private void FaceDetect_Click(object sender, EventArgs e)
{
if (!sw.IsRunning)
{
sw.Reset();
sw.Start();
}
Process.Image = Image.FromFile(filepath, true);
if (bvis == false)
{
bvis = true;
}
else
{
bvis = false;
}
GridOn.GridPaint(bvis, (Bitmap)Process.Image);//绘制网格线
label3.Text = "网络线划分";
try {
Bitmap gray_img = Knowledge.ToGray(originalimg); //将原图转化为灰度图
Bitmap BW = Knowledge.Thresholding(gray_img); //利用大津法进行二值化处理
Bitmap detectimg = Knowledge.FaceDetection(BW); //最后利用算法进行检测
AForge.Imaging.BlobCounter blobCounter = new AForge.Imaging.BlobCounter(detectimg);
Rectangle[] rects = blobCounter.GetObjectsRectangles();
Rectangle[] outputrects = new Rectangle[rects.Count()];
////object count
int minx = 100; int tmp = 0;
int rectsCount = rects.Count();
List <decimal> test = new List <decimal>();
for (int c = 0; c < rectsCount; c++)
{
int p = rects[c].Width * rects[c].Height;
decimal bl = (decimal)rects[c].Height / (decimal)rects[c].Width;
int maxx = (gray_img.Width * gray_img.Height) / 2;
if (p > minx && (double)bl < 1.8 && (double)bl > 0.8 && p < maxx)
{
test.Add(bl);
outputrects[tmp++] = rects[c];
}
}
RectanglesMarker marker = new RectanglesMarker(outputrects, Color.Red);
this.Detected.Image = marker.Apply((Bitmap)Image.FromFile(filepath, true));
label4.Text = "检测结果";
ShowMsg("检测结束！");
}
catch (ArgumentException)
{
MessageBox.Show("Invalid usage!");
}
if (sw.IsRunning)
{
sw.Stop();
string str = sw.Elapsed.ToString();
timeElpse.Text = string.Empty;
timeElpse.Text = "运行时间：" + str;
}
}
private Bitmap FacePicDetect(Bitmap bitmap)
{
lock (this)
{
//留存原始的照片，如果正在拍照，则保存此未添加人脸识别框的照片
currentPicture = (Bitmap)bitmap.Clone();
if (detector == null)
{
//先实例化用于检测人脸的对象detector
detector = new HaarObjectDetector(new FaceHaarCascade(), 100)
{
SearchMode = ObjectDetectorSearchMode.Single, //搜索模式
ScalingMode = ObjectDetectorScalingMode.GreaterToSmaller, //缩放模式
ScalingFactor = 1.5f, //在搜索期间重新缩放搜索窗口时要使用的重新缩放因子
UseParallelProcessing = true
}; //面部级联对象 + 搜索对象时使用的最小窗口大小
}
// 开始对检测区域进行检测并返回结果数组
Rectangle[] regions = detector.ProcessFrame(bitmap);
if (regions != null && regions.Length > 0)
{
//人脸标记
RectanglesMarker marker = new RectanglesMarker(regions, Color.Orange);
regions = null;
return(marker.Apply(bitmap));
}
regions = null;
return(bitmap);
}
}
private void button1_Click(object sender, EventArgs e)
{
detector.SearchMode = (ObjectDetectorSearchMode)cbMode.SelectedValue;
detector.ScalingMode = (ObjectDetectorScalingMode)cbScaling.SelectedValue;
detector.ScalingFactor = 1.5f;
detector.MinSize = new Size(32, 32);
detector.UseParallelProcessing = cbParallel.Checked;
Stopwatch sw = Stopwatch.StartNew();
// prepare grayscale image
picture = Accord.Imaging.Image.Clone(new Bitmap(pictureBox1.Image), System.Drawing.Imaging.PixelFormat.Format24bppRgb);
// Process frame to detect objects
Rectangle[] objects = detector.ProcessFrame(picture);
sw.Stop();
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Red);
pictureBox1.Image = marker.Apply(picture);
}
toolStripStatusLabel1.Text = string.Format("Completed detection of {0} objects in {1}.",
objects.Length, sw.Elapsed);
}
/*
* private async void MainPage_OnLoaded()
* {
* var assembly = Assembly_.GetExecutingAssembly();
* using (var stream = assembly.GetManifestResourceStream("FaceDetection.Images.judybats.jpg"))
* {
* this.ImageView.Source = this.GetImageSourceFromStream(stream);
*
* stream.Seek(0, SeekOrigin.Begin);
* this.bitmap = ((Bitmap)Image.FromStream(stream)).Clone(PixelFormat.Format32bppArgb);
* }
* }
*
* private void DetectButton_OnClick(object sender, EventArgs e)
* {
* var threshold = 10;// (float)Math.Pow(10.0, this.LogThresholdSlider.Value);
* var octaves = 10;// (int)this.OctaveSlider.Value;
* var initial = 10;// (int)this.InitialSlider.Value;
*
* // Create a new SURF Features Detector using the given parameters
* var surf = new SpeededUpRobustFeaturesDetector(threshold, octaves, initial);
*
* var points = surf.ProcessImage(this.bitmap);
*
* // Create a new AForge's Corner Marker Filter
* var features = new FeaturesMarker(points);
*
* // Apply the filter and display it on a picturebox
* this.LenaImage.Source = (BitmapSource)features.Apply(bitmap);
* }
*/
#endregion
#region EVENT HANDLERS
private void OnDetectButtonClicked(object sender, EventArgs args)
{
int searchModeIndex, scalingModeIndex;
ObjectDetectorSearchMode searchMode;
ObjectDetectorScalingMode scalingMode;
if ((searchModeIndex = this.SearchModePicker.SelectedIndex) < 0 ||
(scalingModeIndex = this.ScalingModePicker.SelectedIndex) < 0 ||
!Enum.TryParse(this.SearchModePicker.Items[searchModeIndex], out searchMode) ||
!Enum.TryParse(this.ScalingModePicker.Items[scalingModeIndex], out scalingMode))
{
return;
}
this.detector.SearchMode = searchMode;
this.detector.ScalingMode = scalingMode;
this.detector.ScalingFactor = 1.5f;
this.detector.UseParallelProcessing = false;
// Process frame to detect objects
var objects = this.detector.ProcessFrame(this.bitmap);
if (objects.Length > 0)
{
var marker = new RectanglesMarker(objects, Color.FromArgb(0xff, 0xff, 0x00, 0xff));
using (var stream = new MemoryStream())
{
marker.Apply(this.bitmap).Save(stream, ImageFormat.Jpeg);
this.ImageView.Source = this.GetImageSourceFromStream(stream);
}
}
}
private void button1_Click(object sender, EventArgs e)
{
detector.SearchMode = (ObjectDetectorSearchMode)cbMode.SelectedValue;
detector.ScalingMode = (ObjectDetectorScalingMode)cbScaling.SelectedValue;
detector.ScalingFactor = 1.5f;
detector.UseParallelProcessing = cbParallel.Checked;
detector.Suppression = 2;
Stopwatch sw = Stopwatch.StartNew();
// Process frame to detect objects
Rectangle[] objects = detector.ProcessFrame(picture);
sw.Stop();
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Fuchsia);
pictureBox1.Image = marker.Apply(picture);
}
toolStripStatusLabel1.Text = string.Format("Completed detection of {0} objects in {1}.",
objects.Length, sw.Elapsed);
}
private void btnTrainFace_Click(object sender, EventArgs e)
{
try
{
detector = new HaarObjectDetector(cascade, 30);
detector.SearchMode = ObjectDetectorSearchMode.Single;//.NoOverlap;//.Default; //.Average;
detector.ScalingFactor = 1.5f;
detector.ScalingMode = ObjectDetectorScalingMode.GreaterToSmaller;
detector.UseParallelProcessing = true;
detector.Suppression = 3;
Bitmap picture = new Bitmap(pictureBox1.Image);
Image <Bgr, byte> Frame = new Image <Bgr, byte>(picture);
Stopwatch sw = Stopwatch.StartNew();
Rectangle[] faceObjects = detector.ProcessFrame(picture);
sw.Stop();
if (faceObjects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(faceObjects, Color.Fuchsia);
pictureBox1.Image = marker.Apply(picture);
//Graphics g = Graphics.FromImage(pictureBox1.Image);
foreach (var face in faceObjects)
{
//g.DrawRectangle(Pens.DeepSkyBlue, face);
Frame.Draw(face, new Bgr(Color.Red), 3);
Bitmap c = Frame.ToBitmap();
Bitmap bmp = new Bitmap(face.Width, face.Height);
Graphics gg = Graphics.FromImage(bmp);
gg.DrawImage(c, 0, 0, face, GraphicsUnit.Pixel);
pictureBox2.Image = bmp;
//bmp.Save("myface(accord) " + DateTime.Now.Second.ToString());
gg.Dispose();
}
//g.Dispose();
//label1.Text = "Completed operation!! " + faceObjects.Length.ToString() + " Face detected";
MessageBox.Show("Train Face operation successful!!! " + faceObjects.Length.ToString() + " Face detected", "Train face", MessageBoxButtons.OK, MessageBoxIcon.Information);
txtFaceId.Text = genFaceId();
txtUsername.Text = "User" + txtFaceId.Text;
btnUpload.Enabled = false;
btnTrainFace.Enabled = false;
btnSave.Enabled = true;
}
else
{
MessageBox.Show("Image cannot be trained!!! No face detected in the current image", "Fail to Train face", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
catch (Exception er)
{
MessageBox.Show(er.Message, "Face Detection and Recognition Failure", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
private Bitmap FaceFind(Bitmap bmpBitmap)
{
HaarObjectDetector faceDetector = new HaarObjectDetector(new FaceHaarCascade(), minSize: 300, searchMode: ObjectDetectorSearchMode.Single);
RectanglesMarker faceMarker = new RectanglesMarker(Color.Red)
{
Rectangles = faceDetector.ProcessFrame(bmpBitmap)
};
faceMarker.ApplyInPlace(bmpBitmap);
return(bmpBitmap);
}
private void mixedToolStripMenuItem_Click(object sender, EventArgs e)
{
if (tracker != null)
{
tracking = false;
tracker.Mode = CamshiftMode.Mixed;
tracker.Reset();
marker = null;
}
rGBToolStripMenuItem.Checked = false;
hSLToolStripMenuItem.Checked = false;
mixedToolStripMenuItem.Checked = true;
}
private Bitmap Detecting(Bitmap _bitmap)
{
UnmanagedImage im = UnmanagedImage.FromManagedImage(_bitmap);
float xscale = im.Width / 160f;
float yscale = im.Height / 120f;
ResizeNearestNeighbor resize = new ResizeNearestNeighbor(160, 120);
UnmanagedImage downsample = resize.Apply(im);
Rectangle[] regions = detector.ProcessFrame(downsample);
if (regions.Length > 0)
{
tracker.Reset();
// Reduce the face size to avoid tracking background
Rectangle window = new Rectangle(
(int)((regions[0].X + regions[0].Width / 2f) * xscale),
(int)((regions[0].Y + regions[0].Height / 2f) * yscale),
1, 1);
window.Inflate(
(int)(0.2f * regions[0].Width * xscale),
(int)(0.4f * regions[0].Height * yscale));
this.FaceTracked = window;
// Initialize tracker
tracker.SearchWindow = window;
tracker.ProcessFrame(im);
marker = new RectanglesMarker(window);
marker.ApplyInPlace(im);
// (Bitmap) Helpers.BitmapHelper.ByteArrayToImage(Helpers.RijndaelHelper.EncryptBytes(Helpers.BitmapHelper.ImageToByte(im.ToManagedImage()), "fzafa", "afzd"))
this.isTracking = true;
return(im.ToManagedImage());
}
else
{
this.isDetecting = false;
return(_bitmap);
}
}
private void timer1_Tick(object sender, EventArgs e)
{
Mat frame = new Mat();
frame = cap.QueryFrame();
Image <Bgr, byte> frameImage = frame.ToImage <Bgr, byte>();
Image <Gray, byte> grayFrameImage = frameImage.Convert <Gray, byte>();
if (frame != null)
{
Rectangle[] faces = detector.ProcessFrame(grayFrameImage.ToBitmap());
RectanglesMarker marker = new RectanglesMarker(faces, Color.Fuchsia);
imageViewer.Image = new Image <Bgr, byte>(marker.Apply(frame.Bitmap));
}
}
public Bitmap Detect()
{
_detector.ScalingFactor = 1.5f;
_detector.UseParallelProcessing = true;
Rectangle[] objects = _detector.ProcessFrame(image);
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Yellow);
image = marker.Apply(image);
}
return(image);
}
private void button1_Click(object sender, EventArgs e)
{
try
{
detector = new HaarObjectDetector(cascade, 30);
detector.SearchMode = ObjectDetectorSearchMode.Single; //.Default;//.NoOverlap;//
detector.ScalingFactor = 2.5f;
detector.ScalingMode = ObjectDetectorScalingMode.SmallerToGreater; //.GreaterToSmaller;
detector.UseParallelProcessing = true;
detector.Suppression = 3;
Bitmap picture = new Bitmap(pictureBox2.Image);
Image <Bgr, byte> Frame = new Image <Bgr, byte>(picture);
Stopwatch sw = Stopwatch.StartNew();
Rectangle[] faceObjects = detector.ProcessFrame(picture);
sw.Stop();
if (faceObjects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(faceObjects, Color.Fuchsia);
pictureBox2.Image = marker.Apply(picture);
}
label1.Text = "Operation Completed!!! " + faceObjects.Length.ToString() + " Face detected";
Graphics g = Graphics.FromImage(pictureBox2.Image);
foreach (var face in faceObjects)
{
g.DrawRectangle(Pens.DeepSkyBlue, face);
Frame.Draw(face, new Bgr(Color.Red), 3);
Bitmap c = Frame.ToBitmap();
Bitmap bmp = new Bitmap(face.Width, face.Height);
Graphics gg = Graphics.FromImage(bmp);
gg.DrawImage(c, 0, 0, face, GraphicsUnit.Pixel);
//pictureBox2.Image = bmp;
bmp.Save("myface(accord) " + DateTime.Now.Second.ToString());
MessageBox.Show("Face Detected!!!, Face Save as:" + "myface(accord) " + DateTime.Now.Second.ToString(), "Face Detection Successfully", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
//g.Dispose()
}
catch (Exception er)
{
MessageBox.Show(er.Message, "Face Detection Failure", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
private void skindetect_Click(object sender, EventArgs e)
{
sw.Reset();
sw.Start();
Bitmap img = (Bitmap)Image.FromFile(filepath, true); //将原图进行导入并进行格式转化
Bitmap normalizedImg = YCbCr.Lightingconpensate(img);
Bitmap skin = YCbCr.SkinDetect1(normalizedImg); //肤色检测
Bitmap BWskin = Knowledge.Thresholding(skin); //图片二值化
Bitmap gray_img = Knowledge.ToGray(img);
AForge.Imaging.SusanCornersDetector scd = new AForge.Imaging.SusanCornersDetector(); //susan检测子
//检测人眼部分
AForge.Imaging.BlobCounter blobCounter = new AForge.Imaging.BlobCounter(BWskin); //对图片进行检测联通区域
Rectangle[] rects = blobCounter.GetObjectsRectangles();
Rectangle[] outputrects = new Rectangle[rects.Count()];
////object count
int minx = 150; int tmp = 0;
int rectsCount = rects.Count();
List <decimal> test = new List <decimal>();
for (int c = 0; c < rectsCount; c++)
{
int p = rects[c].Width * rects[c].Height;
decimal bl = (decimal)rects[c].Height / (decimal)rects[c].Width;
int maxx = (img.Width * img.Height) / 2;
if (p > minx && (double)bl < 1.8 && (double)bl > 0.9 && p < maxx)
{
test.Add(bl);
outputrects[tmp++] = rects[c];
}
}
RectanglesMarker marker = new RectanglesMarker(outputrects, Color.Red);
Process2.Image = img;
Detected.Image = marker.Apply((Bitmap)Image.FromFile(filepath, true));
sw.Stop();
string str = sw.Elapsed.ToString();
timeElpsed.Text = string.Empty;
timeElpsed.Text = "运行时间：" + str;
}
private Bitmap Tracking(Bitmap _bitmap)
{
UnmanagedImage im = UnmanagedImage.FromManagedImage(_bitmap);
// Track the object
tracker.ProcessFrame(im);
// Get the object position
var obj = tracker.TrackingObject;
this.FaceTracked = obj.Rectangle;
marker = new RectanglesMarker(obj.Rectangle);
if (marker != null)
{
marker.ApplyInPlace(im);
}
return(im.ToManagedImage());
}
public static string DetectFace(string path)
{
GetPicture(path);
// Process frame to detect objects
HaarCascade cascade = new FaceHaarCascade();
HaarObjectDetector detector = new HaarObjectDetector(cascade, 30);
detector.SearchMode = (ObjectDetectorSearchMode)cbMode;
detector.ScalingMode = (ObjectDetectorScalingMode)cbScaling;
detector.ScalingFactor = 1.5f;
Stopwatch sw = Stopwatch.StartNew();
Rectangle[] objects = detector.ProcessFrame(picture);
sw.Stop();
if (objects.Length > 0)
{
Console.WriteLine("here");
RectanglesMarker marker = new RectanglesMarker(objects, Color.Fuchsia);
picture = marker.Apply(picture);
}
if (picture != null)
{
Console.WriteLine("trying to print picture");
/*ImageCodecInfo myici = ImageCodecInfo.GetImageEncoders();
* int numCodecs = myici.GetLength(0);
* Encoder myEncoder = Encoder.Quality;
* EncoderParameters param = new EncoderParameters(1);
* EncoderParameter param1 = new EncoderParameter(myEncoder, 25L);
*
* picture.Save(@"output.jpg", myici, param);
*/
picture.Save("file.png", ImageFormat.Png);;
}
return(path);
}
public static void Main(string[] args)
{
var picture = Resource.lena_color;
HaarCascade cascade = new FaceHaarCascade();
var detector = new HaarObjectDetector(cascade, 30);
//detector.SearchMode = ObjectDetectorSearchMode.Average;
//detector.ScalingMode = ObjectDetectorScalingMode.GreaterToSmaller;
//detector.ScalingFactor = 1.5f;
//detector.UseParallelProcessing = false;
//detector.Suppression = 2;
Rectangle[] objects = detector.ProcessFrame(picture);
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Fuchsia);
var markedup = marker.Apply(picture);
markedup.Save($"{basedir}{sep}{sep}markedup.jpg");
}
}
private void mytimer_Elapsed(object sender, ElapsedEventArgs e)
{
pic1 = this.videoSourcePlayer1.GetCurrentVideoFrame();
try
{
Rectangle[] objects = detector.ProcessFrame(pic1);
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Black);
pic2 = marker.Apply(pic1);
this.detectedFaceimg.Image = pic2;
}
else
{
this.detectedFaceimg.Image = pic1;
}
}
catch
{
this.detectedFaceimg.Image = pic1;
}
}
/// <summary>
/// This method helps to face detection
/// </summary>
/// <param name="image">Original image</param>
/// <returns>Face detection result</returns>
public static FaceDetectionResult FaceDetection(Bitmap image)
{
// Creating an face detection instance
var result = new FaceDetectionResult();
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
// set min size in the picture to detect faces
var detector = new HaarObjectDetector(cascade, minSize: 100, searchMode: ObjectDetectorSearchMode.NoOverlap);
var bmp = Accord.Imaging.Image.Clone(image);
// execute detection
var faces = detector.ProcessFrame(bmp);
// set rectangle color
var objectMarker = new RectanglesMarker(Color.Red)
{
Rectangles = faces
};
// apply filter and get a new image
var resultImage = objectMarker.Apply(image); // overwrite the frame
result.ImageResult = resultImage;
// set result parameters
result.TotalFacesDetected = faces?.Length ?? 0;
result.Rectangles = faces;
return(result);
}
public void DetectFaces()
{
detector.SearchMode = (ObjectDetectorSearchMode)ObjectDetectorSearchMode.NoOverlap;
detector.ScalingMode = (ObjectDetectorScalingMode)ObjectDetectorScalingMode.SmallerToGreater;
detector.ScalingFactor = 1.5f;
detector.UseParallelProcessing = true; //cbParallel.Checked;
detector.Suppression = 2;
//Stopwatch sw = Stopwatch.StartNew();
// Process frame to detect objects
Rectangle[] objects = detector.ProcessFrame(picture);
//sw.Stop();
if (objects.Length > 0)
{
RectanglesMarker marker = new RectanglesMarker(objects, Color.Red);
image.Image = marker.Apply(picture);
}
//toolStripStatusLabel1.Text = string.Format("Completed detection of {0} objects in {1}.",
// objects.Length, sw.Elapsed);
}
// New frame received by the player
private void videoSourcePlayer_NewFrame(object sender, ref Bitmap image)
{
if (!detecting && !tracking)
{
return;
}
lock (this)
{
if (detecting)
{
detecting = false;
tracking = false;
UnmanagedImage im = UnmanagedImage.FromManagedImage(image);
float xscale = image.Width / 160f;
float yscale = image.Height / 120f;
ResizeNearestNeighbor resize = new ResizeNearestNeighbor(160, 120);
UnmanagedImage downsample = resize.Apply(im);
Rectangle[] regions = detector.ProcessFrame(downsample);
if (regions.Length > 0)
{
tracker.Reset();
// Will track the first face found
Rectangle face = regions[0];
// Reduce the face size to avoid tracking background
Rectangle window = new Rectangle(
(int)((regions[0].X + regions[0].Width / 2f) * xscale),
(int)((regions[0].Y + regions[0].Height / 2f) * yscale),
1, 1);
window.Inflate(
(int)(0.2f * regions[0].Width * xscale),
(int)(0.4f * regions[0].Height * yscale));
// Initialize tracker
tracker.SearchWindow = window;
tracker.ProcessFrame(im);
marker = new RectanglesMarker(window);
marker.ApplyInPlace(im);
image = im.ToManagedImage();
tracking = true;
//detecting = true;
}
else
{
detecting = true;
}
}
else if (tracking)
{
UnmanagedImage im = UnmanagedImage.FromManagedImage(image);
// Track the object
tracker.ProcessFrame(im);
// Get the object position
var obj = tracker.TrackingObject;
var wnd = tracker.SearchWindow;
if (displayBackprojectionToolStripMenuItem.Checked)
{
var backprojection = tracker.GetBackprojection(PixelFormat.Format24bppRgb);
im = UnmanagedImage.FromManagedImage(backprojection);
}
if (drawObjectAxisToolStripMenuItem.Checked)
{
LineSegment axis = obj.GetAxis();
// Draw X axis
Drawing.Line(im, axis.Start.Round(), axis.End.Round(), Color.Red);
}
if (drawObjectBoxToolStripMenuItem.Checked && drawTrackingWindowToolStripMenuItem.Checked)
{
marker = new RectanglesMarker(new Rectangle[] { wnd, obj.Rectangle });
}
else if (drawObjectBoxToolStripMenuItem.Checked)
{
//InteractionPoints p = new InteractionPoints();
//p.setHead(obj.Rectangle);
marker = new RectanglesMarker(obj.Rectangle);
}
else if (drawTrackingWindowToolStripMenuItem.Checked)
{
marker = new RectanglesMarker(wnd);
}
else
{
marker = null;
}
if (marker != null)
{
marker.ApplyInPlace(im);
}
image = im.ToManagedImage();
}
else
{
if (marker != null)
{
image = marker.Apply(image);
}
}
}
}
// New frame received by the player
private void videoSourcePlayer_NewFrame(object sender, ref Bitmap image)
{
lock (this)
{
if (tracker == null)
{
return;
}
if (form != null && !form.IsDisposed)
{
form.Image = image;
}
BitmapData data = image.LockBits(new Rectangle(0, 0, image.Width, image.Height),
ImageLockMode.ReadWrite, image.PixelFormat);
UnmanagedImage img = new UnmanagedImage(data);
tracker.ComputeOrientation = showAngle;
tracker.ProcessFrame(img);
Rectangle rect = tracker.TrackingObject.Rectangle;
UnmanagedImage hand = tracker.TrackingObject.Image;
if (hand != null && (showContour || showFingertips))
{
UnmanagedImage grayhand = Grayscale.CommonAlgorithms.BT709.Apply(hand);
blur.ApplyInPlace(grayhand);
List <IntPoint> contour = bf.FindContour(grayhand);
for (int i = 0; i < contour.Count; i++)
{
contour[i] += new IntPoint(rect.X, rect.Y);
}
List <IntPoint> peaks = kcurv.FindPeaks(contour);
if (showContour)
{
cmarker.Points = contour;
cmarker.ApplyInPlace(img);
}
if (showFingertips)
{
pmarker.Points = peaks;
pmarker.ApplyInPlace(img);
}
}
if (showRectangle)
{
RectanglesMarker marker = new RectanglesMarker(rect);
marker.ApplyInPlace(img);
}
if (showAngle)
{
LineSegment axis = tracker.TrackingObject.GetAxis(AxisOrientation.Vertical);
if (axis != null)
{
// Draw X axis
Drawing.Line(img, axis.Start.Round(), axis.End.Round(), Color.Red);
}
}
image.UnlockBits(data);
}
}
// New frame received by the player
private void videoSourcePlayer_NewFrame(object sender, NewFrameEventArgs args)
{
var direccion = "Centro";
int direccionServo = 2;
if (!detecting && !tracking)
{
return;
}
lock (this)
{
if (detecting)
{
detecting = false;
tracking = false;
UnmanagedImage im = UnmanagedImage.FromManagedImage(args.Frame);
float xscale = im.Width / 160f;
float yscale = im.Height / 120f;
ResizeNearestNeighbor resize = new ResizeNearestNeighbor(160, 120);
UnmanagedImage downsample = resize.Apply(im);
Rectangle[] regions = detector.ProcessFrame(downsample);
if (regions.Length > 0)
{
tracker.Reset();
// Will track the first face found
Rectangle face = regions[0];
// Reduce the face size to avoid tracking background
Rectangle window = new Rectangle(
(int)((regions[0].X + regions[0].Width / 2f) * xscale),
(int)((regions[0].Y + regions[0].Height / 2f) * yscale),
1, 1);
Console.Write("x:" + (int)((regions[0].X + regions[0].Width / 2f) * xscale));
Console.Write("y:" + (int)((regions[0].X + regions[0].Height / 2f) * xscale));
window.Inflate(
(int)(0.2f * regions[0].Width * xscale),
(int)(0.4f * regions[0].Height * yscale));
// Initialize tracker
tracker.SearchWindow = window;
tracker.ProcessFrame(im);
marker = new RectanglesMarker(window);
marker.ApplyInPlace(im);
args.Frame = im.ToManagedImage();
tracking = true;
//detecting = true;
}
else
{
detecting = true;
}
}
else if (tracking)
{
UnmanagedImage im = UnmanagedImage.FromManagedImage(args.Frame);
// Track the object
tracker.ProcessFrame(im);
// Get the object position
var obj = tracker.TrackingObject;
var wnd = tracker.SearchWindow;
//if (displayBackprojectionToolStripMenuItem.Checked)
//{
// var backprojection = tracker.GetBackprojection(PixelFormat.Format24bppRgb);
// im = UnmanagedImage.FromManagedImage(backprojection);
//}
//if (drawObjectAxisToolStripMenuItem.Checked)
//{
// LineSegment axis = obj.GetAxis();
// // Draw X axis
// if (axis != null)
// Drawing.Line(im, axis.Start.Round(), axis.End.Round(), Color.Red);
// else detecting = true;
//}
if (obj.Rectangle.Width < (args.Frame.Width / 3) * 2)
{
if (obj.Rectangle.X < args.Frame.Width / 3)
{
direccion = "Izquierda";
direccionServo = 1;
}
else if (obj.Rectangle.X > (args.Frame.Width / 3) * 2)
{
direccion = "Derecha";
direccionServo = 3;
}
}
try
{
this.Invoke((MethodInvoker) delegate
{
if (textBox1 != null)
{
textBox1.Text = obj.Rectangle.X.ToString();
textBox2.Text = obj.Rectangle.Y.ToString();
label1.Text = direccion;
}
});
ComunicacionPuertoSerie.Instance.enviarEvento(direccionServo.ToString());
}
catch (Exception e) { }
if (/*drawObjectBoxToolStripMenuItem.Checked && drawTrackingWindowToolStripMenuItem.Checked*/ false)
{
marker = new RectanglesMarker(new Rectangle[] { wnd, obj.Rectangle });
}
else if (/*drawObjectBoxToolStripMenuItem.Checked*/ true)
{
marker = new RectanglesMarker(obj.Rectangle);
}
else if (/*drawTrackingWindowToolStripMenuItem.Checked*/ true)
{
marker = new RectanglesMarker(wnd);
}
else
{
marker = null;
}
if (marker != null)
{
marker.ApplyInPlace(im);
}
args.Frame = im.ToManagedImage();
}
else
{
if (marker != null)
{
args.Frame = marker.Apply(args.Frame);
}
}
}
}
public void ProcessFrame()
{
string basePath = Path.Combine(NUnit.Framework.TestContext.CurrentContext.TestDirectory, "matching-tracker");
#region doc_track
// Let's test the tracker using a sample video from
// the collection of test videos in the framework:
TestVideos ds = new TestVideos(basePath);
string fileName = ds["walking.mp4"];
// Now, let's open the video using FFMPEG:
var video = new VideoFileReader();
video.Open(fileName);
// And then check the contents of one of the frames:
Bitmap frame = video.ReadVideoFrame(frameIndex: 150);
frame.Save(Path.Combine(basePath, "walking_frame.png"));
// Let's register a template for the bike rider in gray shirt
Rectangle roi = new Rectangle(x: 70, y: 105, width: 28, height: 54);
// initialization
var tracker = new MatchingTracker()
{
SearchWindow = roi,
Threshold = 0.0, // never reset the tracker in case it gets lost
RegistrationThreshold = 0.95 // re-register the template if we are 95%
// confident that the tracked object is indeed the object we want to follow
};
// Creating bitmaps and locking them is an expensive
// operation. Instead, let's allocate once and reuse
BitmapData bitmapData = frame.LockBits(ImageLockMode.ReadWrite);
UnmanagedImage unmanagedImage = new UnmanagedImage(bitmapData);
// We will create two color markers: one to show the location of the
// tracked object (red) and another one to show the regions of the image
// that the tracker is looking at (white).
RectanglesMarker objectMarker = new RectanglesMarker(Color.Red);
RectanglesMarker windowMarker = new RectanglesMarker(Color.White);
// Now, for each frame of the video
for (int frameIndex = 0; frameIndex < video.FrameCount; frameIndex++)
{
// Read the current frame into the bitmap data
video.ReadVideoFrame(frameIndex, bitmapData);
if (frameIndex > 150) // wait until the bike rider enters the scene
{
// Feed the frame to the tracker
tracker.ProcessFrame(unmanagedImage);
// Mark the location of the tracker object in red color
objectMarker.SingleRectangle = tracker.TrackingObject.Rectangle;
objectMarker.ApplyInPlace(unmanagedImage); // overwrite the frame
windowMarker.SingleRectangle = tracker.SearchWindow;
windowMarker.ApplyInPlace(unmanagedImage); // overwrite the frame
}
// Save it to disk
frame.Save(Path.Combine(basePath, "frame_{0}.png".Format(frameIndex)));
}
frame.UnlockBits(bitmapData);
#endregion
}
private void videoSourcePlayer1_NewFrame(object sender, ref Bitmap image)
{
Invert inv = new Invert();
inv.ApplyInPlace(image);
UnmanagedImage ui = UnmanagedImage.FromManagedImage(image);
pictureBox1.Image = image;
if (controller.Tracker.TrackingObject == null)
{
return;
}
if (controller.Tracker.TrackingObject.IsEmpty)
{
return;
}
var rect = controller.Tracker.TrackingObject.Rectangle;
Crop crop = new Crop(rect);
UnmanagedImage head = crop.Apply(ui);
var points = new List <IntPoint>()
{
new IntPoint(head.Width / 2, head.Height / 2)
};
var pps = head.Collect16bppPixelValues(points);
double mean = Accord.Statistics.Tools.Mean(pps);
double cutoff = mean + 15;
Threshold t = new Threshold((int)cutoff);
var mask = t.Apply(ui);
LevelsLinear16bpp levels = new LevelsLinear16bpp();
levels.InGray = new IntRange((int)cutoff, 65535);
levels.OutGray = new IntRange(0, 65535);
levels.ApplyInPlace(ui);
var mask8bit = AForge.Imaging.Image.Convert16bppTo8bpp(mask.ToManagedImage());
BlobCounter bc = new BlobCounter();
bc.ObjectsOrder = ObjectsOrder.Area;
bc.ProcessImage(mask8bit);
var blobs = bc.GetObjectsInformation();
inv.ApplyInPlace(image);
Intersect intersect = new Intersect();
intersect.UnmanagedOverlayImage = mask;
mask = intersect.Apply(ui);
List <Rectangle> rects = new List <Rectangle>();
// Extract the uppermost largest blobs.
for (int i = 0; i < blobs.Length; i++)
{
double dx = (blobs[i].Rectangle.Top - controller.Tracker.TrackingObject.Center.Y);
double d = (dx * dx) / controller.Tracker.TrackingObject.Area;
if (d < 2 && blobs[i].Area > 1000)
{
rects.Add(blobs[i].Rectangle);
}
}
rects.Sort(compare);
if (rects.Count > 0)
{
captureHand(mask, rects[0], pbLeftArm, pbLeftHand);
}
if (rects.Count > 1)
{
captureHand(mask, rects[1], pbRightArm, pbRightHand);
}
RectanglesMarker marker = new RectanglesMarker(rects);
marker.MarkerColor = Color.White;
marker.ApplyInPlace(mask8bit);
image = mask.ToManagedImage();
}
public void ProcessVideo()
{
string basePath = Path.Combine(NUnit.Framework.TestContext.CurrentContext.TestDirectory, "detector");
#region doc_video
// Let's test the detector using a sample video from
// the collection of test videos in the framework:
TestVideos ds = new TestVideos(basePath);
string fileName = ds["crowd.mp4"];
// In this example, we will be creating a cascade for a Face detector:
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
// Now, create a new Haar object detector with the cascade:
var detector = new HaarObjectDetector(cascade, minSize: 25,
searchMode: ObjectDetectorSearchMode.Average,
scalingMode: ObjectDetectorScalingMode.SmallerToGreater,
scaleFactor: 1.1f)
{
Suppression = 5 // This should make sure we only report regions as faces if
// they have been detected at least 5 times within different cascade scales.
};
// Now, let's open the video using FFMPEG:
var video = new VideoFileReader();
video.Open(fileName);
// And then check the contents of one of the frames:
Bitmap frame = video.ReadVideoFrame(frameIndex: 0);
// Creating bitmaps and locking them is an expensive
// operation. Instead, let's allocate once and reuse
BitmapData bitmapData = frame.LockBits(ImageLockMode.ReadWrite);
UnmanagedImage unmanagedImage = new UnmanagedImage(bitmapData);
// We will create a color marker to show the faces
var objectMarker = new RectanglesMarker(Color.Red);
// This example is going to show two different ways to save results to disk. The
// first is to save the results frame-by-frame, saving each individual frame as
// a separate .png file. The second is to save them as a video in .mp4 format.
// To save results as a movie clip in mp4 format, you can use:
VideoFileWriter writer = new VideoFileWriter();
writer.Open(Path.Combine(basePath, "detected_faces.mp4"), frame.Width, frame.Height);
// Now, for each frame of the video
for (int frameIndex = 0; frameIndex < video.FrameCount; frameIndex++)
{
// Read the current frame into the bitmap data
video.ReadVideoFrame(frameIndex, bitmapData);
// Feed the frame to the tracker
Rectangle[] faces = detector.ProcessFrame(unmanagedImage);
// Mark the location of the tracker object in red color
objectMarker.Rectangles = faces;
objectMarker.ApplyInPlace(unmanagedImage); // overwrite the frame
// Save it to disk: first saving each frame separately:
frame.Save(Path.Combine(basePath, "frame_{0}.png".Format(frameIndex)));
// And then, saving as a .mp4 file:
writer.WriteVideoFrame(bitmapData);
}
// The generated video can be seen at https://1drv.ms/v/s!AoiTwBxoR4OAoLJhPozzixD25XcbiQ
video.Close();
writer.Close();
#endregion
}
