/// <summary>
///
/// </summary>
/// <param name="radius">The radius used for building the Circular Local Binary Pattern. The greater the radius, the</param>
/// <param name="neighbors">The number of sample points to build a Circular Local Binary Pattern from.
/// An appropriate value is to use `8` sample points.Keep in mind: the more sample points you include, the higher the computational cost.</param>
/// <param name="gridX">The number of cells in the horizontal direction, 8 is a common value used in publications.
/// The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.</param>
/// <param name="gridY">The number of cells in the vertical direction, 8 is a common value used in publications.
/// The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.</param>
/// <param name="threshold">The threshold applied in the prediction. If the distance to the nearest neighbor
/// is larger than the threshold, this method returns -1.</param>
/// <returns></returns>
public static LBPHFaceRecognizer CreateLBPHFaceRecognizer(int radius = 1, int neighbors = 8,
int gridX = 8, int gridY = 8, double threshold = Double.MaxValue)
{
IntPtr p = NativeMethods.face_createLBPHFaceRecognizer(radius, neighbors, gridX, gridY, threshold);
return(LBPHFaceRecognizer.FromPtr(p));
}
/// <summary>
/// Creates instance from cv::Ptr<T> .
/// ptr is disposed when the wrapper disposes.
/// </summary>
/// <param name="ptr"></param>
internal new static LBPHFaceRecognizer FromPtr(IntPtr ptr)
{
if (ptr == IntPtr.Zero)
{
throw new OpenCvSharpException($"Invalid cv::Ptr<{nameof(LBPHFaceRecognizer)}> pointer");
}
var ptrObj = new Ptr(ptr);
var detector = new LBPHFaceRecognizer
{
recognizerPtr = ptrObj,
ptr = ptrObj.Get()
};
return(detector);
}
/// <summary>
/// The Circular Local Binary Patterns (used in training and prediction) expect the data given as
/// grayscale images, use cvtColor to convert between the color spaces.
/// This model supports updating.
/// </summary>
/// <param name="radius">The radius used for building the Circular Local Binary Pattern. The greater the radius, the</param>
/// <param name="neighbors">The number of sample points to build a Circular Local Binary Pattern from.
/// An appropriate value is to use `8` sample points.Keep in mind: the more sample points you include, the higher the computational cost.</param>
/// <param name="gridX">The number of cells in the horizontal direction, 8 is a common value used in publications.
/// The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.</param>
/// <param name="gridY">The number of cells in the vertical direction, 8 is a common value used in publications.
/// The more cells, the finer the grid, the higher the dimensionality of the resulting feature vector.</param>
/// <param name="threshold">The threshold applied in the prediction. If the distance to the nearest neighbor
/// is larger than the threshold, this method returns -1.</param>
/// <returns></returns>
// ReSharper disable once InconsistentNaming
public static LBPHFaceRecognizer Create(int radius = 1, int neighbors = 8,
int gridX = 8, int gridY = 8, double threshold = double.MaxValue)
{
IntPtr p = NativeMethods.face_LBPHFaceRecognizer_create(radius, neighbors, gridX, gridY, threshold);
if (p == IntPtr.Zero)
{
throw new OpenCvSharpException($"Invalid cv::Ptr<{nameof(LBPHFaceRecognizer)}> pointer");
}
var ptrObj = new Ptr(p);
var detector = new LBPHFaceRecognizer
{
recognizerPtr = ptrObj,
ptr = ptrObj.Get()
};
return(detector);
}