private void SetupFilters(out DecimationFilter decimate, out SpatialFilter spatial, out TemporalFilter temp, out HoleFillingFilter holeFill, out ThresholdFilter threshold)
{
// Colorizer is used to visualize depth data
colorizer = new Colorizer();
// Decimation filter reduces the amount of data (while preserving best samples)
decimate = new DecimationFilter();
decimate.Options[Option.FilterMagnitude].Value = 1.0F;//change scall
// Define spatial filter (edge-preserving)
spatial = new SpatialFilter();
// Enable hole-filling
// Hole filling is an agressive heuristic and it gets the depth wrong many times
// However, this demo is not built to handle holes
// (the shortest-path will always prefer to "cut" through the holes since they have zero 3D distance)
spatial.Options[Option.HolesFill].Value = 1.0F; //change resolution on the edge of image
spatial.Options[Option.FilterMagnitude].Value = 5.0F;
spatial.Options[Option.FilterSmoothAlpha].Value = 1.0F;
spatial.Options[Option.FilterSmoothDelta].Value = 50.0F;
// Define temporal filter
temp = new TemporalFilter();
// Define holefill filter
holeFill = new HoleFillingFilter();
// Aline color to depth
//align_to = new Align(Stream.Depth);
//try to define depth max
threshold = new ThresholdFilter();
threshold.Options[Option.MinDistance].Value = 0;
threshold.Options[Option.MaxDistance].Value = 1;
}
private void SetupFilters(out DecimationFilter decimate, out SpatialFilter spatial, out ThresholdFilter threshold)
{
// Colorizer is used to visualize depth data
colorizer = new Colorizer();
// Decimation filter reduces the amount of data (while preserving best samples)
decimate = new DecimationFilter();
decimate.Options[Option.FilterMagnitude].Value = 1.0F;//change scall
// Define spatial filter (edge-preserving)
spatial = new SpatialFilter();
spatial.Options[Option.HolesFill].Value = 1.0F; //change resolution on the edge of image
spatial.Options[Option.FilterMagnitude].Value = 5.0F;
spatial.Options[Option.FilterSmoothAlpha].Value = 1.0F;
spatial.Options[Option.FilterSmoothDelta].Value = 50.0F;
// Aline color to depth
//align_to = new Align(Stream.Depth);
//try to define depth max
threshold = new ThresholdFilter();
threshold.Options[Option.MinDistance].Value = 0;
threshold.Options[Option.MaxDistance].Value = 1;
}
public override ProcessingBlock GetFilter()
{
var filter = new ThresholdFilter();
filter.Options[Option.MinDistance].Value = MinDistance;
filter.Options[Option.MaxDistance].Value = MaxDistance;
return(filter);
}
public async Task ApplyThresholdFilter(int w, int h, int threshold)
{
var filter = new ThresholdFilter(threshold);
using (var img = new BitmapImage(TestData.GetTestImage(w, h)))
{
await filter.Apply(img, img.Bounds, CancellationToken.None);
await img.SaveAsync(File.Create(Path.Combine(TestData.RootFolder, $"threshold({threshold})-{w}x{h}.png")), CancellationToken.None);
}
}
public FilterGenerator(int quadrantSize, LocalTerrain localTerrain)
{
globalFilterMountainC = new GlobalCoordinates(100);
globalFilterAverageC = new GlobalCoordinates(100);
globalFilterMedianC = new GlobalCoordinates(100);
globalFilterSpikeC = new GlobalCoordinates(100);
globalFilterGaussianC = new GlobalCoordinates(100);
globalFilterMinThresholdC = new GlobalCoordinates(100);
globalFilterMaxThresholdC = new GlobalCoordinates(100);
lt = localTerrain;
localCoordinates = lt.localTerrainC;
mf = new MountainFilter(this);
af = new AverageFilter(this);
mdf = new MedianFilter(this);
sf = new SpikeFilter(this);
gf = new GaussianFilter(this);
tf = new ThresholdFilter(this);
}
private void ProcessImage(KalikoImage image)
{
image.Resize(XSIZE, YSIZE); // for faster operations / debugging
// operating on image
NormalizationFilter normalization = new NormalizationFilter();
image.ApplyFilter(normalization);
FastGaussianBlurFilter gaussian = new FastGaussianBlurFilter(5f);
image.ApplyFilter(gaussian);
Histogram histogram = new Histogram(image);
byte filteredThreshold = histogram.GetThresholdLevel();
ThresholdFilter threshold = new ThresholdFilter(filteredThreshold);
image.ApplyFilter(threshold);
}
/// <inheritdoc/>
public override ProcessingBlock Read(ref Utf8JsonReader reader, Type typeToConvert, JsonSerializerOptions options)
{
//Note: Maybe we should add checks for each read.
_ = reader.Read(); // Read start object
_ = reader.GetString(); // Read "Name"
_ = reader.Read(); // Read the ':'
var name = reader.GetString(); // Read the name
ProcessingBlock block;
switch (name)
{
case "Decimation Filter":
block = new DecimationFilter();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterMagnitude"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterMagnitude].Value = reader.GetSingle();
_ = reader.Read(); // Read end object
break;
case "Spatial Filter":
block = new SpatialFilter();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterMagnitude"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterMagnitude].Value = reader.GetSingle();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterSmoothAlpha"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterSmoothAlpha].Value = reader.GetSingle();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterSmoothDelta"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterSmoothDelta].Value = reader.GetSingle();
_ = reader.Read(); // Read end object
break;
case "Temporal Filter":
block = new TemporalFilter();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterSmoothAlpha"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterSmoothAlpha].Value = reader.GetSingle();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "FilterSmoothDelta"
_ = reader.Read(); // Read the ':'
block.Options[Option.FilterSmoothDelta].Value = reader.GetSingle();
_ = reader.Read(); // Read end object
break;
case "Hole Filling Filter":
block = new HoleFillingFilter();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "HolesFill"
_ = reader.Read(); // Read the ':'
block.Options[Option.HolesFill].Value = reader.GetSingle();
_ = reader.Read(); // Read end object
break;
case "Threshold Filter":
block = new ThresholdFilter();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "MinDistance"
_ = reader.Read(); // Read the ':'
block.Options[Option.MinDistance].Value = reader.GetSingle();
_ = reader.Read(); // Read the ','
_ = reader.GetString(); // Read "MaxDistance"
_ = reader.Read(); // Read the ':'
block.Options[Option.MaxDistance].Value = reader.GetSingle();
_ = reader.Read(); // Read end object
break;
default:
throw new NotSupportedException($"The filter {name} is not supported in this converter");
}
return(block);
}
public void Init()
{
_pb = new ThresholdFilter();
minOption = _pb.Options[Option.MinDistance];
maxOption = _pb.Options[Option.MaxDistance];
}
private void SetupProcessingBlock(Pipeline pipeline, Colorizer colorizer, DecimationFilter decimate, SpatialFilter spatial, TemporalFilter temp, HoleFillingFilter holeFill, ThresholdFilter threshold)
{
// Setup / start frame processing
processingBlock = new CustomProcessingBlock((f, src) =>
{
// We create a FrameReleaser object that would track
// all newly allocated .NET frames, and ensure deterministic finalization
// at the end of scope.
using (var releaser = new FramesReleaser())
{
using (var frames = pipeline.WaitForFrames().DisposeWith(releaser))
{
var processedFrames = frames
.ApplyFilter(decimate).DisposeWith(releaser)
.ApplyFilter(spatial).DisposeWith(releaser)
.ApplyFilter(temp).DisposeWith(releaser)
.ApplyFilter(holeFill).DisposeWith(releaser)
.ApplyFilter(colorizer).DisposeWith(releaser)
.ApplyFilter(threshold).DisposeWith(releaser);
// Send it to the next processing stage
src.FrameReady(processedFrames);
}
}
});
}
// add MaskFilter
// add contour filter
// draw contours
// неплохо бы у мержделки лвл выбирать (что брать не только предыдущую)
static void Main(string[] args)
{
// dnn tests
DnnInfo dnn = new DnnInfo("model_bn.pb");
//---------------------------------------------------------------------------
String winName = "Test Window"; //The name of the window
CvInvoke.NamedWindow(winName); //Create the window using the specific name
// bitmap to mat
var bitmap = new Bitmap(@"d:\GM\all\15752977512762.png");
Mat fromBitmap = GetCvMatFromBitmap(bitmap);
//CvInvoke.Imshow(winName, fromBitmap);
//CvInvoke.WaitKey(0);
var bittt = GetRGBBitmapFromCvMat(fromBitmap);
bittt.Save("out.jpg");
// graph test-------
GraphFilter graph = new GraphFilter();
var scFilter = graph.Add(FilterType.Source);
scFilter["Source"] = fromBitmap;
var threshFilter = graph.Add(FilterType.Threshold).ConnectBefore(graph.Add(FilterType.Bgr2Gray).ConnectBefore(scFilter));
threshFilter["Type"] = "AdaptiveGaussianBinaryInv";
threshFilter["Threshold"] = 125;
threshFilter["ValueSet"] = 255;
threshFilter["Kern"] = 5;
threshFilter["SubtractedFromMean"] = 0;
var outs = graph.GetOuts();
CvInvoke.Imshow(winName, outs[0].Image);
CvInvoke.WaitKey(0);
threshFilter["Kern"] = 3;
outs = graph.GetOuts();
CvInvoke.Imshow(winName, outs[0].Image);
CvInvoke.WaitKey(0);
//-----------------------------------------------------------
var laadFilter = new LoadBgrFilter();
laadFilter["File"] = new FileInfo(@"d:\GM\all\15808995027720.jpg");
var laadFilter2 = new LoadBgrFilter();
laadFilter2["File"] = new FileInfo(@"d:\GM\all\15808863021350.png");
// gray ------------------------------------
var grayFilter = new Bgr2GrayFilter();
grayFilter.ConnectBefore(laadFilter);
var imgs00 = grayFilter.GetOut();
CvInvoke.Imshow(winName, imgs00[0].Image);
CvInvoke.WaitKey(0);
//rotate -----------------------------------
{
var rotF1 = new RotationFilter();
rotF1["Deg"] = 45.0;
rotF1["Scale"] = 0.75;
rotF1["NewSize"] = 1;
rotF1["Width"] = 500;
rotF1["Height"] = 500;
rotF1.ConnectBefore(laadFilter);
var rotF2 = new RotationFilter();
rotF2["Deg"] = 360.0 - 45.0;
rotF2["Scale"] = 0.75;
rotF2["NewSize"] = 1;
rotF2["Width"] = 500;
rotF2["Height"] = 500;
rotF2.ConnectBefore(laadFilter2);
// MergeFilter
var mergeFilter = new MergeFilter();
mergeFilter.ConnectBefore(rotF1);
mergeFilter.ConnectBefore(rotF2);
mergeFilter["Alpha"] = 0.5;
mergeFilter["Beta"] = 0.5;
mergeFilter["Gamma"] = 0.5;
var imgs0 = mergeFilter.GetOut();
var bittt01 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt01.Save("out1.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
}
// resize
{
var resFinlt1 = new ResizeAbsFilter();
resFinlt1["Width"] = 240;
resFinlt1["Height"] = 320;
resFinlt1.ConnectBefore(laadFilter);
resFinlt1.ConnectBefore(laadFilter2);
var imgs = resFinlt1.GetOut();
CvInvoke.Imshow(winName, imgs[0].Image);
CvInvoke.WaitKey(0);
CvInvoke.Imshow(winName, imgs[1].Image);
CvInvoke.WaitKey(0);
// MergeFilter
var mergeFilter = new MergeFilter();
mergeFilter.ConnectBefore(resFinlt1);
mergeFilter["Alpha"] = 1.0;
mergeFilter["Beta"] = -1.0;
mergeFilter["Gamma"] = 0.0;
var imgs0 = mergeFilter.GetOut();
var bittt02 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt02.Save("out2.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
}
// blur
{
var blurFilter = new BlurFilter();
blurFilter["Type"] = "Median";//"Gaussian";
blurFilter["Kern"] = 6;
blurFilter.ConnectBefore(laadFilter);
var imgs0 = blurFilter.GetOut();
var bittt03 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt03.Save("out3.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
Mat fromBitmap00 = GetCvMatFromBitmap(bittt03);
CvInvoke.Imshow(winName, fromBitmap00);
CvInvoke.WaitKey(0);
}
// Morphology
{
var morphFlt = new MorphologyFilter();
morphFlt["Type"] = "Erode";
morphFlt["Kern"] = 5;
morphFlt["Count"] = 2;
morphFlt["KernType"] = "Ellipse";
morphFlt.ConnectBefore(laadFilter);
var imgs0 = morphFlt.GetOut();
var bittt04 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt04.Save("out4.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
Mat fromBitmap00 = GetCvMatFromBitmap(bittt04);
CvInvoke.Imshow(winName, fromBitmap00);
CvInvoke.WaitKey(0);
}
// Threshold
{
var threshFlt = new ThresholdFilter();
threshFlt["Type"] = "AdaptiveGaussianBinaryInv";
threshFlt["Threshold"] = 125;
threshFlt["ValueSet"] = 255;
threshFlt["Kern"] = 5;
threshFlt["SubtractedFromMean"] = 0;
threshFlt.ConnectBefore(grayFilter);
var imgs0 = threshFlt.GetOut();
var bittt05 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt05.Save("out5.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
Mat fromBitmap00 = GetCvMatFromBitmap(bittt05);
CvInvoke.Imshow(winName, fromBitmap00);
CvInvoke.WaitKey(0);
}
// Grad
{
var gradFltr = new GradientFilter();
gradFltr["Type"] = "Laplacian"; // "Canny" "Sobel"
gradFltr["Kern"] = 1;
gradFltr["Low"] = 0;
gradFltr["Hight"] = 255;
gradFltr.ConnectBefore(laadFilter);
var imgs0 = gradFltr.GetOut();
var bittt06 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt06.Save("out6.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
Mat fromBitmap00 = GetCvMatFromBitmap(bittt06);
CvInvoke.Imshow(winName, fromBitmap00);
CvInvoke.WaitKey(0);
}
// My test------------------------------------
{
var gradFl = new GradientFilter();
gradFl["Type"] = "Sobel";
gradFl["Kern"] = 1;
gradFl.ConnectBefore(laadFilter);
var morphFlt = new MorphologyFilter();
morphFlt["Type"] = "Detate";
morphFlt["Kern"] = 5;
morphFlt["Count"] = 2;
morphFlt["KernType"] = "Ellipse";
morphFlt.ConnectBefore(gradFl);
var mergeFlt = new MergeFilter();
mergeFlt.ConnectBefore(laadFilter);
mergeFlt.ConnectBefore(gradFl);
mergeFlt["Alpha"] = 1.0;
mergeFlt["Beta"] = -1.0;
mergeFlt["Gamma"] = 0.0;
var blurFilter = new BlurFilter();
blurFilter["Type"] = "Median";//"Gaussian";
blurFilter["Kern"] = 6;
blurFilter.ConnectBefore(mergeFlt);
var mergeFlt2 = new MergeFilter();
mergeFlt2.ConnectBefore(blurFilter);
mergeFlt2.ConnectBefore(gradFl);
mergeFlt2["Alpha"] = 0.5;
mergeFlt2["Beta"] = 0.5;
mergeFlt2["Gamma"] = 0.0;
var imgs0 = mergeFlt2.GetOut();
var bittt7 = GetRGBBitmapFromCvMat(imgs0[0].Image);
bittt7.Save("out7.jpg");
CvInvoke.Imshow(winName, imgs0[0].Image);
CvInvoke.WaitKey(0);
Mat fromBitmap00 = GetCvMatFromBitmap(bittt7);
CvInvoke.Imshow(winName, fromBitmap00);
CvInvoke.WaitKey(0);
}
CvInvoke.WaitKey(0); //Wait for the key pressing event
CvInvoke.DestroyWindow(winName); //Destroy the window if key is pressed
return;
}
private void thresholdToolStripMenuItem_Click(object sender, EventArgs e)
{
cipFormThreshold formThreshold = new cipFormThreshold(this.picBoxModifyed.Image,this.GetCurrentRaster(),Thread.CurrentThread.CurrentUICulture);
if (formThreshold.ShowDialog()==DialogResult.OK)
{
byte level = formThreshold.GetLevel();
if (!backgroundWorkerCip.IsBusy)
{
ImageFilter filter = new ThresholdFilter(level);
backgroundWorkerCip.RunWorkerAsync(filter);
this.CalculateHistogram();
}
}
}
void Init()
{
try
{
#region FILTERS
spatialFilter = new SpatialFilter();
spatialFilter.Options[Option.FilterMagnitude].Value = 5.0F;
spatialFilter.Options[Option.FilterSmoothAlpha].Value = 0.25F;
spatialFilter.Options[Option.FilterSmoothDelta].Value = 50.0F;
decimationFilter = new DecimationFilter();
decimationFilter.Options[Option.FilterMagnitude].Value = 2.0F;
holeFilter = new HoleFillingFilter();
thresholdFilter = new ThresholdFilter();
//thresholdFilter.Options[Option.MinDistance].Value = 0.73F;
//thresholdFilter.Options[Option.MaxDistance].Value = 0.81F;
#endregion
align_to = new Align(Intel.RealSense.Stream.Depth);
colorizer = new Colorizer();
pipeline = new Pipeline();
//CONFIG SETTINGS
var cfg = new Config();
cfg.EnableStream(Intel.RealSense.Stream.Depth, resolutionW, resolutionH, Format.Z16, FPS); //depth resolution manuel change
cfg.EnableStream(Intel.RealSense.Stream.Color, 640, 480, Format.Rgb8, 30);
pipelineProfile = pipeline.Start(cfg); //stream starting with user config
var advancedDevice = AdvancedDevice.FromDevice(pipelineProfile.Device); //connected device
//read device's configuration settings from json file
advancedDevice.JsonConfiguration = File.ReadAllText(@"CustomConfig.json");
selectedDevice = pipelineProfile.Device;
#region Field Of View Info
float[] dfov, cfov, irfov;
var depth_stream = pipelineProfile.GetStream <VideoStreamProfile>(Intel.RealSense.Stream.Depth);
Intrinsics depthIntr = depth_stream.GetIntrinsics();
dfov = depthIntr.FOV; // float[2] - horizontal and vertical field of view in degrees
var color_stream = pipelineProfile.GetStream <VideoStreamProfile>(Intel.RealSense.Stream.Color);
Intrinsics colorIntr = color_stream.GetIntrinsics();
cfov = colorIntr.FOV; // float[2] - horizontal and vertical field of view in degrees
var ir_stream = pipelineProfile.GetStream <VideoStreamProfile>(Intel.RealSense.Stream.Infrared);
Intrinsics irIntr = ir_stream.GetIntrinsics();
irfov = irIntr.FOV; // float[2] - horizontal and vertical field of view in degrees
lblDepthFov.Text = "Depth FOV : " + "H = " + Convert.ToInt32(dfov[0]).ToString() + "° , " + "V = " + Convert.ToInt32(dfov[1]).ToString() + "°";
lblColorFov.Text = "RGB FOV : " + "H = " + Convert.ToInt32(cfov[0]).ToString() + "° , " + "V = " + Convert.ToInt32(cfov[1]).ToString() + "°";
lblInfraredFov.Text = "IR FOV : " + "H = " + Convert.ToInt32(irfov[0]).ToString() + "° , " + "V = " + Convert.ToInt32(irfov[1]).ToString() + "°";
#endregion
//get primary screen resolutions
screenWidth = Convert.ToInt32(System.Windows.SystemParameters.PrimaryScreenWidth.ToString());
screenHeight = Convert.ToInt32(System.Windows.SystemParameters.PrimaryScreenHeight.ToString());
//camera started working. transfer image to interface
SetupWindow(pipelineProfile, out updateDepth, out updateColor, out updateIR1, out updateIR2);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
