static void Run()
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat("lena.jpg", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
long detectionTime;
List<Rectangle> faces = new List<Rectangle>();
List<Rectangle> eyes = new List<Rectangle>();
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
foreach (Rectangle face in faces)
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
foreach (Rectangle eye in eyes)
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
//display the image
using (InputArray iaImage = image.GetInputArray())
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
(iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
: "CPU",
detectionTime));
}
static void Run()
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat("C:/Users/lucas/Desktop/samt/anno3/306/Progetto2_FaceDetectionPeopleCounting/img/facce.png", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
//display the image
using (InputArray iaImage = image.GetInputArray())
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
(iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
: "CPU",
detectionTime));
}
string Run(string fname)
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat(fname, ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
// listmMats.Add(image);
//
var aaa = new Image <Emgu.CV.Structure.Gray, byte>(fname);
trainingImages.Add(aaa);
Names_List_ID.Add(Names_List_ID.Count());
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
// richTextBox1.AppendText(Environment.NewLine + "aaa");
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
// richTextBox1.AppendText(Environment.NewLine + "bbb");
//display the image
using (InputArray iaImage = image.GetInputArray())
{
// recognizer.Train(image, );
var tempfile = Path.GetTempFileName() + ".jpg";
// richTextBox1.AppendText(Environment.NewLine + "ccc");
image.Save(tempfile);
// aaa.Save(tempfile);
// recognizer.Train(image, Names_List_ID.ToArray());
// listmMats.Add(iaImage);
//var a = new ImageViewer();
//a.BackgroundImage = ;
//a.ShowDialog();
//ImageViewer.Show(image, String.Format(
// // ImageViewer.Show(image, String.Format(
// "Completed face and eye detection using {0} in {1} milliseconds",
// (iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
// (iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
// : "CPU",
// detectionTime));
richTextBox1.AppendText(Environment.NewLine + "eee");
return(tempfile);
}
}
public static void GetFaceRectangle(String filePath, String baseFolder)
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat(filePath, ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
long detectionTime = 0;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
foreach (var face_file in new DirectoryInfo(baseFolder + "haarcascades").GetFiles("*face*"))
{
foreach (var eye_file in new DirectoryInfo(baseFolder + "haarcascades").GetFiles("*eye*"))
{
long currentDetectionTime = 0;
DetectFace.Detect(
image, face_file.FullName, eye_file.FullName,
faces, eyes,
out currentDetectionTime);
if (faces.Count != 0)
{
break;
}
eyes = new List <Rectangle>();
detectionTime += currentDetectionTime;
}
if (faces.Count != 0)
{
break;
}
}
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
//display the image
using (InputArray iaImage = image.GetInputArray())
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
(iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
: "CPU",
detectionTime));
}
static void Run()
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat("lena.jpg", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
long detectionTime;
/*
* List<Rectangle> faces = new List<Rectangle>();
* List<Rectangle> eyes = new List<Rectangle>();
*
* DetectFace.Detect(
* image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
* faces, eyes,
* out detectionTime);
*
* foreach (Rectangle face in faces)
* CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
* foreach (Rectangle eye in eyes)
* CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
* */
ProcessImage(image, out detectionTime);
//display the image
using (InputArray iaImage = image.GetInputArray())
{
var viewer = new ImageViewer(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda)
? "CUDA" : (iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL" : "CPU",
detectionTime));
viewer.ImageBox.ImageReload += (sender, e) =>
{
ProcessImage(e, out detectionTime);
//(sender as ImageBox)
};
Application.Run(viewer);
/*
* ImageViewer.Show(image, String.Format(
* "Completed face and eye detection using {0} in {1} milliseconds",
* (iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda)
* ? "CUDA": (iaImage.IsUMat && CvInvoke.UseOpenCL)? "OpenCL": "CPU",
* detectionTime));
* */
}
}
//private void Ruc()
//{
// try
// {
// _capture = new VideoCapture();
// }
// catch (Exception ex)
// {
// MetroMessageBox.Show(this, "Mensaje :" + ex.Message, "Error", MessageBoxButtons.OK, MessageBoxIcon.Error, 120);
// return;
// }
// Application.Idle += ProcessFrame;
//}
void Run()
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat("img1.jpg", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
FileInfo file = new FileInfo("haarcascade_frontalface_default.xml");
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
//display the image
InputArray iaImage = image.GetInputArray();
//ME CODE
pbCapture.Image = image;
txtDescription.Text = String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
(iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
: "CPU",
detectionTime);
//ImageViewer.Show(image, String.Format(
// "Completed face and eye detection using {0} in {1} milliseconds",
// (iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
// (iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL"
// : "CPU",
// detectionTime));
}
static void Run()
{
//读取指定路径的图片
IImage image = new UMat("images/IMG_1288.jpg", ImreadModes.Color); //UMat version
//定义人脸识别的时间
long detectionTime;
//人脸列表
List <Rectangle> faces = new List <Rectangle>();
//眼睛列表
List <Rectangle> eyes = new List <Rectangle>();
//开始识别
DetectFace.Detect(image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml", faces, eyes, out detectionTime);
//将识别后的所有面部，用矩形区域标注出来
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
/*
* 2017-10-19 不需要标注眼睛，比较混乱
*
* //将识别后的所有眼睛，用矩形区域标注出来
* foreach (Rectangle eye in eyes)
* {
* CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
* }
*/
using (InputArray iaImage = image.GetInputArray())
{
//获取人脸检测方式
String method = (iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" : (iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL" : "CPU";
//显示图片
ImageViewer.Show(image, String.Format("检测完毕，使用 {0} 模式， 耗时 {1} 毫秒", method, detectionTime));
}
}
private static void Run()
{
IImage image;
//Read the files as an 8-bit Bgr image
image = new UMat("lena.jpg", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
long detectionTime;
var faces = new List <Rectangle>();
var eyes = new List <Rectangle>();
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
out detectionTime);
foreach (var face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (var eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
//display the image
using (var iaImage = image.GetInputArray())
{
ImageViewer.Show(image, string.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda ? "CUDA"
: iaImage.IsUMat && CvInvoke.UseOpenCL ? "OpenCL"
: "CPU",
detectionTime));
}
}
private void SingDetectHaar(string fileName, string fileNameToSave)
{
try
{
IImage image = new UMat(fileName, ImreadModes.Color);
List <Rectangle> sings = new List <Rectangle>();
_singDetectorHaar = new SingDetectorMethodHaara();
long detectTime;
bool success = false;
_singDetectorHaar.Detect(image, _singFileCascad, sings, out detectTime);
foreach (Rectangle sing in sings)
{
CvInvoke.Rectangle(image, sing, new Bgr(Color.Red).MCvScalar, 2);
success = true;
}
using (InputArray iaImage = image.GetInputArray())
{
if (success)
{
timeChart.Invoke(new Action <int, double>(AddHaar), _haarActuation, detectTime);
SaveFileBmp(image.Bitmap, _dirHaar, _haarSingOnImageTag, fileNameToSave);
_haarActuation++;
}
}
_haarDetectTime += detectTime;
Console.WriteLine(String.Format("_haarActuation : {0}", _haarActuation));
haarLabel.Invoke(new Action <int, double>(AddHaarLabel), _haarActuation, _haarDetectTime);
}
catch
{
}
}
} // /////////////////////////////////////////////////////////////////////////////////////////////////////////
private void Run(UMat image) //!!!UMat
//IImage image;
//Read the files as an 8-bit Bgr image
//image = new UMat("lena.jpg", ImreadModes.Color); //UMat version
//image = new Mat("lena.jpg", ImreadModes.Color); //CPU version
{
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
// DetectFace.Detect(
// image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
// faces, eyes, out detectionTime);
DetectFace.DetectOnlyFace(
image, "haarcascade_frontalface_default.xml",
faces, out detectionTime,
FaceParam.ScaleFactor(txScaleFactor), FaceParam.MinNeighbors(txMinNeighbors), FaceParam.MinObjectSize(txMinObjectSize));
foreach (Rectangle face in faces)
{
CvInvoke.Rectangle(image, face, new Bgr(Color.Red).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
double r = gemor.put(faces.Count > 0);
if (r < 0.4 && (signal == Signal.yes || signal == Signal.nodef))
{
signal = Signal.no;
}
else if (r > 0.6 && (signal == Signal.no || signal == Signal.nodef))
{
signal = Signal.yes;
}
string sret = phases.Run(signal, r);
//lbDbgTimers.Text = sret;
MCvScalar color = new MCvScalar(255, 0, 255, 0);
CvInvoke.PutText(image, sret, new Point(2, 25), FontFace.HersheyComplexSmall, 1, color); //_grayFrame
if (signal == Signal.nodef && false)
{
if (faces.Count > 0)
{
using (InputArray iaImage = image.GetInputArray()) {
string sreport = String.Format(
"Completed face detection using {0} in {1} milliseconds. Rct={2} x {3} r={4}",
(iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda) ? "CUDA" :
(iaImage.IsUMat && CvInvoke.UseOpenCL) ? "OpenCL" : "CPU", detectionTime,
faces[0].Width, faces[0].Height, r);
Console.WriteLine(sreport);
}
}
else
{
Console.WriteLine(r.ToString());
}
}
} // ////////////////////////////////////////////////////////////////////////////////////////////////////////////