static void PI(int img)
{
System.Console.WriteLine(DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss.fff"));
Image <Rgba32> image = Image.Load("data\\" + img + ".bmp");
image.Mutate(ctx => ctx.Resize(image.Width / 8, image.Height / 8));
double ConversionFactor = 255 / (5 - 1);
double AverageValue;
MatrixData m = new MatrixData(image.Width, image.Height);
for (int r = 0; r < image.Width; r++)
{
for (int c = 0; c < image.Height; c++)
{
AverageValue = (image[r, c].R + image[r, c].B + image[r, c].G) / 3;
double pv = ((AverageValue / ConversionFactor) + 0.5) * ConversionFactor;
if (pv < 200)
{
pv = 0;
}
m[r, c] = pv;
}
}
m = m.HistEQ();
int mp = (int)m.MeanIfPixel((s) => { return(s > 0); });
for (int r = 0; r < image.Width; r++)
{
for (int c = 0; c < image.Height; c++)
{
if (m[r, c] < mp)
{
m[r, c] = 0;
}
}
}
m = m.HistEQ();
mp = (int)m.MeanIfPixel((s) => { return(s > 0); });
m = m.NormalizeAllBetween(mp, 255) * 255;
m = m - vm;
Tuple <int, int> centerBlob = new Tuple <int, int>(0, 0);
Tuple <int, int> center = new Tuple <int, int>(image.Width / 2, image.Height / 2);
m = m.ToBinary(m.MeanIfPixel((s) => { return(s > 0); })).GetLargestBlob(ref centerBlob);
System.Console.WriteLine(DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss.fff"));
double angle = Math.Atan2(centerBlob.Item1 - center.Item2, centerBlob.Item1 - center.Item1) * (180 / Math.PI);
double dist = Math.Abs(Math.Pow(centerBlob.Item1 - centerBlob.Item2, 2) + Math.Pow(center.Item1 - center.Item2, 2));
List <dynamic> output = m.GetVectorizedMatrix().ToList();
output.Add(angle);
System.Console.WriteLine("image loaded");
}
public dynamic[] ProcessImage2(dynamic[] input)
{
//Turn the input vector into a matrix
//This matrix represents the image
MatrixData pixelMatrix = input.GetReShapedMatrix(19);
//Get the emboss edge
pixelMatrix = pixelMatrix.GetEmbossEdge();
//Apply with hist EQ function
pixelMatrix = pixelMatrix.HistEQ();
//Crop 1 pixel off the edge of the image
//this results in a 17x17 image
pixelMatrix = pixelMatrix.CropEdges(1);
//reduce the size of the image to 16x16 by removing
// a random pixel from each row and column
pixelMatrix = pixelMatrix.ReduceDimensionByOne(0).ReduceDimensionByOne(1);
//Blur the image
pixelMatrix = pixelMatrix.ApplyConvolutionFilter(blurFilter);
//Reduce the 16x16 image to 8x8 using a custom downsampling algorithm
pixelMatrix = pixelMatrix.DownScale(2);
//Clamp the output matrix values between 0 and 255
pixelMatrix = pixelMatrix.Clamp(0, 255);
//return the pixel matrix as a vector
// the size of this vector will be 36 (6x6)
return(pixelMatrix.GetVectorizedMatrix());
}
public dynamic[] ProcessImage3(dynamic[] input)
{
//Turn the input vector into a matrix
//This matrix represents the image
MatrixData pixelMatrix = input.GetReShapedMatrix(19);
//hadamard product
pixelMatrix = pixelMatrix * averageFace;
//reduce the size of the image to 18x18 by removing
// a random pixel from each row and column
pixelMatrix = pixelMatrix.ReduceDimensionByOne(0).ReduceDimensionByOne(1);
pixelMatrix = pixelMatrix.HistEQ();
return(pixelMatrix.DownScale(2, false).GetVectorizedMatrix());
}