public DoubleImage(DoubleImage image) : this(VisionLabPINVOKE.new_DoubleImage__SWIG_3(DoubleImage.getCPtr(image)), true)
{
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
}
public virtual void SnapShot(DoubleImage image)
{
VisionLabPINVOKE.Camera_Double_SnapShot__SWIG_1(swigCPtr, DoubleImage.getCPtr(image));
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
}
/// <summary>
/// Calculates eigen objects
/// </summary>
public static void CalcEigenObjects(Bitmap[] input, int maxIteration, double eps, DoubleImage[] eigVecs, double[] eigVals, DoubleImage avg)
{
if (input.Length == 0)
{
return;
}
int nObjects = input.Length;
int nEigens = nObjects - 1;
byte[][] objs = new byte[nObjects][];
double[][] eigs = new double[nEigens][];
int obj_step = 0, old_step = 0;
int eig_step = 0, oldeig_step = 0;
Size obj_size = avg.Size, old_size = avg.Size, oldeig_size = avg.Size;
for (var i = 0; i < nObjects; i++)
{
Bitmap obj = input[i];
objs[i] = obj.CopyGrayscaleBitmapToByteArray(out obj_step);
obj_size = obj.Size;
if (obj_size != avg.Size || obj_size != old_size)
{
throw new EigenObjectException("Different sizes of objects");
}
if (i > 0 && obj_step != old_step)
{
throw new EigenObjectException("Different steps of objects");
}
old_step = obj_step;
old_size = obj_size;
}
for (var i = 0; i < nEigens; i++)
{
DoubleImage eig = eigVecs[i];
eig_step = eig.Step;
eigs[i] = eig.Data;
if (eig.Size != avg.Size || eig.Size != oldeig_size)
{
throw new EigenObjectException("Different sizes of objects");
}
if (i > 0 && eig_step != oldeig_step)
{
throw new EigenObjectException("Different steps of objects");
}
oldeig_step = eig.Step;
oldeig_size = eig.Size;
}
CalcEigenObjects(nObjects, objs, obj_step,
eigs, eig_step, obj_size,
maxIteration, eps, avg.Data, avg.Step, eigVals);
}
/// <summary>
/// Calculates eigen decomposite
/// </summary>
public static double[] EigenDecomposite(Bitmap obj, DoubleImage[] eigInput, DoubleImage avg)
{
var nEigObjs = eigInput.Length;
var coeffs = new double[nEigObjs];
int i;
int obj_step;
byte[] obj_data = obj.CopyGrayscaleBitmapToByteArray(out obj_step);
Size obj_size = obj.Size;
/*cvGetImageRawData( avg, (uchar **) & avg_data, &avg_step, &avg_size );
* if( avg->depth != IPL_DEPTH_32F )
* CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
* if( avg->nChannels != 1 )
* CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );
*
* cvGetImageRawData( obj, &obj_data, &obj_step, &obj_size );
* if( obj->depth != IPL_DEPTH_8U )
* CV_ERROR( CV_BadDepth, cvUnsupportedFormat );
* if( obj->nChannels != 1 )
* CV_ERROR( CV_BadNumChannels, cvUnsupportedFormat );*/
if (obj_size != avg.Size)
{
throw new EigenObjectException("Different sizes of objects");
}
double[][] eigs = new double[nEigObjs][];
int eig_step = 0, old_step = 0;
Size eig_size = avg.Size, old_size = avg.Size;
for (i = 0; i < nEigObjs; i++)
{
DoubleImage eig = eigInput[i];
eig_step = eig.Step;
eigs[i] = eig.Data;
if (eig_size != avg.Size || eig_size != old_size)
{
throw new EigenObjectException("Different sizes of objects");
}
if (i > 0 && eig_step != old_step)
{
throw new EigenObjectException("Different steps of objects");
}
old_step = eig.Step;
old_size = eig.Size;
}
EigenDecomposite(obj_data, obj_step, nEigObjs, eigs, eig_step, avg.Data, avg.Step, obj_size, coeffs);
return(coeffs);
}
public bool GetImage(string imageName, DoubleImage image)
{
bool ret = VisionLabPINVOKE.VisLibCmdInt_GetImage__SWIG_6(swigCPtr, imageName, DoubleImage.getCPtr(image));
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public double ClassifyOutputTab(DoubleImage image, vector_ClassOutput outputTab)
{
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_ClassifyOutputTab(swigCPtr, DoubleImage.getCPtr(image), vector_ClassOutput.getCPtr(outputTab));
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public double EvaluateImage(DoubleImage image, int classExp, ref int classRes, ref double confidency, vector_double output)
{
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_EvaluateImage(swigCPtr, DoubleImage.getCPtr(image), classExp, ref classRes, ref confidency, vector_double.getCPtr(output));
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public double TrainImage(double learnRate, double momentum, DoubleImage image, int classNr)
{
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_TrainImage(swigCPtr, learnRate, momentum, DoubleImage.getCPtr(image), classNr);
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public int AddImage(string className, DoubleImage image)
{
int ret = VisionLabPINVOKE.ClassImageSet_Double_AddImage(swigCPtr, className, DoubleImage.getCPtr(image));
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public DoubleImage GetImage(int classId, int imageIndex)
{
DoubleImage ret = new DoubleImage(VisionLabPINVOKE.ClassImageSet_Double_GetImage__SWIG_1(swigCPtr, classId, imageIndex), false);
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
public int Classify(DoubleImage image, ref double confidency)
{
int ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_Classify(swigCPtr, DoubleImage.getCPtr(image), ref confidency);
if (VisionLabPINVOKE.SWIGPendingException.Pending)
{
throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
private void btn_exctract_Click(object sender, EventArgs e)
{
try
{
watermark_Extract = algorithm.KIMextract(initial_Extract, changed_Extract, sizeWatermark, sizeWatermark);
txt_status_Extract.Text = "ЦВЗ был успешно извлечен. Для просмотра его необходимо сохранить.";
btn_save_Extract.Enabled = true;
}
catch (Exception ex)
{
txt_status_Extract.Text = ex.Message;
}
}
/// <summary>
/// Calculates eigen objects
/// </summary>
public static void CalcEigenObjects(Bitmap[] input, int maxIteration, double eps, DoubleImage[] eigVecs, double[] eigVals, DoubleImage avg)
{
if (input.Length == 0)
return;
int nObjects = input.Length;
int nEigens = nObjects - 1;
byte[][] objs = new byte[nObjects][];
double[][] eigs = new double[nEigens][];
int obj_step = 0, old_step = 0;
int eig_step = 0, oldeig_step = 0;
Size obj_size = avg.Size, old_size = avg.Size, oldeig_size = avg.Size;
for (var i = 0; i < nObjects; i++)
{
Bitmap obj = input[i];
objs[i] = obj.CopyGrayscaleBitmapToByteArray(out obj_step);
obj_size = obj.Size;
if (obj_size != avg.Size || obj_size != old_size)
throw new EigenObjectException("Different sizes of objects");
if (i > 0 && obj_step != old_step)
throw new EigenObjectException("Different steps of objects");
old_step = obj_step;
old_size = obj_size;
}
for (var i = 0; i < nEigens; i++)
{
DoubleImage eig = eigVecs[i];
eig_step = eig.Step;
eigs[i] = eig.Data;
if (eig.Size != avg.Size || eig.Size != oldeig_size)
throw new EigenObjectException("Different sizes of objects");
if (i > 0 && eig_step != oldeig_step)
throw new EigenObjectException("Different steps of objects");
oldeig_step = eig.Step;
oldeig_size = eig.Size;
}
CalcEigenObjects(nObjects, objs, obj_step,
eigs, eig_step, obj_size,
maxIteration, eps, avg.Data, avg.Step, eigVals);
}
private void btn_Embed_Click(object sender, EventArgs e)
{
try
{
Stopwatch timer = new Stopwatch();
timer.Start();
changed_Embed = algorithm.KIMembed(initial_Embed, watermark_Embed);
timer.Stop();
TimeSpan secs = timer.Elapsed;
string time = string.Format("{0} секунд", secs.TotalSeconds);
txt_Status_Embed.Text = "ЦВЗ был успешно встроен. На это потребовалось " + time + ". Сохраните полученное изображение для его просмотра.";
btn_Save_Embed.Enabled = true;
}
catch (Exception ex)
{
txt_Status_Embed.Text = ex.Message;
}
}
/// <summary>
/// Caculate the eigen images for the specific traning image
/// </summary>
public static void CalcEigenObjects(Bitmap[] trainingImages, int maxIter, double eps, out DoubleImage[] eigenImages, out DoubleImage avg)
{
int width = trainingImages[0].Width;
int height = trainingImages[0].Height;
if (maxIter <= 0 || maxIter > trainingImages.Length)
maxIter = trainingImages.Length;
int maxEigenObjs = maxIter;
eigenImages = new DoubleImage[maxEigenObjs];
for (int i = 0; i < eigenImages.Length; i++)
eigenImages[i] = new DoubleImage(width, height);
avg = new DoubleImage(width, height);
EigenObjects.CalcEigenObjects(trainingImages, maxIter, eps, eigenImages, null, avg);
}
private void btn_loadChanged_Extract_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog1 = new OpenFileDialog();
openFileDialog1.Filter = "jpg files (*.jpg)|*.jpg|png files (*.png)|*.png|All files (*.*)|*.*";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
string filename = openFileDialog1.FileName;
using (Bitmap imageBitmap = new Bitmap(filename))
{
changed_Extract = new DoubleImage(imageBitmap);
}
btn_exctract.Enabled = true;
txt_status_Extract.Text = "Изображение, содержащее ЦВЗ, загружено. Теперь вы можете извлечь ЦВЗ.";
}
private void btn_LoadWM_Embed_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog1 = new OpenFileDialog();
openFileDialog1.Filter = "jpg files (*.jpg)|*.jpg|png files (*.png)|*.png|All files (*.*)|*.*";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
string filename = openFileDialog1.FileName;
using (Bitmap imageBitmap = new Bitmap(filename))
{
DoubleImage dImage = new DoubleImage(imageBitmap);
watermark_Embed = new Watermark(dImage);
}
btn_Embed.Enabled = true;
txt_Status_Embed.Text = "ЦВЗ загружен.";
}
private void btn_LoadInit_Embed_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog1 = new OpenFileDialog();
openFileDialog1.Filter = "jpg files (*.jpg)|*.jpg|png files (*.png)|*.png|All files (*.*)|*.*";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
string filename = openFileDialog1.FileName;
using (Bitmap imageBitmap = new Bitmap(filename))
{
initial_Embed = new DoubleImage(imageBitmap);
}
btn_LoadWM_Embed.Enabled = true;
btn_KnowSizeWM_Embed.Enabled = true;
btn_OptimalSizeWM_Embed.Enabled = true;
txt_Status_Embed.Text = "Изображение загружено. Вы можете проверить максимальный и оптимальный размеры ЦВЗ.";
}
/// <summary>
/// Caculate the eigen images for the specific traning image
/// </summary>
public static void CalcEigenObjects(Bitmap[] trainingImages, int maxIter, double eps, out DoubleImage[] eigenImages, out DoubleImage avg)
{
int width = trainingImages[0].Width;
int height = trainingImages[0].Height;
if (maxIter <= 0 || maxIter > trainingImages.Length)
{
maxIter = trainingImages.Length;
}
int maxEigenObjs = maxIter;
eigenImages = new DoubleImage[maxEigenObjs];
for (int i = 0; i < eigenImages.Length; i++)
{
eigenImages[i] = new DoubleImage(width, height);
}
avg = new DoubleImage(width, height);
EigenObjects.CalcEigenObjects(trainingImages, maxIter, eps, eigenImages, null, avg);
}
public static vector_HoughLine FindFastBestLines(DoubleImage src, HLParams p, double edgeMin, int nrLines, double minR, double minPhi, int minHits) {
vector_HoughLine ret = new vector_HoughLine(VisionLabPINVOKE.FindFastBestLines__SWIG_6(DoubleImage.getCPtr(src), HLParams.getCPtr(p), edgeMin, nrLines, minR, minPhi, minHits), true);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void Extract1Channel(HSV161616Image image, HSVColor plane, DoubleImage chan) {
VisionLabPINVOKE.Extract1Channel__SWIG_78(HSV161616Image.getCPtr(image), (int)plane, DoubleImage.getCPtr(chan));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void InterpolateAtSpecificPixel(DoubleImage src, DoubleImage dest, double value) {
VisionLabPINVOKE.InterpolateAtSpecificPixel__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), value);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void LoGFilter(DoubleImage image, double sigma) {
VisionLabPINVOKE.LoGFilter__SWIG_13(DoubleImage.getCPtr(image), sigma);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void CircleShape(DoubleImage image, XYCoord centre, int r, double value, ZeroOrOriginal zorg) {
VisionLabPINVOKE.CircleShape__SWIG_12(DoubleImage.getCPtr(image), XYCoord.getCPtr(centre), r, value, (int)zorg);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void DeInterlace(DoubleImage image) {
VisionLabPINVOKE.DeInterlace__SWIG_6(DoubleImage.getCPtr(image));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void FastHoughCircleT(DoubleImage src, CircleBrightness brightness, double edgeMin, double minR, double maxR, double deltaR, vector_DoubleImage destTab) {
VisionLabPINVOKE.FastHoughCircleT__SWIG_6(DoubleImage.getCPtr(src), (int)brightness, edgeMin, minR, maxR, deltaR, vector_DoubleImage.getCPtr(destTab));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void AddBorder(DoubleImage src, DoubleImage dest, int top, int left, int right, int bottom, double value) {
VisionLabPINVOKE.AddBorder__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), top, left, right, bottom, value);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public double ClassifyOutputTab(DoubleImage image, vector_ClassOutput outputTab) {
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_ClassifyOutputTab(swigCPtr, DoubleImage.getCPtr(image), vector_ClassOutput.getCPtr(outputTab));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
internal static global::System.Runtime.InteropServices.HandleRef getCPtr(DoubleImage obj)
{
return((obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.swigCPtr);
}
public double TrainImage(double learnRate, double momentum, DoubleImage image, int classNr) {
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_TrainImage(swigCPtr, learnRate, momentum, DoubleImage.getCPtr(image), classNr);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void SNN_MedianFilter(DoubleImage src, DoubleImage dest, double radius, FixEdge edge) {
VisionLabPINVOKE.SNN_MedianFilter__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), radius, (int)edge);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void NonMaximumSuppression(DoubleImage src, DoubleImage dest, DoubleImage direction, double dirScale) {
VisionLabPINVOKE.NonMaximumSuppression__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), DoubleImage.getCPtr(direction), dirScale);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void NormaliseHue(HSV888Image src, byte hue, byte minVal, byte minSat, DoubleImage dest, float notNormalised) {
VisionLabPINVOKE.NormaliseHue__SWIG_2(HSV888Image.getCPtr(src), hue, minVal, minSat, DoubleImage.getCPtr(dest), notNormalised);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static HoughCircle FindBestCircle(DoubleImage src, double minR, double maxR, double deltaR) {
HoughCircle ret = new HoughCircle(VisionLabPINVOKE.FindBestCircle__SWIG_6(DoubleImage.getCPtr(src), minR, maxR, deltaR), true);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void NormaliseHue(HSV161616Image src, short hue, short minVal, short minSat, DoubleImage dest) {
VisionLabPINVOKE.NormaliseHue__SWIG_5(HSV161616Image.getCPtr(src), hue, minVal, minSat, DoubleImage.getCPtr(dest));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
internal static HandleRef getCPtr(DoubleImage obj)
{
return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr);
}
public static void BlockPattern(DoubleImage image, XYCoord leftTop, int height, int width, double value, int repeatx, int repeaty) {
VisionLabPINVOKE.BlockPattern__SWIG_13(DoubleImage.getCPtr(image), XYCoord.getCPtr(leftTop), height, width, value, repeatx, repeaty);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
/// <summary>
/// Decompose the image as eigen values, using the specific eigen vectors
/// </summary>
public static double[] EigenDecomposite(Bitmap src, DoubleImage[] eigenImages, DoubleImage avg)
{
return(EigenObjects.EigenDecomposite(src, eigenImages, avg));
}
public static int CountPixel(DoubleImage image, double value) {
int ret = VisionLabPINVOKE.CountPixel__SWIG_6(DoubleImage.getCPtr(image), value);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void FastHoughLineT(DoubleImage src, HLParams p, double edgeMin, DoubleImage dest) {
VisionLabPINVOKE.FastHoughLineT__SWIG_6(DoubleImage.getCPtr(src), HLParams.getCPtr(p), edgeMin, DoubleImage.getCPtr(dest));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void DiskShape(DoubleImage image, XYCoord centre, double r, double value) {
VisionLabPINVOKE.DiskShape__SWIG_13(DoubleImage.getCPtr(image), XYCoord.getCPtr(centre), r, value);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static HoughLine FindFastBestLine(DoubleImage src, HLParams p, double edgeMin) {
HoughLine ret = new HoughLine(VisionLabPINVOKE.FindFastBestLine__SWIG_6(DoubleImage.getCPtr(src), HLParams.getCPtr(p), edgeMin), true);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static vector_HoughCircle FindBestCircles(DoubleImage src, double minR, double maxR, double deltaR, int nrCircles) {
vector_HoughCircle ret = new vector_HoughCircle(VisionLabPINVOKE.FindBestCircles__SWIG_26(DoubleImage.getCPtr(src), minR, maxR, deltaR, nrCircles), true);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void LocalMinFilter(DoubleImage src, DoubleImage dest, double backGround, FixEdge edge, Mask_Int32 mask) {
VisionLabPINVOKE.LocalMinFilter__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), backGround, (int)edge, Mask_Int32.getCPtr(mask));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static void VarianceFilter(DoubleImage src, DoubleImage dest, FixEdge edge, Mask_Int32 mask) {
VisionLabPINVOKE.VarianceFilter__SWIG_6(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest), (int)edge, Mask_Int32.getCPtr(mask));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public static vector_HoughCircle FindFastBestCircles(DoubleImage src, CircleBrightness brightness, double edgeMin, double minR, double maxR, double deltaR) {
vector_HoughCircle ret = new vector_HoughCircle(VisionLabPINVOKE.FindFastBestCircles__SWIG_27(DoubleImage.getCPtr(src), (int)brightness, edgeMin, minR, maxR, deltaR), true);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public int Classify(DoubleImage image, ref double confidency) {
int ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_Classify(swigCPtr, DoubleImage.getCPtr(image), ref confidency);
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void ZeroCrossings(DoubleImage src, DoubleImage dest) {
VisionLabPINVOKE.ZeroCrossings__SWIG_13(DoubleImage.getCPtr(src), DoubleImage.getCPtr(dest));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
public double EvaluateImage(DoubleImage image, int classExp, ref int classRes, ref double confidency, vector_double output) {
double ret = VisionLabPINVOKE.BPN_ImageClassifier_Double_EvaluateImage(swigCPtr, DoubleImage.getCPtr(image), classExp, ref classRes, ref confidency, vector_double.getCPtr(output));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static void HoughCircleT(DoubleImage src, double minR, double maxR, double deltaR, vector_DoubleImage destTab) {
VisionLabPINVOKE.HoughCircleT__SWIG_6(DoubleImage.getCPtr(src), minR, maxR, deltaR, vector_DoubleImage.getCPtr(destTab));
if (VisionLabPINVOKE.SWIGPendingException.Pending) throw VisionLabPINVOKE.SWIGPendingException.Retrieve();
}
