/// <summary>
/// Find best matches for each query descriptor which have distance less than
/// maxDistance (in increasing order of distances).
/// </summary>
/// <param name="queryDescriptors"></param>
/// <param name="maxDistance"></param>
/// <param name="masks"></param>
/// <param name="compactResult"></param>
/// <returns></returns>
public DMatch[][] RadiusMatch(Mat queryDescriptors, float maxDistance, Mat[] masks = null, bool compactResult = false)
{
ThrowIfDisposed();
if (queryDescriptors == null)
throw new ArgumentNullException("queryDescriptors");
var masksPtrs = new IntPtr[0];
if (masks != null)
{
masksPtrs = EnumerableEx.SelectPtrs(masks);
}
using (var matchesVec = new VectorOfVectorDMatch())
{
NativeMethods.features2d_DescriptorMatcher_radiusMatch2(
ptr, queryDescriptors.CvPtr, matchesVec.CvPtr, maxDistance,
masksPtrs, masksPtrs.Length, compactResult ? 1 : 0);
return matchesVec.ToArray();
}
}
/// <summary>
/// Performs images matching.
/// </summary>
/// <param name="features">Features of the source images</param>
/// <param name="mask">Mask indicating which image pairs must be matched</param>
/// <returns>Found pairwise matches</returns>
public virtual MatchesInfo[] Apply(
IEnumerable <ImageFeatures> features, Mat?mask = null)
{
if (features == null)
{
throw new ArgumentNullException(nameof(features));
}
ThrowIfDisposed();
var featuresArray = features.CastOrToArray();
if (featuresArray.Length == 0)
{
throw new ArgumentException("Empty features array", nameof(features));
}
var keypointVecs = new VectorOfKeyPoint?[featuresArray.Length];
var wImageFeatures = new WImageFeatures[featuresArray.Length];
try
{
for (int i = 0; i < featuresArray.Length; i++)
{
if (featuresArray[i].Descriptors == null)
{
throw new ArgumentException("features contain null descriptor mat", nameof(features));
}
featuresArray[i].Descriptors.ThrowIfDisposed();
keypointVecs[i] = new VectorOfKeyPoint();
wImageFeatures[i] = new WImageFeatures
{
ImgIdx = featuresArray[i].ImgIdx,
ImgSize = featuresArray[i].ImgSize,
Keypoints = keypointVecs[i] !.CvPtr,
Descriptors = featuresArray[i].Descriptors.CvPtr,
};
}
using var srcImgIndexVecs = new VectorOfInt32();
using var dstImgIndexVecs = new VectorOfInt32();
using var matchesVec = new VectorOfVectorDMatch();
using var inlinersMaskVec = new VectorOfVectorByte();
using var numInliersVecs = new VectorOfInt32();
using var hVecs = new VectorOfMat();
using var confidenceVecs = new VectorOfDouble();
NativeMethods.HandleException(
NativeMethods.stitching_FeaturesMatcher_apply2(
ptr,
wImageFeatures, wImageFeatures.Length,
mask?.CvPtr ?? IntPtr.Zero,
srcImgIndexVecs.CvPtr,
dstImgIndexVecs.CvPtr,
matchesVec.CvPtr,
inlinersMaskVec.CvPtr,
numInliersVecs.CvPtr,
hVecs.CvPtr,
confidenceVecs.CvPtr
));
var srcImgIndices = srcImgIndexVecs.ToArray();
var dstImgIndices = dstImgIndexVecs.ToArray();
var matches = matchesVec.ToArray();
var inlinersMasks = inlinersMaskVec.ToArray();
var numInliers = numInliersVecs.ToArray();
var hs = hVecs.ToArray();
var confidences = confidenceVecs.ToArray();
var result = new MatchesInfo[srcImgIndices.Length];
for (int i = 0; i < srcImgIndices.Length; i++)
{
result[i] = new MatchesInfo(
srcImgIndices[i],
dstImgIndices[i],
matches[i],
inlinersMasks[i],
numInliers[i],
hs[i],
confidences[i]);
}
return(result);
}
finally
{
foreach (var vec in keypointVecs)
{
vec?.Dispose();
}
GC.KeepAlive(this);
}
}
/// <summary>
/// Find best matches for each query descriptor which have distance less than
/// maxDistance (in increasing order of distances).
/// </summary>
/// <param name="queryDescriptors"></param>
/// <param name="trainDescriptors"></param>
/// <param name="maxDistance"></param>
/// <param name="mask"></param>
/// <param name="compactResult"></param>
/// <returns></returns>
public DMatch[][] RadiusMatch(Mat queryDescriptors, Mat trainDescriptors,
float maxDistance, Mat mask = null, bool compactResult = false)
{
ThrowIfDisposed();
if (queryDescriptors == null)
throw new ArgumentNullException("queryDescriptors");
if (trainDescriptors == null)
throw new ArgumentNullException("trainDescriptors");
using (var matchesVec = new VectorOfVectorDMatch())
{
NativeMethods.features2d_DescriptorMatcher_radiusMatch1(
ptr, queryDescriptors.CvPtr, trainDescriptors.CvPtr,
matchesVec.CvPtr, maxDistance, Cv2.ToPtr(mask), compactResult ? 1 : 0);
return matchesVec.ToArray();
}
}
