public static float[] histogramFeatures(Image <Bgr, byte> src, Image <Gray, byte> mask)
{
Image <Lab, Byte> dst = src.Convert <Lab, Byte>();
DenseHistogram histo = new DenseHistogram(255, new RangeF(0, 255));
Image <Gray, Byte>[] channels = dst.Split();
histo.Calculate(new Image <Gray, Byte>[] { channels[0] }, true, mask);
CvInvoke.Normalize(histo, histo);
MatND <float> mat = new MatND <float>(255);
histo.CopyTo(mat);
float[] binValuesB = (float[])mat.ManagedArray;
histo.Clear();
histo.Calculate(new Image <Gray, Byte>[] { channels[1] }, true, mask);
CvInvoke.Normalize(histo, histo);
mat = new MatND <float>(255);
histo.CopyTo(mat);
float[] binValuesG = (float[])mat.ManagedArray;
histo.Clear();
histo.Calculate(new Image <Gray, Byte>[] { channels[2] }, true, mask);
CvInvoke.Normalize(histo, histo);
mat = new MatND <float>(255);
histo.CopyTo(mat);
float[] binValuesR = (float[])mat.ManagedArray;
histo.Clear();
return(binValuesB.Concat(binValuesG).Concat(binValuesR).ToArray());
}
private static void DebugVisualizer()
{
using (MatND <float> mat = new MatND <float>(3, 5, 1))
{
mat.SetRandNormal(new MCvScalar(), new MCvScalar(255));
VisualizerDevelopmentHost myHost =
new VisualizerDevelopmentHost(mat, typeof(MatNDVisualizer));
myHost.ShowVisualizer();
}
}
private static void DebugVisualizer()
{
using (MatND<float> mat = new MatND<float>(3, 5, 1))
{
mat.SetRandNormal(new MCvScalar(), new MCvScalar(255));
VisualizerDevelopmentHost myHost =
new VisualizerDevelopmentHost(mat, typeof(MatNDVisualizer));
myHost.ShowVisualizer();
}
}
public static float[] imageFeatures(Image <Bgr, byte> src, int w = 20, int h = 20)
{
Image <Bgr, float> copy = src.Convert <Bgr, float>();
copy = copy.Resize(w, h, Emgu.CV.CvEnum.Inter.Linear, false);
Mat[] channels = copy.Mat.Split();
int n = copy.Rows * copy.Cols;
float[] vectorOfFeature = new float[n * 3];
for (int i = 0; i < channels.Length; i++)
{
Mat c = channels[0].Reshape(1, n);
MatND <float> temp = new MatND <float>(n);
c.CopyTo(temp);
float[] partition = (float[])temp.ManagedArray;
partition.CopyTo(vectorOfFeature, i * n);
c.Dispose();
temp.Dispose();
}
channels = null;
copy.Dispose();
return(vectorOfFeature);
}
public void TestMatNDRuntimeSerialization()
{
using (MatND<float> mat = new MatND<float>(2, 3, 4, 5))
{
using (MemoryStream ms = new MemoryStream())
{
mat.SetRandNormal(new MCvScalar(100), new MCvScalar(50));
mat.SerializationCompressionRatio = 6;
System.Runtime.Serialization.Formatters.Binary.BinaryFormatter
formatter = new System.Runtime.Serialization.Formatters.Binary.BinaryFormatter();
formatter.Serialize(ms, mat);
Byte[] bytes = ms.GetBuffer();
using (MemoryStream ms2 = new MemoryStream(bytes))
{
Object o = formatter.Deserialize(ms2);
MatND<float> mat2 = (MatND<float>)o;
Assert.IsTrue(mat.Equals(mat2));
}
}
}
}
public void TestMatND()
{
using (MatND<float> mat = new MatND<float>(3, 5, 1))
{
mat.SetRandNormal(new MCvScalar(), new MCvScalar(255));
MatND<double> matD = mat.Convert<double>();
MCvMatND matND = matD.MCvMatND;
int rows = matND.dim[0].Size;
int cols = matND.dims >= 2 ? matND.dim[1].Size : 1;
int channels = matND.dims >= 3 ? matND.dim[2].Size : 1;
Matrix<double> matrix = new Matrix<double>(rows, cols, channels);
CvInvoke.cvCopy(matD, matrix, IntPtr.Zero);
//using (MatrixViewer viewer = new MatrixViewer())
{
//viewer.Matrix = matrix;
//viewer.ShowDialog();
}
}
}
protected override Arr CreateArr(int channels, Depth depth, int dim0, int dim1)
{
return(mat = new MatND(new[] { dim0, dim1 }, depth, channels));
}
internal static extern IntPtr cvCloneMatND(MatND mat);
