/// <summary>
/// Find rectangular regions in the given image that are likely to contain objects of
/// loaded classes (models) and corresponding confidence levels.
/// </summary>
/// <param name="image">An image.</param>
/// <param name="overlapThreshold">Threshold for the non-maximum suppression algorithm.</param>
/// <param name="numThreads">Number of threads used in parallel version of the algorithm.</param>
/// <returns>The detections: rectangulars, scores and class IDs.</returns>
public virtual ObjectDetection[] Detect(Mat image,
float overlapThreshold = 0.5f, int numThreads = -1)
{
if (disposed)
{
throw new ObjectDisposedException("LatentSvmDetector");
}
if (image == null)
{
throw new ArgumentNullException("image");
}
image.ThrowIfDisposed();
using (var odVec = new VectorOfVec6d())
{
NativeMethods.objdetect_LatentSvmDetector_detect(
ptr, image.CvPtr, odVec.CvPtr, overlapThreshold, numThreads);
return(EnumerableEx.SelectToArray(odVec.ToArray(), v =>
new ObjectDetection
{
Rect = new Rect((int)v.Item0, (int)v.Item1, (int)v.Item2, (int)v.Item3),
Score = (float)v.Item4,
ClassId = (int)v.Item5
}
));
}
}
/// <summary>
/// Draws matches of keypints from two images on output image.
/// </summary>
/// <param name="img1"></param>
/// <param name="keypoints1"></param>
/// <param name="img2"></param>
/// <param name="keypoints2"></param>
/// <param name="matches1To2"></param>
/// <param name="outImg"></param>
/// <param name="matchColor"></param>
/// <param name="singlePointColor"></param>
/// <param name="matchesMask"></param>
/// <param name="flags"></param>
public static void DrawMatches(Mat img1, IEnumerable <KeyPoint> keypoints1,
Mat img2, IEnumerable <KeyPoint> keypoints2,
IEnumerable <IEnumerable <DMatch> > matches1To2, Mat outImg,
Scalar?matchColor = null, Scalar?singlePointColor = null,
IEnumerable <IEnumerable <byte> > matchesMask = null,
DrawMatchesFlags flags = DrawMatchesFlags.Default)
{
if (img1 == null)
{
throw new ArgumentNullException(nameof(img1));
}
if (img2 == null)
{
throw new ArgumentNullException(nameof(img2));
}
if (outImg == null)
{
throw new ArgumentNullException(nameof(outImg));
}
if (keypoints1 == null)
{
throw new ArgumentNullException(nameof(keypoints1));
}
if (keypoints2 == null)
{
throw new ArgumentNullException(nameof(keypoints2));
}
if (matches1To2 == null)
{
throw new ArgumentNullException(nameof(matches1To2));
}
img1.ThrowIfDisposed();
img2.ThrowIfDisposed();
outImg.ThrowIfDisposed();
KeyPoint[] keypoints1Array = EnumerableEx.ToArray(keypoints1);
KeyPoint[] keypoints2Array = EnumerableEx.ToArray(keypoints2);
DMatch[][] matches1To2Array = EnumerableEx.SelectToArray(matches1To2, EnumerableEx.ToArray);
int matches1To2Size1 = matches1To2Array.Length;
int[] matches1To2Size2 = EnumerableEx.SelectToArray(matches1To2Array, dm => dm.Length);
Scalar matchColor0 = matchColor.GetValueOrDefault(Scalar.All(-1));
Scalar singlePointColor0 = singlePointColor.GetValueOrDefault(Scalar.All(-1));
using (var matches1To2Ptr = new ArrayAddress2 <DMatch>(matches1To2Array))
{
if (matchesMask == null)
{
NativeMethods.features2d_drawMatches2(img1.CvPtr, keypoints1Array, keypoints1Array.Length,
img2.CvPtr, keypoints2Array, keypoints2Array.Length,
matches1To2Ptr, matches1To2Size1, matches1To2Size2,
outImg.CvPtr, matchColor0, singlePointColor0,
null, 0, null, (int)flags);
}
else
{
byte[][] matchesMaskArray = EnumerableEx.SelectToArray(matchesMask, EnumerableEx.ToArray);
int matchesMaskSize1 = matches1To2Array.Length;
int[] matchesMaskSize2 = EnumerableEx.SelectToArray(matchesMaskArray, dm => dm.Length);
using (var matchesMaskPtr = new ArrayAddress2 <byte>(matchesMaskArray))
{
NativeMethods.features2d_drawMatches2(img1.CvPtr, keypoints1Array, keypoints1Array.Length,
img2.CvPtr, keypoints2Array, keypoints2Array.Length,
matches1To2Ptr.Pointer, matches1To2Size1, matches1To2Size2,
outImg.CvPtr, matchColor0, singlePointColor0,
matchesMaskPtr, matchesMaskSize1, matchesMaskSize2, (int)flags);
}
}
}
}