// ROI: Region of Interest
private bool myDetector(InputArray image, out System.Drawing.Rectangle[] ROIs)
{
Mat gray = null;
// Convert multi-channel BGR image to gray
if (image.GetChannels() > 1)
{
CvInvoke.CvtColor(image.GetMat(), gray, ColorConversion.Bgr2Gray);
}
else
{
gray = image.GetMat().Clone();
}
CvInvoke.EqualizeHist(gray, gray);
ROIs = faceCsc.DetectMultiScale(gray, 1.1, 3, Size.Empty);
return(true);
}
/// <summary>
/// Get the color type of the image
/// </summary>
/// <param name="image">The image to apply reflection on</param>
/// <returns>The color type of the image</returns>
public static Type GetTypeOfColor(IInputArray image)
{
Type baseType = Toolbox.GetBaseType(image.GetType(), "Image`2") ??
Toolbox.GetBaseType(image.GetType(), "CudaImage`2");
if (baseType != null)
{
return(baseType.GetGenericArguments()[0]);
}
else
{
using (InputArray ia = image.GetInputArray())
{
int numberOfChannels = ia.GetChannels();
return
(numberOfChannels == 1 ? typeof(Gray) :
numberOfChannels == 3 ? typeof(Bgr) :
numberOfChannels == 4 ? typeof(Bgra) :
null);
}
}
}
/// <summary>
/// Generate histograms for the image. One histogram is generated for each color channel.
/// You will need to call the Refresh function to do the painting afterward.
/// </summary>
/// <param name="image">The image to generate histogram from</param>
/// <param name="numberOfBins">The number of bins for each histogram</param>
public void GenerateHistograms(IInputArray image, int numberOfBins)
{
using (InputArray iaImage = image.GetInputArray())
{
int channelCount = iaImage.GetChannels();
Mat[] channels = new Mat[channelCount];
Type imageType;
if ((imageType = Toolbox.GetBaseType(image.GetType(), "Image`2")) != null ||
(imageType = Toolbox.GetBaseType(image.GetType(), "Mat")) != null ||
(imageType = Toolbox.GetBaseType(image.GetType(), "UMat")) != null)
{
for (int i = 0; i < channelCount; i++)
{
Mat channel = new Mat();
CvInvoke.ExtractChannel(image, channel, i);
channels[i] = channel;
}
}
else if ((imageType = Toolbox.GetBaseType(image.GetType(), "CudaImage`2")) != null)
{
using (Mat img = imageType.GetMethod("ToMat").Invoke(image, null) as Mat)
for (int i = 0; i < channelCount; i++)
{
Mat channel = new Mat();
CvInvoke.ExtractChannel(img, channel, i);
channels[i] = channel;
}
}
else
{
throw new ArgumentException(String.Format("The input image type of {0} is not supported",
image.GetType().ToString()));
}
Type[] genericArguments = imageType.GetGenericArguments();
String[] channelNames;
Color[] colors;
Type typeOfDepth;
if (genericArguments.Length > 0)
{
IColor typeOfColor = Activator.CreateInstance(genericArguments[0]) as IColor;
channelNames = Reflection.ReflectColorType.GetNamesOfChannels(typeOfColor);
colors = Reflection.ReflectColorType.GetDisplayColorOfChannels(typeOfColor);
typeOfDepth = imageType.GetGenericArguments()[1];
}
else
{
channelNames = new String[channelCount];
colors = new Color[channelCount];
for (int i = 0; i < channelCount; i++)
{
channelNames[i] = String.Format("Channel {0}", i);
colors[i] = Color.Red;
}
if (image is Mat)
{
typeOfDepth = CvInvoke.GetDepthType(((Mat)image).Depth);
}
else if (image is UMat)
{
typeOfDepth = CvInvoke.GetDepthType(((UMat)image).Depth);
}
else
{
throw new ArgumentException(String.Format(
"Unable to get the type of depth from image of type {0}", image.GetType().ToString()));
}
}
float minVal, maxVal;
#region Get the maximum and minimum color intensity values
if (typeOfDepth == typeof(Byte))
{
minVal = 0.0f;
maxVal = 256.0f;
}
else
{
#region obtain the maximum and minimum color value
double[] minValues, maxValues;
Point[] minLocations, maxLocations;
using (InputArray ia = image.GetInputArray())
using (Mat m = ia.GetMat())
{
m.MinMax(out minValues, out maxValues, out minLocations, out maxLocations);
double min = minValues[0], max = maxValues[0];
for (int i = 1; i < minValues.Length; i++)
{
if (minValues[i] < min)
{
min = minValues[i];
}
if (maxValues[i] > max)
{
max = maxValues[i];
}
}
minVal = (float)min;
maxVal = (float)max;
}
#endregion
}
#endregion
Mat[] histograms = new Mat[channels.Length];
for (int i = 0; i < channels.Length; i++)
{
//using (DenseHistogram hist = new DenseHistogram(numberOfBins, new RangeF(minVal, maxVal)))
using (Mat hist = new Mat())
using (Util.VectorOfMat vm = new Util.VectorOfMat())
{
vm.Push(channels[i]);
float[] ranges = new float[] { minVal, maxVal };
CvInvoke.CalcHist(vm, new int[] { 0 }, null, hist, new int[] { numberOfBins }, ranges, false);
//hist.Calculate(new IImage[1] { channels[i] }, true, null);
histograms[i] = GenerateHistogram(channelNames[i], colors[i], hist, numberOfBins, ranges);
}
}
if (histograms.Length == 1)
{
this.Image = histograms[0];
}
else
{
int maxWidth = 0;
int totalHeight = 0;
for (int i = 0; i < histograms.Length; i++)
{
maxWidth = Math.Max(maxWidth, histograms[i].Width);
totalHeight += histograms[i].Height;
}
Mat concated = new Mat(new Size(maxWidth, totalHeight), histograms[0].Depth, histograms[0].NumberOfChannels);
int currentY = 0;
for (int i = 0; i < histograms.Length; i++)
{
using (Mat roi = new Mat(concated, new Rectangle(new Point(0, currentY), histograms[i].Size)))
{
histograms[i].CopyTo(roi);
}
currentY += histograms[i].Height;
histograms[i].Dispose();
}
this.Image = concated;
}
}
}