/// <summary>
/// finds intrinsic and extrinsic parameters of a stereo camera
/// </summary>
/// <param name="objectPoints">Vector of vectors of the calibration pattern points.</param>
/// <param name="imagePoints1">Vector of vectors of the projections of the calibration pattern points, observed by the first camera.</param>
/// <param name="imagePoints2">Vector of vectors of the projections of the calibration pattern points, observed by the second camera.</param>
/// <param name="cameraMatrix1">Input/output first camera matrix</param>
/// <param name="distCoeffs1">Input/output vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements.
/// The output vector length depends on the flags.</param>
/// <param name="cameraMatrix2"> Input/output second camera matrix. The parameter is similar to cameraMatrix1 .</param>
/// <param name="distCoeffs2">Input/output lens distortion coefficients for the second camera. The parameter is similar to distCoeffs1 .</param>
/// <param name="imageSize">Size of the image used only to initialize intrinsic camera matrix.</param>
/// <param name="R">Output rotation matrix between the 1st and the 2nd camera coordinate systems.</param>
/// <param name="T">Output translation vector between the coordinate systems of the cameras.</param>
/// <param name="E">Output essential matrix.</param>
/// <param name="F">Output fundamental matrix.</param>
/// <param name="criteria">Termination criteria for the iterative optimization algorithm.</param>
/// <param name="flags">Different flags that may be zero or a combination of the CalibrationFlag values</param>
/// <returns></returns>
public static double StereoCalibrate(IEnumerable<InputArray> objectPoints,
IEnumerable<InputArray> imagePoints1,
IEnumerable<InputArray> imagePoints2,
InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
Size imageSize, OutputArray R,
OutputArray T, OutputArray E, OutputArray F,
TermCriteria? criteria = null,
CalibrationFlag flags = CalibrationFlag.FixIntrinsic)
{
if (objectPoints == null)
throw new ArgumentNullException("objectPoints");
if (imagePoints1 == null)
throw new ArgumentNullException("imagePoints1");
if (imagePoints2 == null)
throw new ArgumentNullException("imagePoints2");
if (cameraMatrix1 == null)
throw new ArgumentNullException("cameraMatrix1");
if (distCoeffs1 == null)
throw new ArgumentNullException("distCoeffs1");
if (cameraMatrix2 == null)
throw new ArgumentNullException("cameraMatrix2");
if (distCoeffs2 == null)
throw new ArgumentNullException("distCoeffs2");
cameraMatrix1.ThrowIfDisposed();
distCoeffs1.ThrowIfDisposed();
cameraMatrix2.ThrowIfDisposed();
distCoeffs2.ThrowIfDisposed();
cameraMatrix1.ThrowIfNotReady();
cameraMatrix2.ThrowIfNotReady();
distCoeffs1.ThrowIfNotReady();
distCoeffs2.ThrowIfNotReady();
IntPtr[] opPtrs = EnumerableEx.SelectPtrs(objectPoints);
IntPtr[] ip1Ptrs = EnumerableEx.SelectPtrs(imagePoints1);
IntPtr[] ip2Ptrs = EnumerableEx.SelectPtrs(imagePoints2);
TermCriteria criteria0 = criteria.GetValueOrDefault(
new TermCriteria(CriteriaType.Iteration | CriteriaType.Epsilon, 30, 1e-6));
double result =
NativeMethods.calib3d_stereoCalibrate_InputArray(
opPtrs, opPtrs.Length,
ip1Ptrs, ip1Ptrs.Length, ip2Ptrs, ip2Ptrs.Length,
cameraMatrix1.CvPtr, distCoeffs1.CvPtr,
cameraMatrix2.CvPtr, distCoeffs2.CvPtr,
imageSize, ToPtr(R), ToPtr(T), ToPtr(E), ToPtr(F),
criteria0, (int)flags
);
cameraMatrix1.Fix();
distCoeffs1.Fix();
cameraMatrix2.Fix();
distCoeffs2.Fix();
if (R != null)
R.Fix();
if (T != null)
T.Fix();
if (E != null)
E.Fix();
if (F != null)
F.Fix();
return result;
}
/// <summary>
/// clusters the input data using k-Means algorithm
/// </summary>
/// <param name="data"></param>
/// <param name="k"></param>
/// <param name="bestLabels"></param>
/// <param name="criteria"></param>
/// <param name="attempts"></param>
/// <param name="flags"></param>
/// <param name="centers"></param>
/// <returns></returns>
public static double Kmeans(InputArray data, int k, InputOutputArray bestLabels,
TermCriteria criteria, int attempts, KMeansFlag flags, OutputArray centers = null)
{
if (data == null)
throw new ArgumentNullException("data");
if (bestLabels == null)
throw new ArgumentNullException("bestLabels");
data.ThrowIfDisposed();
bestLabels.ThrowIfDisposed();
double ret = NativeMethods.core_kmeans(data.CvPtr, k, bestLabels.CvPtr, criteria, attempts, (int)flags, ToPtr(centers));
bestLabels.Fix();
if(centers != null)
centers.Fix();
return ret;
}