private static Collection <double> IVA_GetDistance(VisionImage image,
IVA_Data ivaData,
int stepIndex,
int stepIndex1,
int resultIndex1,
int stepIndex2,
int resultIndex2)
{
Collection <PointContour> points = new Collection <PointContour>();
points.Add(Functions.IVA_GetPoint(ivaData, stepIndex1, resultIndex1));
points.Add(Functions.IVA_GetPoint(ivaData, stepIndex2, resultIndex2));
// Computes the distance between the points.
Collection <double> distances = Algorithms.FindPointDistances(points);
// Store the results in the data structure.
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Distance (Pix.)", distances[0]));
// If the image is calibrated, compute the real world distance.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
CoordinatesReport realWorldPosition = Algorithms.ConvertPixelToRealWorldCoordinates(image, points);
Collection <double> calibratedDistance = Algorithms.FindPointDistances(realWorldPosition.Points);
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Distance (Calibrated)", calibratedDistance[0]));
distances.Add(calibratedDistance[0]);
}
return(distances);
}
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);
}
private static Collection <PointContour> IVA_SimpleEdge(VisionImage image,
Roi roi,
SimpleEdgeOptions simpleEdgeOptions,
IVA_Data ivaData,
int stepIndex)
{
// Calculates the profile of the pixels along the edge of each contour in the region of interest.
using (VisionImage monoImage = new VisionImage(ImageType.U8, 7))
{
if (image.Type == ImageType.Rgb32 || image.Type == ImageType.Hsl32)
{
Algorithms.ExtractColorPlanes(image, ColorMode.Hsl, null, null, monoImage);
}
else
{
Algorithms.Copy(image, monoImage);
}
RoiProfileReport roiProfile = Algorithms.RoiProfile(monoImage, roi);
// Finds prominent edges along the array of pixel coordinates.
Collection <PointContour> edges = Algorithms.SimpleEdge(monoImage, roiProfile.Pixels, simpleEdgeOptions);
// Store the results in the data structure.
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("# of Edges", edges.Count));
for (int i = 0; i < edges.Count; ++i)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Edge {0}.X Position (Pix.)", i + 1), edges[i].X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Edge {0}.Y Position (Pix.)", i + 1), edges[i].Y));
// If the image is calibrated, convert the pixel values to real world coordinates.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
PointContour edgeLocation = new PointContour(edges[i].X, edges[i].Y);
CoordinatesReport realWorldPosition = Algorithms.ConvertPixelToRealWorldCoordinates(image, new Collection <PointContour>(new PointContour[] { edgeLocation }));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Edge {0}.X Position (World)", i + 1), realWorldPosition.Points[0].X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Edge {0}.Y Position (World)", i + 1), realWorldPosition.Points[0].Y));
}
}
return(edges);
}
}
private static void IVA_CoordSys(int coordSysIndex,
int originStepIndex,
int originResultIndex,
int angleStepIndex,
int angleResultIndex,
double baseOriginX,
double baseOriginY,
double baseAngle,
AxisOrientation baseAxisOrientation,
int mode,
IVA_Data ivaData)
{
ivaData.baseCoordinateSystems[coordSysIndex].Origin.X = baseOriginX;
ivaData.baseCoordinateSystems[coordSysIndex].Origin.Y = baseOriginY;
ivaData.baseCoordinateSystems[coordSysIndex].Angle = baseAngle;
ivaData.baseCoordinateSystems[coordSysIndex].AxisOrientation = baseAxisOrientation;
ivaData.MeasurementSystems[coordSysIndex].Origin.X = baseOriginX;
ivaData.MeasurementSystems[coordSysIndex].Origin.Y = baseOriginY;
ivaData.MeasurementSystems[coordSysIndex].Angle = baseAngle;
ivaData.MeasurementSystems[coordSysIndex].AxisOrientation = baseAxisOrientation;
switch (mode)
{
// Horizontal motion
case 0:
ivaData.MeasurementSystems[coordSysIndex].Origin.X = Functions.IVA_GetNumericResult(ivaData, originStepIndex, originResultIndex);
break;
// Vertical motion
case 1:
ivaData.MeasurementSystems[coordSysIndex].Origin.Y = Functions.IVA_GetNumericResult(ivaData, originStepIndex, originResultIndex + 1);
break;
// Horizontal and vertical motion
case 2:
ivaData.MeasurementSystems[coordSysIndex].Origin = Functions.IVA_GetPoint(ivaData, originStepIndex, originResultIndex);
break;
// Horizontal, vertical and angular motion
case 3:
ivaData.MeasurementSystems[coordSysIndex].Origin = Functions.IVA_GetPoint(ivaData, originStepIndex, originResultIndex);
ivaData.MeasurementSystems[coordSysIndex].Angle = Functions.IVA_GetNumericResult(ivaData, angleStepIndex, angleResultIndex);
break;
}
}
private static FindEdgeReport IVA_FindEdge(VisionImage image,
Roi roi,
RakeDirection direction,
EdgeOptions options,
StraightEdgeOptions straightEdgeOptions,
IVA_Data ivaData,
int stepIndex)
{
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
// Find the Edge
FindEdgeOptions edgeOptions = new FindEdgeOptions(direction);
edgeOptions.EdgeOptions = options;
edgeOptions.StraightEdgeOptions = straightEdgeOptions;
FindEdgeReport lineReport = new FindEdgeReport();
lineReport = Algorithms.FindEdge(image, roi, edgeOptions);
// If there was at least one line, get data
if (lineReport.StraightEdges.Count >= 1)
{
// Store the results in the data structure.
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 1.X Position (Pix.)", lineReport.StraightEdges[0].StraightEdge.Start.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 1.Y Position (Pix.)", lineReport.StraightEdges[0].StraightEdge.Start.Y));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 2.X Position (Pix.)", lineReport.StraightEdges[0].StraightEdge.End.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 2.Y Position (Pix.)", lineReport.StraightEdges[0].StraightEdge.End.Y));
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 1.X Position (World)", lineReport.StraightEdges[0].CalibratedStraightEdge.Start.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 1.Y Position (World)", lineReport.StraightEdges[0].CalibratedStraightEdge.Start.Y));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 2.X Position (World)", lineReport.StraightEdges[0].CalibratedStraightEdge.End.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Point 2.Y Position (World)", lineReport.StraightEdges[0].CalibratedStraightEdge.End.Y));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Angle", lineReport.StraightEdges[0].Angle));
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Angle (World)", lineReport.StraightEdges[0].CalibratedAngle));
}
}
return(lineReport);
}
private static Collection <PointContour> IVA_GetIntersection(VisionImage image,
IVA_Data ivaData,
int stepIndex,
int stepIndex1,
int resultIndex1,
int stepIndex2,
int resultIndex2,
int stepIndex3,
int resultIndex3,
int stepIndex4,
int resultIndex4)
{
// Caliper: Lines Intersection
// Computes the intersection point between two lines.
PointContour point1 = Functions.IVA_GetPoint(ivaData, stepIndex1, resultIndex1);
PointContour point2 = Functions.IVA_GetPoint(ivaData, stepIndex2, resultIndex2);
PointContour point3 = Functions.IVA_GetPoint(ivaData, stepIndex3, resultIndex3);
PointContour point4 = Functions.IVA_GetPoint(ivaData, stepIndex4, resultIndex4);
LineContour line1 = new LineContour(point1, point2);
LineContour line2 = new LineContour(point3, point4);
Collection <PointContour> intersectionPoint = new Collection <PointContour>();
intersectionPoint.Add(Algorithms.FindIntersectionPoint(line1, line2));
// Store the results in the data structure.
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Intersection Point X Position (Pix.)", intersectionPoint[0].X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Intersection Point X Position (Pix.)", intersectionPoint[0].Y));
// If the image is calibrated, compute the real world position.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
CoordinatesReport realWorldPosition = Algorithms.ConvertPixelToRealWorldCoordinates(image, intersectionPoint);
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Intersection Point X Position (Calibrated)", realWorldPosition.Points[0].X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Intersection Point X Position (Calibrated)", realWorldPosition.Points[0].Y));
intersectionPoint.Add(realWorldPosition.Points[0]);
}
return(intersectionPoint);
}
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);
}
private static FindCircularEdgeReport IVA_FindCircularEdge(VisionImage image,
Roi roi,
SpokeDirection direction,
EdgeOptions options,
CircularEdgeFitOptions fitOptions,
IVA_Data ivaData,
int stepIndex)
{
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
FindCircularEdgeOptions circleOptions = new FindCircularEdgeOptions(direction);
circleOptions.EdgeOptions = options;
FindCircularEdgeReport circleReport = new FindCircularEdgeReport();
// Calculate the edge locations
circleReport = Algorithms.FindCircularEdge(image, roi, circleOptions, fitOptions);
// If a circle was found, add results
if (circleReport.CircleFound)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Center.X Position (Pix.)", circleReport.Center.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Center.Y Position (Pix.)", circleReport.Center.Y));
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Center.X Position (Calibrated)", circleReport.CenterCalibrated.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Center.Y Position (Calibrated)", circleReport.CenterCalibrated.Y));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Radius (Pix.)", circleReport.Radius));
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Radius (Calibrated)", circleReport.RadiusCalibrated));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Deviation", circleReport.Roundness));
}
return(circleReport);
}
private Collection <PatternMatch> IVA_MatchPattern(VisionImage image,
IVA_Data ivaData,
string templatePath,
MatchMode matchMode,
bool subpixel,
int[] angleRangeMin,
int[] angleRangeMax,
int matchesRequested,
double score,
Roi roi,
double matchOffset_x,
double matchOffset_y,
int stepIndex)
{
using (VisionImage imageTemplate = new VisionImage(ImageType.U8, 7))
{
int numObjectResults = 4;
Collection <PatternMatch> patternMatchingResults = new Collection <PatternMatch>();
CoordinatesReport realWorldPosition = new CoordinatesReport();
PointContour matchLocation = new PointContour();
// Read the image template.
imageTemplate.ReadVisionFile(templatePath);
//Algorithms.LearnPattern(imageTemplate);
// If the image is calibrated, we also need to log the calibrated position (x and y) -> 6 results instead of 4
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
numObjectResults = 6;
}
// Fill in the Pattern Matching options.
MatchPatternOptions matchPatternOptions = new MatchPatternOptions(matchMode, matchesRequested);
matchPatternOptions.MinimumContrast = 0;
matchPatternOptions.SubpixelAccuracy = subpixel;
for (int i = 0; i < 2; ++i)
{
matchPatternOptions.RotationAngleRanges.Add(new Range(angleRangeMin[i], angleRangeMax[i]));
}
matchPatternOptions.MinimumMatchScore = score;
// Searches for areas in the image that match a given pattern.
patternMatchingResults = Algorithms.MatchPattern2(image, imageTemplate, matchPatternOptions, roi);
// ////////////////////////////////////////
// Store the results in the data structure.
// ////////////////////////////////////////
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
if (patternMatchingResults.Count > 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("# of objects", patternMatchingResults.Count));
for (int i = 0; i < patternMatchingResults.Count; ++i)
{
// Adjust the match location using the specified offsets.
matchLocation.X = patternMatchingResults[i].Position.X + Functions.IVA_ComputePMOffset(matchOffset_x, matchOffset_y, patternMatchingResults[i].Rotation).X;
matchLocation.Y = patternMatchingResults[i].Position.Y + Functions.IVA_ComputePMOffset(matchOffset_x, matchOffset_y, patternMatchingResults[i].Rotation).Y;
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (Pix.)", i + 1), matchLocation.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (Pix.)", i + 1), matchLocation.Y));
// If the image is calibrated, convert the pixel values to real world coordinates.
if (numObjectResults == 6)
{
realWorldPosition = Algorithms.ConvertPixelToRealWorldCoordinates(image, new Collection <PointContour>(new PointContour[] { matchLocation }));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (World)", i + 1), realWorldPosition.Points[0].X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (World)", i + 1), realWorldPosition.Points[0].Y));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Angle (degrees)", i + 1), patternMatchingResults[i].Rotation));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Score", i + 1), patternMatchingResults[i].Score));
}
}
return(patternMatchingResults);
}
}
private static Collection <PatternMatchReport> IVA_MatchPattern(VisionImage image,
IVA_Data ivaData,
string templatePath,
MatchingAlgorithm algorithm,
float[] angleRangeMin,
float[] angleRangeMax,
int[] advOptionsItems,
double[] advOptionsValues,
int numAdvancedOptions,
int matchesRequested,
float score,
Roi roi,
int stepIndex)
{
FileInformation fileInfo;
fileInfo = Algorithms.GetFileInformation(templatePath);
using (VisionImage imageTemplate = new VisionImage(fileInfo.ImageType, 7))
{
int numObjectResults = 4;
Collection <PatternMatchReport> patternMatchingResults = new Collection <PatternMatchReport>();
// Read the image template.
imageTemplate.ReadVisionFile(templatePath);
// If the image is calibrated, we also need to log the calibrated position (x and y) and angle -> 7 results instead of 4
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
numObjectResults = 7;
}
// Set the angle range.
Collection <RotationAngleRange> angleRange = new Collection <RotationAngleRange>();
for (int i = 0; i < 2; ++i)
{
angleRange.Add(new RotationAngleRange(angleRangeMin[i], angleRangeMax[i]));
}
// Set the advanced options.
Collection <PMMatchAdvancedSetupDataOption> advancedMatchOptions = new Collection <PMMatchAdvancedSetupDataOption>();
for (int i = 0; i < numAdvancedOptions; ++i)
{
advancedMatchOptions.Add(new PMMatchAdvancedSetupDataOption((MatchSetupOption)advOptionsItems[i], advOptionsValues[i]));
}
// Searches for areas in the image that match a given pattern.
patternMatchingResults = Algorithms.MatchPattern3(image, imageTemplate, algorithm, matchesRequested, score, angleRange, roi, advancedMatchOptions);
// ////////////////////////////////////////
// Store the results in the data structure.
// ////////////////////////////////////////
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
if (patternMatchingResults.Count > 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("# of objects", patternMatchingResults.Count));
for (int i = 0; i < patternMatchingResults.Count; ++i)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (Pix.)", i + 1), patternMatchingResults[i].Position.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (Pix.)", i + 1), patternMatchingResults[i].Position.Y));
// If the image is calibrated, add the calibrated positions.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (World)", i + 1), patternMatchingResults[i].CalibratedPosition.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (World)", i + 1), patternMatchingResults[i].CalibratedPosition.Y));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Angle (degrees)", i + 1), patternMatchingResults[i].Rotation));
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Calibrated Angle (degrees)", i + 1), patternMatchingResults[i].CalibratedRotation));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Score", i + 1), patternMatchingResults[i].Score));
}
}
return(patternMatchingResults);
}
}
private static void IVA_Particle(VisionImage image,
Connectivity connectivity,
Collection <MeasurementType> pPixelMeasurements,
Collection <MeasurementType> pCalibratedMeasurements,
IVA_Data ivaData,
int stepIndex,
out ParticleMeasurementsReport partReport,
out ParticleMeasurementsReport partReportCal)
{
// Computes the requested pixel measurements.
if (pPixelMeasurements.Count != 0)
{
partReport = Algorithms.ParticleMeasurements(image, pPixelMeasurements, connectivity, ParticleMeasurementsCalibrationMode.Pixel);
}
else
{
partReport = new ParticleMeasurementsReport();
}
// Computes the requested calibrated measurements.
if (pCalibratedMeasurements.Count != 0)
{
partReportCal = Algorithms.ParticleMeasurements(image, pCalibratedMeasurements, connectivity, ParticleMeasurementsCalibrationMode.Calibrated);
}
else
{
partReportCal = new ParticleMeasurementsReport();
}
// Computes the center of mass of each particle to log as results.
ParticleMeasurementsReport centerOfMass;
Collection <MeasurementType> centerOfMassMeasurements = new Collection <MeasurementType>();
centerOfMassMeasurements.Add(MeasurementType.CenterOfMassX);
centerOfMassMeasurements.Add(MeasurementType.CenterOfMassY);
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
centerOfMass = Algorithms.ParticleMeasurements(image, centerOfMassMeasurements, connectivity, ParticleMeasurementsCalibrationMode.Both);
}
else
{
centerOfMass = Algorithms.ParticleMeasurements(image, centerOfMassMeasurements, connectivity, ParticleMeasurementsCalibrationMode.Pixel);
}
// Delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("Object #", centerOfMass.PixelMeasurements.GetLength(0)));
if (centerOfMass.PixelMeasurements.GetLength(0) > 0)
{
for (int i = 0; i < centerOfMass.PixelMeasurements.GetLength(0); ++i)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Particle {0}.X Position (Pix.)", i + 1), centerOfMass.PixelMeasurements[i, 0]));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Particle {0}.Y Position (Pix.)", i + 1), centerOfMass.PixelMeasurements[i, 1]));
// If the image is calibrated, also store the real world coordinates.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Particle {0}.X Position (Calibrated)", i + 1), centerOfMass.CalibratedMeasurements[i, 0]));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Particle {0}.Y Position (Calibrated)", i + 1), centerOfMass.CalibratedMeasurements[i, 1]));
}
}
}
}
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 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);
}
/// <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);
}
private static Collection <GeometricEdgeBasedPatternMatch> IVA_MatchGeometricPattern2(VisionImage image,
string templatePath,
CurveOptions curveOptions,
MatchGeometricPatternEdgeBasedOptions matchOptions,
IVA_Data ivaData,
int stepIndex,
Roi roi)
{
// Geometric Matching (Edge Based)
// Creates the image template.
using (VisionImage imageTemplate = new VisionImage(ImageType.U8, 7))
{
// Read the image template.
imageTemplate.ReadVisionFile(templatePath);
Collection <GeometricEdgeBasedPatternMatch> gpmResults = Algorithms.MatchGeometricPatternEdgeBased(image, imageTemplate, curveOptions, matchOptions, roi);
// Store the results in the data structure.
// First, delete all the results of this step (from a previous iteration)
Functions.IVA_DisposeStepResults(ivaData, stepIndex);
ivaData.stepResults[stepIndex].results.Add(new IVA_Result("# Matches", gpmResults.Count));
for (int i = 0; i < gpmResults.Count; ++i)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (Pix.)", i + 1), gpmResults[i].Position.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (Pix.)", i + 1), gpmResults[i].Position.Y));
// If the image is calibrated, log the calibrated results.
if ((image.InfoTypes & InfoTypes.Calibration) != 0)
{
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.X Position (World)", i + 1), gpmResults[i].CalibratedPosition.X));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Y Position (World)", i + 1), gpmResults[i].CalibratedPosition.Y));
}
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Angle (degrees)", i + 1), gpmResults[i].Rotation));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Scale", i + 1), gpmResults[i].Scale));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Score", i + 1), gpmResults[i].Score));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Occlusion", i + 1), gpmResults[i].Occlusion));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Template Target Curve Score", i + 1), gpmResults[i].TemplateMatchCurveScore));
ivaData.stepResults[stepIndex].results.Add(new IVA_Result(String.Format("Match {0}.Correlation Score", i + 1), gpmResults[i].CorrelationScore));
}
return(gpmResults);
}
}
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 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);
}