/*
public void TestCodeBookBGModel()
{
using (Capture capture = new Capture())
using (BGCodeBookModel<Bgr> model = new BGCodeBookModel<Bgr>())
{
ImageViewer viewer = new ImageViewer();
Image<Gray, byte> fgMask = capture.QueryFrame().Convert<Gray, Byte>();
Application.Idle += delegate(Object sender, EventArgs args)
{
Mat frame = capture.QueryFrame();
model.Apply(frame);
viewer.Image = model.ForegroundMask;
};
viewer.ShowDialog();
}
}
public void TestBlobTracking()
{
MCvFGDStatModelParams fgparam = new MCvFGDStatModelParams();
fgparam.alpha1 = 0.1f;
fgparam.alpha2 = 0.005f;
fgparam.alpha3 = 0.1f;
fgparam.delta = 2;
fgparam.is_obj_without_holes = 1;
fgparam.Lc = 32;
fgparam.Lcc = 16;
fgparam.minArea = 15;
fgparam.N1c = 15;
fgparam.N1cc = 25;
fgparam.N2c = 25;
fgparam.N2cc = 35;
fgparam.perform_morphing = 0;
fgparam.T = 0.9f;
BlobTrackerAutoParam<Bgr> param = new BlobTrackerAutoParam<Bgr>();
param.BlobDetector = new BlobDetector(Emgu.CV.CvEnum.BlobDetectorType.CC);
param.FGDetector = new FGDetector<Bgr>(Emgu.CV.CvEnum.ForgroundDetectorType.Fgd, fgparam);
param.BlobTracker = new BlobTracker(Emgu.CV.CvEnum.BLOBTRACKER_TYPE.MSFG);
param.FGTrainFrames = 10;
BlobTrackerAuto<Bgr> tracker = new BlobTrackerAuto<Bgr>(param);
//MCvFont font = new MCvFont(Emgu.CV.CvEnum.FontFace.HersheySimplex, 1.0, 1.0);
using(ImageViewer viewer = new ImageViewer())
using (Capture capture = new Capture())
{
capture.ImageGrabbed += delegate(object sender, EventArgs e)
{
tracker.Process(capture.RetrieveBgrFrame());
//Image<Bgr, Byte> img = capture.RetrieveBgrFrame();
Image<Bgr, Byte> img = tracker.ForegroundMask.Convert<Bgr, Byte>();
foreach (MCvBlob blob in tracker)
{
img.Draw((Rectangle)blob, new Bgr(255.0, 255.0, 255.0), 2);
img.Draw(blob.ID.ToString(), Point.Round(blob.Center), CvEnum.FontFace.HersheySimplex, 1.0, new Bgr(255.0, 255.0, 255.0));
}
viewer.Image = img;
};
capture.Start();
viewer.ShowDialog();
}
}*/
public void TestCvBlob()
{
//MCvFont font = new MCvFont(Emgu.CV.CvEnum.FontFace.HersheySimplex, 0.5, 0.5);
using (CvTracks tracks = new CvTracks())
using (ImageViewer viewer = new ImageViewer())
using (Capture capture = new Capture())
using (Mat fgMask = new Mat())
{
//BGStatModel<Bgr> bgModel = new BGStatModel<Bgr>(capture.QueryFrame(), Emgu.CV.CvEnum.BG_STAT_TYPE.GAUSSIAN_BG_MODEL);
BackgroundSubtractorMOG2 bgModel = new BackgroundSubtractorMOG2(0, 0, true);
//BackgroundSubstractorMOG bgModel = new BackgroundSubstractorMOG(0, 0, 0, 0);
capture.ImageGrabbed += delegate(object sender, EventArgs e)
{
Mat frame = new Mat();
capture.Retrieve(frame);
bgModel.Apply(frame, fgMask);
using (CvBlobDetector detector = new CvBlobDetector())
using (CvBlobs blobs = new CvBlobs())
{
detector.Detect(fgMask.ToImage<Gray, Byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
tracks.Update(blobs, 20.0, 10, 0);
Image<Bgr, Byte> result = new Image<Bgr, byte>(frame.Size);
using (Image<Gray, Byte> blobMask = detector.DrawBlobsMask(blobs))
{
frame.CopyTo(result, blobMask);
}
//CvInvoke.cvCopy(frame, result, blobMask);
foreach (KeyValuePair<uint, CvTrack> pair in tracks)
{
if (pair.Value.Inactive == 0) //only draw the active tracks.
{
CvBlob b = blobs[pair.Value.BlobLabel];
Bgr color = detector.MeanColor(b, frame.ToImage<Bgr, Byte>());
result.Draw(pair.Key.ToString(), pair.Value.BoundingBox.Location, CvEnum.FontFace.HersheySimplex, 0.5, color);
result.Draw(pair.Value.BoundingBox, color, 2);
Point[] contour = b.GetContour();
result.Draw(contour, new Bgr(0, 0, 255), 1);
}
}
viewer.Image = frame.ToImage<Bgr, Byte>().ConcateVertical(fgMask.ToImage<Bgr, Byte>().ConcateHorizontal(result));
}
};
capture.Start();
viewer.ShowDialog();
}
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Image <Bgr, Byte> smoothedFrame = new Image <Bgr, byte>(frame.Size);
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//CvInvoke.PutText(frame, blob.ID.ToString(), Point.Round(blob.Center), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
public void 評価結果画像作成_debug(Mat 検査結果, Mat テンプレート, int[,] 正解座標, ref Mat color_debug)
{
Mat res_color = new Mat(new Size(検査結果.Width, 検査結果.Height), MatType.CV_8UC3, Scalar.All(0));
var temp_color = res_color.Clone();
var result_clone = 検査結果.Clone();
paint_black(ref result_clone, テンプレート);
CvBlobs blobs = new CvBlobs(result_clone);
blobs.FilterByArea(9, 250);
blobs.RenderBlobs(result_clone, res_color);
Cv2.CvtColor(テンプレート, temp_color, ColorConversionCodes.GRAY2BGR);
Cv2.Add(temp_color, res_color, color_debug);
点数計算_debug(blobs, 正解座標, ref color_debug);
res_color = null;
temp_color = null;
blobs = null;
result_clone = null;
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width)/2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
public static void Blob_CvBlobs(int filterArea = 0)
{
Glb.DrawMatAndHist0(Glb.matSrc);
var matThr = Glb.matSrc.CvtColor(ColorConversionCodes.BGR2GRAY).Threshold(128, 255, ThresholdTypes.Otsu);
var blobs = new CvBlobs();
Glb.TimerStart();
int cnt = blobs.Label(matThr);
Console.WriteLine("=> Label Time: {0}ms", Glb.TimerStop());
blobs.FilterByArea(filterArea, int.MaxValue);
var matDsp = new Mat(Glb.matSrc.Rows, Glb.matSrc.Cols, MatType.CV_8UC3);
matDsp.SetTo(Scalar.Black);
Glb.TimerStart();
MyBlobRenderer.RenderBlobs(blobs, matDsp);
Console.WriteLine("=> Render Time: {0}ms", Glb.TimerStop());
Console.WriteLine("=> Blob Count: {0}", blobs.Count);
Glb.DrawMatAndHist1(matThr);
Glb.DrawMatAndHist2(matDsp);
matThr.Dispose();
matDsp.Dispose();
}
public int[] 点数計算(Mat 検査結果, Mat テンプレート, int[,] 正解座標)
{
int score = 0;
var result_clone = 検査結果.Clone();
paint_black(ref result_clone, テンプレート);
CvBlobs blobs = new CvBlobs(result_clone);
blobs.FilterByArea(9, 250);
int[,] 正解座標2 = (int[, ])正解座標.Clone();
int 正解数 = 0;
int 正解数 = 0;
int 許容回数 = 5;
int 未検出数 = 0;
foreach (CvBlob item in blobs.Values)
{
CvContourPolygon polygon = item.Contour.ConvertToPolygon();
Point2f circleCenter;
float circleRadius;
GetEnclosingCircle(polygon, out circleCenter, out circleRadius);
for (int j = 0; j < 正解座標2.Length / 2; j++)
{
if (正解座標2[j, 0] != 0 && (Math.Pow(circleCenter.X - 正解座標2[j, 0], 2) + Math.Pow(circleCenter.Y - 正解座標2[j, 1], 2) < circleRadius * circleRadius))
{//外接円内にあったら
正解数++;
正解座標2[j, 0] = 正解座標2[j, 1] = 0;
j = 正解座標2.Length;//ひとつ照合確定したら，このfor文を抜けて次のラベルの検査に移動
}
}
}
for (int i = 0; i < 正解座標2.Length / 2; i++)
{//検出されなかった座標が残る
if (正解座標2[i, 0] != 0)
{
未検出数++;
}
}
正解数 = blobs.Count - 正解数;
if (正解数 <= 許容回数)
{
score = (int)((float)(正解数) * (10000.0f / (正解座標.Length / 2)));
}
else
{
score = (int)((float)(正解数 - (正解数 - 許容回数)) * (10000.0f / (正解座標.Length / 2)));
}
blobs = null;
result_clone = null;
return(new int[] { score, 正解数, 未検出数 });
}
public static IEnumerable <CvBlob> DetectAndFilterBlobs(Image <Gray, byte> img, int min, int max)
{
CvBlobs blobs = new CvBlobs();
PerThreadUtils.GetBlobDetector().Detect(img, blobs);
blobs.FilterByArea(min, max);
return(blobs.Values);
}
private Rectangle GetBlueGameBoxRegion(Rectangle rcGame, Image <Gray, Byte> imgGray)
{
byte[,,] pData = imgGray.Data;
int nWid = imgGray.Width; int nHei = imgGray.Height;
for (int y = 0; y < nHei; y++)
{
for (int x = 0; x < nWid; x++)
{
if (!rcGame.Contains(x, y))
{
pData[y, x, 0] = 0;
continue;
}
byte c = pData[y, x, 0];
if (c >= 100 && c <= 120)
{
pData[y, x, 0] = 255;
}
else
{
pData[y, x, 0] = 0;
}
}
}
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(imgGray, blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
if (blobs.Count < 1)
{
return(Rectangle.Empty);
}
//-------------------------------
Rectangle rc = Rectangle.Empty;
int nSizeMax = 0;
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
if (b.BoundingBox.Width * b.BoundingBox.Height > nSizeMax)
{
rc = b.BoundingBox;
nSizeMax = rc.Width * rc.Height;
}
//break;
}
return(rc);
}
private Point centroideDeCorTime(Image <Gray, Byte> imgGray, Point individual)
{
blobDetector.Detect(imgGray, detectedBlobs);
detectedBlobs.FilterByArea(300, 99999);
blobList = detectedBlobs.Values.ToList();
time.Clear();
foreach (var blob in blobList)
{
time.Add(new Point((int)blob.Centroid.X, (int)blob.Centroid.Y));
}
detectedBlobs.Clear();
return(nearest(time, infoVtoERobo.PosicaoIndividual));
}
/// <summary>
/// Gets the largest blob
/// </summary>
/// <param name="imgSrc"></param>
/// <param name="imgRender"></param>
private void FilterByMaximumBlob(IplImage imgSrc, IplImage imgDst)
{
CvBlobs blobs = new CvBlobs();
imgDst.Zero();
blobs.Label(imgSrc);
CvBlob max = blobs.GreaterBlob();
if (max == null)
{
return;
}
blobs.FilterByArea(max.Area, max.Area);
blobs.FilterLabels(imgDst);
}
private static void FilterByMaximalBlob(IplImage imgSrc, IplImage imgDst)
{
using (CvBlobs blobs = new CvBlobs())
using (IplImage imgLabelData = new IplImage(imgSrc.Size, CvBlobLib.DepthLabel, 1))
{
imgDst.Zero();
blobs.Label(imgSrc, imgLabelData);
CvBlob max = blobs[blobs.GreaterBlob()];
if (max == null)
{
return;
}
blobs.FilterByArea(max.Area, max.Area);
blobs.FilterLabels(imgLabelData, imgDst);
}
}
public static IplImage test(IplImage target)
{
CvBlobs blobs = new CvBlobs();
IplImage lableImg = new IplImage(target.Size, CvBlobLib.DepthLabel, 1);
IplImage retImg = new IplImage(target.Size, BitDepth.U8, 1);
blobs.Label(target);
CvBlob max = blobs.GreaterBlob();
if (max == null)
{
return(target);
}
blobs.FilterByArea(max.Area, max.Area);
blobs.FilterLabels(retImg);
return(retImg);
}
private Rectangle GetBlackGameBoxRegion(Image <Gray, Byte> imgGray)
{
int nWid = imgGray.Width; int nHei = imgGray.Height;
byte[,,] pData = imgGray.Data;
for (int y = 0; y < nHei; y++)
{
for (int x = 0; x < nWid; x++)
{
byte c = pData[y, x, 0];
if (c > 5)
{
pData[y, x, 0] = 0;
}
else
{
pData[y, x, 0] = 255;
}
}
}
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(imgGray, blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
if (blobs.Count < 1)
{
return(Rectangle.Empty);
}
//-------------------------------
Rectangle rc = Rectangle.Empty;
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
rc = b.BoundingBox;
//CvInvoke.Rectangle(imgBgr, b.BoundingBox, new MCvScalar(255.0, 0, 0), 2);
break;
}
return(rc);
}
public static void CarbonPaper(int x1 = 100, int y1 = 300, int x2 = 1100, int y2 = 1600, ThresholdTypes thrType = ThresholdTypes.Binary, int thr = 128, int filterArea = 30)
{
// 1. convert to grayscale
var matGray = Glb.matSrc.CvtColor(ColorConversionCodes.BGR2GRAY);
// 2. roi crop
Rect roi = new Rect(x1, y1, x2 - x1 + 1, y2 - y1 + 1);
var matGrayDrawRoi = Glb.matSrc.Clone();
matGrayDrawRoi.Rectangle(roi, Scalar.Yellow);
Glb.DrawMat0(matGrayDrawRoi);
var matRoi = new Mat(matGray, roi);
Glb.DrawHist0(matRoi);
// 3. threshold
var matThr = matRoi.Threshold(thr, 255, thrType);
Glb.DrawMatAndHist1(matThr);
// 4. blob with area filter
CvBlobs blobs = new CvBlobs();
blobs.Label(matThr);
blobs.FilterByArea(filterArea, int.MaxValue);
// 5. display blob
var matDsp = new Mat(matRoi.Rows, matRoi.Cols, MatType.CV_8UC3);
matDsp.SetTo(Scalar.Black);
blobs.RenderBlobs(matDsp, matDsp, RenderBlobsModes.Color);
Glb.DrawMatAndHist2(matDsp);
Console.WriteLine("blobs.cnt = {0}", blobs.Count);
matGray.Dispose();
matGrayDrawRoi.Dispose();
matRoi.Dispose();
matThr.Dispose();
matDsp.Dispose();
}
public void 評価結果画像作成_debug(Mat 検査結果, Mat テンプレート, int[,] 正解座標, ref Mat color_debug)
{
Mat res_color = new Mat(new Size(検査結果.Width, 検査結果.Height), MatType.CV_8UC3, Scalar.All(0));
var temp_color = res_color.Clone();
CvBlobs blobs = new CvBlobs(検査結果);
int score = 0;
blobs.FilterByArea(Main.FilterByArea[0], Main.FilterByArea[1]);
blobs.RenderBlobs(検査結果, res_color);
Cv2.CvtColor(テンプレート, temp_color, ColorConversionCodes.GRAY2BGR);
Cv2.Add(temp_color, res_color, color_debug);
点数計算_debug(blobs, 正解座標, ref color_debug, ref score);
res_color.Dispose();
temp_color.Dispose();
blobs = null;
}
protected override void processarImagem(bool mapeamento)
{
preencherImagemPlanoDeFundo();
preencherImagemBinariaSemPlanoDeFundo();
Mat imagemCinza = ConverterParaCinzas(mImagemBinariaSemPlanoDeFundo);
if (mapeamento)
{
//Image<Bgr, byte> mCopiaMenorPlanoFundo = mCopiaImagemPlanoDeFundo.Resize(0.7, Inter.Area);
Mat mCopiaMenorPlanoFundo = new Mat();
CvInvoke.Resize(mCopiaImagemPlanoDeFundo, mCopiaMenorPlanoFundo, mCopiaImagemPlanoDeFundo.Size, 0.7, 0.7);
// Image<Gray, byte> mCopiaMenorImagemCinza = imagemCinza.Resize(0.7, Inter.Area);
// Image<Gray, byte> mCopiaMenorImagemCinza = imagemCinza.Clone();
//imagemCinza = imagemCinza.Resize(0.7, Inter.Area);
mJanelaCalibracao.PlanoDeFundo.Image = mCopiaMenorPlanoFundo;
//mJanelaCalibracao.Objetos.Image = imagemCinza;
}
//mTracker.Process(mImagemColorida, ConverterParaCinzas(mImagemBinariaSemPlanoDeFundo));
mblobs = new CvBlobs();
mBlobDetector.Detect(imagemCinza.ToImage <Gray, byte>(), mblobs);
mblobs.FilterByArea(100, int.MaxValue);
}
/// <summary>
/// Finds blobs with the specified min and max area.
/// </summary>
/// <param name="src">Source image</param>
/// <param name="minArea">The minimum allowable area</param>
/// <param name="maxArea">The maximum allowable area</param>
/// <returns>List containing the X and Y coordinates of the found blobs</returns>
public IEnumerable <PointF> FindBlobs(Bitmap src, uint minArea, uint maxArea)
{
if (src == null)
{
throw new ArgumentNullException(nameof(src), @"Source image cannot be null");
}
using (var sourceImage = new Image <Gray, byte>(src))
using (var blobDetector = new CvBlobDetector( ))
using (var blobs = new CvBlobs( ))
{
Image <Gray, byte> filteredSrc = null;
try
{
// Binarize and invert the image so that
// that blob detector can locate the dots.
filteredSrc = sourceImage.ThresholdBinaryInv(new Gray(90), new Gray(255));
// Finds all blobs in the input image and
// stores them in to the CvBlobs structure.
blobDetector.Detect(filteredSrc, blobs);
// Filter the blobs by area. The alignment dots
// have an average area of roughly 3500 pixels.
blobs.FilterByArea(( int )minArea, ( int )maxArea);
// Return the centroids of each blob.
return(blobs.Values.Select(b => new PointF(b.Centroid.X, b.Centroid.Y)));
}
finally
{
filteredSrc?.Dispose( );
}
}
}
/// <summary>
/// Filter blobs by area.
/// Those blobs whose areas are not in range will be erased from the input list of blobs. (cvFilterByArea)
/// </summary>
/// <param name="blobs">List of blobs.</param>
/// <param name="minArea">Minimun area.</param>
/// <param name="maxArea">Maximun area.</param>
public static void FilterByArea(CvBlobs blobs, int minArea, int maxArea)
{
if (blobs == null)
throw new ArgumentNullException(nameof(blobs));
blobs.FilterByArea(minArea, maxArea);
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Mat frame_crop = frame;
Image <Hsv, Byte> currenthsvFrame = (frame.ToImage <Bgr, Byte>()).Convert <Hsv, Byte>();
Image <Gray, Byte> color_one = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_two = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_three = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_four = new Image <Gray, Byte>(frame.Width, frame.Height);
/*
* Color one is Red
* Color two is Blue
* Color three is Green
* Color Four is Yellow
* Green is in Right Index Finger
* Blue is in Left Index Finger
* Red in Right Thumb
* Yelloe in Left Thumb
*/
Hsv hsv_min_color_one = new Hsv(0, 135, 110);
//Hsv hsv_max_color_one = new Hsv(6, 255, 255);
Hsv hsv_max_color_one = new Hsv(8, 255, 255);
Hsv hsv_min_color_two = new Hsv(112, 53, 10);
Hsv hsv_max_color_two = new Hsv(119, 255, 255);
/*
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);
*/
Hsv hsv_min_color_three = new Hsv(83, 109, 105);
Hsv hsv_max_color_three = new Hsv(109, 255, 255);
Hsv hsv_min_color_four = new Hsv(18, 155, 155);
Hsv hsv_max_color_four = new Hsv(35, 255, 255);
color_one = currenthsvFrame.InRange(hsv_min_color_one, hsv_max_color_one);
color_two = currenthsvFrame.InRange(hsv_min_color_two, hsv_max_color_two);
color_three = currenthsvFrame.InRange(hsv_min_color_three, hsv_max_color_three);
color_four = currenthsvFrame.InRange(hsv_min_color_four, hsv_max_color_four);
//Blob detection
#region Blob Detection
//Color one detection
Image <Bgr, Byte> smoothedFrame_cone = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_one, smoothedFrame_cone, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cone = new Mat();
fgDetector.Apply(smoothedFrame_cone, forgroundMask_cone);
CvBlobs blobs_color_one = new CvBlobs();
blobDetector.Detect(forgroundMask_cone.ToImage <Gray, byte>(), blobs_color_one);
blobs_color_one.FilterByArea(minarea, maxarea);
//Color two Blob Detection
Image <Bgr, Byte> smoothedFrame_ctwo = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_two, smoothedFrame_ctwo, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_ctwo = new Mat();
fgDetector.Apply(smoothedFrame_ctwo, forgroundMask_ctwo);
CvBlobs blobs_color_two = new CvBlobs();
blobDetector.Detect(forgroundMask_ctwo.ToImage <Gray, byte>(), blobs_color_two);
blobs_color_two.FilterByArea(minarea, maxarea);
//Color three blob detection
Image <Bgr, Byte> smoothedFrame_cthree = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_three, smoothedFrame_cthree, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cthree = new Mat();
fgDetector.Apply(smoothedFrame_cthree, forgroundMask_cthree);
CvBlobs blobs_color_three = new CvBlobs();
blobDetector.Detect(forgroundMask_cthree.ToImage <Gray, byte>(), blobs_color_three);
blobs_color_three.FilterByArea(minarea, maxarea);
//Color four detection
Image <Bgr, Byte> smoothedFrame_cfour = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_four, smoothedFrame_cfour, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cfour = new Mat();
fgDetector.Apply(smoothedFrame_cfour, forgroundMask_cfour);
CvBlobs blobs_color_four = new CvBlobs();
blobDetector.Detect(forgroundMask_cfour.ToImage <Gray, byte>(), blobs_color_four);
blobs_color_four.FilterByArea(minarea, maxarea);
//Makers Interpretition
float[] cent_color_one = new float[2];
float[] cent_color_two = new float[2];
float[] cent_color_three = new float[2];
float[] cent_color_four = new float[2];
//Centroids of Markers
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_one[0] = b.Centroid.X;
cent_color_one[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_two)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_two[0] = b.Centroid.X;
cent_color_two[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_three[0] = b.Centroid.X;
cent_color_three[1] = b.Centroid.Y;
}
foreach (var pair in blobs_color_four)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_four[0] = b.Centroid.X;
cent_color_four[1] = b.Centroid.Y;
}
#endregion
#region Calculation
int click_flag = 0;
int[] x_cor = new int[4];
int[] y_cor = new int[4];
if (blobs_color_one.Count != 0 && blobs_color_two.Count != 0 && blobs_color_three.Count != 0 && blobs_color_four.Count != 0)
{
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
foreach (var pairr in blobs_color_two)
{
CvBlob c = pairr.Value;
if ((b.Centroid.X - c.Centroid.X) * (b.Centroid.X - c.Centroid.X) + (b.Centroid.Y - c.Centroid.Y) * (b.Centroid.Y - c.Centroid.Y) <= 5000)
{
click_flag = 1;
x_cor[0] = ((int)b.Centroid.X);
x_cor[1] = ((int)c.Centroid.X);
y_cor[0] = ((int)b.Centroid.Y);
y_cor[1] = ((int)c.Centroid.Y);
break;
}
}
if (click_flag == 1)
{
break;
}
}
if (click_flag == 1)
{
click_flag = 0;
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
foreach (var pairr in blobs_color_four)
{
CvBlob c = pairr.Value;
if ((b.Centroid.X - c.Centroid.X) * (b.Centroid.X - c.Centroid.X) + (b.Centroid.Y - c.Centroid.Y) * (b.Centroid.Y - c.Centroid.Y) <= 10000)
{
click_flag = 1;
x_cor[2] = ((int)b.Centroid.X);
x_cor[3] = ((int)c.Centroid.X);
y_cor[2] = ((int)b.Centroid.Y);
y_cor[3] = ((int)c.Centroid.Y);
break;
}
}
if (click_flag == 1)
{
break;
}
}
}
}
if (click_flag == 1)
{
//MessageBox.Show("clicked");
SoundPlayer simpleSound = new SoundPlayer(@"click_sound.wav");
simpleSound.Play();
Array.Sort(x_cor);
Array.Sort(y_cor);
Bitmap ori_image = frame_crop.ToImage <Bgr, Byte>().ToBitmap();
Bitmap crop_image = new Bitmap(x_cor[2] - x_cor[1], y_cor[2] - y_cor[1]);
Graphics g = Graphics.FromImage(crop_image);
g.DrawImage(ori_image, -x_cor[1], -y_cor[1]);
//string name = string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}.jpg",DateTime.Now);
frame.Save(@"C:\Users\Shubhankar\Pictures\Camera Roll\" + string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}_original.jpg", DateTime.Now));
crop_image.Save(@"C:\Users\Shubhankar\Pictures\Camera Roll\" + string.Format("SAP_{0:ddMMyyyy_hh_mm_ss}.jpg", DateTime.Now));
Thread.Sleep(500);
}
#endregion
#region Click Gesture
#endregion
captureImageBox.Image = frame;
grayscaleImageBox.Image = color_one;
smoothedGrayscaleImageBox.Image = color_two;
cannyImageBox.Image = color_three;
Color4ImageBox.Image = color_four;
}
protected override void processarImagem(bool mapeamento)
{
preencherImagemPlanoDeFundo();
preencherImagemBinariaSemPlanoDeFundo();
Mat imagemCinza = ConverterParaCinzas(mImagemBinariaSemPlanoDeFundo);
if (mapeamento)
{
//Image<Bgr, byte> mCopiaMenorPlanoFundo = mCopiaImagemPlanoDeFundo.Resize(0.7, Inter.Area);
Mat mCopiaMenorPlanoFundo = new Mat();
CvInvoke.Resize(mCopiaImagemPlanoDeFundo, mCopiaMenorPlanoFundo, mCopiaImagemPlanoDeFundo.Size, 0.7, 0.7);
// Image<Gray, byte> mCopiaMenorImagemCinza = imagemCinza.Resize(0.7, Inter.Area);
// Image<Gray, byte> mCopiaMenorImagemCinza = imagemCinza.Clone();
//imagemCinza = imagemCinza.Resize(0.7, Inter.Area);
mJanelaCalibracao.PlanoDeFundo.Image = mCopiaMenorPlanoFundo;
//mJanelaCalibracao.Objetos.Image = imagemCinza;
}
//mTracker.Process(mImagemColorida, ConverterParaCinzas(mImagemBinariaSemPlanoDeFundo));
mblobs = new CvBlobs();
mBlobDetector.Detect(imagemCinza.ToImage<Gray, byte>(), mblobs);
mblobs.FilterByArea(100, int.MaxValue);
}
//private void CountBlobs(WriteableBitmap writableBitmap)
private void CountBlobs(WriteableBitmap writeableBitmap)
{
Mat imgIR = writeableBitmap.ToMat();// CV_16UC1
imgIR.ConvertTo(imgIR, MatType.CV_8UC1, 1.0 / 256.0);
Mat imgIRbin = new Mat(imgIR.Rows, imgIR.Cols, MatType.CV_8UC1);
Cv2.Threshold(imgIR, imgIRbin, 225, 255, ThresholdTypes.Binary);
//imgIR.SaveImage("D:/imgIR.png");
CvBlobs blobs = new CvBlobs(imgIRbin);
blobs.FilterByArea(30, 2000);
//label_sample.Content = blobs.Count().ToString();
// Canvasに追加
canvas_blob.Children.Clear();
list_arr_index.Clear();
//label_sample.Content = blobs.Count.ToString();
if (blobs.Count > 0)
{
foreach (KeyValuePair <int, CvBlob> item in blobs)
{
int labelValue = item.Key;
CvBlob blob = item.Value;
Rectangle blob_rect = new Rectangle
{
Width = blob.Rect.Width,
Height = blob.Rect.Height,
Stroke = Brushes.Red,
StrokeThickness = 2
};
canvas_blob.Children.Add(blob_rect);
Canvas.SetLeft(blob_rect, blob.Rect.Left);
Canvas.SetTop(blob_rect, blob.Rect.Top);
}
// blobsから各blobのindexを取り出す////////////////////
// blobsからLabelsに変換
LabelData labelBlobs = blobs.Labels;
// Labelsを1dデータに変換
int[] label_blobs_vector = new int[labelBlobs.Rows * labelBlobs.Cols];
int ii = 0;
//for (int i_col = 0; i_col< labelBlobs.Cols; i_col++)
for (int i_row = 0; i_row < labelBlobs.Rows; i_row++)
{
//for (int i_row = 0; i_row<labelBlobs.Rows;i_row++)
for (int i_col = 0; i_col < labelBlobs.Cols; i_col++)
{
label_blobs_vector[ii] = labelBlobs[i_row, i_col];
ii += 1;
}
}
// // Labelsからblob.Valueに一致するindexの配列を作成
// list_arr_indexに格納する
// int count_blobs = blobs.Count;
//label_sample.Content = list_arr_index.Count().ToString();
foreach (KeyValuePair <int, CvBlob> item in blobs)
{
int count_blobs = blobs.Count();
int labelvalue = item.Key;
// Labelsからlabelvalueに一致するindex配列を作成
int area_blob = item.Value.Area;//
int[] arr_idx_label = new int[area_blob];
ii = 0;
for (int i_lab = 0; i_lab < label_blobs_vector.Length; i_lab++)
{
if (label_blobs_vector[i_lab] == labelvalue)
{
arr_idx_label[ii] = i_lab;
ii += 1;
}
}
//int[] arr_idx_label = label_blobs_vector.FindIndex<int>(label => label == labelvalue);
list_arr_index.Add(arr_idx_label);
}
//label_sample.Content = list_arr_index.Count().ToString();
Console.WriteLine("hoge");//ブレイクポイント用
}
}
private void ProcessFrameMP4(object sender, EventArgs e)
{
px = new Point(px1, px2);
py = new Point(py1, py2);
if (cap != null)
{
cap.Retrieve(frame, 0);
currentframe = frame.ToImage <Bgr, byte>();
Mat mask = new Mat();
sub.Apply(currentframe, mask);
Mat kernelOp = new Mat();
Mat kernelCl = new Mat();
Mat kernelEl = new Mat();
Mat Dilate = new Mat();
kernelOp = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(3, 3), new Point(-1, -1));
kernelCl = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(11, 11), new Point(-1, -1));
var element = CvInvoke.GetStructuringElement(ElementShape.Cross, new Size(3, 3), new Point(-1, -1));
CvInvoke.GaussianBlur(mask, mask, new Size(13, 13), 1.5);
CvInvoke.MorphologyEx(mask, mask, MorphOp.Open, kernelOp, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
CvInvoke.MorphologyEx(mask, mask, MorphOp.Close, kernelCl, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
CvInvoke.Dilate(mask, mask, element, new Point(-1, -1), 1, BorderType.Reflect, default(MCvScalar));
CvInvoke.Threshold(mask, mask, 127, 255, ThresholdType.Binary);
detect.Detect(mask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(500, 20000);
tracks.Update(blobs, 20.0, 1, 10);
Image <Bgr, byte> result = new Image <Bgr, byte>(currentframe.Size);
using (Image <Gray, Byte> blobMask = detect.DrawBlobsMask(blobs))
{
frame.CopyTo(result, blobMask);
}
CvInvoke.Line(currentframe, px, py, new MCvScalar(0, 0, 255), 2);
foreach (KeyValuePair <uint, CvTrack> pair in tracks)
{
if (pair.Value.Inactive == 0) //only draw the active tracks.
{
int cx = Convert.ToInt32(pair.Value.Centroid.X);
int cy = Convert.ToInt32(pair.Value.Centroid.Y);
CvBlob b = blobs[pair.Value.BlobLabel];
Bgr color = detect.MeanColor(b, frame.ToImage <Bgr, Byte>());
result.Draw(pair.Key.ToString(), pair.Value.BoundingBox.Location, FontFace.HersheySimplex, 0.5, color);
currentframe.Draw(pair.Value.BoundingBox, new Bgr(0, 0, 255), 1);
Point[] contour = b.GetContour();
//result.Draw(contour, new Bgr(0, 0, 255), 1);
Point center = new Point(cx, cy);
CvInvoke.Circle(currentframe, center, 1, new MCvScalar(255, 0, 0), 2);
if (center.Y <= px.Y + 10 && center.Y > py.Y - 10 && center.X <= py.X && center.X > px.X)
{
if (pair.Key.ToString() != "")
{
if (!carid.Contains(pair.Key.ToString()))
{
carid.Add(pair.Key.ToString());
if (carid.Count == 20)
{
carid.Clear();
}
carcount++;
if (carcount != countBrd + 1 && carcount != countBrd + 2 && carcount != countBrd + 3 && carcount != countBrd + 4 && carcount != countBrd + 5)
{
//Json Logger
Logs log = new Logs()
{
Date = DateTime.Now.ToString(),
Id = carcount
};
string strResultJson = JsonConvert.SerializeObject(log);
File.AppendAllText(cfg.LogSavePath + @"\log.json", strResultJson + Environment.NewLine);
}
}
}
CvInvoke.Line(currentframe, px, py, new MCvScalar(0, 255, 0), 2);
}
}
}
CvInvoke.PutText(currentframe, "Count :" + carcount.ToString(), new Point(10, 25), FontFace.HersheySimplex, 1, new MCvScalar(255, 0, 255), 2, LineType.AntiAlias);
//Frame Rate
double framerate = cap.GetCaptureProperty(CapProp.Fps);
Thread.Sleep((int)(1000.0 / framerate));
if (firstCount == false && carcount == countBrd)
{
Image_Name = cfg.PhotoSavePath + @"\" + "Car" + DateTime.Now.ToString("dd-mm-yyyy-hh-mm-ss") + ".jpg";
currentframe.Save(Image_Name);
sendMail = new Thread(SendMail);
sendMail.Start();
firstCount = true;
}
if (isRecording)
{
if (firstFrameTime != null)
{
writer.WriteVideoFrame(currentframe.Bitmap, DateTime.Now - firstFrameTime.Value);
}
else
{
writer.WriteVideoFrame(currentframe.Bitmap);
firstFrameTime = DateTime.Now;
}
}
//pictureBox1.SizeMode = PictureBoxSizeMode.StretchImage;
pictureBox1.Image = currentframe.Bitmap;
}
}
static Image <Bgr, Byte> _doDetect(string fileName)
{
Debug.WriteLine($"Processing: {fileName}");
var frameOrig = new Image <Bgr, Byte>(fileName);
var frame = frameOrig.Convert <Gray, Byte>();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(19, 19), 7); //filter out noises
var smoothedImage = smoothedFrame.ToImage <Gray, Byte>();
if (_original == null)
{
_original = smoothedImage;
return(null);
}
var frameDelta = smoothedImage.AbsDiff(_original);
var thresh = frameDelta.ThresholdBinary(new Gray(25), new Gray(255));
thresh = thresh.Dilate(2);
//File.WriteAllBytes(@"C:\Temp\imagery\aathreh.jpg", thresh.ToJpegData(95));
_original = smoothedImage;
//var cnts = new VectorOfVectorOfPoint();
//CvInvoke.FindContours(thresh.Copy(), cnts, null, RetrType.External,
// ChainApproxMethod.ChainApproxSimple);
//var goer = false;
//for (var i = 0; i < cnts.Size; i++)
//{
// var c = cnts[i];
// if (CvInvoke.ContourArea(c) < 500)
// {
// continue;
// }
// goer = true;
// //Debug.WriteLine(CvInvoke.ContourArea(c));
// //var rect = CvInvoke.BoundingRectangle(c);
// //CvInvoke.Rectangle(frame, rect, new MCvScalar(255.0, 255.0, 255.0), 2);
//}
////// File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
// return goer;
//Mat forgroundMask = new Mat();
//_fgDetector.Apply(smoothedFrame, forgroundMask);
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(thresh, blobs);
blobs.FilterByArea(1600, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
//File.WriteAllBytes(@"C:\Temp\imagery\aaout.jpg", smoothedImage.ToJpegData(95));
_tracker.Update(blobs, scale, 5, 5);
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
CvInvoke.Rectangle(frameOrig, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
CvInvoke.PutText(frameOrig, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
}
// File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
// File.WriteAllBytes(@"C:\Temp\imagery\aablur.jpg", smoothedFrame.ToImage<Gray, byte>().ToJpegData(95));
return(_tracker.Count > 0 ? frameOrig : null);
//var cnts = new VectorOfVectorOfPoint();
//CvInvoke.FindContours(thresh.Copy(), cnts, null, RetrType.External,
// ChainApproxMethod.ChainApproxSimple);
//for (var i = 0; i < cnts.Size; i++)
//{
// var c = cnts[i];
// Debug.WriteLine(CvInvoke.ContourArea(c));
// var rect = CvInvoke.BoundingRectangle(c);
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//}
//Mat smoothedFrame = new Mat();
//CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(23, 23), 5); //filter out noises
////frame._SmoothGaussian(3);
//Mat forgroundMask = new Mat();
//_fgDetector.Apply(smoothedFrame, forgroundMask);
//CvBlobs blobs = new CvBlobs();
//_blobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), blobs);
//blobs.FilterByArea(100, int.MaxValue);
//float scale = (frame.Width + frame.Width) / 2.0f;
//File.WriteAllBytes(@"C:\Temp\imagery\aaout.jpg", forgroundMask.ToImage<Gray, byte>().ToJpegData(95));
//_tracker.Update(blobs, scale, 5, 5);
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
//}
//File.WriteAllBytes(@"C:\Temp\imagery\aaframes.jpg", frame.ToJpegData(95));
//File.WriteAllBytes(@"C:\Temp\imagery\aablur.jpg", smoothedFrame.ToImage<Gray, byte>().ToJpegData(95));
//Console.WriteLine($" >>>> Tracker: {_tracker.Count}, Blobs: {blobs.Count}");
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, b.Id.ToString(), new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
//}
//imageBox1.Image = frame;
//imageBox2.Image = forgroundMask;
}
// 別スレッド処理（キャプチャー）
private void worker_DoWork(object sender, DoWorkEventArgs e)
{
BackgroundWorker bw = (BackgroundWorker)sender;
Stopwatch sw = new Stopwatch();
string str;
id = 0;
//PID送信用UDP
//バインドするローカルポート番号
// FSI_PID_DATA pid_data = new FSI_PID_DATA();
int localPort = mmFsiUdpPortMT3PV;
System.Net.Sockets.UdpClient udpc2 = null;;
/* try
* {
* udpc2 = new System.Net.Sockets.UdpClient(localPort);
*
* }
* catch (Exception ex)
* {
* //匿名デリゲートで表示する
* this.Invoke(new dlgSetString(ShowRText), new object[] { richTextBox1, ex.ToString() });
* }
*/
//videoInputオブジェクト
const int DeviceID = 0; // 0; // 3 (pro), 4(piccolo) 7(DMK)
const int CaptureFps = 30; // 30
int interval = (int)(1000 / CaptureFps / 10);
const int CaptureWidth = 640;
const int CaptureHeight = 480;
// 画像保存枚数
int mmFsiPostRec = 60;
int save_counter = mmFsiPostRec;
using (VideoInput vi = new VideoInput())
{
vi.SetIdealFramerate(DeviceID, CaptureFps);
vi.SetupDevice(DeviceID, CaptureWidth, CaptureHeight);
int width = vi.GetWidth(DeviceID);
int height = vi.GetHeight(DeviceID);
using (IplImage img = new IplImage(width, height, BitDepth.U8, 3))
using (IplImage img_dark8 = Cv.LoadImage(@"C:\piccolo\MT3V_dark.bmp", LoadMode.GrayScale))
//using (IplImage img_dark = new IplImage(width, height, BitDepth.U8, 3))
using (IplImage img_mono = new IplImage(width, height, BitDepth.U8, 1))
using (IplImage img2 = new IplImage(width, height, BitDepth.U8, 1))
// using (Bitmap bitmap = new Bitmap(width, height, PixelFormat.Format24bppRgb))
using (CvFont font = new CvFont(FontFace.HersheyComplex, 0.45, 0.45))
//using (CvWindow window0 = new CvWindow("FIFO0", WindowMode.AutoSize))
{
//this.Size = new Size(width + 12, height + 148);
double min_val, max_val;
CvPoint min_loc, max_loc;
int size = 15;
int size2x = size / 2;
int size2y = size / 2;
int crop = 20;
double sigma = 3;
long elapsed0 = 0, elapsed1 = 0;
double framerate0 = 0, framerate1 = 0;
double alfa_fr = 0.99;
sw.Start();
while (bw.CancellationPending == false)
{
if (vi.IsFrameNew(DeviceID))
{
DateTime dn = DateTime.Now; //取得時刻
vi.GetPixels(DeviceID, img.ImageData, false, true);
// 画面time表示
str = String.Format("Wide ID:{0:D2} ", id) + dn.ToString("yyyyMMdd_HHmmss_fff");// +String.Format(" ({0,000:F2},{1,000:F2}) ({2,000:0},{3,000:0})({4,0:F1})", gx, gy, max_loc.X, max_loc.Y, max_val);
img.PutText(str, new CvPoint(10, 475), font, new CvColor(0, 100, 40));
Cv.CvtColor(img, img_mono, ColorConversion.BgrToGray);
Cv.Sub(img_mono, img_dark8, imgdata.img); // dark減算
imgdata.id = ++id;
imgdata.t = dn;
imgdata.ImgSaveFlag = !(ImgSaveFlag != 0); //int->bool変換
if (fifo.Count == MaxFrame - 1)
{
fifo.EraseLast();
}
fifo.InsertFirst(imgdata);
#region 位置検出1//MinMaxLoc
/*// 位置検出
* Cv.Smooth(imgdata.img, img2, SmoothType.Gaussian, size, 0, sigma, 0);
* CvRect rect;
* if (PvMode == MyDETECT)
* {
* rect = new CvRect( (int)(gx+0.5) - size, (int)(gy+0.5) - size, size*2, size*2);
* Cv.SetImageROI(img2, rect);
* Cv.MinMaxLoc(img2, out min_val, out max_val, out min_loc, out max_loc, null);
* Cv.ResetImageROI(img2);
* max_loc.X += (int)(gx + 0.5) - size; // 基準点が(1,1)のため＋１
* max_loc.Y += (int)(gy + 0.5) - size;
* }
* else
* {
* rect = new CvRect(crop, crop, width - (crop + crop), height - (crop + crop));
* Cv.SetImageROI(img2, rect);
* Cv.MinMaxLoc(img2, out min_val, out max_val, out min_loc, out max_loc, null);
* Cv.ResetImageROI(img2);
* max_loc.X += crop; // 基準点が(1,1)のため＋１
* max_loc.Y += crop;
* }
* window0.ShowImage(img2);
*
* double m00, m10, m01;
* size2x = size2y = size / 2;
* if (max_loc.X - size2x < 0) size2x = max_loc.X;
* if (max_loc.Y - size2y < 0) size2y = max_loc.Y;
* if (max_loc.X + size2x >= width ) size2x = width -max_loc.X -1;
* if (max_loc.Y + size2y >= height) size2y = height -max_loc.Y -1;
* rect = new CvRect(max_loc.X - size2x, max_loc.Y - size2y, size, size);
* CvMoments moments;
* Cv.SetImageROI(img2, rect);
* Cv.Moments(img2, out moments, false);
* Cv.ResetImageROI(img2);
* m00 = Cv.GetSpatialMoment(moments, 0, 0);
* m10 = Cv.GetSpatialMoment(moments, 1, 0);
* m01 = Cv.GetSpatialMoment(moments, 0, 1);
* gx = max_loc.X - size2x + m10 / m00;
* gy = max_loc.Y - size2y + m01 / m00;
*/
#endregion
#region 位置検出2 //Blob
Cv.Threshold(imgdata.img, img2, threshold_blob, 255, ThresholdType.Binary); //2ms
blobs.Label(img2, imgLabel); //1.4ms
max_label = blobs.GreaterBlob();
elapsed1 = sw.ElapsedTicks; //1.3ms
if (blobs.Count > 1 && gx >= 0)
{
uint min_area = (uint)(threshold_min_area * blobs[max_label].Area);
blobs.FilterByArea(min_area, uint.MaxValue); //0.001ms
// 最適blobの選定（area大 かつ 前回からの距離小）
double x = blobs[max_label].Centroid.X;
double y = blobs[max_label].Centroid.Y;
uint area = blobs[max_label].Area;
//CvRect rect;
distance_min = ((x - gx) * (x - gx) + (y - gy) * (y - gy)); //Math.Sqrt()
foreach (var item in blobs)
{
//Console.WriteLine("{0} | Centroid:{1} Area:{2}", item.Key, item.Value.Centroid, item.Value.Area);
x = item.Value.Centroid.X;
y = item.Value.Centroid.Y;
//rect = item.Value.Rect;
distance = ((x - gx) * (x - gx) + (y - gy) * (y - gy)); //将来はマハラノビス距離
if (distance < distance_min)
{
d_val = (item.Value.Area) / max_area;
if (distance <= 25) //近距離(5pix)
{
if (d_val >= 0.4) //&& d_val <= 1.2)
{
max_label = item.Key;
distance_min = distance;
}
}
else
{
if (d_val >= 0.8 && d_val <= 1.5)
{
max_label = item.Key;
distance_min = distance;
}
}
}
//w.WriteLine("{0} {1} {2} {3} {4}", dis, dv, i, item.Key, item.Value.Area);
}
//gx = x; gy = y; max_val = area;
}
if (max_label > 0)
{
maxBlob = blobs[max_label];
max_centroid = maxBlob.Centroid;
gx = max_centroid.X;
gy = max_centroid.Y;
max_area = maxBlob.Area;
if (this.States == SAVE)
{
Pid_Data_Send();
timerSavePostTime.Stop();
timerSaveMainTime.Stop();
timerSaveMainTime.Start();
}
}
else
{
gx = gy = 0;
max_area = 0;
}
#endregion
// 画面表示
str = String.Format("ID:{0:D2} ", id) + dn.ToString("yyyyMMdd_HHmmss_fff") + String.Format(" ({0,000:F2},{1,000:F2}) ({2,000:0},{3,000:0})({4,0:F1})", gx, gy, xoa, yoa, max_area);
if (imgdata.ImgSaveFlag)
{
str += " True";
}
img.PutText(str, new CvPoint(10, 20), font, new CvColor(0, 255, 100));
img.Circle(new CvPoint((int)gx, (int)gy), 10, new CvColor(255, 255, 100));
bw.ReportProgress(0, img);
// 処理速度
elapsed0 = sw.ElapsedTicks - elapsed1; // 1frameのticks
elapsed1 = sw.ElapsedTicks;
framerate0 = alfa_fr * framerate1 + (1 - alfa_fr) * (Stopwatch.Frequency / (double)elapsed0);
framerate1 = framerate0;
str = String.Format("fr time = {0}({1}){2:F1}", sw.Elapsed, id, framerate0); //," ", sw.ElapsedMilliseconds);
//匿名デリゲートで現在の時間をラベルに表示する
this.Invoke(new dlgSetString(ShowText), new object[] { textBox1, str });
//img.ToBitmap(bitmap);
//pictureBox1.Refresh();
}
Application.DoEvents();
Thread.Sleep(interval);
}
this.States = STOP;
this.Invoke(new dlgSetColor(SetColor), new object[] { ObsStart, this.States });
this.Invoke(new dlgSetColor(SetColor), new object[] { ObsEndButton, this.States });
vi.StopDevice(DeviceID);
//udpc2.Close();
}
}
}
static void Main2(string[] args)
{
CvCapture videoCaprure = null;
try
{
videoCaprure = CvCapture.FromFile(FILE_NAME);
}
catch (Exception e)
{
Console.WriteLine("Unable to open file {0}", FILE_NAME);
Console.WriteLine(e.ToString());
Console.ReadKey();
}
Cv.NamedWindow(MAIN_WINDOW_NAME, WindowMode.AutoSize);
double rate = videoCaprure.GetCaptureProperty(CvConst.CV_CAP_PROP_FPS);
int delay = (int) (1000/ rate);
IplImage previousOriginalFrame = null;
int counter = 0;
while(true)
{
var currentOgirinalFrame = videoCaprure.QueryFrame();
if (currentOgirinalFrame == null)
return;
if (previousOriginalFrame == null)
{
previousOriginalFrame = Cv.CreateImage(currentOgirinalFrame.Size, currentOgirinalFrame.Depth, currentOgirinalFrame.NChannels);
currentOgirinalFrame.Copy(previousOriginalFrame);
continue;
}
counter++;
if (counter % 3 != 0)
continue;
//algo
IplImage currentGrayImage = Cv.CreateImage(currentOgirinalFrame.Size, currentOgirinalFrame.Depth, 1);
Cv.CvtColor(currentOgirinalFrame, currentGrayImage, ColorConversion.RgbToGray);
IplImage previousGrayImage = Cv.CreateImage(previousOriginalFrame.Size, previousOriginalFrame.Depth, 1);
Cv.CvtColor(previousOriginalFrame, previousGrayImage, ColorConversion.RgbToGray);
IplImage differenceBetweenFrames = Cv.CreateImage(currentGrayImage.Size, currentGrayImage.Depth, 1);
Cv.AbsDiff(previousGrayImage, currentGrayImage, differenceBetweenFrames);
Cv.Threshold(differenceBetweenFrames, differenceBetweenFrames, 10, 255, ThresholdType.Binary);
Cv.Erode(differenceBetweenFrames, differenceBetweenFrames);
//finding blobs
CvBlobs blobs = new CvBlobs(differenceBetweenFrames);
blobs.FilterByArea(300, 10000);
//blobs.Label(differenceBetweenFrames);
var currentFrameWithRedRects = Cv.CreateImage(currentOgirinalFrame.Size, currentOgirinalFrame.Depth, currentOgirinalFrame.NChannels);
currentOgirinalFrame.Copy(currentFrameWithRedRects);
foreach (var cvBlob in blobs)
{
Cv.Rectangle(currentFrameWithRedRects, cvBlob.Value.Rect, CvColor.Red, 4);
}
Console.WriteLine(blobs.Count);
Cv.ShowImage(MAIN_WINDOW_NAME, currentFrameWithRedRects);
Cv.ShowImage("Result", differenceBetweenFrames);
Cv.WaitKey(delay * 4);
currentOgirinalFrame.Copy(previousOriginalFrame);
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Image <Hsv, Byte> currenthsvFrame = (frame.ToImage <Bgr, Byte>()).Convert <Hsv, Byte>();
Image <Gray, Byte> color_one = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_two = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_three = new Image <Gray, Byte>(frame.Width, frame.Height);
Image <Gray, Byte> color_four = new Image <Gray, Byte>(frame.Width, frame.Height);
/*
* Color one is Red
* Color two is Blue
* Color three is Green
* Color Four is Yellow
* Green is in Right Index Finger
* Blue is in Left Index Finger
* Red in Right Thumb
* Yelloe in Left Thumb
*/
/* Hsv hsv_min_color_one = new Hsv(0, 135, 110);
* Hsv hsv_max_color_one = new Hsv(6, 255, 255);
* Hsv hsv_min_color_two = new Hsv(112, 53, 10);
* Hsv hsv_max_color_two = new Hsv(119, 255, 255);
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);*/
Hsv hsv_min_color_one = new Hsv(0, 135, 50);
//Hsv hsv_max_color_one = new Hsv(6, 255, 255);
Hsv hsv_max_color_one = new Hsv(8, 255, 255);
Hsv hsv_min_color_two = new Hsv(112, 53, 10);
Hsv hsv_max_color_two = new Hsv(119, 255, 255);
/*
* Hsv hsv_min_color_three = new Hsv(68, 59, 80);
* Hsv hsv_max_color_three = new Hsv(85, 255, 255);
* Hsv hsv_min_color_four = new Hsv(20, 165, 165);
* Hsv hsv_max_color_four = new Hsv(36, 255, 255);
*/
Hsv hsv_min_color_three = new Hsv(65, 70, 0);
Hsv hsv_max_color_three = new Hsv(109, 255, 255);
Hsv hsv_min_color_four = new Hsv(18, 155, 155);
Hsv hsv_max_color_four = new Hsv(35, 255, 255);
color_one = currenthsvFrame.InRange(hsv_min_color_one, hsv_max_color_one);
color_two = currenthsvFrame.InRange(hsv_min_color_two, hsv_max_color_two);
color_three = currenthsvFrame.InRange(hsv_min_color_three, hsv_max_color_three);
color_four = currenthsvFrame.InRange(hsv_min_color_four, hsv_max_color_four);
//Blob detection
#region Blob Detection
//Color one detection
Image <Bgr, Byte> smoothedFrame_cone = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_one, smoothedFrame_cone, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cone = new Mat();
fgDetector.Apply(smoothedFrame_cone, forgroundMask_cone);
CvBlobs blobs_color_one = new CvBlobs();
blobDetector.Detect(forgroundMask_cone.ToImage <Gray, byte>(), blobs_color_one);
blobs_color_one.FilterByArea(minarea, maxarea);
//Color two Blob Detection
Image <Bgr, Byte> smoothedFrame_ctwo = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_two, smoothedFrame_ctwo, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_ctwo = new Mat();
fgDetector.Apply(smoothedFrame_ctwo, forgroundMask_ctwo);
CvBlobs blobs_color_two = new CvBlobs();
blobDetector.Detect(forgroundMask_ctwo.ToImage <Gray, byte>(), blobs_color_two);
blobs_color_two.FilterByArea(minarea, maxarea);
//Color three blob detection
Image <Bgr, Byte> smoothedFrame_cthree = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_three, smoothedFrame_cthree, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cthree = new Mat();
fgDetector.Apply(smoothedFrame_cthree, forgroundMask_cthree);
CvBlobs blobs_color_three = new CvBlobs();
blobDetector.Detect(forgroundMask_cthree.ToImage <Gray, byte>(), blobs_color_three);
blobs_color_three.FilterByArea(minarea, maxarea);
//Color four detection
Image <Bgr, Byte> smoothedFrame_cfour = new Image <Bgr, byte>(currenthsvFrame.Size);
CvInvoke.GaussianBlur(color_four, smoothedFrame_cfour, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_cfour = new Mat();
fgDetector.Apply(smoothedFrame_cfour, forgroundMask_cfour);
CvBlobs blobs_color_four = new CvBlobs();
blobDetector.Detect(forgroundMask_cfour.ToImage <Gray, byte>(), blobs_color_four);
blobs_color_four.FilterByArea(minarea, maxarea);
#endregion
//Makers Interpretition
float[] cent_color_one = new float[2];
float[] cent_color_two = new float[2];
float[] cent_color_three = new float[2];
float[] cent_color_four = new float[2];
cent_color_one[0] = 0;
cent_color_one[1] = 0;
cent_color_two[0] = 0;
cent_color_two[1] = 0;
cent_color_three[0] = green_history_x;
cent_color_three[1] = green_history_y;
cent_color_four[0] = 0;
cent_color_four[1] = 0;
//Corsor control with Green Marker
if (blobs_color_three.Count == 1 || mouseflag != 0)
{
foreach (var pair in blobs_color_three)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cursor_history_x.Enqueue((int)b.Centroid.X);
cursor_history_y.Enqueue((int)b.Centroid.Y);
cursor_history_x.Dequeue();
cursor_history_y.Dequeue();
cent_color_three[0] = (int)b.Centroid.X;
cent_color_three[1] = (int)b.Centroid.Y;
/*int temp_sum = 0;
* int[] temp = cursor_history_x.ToArray();
* for (int i = 0; i < queue_cursor_length; i++)
* temp_sum += temp[i];
* cent_color_three[0] = temp_sum / queue_cursor_length;
*
* temp_sum = 0;
* temp = cursor_history_y.ToArray();
* for (int i = 0; i < queue_cursor_length; i++)
* temp_sum += temp[i];
* cent_color_three[1] = temp_sum / queue_cursor_length;
*
* green_history_x = (int)cent_color_three[0];
* green_history_y = (int)cent_color_three[1];*/
}
//Cursor Movement Controlled
//Primary Screem
// if (Screen.AllScreens.Length == 1)
{
//Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * (int)cent_color_three[0] * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_color_three[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
Cursor.Position = new Point((int)((cursor_mul_x * (int)cent_color_three[0]) * (Screen.PrimaryScreen.Bounds.Width) / capture.Width) + cursor_add_x, (((int)cursor_mul_y * (int)cent_color_three[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height) + cursor_add_y);
//mouse_event(MOUSEEVENTF_MOVE, ( (-(int)cent_color_three[0] + green_history_x)), ( (-(int)cent_color_three[1] + green_history_y)),0,0);
//mouse_event(MOUSEEVENTF_ABSOLUTE, 0, 0, 0, 0);
}
//Secondary Screen
//Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * Screen.AllScreens[1].Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_color_three[1]) * Screen.AllScreens[1].Bounds.Height / capture.Height);
//Number of Screen = 2 and both a same time
/* if (Screen.AllScreens.Length == 2)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_color_three[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
* //Number of screen =3 and all at same time
* if (Screen.AllScreens.Length == 3)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_color_three[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width + Screen.AllScreens[2].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_color_three[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
*/
//Check for Clicks
if (blobs_color_one.Count == 1)
{
foreach (var pair in blobs_color_one)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_one[0] = b.Centroid.X;
cent_color_one[1] = b.Centroid.Y;
}
if (blobs_color_three.Count == 0)
{
if (ccount == 1)
{
//double click
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
Thread.Sleep(150);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
}
else
{
ccount--;
}
}
else if ((cent_color_one[0] - cent_color_three[0]) * (cent_color_one[0] - cent_color_three[0]) + (cent_color_one[1] - cent_color_three[1]) * (cent_color_one[1] - cent_color_three[1]) <= 5000)
{
ccount = safevalue;
mouseflag = 1;
//single click
mouse_event(MOUSEEVENTF_LEFTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_LEFTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE, 0, 0, 0, 0);
}
}
else
{
ccount = 0;
}
}
if (blobs_color_two.Count == 1)
{
foreach (var pair in blobs_color_two)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_color_two[0] = b.Centroid.X;
cent_color_two[1] = b.Centroid.Y;
}
if (blobs_color_three.Count == 1 && ((cent_color_three[0] - cent_color_two[0]) * (cent_color_three[0] - cent_color_two[0]) + (cent_color_three[1] - cent_color_two[1]) * (cent_color_three[1] - cent_color_two[1]) <= 5000))
{
//right click
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_RIGHTDOWN, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
mouse_event(MOUSEEVENTF_ABSOLUTE | MOUSEEVENTF_RIGHTUP, (uint)cent_color_three[0], (uint)cent_color_three[1], 0, 0);
}
else //if(blobs_g.Count == 0)
{
//MessageBox.Show("d");
//Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * green_history_x * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * green_history_y) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
//mouse_event(MOUSEEVENTF_VWHEEL, 0, 0, (scroll_y - (int)cent_color_two[1]) * scroll_mul_v, 0);
mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, (uint)((scroll_x - (int)cent_color_two[0]) * scroll_mul_h), 0);
mouse_event(MOUSEEVENTF_VWHEEL, (uint)Cursor.Position.X, (uint)Cursor.Position.Y, 50, 0);
//mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, 50, 0);
scroll_y = (int)cent_color_two[1];
scroll_x = (int)cent_color_two[0];
}
}
captureImageBox.Image = frame;
grayscaleImageBox.Image = color_one;
smoothedGrayscaleImageBox.Image = color_two;
cannyImageBox.Image = color_three;
Color4ImageBox.Image = color_four;
}
private void capture_ImageGrabbed(object sender, EventArgs e)
{
try
{
Mat iMat = new Mat();
capture.Retrieve(iMat);
img = iMat.ToImage <Bgr, byte>();
FrameOld = img.Clone();
Bitmap imgB = FrameOld.Bitmap;
Gray_Frame = img.Convert <Gray, Byte>().Clone();
// When enabled Equalize Hist and GammaCorrect adjust contrast and brithness
if (EqualizeHist)
{
Gray_Frame._EqualizeHist(); // Equalize Histogram
}
if (GammaCorrect)
{
Gray_Frame._GammaCorrect(valCorrectGamma); // Correct Gamma
}
if (GaussianBlure)
{
CvInvoke.GaussianBlur(Gray_Frame, Gray_Frame, new Size(3, 3), 1);
}
grayImg.Image = Gray_Frame;
faces = _face.DetectMultiScale(Gray_Frame, 1.3, 5,
new System.Drawing.Size(24, 24),
System.Drawing.Size.Empty); /**/
lblDetectedFaces.BeginInvoke((Action)(() => { // This is used to update the label of Faces detected count
int nbrFaces = faces.Length;
lblDetectedFaces.Text = nbrFaces + "";
}));
foreach (Rectangle face in faces)
{
img.Draw(face, new Bgr(System.Drawing.Color.Blue), 2);
}
// Detecting bodies
if (bodyDetection)
{
_bodies = _body.DetectMultiScale(Gray_Frame, 1.3, 5,
new System.Drawing.Size(24, 24),
System.Drawing.Size.Empty);
foreach (Rectangle body in _bodies)
{
img.Draw(body, new Bgr(System.Drawing.Color.Red), 2);
}
lblBodies.BeginInvoke((Action)(() => {// This is used to update the label of Faces detected count
lblBodies.Text = _bodies.Length + "";
}));
}
//
captureImageBox.Image = img;
// ##### Histogram
Histo.Clear();
Histo.Calculate(new Image <Gray, Byte>[] { Gray_Frame }, true, null);
Mat hMat = new Mat();
Histo.CopyTo(hMat);
myHistogram.BeginInvoke((Action)(() => {
myHistogram.ClearHistogram();
myHistogram.AddHistogram("Gray Histogram ", Color.Red, hMat, 256, new float[] { 0, 256 });
myHistogram.Refresh();
}));
//########################
//######## Fram diffrencess :detectMotionAnoramlities MoveTowards moveTowardsFilter = new MoveTowards();
if (detectMotionAnoramlities)
{
#region Contour
VectorOfVectorOfPoint polygon = new VectorOfVectorOfPoint(); // to draw the perimeter
Image <Gray, byte> gray = img.Convert <Gray, byte>(); // convert source to gray
Image <Gray, byte> thresh = gray.PyrDown().PyrUp(); // attempt to make edges more distinct?
Image <Gray, byte> cannyImg = thresh.Canny(new Gray(10).Intensity, new Gray(50).Intensity);
Mat tmpMat = new Mat();
Image <Gray, byte> imOut = new Image <Gray, byte>(img.Width, img.Height, new Gray(0));
CvInvoke.FindContours(cannyImg, polygon, tmpMat, RetrType.External, ChainApproxMethod.ChainApproxTc89Kcos);
CvInvoke.DrawContours(imOut, polygon, -1, new MCvScalar(255, 0, 0), 2);
pBoxContours.Image = imOut.Bitmap;
#endregion
Mat forgroundMask = new Mat();
fgDetector.Apply(img, forgroundMask);
pBoxBackground.Image = forgroundMask.Bitmap;
f = motionDetector.ProcessFrame(imgB);
lblDetectedMotions.BeginInvoke((Action)(() =>
{ // This is used to update the label of Faces detected count
lblDetectedMotions.Text = f + "";
}));
if (f > 0.2f)
{
txtAlerts.BeginInvoke((Action)(() =>
{ // This is used to update the label of diff %
txtAlerts.Text += "+ Quick Motion detected or more than 2% of fram changed" + DateTime.Now + Environment.NewLine;
}));
taINCIDENTS.Insert("NA", "+ Quick Motion detected or more than 2% of fram changed", "INCIDENT TYPE 1", DateTime.Now.ToString());
}
/*
*
* */
// Blob Counter
CvBlobs blobs = new CvBlobs();
blobs.FilterByArea(100, int.MaxValue);
BlobCounter blobcounter = new BlobCounter();
blobcounter.MinHeight = 100;
blobcounter.MaxWidth = 20;
blobcounter.ObjectsOrder = ObjectsOrder.Size;
blobcounter.ProcessImage(forgroundMask.Bitmap);
Rectangle[] rect = blobcounter.GetObjectsRectangles();
Graphics g = Graphics.FromImage(imgB);
int BlobCPT = 0;
if (rect.Length > 0)
{
Rectangle objec = rect[0];
Graphics graphic = Graphics.FromImage(imgB);
using (Pen pen = new Pen(Color.Red, 2))
foreach (Rectangle rec in rect)
{
if ((rec.Width > 50) && (rec.Height > 50))
{
g.DrawRectangle(pen, rec);
BlobCPT++;
}
}
{
}
g.Dispose();
}
if (f == 0.00f && blobs.Count == 0 && faces.Length == 0)
{
if (!wasInFreez && freezTriggered)
{
freezTime = 0;
wasInFreez = true;
// We suppose 0.5% and less as freez
txtAlerts.BeginInvoke((Action)(() =>
{ // This is used to update the label of Faces detected count
txtAlerts.Text += "+Freez detecte : - Time:" + DateTime.Now.ToString() + Environment.NewLine;
}));
taEVENT.Insert("+Freez detecte : - Time:", "FREEZ", DateTime.Now.ToString());
}
if (!wasInFreez && !freezTriggered && !TimerStarted)
{
TimerStarted = true;
freezTimer.Start();
}
}
else if (BlobCPT > 0 && f != 0.00f)
{
if (wasInFreez) // We need to stop the timer and send the notification message
{
txtAlerts.BeginInvoke((Action)(() =>
{ // This is used to update the label of Faces detected count
txtAlerts.Text += "+Freez Stoped after : " + freezTime + " Second - Time:" + DateTime.Now.ToString() + Environment.NewLine;
}));
taEVENT.Insert("+Freez Stoped after : " + freezTime + " Second", "FREEZ STOP", DateTime.Now.ToString());
freezTimer.Stop();
TimerStarted = false;
wasInFreez = false;
freezTriggered = false;
}
}
pBox.Image = imgB;
}
//#######################
Application.DoEvents(); // Allow app to run other threads
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = new Mat();
capture.Retrieve(frame, 0);
Mat grayFrame = new Mat();
CvInvoke.CvtColor(frame, grayFrame, ColorConversion.Bgr2Gray);
//Mat smallGrayFrame = new Mat();
//CvInvoke.PyrDown(grayFrame, smallGrayFrame);
//Mat smoothedGrayFrame = new Mat();
//CvInvoke.PyrUp(smallGrayFrame, smoothedGrayFrame);
//Image<Gray, Byte> smallGrayFrame = grayFrame.PyrDown();
//Image<Gray, Byte> smoothedGrayFrame = smallGrayFrame.PyrUp();
//Mat cannyFrame = new Mat();
//CvInvoke.Canny(smoothedGrayFrame, cannyFrame, 100, 60);
//Image<Gray, Byte> cannyFrame = smoothedGrayFrame.Canny(100, 60);
Image <Bgra, Byte> _frame = frame.ToImage <Bgra, Byte>();
Image <Gray, Byte> _grayFrame = grayFrame.ToImage <Gray, Byte>();
Image <Gray, Byte>[] rgb_frame = _frame.Split(); //components of rgb image
Image <Gray, Byte> red_com = rgb_frame[2] - _grayFrame;
var red_bi = red_com.Convert <Gray, byte>().ThresholdBinary(new Gray(redThres), new Gray(255));
Image <Gray, Byte> blue_com = rgb_frame[0] - _grayFrame;
var blue_bi = blue_com.Convert <Gray, byte>().ThresholdBinary(new Gray(blueThres), new Gray(255));
Image <Gray, Byte> green_com = rgb_frame[1] - _grayFrame;
var green_bi = green_com.Convert <Gray, byte>().ThresholdBinary(new Gray(greenThres), new Gray(255));
//System.Windows.Forms.MessageBox.Show("");
///////////////////////////////////////////////////////////////////////////////////
//Blob detection
//Red Blob detection
Image <Bgr, Byte> smoothedFrame_r = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(red_bi, smoothedFrame_r, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_r = new Mat();
fgDetector.Apply(smoothedFrame_r, forgroundMask_r);
CvBlobs blobs_r = new CvBlobs();
blobDetector.Detect(forgroundMask_r.ToImage <Gray, byte>(), blobs_r);
blobs_r.FilterByArea(minarea, maxarea);
//blue Blob Detection
Image <Bgr, Byte> smoothedFrame_b = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(blue_bi, smoothedFrame_b, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_b = new Mat();
fgDetector.Apply(smoothedFrame_b, forgroundMask_b);
CvBlobs blobs_b = new CvBlobs();
blobDetector.Detect(forgroundMask_b.ToImage <Gray, byte>(), blobs_b);
blobs_b.FilterByArea(minarea, maxarea);
//Green blob detection
Image <Bgr, Byte> smoothedFrame_g = new Image <Bgr, byte>(red_com.Size);
CvInvoke.GaussianBlur(green_bi, smoothedFrame_g, new Size(3, 3), 1); //filter out noises
Mat forgroundMask_g = new Mat();
fgDetector.Apply(smoothedFrame_g, forgroundMask_g);
CvBlobs blobs_g = new CvBlobs();
blobDetector.Detect(forgroundMask_g.ToImage <Gray, byte>(), blobs_g);
blobs_g.FilterByArea(minarea, maxarea);
//Mouse Interpretition
float[] cent_r = new float[2];
float[] cent_g = new float[2];
float[] cent_b = new float[2];
//Corsor control with Green Marker
foreach (var pair in blobs_g)
{
CvBlob b = pair.Value;
CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
cent_g[0] = b.Centroid.X;
cent_g[1] = b.Centroid.Y;
}
if (blobs_g.Count == 1 || mouseflag != 0)
{
//Cursor Movement Controlled
//Primary Screem
//if (Screen.AllScreens.Length == 1)
{
Cursor.Position = new Point(Screen.PrimaryScreen.Bounds.Width - (int)(cursor_mul * (int)cent_g[0] * Screen.PrimaryScreen.Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_g[1]) * Screen.PrimaryScreen.Bounds.Height / capture.Height);
}
//Secondary Screen
//Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * Screen.AllScreens[1].Bounds.Width / capture.Width), (int)(cursor_mul * (int)cent_g[1]) * Screen.AllScreens[1].Bounds.Height / capture.Height);
//Number of Screen = 2 and both a same time
/* if (Screen.AllScreens.Length == 2)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_g[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
* //Number of screen =3 and all at same time
* if (Screen.AllScreens.Length == 3)
* {
*
* Cursor.Position = new Point((int)(cursor_mul * (int)cent_g[0] * (Screen.AllScreens[1].Bounds.Width + Screen.AllScreens[0].Bounds.Width + Screen.AllScreens[2].Bounds.Width) / capture.Width),
* (int)(cursor_mul * (int)cent_g[1]) * (Screen.AllScreens[1].Bounds.Height + Screen.AllScreens[0].Bounds.Height + Screen.AllScreens[0].Bounds.Height) / capture.Height);
* }
*/
/*
* //Check for Clicks
* if (blobs_r.Count == 1)
* {
* if(blobs_g.Count == 0)
* {
* if(ccount == 1)
* {
* //double click
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* Thread.Sleep(150);
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
* else
* {
* ccount--;
* }
* }
*
* else if ((cent_g[0] - cent_r[0] >= 10 || cent_r[0] - cent_g[0] <= 10) && (cent_g[1] - cent_r[1] >= 10 || cent_r[1] - cent_g[1] <= 10))
* {
* ccount = safevalue;
* mouseflag = 1;
* //single click
* mouse_event(MOUSEEVENTF_LEFTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_LEFTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
* }
* else
* {
* ccount = 0;
*
* }
*
* }
*
* if (blobs_b.Count == 1)
* {
* foreach (var pair in blobs_b)
* {
* CvBlob b = pair.Value;
* CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
* cent_b[0] = b.Centroid.X;
* cent_b[1] = b.Centroid.Y;
* }
*
* if (blobs_g.Count == 1 && (cent_g[0] - cent_b[0] >= 10 || cent_b[0] - cent_g[0] <= 10) && (cent_g[1] - cent_b[1] >= 10 || cent_b[1] - cent_g[1] <= 10))
* {
* //right click
* mouse_event(MOUSEEVENTF_RIGHTDOWN, (int)cent_g[0], (int)cent_g[1], 0, 0);
* mouse_event(MOUSEEVENTF_RIGHTUP, (int)cent_g[0], (int)cent_g[1], 0, 0);
* }
*
* else if(blobs_g.Count == 0)
* {
* mouse_event(MOUSEEVENTF_VWHEEL, 0, 0, (scroll_y - (int)cent_b[1]) * scroll_mul_v, 0);
* mouse_event(MOUSEEVENTF_HWHEEL, 0, 0, (scroll_x - (int)cent_b[0]) * scroll_mul_h, 0);
* scroll_y = (int)cent_b[1];
* scroll_x = (int)cent_b[0];
*
* }
*/
}
captureImageBox.Image = frame;
grayscaleImageBox.Image = red_bi;
smoothedGrayscaleImageBox.Image = green_bi;
cannyImageBox.Image = blue_bi;
}
public CameraTrackingFindSubjectsReturnModel FindSubjects()
{
double largestW = 0;
double largestH = 0;
double centerX = 0;
double centerY = 0;
bool foundSubject = false;
Rectangle subject = new Rectangle();
// get detection 'blobs' or regions
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(this.lastMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (this.lastFrame.Width + this.lastFrame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
FrameWidth = this.lastFrame.Width;
FrameHeight = this.lastFrame.Height;
foreach (var pair in _tracker)
{
CvTrack b = pair.Value;
// limit the largest and smallest size boxes we care about.
if (b.BoundingBox.Width < (this.lastFrame.Width / this.smallestDetectionWidthSizeDivisor) ||
b.BoundingBox.Height < (this.lastFrame.Height / this.smallestDetectionHeightSizeDivisor) ||
(b.BoundingBox.Width > (this.lastFrame.Width / this.largestDetectionWidthSizeDivisor) &&
b.BoundingBox.Height > (this.lastFrame.Height / this.largestDetectionHeightSizeDivisor)))
{
continue;
}
// keep track of the largest regions as we only care to track the largest
if (b.BoundingBox.Width > largestW)
{
subject = b.BoundingBox;
largestW = b.BoundingBox.Width;
largestH = b.BoundingBox.Height;
centerX = b.Centroid.X;
centerY = b.Centroid.Y;
CvInvoke.Rectangle(
this.lastFrame,
b.BoundingBox,
new MCvScalar(
255.0,
255.0,
255.0),
20);
CvInvoke.PutText(
this.lastFrame,
b.Id.ToString(),
new Point(
(int)Math.Round(b.Centroid.X),
(int)Math.Round(b.Centroid.Y)),
FontFace.HersheyPlain,
1.0,
new MCvScalar(255.0, 255.0, 255.0));
foundSubject = true;
}
else
{
CvInvoke.Rectangle(
this.lastFrame,
b.BoundingBox,
new MCvScalar(
255.0,
255.0,
255.0),
1);
CvInvoke.PutText(
this.lastFrame,
b.Id.ToString(),
new Point(
(int)Math.Round(b.Centroid.X),
(int)Math.Round(b.Centroid.Y)),
FontFace.HersheyPlain,
1.0,
new MCvScalar(
255.0,
255.0,
255.0));
}
}
return(new CameraTrackingFindSubjectsReturnModel()
{
CenterX = centerX,
CenterY = centerY,
BoundingBox = subject,
FoundSubject = foundSubject
});
}
private void ExtractBlobAndCrop(Image <Gray, byte> skin)
{
using (MemStorage storage = new MemStorage())
{
Image <Gray, Byte> smoothedFrame = new Image <Gray, byte>(skin.Size);
CvInvoke.GaussianBlur(skin, smoothedFrame, new Size(3, 3), 1); //filter out noises
imageBoxFrameGrabber.Image = skin;
Mat forgroundMask = new Mat();
Mat ss = new Mat();
ss = skin.Mat;
//grabber.Retrieve(ss);
fgDetector.Apply(ss, forgroundMask);
//imageBox1.Image = forgroundMask;
CvBlobs blobs = new CvBlobs();
//blobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), blobs);
blobDetector.Detect(skin, blobs);
blobs.FilterByArea(30000, 150000);
CvBlob b = null;
CvBlob btemp;
int area = 0;
foreach (var pair in blobs)
{
btemp = pair.Value;
if (area < btemp.Area)
{
b = pair.Value;
area = btemp.Area;
}
}
//Crop LArgest Blob
Bitmap skin_bit = skin.ToBitmap();
//MessageBox.Show("" + area);
if (area != 0)
{
CvInvoke.Rectangle(currentFrame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
//Rectangle rec = new Rectangle(b.BoundingBox.X, b.BoundingBox.Y, b.BoundingBox.Width, b.BoundingBox.Height);
Bitmap crop_image = new Bitmap((b.BoundingBox.Width > b.BoundingBox.Height ? b.BoundingBox.Width : b.BoundingBox.Height), (b.BoundingBox.Width > b.BoundingBox.Height ? b.BoundingBox.Width : b.BoundingBox.Height));
//Bitmap crop_image = skin_bit.Clone(rec, skin_bit.PixelFormat);
Graphics g = Graphics.FromImage(crop_image);
g.DrawImage(skin_bit, -b.BoundingBox.X, -b.BoundingBox.Y);
//g.DrawImage(skin_bit, -50, -50);
croped = new Image <Gray, Byte>(crop_image).Resize(350, 350, Inter.Cubic);
croped1 = new Image <Gray, Byte>(crop_image).Resize(100, 100, Inter.Cubic);
croped2 = new Image <Gray, Byte>(crop_image).Resize(50, 50, Inter.Cubic);
int gesture_number = fow_prop.image(croped2);
label1.Text = "" + gesture_number;
imageBoxSkin.Image = croped;
crop_image.Dispose();
skin_bit.Dispose();
}
}
}
private void timer_process_Tick(object sender, EventArgs e)
{
timer_process.Enabled = false;
Bitmap bitmap = new Bitmap(Screen.PrimaryScreen.Bounds.Width, Screen.PrimaryScreen.Bounds.Height);
Graphics graphics = Graphics.FromImage(bitmap as Image);
graphics.CopyFromScreen(0, 0, 0, 0, bitmap.Size);
bitmap.Save("4.png");
long Ticks = DateTime.Now.Millisecond;
Mat mat = new Mat("4.png", Emgu.CV.CvEnum.LoadImageType.Color);
Image <Bgr, Byte> imgBgr = mat.ToImage <Bgr, Byte>();
Image <Gray, Byte> imgGray = mat.ToImage <Gray, Byte>();
int nWid = imgGray.Width; int nHei = imgGray.Height;
byte[,,] pData = imgGray.Data;
for (int y = 0; y < nHei; y++)
{
for (int x = 0; x < nWid; x++)
{
byte c = pData[y, x, 0];
if (c > 5)
{
pData[y, x, 0] = 0;
}
else
{
pData[y, x, 0] = 255;
}
}
}
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(imgGray, blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
if (blobs.Count < 1)
{
timer_process.Enabled = true;
return;
}
//-------------------------------
Rectangle rc = Rectangle.Empty;
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
rc = b.BoundingBox;
//CvInvoke.Rectangle(imgBgr, b.BoundingBox, new MCvScalar(255.0, 0, 0), 2);
break;
}
// -------Detect Blue Region ---- /
imgGray = imgBgr.Convert <Gray, Byte>();
pData = imgGray.Data;
for (int y = 0; y < nHei; y++)
{
for (int x = 0; x < nWid; x++)
{
if (!rc.Contains(x, y))
{
pData[y, x, 0] = 0;
continue;
}
byte c = pData[y, x, 0];
if (c >= 100 && c <= 120)
{
pData[y, x, 0] = 255;
}
else
{
pData[y, x, 0] = 0;
}
}
}
blobs.Clear();
_blobDetector.Detect(imgGray, blobs);
blobs.FilterByArea(100, int.MaxValue);
//_tracker.Process(smoothedFrame, forgroundMask);
if (blobs.Count < 1)
{
timer_process.Enabled = true;
return;
}
//-------------------------------
rc = Rectangle.Empty;
int nSizeMax = 0;
foreach (var pair in blobs)
{
CvBlob b = pair.Value;
if (b.BoundingBox.Width * b.BoundingBox.Height > nSizeMax)
{
rc = b.BoundingBox;
nSizeMax = rc.Width * rc.Height;
}
//break;
}
CvInvoke.Rectangle(imgBgr, rc, new MCvScalar(255, 255, 0), 2);
Global.g_rcROI = rc;
Global.DEF_MAIN_BOARD_X = 238;
Global.DEF_MAIN_BOARD_Y = 42;
Global.DEF_MAIN_BOARD_W = 570;
Global.DEF_MAIN_BOARD_H = 570;
int nGameBoardX = Global.DEF_MAIN_BOARD_X + rc.X;
int nGameBoardY = Global.DEF_MAIN_BOARD_Y + rc.Y;
Global.GetRatioCalcedValues(rc.Width, rc.Height, ref nGameBoardX, ref nGameBoardY);
Global.GetRatioCalcedValues(rc.Width, rc.Height, ref Global.DEF_MAIN_BOARD_W, ref Global.DEF_MAIN_BOARD_H);
CvInvoke.Rectangle(imgBgr, new Rectangle(nGameBoardX, nGameBoardY, Global.DEF_MAIN_BOARD_W, Global.DEF_MAIN_BOARD_H), new MCvScalar(255, 255, 0), 2);
Global.DEF_MARKS_X = 15;
Global.DEF_MARKS_Y = 204;
Global.DEF_MARKS_W = 189;
Global.DEF_MARKS_H = 69;
int nMarksX = Global.DEF_MARKS_X + rc.X;
int nMarksY = Global.DEF_MARKS_Y + rc.Y;
Global.GetRatioCalcedValues(rc.Width, rc.Height, ref nMarksX, ref nMarksY);
Global.GetRatioCalcedValues(rc.Width, rc.Height, ref Global.DEF_MARKS_W, ref Global.DEF_MARKS_H);
CvInvoke.Rectangle(imgBgr, new Rectangle(nMarksX, nMarksY, Global.DEF_MARKS_W, Global.DEF_MARKS_H), new MCvScalar(255, 255, 0), 2);
int nStepX = Global.DEF_MAIN_BOARD_W / 8;
int nStepY = Global.DEF_MAIN_BOARD_H / 8;
var rois = new List <Rectangle>(); // List of rois
var imageparts = new List <Image <Bgr, byte> >(); // List of extracted image parts
for (int i = 0; i < 8; i++)
{
for (int j = 0; j < 8; j++)
{
Rectangle roi = new Rectangle(nGameBoardX + j * nStepX, nGameBoardY + i * nStepY, Global.DEF_ITEM_W, Global.DEF_ITEM_H);
rois.Add(roi);
imgBgr.ROI = roi;
imageparts.Add(imgBgr.Copy());
}
}
imgBgr.ROI = Rectangle.Empty;
m_LstCharacter.Clear();
bool bCanProcess = true;
int k = 0, nRow = 0, nCol = 0;
foreach (Image <Bgr, Byte> img in imageparts)
{
int nCharac = (int)ImageMatcher.DetermineCharacter(img);
m_LstCharacter.Add(nCharac);
MovementDecision.g_AllocCharacters[nRow, nCol] = nCharac;
nCol++;
if (nCol >= 8)
{
nRow++; nCol = 0;
}
//if (nCharac != 0)
CvInvoke.Rectangle(imgBgr, rois[k], new MCvScalar(255, 255, 0), 2);
//CvInvoke.Rectangle(imgBgr, rois[k], cols[nCharac - 1], 2);
if (nCharac == 0)
{
bCanProcess = false;
}
k++;
}
string szLine = "";
lstBox.Items.Clear();
for (int i = 0; i < 8; i++)
{
szLine = "";
for (int j = 0; j < 8; j++)
{
szLine += "" + MovementDecision.g_AllocCharacters[i, j] + " ";
}
lstBox.Items.Add(szLine);
}
//imgBgr.Save("processed.png");
picScr.Image = imgBgr.Bitmap;
if (!bCanProcess)
{
timer_process.Enabled = true;
return;
}
MovementDecision.Process();
long Ticks2 = DateTime.Now.Millisecond;
lbProcessTime.Text = "" + (Ticks2 - Ticks);
timer_process.Enabled = true;
}
/// <summary>
/// ラベリングにより最大の面積の領域を残す
/// </summary>
/// <param name="imgSrc"></param>
/// <param name="imgRender"></param>
private void FilterByMaximalBlob(IplImage imgSrc, IplImage imgDst)
{
CvBlobs blobs = new CvBlobs();
imgDst.Zero();
blobs.Label(imgSrc);
CvBlob max = blobs.GreaterBlob();
if (max == null)
return;
blobs.FilterByArea(max.Area, max.Area);
blobs.FilterLabels(imgDst);
}
void ProcessFrame(object sender, EventArgs e)
{
Mat frame = _cameraCapture.QueryFrame();
Mat smoothedFrame = new Mat();
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(3, 3), 1); //filter out noises
//frame._SmoothGaussian(3);
#region use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
_fgDetector.Apply(smoothedFrame, forgroundMask);
#endregion
CvBlobs blobs = new CvBlobs();
_blobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), blobs);
blobs.FilterByArea(100, int.MaxValue);
float scale = (frame.Width + frame.Width) / 2.0f;
_tracker.Update(blobs, 0.01 * scale, 5, 5);
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
IImage image = (IImage)frame;//这一步是重点
faceImage = frame.Bitmap;
DetectFace.Detect(image
, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
#region 多人识别 多人识别存在较大误差率（图片库 如果高清，识别效果就是好）
//Graphics g1 = Graphics.FromImage(frame.Bitmap);
//List<FaceIdentifyModel> tempList = new List<FaceIdentifyModel>();
//foreach (Rectangle face in faces)
//{
// Image rectImage1 = ImageHelper.CaptureImage(frame.Bitmap, face);
// FaceIdentifyModel MoreIdentifyInfo = FaceAPI.FaceIdentify(rectImage1, tb_Group.Text.Trim(), 1, 1);//人脸识别 一个人的识别效果比较好
// MoreIdentifyInfo.rect = face;
// tempList.Add(MoreIdentifyInfo);
//}
//Color color_of_pen1 = Color.Gray;
//color_of_pen1 = Color.Yellow;
//Pen pen1 = new Pen(color_of_pen1, 2.0f);
//Font font1 = new Font("微软雅黑", 16, GraphicsUnit.Pixel);
//SolidBrush drawBrush1 = new SolidBrush(Color.Yellow);
//tb_Identify.Text = tempList.ToJson();
//foreach (var t in tempList)
//{
// g1.DrawRectangle(pen1, t.rect);
// if (t.result != null)
// {
// g1.DrawString(t.result[0].user_info.Replace("，", "\r\n"), font1, drawBrush1, new Point(t.rect.X + 20, t.rect.Y - 20));
// }
//}
#endregion
#region 单人识别
//单人 人脸识别 多人效果比较差
foreach (Rectangle face in faces)
{
#region 采用画图，显示自己的文本框
Graphics g = Graphics.FromImage(frame.Bitmap);
ImageModel tempImage = new ImageModel();
tempImage.Rect = face;
tempImage.Image = frame.Bitmap;
//接口查询速度差
//string faceInfo = FaceAPI.FaceDetect(ImageHelper.CaptureImage(frame.Bitmap, face));//人脸检测
Image rectImage = ImageHelper.CaptureImage(frame.Bitmap, face);
FaceIdentifyModel IdentifyInfo = FaceAPI.FaceIdentify(rectImage, tb_Group.Text.Trim(), 1, 1);//人脸识别 一个人的识别效果比较好 // tb_Result.Text = faceInfo;
tb_Identify.Text = IdentifyInfo.ToJson().ToString();
//采用画板
Color color_of_pen = Color.Gray;
color_of_pen = Color.Yellow;
Pen pen = new Pen(color_of_pen, 2.0f);
Rectangle rect = face;
g.DrawRectangle(pen, rect);
Font font = new Font("微软雅黑", 16, GraphicsUnit.Pixel);
SolidBrush drawBrush = new SolidBrush(Color.Yellow);
if (IdentifyInfo != null)
{
if (IdentifyInfo.result != null)
{
for (int i = 0; i < IdentifyInfo.result.Count; i++)
{
string faceInfo = "";
faceInfo = IdentifyInfo.result[i].user_info.Replace("，", "\r\n");
//显示用户信息
g.DrawString(faceInfo, font, drawBrush, new Point(face.X + 20, face.Y - 20));
}
}
}
//CvInvoke.Rectangle(frame, face, new MCvScalar(255.0, 255.0, 255.0), 2);
//CvInvoke.PutText(frame, faceInfo, new Point(face.X + 20, face.Y - 20), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
// 保存原始截图
//System.Drawing.Image ResourceImage = frame.Bitmap;
//ResourceImage.Save(saveDir + saveFileName);
//线程队列 保存人脸识别截图
QueueHelper.WriteImage(tempImage);
//t1 = new Thread(new ThreadStart(() =>
//{
// faceInfo = FaceAPI.FaceDetect(ImageHelper.CaptureImage(frame.Bitmap, face));
// this.Invoke(new Action(() =>
// {
// g.DrawString(faceInfo, font, drawBrush, new Point(face.X + 20, face.Y - 20));
// }));
//}));
//t1.IsBackground = true;
//t1.Start();
#endregion
}
#endregion
#region 视频调用原有的Open CV 不支持中文字
//foreach (var pair in _tracker)
//{
// CvTrack b = pair.Value;
// #region 视频中调用open CV 上直接画文本框
// CvInvoke.Rectangle(frame, b.BoundingBox, new MCvScalar(255.0, 255.0, 255.0), 2);
// CvInvoke.PutText(frame, "man,show", new Point((int)Math.Round(b.Centroid.X), (int)Math.Round(b.Centroid.Y)), FontFace.HersheyPlain, 1.0, new MCvScalar(255.0, 255.0, 255.0));
// if (b.BoundingBox.Width < 100 || b.BoundingBox.Height < 50)
// {
// continue;
// }
// #endregion
//}
#endregion
imageBox1.Image = frame;
imageBox2.Image = forgroundMask;
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = _capture.QueryFrame();
if (frame == null)
{
if (mEtapa == 1)
preencherParametrosMapeamento();
_capture.Dispose();
return;
}
mContadorDeFrames++;
if (mEtapa == 0)
{
verificarEatualizarParametrosCalibracao();
}
_capture.Retrieve(frame, 0);
Image<Bgr, Byte> smoothedFrame = new Image<Bgr, byte>(frame.Size);
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(parametros.AlphaMediaMovel, parametros.AlphaMediaMovel), parametros.AlphaMediaMovel); //filter out noises
// use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
mDetector.Apply(smoothedFrame, forgroundMask);
//CvInvoke.AbsDiff(smoothedFrame, forgroundMask.ToImage<Bgr, byte>(), vPlanoFundo);
mblobs = new CvBlobs();
mBlobDetector.Detect(forgroundMask.ToImage<Gray, byte>(), mblobs);
mblobs.FilterByArea(100, int.MaxValue);
if (mEtapa == 0)
{
mJanelaCalibracao.Imagem.Image = frame;
Mat vCopiaMenorBinaria = new Mat();
CvInvoke.Resize(forgroundMask, vCopiaMenorBinaria, new Size(0, 0), 0.7, 0.7, Inter.Area);
mJanelaCalibracao.PlanoDeFundo.Image = smoothedFrame;
mJanelaCalibracao.Objetos.Image = vCopiaMenorBinaria;
}
if (mEtapa == 1)
{
mJanelaAreaRestrita.Imagem.Image = frame;
}
if (mEtapa == 2)
{
mJanelaMonitoramento.ImagemMonitorada.Image = frame;
}
mImagemColorida = frame;
if (mEtapa == 0)
{
desenharParametroTamanhoPessoa();
desenharRetanguloPessoa();
}
if (mEtapa == 1)
{
desenharEMapear();
}
if(mEtapa == 2)
{
atualizarParametros(parametros);
desenharEprocessar();
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = _capture.QueryFrame();
if (frame == null)
{
if (mEtapa == 1)
{
preencherParametrosMapeamento();
}
_capture.Dispose();
return;
}
mContadorDeFrames++;
if (mEtapa == 0)
{
verificarEatualizarParametrosCalibracao();
}
_capture.Retrieve(frame, 0);
Image <Bgr, Byte> smoothedFrame = new Image <Bgr, byte>(frame.Size);
CvInvoke.GaussianBlur(frame, smoothedFrame, new Size(parametros.AlphaMediaMovel, parametros.AlphaMediaMovel), parametros.AlphaMediaMovel); //filter out noises
// use the BG/FG detector to find the forground mask
Mat forgroundMask = new Mat();
mDetector.Apply(smoothedFrame, forgroundMask);
//CvInvoke.AbsDiff(smoothedFrame, forgroundMask.ToImage<Bgr, byte>(), vPlanoFundo);
mblobs = new CvBlobs();
mBlobDetector.Detect(forgroundMask.ToImage <Gray, byte>(), mblobs);
mblobs.FilterByArea(100, int.MaxValue);
if (mEtapa == 0)
{
mJanelaCalibracao.Imagem.Image = frame;
Mat vCopiaMenorBinaria = new Mat();
CvInvoke.Resize(forgroundMask, vCopiaMenorBinaria, new Size(0, 0), 0.7, 0.7, Inter.Area);
mJanelaCalibracao.PlanoDeFundo.Image = smoothedFrame;
mJanelaCalibracao.Objetos.Image = vCopiaMenorBinaria;
}
if (mEtapa == 1)
{
mJanelaAreaRestrita.Imagem.Image = frame;
}
if (mEtapa == 2)
{
mJanelaMonitoramento.ImagemMonitorada.Image = frame;
}
mImagemColorida = frame;
if (mEtapa == 0)
{
desenharParametroTamanhoPessoa();
desenharRetanguloPessoa();
}
if (mEtapa == 1)
{
desenharEMapear();
}
if (mEtapa == 2)
{
atualizarParametros(parametros);
desenharEprocessar();
}
}
private void CaptureMotion()
{
try
{
float wFactor = (float)this.Width / (float)CaptureBox.Width;
float hFactor = (float)this.Height / (float)CaptureBox.Height;
CvArr array = null;
CvCapture cap = CvCapture.FromCamera(CaptureDevice.Any);
this.Invoke(new Action(() =>
{
lblLoading.Visible = false;
radioButton1.Visible = true;
radioButton2.Visible = true;
}));
while (true)
{
IplImage img = cap.QueryFrame();
if (img == null)
{
continue;
}
img.Flip(array, FlipMode.Y);
if (mode == 1)
{
string filepath = "haarcascade_frontalface_alt2.xml";
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile(filepath);
CvSeq <CvAvgComp> faces = Cv.HaarDetectObjects(img, cascade, Cv.CreateMemStorage(), 3.0, 1,
HaarDetectionType.Zero, new CvSize(70, 70),
new CvSize(500, 500));
foreach (CvAvgComp face in faces)
{
//IplImage ClonedImage = img.Clone();
//Cv.SetImageROI(ClonedImage, face.Rect);
//IplImage ThisFace = Cv.CreateImage(face.Rect.Size, ClonedImage.Depth, ClonedImage.NChannels);
//Cv.Copy(ClonedImage, ThisFace, null);
//Cv.ResetImageROI(ClonedImage);
//Bitmap FaceImage = BitmapConverter.ToBitmap(ThisFace);
//FaceImage.SetResolution(240, 180);
//CaptureBox.Image = FaceImage;
img.DrawRect(face.Rect, CvColor.Red, 3);
Bitmap FaceImage = BitmapConverter.ToBitmap(img);
FaceImage.SetResolution(240, 180);
CaptureBox.Image = FaceImage;
this.Invoke(new Action(() =>
{
LifeBox.Left = (int)(face.Rect.Left * wFactor - (float)(LifeBox.Width / 2.0) - (float)(this.Width / 2.0));
LifeBox.Top = (int)(face.Rect.Top * hFactor - (float)(LifeBox.Height / 2.0) - (float)(this.Height / 2.0));
if (LifeBox.Left > (this.Width - LifeBox.Width - 12))
{
LifeBox.Left = (this.Width - LifeBox.Width - 24);
}
if (LifeBox.Top > (this.Height - LifeBox.Height - 48))
{
LifeBox.Top = (this.Height - LifeBox.Height - 48);
}
if (LifeBox.Left < 12)
{
LifeBox.Left = 12;
}
if (LifeBox.Top < 12)
{
LifeBox.Top = 12;
}
Thread.Sleep(30);
}));
break;
}
}
else
{
int AllBlobs = 0;
CvBlobs blobs = null;
IplImage imgHSVsrc = Cv.CreateImage(Cv.GetSize(img), BitDepth.U8, 3);
IplImage imgHSVdst = Cv.CreateImage(Cv.GetSize(img), BitDepth.U8, 1);
Cv.CvtColor(img, imgHSVsrc, ColorConversion.BgrToHsv);
Cv.InRangeS(imgHSVsrc, new CvScalar(86, 80, 30), new CvScalar(115, 250, 250), imgHSVdst);
Cv.ReleaseImage(imgHSVsrc);
blobs = new CvBlobs(imgHSVdst);
blobs.FilterByArea(7000, 40000);
AllBlobs = blobs.Count;
foreach (KeyValuePair <int, CvBlob> blob in blobs)
{
CvBlob CurrentBlob = blob.Value;
CvRect BlobRect = CurrentBlob.Rect;
CvPoint Point1, Point2;
Point1.X = BlobRect.X;
Point1.Y = BlobRect.Y;
Point2.X = BlobRect.X + BlobRect.Width;
Point2.Y = BlobRect.Y + BlobRect.Height;
img.DrawRect(Point1, Point2, CvColor.LightGreen, 3, LineType.AntiAlias);
this.Invoke(new Action(() =>
{
LifeBox.Left = (int)(BlobRect.Left * wFactor - (float)(LifeBox.Width / 2.0) - (float)(this.Width / 2.0));
LifeBox.Top = (int)(BlobRect.Top * hFactor - (float)(LifeBox.Height / 2.0) - (float)(this.Height / 2.0));
if (LifeBox.Left > (this.Width - LifeBox.Width - 12))
{
LifeBox.Left = (this.Width - LifeBox.Width - 24);
}
if (LifeBox.Top > (this.Height - LifeBox.Height - 48))
{
LifeBox.Top = (this.Height - LifeBox.Height - 48);
}
if (LifeBox.Left < 12)
{
LifeBox.Left = 12;
}
if (LifeBox.Top < 12)
{
LifeBox.Top = 12;
}
Thread.Sleep(30);
}));
break;
}
Bitmap Item = BitmapConverter.ToBitmap(img);
Item.SetResolution(240, 180);
CaptureBox.Image = Item;
Bitmap HSVItem = BitmapConverter.ToBitmap(imgHSVdst);
HSVItem.SetResolution(240, 180);
HSVCaptureBox.Image = HSVItem;
Cv.ReleaseImage(imgHSVdst);
}
}
}
catch (Exception e)
{
Console.WriteLine("ERROR: " + e.Message + "DETAILS: " + e.StackTrace);
}
}
private void ProcessFrame(object sender, EventArgs e)
{
//String str = String.Format("withBall.jpg");
//originalImg = CvInvoke.Imread(str)
originalImg = capture.QueryFrame();
Image <Bgr, Byte> outputImg = originalImg.ToImage <Bgr, Byte>();
int imgWidth = originalImg.Width;
int imgHeight = originalImg.Height;
UMat grayImg = new UMat();
//Convert RBG to Gray
CvInvoke.CvtColor(originalImg, grayImg, ColorConversion.Bgr2Gray);
//use image pyr to remove noise
UMat pyrDown = new UMat();
CvInvoke.PyrDown(grayImg, pyrDown);
CvInvoke.PyrUp(pyrDown, grayImg);
UMat binaryImg = new UMat();
//Find Potiential Plate Region
CvInvoke.Threshold(grayImg, binaryImg, 200, 255, ThresholdType.BinaryInv);
Image <Gray, Byte> binaryImgG = binaryImg.ToImage <Gray, Byte>();
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
int[,] hierachy = CvInvoke.FindContourTree(binaryImgG, contours, ChainApproxMethod.ChainApproxNone);
int maxArea = 0;
int maxAreaContourIndex = 0;
for (int idx = 0; idx < contours.Size; idx++)
{
//bool isChild = isChildContour(hierachy, idx);
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
using (VectorOfPoint contour = contours[idx])
{
if ((numberOfChildren > 3))
{
if (CvInvoke.ContourArea(contour) > maxArea)
{
maxAreaContourIndex = idx;
}
}
}
}
Image <Gray, Byte> mask1 = new Image <Gray, Byte>(imgWidth, imgHeight);
CvInvoke.DrawContours(mask1, contours, maxAreaContourIndex, new MCvScalar(255), -1);
int openingFactor1 = 100;
Image <Gray, Byte> plateMask = new Image <Gray, Byte>(imgWidth, imgHeight);
plateMask = mask1.Erode(openingFactor1);
plateMask = plateMask.Dilate(openingFactor1);
CvBlobs blobs = new CvBlobs();
CvBlobDetector blob_detector = new CvBlobDetector();
//blobs.FilterByArea(10000, 1000000);
blob_detector.Detect(plateMask, blobs);
foreach (CvBlob blob in blobs.Values)
{
Rectangle r = blob.BoundingBox;
outputImg.Draw(r, new Bgr(0, 255, 255), 4);
}
Image <Gray, Byte> invBinaryImgG = binaryImg.ToImage <Gray, Byte>();
CvInvoke.BitwiseNot(invBinaryImgG, invBinaryImgG);
Image <Gray, Byte> mask3 = plateMask.Clone();
CvInvoke.BitwiseAnd(plateMask, invBinaryImgG, mask3);
blob_detector.Detect(mask3, blobs);
int patternSize = 20;
int ballSize = 60;
int tolerance = 10;
int patternHigh = patternSize + tolerance;
int patternLow = patternSize - tolerance;
int ballHigh = ballSize + tolerance * 2;
int ballLow = ballSize - tolerance * 2;
blobs.FilterByArea(patternLow * patternLow, ballHigh * ballHigh);
List <PointF> patternPoints = new List <PointF>();
PointF ballPoint = new PointF();
int numberOfPatternPointFound = 0;
foreach (CvBlob blob in blobs.Values)
{
Rectangle r = blob.BoundingBox;
if ((r.Height > patternLow) && (r.Height < patternHigh) &&
(r.Width > patternLow) && (r.Width < patternHigh))
{
outputImg.Draw(new CircleF(blob.Centroid, 2), new Bgr(0, 0, 255), 2);
patternPoints.Add(blob.Centroid);
numberOfPatternPointFound++;
}
if ((r.Height > ballLow) && (r.Height < ballHigh) &&
(r.Width > ballLow) && (r.Width < ballHigh))
{
outputImg.Draw(new CircleF(blob.Centroid, 5), new Bgr(0, 0, 255), 5);
ballPoint = blob.Centroid;
}
}
label14.Text = String.Format("{0}", numberOfPatternPointFound);
List <PointF> sortedPatternPoints = new List <PointF>();
// 1 for TopLeft - 2 for Top Right - 3 for Bottom Right - 4 for Bottom Left
List <int> pointType = new List <int>();;
PointF centerPoint = new PointF();
foreach (PointF patternPoint in patternPoints)
{
centerPoint.X += patternPoint.X;
centerPoint.Y += patternPoint.Y;
}
centerPoint.X /= numberOfPatternPointFound;
centerPoint.Y /= numberOfPatternPointFound;
x_position.Text = ballPoint.X.ToString();
y_position.Text = ballPoint.Y.ToString();
foreach (PointF patternPoint in patternPoints)
{
if ((patternPoint.X < centerPoint.X) && (patternPoint.Y < centerPoint.Y))
{
sortedPatternPoints.Add(patternPoint);
pointType.Add(1);
}
else if ((patternPoint.X > centerPoint.X) && (patternPoint.Y < centerPoint.Y))
{
sortedPatternPoints.Add(patternPoint);
pointType.Add(2);
}
else if ((patternPoint.X > centerPoint.X) && (patternPoint.Y > centerPoint.Y))
{
sortedPatternPoints.Add(patternPoint);
pointType.Add(3);
}
else if ((patternPoint.X < centerPoint.X) && (patternPoint.Y > centerPoint.Y))
{
sortedPatternPoints.Add(patternPoint);
pointType.Add(4);
}
}
int id = 0;
foreach (PointF patternPoint in sortedPatternPoints)
{
CvInvoke.PutText(outputImg,
String.Format("{0}", pointType[id++]),
new System.Drawing.Point((int)patternPoint.X, (int)patternPoint.Y),
FontFace.HersheyComplex,
1.0,
new Bgr(0, 255, 0).MCvScalar);
}
imageBox1.Image = outputImg;
}
