public static void ApplyColormap(ref double[,] source, out Emgu.CV.Image <Bgr, Byte> destination, ColorMapType colorMapType)
{
double max = 0;
for (int y = 0; y < source.GetLength(1); y++)
{
for (int x = 0; x < source.GetLength(0); x++)
{
if (source[y, x] > max)
{
max = source[y, x];
}
}
}
Image <Gray, byte> buffer = new Image <Gray, Byte>(source.GetLength(0), source.GetLength(1));
for (int y = 0; y < source.GetLength(1); y++)
{
for (int x = 0; x < source.GetLength(0); x++)
{
buffer[y, x] = new Gray(source[y, x] * 255 / max);
}
}
destination = new Image <Bgr, Byte>(source.GetLength(0), source.GetLength(1));
CvInvoke.ApplyColorMap(buffer, destination, colorMapType);
}
private void ProcessImage(List <string> lines)
{
Mat imageOriginal = CvInvoke.Imread(ImageRecievedName, LoadImageType.AnyColor);
var imageWithHitsBgr = CreateHitImage(imageOriginal.Size, lines);
// create mask to have white circles wherever hits exist and to be black on all other parts
var mask = new Mat();
CvInvoke.Threshold(imageWithHitsBgr, mask, 1, 255, ThresholdType.Binary);
var inverseMask = new Mat();
CvInvoke.BitwiseNot(mask, inverseMask);
// mapping level of gray to ColorMap
CvInvoke.ApplyColorMap(imageWithHitsBgr, imageWithHitsBgr, ColorMapType.Jet);
// from mapped image remove everything except hits
var imageWithHitsWithoutBackground = new Mat();
CvInvoke.BitwiseAnd(imageWithHitsBgr, imageWithHitsBgr, imageWithHitsWithoutBackground, mask);
// from original image remove only parts where hits happended
var imageOriginalWithoutHits = new Mat();
CvInvoke.BitwiseAnd(imageOriginal, imageOriginal, imageOriginalWithoutHits, inverseMask);
// result is combination of original image without hits and image with hits mapped to certain ColorMap
var result = new Mat();
CvInvoke.Add(imageOriginalWithoutHits, imageWithHitsWithoutBackground, result);
result.Save(ImageProcessedName);
}
private static Image <Bgr, byte> Map(IImage image, ColorMapType palette)
{
var output = new Image <Bgr, byte>(image.Size);
CvInvoke.ApplyColorMap(image, output, palette);
return(output);
}
public virtual void dispImg(UMat inImg)
{
UMat toUpdate = (imageBox1.Image == disp_1) ? disp_2 : disp_1;
if (!showColorMap)
{
inImg.CopyTo(toUpdate);
}
else
{
CvInvoke.ApplyColorMap(inImg, toUpdate, ColorMapType.Jet);
}
if (run1disp_1 == 0 || run1disp_2 == 0)
{
run1disp_1 = disp_1.Bytes[0];
run1disp_2 = disp_2.Bytes[0];
}
imageBox1.Image = toUpdate;
}
public static void ApplyColormap(ref Emgu.CV.Image <Gray, double> source, out Emgu.CV.Image <Bgr, Byte> destination, ColorMapType colorMapType, bool invert = false)
{
destination = new Image <Bgr, Byte>(source.Width, source.Height);
var max = 0.0;
for (int y = 0; y < source.Height; y++)
{
for (int x = 0; x < source.Width; x++)
{
if (source[y, x].Intensity > max)
{
max = source[y, x].Intensity;
}
}
}
Image <Gray, byte> bufferImage = new Image <Gray, Byte>(source.Width, source.Height);
for (int y = 0; y < source.Height; y++)
{
for (int x = 0; x < source.Width; x++)
{
if (invert)
{
bufferImage[y, x] = new Gray(255 - source[y, x].Intensity * 255 / max);
}
else
{
bufferImage[y, x] = new Gray(source[y, x].Intensity * 255 / max);
}
}
}
CvInvoke.ApplyColorMap(bufferImage, destination, colorMapType);
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
_capture.Retrieve(frame, 0);
Mat newFrame = new Mat();
//CvInvoke.EdgePreservingFilter(frame, newFrame);
//CvInvoke.Dct(frame, newFrame, DctType.Forward);
//CvInvoke.CornerHarris(frame, newFrame, 4);
//CvInvoke.ConvertPointsToHomogeneous(frame, newFrame);
//CvInvoke.ConvertPointsFromHomogeneous(frame, newFrame);
//CvInvoke.Blur(frame, newFrame, new System.Drawing.Size(100,100), new System.Drawing.Point(100,50));
//CvInvoke.BoxFilter(frame, newFrame, DepthType.Default, new System.Drawing.Size(100, 100), new System.Drawing.Point(100, 50));
//this.ImgMainZm.Image = newFrame;
//return;
if (this.CurFilterType == FilterType.ftNormal)
{
this.ImgMainZm.Image = frame;
}
else if (this.CurFilterType == FilterType.ftGray)
{
newFrame = new Mat();
CvInvoke.CvtColor(frame, newFrame, ColorConversion.Bgr2Gray);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftSmallGray)
{
Mat grayFrame = new Mat();
CvInvoke.CvtColor(frame, grayFrame, ColorConversion.Bgr2Gray);
Mat smallGrayFrame = new Mat();
CvInvoke.PyrDown(grayFrame, smallGrayFrame);
this.ImgMainZm.Image = smallGrayFrame;
}
else if (this.CurFilterType == FilterType.ftSmoothGray)
{
Mat grayFrame = new Mat();
CvInvoke.CvtColor(frame, grayFrame, ColorConversion.Bgr2Gray);
Mat smallGrayFrame = new Mat();
CvInvoke.PyrDown(grayFrame, smallGrayFrame);
Mat smoothedGrayFrame = new Mat();
CvInvoke.PyrUp(smallGrayFrame, smoothedGrayFrame);
this.ImgMainZm.Image = smoothedGrayFrame;
}
else if (this.CurFilterType == FilterType.ftCanny)
{
Mat grayFrame = new Mat();
CvInvoke.CvtColor(frame, grayFrame, ColorConversion.Bgr2Gray);
Mat smallGrayFrame = new Mat();
CvInvoke.PyrDown(grayFrame, smallGrayFrame);
Mat smoothedGrayFrame = new Mat();
CvInvoke.PyrUp(smallGrayFrame, smoothedGrayFrame);
Mat cannyFrame = new Mat();
CvInvoke.Canny(smoothedGrayFrame, cannyFrame, 100, 60);
this.ImgMainZm.Image = cannyFrame;
}
else if (this.CurFilterType == FilterType.ftAutumn)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Autumn);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftCool)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Cool);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftBone)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Bone);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftHot)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Hot);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftHsv)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Hsv);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftJet)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Jet);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftOcean)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Ocean);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftPink)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Pink);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftRainbow)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Rainbow);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftSpring)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Spring);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftSummer)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Summer);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftWinter)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Winter);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftWinter)
{
newFrame = new Mat();
CvInvoke.ApplyColorMap(frame, newFrame, ColorMapType.Winter);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftBitwiseNot)
{
newFrame = new Mat();
CvInvoke.BitwiseNot(frame, newFrame);
this.ImgMainZm.Image = newFrame;
}
else if (this.CurFilterType == FilterType.ftEdgePreservingFilter)
{
newFrame = new Mat();
CvInvoke.EdgePreservingFilter(frame, newFrame);
this.ImgMainZm.Image = newFrame;
}
}
private void ProcessImages(object sender, EventArgs e)
{
StereoImage <Bgr, byte> image = null;
if (Model.Mode == SourceMode.Camera)
{
if (Controller.CameraIsEnabled())
{
//image = Controller.GeatedStereoImage();
}
}
else
{
if (Model.Image != null)
{
image = Model.Image;
}
}
if (image == null)
{
return;
}
SourceImage.ViewModel.Image = image;
var temp = new StereoImage <Bgr, byte>();
if (ResultImage.ViewModel.ShowLeft)
{
var model = (StereoSgbmModel)_viewModel.SgbmModel.Clone();
model.Image1 = image.LeftImage.Convert <Gray, byte>();
model.Image2 = image.RightImage.Convert <Gray, byte>();
var map = Stereo.Compute(model);
var test = map.Convert <Bgr, byte>();
CvInvoke.ApplyColorMap(test, test, ColorMapType.Rainbow);
temp.LeftImage = test;
test = test.SmoothGaussian(15);
temp.RightImage = test;
}
if (ResultImage.ViewModel.ShowRight)
{
var model = (OpticalFlowModel)_viewModel.FlowModel.Clone();
model.Image1 = image.LeftImage.Convert <Gray, byte>();
model.Image2 = image.RightImage.Convert <Gray, byte>();
var map = OpticalFlow.Compute(model);
temp.RightImage = map.Convert <Bgr, byte>();
if (temp.LeftImage == null)
{
temp.LeftImage = temp.RightImage;
}
}
ResultImage.ViewModel.Image = temp.Convert <Bgr, byte>();
if (_viewModel.SaveImage)
{
if (_viewModel.AllowGrabImage)
{
_viewModel.Images.Add(image);
ImageListBox.Items.Refresh();
}
if (_viewModel.AllowSaveImages)
{
Controller.SaveImages(_viewModel.Images, DateTime.Now.Ticks.ToString());
_viewModel.Images.Clear();
ImageListBox.Items.Refresh();
}
}
}
/// <summary>
/// Main method for processing the image
/// </summary>
/// <param name="input"></param>
private void ProcessFrame(Image <Bgr, Byte> input)
{
//input._EqualizeHist();
if (prevgrayframe == null)
{
prevgrayframe = input.Convert <Gray, Byte>();
preFeatures = prevgrayframe.GoodFeaturesToTrack(1000, 0.05, 5.0, 3);
prevgrayframe.FindCornerSubPix(preFeatures, new Size(5, 5), new Size(-1, -1), new MCvTermCriteria(25, 1.5d)); //This just increase the accuracy of the points
//mixChannel_src = input.PyrDown().PyrDown().Convert<Hsv, float>()[0];
return;
}
grayframe = input.Convert <Gray, Byte>();
//apply the Optical flow
Emgu.CV.OpticalFlow.PyrLK(prevgrayframe, grayframe, preFeatures[0], new Size(10, 10), 3, criteria, out curFeatures, out status, out error);
Image <Gray, float> FlowX = new Image <Gray, float>(grayframe.Size),
FlowY = new Image <Gray, float>(grayframe.Size),
FlowAngle = new Image <Gray, float>(grayframe.Size),
FlowLength = new Image <Gray, float>(grayframe.Size),
FlowResult = new Image <Gray, float>(grayframe.Size);
#region Farneback method to display movement in colour intensity
//Same as bellow CvInvoke method but a bit simpler
Emgu.CV.OpticalFlow.Farneback(prevgrayframe, grayframe, FlowX, FlowY, 0.5, 1, 10, 2, 5, 1.1, OPTICALFLOW_FARNEBACK_FLAG.USE_INITIAL_FLOW);
//CvInvoke.cvShowImage("FlowX", FlowX); //Uncomment to see in external window
//CvInvoke.cvShowImage("FlowY", FlowY);//Uncomment to see in external window
//CvInvoke.cvWaitKey(1); //Uncomment to see in external window (NOTE: You only need this line once)
//CvInvoke Method
//IntPtr Flow = CvInvoke.cvCreateImage(grayframe.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_32F, 2);
//CvInvoke.cvCalcOpticalFlowFarneback(prevgrayframe, grayframe, Flow, 0.5, 1, 10, 2, 5, 1.1, OPTICALFLOW_FARNEBACK_FLAG.USE_INITIAL_FLOW);
//CvInvoke.cvSplit(Flow, FlowX, FlowY, IntPtr.Zero, IntPtr.Zero);
//CvInvoke.cvShowImage("FlowFX", FlowX); //Uncomment to see in external window
//CvInvoke.cvShowImage("FlowFY", FlowY); //Uncomment to see in external window
//CvInvoke.cvWaitKey(1); //Uncomment to see in external window (NOTE: You only need this line once)
#region All this is accomplished in the region bellow
// for (int i = 0; i < FlowX.Width; i++)
// {
// for (int j = 0; j < FlowX.Height; j++)
// {
// FlowLength.Data[j, i, 0] = (float)(Math.Sqrt((FlowX.Data[j, i, 0] * FlowX.Data[j, i, 0]) + (FlowY.Data[j, i, 0] * FlowY.Data[j, i, 0]))); //Gradient
// if (FlowLength.Data[j, i, 0] < 0)
// {
// FlowAngle.Data[j, i, 0] = (float)(Math.Atan2(FlowY.Data[j, i, 0], FlowX.Data[j, i, 0]) * 180 / Math.PI);
// }
// else
// {
// FlowAngle.Data[j, i, 0] = (float)(Math.Atan2(FlowY.Data[j, i, 0], (FlowX.Data[j, i, 0] * -1)) * 180 / Math.PI);
// }
// //FlowResult.Data[j, i, 0] = FlowAngle.Data[j, i, 0] * FlowLength.Data[j, i, 0];
// FlowResult.Data[j, i, 0] = FlowLength.Data[j, i, 0] * 5;
// }
// }
// Image<Bgr, Byte> Result = new Image<Bgr, Byte>(grayframe.Size);
// CvInvoke.ApplyColorMap(FlowResult.Convert<Gray, Byte>(), Result, ColorMapType.Hot);
//// CvInvoke.cvShowImage("Flow Angle", FlowAngle.Convert<Gray,Byte>());//Uncomment to see in external window
//// CvInvoke.cvShowImage("Flow Length", FlowLength.Convert<Gray, Byte>());//Uncomment to see in external window
// CvInvoke.cvShowImage("Flow Angle Colour", Result);//Uncomment to see in external window
#endregion
#region This code is much simpler
//Find the length for the whole array
FlowY = FlowY.Mul(FlowY); //Y*Y
FlowX = FlowX.Mul(FlowX); //X*X
FlowResult = FlowX + FlowY; //X^2 + Y^2
CvInvoke.cvSqrt(FlowResult, FlowResult); //SQRT(X^2 + Y^2)
//Apply a colour map.
Image <Bgr, Byte> Result = new Image <Bgr, Byte>(grayframe.Size); //store the result
CvInvoke.ApplyColorMap(FlowResult.Convert <Gray, Byte>() * 5, Result, ColorMapType.Hot); //Scale the FlowResult by a factor of 5 for a better visual difference
CvInvoke.cvShowImage("Flow Angle Colour II", Result); //Uncomment to see in external window
CvInvoke.cvWaitKey(1); //Uncomment to see in external window (NOTE: You only need this line once)
#endregion
#endregion
prevgrayframe = grayframe.Copy(); //copy current frame to previous
//Image<Gray, float> mixCahnnel_dest2 = Histo.BackProjectPatch<float>(new Image<Gray, float>[] { input.PyrDown().PyrDown().Convert<Hsv, float>()[0] }, new Size(1, 1), HISTOGRAM_COMP_METHOD.CV_COMP_BHATTACHARYYA, 1.0);
//CvInvoke.cvShowImage("BackProjection", mixCahnnel_dest2);
//CvInvoke.cvWaitKey(1); //Uncomment to see in external window (NOTE: You only need this line once)
for (int i = 0; i < curFeatures.Length; i++)
{
LineSegment2DF line = new LineSegment2DF(preFeatures[0][i], curFeatures[i]);
double dx = Math.Abs(line.P1.X - line.P2.X);
double dy = Math.Abs(line.P1.Y - line.P2.Y);
double l = Math.Sqrt(dx * dx + dy * dy);
double spinSize = 0.1 * l;
if (l > 5 && l < 100)
{
frame.Draw(line, new Bgr(Color.Red), 2);
double angle = Math.Atan2((double)line.P1.Y - line.P2.Y, (double)line.P1.X - line.P2.X);
Point Tip1 = new Point((int)(line.P2.X + spinSize * Math.Cos(angle + 3.1416 / 4)), (int)(line.P2.Y + spinSize * Math.Sin(angle + 3.1416 / 4)));
Point Tip2 = new Point((int)(line.P2.X + spinSize * Math.Cos(angle - 3.1416 / 4)), (int)(line.P2.Y + spinSize * Math.Sin(angle - 3.1416 / 4)));
LineSegment2DF line1 = new LineSegment2DF(Tip1, curFeatures[i]);
LineSegment2DF line2 = new LineSegment2DF(Tip2, curFeatures[i]);
frame.Draw(line1, new Bgr(Color.Blue), 2);
frame.Draw(line2, new Bgr(Color.Blue), 2);
}
//int range = 20;
//if (preFeatures[0][i].X > curFeatures[i].X - range && preFeatures[0][i].X < curFeatures[i].X + range) preFeatures[0][i].X = curFeatures[i].X;
//if (preFeatures[0][i].Y > curFeatures[i].Y - range && preFeatures[0][i].Y < curFeatures[i].Y + range) preFeatures[0][i].Y = curFeatures[i].Y;
}
preFeatures = prevgrayframe.GoodFeaturesToTrack(1000, 0.05, 5.0, 3);
prevgrayframe.FindCornerSubPix(preFeatures, new Size(5, 5), new Size(-1, -1), new MCvTermCriteria(25, 1.5d)); //This just increase the accuracy of the points
/*---------------------------------------------*/
DisplayImage(input.ToBitmap(), PCBX_Image); //thread safe display for camera cross thread errors
}
public override void Process(ref Image <Bgr, byte> image)
{
CvInvoke.ApplyColorMap(image, image, _colorMapType);
}
