private float[] GetGrad(Models.Image image, int line_x, int line_y, int rows_AVG, int line_length)
{
//throw new NotImplementedException();
float[] averaged_grad = new float[Convert.ToInt32(image_cnv.Width)];
for (int i = line_x; i < line_x + line_length; i++)
{
float sumDiff = 0; int count = 0;
for (int j = Convert.ToInt32(line_y - rows_AVG / 2); j < Convert.ToInt32(line_y + rows_AVG / 2); j++)
{
sumDiff += Math.Abs(image.pixels[j][i + 1] - image.pixels[j][i]);
count++;
}
averaged_grad[Convert.ToInt32(profile_ln.Margin.Left) + i - line_x] = sumDiff / count;
}
return(averaged_grad);
}
private float[] GetProf(Models.Image image, int line_x, int line_y, int rows_AVG, int line_length)
{
//throw new NotImplementedException();
float[] averaged_row = new float[Convert.ToInt32(image_cnv.Width)];
for (int i = line_x; i < line_x + line_length; i++)
{
//loop through and get the average based on the thickness of the line.
float sum = 0; int count = 0;
for (int j = Convert.ToInt32(line_y - rows_AVG / 2); j < Convert.ToInt32(line_y + rows_AVG / 2); j++)
{
sum += image.pixels[j][i];
count++;
}
averaged_row[Convert.ToInt32(profile_ln.Margin.Left) + i - line_x] = sum / count;
}
return(averaged_row);
}
public static BitmapSource DrawImage(Models.Image image)
{
//PD_AdvAnalysis.WLAnalysis wla = new PD_AdvAnalysis.WLAnalysis();
//System.Windows.Controls.Image imag = wla.field_img; //System.Windows.Application.Current.MainWindow.FindName("field_img") as System.Windows.Controls.Image;
WL_AutoDetectTest.MainWindow mw = new WL_AutoDetectTest.MainWindow();
System.Windows.Controls.Image imag = mw.image_im;
int w = Convert.ToInt32(imag.Width); int h = Convert.ToInt32(imag.Height);
double[] image_pixels = new double[w * h];
int index_out = 0;
//this does a lot of the scaling. It insures the size of the image is the same as the size of the canvas.
for (int j = (image.sizeY + h) / 2; j > (image.sizeY - h) / 2; j--)//I'm not sure why this has to be backward from the PD analysis code
{
int index_in = 0;
for (int k = (image.sizeX - w) / 2; k < (image.sizeX + w) / 2; k++)
{
image_pixels[index_in + index_out * w] = image.pixels[j][k];
index_in++;
}
//index_out+=zoom_level;
index_out++; //no zoom implemented in this code.
}
double image_max = image_pixels.Max();
double image_min = image_pixels.Min();
//byte[] image_bytes = new byte[image_pixels.Length * sizeof(UInt16)];
//Buffer.BlockCopy(image_pixels, 0, image_bytes, 0, image_bytes.Length);
PixelFormat format = PixelFormats.Rgb24;
//get min and max of the data.
//iamge min now comes from the method input parameter image_min
//image_min = image_pixels.Min();//this is the red value. I.e. 255,0,0
//image_max = image_pixels.Max();//this is the blue value. i.e. 0,0,255.
double image_med = (image_max + image_min) / 2;
int stride = (w * format.BitsPerPixel + 7) / 8;
byte[] image_bytes = new byte[stride * h];
//copy data to image bytes
for (int j = 0; j < image_pixels.Length; j++)
{
double value = image_pixels[j];
if (value < 0)
{
MessageBox.Show("hello");
}
System.Windows.Media.Color c = new System.Windows.Media.Color();
if (value < image_min)
{
c.B = 0;
c.R = 0;
c.G = 0;
}
else if (value < image_med)
{
c.R = 0;
c.B = Convert.ToByte(255 - (255 * (value - image_min) / (image_med - image_min)));
c.G = Convert.ToByte(255 - (255 * (image_med - value) / (image_med - image_min)));
}
else if (value <= image_max)
{
c.B = 0;
c.R = Convert.ToByte(255 - (255 * (image_max - value) / (image_max - image_med)));
c.G = Convert.ToByte(255 - (255 * (value - image_med) / (image_max - image_med)));
}
else if (value > image_max)
{
c.R = 0;
c.B = 0;
c.G = 0;
}
image_bytes[j * 3] = c.R;
image_bytes[j * 3 + 1] = c.G;
image_bytes[j * 3 + 2] = c.B;
}
BitmapSource bmp = BitmapSource.Create(
w,
h,
10 * 2.54 / image.resX,
10 * 2.54 / image.resY,
format,
null,
image_bytes,
stride
);
return(bmp);
}
private void image_btn_Click(object sender, RoutedEventArgs e)
{
//global variable declaration
int xSize = 0;
int ySize = 0;
int data_line;
//load image here.
OpenFileDialog ofd = new OpenFileDialog();
ofd.RestoreDirectory = true;
ofd.Filter = "DXF Files (*.dxf)|*.dxf";
if (ofd.ShowDialog() == true)
{
bool line_count = false;
bool xSizeb = false;
bool ySizeb = false;
//List<float[]> image = new List<float[]>();
Models.Image image = new Models.Image();
foreach (string line in File.ReadAllLines(ofd.FileName))
{
if (line_count && xSizeb && ySizeb)
{
//this evaluates once you've found all 3.
float[] row = new float[ySize];
//image.sizeX = xSize; image.sizeY = ySize;
row = Array.ConvertAll(line.Split('\t'), float.Parse);
image.pixels.Add(row);
}
else
{
if (line.Contains("Size1"))
{
//xSizeb = int.TryParse(line.Split('=').Last(), out xSize);
image.sizeX = int.Parse(line.Split('=').Last());
xSizeb = true;
}
else if (line.Contains("Size2"))
{
//ySizeb = int.TryParse(line.Split('=').Last(), out ySize);
image.sizeY = int.Parse(line.Split('=').Last());
ySizeb = true;
}
else if (line.Contains("Res1"))
{
image.resX = double.Parse(line.Split('=').Last());
}
else if (line.Contains("Res2"))
{
image.resY = double.Parse(line.Split('=').Last());
}
else if (line == "[Data]")
{
line_count = true;
}
}
//line_count++;
}
//write image
if (line_count && ySizeb && xSizeb)
{
//float[,] image_f = new float[ySize, xSize];
//for(int i =0; i<image.Count; i++)
//{
// image_f.getrow = image[i];
//}
BitmapSource bms = WL_AutoDetectTest.ImageDecon2.DrawImage(image);
image_im.Source = bms;
//get x and y position of the line.
int line_x = Convert.ToInt32((image.sizeX - image_cnv.Width) / 2 + profile_ln.Margin.Left);
int line_y = Convert.ToInt32((image.sizeY - image_cnv.Height) / 2 + profile_ln.Margin.Top);
int rows_AVG = Convert.ToInt16(profile_ln.StrokeThickness);//some rounding issues may occur.
int line_length = Convert.ToInt32(profile_ln.Width);
//line orientation shoudl be here as well in order to allow the user to get vertical position.
//get profile row.
float[] profile = GetProf(image, line_x, line_y, rows_AVG, line_length);
plotCanv1(profile, profile_cnv);
float[] gradient = GetGrad(image, line_x, line_y, rows_AVG, line_length);
plotCanv1(gradient, gradient_cnv);
}
}
}
