/// <summary>
/// Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.
/// The function scans the image several times at different scales. Each time it considers overlapping regions in the image.
/// It may also apply some heuristics to reduce number of analyzed regions, such as Canny prunning.
/// After it has proceeded and collected the candidate rectangles (regions that passed the classifier cascade), it groups them and returns a sequence of average rectangles for each large enough group.
/// </summary>
/// <param name="image">The image where the objects are to be detected from</param>
/// <param name="scaleFactor">The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%</param>
/// <param name="minNeighbors">Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. Use 3 for default.</param>
/// <param name="minSize">Minimum window size. Use Size.Empty for default, where it is set to the size of samples the classifier has been trained on (~20x20 for face detection)</param>
/// <param name="maxSize">Maximum window size. Use Size.Empty for default, where the parameter will be ignored.</param>
/// <returns>The objects detected, one array per channel</returns>
public Rectangle[] DetectMultiScale(IInputArray image, double scaleFactor = 1.1, int minNeighbors = 3, Size minSize = new Size(), Size maxSize = new Size())
{
using (Util.VectorOfRect rectangles = new Util.VectorOfRect())
using (InputArray iaImage = image.GetInputArray())
{
CvCascadeClassifierDetectMultiScale(_ptr, iaImage, rectangles, scaleFactor, minNeighbors, 0, ref minSize, ref maxSize);
return(rectangles.ToArray());
}
}
/// <summary>
/// Create the standard vector of VectorOfRect
/// </summary>
public VectorOfVectorOfRect(Rectangle[][] values)
: this()
{
using (VectorOfRect v = new VectorOfRect())
{
for (int i = 0; i < values.Length; i++)
{
v.Push(values[i]);
Push(v);
v.Clear();
}
}
}
/// <summary>
/// Convert the standard vector to arrays of int
/// </summary>
/// <returns>Arrays of int</returns>
public Rectangle[][] ToArrayOfArray()
{
int size = Size;
Rectangle[][] res = new Rectangle[size][];
for (int i = 0; i < size; i++)
{
using (VectorOfRect v = this[i])
{
res[i] = v.ToArray();
}
}
return(res);
}
/// <summary>
/// Push a value into the standard vector
/// </summary>
/// <param name="value">The value to be pushed to the vector</param>
public void Push(VectorOfRect value)
{
VectorOfVectorOfRectPush(_ptr, value.Ptr);
}
public DebuggerProxy(VectorOfRect v)
{
_v = v;
}
/// <summary>
/// Push multiple values from the other vector into this vector
/// </summary>
/// <param name="other">The other vector, from which the values will be pushed to the current vector</param>
public void Push(VectorOfRect other)
{
VectorOfRectPushVector(_ptr, other);
}
