//
// C++: void cv::xfeatures2d::matchLOGOS(vector_KeyPoint keypoints1, vector_KeyPoint keypoints2, vector_int nn1, vector_int nn2, vector_DMatch matches1to2)
//
/**
* LOGOS (Local geometric support for high-outlier spatial verification) feature matching strategy described in CITE: Lowry2018LOGOSLG .
* param keypoints1 Input keypoints of image1.
* param keypoints2 Input keypoints of image2.
* param nn1 Index to the closest BoW centroid for each descriptors of image1.
* param nn2 Index to the closest BoW centroid for each descriptors of image2.
* param matches1to2 Matches returned by the LOGOS matching strategy.
* <b>Note:</b>
* This matching strategy is suitable for features matching against large scale database.
* First step consists in constructing the bag-of-words (BoW) from a representative image database.
* Image descriptors are then represented by their closest codevector (nearest BoW centroid).
*/
public static void matchLOGOS(MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfInt nn1, MatOfInt nn2, MatOfDMatch matches1to2)
{
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (nn1 != null)
{
nn1.ThrowIfDisposed();
}
if (nn2 != null)
{
nn2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat nn1_mat = nn1;
Mat nn2_mat = nn2;
Mat matches1to2_mat = matches1to2;
xfeatures2d_Xfeatures2d_matchLOGOS_10(keypoints1_mat.nativeObj, keypoints2_mat.nativeObj, nn1_mat.nativeObj, nn2_mat.nativeObj, matches1to2_mat.nativeObj);
}
//
// C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, Mat trainDescriptors, vector_DMatch& matches, Mat mask = Mat())
//
//javadoc: DescriptorMatcher::match(queryDescriptors, trainDescriptors, matches, mask)
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();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat matches_mat = matches;
features2d_DescriptorMatcher_match_10(nativeObj, queryDescriptors.nativeObj, trainDescriptors.nativeObj, matches_mat.nativeObj, mask.nativeObj);
return;
#else
return;
#endif
}
/**
* GMS (Grid-based Motion Statistics) feature matching strategy described in CITE: Bian2017gms .
* param size1 Input size of image1.
* param size2 Input size of image2.
* param keypoints1 Input keypoints of image1.
* param keypoints2 Input keypoints of image2.
* param matches1to2 Input 1-nearest neighbor matches.
* param matchesGMS Matches returned by the GMS matching strategy.
* param withRotation Take rotation transformation into account.
* param withScale Take scale transformation into account.
* <b>Note:</b>
* Since GMS works well when the number of features is large, we recommend to use the ORB feature and set FastThreshold to 0 to get as many as possible features quickly.
* If matching results are not satisfying, please add more features. (We use 10000 for images with 640 X 480).
* If your images have big rotation and scale changes, please set withRotation or withScale to true.
*/
public static void matchGMS(Size size1, Size size2, MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, MatOfDMatch matchesGMS, bool withRotation, bool withScale)
{
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (matchesGMS != null)
{
matchesGMS.ThrowIfDisposed();
}
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
Mat matchesGMS_mat = matchesGMS;
xfeatures2d_Xfeatures2d_matchGMS_11(size1.width, size1.height, size2.width, size2.height, keypoints1_mat.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, matchesGMS_mat.nativeObj, withRotation, withScale);
}
/**
* Draws the found matches of keypoints from two images.
*
* param img1 First source image.
* param keypoints1 Keypoints from the first source image.
* param img2 Second source image.
* param keypoints2 Keypoints from the second source image.
* param matches1to2 Matches from the first image to the second one, which means that keypoints1[i]
* has a corresponding point in keypoints2[matches[i]] .
* param outImg Output image. Its content depends on the flags value defining what is drawn in the
* output image. See possible flags bit values below.
* , the color is generated randomly.
* have the matches. If singlePointColor==Scalar::all(-1) , the color is generated randomly.
* drawn.
* DrawMatchesFlags.
*
* This function draws matches of keypoints from two images in the output image. Match is a line
* connecting two keypoints (circles). See cv::DrawMatchesFlags.
*/
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
features2d_Features2d_drawMatches_14(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj);
}
//javadoc: matchGMS(size1, size2, keypoints1, keypoints2, matches1to2, matchesGMS, withRotation)
public static void matchGMS(Size size1, Size size2, MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, MatOfDMatch matchesGMS, bool withRotation)
{
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (matchesGMS != null)
{
matchesGMS.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
Mat matchesGMS_mat = matchesGMS;
xfeatures2d_Xfeatures2d_matchGMS_12(size1.width, size1.height, size2.width, size2.height, keypoints1_mat.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, matchesGMS_mat.nativeObj, withRotation);
return;
#else
return;
#endif
}
/**
* Draws the found matches of keypoints from two images.
*
* param img1 First source image.
* param keypoints1 Keypoints from the first source image.
* param img2 Second source image.
* param keypoints2 Keypoints from the second source image.
* param matches1to2 Matches from the first image to the second one, which means that keypoints1[i]
* has a corresponding point in keypoints2[matches[i]] .
* param outImg Output image. Its content depends on the flags value defining what is drawn in the
* output image. See possible flags bit values below.
* param matchColor Color of matches (lines and connected keypoints). If matchColor==Scalar::all(-1)
* , the color is generated randomly.
* param singlePointColor Color of single keypoints (circles), which means that keypoints do not
* have the matches. If singlePointColor==Scalar::all(-1) , the color is generated randomly.
* drawn.
* DrawMatchesFlags.
*
* This function draws matches of keypoints from two images in the output image. Match is a line
* connecting two keypoints (circles). See cv::DrawMatchesFlags.
*/
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
features2d_Features2d_drawMatches_12(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj, matchColor.val[0], matchColor.val[1], matchColor.val[2], matchColor.val[3], singlePointColor.val[0], singlePointColor.val[1], singlePointColor.val[2], singlePointColor.val[3]);
}
/**
*
* 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::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 <Mat> 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);
}
//
// C++: void cv::drawMatches(Mat img1, vector_KeyPoint keypoints1, Mat img2, vector_KeyPoint keypoints2, vector_DMatch matches1to2, Mat& outImg, Scalar matchColor = Scalar::all(-1), Scalar singlePointColor = Scalar::all(-1), vector_char matchesMask = std::vector<char>(), DrawMatchesFlags flags = DrawMatchesFlags::DEFAULT)
//
//javadoc: drawMatches(img1, keypoints1, img2, keypoints2, matches1to2, outImg, matchColor, singlePointColor, matchesMask)
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg, Scalar matchColor, Scalar singlePointColor, MatOfByte matchesMask)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
if (matchesMask != null)
{
matchesMask.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
Mat matchesMask_mat = matchesMask;
features2d_Features2d_drawMatches_10(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj, matchColor.val[0], matchColor.val[1], matchColor.val[2], matchColor.val[3], singlePointColor.val[0], singlePointColor.val[1], singlePointColor.val[2], singlePointColor.val[3], matchesMask_mat.nativeObj);
return;
#else
return;
#endif
}
//
// C++: void cv::DescriptorMatcher::match(Mat queryDescriptors, vector_DMatch& matches, vector_Mat masks = vector_Mat())
//
//javadoc: DescriptorMatcher::match(queryDescriptors, matches, masks)
public void match(Mat queryDescriptors, MatOfDMatch matches, List <Mat> masks)
{
ThrowIfDisposed();
if (queryDescriptors != null)
{
queryDescriptors.ThrowIfDisposed();
}
if (matches != null)
{
matches.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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);
return;
#else
return;
#endif
}
//javadoc: drawMatches(img1, keypoints1, img2, keypoints2, matches1to2, outImg)
public static void drawMatches(Mat img1, MatOfKeyPoint keypoints1, Mat img2, MatOfKeyPoint keypoints2, MatOfDMatch matches1to2, Mat outImg)
{
if (img1 != null)
{
img1.ThrowIfDisposed();
}
if (keypoints1 != null)
{
keypoints1.ThrowIfDisposed();
}
if (img2 != null)
{
img2.ThrowIfDisposed();
}
if (keypoints2 != null)
{
keypoints2.ThrowIfDisposed();
}
if (matches1to2 != null)
{
matches1to2.ThrowIfDisposed();
}
if (outImg != null)
{
outImg.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat keypoints1_mat = keypoints1;
Mat keypoints2_mat = keypoints2;
Mat matches1to2_mat = matches1to2;
features2d_Features2d_drawMatches_14(img1.nativeObj, keypoints1_mat.nativeObj, img2.nativeObj, keypoints2_mat.nativeObj, matches1to2_mat.nativeObj, outImg.nativeObj);
return;
#else
return;
#endif
}
//
// C++: void cv::ShapeTransformer::estimateTransformation(Mat transformingShape, Mat targetShape, vector_DMatch matches)
//
//javadoc: ShapeTransformer::estimateTransformation(transformingShape, targetShape, matches)
public void estimateTransformation(Mat transformingShape, Mat targetShape, MatOfDMatch matches)
{
ThrowIfDisposed();
if (transformingShape != null)
{
transformingShape.ThrowIfDisposed();
}
if (targetShape != null)
{
targetShape.ThrowIfDisposed();
}
if (matches != null)
{
matches.ThrowIfDisposed();
}
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
Mat matches_mat = matches;
shape_ShapeTransformer_estimateTransformation_10(nativeObj, transformingShape.nativeObj, targetShape.nativeObj, matches_mat.nativeObj);
return;
#else
return;
#endif
}
