORCE_L1 = 3; public const int BRUTEFORCE_HAMMING = 4; public const int BRUTEFORCE_HAMMINGLUT = 5; public const int BRUTEFORCE_SL2 = 6; // // C++: void cv::DescriptorMatcher::add(vector_Mat descriptors) // /** * 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. * * param descriptors Descriptors to add. Each descriptors[i] is a set of descriptors from the same * train image. */ public void add(List descriptors) { ThrowIfDisposed(); Mat descriptors_mat = Converters.vector_Mat_to_Mat(descriptors); features2d_DescriptorMatcher_add_10(nativeObj, descriptors_mat.nativeObj); } // // C++: vector_Mat cv::DescriptorMatcher::getTrainDescriptors() // /** * Returns a constant link to the train descriptor collection trainDescCollection . * return automatically generated */ public List getTrainDescriptors() { ThrowIfDisposed(); List retVal = new List(); Mat retValMat = new Mat(DisposableObject.ThrowIfNullIntPtr(features2d_DescriptorMatcher_getTrainDescriptors_10(nativeObj))); Converters.Mat_to_vector_Mat(retValMat, retVal); return retVal; } // // C++: void cv::DescriptorMatcher::clear() // /** * Clears the train descriptor collections. */ public override void clear() { ThrowIfDisposed(); features2d_DescriptorMatcher_clear_10(nativeObj); } // // C++: bool cv::DescriptorMatcher::empty() // /** * Returns true if there are no train descriptors in the both collections. * return automatically generated */ public override bool empty() { ThrowIfDisposed(); return features2d_DescriptorMatcher_empty_10(nativeObj); } // // C++: bool cv::DescriptorMatcher::isMaskSupported() // /** * Returns true if the descriptor matcher supports masking permissible matches. * return automatically generated */ public bool isMaskSupported() { ThrowIfDisposed(); return features2d_DescriptorMatcher_isMaskSupported_10(nativeObj); } // // C++: void cv::DescriptorMatcher::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 ). */ public void train() { ThrowIfDisposed(); features2d_DescriptorMatcher_train_10(nativeObj); } // // C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, Mat trainDescriptors, vector_DMatch& matches, Mat mask = Mat()) // /** * Finds the best match for each descriptor from a query set. * * 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. * * 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. */ public void match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (matches != null) matches.ThrowIfDisposed(); if (mask != null) mask.ThrowIfDisposed(); Mat matches_mat = matches; features2d_DescriptorMatcher_match_10(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, mask.nativeObj); } /** * Finds the best match for each descriptor from a query set. * * 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. * 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. */ public void match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (matches != null) matches.ThrowIfDisposed(); Mat matches_mat = matches; features2d_DescriptorMatcher_match_11(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj); } // // C++: void cv::DescriptorMatcher::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. * * 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 mask Mask specifying permissible matches between an input query and train matrices 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 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. */ public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, int k, Mat mask, bool compactResult) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (mask != null) mask.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_knnMatch_10(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, k, mask.nativeObj, compactResult); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * Finds the k best matches for each descriptor from a query set. * * 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 mask Mask specifying permissible matches between an input query and train matrices 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. * 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. */ public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, int k, Mat mask) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (mask != null) mask.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_knnMatch_11(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, k, mask.nativeObj); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * Finds the k best matches for each descriptor from a query set. * * 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. * 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. * 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. */ public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, int k) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_knnMatch_12(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, k); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } // // C++: void cv::DescriptorMatcher::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. * * 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 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. * 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. * * 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. */ public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, float maxDistance, Mat mask, bool compactResult) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (mask != null) mask.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_radiusMatch_10(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, mask.nativeObj, compactResult); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * For each query descriptor, finds the training descriptors not farther than the specified distance. * * 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. * 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. * 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. * * 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. */ public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, float maxDistance, Mat mask) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); if (mask != null) mask.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_radiusMatch_11(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, mask.nativeObj); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * For each query descriptor, finds the training descriptors not farther than the specified distance. * * 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. * 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. * 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)! * 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. */ public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List matches, float maxDistance) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (trainDescriptors != null) trainDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_radiusMatch_12(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, maxDistance); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } // // C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, vector_DMatch& matches, vector_Mat masks = vector_Mat()) // /** * * 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]. */ public void match(Mat queryDescriptors, MatOfDMatch matches, List masks) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (matches != null) matches.ThrowIfDisposed(); Mat matches_mat = matches; Mat masks_mat = Converters.vector_Mat_to_Mat(masks); features2d_DescriptorMatcher_match_12(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, masks_mat.nativeObj); } /** * * 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. * descriptors and stored train descriptors from the i-th image trainDescCollection[i]. */ public void match(Mat queryDescriptors, MatOfDMatch matches) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); if (matches != null) matches.ThrowIfDisposed(); Mat matches_mat = matches; features2d_DescriptorMatcher_match_13(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj); } // // C++: void cv::DescriptorMatcher::knnMatch(Mat queryDescriptors, vector_vector_DMatch& matches, int k, vector_Mat masks = vector_Mat(), bool compactResult = false) // /** * * 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. */ public void knnMatch(Mat queryDescriptors, List matches, int k, List masks, bool compactResult) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); Mat masks_mat = Converters.vector_Mat_to_Mat(masks); features2d_DescriptorMatcher_knnMatch_13(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, k, masks_mat.nativeObj, compactResult); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * * 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]. * 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. */ public void knnMatch(Mat queryDescriptors, List matches, int k, List masks) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); Mat masks_mat = Converters.vector_Mat_to_Mat(masks); features2d_DescriptorMatcher_knnMatch_14(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, k, masks_mat.nativeObj); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * * 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. * descriptors and stored train descriptors from the i-th image trainDescCollection[i]. * 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. */ public void knnMatch(Mat queryDescriptors, List matches, int k) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_knnMatch_15(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, k); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } // // C++: void cv::DescriptorMatcher::radiusMatch(Mat queryDescriptors, vector_vector_DMatch& matches, float maxDistance, vector_Mat masks = vector_Mat(), bool compactResult = false) // /** * * 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. */ public void radiusMatch(Mat queryDescriptors, List matches, float maxDistance, List masks, bool compactResult) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); Mat masks_mat = Converters.vector_Mat_to_Mat(masks); features2d_DescriptorMatcher_radiusMatch_13(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, masks_mat.nativeObj, compactResult); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * * 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]. * 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. */ public void radiusMatch(Mat queryDescriptors, List matches, float maxDistance, List masks) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); Mat masks_mat = Converters.vector_Mat_to_Mat(masks); features2d_DescriptorMatcher_radiusMatch_14(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, maxDistance, masks_mat.nativeObj); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } /** * * 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)! * descriptors and stored train descriptors from the i-th image trainDescCollection[i]. * 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. */ public void radiusMatch(Mat queryDescriptors, List matches, float maxDistance) { ThrowIfDisposed(); if (queryDescriptors != null) queryDescriptors.ThrowIfDisposed(); Mat matches_mat = new Mat(); features2d_DescriptorMatcher_radiusMatch_15(nativeObj, queryDescriptors.nativeObj, matches_mat.nativeObj, maxDistance); Converters.Mat_to_vector_vector_DMatch(matches_mat, matches); matches_mat.release(); } // // C++: void cv::DescriptorMatcher::write(String fileName) // public void write(string fileName) { ThrowIfDisposed(); features2d_DescriptorMatcher_write_10(nativeObj, fileName); } // // C++: void cv::DescriptorMatcher::read(String fileName) // public void read(string fileName) { ThrowIfDisposed(); features2d_DescriptorMatcher_read_10(nativeObj, fileName); } // // C++: void cv::DescriptorMatcher::read(FileNode arg1) // // Unknown type 'FileNode' (I), skipping the function // // C++: Ptr_DescriptorMatcher cv::DescriptorMatcher::clone(bool emptyTrainData = false) // /** * Clones the matcher. * * param 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. * return automatically generated */ public DescriptorMatcher clone(bool emptyTrainData) { ThrowIfDisposed(); return DescriptorMatcher.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_DescriptorMatcher_clone_10(nativeObj, emptyTrainData))); } /** * Clones the matcher. * * 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. * return automatically generated */ public DescriptorMatcher clone() { ThrowIfDisposed(); return DescriptorMatcher.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_DescriptorMatcher_clone_11(nativeObj))); } // // C++: static Ptr_DescriptorMatcher cv::DescriptorMatcher::create(String descriptorMatcherType) // /** * Creates a descriptor matcher of a given type with the default parameters (using default * constructor). * * param descriptorMatcherType Descriptor matcher type. Now the following matcher types are * supported: *
    *
  • * {code BruteForce} (it uses L2 ) *
    • *
  • * {code BruteForce-L1} *
    • *
  • * {code BruteForce-Hamming} *
    • *
  • * {code BruteForce-Hamming(2)} *
    • *
  • * {code FlannBased} *
    • *
* return automatically generated */ public static DescriptorMatcher create(string descriptorMatcherType) { return DescriptorMatcher.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_DescriptorMatcher_create_10(descriptorMatcherType))); } // // C++: static Ptr_DescriptorMatcher cv::DescriptorMatcher::create(DescriptorMatcher_MatcherType matcherType) // public static DescriptorMatcher create(int matcherType) { return DescriptorMatcher.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(features2d_DescriptorMatcher_create_11(matcherType))); } // // C++: void cv::DescriptorMatcher::write(FileStorage fs, String name) // // Unknown type 'FileStorage' (I), skipping the function #if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR const string LIBNAME = "__Internal"; #else const string LIBNAME = "opencvforunity"; #endif // C++: void cv::DescriptorMatcher::add(vector_Mat descriptors) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_add_10(IntPtr nativeObj, IntPtr descriptors_mat_nativeObj); // C++: vector_Mat cv::DescriptorMatcher::getTrainDescriptors() [DllImport(LIBNAME)] private static extern IntPtr features2d_DescriptorMatcher_getTrainDescriptors_10(IntPtr nativeObj); // C++: void cv::DescriptorMatcher::clear() [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_clear_10(IntPtr nativeObj); // C++: bool cv::DescriptorMatcher::empty() [DllImport(LIBNAME)] [return: MarshalAs(UnmanagedType.U1)] private static extern bool features2d_DescriptorMatcher_empty_10(IntPtr nativeObj); // C++: bool cv::DescriptorMatcher::isMaskSupported() [DllImport(LIBNAME)] [return: MarshalAs(UnmanagedType.U1)] private static extern bool features2d_DescriptorMatcher_isMaskSupported_10(IntPtr nativeObj); // C++: void cv::DescriptorMatcher::train() [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_train_10(IntPtr nativeObj); // C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, Mat trainDescriptors, vector_DMatch& matches, Mat mask = Mat()) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_match_10(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, IntPtr mask_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_match_11(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj); // C++: void cv::DescriptorMatcher::knnMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, int k, Mat mask = Mat(), bool compactResult = false) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_10(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k, IntPtr mask_nativeObj, [MarshalAs(UnmanagedType.U1)] bool compactResult); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_11(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k, IntPtr mask_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_12(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k); // C++: void cv::DescriptorMatcher::radiusMatch(Mat queryDescriptors, Mat trainDescriptors, vector_vector_DMatch& matches, float maxDistance, Mat mask = Mat(), bool compactResult = false) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_10(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance, IntPtr mask_nativeObj, [MarshalAs(UnmanagedType.U1)] bool compactResult); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_11(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance, IntPtr mask_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_12(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr trainDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance); // C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, vector_DMatch& matches, vector_Mat masks = vector_Mat()) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_match_12(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, IntPtr masks_mat_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_match_13(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj); // C++: void cv::DescriptorMatcher::knnMatch(Mat queryDescriptors, vector_vector_DMatch& matches, int k, vector_Mat masks = vector_Mat(), bool compactResult = false) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_13(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k, IntPtr masks_mat_nativeObj, [MarshalAs(UnmanagedType.U1)] bool compactResult); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_14(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k, IntPtr masks_mat_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_knnMatch_15(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, int k); // C++: void cv::DescriptorMatcher::radiusMatch(Mat queryDescriptors, vector_vector_DMatch& matches, float maxDistance, vector_Mat masks = vector_Mat(), bool compactResult = false) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_13(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance, IntPtr masks_mat_nativeObj, [MarshalAs(UnmanagedType.U1)] bool compactResult); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_14(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance, IntPtr masks_mat_nativeObj); [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_radiusMatch_15(IntPtr nativeObj, IntPtr queryDescriptors_nativeObj, IntPtr matches_mat_nativeObj, float maxDistance); // C++: void cv::DescriptorMatcher::write(String fileName) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_write_10(IntPtr nativeObj, string fileName); // C++: void cv::DescriptorMatcher::read(String fileName) [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_read_10(IntPtr nativeObj, string fileName); // C++: Ptr_DescriptorMatcher cv::DescriptorMatcher::clone(bool emptyTrainData = false) [DllImport(LIBNAME)] private static extern IntPtr features2d_DescriptorMatcher_clone_10(IntPtr nativeObj, [MarshalAs(UnmanagedType.U1)] bool emptyTrainData); [DllImport(LIBNAME)] private static extern IntPtr features2d_DescriptorMatcher_clone_11(IntPtr nativeObj); // C++: static Ptr_DescriptorMatcher cv::DescriptorMatcher::create(String descriptorMatcherType) [DllImport(LIBNAME)] private static extern IntPtr features2d_DescriptorMatcher_create_10(string descriptorMatcherType); // C++: static Ptr_DescriptorMatcher cv::DescriptorMatcher::create(DescriptorMatcher_MatcherType matcherType) [DllImport(LIBNAME)] private static extern IntPtr features2d_DescriptorMatcher_create_11(int matcherType); // native support for java finalize() [DllImport(LIBNAME)] private static extern void features2d_DescriptorMatcher_delete(IntPtr nativeObj); } }