/// <summary>
/// サンプル集合からガウス混合パラメータを推定する
/// </summary>
/// <param name="samples"></param>
/// <param name="means0"></param>
/// <param name="covs0"></param>
/// <param name="weights0"></param>
/// <param name="logLikelihoods"></param>
/// <param name="labels"></param>
/// <param name="probs"></param>
#else
/// <summary>
/// Estimates Gaussian mixture parameters from the sample set
/// </summary>
/// <param name="samples"></param>
/// <param name="means0"></param>
/// <param name="covs0"></param>
/// <param name="weights0"></param>
/// <param name="logLikelihoods"></param>
/// <param name="labels"></param>
/// <param name="probs"></param>
#endif
public virtual bool TrainE(
InputArray samples,
InputArray means0,
InputArray covs0 = null,
InputArray weights0 = null,
OutputArray logLikelihoods = null,
OutputArray labels = null,
OutputArray probs = null)
{
if (disposed)
{
throw new ObjectDisposedException(GetType().Name);
}
if (samples == null)
{
throw new ArgumentNullException(nameof(samples));
}
if (means0 == null)
{
throw new ArgumentNullException(nameof(means0));
}
samples.ThrowIfDisposed();
means0.ThrowIfDisposed();
if (logLikelihoods != null)
{
logLikelihoods.ThrowIfNotReady();
}
if (covs0 != null)
{
covs0.ThrowIfDisposed();
}
if (weights0 != null)
{
weights0.ThrowIfDisposed();
}
if (labels != null)
{
labels.ThrowIfNotReady();
}
if (probs != null)
{
probs.ThrowIfNotReady();
}
int ret = NativeMethods.ml_EM_trainE(
ptr,
samples.CvPtr,
means0.CvPtr,
Cv2.ToPtr(covs0),
Cv2.ToPtr(weights0),
Cv2.ToPtr(logLikelihoods),
Cv2.ToPtr(labels),
Cv2.ToPtr(probs));
if (logLikelihoods != null)
{
logLikelihoods.Fix();
}
if (labels != null)
{
labels.Fix();
}
if (probs != null)
{
probs.Fix();
}
GC.KeepAlive(samples);
GC.KeepAlive(means0);
GC.KeepAlive(covs0);
GC.KeepAlive(weights0);
return(ret != 0);
}
/// <summary>
/// Merges images.
/// </summary>
/// <param name="src">vector of input images</param>
/// <param name="dst">result image</param>
/// <param name="times">vector of exposure time values for each image</param>
/// <param name="response"> 256x1 matrix with inverse camera response function for each pixel value, it should have the same number of channels as images.</param>
public virtual void Process(IEnumerable <Mat> src, OutputArray dst, IEnumerable <float> times, InputArray response)
{
if (src == null)
{
throw new ArgumentNullException(nameof(src));
}
if (dst == null)
{
throw new ArgumentNullException(nameof(dst));
}
if (times == null)
{
throw new ArgumentNullException(nameof(times));
}
if (response == null)
{
throw new ArgumentNullException(nameof(response));
}
dst.ThrowIfNotReady();
var srcArray = EnumerableEx.SelectPtrs(src);
var timesArray = EnumerableEx.ToArray(times);
if (srcArray.Length != timesArray.Length)
{
throw new OpenCvSharpException("src.Count() != times.Count");
}
NativeMethods.photo_MergeExposures_process(ptr, srcArray, srcArray.Length, dst.CvPtr, timesArray, response.CvPtr);
dst.Fix();
GC.KeepAlive(this);
GC.KeepAlive(src);
GC.KeepAlive(dst);
GC.KeepAlive(response);
}
/// <summary>
///
/// </summary>
/// <param name="mat"></param>
/// <param name="distType"></param>
/// <param name="a"></param>
/// <param name="b"></param>
/// <param name="saturateRange"></param>
public void Fill(InputOutputArray mat, DistributionType distType, InputArray a, InputArray b, bool saturateRange = false)
{
if (mat == null)
{
throw new ArgumentNullException("mat");
}
if (a == null)
{
throw new ArgumentNullException("a");
}
if (b == null)
{
throw new ArgumentNullException("b");
}
mat.ThrowIfNotReady();
a.ThrowIfDisposed();
b.ThrowIfDisposed();
NativeMethods.core_RNG_fill(State, mat.CvPtr, (int)distType, a.CvPtr, b.CvPtr, saturateRange ? 1 : 0);
mat.Fix();
}
/// <summary>
/// Decodes QR codes in image once it's found by the detect() method.
/// Returns UTF8-encoded output string or empty string if the code cannot be decoded.
/// </summary>
/// <param name="img">grayscale or color (BGR) image containing QR code.</param>
/// <param name="points">Quadrangle vertices found by detect() method (or some other algorithm).</param>
/// <param name="decodedInfo">UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded. </param>
/// <param name="straightQrCode">The optional output image containing rectified and binarized QR code</param>
/// <returns></returns>
public bool DecodeMulti(InputArray img, IEnumerable <Point2f> points, out string?[] decodedInfo, out Mat[] straightQrCode)
{
return(DecodeMulti(img, points, out decodedInfo, out straightQrCode, true));
}
/// <summary>
/// Decodes QR codes in image once it's found by the detect() method.
/// Returns UTF8-encoded output string or empty string if the code cannot be decoded.
/// </summary>
/// <param name="img">grayscale or color (BGR) image containing QR code.</param>
/// <param name="points">Quadrangle vertices found by detect() method (or some other algorithm).</param>
/// <param name="decodedInfo">UTF8-encoded output vector of string or empty vector of string if the codes cannot be decoded. </param>
/// <returns></returns>
public bool DecodeMulti(InputArray img, IEnumerable <Point2f> points, out string?[] decodedInfo)
{
return(DecodeMulti(img, points, out decodedInfo, out _, false));
}
/// <summary> /// /// </summary> /// <param name="frame0"></param> /// <param name="frame1"></param> /// <param name="flow"></param> public abstract void Calc(InputArray frame0, InputArray frame1, InputOutputArray flow);
/// <summary>
/// Calculates all of the moments
/// up to the third order of a polygon or rasterized shape.
/// </summary>
/// <param name="array">A raster image (single-channel, 8-bit or floating-point
/// 2D array) or an array ( 1xN or Nx1 ) of 2D points ( Point or Point2f )</param>
/// <param name="binaryImage">If it is true, then all the non-zero image pixels are treated as 1’s</param>
/// <returns></returns>
private void InitializeFromInputArray(InputArray array, bool binaryImage)
{
var m = NativeMethods.imgproc_moments(array.CvPtr, binaryImage ? 1 : 0);
Initialize(m.m00, m.m10, m.m01, m.m20, m.m11, m.m02, m.m30, m.m21, m.m12, m.m03);
}
/// <summary> /// /// </summary> /// <param name="frame0"></param> /// <param name="frame1"></param> /// <param name="flow"></param> protected abstract void Calc(InputArray frame0, InputArray frame1, InputOutputArray flow);
