protected override void OnCreate(Bundle bundle)
{
base.OnCreate(bundle);
OnButtonClick += delegate
{
long time;
using (Image <Bgr, Byte> image = PickImage("pedestrian.png"))
{
if (image == null)
{
return;
}
Rectangle[] pedestrians = FindPedestrian.Find(image.Mat, false, true, out time);
SetMessage(String.Format("Detection completed in {0} milliseconds.", time));
foreach (Rectangle rect in pedestrians)
{
image.Draw(rect, new Bgr(System.Drawing.Color.Red), 2);
}
SetImageBitmap(image.ToBitmap());
}
};
}
public PeopleDetect Post(string url)
{
PeopleDetect results = new PeopleDetect();
results.counted = 0;
var webClient = new WebClient();
//download image from url
byte[] imageBytes = webClient.DownloadData(url);
Mat image = new Mat();
CvInvoke.Imdecode(imageBytes, LoadImageType.Color, image);
bool tryUseCuda = false;
long processingTime;
//find the pedestrians in the image and return rectangles and count
results.rectCoord = FindPedestrian.Find(image, tryUseCuda, out processingTime);
foreach (Rectangle rect in results.rectCoord)
{
results.counted = results.counted + 1;
}
return(results);
}
public override void ViewDidLoad()
{
base.ViewDidLoad();
ButtonText = "Detect Pedestrian";
OnButtonClick += delegate
{
long processingTime;
using (Image <Bgr, byte> image = new Image <Bgr, byte>("pedestrian.png"))
{
Rectangle[] pedestrians = FindPedestrian.Find(
image.Mat, false, false,
out processingTime
);
foreach (Rectangle rect in pedestrians)
{
image.Draw(rect, new Bgr(Color.Red), 1);
}
Size frameSize = FrameSize;
using (Image <Bgr, Byte> resized = image.Resize(frameSize.Width, frameSize.Height, Emgu.CV.CvEnum.Inter.Nearest, true))
{
MessageText = String.Format(
"Detection Time: {0} milliseconds.",
processingTime
);
SetImage(resized);
}
}
};
}
public void viewing()
{
Image <Bgr, byte> image1 = new Image <Bgr, byte>("p1.jpg");
this.WindowState = FormWindowState.Maximized;
pictureBox1.Height = this.Height;
pictureBox1.Width = this.Width;
image1 = image1.Resize(this.Width, this.Height, Emgu.CV.CvEnum.Inter.Linear);
Mat image = image1.Mat;
long processingTime;
Rectangle[] results;
if (CudaInvoke.HasCuda)
{
using (GpuMat gpuMat = new GpuMat(image))
results = FindPedestrian.Find(gpuMat, out processingTime);
}
else
{
using (UMat uImage = image.ToUMat(AccessType.ReadWrite))
results = FindPedestrian.Find(uImage, out processingTime);
}
foreach (Rectangle rect in results)
{
CvInvoke.Rectangle(image, rect, new Bgr(Color.Red).MCvScalar);
}
Image <Bgr, Byte> img = image.ToImage <Bgr, Byte>();
pictureBox1.Image = img.ToBitmap();
}
public PedestrianDetectionPage()
: base()
{
var button = this.GetButton();
button.Text = "Perform Pedestrian Detection";
OnImagesLoaded += async(sender, image) =>
{
if (image == null || image [0] == null)
{
return;
}
GetLabel().Text = "please wait...";
SetImage(null);
Task <Tuple <Mat, long> > t = new Task <Tuple <Mat, long> >(
() =>
{
long time;
Rectangle [] pedestrians;
if (image[0].NumberOfChannels == 4)
{
//if the png file is loaded with alpha channel
using (Mat bgr = new Mat())
{
CvInvoke.CvtColor(image [0], bgr, ColorConversion.Bgra2Bgr);
pedestrians = FindPedestrian.Find(bgr, out time);
}
}
else
{
pedestrians = FindPedestrian.Find(image[0], out time);
}
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(image[0], rect, new MCvScalar(0, 0, 255), 2);
}
return(new Tuple <Mat, long>(image[0], time));
});
t.Start();
var result = await t;
String computeDevice = CvInvoke.UseOpenCL ? "OpenCL: " + Ocl.Device.Default.Name : "CPU";
GetLabel().Text = String.Format("Detection completed with {1} in {0} milliseconds.", t.Result.Item2,
computeDevice);
SetImage(t.Result.Item1);
};
button.Clicked += OnButtonClicked;
}
public PeopleDetect UploadFile()
{
if (HttpContext.Current.Request.Files.AllKeys.Any())
{
// Get the uploaded image from the Files collection
var httpPostedFile = HttpContext.Current.Request.Files[0];
if (httpPostedFile != null)
{
//get the file path and save the image
var fileSavePath = Path.Combine(HttpContext.Current.Server.MapPath("~/UploadedFiles"), httpPostedFile.FileName);
httpPostedFile.SaveAs(fileSavePath);
PeopleDetect results = new PeopleDetect();
results.counted = 0;
Mat image = new Mat(fileSavePath, LoadImageType.Color);
bool tryUseCuda = false;
long processingTime;
//find the pedestrians in the image and return rectangles and count
results.rectCoord = FindPedestrian.Find(image, tryUseCuda, out processingTime);
foreach (Rectangle rect in results.rectCoord)
{
results.counted = results.counted + 1;
}
File.Delete(fileSavePath);
return(results);
}
else
{
PeopleDetect results = new PeopleDetect();
results.counted = 0;
return(results);
}
}
else
{
PeopleDetect results = new PeopleDetect();
results.counted = 0;
return(results);
}
}
public PedestrianDetectionPage()
: base()
{
var button = this.GetButton();
button.Text = "Perform Pedestrian Detection";
OnImageLoaded += async(sender, image) =>
{
GetLabel().Text = "please wait...";
SetImage(null);
Task <Tuple <Mat, long> > t = new Task <Tuple <Mat, long> >(
() =>
{
long time;
if (image == null)
{
return(new Tuple <Mat, long>(null, 0));
}
Rectangle[] pedestrians = FindPedestrian.Find(image, false, out time);
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(image, rect, new MCvScalar(0, 0, 255), 2);
}
return(new Tuple <Mat, long>(image, time));
});
t.Start();
var result = await t;
String computeDevice = CvInvoke.UseOpenCL ? "OpenCL: " + OclDevice.Default.Name : "CPU";
GetLabel().Text = String.Format("Detection completed with {1} in {0} milliseconds.", t.Result.Item2,
computeDevice);
SetImage(t.Result.Item1);
};
button.Clicked += OnButtonClicked;
}
public void ProcessImage(Mat m)
{
Rectangle[] pedestrians;
if (m.NumberOfChannels == 4)
{
//if the png file is loaded with alpha channel
using (Mat bgr = new Mat())
{
CvInvoke.CvtColor(m, bgr, ColorConversion.Bgra2Bgr);
pedestrians = FindPedestrian.Find(bgr);
}
}
else
{
pedestrians = FindPedestrian.Find(m);
}
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(m, rect, new MCvScalar(0, 0, 255), 2);
}
}
protected override void OnCreate(Bundle bundle)
{
base.OnCreate(bundle);
OnImagePicked += (sender, image) =>
{
if (image == null)
{
return;
}
AppPreference appPreference = new AppPreference();
CvInvoke.UseOpenCL = appPreference.UseOpenCL;
String oclDeviceName = appPreference.OpenClDeviceName;
if (!String.IsNullOrEmpty(oclDeviceName) && CvInvoke.UseOpenCL)
{
CvInvoke.OclSetDefaultDevice(oclDeviceName);
}
long time;
Rectangle[] pedestrians;
using (UMat umat = image.GetUMat(AccessType.ReadWrite))
pedestrians = FindPedestrian.Find(image, out time);
String computeDevice = CvInvoke.UseOpenCL ? "OpenCL: " + Emgu.CV.Ocl.Device.Default.Name : "CPU";
SetMessage(String.Format("Detection completed with {1} in {0} milliseconds.", time, computeDevice));
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(image, rect, new Bgr(System.Drawing.Color.Red).MCvScalar, 2);
}
SetImageBitmap(image.ToBitmap());
image.Dispose();
};
OnButtonClick += (sender, args) =>
{
PickImage("pedestrian.png");
};
}
private void ProcessFrame(object sender, EventArgs arg)
{
Mat frame = _capture.QueryFrame();
pictureBox1.Height = frame.Height;
pictureBox1.Width = frame.Width;
if (frame != null)
{
//image_array.Add(frame.Copy());
long processingTime;
Rectangle[] results;
if (CudaInvoke.HasCuda)
{
using (GpuMat gpuMat = new GpuMat(frame))
results = FindPedestrian.Find(gpuMat, out processingTime);
}
else
{
using (UMat uImage = frame.ToUMat(AccessType.ReadWrite))
results = FindPedestrian.Find(uImage, out processingTime);
}
foreach (Rectangle rect in results)
{
CvInvoke.Rectangle(frame, rect, new Bgr(Color.Red).MCvScalar);
}
Image <Bgr, Byte> img = frame.ToImage <Bgr, Byte>();
img.Resize(384, 288, Emgu.CV.CvEnum.Inter.Linear);
Image <Gray, Byte> grayFrame = img.Convert <Gray, Byte>();
Image <Gray, Byte> smallGrayFrame = grayFrame.PyrDown();
Image <Gray, Byte> smoothedGrayFrame = smallGrayFrame.PyrUp();
pictureBox1.Image = smoothedGrayFrame.ToBitmap();
}
else
{
Application.Idle -= ProcessFrame;// treat as end of file
}
}
public override void ViewDidLoad()
{
base.ViewDidLoad();
ButtonText = "Detect Pedestrian";
OnButtonClick += delegate
{
//long processingTime;
using (Mat image = CvInvoke.Imread("pedestrian.png", ImreadModes.Color))
using (HOGDescriptor hog = new HOGDescriptor())
{
hog.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
Stopwatch watch = Stopwatch.StartNew();
Rectangle[] pedestrians = FindPedestrian.Find(image, hog);
watch.Stop();
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(
image,
rect,
new MCvScalar(0, 0, 255),
1);
}
Size frameSize = FrameSize;
using (Mat resized = new Mat())
{
CvInvoke.ResizeForFrame(image, resized, frameSize);
MessageText = String.Format(
"Detection Time: {0} milliseconds.",
watch.ElapsedMilliseconds
);
SetImage(resized);
}
}
};
}
public override void ViewDidLoad()
{
base.ViewDidLoad();
ButtonText = "Detect Pedestrian";
OnButtonClick += delegate
{
long processingTime;
using (Mat image = CvInvoke.Imread("pedestrian.png", ImreadModes.Color))
{
Rectangle[] pedestrians = FindPedestrian.Find(
image,
out processingTime
);
foreach (Rectangle rect in pedestrians)
{
CvInvoke.Rectangle(
image,
rect,
new MCvScalar(0, 0, 255),
1);
}
Size frameSize = FrameSize;
using (Mat resized = new Mat())
{
CvInvoke.ResizeForFrame(image, resized, frameSize);
MessageText = String.Format(
"Detection Time: {0} milliseconds.",
processingTime
);
SetImage(resized);
}
}
};
}
private void ProcessFrame(object sender, EventArgs e)
{
List <Rectangle> rt = new List <Rectangle>();
double overallAngle = default(double), overallMotionPixelCount = default(double);
Mat image = new Mat();
_capture.Retrieve(image);
if (fpsc++ >= allfpsc)
{
fpsc = 0;
if (_forgroundDetector == null)
{
_forgroundDetector = new BackgroundSubtractorMOG2();
}
_forgroundDetector.Apply(image, _forgroundMask);
//update the motion history
_motionHistory.Update(_forgroundMask);
#region get a copy of the motion mask and enhance its color
double[] minValues, maxValues;
Point[] minLoc, maxLoc;
_motionHistory.Mask.MinMax(out minValues, out maxValues, out minLoc, out maxLoc);
Mat motionMask = new Mat();
using (ScalarArray sa = new ScalarArray(255.0 / maxValues[0]))
CvInvoke.Multiply(_motionHistory.Mask, sa, motionMask, 1, DepthType.Cv8U);
//Image<Gray, Byte> motionMask = _motionHistory.Mask.Mul(255.0 / maxValues[0]);
#endregion
//create the motion image
Mat motionImage = new Mat(motionMask.Size.Height, motionMask.Size.Width, DepthType.Cv8U, 3);
motionImage.SetTo(new MCvScalar(0));
//display the motion pixels in blue (first channel)
//motionImage[0] = motionMask;
CvInvoke.InsertChannel(motionMask, motionImage, 0);
//Threshold to define a motion area, reduce the value to detect smaller motion
double minArea = 100;
//storage.Clear(); //clear the storage
Rectangle[] rects;
using (VectorOfRect boundingRect = new VectorOfRect())
{
_motionHistory.GetMotionComponents(_segMask, boundingRect);
rects = boundingRect.ToArray();
}
//iterate through each of the motion component
foreach (Rectangle comp in rects)
{
if (Zone.Contains(comp))
{
rt.Add(comp);
}
int area = comp.Width * comp.Height;
//reject the components that have small area;
if (area < minArea)
{
continue;
}
// find the angle and motion pixel count of the specific area
double angle, motionPixelCount;
_motionHistory.MotionInfo(_forgroundMask, comp, out angle, out motionPixelCount);
//reject the area that contains too few motion
if (motionPixelCount < area * 0.05)
{
continue;
}
//Draw each individual motion in red
//DrawMotion(motionImage, comp, angle, new Bgr(Color.Blue));
}
//rects = rt.ToArray();
// find and draw the overall motion angle
if (Zone.Width <= 0 & Zone.Height <= 0 & Zone.X < 0 & Zone.Y < 0)
{
Zone = new Rectangle(0, 0, 10, 10);
}
_motionHistory.MotionInfo(_forgroundMask, Zone /*new Rectangle(Point.Empty, motionMask.Size)*/, out overallAngle, out overallMotionPixelCount);
//DrawMotion(motionImage, new Rectangle(Point.Empty, motionMask.Size), overallAngle, new Bgr(Color.Green));
Image <Bgr, Byte> grayImage = image.ToImage <Bgr, Byte>();
if (DetectPed)
{
long processingTime;
Rectangle[] results;
if (CudaInvoke.HasCuda)
{
using (GpuMat gpuMat = new GpuMat(image))
results = FindPedestrian.Find(gpuMat, out processingTime);
}
else
{
using (UMat uImage = image.GetUMat(AccessType.ReadWrite))
results = FindPedestrian.Find(uImage, out processingTime);
}
foreach (Rectangle rect in results)
{
CvInvoke.Rectangle(image, rect, new Bgr(Color.Red).MCvScalar);
}
}
}
if (maxfpsc++ > skipfpsc)
{
OnMD?.Invoke((long)overallMotionPixelCount, image, rt.Count);
}
else
{
OnMD?.Invoke(default(long), image, default(int));
}
}
void matchingVideoTimer_Tick(object sender, EventArgs e)
{
//如果有影片
if (videoCapture != null)
{
if (isPlay)
{
lock (this)
{
//如果Frame的index沒有差過影片的最大index
if (oneSecFrameIndex < matchingVideoTotalFrame && videoCapture.GetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_POS_FRAMES) < matchingVideoTotalFrame)
{
videoCapture.SetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_POS_FRAMES, oneSecFrameIndex);
oneSecFrameIndex += 15;
//顯示
senceImage = videoCapture.QueryFrame();
senceImage = senceImage.Resize(640, 480, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR);
if (surfOpenCheckBox.Checked)
{
pedesrianWorker = new System.Threading.Thread(new System.Threading.ParameterizedThreadStart(MatchImage));
pedesrianWorker.Start(senceImage);
//Match
//MatchImage(senceImage, ReadSURFFeature(dir.Parent.Parent.FullName + "\\SurfFeatureData\\000-0.xml"));
}
if (pedestrianCheckBox.Checked)
{
//行人偵測
long processingTime;
//Rectangle roi = new Rectangle( (senceImage.Width / 3) ,0, (senceImage.Width / 3),senceImage.Height);
////切割區塊，只抓路中央
//Image<Bgr,byte> roadROI = senceImage.Copy();
//roadROI.ROI = roi;
//Image<Bgr, Byte> result = FindPedestrian.Find(roadROI, out processingTime);
////抓人臉
//Image<Gray, byte> graySence = senceImage.Convert<Gray, byte>();
//var faces = graySence.DetectHaarCascade(
// haar, 1.4, 4,
// HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
// new Size(senceImage.Width / 8, senceImage.Height / 8)
// )[0];
//Image<Bgr, Byte> result = senceImage.Copy();
//foreach (var face in faces)
//{
// result.Draw(face.rect, new Bgr(0, double.MaxValue, 0), 3);
//}
Image <Bgr, Byte> result = FindPedestrian.Find(senceImage, out processingTime);
Console.WriteLine("Pedesrian process time = " + processingTime + "ms\n");
if (result != null)
{
pedestrianViewer.Image = result;
pedestrianViewer.Show();
}
}
mathcingVideoPictureBox.Image = senceImage.ToBitmap();
}
}
}
else if (isSuspend)
{
//Nothing to do..
}
else if (isStop)
{
//關閉，回到一開始畫面
videoCapture.SetCaptureProperty(Emgu.CV.CvEnum.CAP_PROP.CV_CAP_PROP_POS_AVI_RATIO, 0);
}
}
}
