public Mat Detect(Mat mat)
{
byte[] array = new byte[_width * _height * mat.ElemSize()];
Marshal.Copy(mat.DataStart, array, 0, array.Length);
using (Image <Bgr, byte> image1 = new Image <Bgr, byte>(_width, _height))
{
image1.Bytes = array;
var frame = image1.Mat;
int cols = 640;
int rows = 480;
_net.SetInput(DnnInvoke.BlobFromImage(frame, 1, new System.Drawing.Size(300, 300), default(MCvScalar), false, false));
using (Emgu.CV.Mat matt = _net.Forward())
{
float[,,,] flt = (float[, , , ])matt.GetData();
for (int x = 0; x < flt.GetLength(2); x++)
{
if (flt[0, 0, x, 2] > _probability)
{
int X1 = Convert.ToInt32(flt[0, 0, x, 3] * cols);
int Y1 = Convert.ToInt32(flt[0, 0, x, 4] * rows);
int X2 = Convert.ToInt32(flt[0, 0, x, 5] * cols);
int Y2 = Convert.ToInt32(flt[0, 0, x, 6] * rows);
mat.Rectangle(new OpenCvSharp.Rect((int)X1, (int)Y1, (int)X2 - (int)X1, (int)Y2 - (int)Y1), Scalar.Red);
}
}
}
}
return(mat);
}
public void Run()
{
Mat src = Cv2.ImRead(FilePath.Image.Lenna, ImreadModes.GrayScale);
// Histogram view
const int Width = 260, Height = 200;
Mat render = new Mat(new Size(Width, Height), MatType.CV_8UC3, Scalar.All(255));
// Calculate histogram
Mat hist = new Mat();
int[] hdims = {256}; // Histogram size for each dimension
Rangef[] ranges = { new Rangef(0,256), }; // min/max
Cv2.CalcHist(
new Mat[]{src},
new int[]{0},
null,
hist,
1,
hdims,
ranges);
// Get the max value of histogram
double minVal, maxVal;
Cv2.MinMaxLoc(hist, out minVal, out maxVal);
Scalar color = Scalar.All(100);
// Scales and draws histogram
hist = hist * (maxVal != 0 ? Height / maxVal : 0.0);
for (int j = 0; j < hdims[0]; ++j)
{
int binW = (int)((double)Width / hdims[0]);
render.Rectangle(
new Point(j * binW, render.Rows),
new Point((j + 1) * binW, render.Rows - (int)(hist.Get<float>(j))),
color,
-1);
}
using (new Window("Image", WindowMode.AutoSize | WindowMode.FreeRatio, src))
using (new Window("Histogram", WindowMode.AutoSize | WindowMode.FreeRatio, render))
{
Cv2.WaitKey();
}
}