public static void LearnPattern(ImageViewer SourceImage, float fUpper = 0, float fLower = 0)
{
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the green color plane and copy it to the main image.
if (SourceImage.Image.Type == ImageType.Rgb32)
{
Algorithms.ExtractColorPlanes(SourceImage.Image, NationalInstruments.Vision.ColorMode.Rgb, null, plane, null);
Algorithms.Copy(plane, SourceImage.Image);
}
}
// Algorithms.LearnPattern2(SourceImage.Image);
OvalContour vaRect2 = new OvalContour(0, 0, 0, 0);
Roi roi = new Roi();
roi.Add(vaRect2);
// Histogram Grayscale
using (VisionImage imageMask = new VisionImage(ImageType.U8, 7))
{
RotationAngleRange ra = new RotationAngleRange(fLower, fUpper);
PixelValue fillValue = new PixelValue(255);
Algorithms.RoiToMask(imageMask, roi, fillValue, SourceImage.Image);
Algorithms.LearnPattern2(SourceImage.Image, imageMask, MatchingAlgorithm.MatchGrayValuePyramid, ra);
}
roi.Dispose();
}
public static PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(3, 0);
// Extract Color Plane
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the green color plane and copy it to the main image.
Algorithms.ExtractColorPlanes(image, ColorMode.Rgb, null, plane, null);
Algorithms.Copy(plane, image);
}
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(20, 20, 2552, 1904);
roi.Add(vaRect);
// Geometric Matching
string vaTemplateFile = $"{ @"./VisionModel/Polygon_20.5M/Mode.png"}";
CurveOptions vaCurveOptions = new CurveOptions();
vaCurveOptions.ColumnStepSize = 15;
vaCurveOptions.ExtractionMode = ExtractionMode.NormalImage;
vaCurveOptions.FilterSize = EdgeFilterSize.Normal;
vaCurveOptions.MaximumEndPointGap = 10;
vaCurveOptions.MinimumLength = 20;
vaCurveOptions.RowStepSize = 15;
vaCurveOptions.Threshold = 145;
MatchGeometricPatternEdgeBasedOptions matchGPMOptions = new MatchGeometricPatternEdgeBasedOptions();
matchGPMOptions.Advanced.ContrastMode = ContrastMode.Original;
matchGPMOptions.Advanced.MatchStrategy = GeometricMatchingSearchStrategy.Balanced;
matchGPMOptions.MinimumMatchScore = 800;
matchGPMOptions.Mode = GeometricMatchModes.RotationInvariant;
matchGPMOptions.NumberOfMatchesRequested = 1;
double[] vaRangesMin = { -20, 0, 50, 0 };
double[] vaRangesMax = { 20, 0, 200, 50 };
matchGPMOptions.OcclusionRange = new Range(vaRangesMin[3], vaRangesMax[3]);
matchGPMOptions.RotationAngleRanges.Add(new Range(vaRangesMin[0], vaRangesMax[0]));
matchGPMOptions.RotationAngleRanges.Add(new Range(vaRangesMin[1], vaRangesMax[1]));
matchGPMOptions.ScaleRange = new Range(vaRangesMin[2], vaRangesMax[2]);
matchGPMOptions.SubpixelAccuracy = true;
gpm2Results = IVA_MatchGeometricPattern2(image, vaTemplateFile, vaCurveOptions, matchGPMOptions, ivaData, 2, roi);
roi.Dispose();
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Gray);
}
public static PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(2, 0);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// 建一條巡邊線Star(229,40) End(229,300)
PointContour vaStartPoint = new PointContour(229, 40);
PointContour vaEndPoint = new PointContour(229, 300);
LineContour vaLine = new LineContour(vaStartPoint, vaEndPoint);
roi.Add(vaLine);
// 邊緣偵測;採用簡單邊緣偵測方式
SimpleEdgeOptions vaSimpleEdgeOptions = new SimpleEdgeOptions();
vaSimpleEdgeOptions.Process = EdgeProcess.All;
vaSimpleEdgeOptions.Type = LevelType.Absolute;
vaSimpleEdgeOptions.Threshold = 128;
vaSimpleEdgeOptions.Hysteresis = 2;
vaSimpleEdgeOptions.SubPixel = true;
simpleEdges = IVA_SimpleEdge(image, roi, vaSimpleEdgeOptions, ivaData, 0);
roi.Dispose();
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 1);
// Computes the vaDistance between two points.
Collection <double> vaDistance = IVA_GetDistance(image, ivaData, 1, 0, 3, 0, 5);
caliperDistance = vaDistance[0];
// Dispose the IVA_Data structure.
ivaData.Dispose();
//列出相關AOI資料
MessageBox.Show("座標點1" + simpleEdges[2].ToString() + "\r\n" +
"座標點2" + simpleEdges[0].ToString() + "\r\n" +
"座標點3" + simpleEdges[1].ToString() + "\r\n" + "\r\n" +
"間距量測" + caliperDistance.ToString());
//繪出檢測直線(巡邊線)
//Graphics g = Graphics.FromImage(FileName)
//g.DrawLine(0, 0, 100, 100);
// Return the palette type of the final image.
return(PaletteType.Gray);
}
public string ProcessQR(VisionImage image, List <QRConfig> qRConfigs)
{
string qRInfo = string.Empty;
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(1, 0);
for (int i = 0; i < qRConfigs.Count; i++)
{
// Creates a new, empty region of interest.
Roi roi = new Roi();
//// Creates a new RectangleContour using the given values.
//RectangleContour vaRect = new RectangleContour(720, 96, 1792, 1240);
RectangleContour vaRect = new RectangleContour(qRConfigs[i].Rectangle.Left,
qRConfigs[i].Rectangle.Top, qRConfigs[i].Rectangle.Height, qRConfigs[i].Rectangle.Width);
roi.Add(vaRect);
image.Overlays.Default.AddRoi(roi);
// Read QR Code
QRDescriptionOptions vaQROptions = new QRDescriptionOptions();
vaQROptions.Dimensions = qRConfigs[i].QRDimension;
vaQROptions.MirrorMode = QRMirrorMode.AutoDetect;
vaQROptions.ModelType = QRModelType.AutoDetect;
vaQROptions.Polarity = qRConfigs[i].Polarity;
QRSizeOptions vaQRSizeOptions = new QRSizeOptions(3, 15);
QRSearchOptions vaQRSearchOptions = new QRSearchOptions();
vaQRSearchOptions.CellFilterMode = QRCellFilterMode.AutoDetect;
vaQRSearchOptions.CellSampleSize = qRConfigs[i].CellSize;
vaQRSearchOptions.DemodulationMode = QRDemodulationMode.AutoDetect;
vaQRSearchOptions.EdgeThreshold = 30;
vaQRSearchOptions.RotationMode = QRRotationMode.Unlimited;
vaQRSearchOptions.SkewDegreesAllowed = 10;
vaQRSearchOptions.SkipLocation = false;
vaQRCode = Algorithms.ReadQRCode(image, roi, vaQROptions, vaQRSizeOptions, vaQRSearchOptions);
if (vaQRCode.Found)
{
image.Overlays.Default.AddPolygon(new PolygonContour(vaQRCode.Corners), Rgb32Value.RedColor, DrawingMode.DrawValue);
}
System.Text.ASCIIEncoding vaASCIIEncoding = new System.Text.ASCIIEncoding();
vaQRCodeData = vaASCIIEncoding.GetString(vaQRCode.GetData());
qRInfo += string.Format("{0},", vaQRCodeData);
roi.Dispose();
}
qRInfo = qRInfo.Substring(0, qRInfo.Length - 1);
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(qRInfo);
}
public static PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(4, 0);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new AnnulusContour using the given values.
PointContour vaCenter = new PointContour(1295, 970);
AnnulusContour vaOval = new AnnulusContour(vaCenter, 412, 954, 0, 0);
roi.Add(vaOval);
// Find Circular Edge
EdgeOptions vaOptions = new EdgeOptions();
vaOptions.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions.InterpolationType = InterpolationMethod.Bilinear;
vaOptions.KernelSize = 3;
vaOptions.MinimumThreshold = 50;
vaOptions.Polarity = EdgePolaritySearchMode.Rising;
vaOptions.Width = 3;
CircularEdgeFitOptions vaFitOptions = new CircularEdgeFitOptions();
vaFitOptions.ProcessType = RakeProcessType.GetBestEdges;
vaFitOptions.StepSize = 10;
vaFitOptions.MaxPixelRadius = 3;
vaCircularEdgeReport = IVA_FindCircularEdge(image, roi, SpokeDirection.InsideToOutside, vaOptions, vaFitOptions, ivaData, 1);
roi.Dispose();
// Overlays a line onto the image.
int[] xCoords = { 1296, 1296 };
int[] yCoords = { 0, 1944 };
byte[] vaColor = { 6, 0, 239 };
IVA_OverlayLine(image, xCoords, yCoords, vaColor);
// Overlays a line onto the image.
int[] xCoords2 = { 0, 2592 };
int[] yCoords2 = { 972, 972 };
byte[] vaColor2 = { 6, 0, 239 };
IVA_OverlayLine(image, xCoords2, yCoords2, vaColor2);
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Gray);
}
protected override void Dispose(bool disposing)
{
if (Roi != null)
{
Roi.Dispose();
Roi = null;
}
if (Matcher != null)
{
Matcher.Dispose();
Matcher = null;
}
if (Finder != null)
{
Finder.Dispose();
Finder = null;
}
base.Dispose(disposing);
}
public static PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(2, 0);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new LineContour using the given values.
PointContour vaStartPoint = new PointContour(229, 42);
PointContour vaEndPoint = new PointContour(229, 298);
LineContour vaLine = new LineContour(vaStartPoint, vaEndPoint);
roi.Add(vaLine);
// Edge Detector - Simple Edge
SimpleEdgeOptions vaSimpleEdgeOptions = new SimpleEdgeOptions();
vaSimpleEdgeOptions.Process = EdgeProcess.All;
vaSimpleEdgeOptions.Type = LevelType.Absolute;
vaSimpleEdgeOptions.Threshold = 128;
vaSimpleEdgeOptions.Hysteresis = 2;
vaSimpleEdgeOptions.SubPixel = true;
simpleEdges = IVA_SimpleEdge(image, roi, vaSimpleEdgeOptions, ivaData, 0);
roi.Dispose();
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 1);
// Computes the vaDistance between two points.
Collection <double> vaDistance = IVA_GetDistance(image, ivaData, 1, 0, 3, 0, 5);
caliperDistance = vaDistance[0];
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Gray);
}
public static double FindCircleHistogramMean(VisionImage image, OvalContour vaRect2)
{
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
roi.Add(vaRect2);
// Histogram Grayscale
double HistogramMean = -100;
using (VisionImage imageMask = new VisionImage(ImageType.U8, 7))
{
PixelValue fillValue = new PixelValue(255);
Range intervalRange = new Range(0, 0);
Algorithms.RoiToMask(imageMask, roi, fillValue, image);
// Calculates and returns statistical parameters on the image.
HistogramMean = Algorithms.Histogram(image, 256, intervalRange, imageMask).Mean;
}
roi.Dispose();
return(HistogramMean);
}
////////////////////////////////////////////////////////////////////////////////
//
// Function Name: IVA_Classification_Segmentation
//
// Description : Segments the classification image
//
// Parameters : image - Input Image
// imageMask - Segmented image
// roi - Region of Interest
// preprocessingOptions - Preprocessing options
//
// Return Value : None
//
////////////////////////////////////////////////////////////////////////////////
public static void IVA_Classification_Segmentation(VisionImage image, VisionImage imageMask, Roi roi, ParticleClassifierPreprocessingOptions preprocessingOptions)
{
int useExpandedROI = 0;
RectangleContour boundingBox = roi.GetBoundingRectangle(), expandedBox = roi.GetBoundingRectangle(), reducedBox = roi.GetBoundingRectangle();
// Local Threshold method uses a kernel size, and the ROI must be larger than the kernel size for the function to work
// Take care of making the ROI to extract larger if needed for the local threshold case
if (preprocessingOptions.ThresholdType == ThresholdType.Local)
{
// Get the image size
int xRes, yRes;
xRes = image.Width;
yRes = image.Height;
boundingBox = roi.GetBoundingRectangle();
// Take into account clipping of ROI. Just get ROI that's within bounds of image.
if (Math.Min(xRes, (boundingBox.Left + boundingBox.Width)) - Math.Max(0, boundingBox.Left) < preprocessingOptions.LocalThresholdOptions.WindowWidth || Math.Min(yRes, (boundingBox.Top + boundingBox.Height)) - Math.Max(0, boundingBox.Top) < preprocessingOptions.LocalThresholdOptions.WindowHeight)
{
// The ROI is smaller than the kernel. Try to expand the kernel in the directions needed to meet the minimum size required by the kernel.
int expandX = (int)(preprocessingOptions.LocalThresholdOptions.WindowWidth / 2);
int expandY = (int)(preprocessingOptions.LocalThresholdOptions.WindowHeight / 2);
int leftExpand = expandX;
int rightExpand = expandX;
int leftSlack = (int)boundingBox.Left;
int rightSlack = (int)(xRes - (boundingBox.Left + boundingBox.Width));
if (leftExpand > leftSlack)
{
rightExpand += (leftExpand - leftSlack);
}
if (rightExpand > rightSlack)
{
leftExpand += (rightExpand - rightSlack);
}
int leftOut = (int)boundingBox.Left - leftExpand;
if (leftOut < 0)
{
leftOut = 0;
}
int rightOut = (int)(boundingBox.Left + boundingBox.Width + rightExpand);
if (rightOut > xRes)
{
rightOut = xRes;
}
int topExpand = expandY;
int bottomExpand = expandY;
int topSlack = (int)boundingBox.Top;
int bottomSlack = (int)(yRes - (boundingBox.Top + boundingBox.Height));
if (topExpand > topSlack)
{
bottomExpand += (topExpand - topSlack);
}
if (bottomExpand > bottomSlack)
{
topExpand += (bottomExpand - bottomSlack);
}
int topOut = (int)(boundingBox.Top - topExpand);
if (topOut < 0)
{
topOut = 0;
}
int bottomOut = (int)(boundingBox.Top + boundingBox.Height + bottomExpand);
if (bottomOut > yRes)
{
bottomOut = yRes;
}
expandedBox.Initialize(leftOut, topOut, rightOut - leftOut, bottomOut - topOut);
// Create the reduced Rect so after performing the local threshold, we can reduce the size back to the original ROI dimensions.
reducedBox.Initialize(Math.Max(boundingBox.Left - leftOut, 0), Math.Max(boundingBox.Top - topOut, 0), boundingBox.Width + Math.Min(boundingBox.Left, 0), boundingBox.Height + Math.Min(boundingBox.Top, 0));
// Set this flag so the image can be reduced after performing the local threshold.
useExpandedROI = 1;
}
}
// if Expanded Box hasn't been updated, use the boundingBox passed in to extract.
if (useExpandedROI == 0)
{
expandedBox = boundingBox;
}
// Extract the region of interest into the mask image.
Algorithms.Extract(image, imageMask, expandedBox, 1, 1);
// Create a temporary ROI that will be used to mask the extracted image, to get rid of
// the pixels outside of the rotated rectangle.
Roi tmpROI = new Roi(roi);
// If the ROI is a rotated rectangle, then compute the new location of the search ROI.
if ((roi[0].Type == ContourType.RotatedRectangle) && (((RotatedRectangleContour)roi[0].Shape).Angle > 0.01))
{
CoordinateSystem baseSystem = new CoordinateSystem();
baseSystem.Origin.X = (roi.GetBoundingRectangle().Left < 0 ? 0 : roi.GetBoundingRectangle().Left);
baseSystem.Origin.Y = (roi.GetBoundingRectangle().Top < 0 ? 0 : roi.GetBoundingRectangle().Top);
baseSystem.Angle = 0;
baseSystem.AxisOrientation = AxisOrientation.Direct;
CoordinateSystem newSystem = new CoordinateSystem(new PointContour(0, 0), 0, AxisOrientation.Direct);
CoordinateTransform transform = new CoordinateTransform(baseSystem, newSystem);
Algorithms.TransformRoi(tmpROI, transform);
}
// Create a temporary image.
using (VisionImage tmpImageMask = new VisionImage(ImageType.U8, 7))
{
double thresholdMin;
double thresholdMax;
switch (preprocessingOptions.ThresholdType)
{
case ThresholdType.Manual:
thresholdMin = preprocessingOptions.ManualThresholdRange.Minimum;
thresholdMax = preprocessingOptions.ManualThresholdRange.Maximum;
Algorithms.Threshold(imageMask, imageMask, new Range(thresholdMin, thresholdMax), true, 1);
break;
case ThresholdType.Auto:
Collection <ThresholdData> thresholdData;
thresholdData = Algorithms.AutoThreshold(image, tmpImageMask, 2, preprocessingOptions.AutoThresholdOptions.Method);
if (preprocessingOptions.AutoThresholdOptions.ParticleType == ParticleType.Bright)
{
thresholdMin = (thresholdData[0].Range.Maximum > preprocessingOptions.AutoThresholdOptions.Limits.Minimum ?
thresholdData[0].Range.Maximum : preprocessingOptions.AutoThresholdOptions.Limits.Minimum);
thresholdMax = 255;
}
else
{
thresholdMin = 0;
thresholdMax = (thresholdData[0].Range.Maximum < preprocessingOptions.AutoThresholdOptions.Limits.Maximum ?
thresholdData[0].Range.Maximum : preprocessingOptions.AutoThresholdOptions.Limits.Maximum);
}
Algorithms.Threshold(imageMask, imageMask, new Range(thresholdMin, thresholdMax), true, 1);
break;
case ThresholdType.Local:
LocalThresholdOptions Options = new LocalThresholdOptions(preprocessingOptions.LocalThresholdOptions.ParticleType, preprocessingOptions.LocalThresholdOptions.Method, 1.0, preprocessingOptions.LocalThresholdOptions.WindowWidth, preprocessingOptions.LocalThresholdOptions.WindowHeight);
Options.DeviationWeight = preprocessingOptions.LocalThresholdOptions.DeviationWeight;
Algorithms.LocalThreshold(imageMask, imageMask, Options);
break;
default:
break;
}
/// If the expanded ROI was used, reduce it so no particles are found outside requested ROI.
if (useExpandedROI == 1)
{
Algorithms.Extract(imageMask, imageMask, reducedBox, 1, 1);
}
// Cast the image to 8 bit.
imageMask.Type = ImageType.U8;
// Eliminates particles that touch the border of the image.
if (preprocessingOptions.RejectBorder)
{
if ((roi[0].Type == ContourType.RotatedRectangle) && (((RotatedRectangleContour)roi[0].Shape).Angle > 0.01))
{
// Special case for the rotated rectangle.
Algorithms.Label(imageMask, imageMask, Connectivity.Connectivity8);
Collection <short> lookupTable = new Collection <short>();
lookupTable.Add(0);
for (int i = 1; i < 256; i++)
{
lookupTable.Add(1);
}
RoiProfileReport roiProfile = Algorithms.RoiProfile(imageMask, tmpROI);
for (int i = 0; i < roiProfile.Report.ProfileData.Count; i++)
{
lookupTable[0] = (short)roiProfile.Report.ProfileData[i];
}
Algorithms.UserLookup(imageMask, imageMask, lookupTable);
}
else
{
Algorithms.RejectBorder(imageMask, imageMask, Connectivity.Connectivity8);
}
}
// Remove small particles.
if (preprocessingOptions.NumberOfErosions > 0)
{
Algorithms.RemoveParticle(imageMask, imageMask, preprocessingOptions.NumberOfErosions, SizeToKeep.KeepLarge);
}
// If the rectangle is rotated, mask out the areas of the image that are not in the ROI.
if ((roi[0].Type == ContourType.RotatedRectangle) && (((RotatedRectangleContour)roi[0].Shape).Angle > 0.01))
{
// Perform the mask
Algorithms.RoiToMask(tmpImageMask, tmpROI, new PixelValue(255));
Algorithms.And(imageMask, tmpImageMask, imageMask);
}
// Sets the mask offset.
imageMask.MaskOffset.X = Math.Max(0, roi.GetBoundingRectangle().Left);
imageMask.MaskOffset.Y = Math.Max(0, roi.GetBoundingRectangle().Top);
}
tmpROI.Dispose();
}
public static PaletteType ProcessImage(VisionImage image, string path, out double[] distance)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(17, 1);
distance = new double[4] {
0, 0, 0, 0
};
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new AnnulusContour using the given values.
PointContour vaCenter = new PointContour(1283, 965);
AnnulusContour vaOval = new AnnulusContour(vaCenter, 418, 702, 0, 0);
roi.Add(vaOval);
// Find Circular Edge
EdgeOptions vaOptions = new EdgeOptions();
vaOptions.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions.InterpolationType = InterpolationMethod.Bilinear;
vaOptions.KernelSize = 3;
vaOptions.MinimumThreshold = 18;
vaOptions.Polarity = EdgePolaritySearchMode.Rising;
vaOptions.Width = 3;
CircularEdgeFitOptions vaFitOptions = new CircularEdgeFitOptions();
vaFitOptions.ProcessType = RakeProcessType.GetFirstEdges;
vaFitOptions.StepSize = 7;
vaFitOptions.MaxPixelRadius = 3;
vaCircularEdgeReport = IVA_FindCircularEdge(image, roi, SpokeDirection.InsideToOutside, vaOptions, vaFitOptions, ivaData, 1);
roi.Dispose();
// Set Coordinate System
int vaCoordSystemIndex = 0;
int stepIndexOrigin = 1;
int resultIndexOrigin = 0;
int stepIndexAngle = -1;
int resultIndexAngle = 0;
double refSysOriginX = vaCircularEdgeReport.Center.X;
double refSysOriginY = vaCircularEdgeReport.Center.Y;
double refSysAngle = 0;
AxisOrientation refSysAxisOrientation = AxisOrientation.Direct;
int vaCoordSystemType = 0;
IVA_CoordSys(vaCoordSystemIndex, stepIndexOrigin, resultIndexOrigin, stepIndexAngle, resultIndexAngle, refSysOriginX, refSysOriginY, refSysAngle, refSysAxisOrientation, vaCoordSystemType, ivaData);
// Image Buffer: Push
Functions.IVA_PushBuffer(ivaData, image, 0);
// Get Image
string vaFilePath = path;
FileInformation vaFileInfo = Algorithms.GetFileInformation(vaFilePath);
// Set the image size to 0 to speed up the cast.
//image.SetSize(0, 0);
//image.Type = vaFileInfo.ImageType;
//image.BitDepth = 0;
image.ReadFile(vaFilePath);
switch (image.Type)
{
case ImageType.I16:
case ImageType.U16:
if (image.BitDepth == 0 & false)
{
image.BitDepth = 10;
}
break;
default:
break;
}
// Operators: Absolute Difference Image
Algorithms.AbsoluteDifference(image, Functions.IVA_GetBuffer(ivaData, 0), image);
// Creates a new, empty region of interest.
Roi roi2 = new Roi();
// Creates a new AnnulusContour using the given values.
PointContour vaCenter2 = new PointContour(vaCircularEdgeReport.Center.X, vaCircularEdgeReport.Center.Y);
AnnulusContour vaOval2 = new AnnulusContour(vaCenter2, 527, 846, 0, 0);
roi2.Add(vaOval2);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex = 0;
Algorithms.TransformRoi(roi2, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex], ivaData.MeasurementSystems[coordSystemIndex]));
// Mask from ROI
IVA_Mask_From_ROI(image, roi2, false, false);
roi2.Dispose();
// Color Threshold
Range plane1Range = new Range(0, 60);
Range plane2Range = new Range(0, 50);
Range plane3Range = new Range(0, 255);
using (VisionImage thresholdImage = new VisionImage(ImageType.U8, 7))
{
Algorithms.ColorThreshold(image, thresholdImage, ColorMode.Rgb, 1, plane1Range, plane2Range, plane3Range);
Algorithms.Copy(thresholdImage, image);
}
// Truncates the frequencies of an image.
IVA_FFT_Truncate(image, TruncateMode.High, 7);
// Advanced Morphology: Remove Objects
int[] vaCoefficients = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem = new StructuringElement(3, 3, vaCoefficients);
vaStructElem.Shape = StructuringElementShape.Square;
// Filters particles based on their size.
Algorithms.RemoveParticle(image, image, 30, SizeToKeep.KeepLarge, Connectivity.Connectivity8, vaStructElem);
// Invert Binary Image.
IVA_BinaryInverse(image);
// Advanced Morphology: Remove Objects
int[] vaCoefficients2 = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem2 = new StructuringElement(3, 3, vaCoefficients2);
vaStructElem.Shape = StructuringElementShape.Square;
// Filters particles based on their size.
Algorithms.RemoveParticle(image, image, 5, SizeToKeep.KeepLarge, Connectivity.Connectivity8, vaStructElem2);
// Basic Morphology - Applies morphological transformations to binary images.
int[] vaCoefficients3 = { 0, 1, 0, 1, 1, 1, 0, 1, 0 };
StructuringElement vaStructElem3 = new StructuringElement(3, 3, vaCoefficients3);
vaStructElem.Shape = StructuringElementShape.Square;
// Applies morphological transformations
for (int i = 0; i < 3; ++i)
{
Algorithms.Morphology(image, image, MorphologyMethod.Erode, vaStructElem3);
}
// Advanced Morphology: Fill Holes
VisionImage image1 = new VisionImage();
Algorithms.FillHoles(image, image1, Connectivity.Connectivity8);
// Particle Analysis - Computes the number of particles detected in a binary image and
// returns the requested measurements about the particles.
Collection <MeasurementType> vaPixelMeasurements = new Collection <MeasurementType>(new MeasurementType[] { MeasurementType.Area });
Collection <MeasurementType> vaCalibratedMeasurements = new Collection <MeasurementType>(new MeasurementType[] { });
IVA_Particle(image1, Connectivity.Connectivity8, vaPixelMeasurements, vaCalibratedMeasurements, ivaData, 16, out vaParticleReport, out vaParticleReportCalibrated);
double[,] area = vaParticleReport.PixelMeasurements;
double Maxarea = 0;
for (int i = 0; i < area.GetLength(0); i++)
{
for (int j = 0; j < area.GetLength(1); j++)
{
if (area[i, j] > Maxarea)
{
Maxarea = area[i, j];
}
}
}
image1.Dispose();
if (Maxarea > 1000000)
{
// Creates a new, empty region of interest.
Roi roi3 = new Roi();
// Creates a new AnnulusContour using the given values.
PointContour vaCenter3 = new PointContour(1295, 963);
AnnulusContour vaOval3 = new AnnulusContour(vaCenter3, 496, 892, 0, 0);
roi3.Add(vaOval3);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex2 = 0;
Algorithms.TransformRoi(roi3, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex2], ivaData.MeasurementSystems[coordSystemIndex2]));
// Extract the contour edges from the image
CurveParameters vaCurveParams = new CurveParameters(ExtractionMode.NormalImage, 1, EdgeFilterSize.ContourTracing, 30, 20, 10, true);
double[] vaConstraintMinArray = { };
double[] vaConstraintMaxArray = { };
ConnectionConstraintType[] vaConstraintTypeArray = { };
ExtractContourReport vaExtractReport = IVA_ExtractContour(image, roi3, ExtractContourDirection.AnnulusOuterInner, vaCurveParams, vaConstraintTypeArray, vaConstraintMinArray, vaConstraintMaxArray, ExtractContourSelection.Closest);
// Fit a circle to the contour
ContourOverlaySettings vaEquationOverlay = new ContourOverlaySettings(true, Rgb32Value.GreenColor, 1, true);
ContourOverlaySettings vaPointsOverlay = new ContourOverlaySettings(true, Rgb32Value.RedColor, 1, true);
PartialCircle vaCircleReport = Algorithms.ContourFitCircle(image, 100, true);
Algorithms.ContourOverlay(image, image, vaPointsOverlay, vaEquationOverlay);
ComputeDistanceReport vaDistanceReport = Algorithms.ContourComputeDistances(image, image, 0);
MaxDistance = 0;
MaxDistanceIndex = 0;
for (int i = 0; i < vaDistanceReport.Distances.Count; i++)
{
if (vaDistanceReport.Distances[i].Distance > MaxDistance)
{
MaxDistance = vaDistanceReport.Distances[i].Distance;
MaxDistanceIndex = i;
}
}
var pos = vaDistanceReport.Distances[MaxDistanceIndex];
distance[0] = MaxDistance;
roi3.Dispose();
// Creates a new, empty region of interest.
Roi roi4 = new Roi();
// Creates a new AnnulusContour using the given values.
PointContour vaCenter4 = new PointContour(1294, 962);
AnnulusContour vaOval4 = new AnnulusContour(vaCenter4, 499, 885, 0, 0);
roi4.Add(vaOval4);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex3 = 0;
Algorithms.TransformRoi(roi4, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex3], ivaData.MeasurementSystems[coordSystemIndex3]));
// Extract the contour edges from the image
CurveParameters vaCurveParams2 = new CurveParameters(ExtractionMode.NormalImage, 1, EdgeFilterSize.ContourTracing, 30, 25, 10, true);
double[] vaConstraintMinArray2 = { };
double[] vaConstraintMaxArray2 = { };
ConnectionConstraintType[] vaConstraintTypeArray2 = { };
ExtractContourReport vaExtractReport2 = IVA_ExtractContour(image, roi4, ExtractContourDirection.AnnulusInnerOuter, vaCurveParams2, vaConstraintTypeArray2, vaConstraintMinArray2, vaConstraintMaxArray2, ExtractContourSelection.Closest);
// Fit a circle to the contour
ContourOverlaySettings vaEquationOverlay2 = new ContourOverlaySettings(true, Rgb32Value.GreenColor, 1, true);
ContourOverlaySettings vaPointsOverlay2 = new ContourOverlaySettings(true, Rgb32Value.RedColor, 1, true);
PartialCircle vaCircleReport2 = Algorithms.ContourFitCircle(image, 100, true);
Algorithms.ContourOverlay(image, image, vaPointsOverlay2, vaEquationOverlay2);
ComputeDistanceReport vaDistanceReport2 = Algorithms.ContourComputeDistances(image, image, 0);
MaxDistance1 = 0;
MaxDistanceIndex1 = 0;
for (int i = 0; i < vaDistanceReport2.Distances.Count; i++)
{
if (vaDistanceReport2.Distances[i].Distance > MaxDistance1)
{
MaxDistance1 = vaDistanceReport2.Distances[i].Distance;
MaxDistanceIndex1 = i;
}
}
var pos1 = vaDistanceReport2.Distances[MaxDistanceIndex1];
distance[1] = MaxDistance1;
distance[2] = (vaCircleReport2.Center.X - vaCircularEdgeReport.Center.X) / 96;
distance[3] = (vaCircleReport2.Center.Y - vaCircularEdgeReport.Center.Y) / 96;
roi4.Dispose();
}
else
{
distance[0] = 9999;
distance[1] = 9999;
distance[2] = 9999;
distance[3] = 9999;
}
// Dispose the IVA_Data structure.
ivaData.Dispose();
if (path == $"{ @"./ImageTemp/temp.jpg"}")
{
image.Dispose();
}
// Return the palette type of the final image.
return(PaletteType.Binary);
}
public PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(7, 0);
// Extract Color Plane
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the red color plane and copy it to the main image.
Algorithms.ExtractColorPlanes(image, ColorMode.Rgb, plane, null, null);
Algorithms.Copy(plane, image);
}
// Filters: Convolution - Applies a linear filter to an image by convolving the image with a filtering kernel.
double[] vaCoefficients = { 1, 2, 4, 2, 1, 2, 4, 8, 4, 2, 4, 8, 16, 8, 4, 2, 4, 8, 4, 2, 1, 2, 4, 2, 1 };
Algorithms.Convolute(image, image, new Kernel(5, 5, vaCoefficients));
// Filters: Convolution - Applies a linear filter to an image by convolving the image with a filtering kernel.
double[] vaCoefficients2 = { -1, -1, -1, -1, 10, -1, -1, -1, -1 };
Algorithms.Convolute(image, image, new Kernel(3, 3, vaCoefficients2));
// Automatic Threshold
Algorithms.AutoThreshold(image, image, 2, ThresholdMethod.Clustering);
// Basic Morphology - Applies morphological transformations to binary images.
int[] vaCoefficients3 = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem = new StructuringElement(7, 7, vaCoefficients3);
vaStructElem.Shape = StructuringElementShape.Hexagon;
// Applies morphological transformations
Algorithms.Morphology(image, image, MorphologyMethod.Open, vaStructElem);
// Lookup Table: Equalize
// Calculates the histogram of the image and redistributes pixel values
// accross the desired range to maintain the same pixel value distribution.
Range equalizeRange = new Range(0, 255);
if (image.Type != ImageType.U8)
{
equalizeRange.Maximum = 0;
}
Algorithms.Equalize(image, image, null, equalizeRange, null);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(0, 0, image.Width, image.Height);
roi.Add(vaRect);
// Classifies all the objects located in the given ROI.
string vaClassifierFilePath = "C:\\DATA\\#hasilscan2\\Ukuran Classifier.clf";
vaClassifierReports = IVA_Classify(image, roi, vaClassifierFilePath);
roi.Dispose();
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Binary);
}
public string Process1DBarcode(VisionImage image, TemplateConfig templateConfig, List <BarcodeConfig> barcodeConfigs)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(5, 1);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RotatedRectangleContour using the given values.
//PointContour vaCenter = new PointContour(1294, 972);
//RotatedRectangleContour vaRotatedRect = new RotatedRectangleContour(vaCenter, 2548, 1904, 0);
// Creates a new RectangleContour using the given values.
RectangleContour vaRotatedRect = new RectangleContour(templateConfig.Rectangle.Left,
templateConfig.Rectangle.Top, templateConfig.Rectangle.Width, templateConfig.Rectangle.Height);
roi.Add(vaRotatedRect);
image.Overlays.Default.AddRoi(roi);
// MatchPattern Grayscale
MatchMode vaMode = MatchMode.RotationInvariant;
bool vaSubpixelVal = false;
int[] minAngleVals = { -30, 0 };
int[] maxAngleVals = { 30, 0 };
int vaNumMatchesRequested = 1;
double vaMinMatchScore = 800;
double vaOffsetX = 0;
double vaOffsetY = 0;
pmResults = IVA_MatchPattern(image, ivaData, templateConfig.TemplatePath, vaMode, vaSubpixelVal,
minAngleVals, maxAngleVals, vaNumMatchesRequested, vaMinMatchScore, roi, vaOffsetX, vaOffsetY, 0);
foreach (PatternMatch match in pmResults)
{
image.Overlays.Default.AddPolygon(new PolygonContour(match.Corners), Rgb32Value.RedColor);
}
roi.Dispose();
// Set Coordinate System
int vaCoordSystemIndex = 0;
int stepIndexOrigin = 0;
int resultIndexOrigin = 1;
int stepIndexAngle = 0;
int resultIndexAngle = 3;
double refSysOriginX = templateConfig.Position.X;
double refSysOriginY = templateConfig.Position.Y;
double refSysAngle = 0;
AxisOrientation refSysAxisOrientation = AxisOrientation.Direct;
int vaCoordSystemType = 3;
IVA_CoordSys(vaCoordSystemIndex, stepIndexOrigin, resultIndexOrigin, stepIndexAngle,
resultIndexAngle, refSysOriginX, refSysOriginY, refSysAngle, refSysAxisOrientation, vaCoordSystemType, ivaData);
string barcodeInfo = "";
for (int i = 0; i < barcodeConfigs.Count; i++)
{
Roi roiBarcode = new Roi();
RectangleContour vaRect = new RectangleContour(barcodeConfigs[i].Rectangle.Left,
barcodeConfigs[i].Rectangle.Top, barcodeConfigs[i].Rectangle.Width, barcodeConfigs[i].Rectangle.Height);
roiBarcode.Add(vaRect);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex = 0;
Algorithms.TransformRoi(roiBarcode, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex],
ivaData.MeasurementSystems[coordSystemIndex]));
image.Overlays.Default.AddRoi(roiBarcode);
// Reads the barcode from the image.
BarcodeReport vaBarcode = Algorithms.ReadBarcode(image, barcodeConfigs[i].Type, roiBarcode, false);
barcodeInfo += string.Format("{0},", vaBarcode.Text);
roiBarcode.Dispose();
}
barcodeInfo = barcodeInfo.Substring(0, barcodeInfo.Length - 1);
// Dispose the IVA_Data structure.
ivaData.Dispose();
return(barcodeInfo);
}
public string ProcessDatamatrix(VisionImage image, TemplateConfig templateConfig, List <DataMatrixConfig> dataMatrixConfigs)
{
string dataMatrixInfo = string.Empty;
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(3, 1);
// Creates a new, empty region of interest.
Roi roi = new Roi();
//// Creates a new RotatedRectangleContour using the given values.
//RotatedRectangleContour vaRotatedRect = new RotatedRectangleContour(vaCenter, 1268, 1220, 0);
// Creates a new RectangleContour using the given values.
RectangleContour vaRotatedRect = new RectangleContour(templateConfig.Rectangle.Left,
templateConfig.Rectangle.Top, templateConfig.Rectangle.Width, templateConfig.Rectangle.Height);
roi.Add(vaRotatedRect);
image.Overlays.Default.AddRoi(roi);
// MatchPattern Grayscale
MatchMode vaMode = MatchMode.RotationInvariant;
bool vaSubpixelVal = false;
int[] minAngleVals = { -30, 0 };
int[] maxAngleVals = { 30, 0 };
int vaNumMatchesRequested = 1;
double vaMinMatchScore = 800;
double vaOffsetX = 0;
double vaOffsetY = 0;
pmResults = IVA_MatchPattern(image, ivaData, templateConfig.TemplatePath, vaMode, vaSubpixelVal,
minAngleVals, maxAngleVals, vaNumMatchesRequested, vaMinMatchScore, roi, vaOffsetX, vaOffsetY, 0);
foreach (PatternMatch match in pmResults)
{
image.Overlays.Default.AddPolygon(new PolygonContour(match.Corners), Rgb32Value.RedColor);
}
roi.Dispose();
// Set Coordinate System
int vaCoordSystemIndex = 0;
int stepIndexOrigin = 0;
int resultIndexOrigin = 1;
int stepIndexAngle = 0;
int resultIndexAngle = 3;
double refSysOriginX = templateConfig.Position.X;
double refSysOriginY = templateConfig.Position.Y;
double refSysAngle = 0;
AxisOrientation refSysAxisOrientation = AxisOrientation.Direct;
int vaCoordSystemType = 3;
IVA_CoordSys(vaCoordSystemIndex, stepIndexOrigin, resultIndexOrigin, stepIndexAngle,
resultIndexAngle, refSysOriginX, refSysOriginY, refSysAngle, refSysAxisOrientation, vaCoordSystemType, ivaData);
for (int i = 0; i < dataMatrixConfigs.Count; i++)
{
// Creates a new, empty region of interest.
Roi roiDM = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(dataMatrixConfigs[i].Rectangle.Left,
dataMatrixConfigs[i].Rectangle.Top, dataMatrixConfigs[i].Rectangle.Width, dataMatrixConfigs[i].Rectangle.Height);
roiDM.Add(vaRect);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex = 0;
Algorithms.TransformRoi(roiDM, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex], ivaData.MeasurementSystems[coordSystemIndex]));
image.Overlays.Default.AddRoi(roiDM);
// Read DataMatrix Barcode
DataMatrixDescriptionOptions vaDescriptionOptions = new DataMatrixDescriptionOptions();
vaDescriptionOptions.AspectRatio = 0;
vaDescriptionOptions.CellFill = DataMatrixCellFillMode.AutoDetect;
uint matrixSizeColumns = 25;
uint.TryParse(dataMatrixConfigs[i].MatrixSize.Split('X')[1], out matrixSizeColumns);
vaDescriptionOptions.Columns = matrixSizeColumns;
vaDescriptionOptions.MinimumBorderIntegrity = 90;
vaDescriptionOptions.MirrorMode = DataMatrixMirrorMode.AutoDetect;
vaDescriptionOptions.Polarity = dataMatrixConfigs[0].Polarity;
vaDescriptionOptions.Rectangle = false;
uint matrixSizeRows = 25;
uint.TryParse(dataMatrixConfigs[i].MatrixSize.Split('X')[0], out matrixSizeRows);
vaDescriptionOptions.Rows = matrixSizeRows;
DataMatrixSizeOptions vaSizeOptions = new DataMatrixSizeOptions();
vaSizeOptions.MaximumSize = 250;
vaSizeOptions.MinimumSize = 50;
vaSizeOptions.QuietZoneWidth = 0;
DataMatrixSearchOptions vaSearchOptions = new DataMatrixSearchOptions();
vaSearchOptions.CellFilterMode = DataMatrixCellFilterMode.AutoDetect;
vaSearchOptions.CellSampleSize = dataMatrixConfigs[0].CellSize;
vaSearchOptions.DemodulationMode = DataMatrixDemodulationMode.AutoDetect;
vaSearchOptions.EdgeThreshold = 30;
vaSearchOptions.InitialSearchVectorWidth = 5;
vaSearchOptions.MaximumIterations = 150;
vaSearchOptions.RotationMode = DataMatrixRotationMode.Unlimited;
vaSearchOptions.SkewDegreesAllowed = 5;
vaSearchOptions.SkipLocation = false;
// Reads the data matrix from the image.
vaDataMatrixReport = Algorithms.ReadDataMatrixBarcode(image, roiDM, DataMatrixGradingMode.None,
vaDescriptionOptions, vaSizeOptions, vaSearchOptions);
if (vaDataMatrixReport.Found)
{
image.Overlays.Default.AddPolygon(new PolygonContour(vaDataMatrixReport.Corners),
Rgb32Value.RedColor, DrawingMode.DrawValue);
}
dataMatrixInfo += string.Format("{0},", vaDataMatrixReport.StringData);
roiDM.Dispose();
}
dataMatrixInfo = dataMatrixInfo.Substring(0, dataMatrixInfo.Length - 1);
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(dataMatrixInfo);
}
public PaletteType ProcessImage(VisionImage image)
{
//vaParticleReportCalibrated = new ParticleMeasurementsReport();
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(15, 0);
// Image Buffer: Push
Functions.IVA_PushBuffer(ivaData, image, 0);
// Operators: NOR Image
Algorithms.Nor(image, Functions.IVA_GetBuffer(ivaData, 0), image);
// Extract Color Plane
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the red color plane and copy it to the main image.
Algorithms.ExtractColorPlanes(image, ColorMode.Rgb, plane, null, null);
Algorithms.Copy(plane, image);
}
// Thresholds an image into 2 classes by using local thresholding.
LocalThresholdOptions vaLocalThresholdOptions = new LocalThresholdOptions();
vaLocalThresholdOptions.DeviationWeight = 1;
vaLocalThresholdOptions.Method = LocalThresholdMethod.BackgroundCorrection;
vaLocalThresholdOptions.ParticleType = ParticleType.Dark;
vaLocalThresholdOptions.ReplaceValue = 1;
vaLocalThresholdOptions.WindowHeight = 35;
vaLocalThresholdOptions.WindowWidth = 35;
Algorithms.LocalThreshold(image, image, vaLocalThresholdOptions);
// Basic Morphology - Applies morphological transformations to binary images.
int[] vaCoefficients = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem = new StructuringElement(3, 3, vaCoefficients);
vaStructElem.Shape = StructuringElementShape.Square;
// Applies morphological transformations
Algorithms.Morphology(image, image, MorphologyMethod.GradientOut, vaStructElem);
// Advanced Morphology: Fill Holes
Algorithms.FillHoles(image, image, Connectivity.Connectivity8);
// Advanced Morphology: Remove Objects
int[] vaCoefficients2 = { 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem2 = new StructuringElement(3, 3, vaCoefficients2);
vaStructElem.Shape = StructuringElementShape.Hexagon;
// Filters particles based on their size.
Algorithms.RemoveParticle(image, image, 6, SizeToKeep.KeepLarge, Connectivity.Connectivity8, vaStructElem2);
// Advanced Morphology: Remove Border Objects - Eliminates particles touching the border of the image.
Algorithms.RejectBorder(image, image, Connectivity.Connectivity8);
// Lookup Table: Equalize
// Calculates the histogram of the image and redistributes pixel values
// accross the desired range to maintain the same pixel value distribution.
Range equalizeRange = new Range(0, 255);
if (image.Type != ImageType.U8)
{
equalizeRange.Maximum = 0;
}
Algorithms.Equalize(image, image, null, equalizeRange, null);
// Image Buffer: Push
Functions.IVA_PushBuffer(ivaData, image, 1);
// Particle Analysis - Computes the number of particles detected in a binary image and
// returns the requested measurements about the particles.
Collection <MeasurementType> vaPixelMeasurements = new Collection <MeasurementType>(new MeasurementType[] { MeasurementType.BoundingRectLeft, MeasurementType.BoundingRectTop, MeasurementType.BoundingRectRight, MeasurementType.BoundingRectBottom, MeasurementType.MaxFeretDiameter });
Collection <MeasurementType> vaCalibratedMeasurements = new Collection <MeasurementType>(new MeasurementType[] {});
//IVA_Particle(image, Connectivity.Connectivity4, null, null, null, 10, out vaParticleReport, out vaParticleReportCalibrated);
IVA_Particle(image, Connectivity.Connectivity4, vaPixelMeasurements, vaCalibratedMeasurements, ivaData, 10, out vaParticleReport, out vaParticleReportCalibrated);
// Image Buffer: Pop
Algorithms.Copy(Functions.IVA_GetBuffer(ivaData, 1), image);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(0, 0, image.Width, image.Height);
roi.Add(vaRect);
// Classifies all the objects located in the given ROI.
string vaClassifierFilePath = "C:\\DATA\\#hasilscan3\\Particle Classifier.clf";
vaClassifierReports = IVA_Classify(image, roi, vaClassifierFilePath);
VisGrainTypeCollection colType = new VisGrainTypeCollection(vaClassifierReports);
roi.Dispose();
// Image Buffer: Pop
Algorithms.Copy(Functions.IVA_GetBuffer(ivaData, 1), image);
// Creates a new, empty region of interest.
Roi roi2 = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect2 = new RectangleContour(0, 0, image.Width, image.Height);
roi2.Add(vaRect2);
// Classifies all the objects located in the given ROI.
string vaClassifierFilePath2 = "C:\\DATA\\#hasilscan3\\Ukuran Classifier.clf";
vaClassifierReports2 = IVA_Classify(image, roi2, vaClassifierFilePath2);
VisGrainSizeCollection colSize = new VisGrainSizeCollection(vaClassifierReports2);
GrainResults = new VisGrainDataCollection(vaClassifierReports, vaClassifierReports2, ListShape);
roi2.Dispose();
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Binary);
}
public static PointContour MatchPattern(VisionImage SourceImage, RectangleContour vaRect, string TemplateFile, int vaNumMatchesRequested, float vaMinMatchScore, float fUpper = 0, float fLower = 0)
{
PointContour point = new PointContour();
point.X = -10000;
point.Y = -10000;
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter = new PointContour(vaRect.Left + vaRect.Width / 2, vaRect.Top + vaRect.Height / 2);
RotatedRectangleContour vaRotatedRect = new RotatedRectangleContour(vaCenter, vaRect.Width - 50, vaRect.Height - 50, 0);
roi.Add(vaRotatedRect);
// MatchPattern Grayscale
// string TemplateFile = "D:\\t1.png";
MatchingAlgorithm matchAlgorithm = MatchingAlgorithm.MatchGrayValuePyramid;
float[] minAngleVals = { fLower, 0 };
float[] maxAngleVals = { fUpper, 0 };
int[] advancedOptionsItems = { 102, 106, 107, 108, 109, 111, 112, 113, 103, 104, 105, 100 };
double[] advancedOptionsValues = { 10, 300, 0, 6, 1, 20, 10, 20, 1, 20, 0, 5 };
int numberAdvOptions = 12;
//int vaNumMatchesRequested = 1;
//float vaMinMatchScore = 800;
using (VisionImage imageTemplate = new VisionImage(ImageType.U8, 7))
{
Collection <PatternMatchReport> patternMatchingResults = new Collection <PatternMatchReport>();
// Read the image template.
imageTemplate.ReadVisionFile(TemplateFile);
// Set the angle range.
Collection <RotationAngleRange> angleRange = new Collection <RotationAngleRange>();
for (int i = 0; i < 2; ++i)
{
angleRange.Add(new RotationAngleRange(minAngleVals[i], maxAngleVals[i]));
}
// Set the advanced options.
Collection <PMMatchAdvancedSetupDataOption> advancedMatchOptions = new Collection <PMMatchAdvancedSetupDataOption>();
for (int i = 0; i < numberAdvOptions; ++i)
{
advancedMatchOptions.Add(new PMMatchAdvancedSetupDataOption((MatchSetupOption)advancedOptionsItems[i], advancedOptionsValues[i]));
}
// Searches for areas in the image that match a given pattern.
patternMatchingResults = Algorithms.MatchPattern3(SourceImage, imageTemplate, matchAlgorithm, vaNumMatchesRequested, vaMinMatchScore, angleRange, roi, advancedMatchOptions);
string sPatterScore = "";
if (patternMatchingResults.Count > 0)
{
for (int i = 0; i < 1 /* patternMatchingResults.Count*/; ++i)
{
point.X = patternMatchingResults[i].Position.X;
point.Y = patternMatchingResults[i].Position.Y;
sPatterScore += " " + patternMatchingResults[i].Score.ToString();
//SourceImage.Overlays.Default.AddRectangle(new RectangleContour(point.X - imageTemplate.Width / 2 - 1, point.Y - imageTemplate.Height / 2 - 1, imageTemplate.Width, imageTemplate.Height), Rgb32Value.GreenColor);
LineContour l1 = new LineContour();
l1.Start.X = point.X - (imageTemplate.Width / 2 - 3);
l1.Start.Y = point.Y;
l1.End.X = point.X + (imageTemplate.Width / 2 - 3);
l1.End.Y = point.Y;
SourceImage.Overlays.Default.AddLine(l1, Rgb32Value.RedColor);
LineContour l2 = new LineContour();
l2.Start.X = point.X;
l2.Start.Y = point.Y - (imageTemplate.Height / 2 - 3);
l2.End.X = point.X;
l2.End.Y = point.Y + (imageTemplate.Height / 2 - 3);
SourceImage.Overlays.Default.AddLine(l2, Rgb32Value.RedColor);
}
}
}
roi.Dispose();
return(point);
}
//Circle****************************************************************************************
/// <summary>
/// 找圆-使用ROI-RectangleRegion
/// </summary>
/// <param name="img">图片</param>
/// <param name="rectRoi">ROI</param>
/// <param name="MinRadius">最小半径</param>
/// <param name="MaxRadius">最大半径</param>
/// <param name="Center">中心点</param>
/// <param name="Radius">半径</param>
/// <param name="ho_Contcircle">圆轮廓</param>
/// <param name="ho_cross">圆中心</param>
/// <returns></returns>
public static bool DetectCircle(HObject img, RectangleContour rectRoi, double MinRadius, double MaxRadius, out PointF Center, out double Radius, out HObject ho_Contcircle, out HObject ho_cross)
{
//*************************************************************************************************
ho_Contcircle = null;
ho_cross = null;
Center = new PointF();
Radius = 0;
HObject ho_ImageROI, Roi, hCircles, countour;
HOperatorSet.GenEmptyObj(out ho_ImageROI);
HOperatorSet.GenEmptyObj(out hCircles);
HOperatorSet.GenEmptyObj(out countour);
HOperatorSet.GenRectangle1(out Roi, rectRoi.Left, rectRoi.Top, rectRoi.Left + rectRoi.Height, rectRoi.Width);
//*************************************************************************************************
HTuple hv_numbers, CoutourType;//返回拟合圆个数
try
{
HOperatorSet.ReduceDomain(img, Roi, out ho_ImageROI); //获取图像区域 形态学处理后
HOperatorSet.EdgesSubPix(ho_ImageROI, out ho_ImageROI, "canny", 1.5, 50, 75);
HOperatorSet.SegmentContoursXld(ho_ImageROI, out ho_ImageROI, "lines_circles", 5, 4, 2);
HOperatorSet.SelectShapeXld(ho_ImageROI, out ho_ImageROI, "circularity", "and", 0.5, 1);
HOperatorSet.SelectShapeXld(ho_ImageROI, out ho_ImageROI, "outer_radius", "and", MinRadius, MaxRadius);
HOperatorSet.CountObj(ho_ImageROI, out hv_numbers);
if (hv_numbers.D != 0)
{
for (int i = 0; i < hv_numbers.D; i++)
{
HOperatorSet.SelectObj(ho_ImageROI, out countour, i);
HOperatorSet.GetContourAttribXld(countour, "cont_approx", out CoutourType);
if (CoutourType.D != -1)//-1=line 0- 1-circle
{
HOperatorSet.ConcatObj(hCircles, countour, out hCircles);
}
}
HOperatorSet.CountObj(hCircles, out hv_numbers);
if (hv_numbers.D == 0)
{
Roi.Dispose();
ho_ImageROI.Dispose();
hCircles.Dispose();
countour.Dispose();
return(false);
}
HTuple hv_Row, hv_Column, hv_Radius, hv_startPhi, hv_endPhi, hv_PointOrder;
HOperatorSet.FitCircleContourXld(hCircles, "geometric", -1, 2, 0, 3, 2, out hv_Row, out hv_Column, out hv_Radius, out hv_startPhi, out hv_endPhi, out hv_PointOrder);
hv_numbers = new HTuple(hv_Row.TupleLength());
if (hv_numbers.D == 0)
{
Roi.Dispose();
ho_ImageROI.Dispose();
hCircles.Dispose();
countour.Dispose();
return(false);
}
Center.X = (float)(hv_Column[0].D);
Center.Y = (float)(hv_Row[0].D);
Radius = hv_Radius[0].D;
HOperatorSet.GenCircleContourXld(out ho_Contcircle, hv_Row[0], hv_Column[0], hv_Radius[0], 0, 6.28, "positive", 1);
HOperatorSet.GenCrossContourXld(out ho_cross, hv_Row[0], hv_Column[0], 10, 0);
Roi.Dispose();
ho_ImageROI.Dispose();
hCircles.Dispose();
countour.Dispose();
return(true);
}
else
{
Roi.Dispose();
ho_ImageROI.Dispose();
hCircles.Dispose();
countour.Dispose();
return(false);
}
}
catch
{
Roi.Dispose();
ho_ImageROI.Dispose();
hCircles.Dispose();
countour.Dispose();
return(false);
}
}
/// <summary>
/// Process QR code with coordinate
/// </summary>
/// <param name="image"></param>
/// <param name="userProgram"></param>
/// <returns>split with ','</returns>
public string ProcessQRCoordinate(VisionImage image, UserProgram userProgram)
{
string qRInfo = string.Empty;
TemplateConfig templateConfig = userProgram.TemplateConfig;
List <QRConfig> qRConfigs = userProgram.QRConfigs;
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(3, 1);
// Creates a new, empty region of interest.
Roi roiFullRange = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter = new PointContour(1405.5, 954);
RotatedRectangleContour vaRotatedRect = new RotatedRectangleContour(vaCenter, 1661, 1184, 0);
RectangleContour rectangle = new RectangleContour(templateConfig.Rectangle.Left, templateConfig.Rectangle.Top,
templateConfig.Rectangle.Width, templateConfig.Rectangle.Height);
roiFullRange.Add(rectangle);
// MatchPattern Grayscale
string vaTemplateFile = templateConfig.TemplatePath;
MatchMode vaMode = MatchMode.RotationInvariant;
bool vaSubpixelVal = false;
int[] minAngleVals = { -20, 0 };
int[] maxAngleVals = { 20, 0 };
int vaNumMatchesRequested = 1;
double vaMinMatchScore = 800;
double vaOffsetX = 0;
double vaOffsetY = 0;
pmResults = IVA_MatchPattern(image, ivaData, vaTemplateFile, vaMode, vaSubpixelVal,
minAngleVals, maxAngleVals, vaNumMatchesRequested, vaMinMatchScore, roiFullRange, vaOffsetX, vaOffsetY, 0);
if (pmResults.Count < 1)
{
return(string.Empty);
}
foreach (PatternMatch match in pmResults)
{
image.Overlays.Default.AddPolygon(new PolygonContour(match.Corners), Rgb32Value.RedColor);
}
roiFullRange.Dispose();
// Set Coordinate System
int vaCoordSystemIndex = 0;
int stepIndexOrigin = 0;
int resultIndexOrigin = 1;
int stepIndexAngle = 0;
int resultIndexAngle = 3;
double refSysOriginX = templateConfig.Position.X;
double refSysOriginY = templateConfig.Position.Y;
double refSysAngle = 0;
AxisOrientation refSysAxisOrientation = AxisOrientation.Direct;
int vaCoordSystemType = 3;
IVA_CoordSys(vaCoordSystemIndex, stepIndexOrigin, resultIndexOrigin, stepIndexAngle,
resultIndexAngle, refSysOriginX, refSysOriginY, refSysAngle, refSysAxisOrientation, vaCoordSystemType, ivaData);
for (int i = 0; i < qRConfigs.Count; i++)
{
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(qRConfigs[i].Rectangle.Left,
qRConfigs[i].Rectangle.Top, qRConfigs[i].Rectangle.Width, qRConfigs[i].Rectangle.Height);
roi.Add(vaRect);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex = 0;
Algorithms.TransformRoi(roi, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex],
ivaData.MeasurementSystems[coordSystemIndex]));
// Read QR Code
QRDescriptionOptions vaQROptions = new QRDescriptionOptions();
vaQROptions.Dimensions = qRConfigs[i].QRDimension;
vaQROptions.MirrorMode = QRMirrorMode.AutoDetect;
vaQROptions.ModelType = QRModelType.AutoDetect;
vaQROptions.Polarity = qRConfigs[i].Polarity;
QRSizeOptions vaQRSizeOptions = new QRSizeOptions(3, 15);
QRSearchOptions vaQRSearchOptions = new QRSearchOptions();
vaQRSearchOptions.CellFilterMode = QRCellFilterMode.AutoDetect;
vaQRSearchOptions.CellSampleSize = qRConfigs[i].CellSize;
vaQRSearchOptions.DemodulationMode = QRDemodulationMode.AutoDetect;
vaQRSearchOptions.EdgeThreshold = 30;
vaQRSearchOptions.RotationMode = QRRotationMode.Unlimited;
vaQRSearchOptions.SkewDegreesAllowed = 5;
vaQRSearchOptions.SkipLocation = false;
vaQRCode = Algorithms.ReadQRCode(image, roi, vaQROptions, vaQRSizeOptions, vaQRSearchOptions);
if (vaQRCode.Found)
{
image.Overlays.Default.AddPolygon(new PolygonContour(vaQRCode.Corners), Rgb32Value.RedColor, DrawingMode.DrawValue);
}
System.Text.ASCIIEncoding vaASCIIEncoding = new System.Text.ASCIIEncoding();
vaQRCodeData = vaASCIIEncoding.GetString(vaQRCode.GetData());
qRInfo += string.Format("{0},", vaQRCodeData);
roi.Dispose();
}
if (!string.IsNullOrEmpty(qRInfo))
{
qRInfo = qRInfo.Substring(0, qRInfo.Length - 1);
}
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(qRInfo);
}
public static PaletteType RectLeftPos(VisionImage image, Point pointoffset)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(12, 1);
// Extract Color Plane
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the red color plane and copy it to the main image.
Algorithms.ExtractColorPlanes(image, ColorMode.Rgb, plane, null, null);
Algorithms.Copy(plane, image);
}
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(630, 1313, 1073, 416);
roi.Add(vaRect);
// MatchPattern Grayscale
string dicpath = System.Windows.Forms.Application.StartupPath;
string vaTemplateFile = dicpath + $"{ @"/ImageConfig/LeftRectPos.png"}";
MatchingAlgorithm matchAlgorithm = MatchingAlgorithm.MatchGrayValuePyramid;
float[] minAngleVals = { -10, 0 };
float[] maxAngleVals = { 10, 0 };
int[] advancedOptionsItems = { 100, 102, 106, 107, 108, 109, 114, 116, 117, 118, 111, 112, 113, 103, 104, 105 };
double[] advancedOptionsValues = { 5, 10, 300, 0, 6, 1, 25, 0, 0, 0, 20, 10, 20, 1, 20, 0 };
int numberAdvOptions = 16;
int vaNumMatchesRequested = 1;
float vaMinMatchScore = 700;
pmResults = IVA_MatchPattern(image, ivaData, vaTemplateFile, matchAlgorithm, minAngleVals, maxAngleVals, advancedOptionsItems, advancedOptionsValues, numberAdvOptions, vaNumMatchesRequested, vaMinMatchScore, roi, 2);
roi.Dispose();
if (pmResults.Count == 1)
{
// Set Coordinate System
int vaCoordSystemIndex = 0;
int stepIndexOrigin = 2;
int resultIndexOrigin = 1;
int stepIndexAngle = 2;
int resultIndexAngle = 3;
double refSysOriginX = 1160.5;
double refSysOriginY = 1500.5;
double refSysAngle = 0;
AxisOrientation refSysAxisOrientation = AxisOrientation.Direct;
int vaCoordSystemType = 3;
IVA_CoordSys(vaCoordSystemIndex, stepIndexOrigin, resultIndexOrigin, stepIndexAngle, resultIndexAngle, refSysOriginX, refSysOriginY, refSysAngle, refSysAxisOrientation, vaCoordSystemType, ivaData);
// Creates a new, empty region of interest.
Roi roi2 = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter = new PointContour(789, 965.5);
RotatedRectangleContour vaRotatedRect = new RotatedRectangleContour(vaCenter, 72, 1119, 0);
roi2.Add(vaRotatedRect);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex = 0;
Algorithms.TransformRoi(roi2, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex], ivaData.MeasurementSystems[coordSystemIndex]));
// Find Straight Edge
EdgeOptions vaOptions = new EdgeOptions();
vaOptions.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions.InterpolationType = InterpolationMethod.Bilinear;
vaOptions.KernelSize = 9;
vaOptions.MinimumThreshold = Position.Instance.EdgeThreshold_Left;
vaOptions.Polarity = EdgePolaritySearchMode.Falling;
vaOptions.Width = 5;
StraightEdgeOptions vaStraightEdgeOptions = new StraightEdgeOptions();
vaStraightEdgeOptions.AngleRange = 45;
vaStraightEdgeOptions.AngleTolerance = 1;
vaStraightEdgeOptions.HoughIterations = 5;
vaStraightEdgeOptions.MinimumCoverage = 25;
vaStraightEdgeOptions.MinimumSignalToNoiseRatio = 0;
vaStraightEdgeOptions.NumberOfLines = 1;
vaStraightEdgeOptions.Orientation = 0;
Range vaRange = new Range(0, 1000);
vaStraightEdgeOptions.ScoreRange = vaRange;
vaStraightEdgeOptions.StepSize = 20;
vaStraightEdgeOptions.SearchMode = StraightEdgeSearchMode.FirstRakeEdges;
vaEdgeReport = IVA_FindEdge(image, roi2, RakeDirection.LeftToRight, vaOptions, vaStraightEdgeOptions, ivaData, 4);
roi2.Dispose();
// Creates a new, empty region of interest.
Roi roi3 = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter2 = new PointContour(1162.5, 263);
RotatedRectangleContour vaRotatedRect2 = new RotatedRectangleContour(vaCenter2, 595, 78, 0);
roi3.Add(vaRotatedRect2);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex2 = 0;
Algorithms.TransformRoi(roi3, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex2], ivaData.MeasurementSystems[coordSystemIndex2]));
// Find Straight Edge
EdgeOptions vaOptions2 = new EdgeOptions();
vaOptions2.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions2.InterpolationType = InterpolationMethod.Bilinear;
vaOptions2.KernelSize = 9;
vaOptions2.MinimumThreshold = Position.Instance.EdgeThreshold_Left;
vaOptions2.Polarity = EdgePolaritySearchMode.Falling;
vaOptions2.Width = 9;
StraightEdgeOptions vaStraightEdgeOptions2 = new StraightEdgeOptions();
vaStraightEdgeOptions2.AngleRange = 45;
vaStraightEdgeOptions2.AngleTolerance = 1;
vaStraightEdgeOptions2.HoughIterations = 5;
vaStraightEdgeOptions2.MinimumCoverage = 25;
vaStraightEdgeOptions2.MinimumSignalToNoiseRatio = 0;
vaStraightEdgeOptions2.NumberOfLines = 1;
vaStraightEdgeOptions2.Orientation = 0;
Range vaRange2 = new Range(0, 1000);
vaStraightEdgeOptions2.ScoreRange = vaRange2;
vaStraightEdgeOptions2.StepSize = 20;
vaStraightEdgeOptions2.SearchMode = StraightEdgeSearchMode.FirstRakeEdges;
vaEdgeReport2 = IVA_FindEdge(image, roi3, RakeDirection.TopToBottom, vaOptions2, vaStraightEdgeOptions2, ivaData, 5);
roi3.Dispose();
// Creates a new, empty region of interest.
Roi roi4 = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter3 = new PointContour(1530, 968.5);
RotatedRectangleContour vaRotatedRect3 = new RotatedRectangleContour(vaCenter3, 78, 1137, 0);
roi4.Add(vaRotatedRect3);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex3 = 0;
Algorithms.TransformRoi(roi4, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex3], ivaData.MeasurementSystems[coordSystemIndex3]));
// Find Straight Edge
EdgeOptions vaOptions3 = new EdgeOptions();
vaOptions3.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions3.InterpolationType = InterpolationMethod.Bilinear;
vaOptions3.KernelSize = 9;
vaOptions3.MinimumThreshold = Position.Instance.EdgeThreshold_Left;
vaOptions3.Polarity = EdgePolaritySearchMode.Falling;
vaOptions3.Width = 9;
StraightEdgeOptions vaStraightEdgeOptions3 = new StraightEdgeOptions();
vaStraightEdgeOptions3.AngleRange = 45;
vaStraightEdgeOptions3.AngleTolerance = 1;
vaStraightEdgeOptions3.HoughIterations = 5;
vaStraightEdgeOptions3.MinimumCoverage = 25;
vaStraightEdgeOptions3.MinimumSignalToNoiseRatio = 0;
vaStraightEdgeOptions3.NumberOfLines = 1;
vaStraightEdgeOptions3.Orientation = 0;
Range vaRange3 = new Range(0, 1000);
vaStraightEdgeOptions3.ScoreRange = vaRange3;
vaStraightEdgeOptions3.StepSize = 20;
vaStraightEdgeOptions3.SearchMode = StraightEdgeSearchMode.FirstRakeEdges;
vaEdgeReport3 = IVA_FindEdge(image, roi4, RakeDirection.RightToLeft, vaOptions3, vaStraightEdgeOptions3, ivaData, 6);
roi4.Dispose();
// Creates a new, empty region of interest.
Roi roi5 = new Roi();
// Creates a new RotatedRectangleContour using the given values.
PointContour vaCenter4 = new PointContour(1171.5, 1691.5);
RotatedRectangleContour vaRotatedRect4 = new RotatedRectangleContour(vaCenter4, 543, 75, 0);
roi5.Add(vaRotatedRect4);
// Reposition the region of interest based on the coordinate system.
int coordSystemIndex4 = 0;
Algorithms.TransformRoi(roi5, new CoordinateTransform(ivaData.baseCoordinateSystems[coordSystemIndex4], ivaData.MeasurementSystems[coordSystemIndex4]));
// Find Straight Edge
EdgeOptions vaOptions4 = new EdgeOptions();
vaOptions4.ColumnProcessingMode = ColumnProcessingMode.Average;
vaOptions4.InterpolationType = InterpolationMethod.Bilinear;
vaOptions4.KernelSize = 11;
vaOptions4.MinimumThreshold = Position.Instance.EdgeThreshold_Left;
vaOptions4.Polarity = EdgePolaritySearchMode.Falling;
vaOptions4.Width = 9;
StraightEdgeOptions vaStraightEdgeOptions4 = new StraightEdgeOptions();
vaStraightEdgeOptions4.AngleRange = 45;
vaStraightEdgeOptions4.AngleTolerance = 1;
vaStraightEdgeOptions4.HoughIterations = 5;
vaStraightEdgeOptions4.MinimumCoverage = 25;
vaStraightEdgeOptions4.MinimumSignalToNoiseRatio = 0;
vaStraightEdgeOptions4.NumberOfLines = 1;
vaStraightEdgeOptions4.Orientation = 0;
Range vaRange4 = new Range(0, 1000);
vaStraightEdgeOptions4.ScoreRange = vaRange4;
vaStraightEdgeOptions4.StepSize = 20;
vaStraightEdgeOptions4.SearchMode = StraightEdgeSearchMode.FirstRakeEdges;
vaEdgeReport4 = IVA_FindEdge(image, roi5, RakeDirection.BottomToTop, vaOptions4, vaStraightEdgeOptions4, ivaData, 7);
roi5.Dispose();
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 8);
// Computes the vaIntersection point between two lines.
Collection <PointContour> vaIntersection = IVA_GetIntersection(image, ivaData, 8, 5, 0, 5, 2, 6, 0, 6, 2);
caliperIntersection = vaIntersection[0];
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 9);
// Computes the vaIntersection point between two lines.
Collection <PointContour> vaIntersection2 = IVA_GetIntersection(image, ivaData, 9, 6, 0, 6, 2, 7, 0, 7, 2);
caliperIntersection2 = vaIntersection2[0];
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 10);
// Computes the vaIntersection point between two lines.
Collection <PointContour> vaIntersection3 = IVA_GetIntersection(image, ivaData, 10, 4, 0, 4, 2, 7, 0, 7, 2);
caliperIntersection3 = vaIntersection3[0];
// Caliper
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, 11);
// Computes the vaIntersection point between two lines.
Collection <PointContour> vaIntersection4 = IVA_GetIntersection(image, ivaData, 11, 4, 0, 4, 2, 5, 0, 5, 2);
caliperIntersection4 = vaIntersection4[0];
//计算每个角的偏差
string str1 = Math.Round((-caliperIntersection.X - pointoffset.X + Position.Instance.SpecLeftPos_X[0]) / 96, 3).ToString() + ";" + Math.Round((-caliperIntersection.Y - pointoffset.Y + Position.Instance.SpecLeftPos_Y[0]) / 96, 3).ToString() + ";";
string str2 = Math.Round((-caliperIntersection2.X - pointoffset.X + Position.Instance.SpecLeftPos_X[1]) / 96, 3).ToString() + ";" + Math.Round((-caliperIntersection2.Y - pointoffset.Y + Position.Instance.SpecLeftPos_Y[1]) / 96, 3).ToString() + ";";
string str3 = Math.Round((-caliperIntersection3.X - pointoffset.X + Position.Instance.SpecLeftPos_X[2]) / 96, 3).ToString() + ";" + Math.Round((-caliperIntersection3.Y - pointoffset.Y + Position.Instance.SpecLeftPos_Y[2]) / 96, 3).ToString() + ";";
string str4 = Math.Round((-caliperIntersection4.X - pointoffset.X + Position.Instance.SpecLeftPos_X[3]) / 96, 3).ToString() + ";" + Math.Round((-caliperIntersection4.Y - pointoffset.Y + Position.Instance.SpecLeftPos_Y[3]) / 96, 3).ToString();
LeftCali = str1 + str2 + str3 + str4;
LeftCaliArrary = new string[] { str1, str2, str3, str4 };
}
else
{
LeftCali = "0;0;0;0;0;0;0;0";
LeftCaliArrary = new string[] { "0;0", "0;0", "0;0", "0;0" };
}
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Gray);
}