/// <summary>
/// Detects objects from an image and stores them as rectangles.
/// </summary>
private void Detect()
{
//areas of detected elements are described as rectangles
faces = new List <Rectangle>();
eyePairs = new List <Rectangle>();
leftEyes = new List <Rectangle>();
rightEyes = new List <Rectangle>();
noses = new List <Rectangle>();
mouths = new List <Rectangle>();
try
{
DetectFace.Detect(
image, "haarcascades\\frontalface_default.xml", "haarcascades\\eyes.xml", "haarcascades\\lefteye_2splits.xml",
"haarcascades\\righteye_2splits.xml", "haarcascades\\nose.xml", "haarcascades\\mouth.xml",
faces, eyePairs, leftEyes, rightEyes, noses, mouths,
out long detectionTime);
Console.WriteLine($"Image {FilePath} finished, detection time: {detectionTime} ms");
}
catch (Emgu.CV.Util.CvException e)
{
Console.WriteLine("\n" + e.Message);
Console.WriteLine("ERROR: Out of memory! Try to load smaller images!");
System.Windows.Forms.MessageBox.Show(new System.Windows.Forms.Form {
TopMost = true
},
"Out of memory! Try to load smaller images!", "Warning");
}
foreach (Rectangle f in faces)
{
CvInvoke.Rectangle(image, f, new Bgr(Color.Red).MCvScalar, lineThickness);
faceCount++;
}
foreach (Rectangle e in eyePairs)
{
CvInvoke.Rectangle(image, e, new Bgr(Color.Green).MCvScalar, lineThickness);
eyePairCount++;
}
foreach (Rectangle le in leftEyes)
{
CvInvoke.Rectangle(image, le, new Bgr(Color.Pink).MCvScalar, lineThickness);
leftEyeCount++;
}
foreach (Rectangle re in rightEyes)
{
CvInvoke.Rectangle(image, re, new Bgr(Color.Blue).MCvScalar, lineThickness);
rightEyeCount++;
}
foreach (Rectangle n in noses)
{
CvInvoke.Rectangle(image, n, new Bgr(Color.White).MCvScalar, lineThickness);
noseCount++;
}
foreach (Rectangle m in mouths)
{
CvInvoke.Rectangle(image, m, new Bgr(Color.Black).MCvScalar, lineThickness);
mouthCount++;
}
}
static void Run()
{
Mat image = new Mat("lena.jpg", LoadImageType.Color); //Read the files as an 8-bit Bgr image
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
//The cuda cascade classifier doesn't seem to be able to load "haarcascade_frontalface_default.xml" file in this release
//disabling CUDA module for now
bool tryUseCuda = false;
DetectFace.Detect(
image, "haarcascade_frontalface_default.xml", "haarcascade_eye.xml",
faces, eyes,
tryUseCuda,
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
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
(tryUseCuda && CudaInvoke.HasCuda) ? "GPU"
: 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));
}
static void Run()
{
IImage image;
Camera camera = new Camera();
camera.Show();
while (true)
{
image = camera.GetImage();
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.Green).MCvScalar, 2);
}
foreach (Rectangle eye in eyes)
{
CvInvoke.Rectangle(image, eye, new Bgr(Color.Blue).MCvScalar, 2);
}
camera.Refresh();
}
}
private Mat ApplyDetection(Mat image)
{
long detectionTime;
List <Rectangle> faces = new List <Rectangle>();
List <Rectangle> eyes = new List <Rectangle>();
//The cuda cascade classifier doesn't seem to be able to load "haarcascade_frontalface_default.xml" file in this release
//disabling CUDA module for now
bool tryUseCuda = false;
bool tryUseOpenCL = true;
DetectFace.Detect(
image, "Dlls\\EmguCv\\haarcascade_frontalface_default.xml", "Dlls\\EmguCv\\haarcascade_eye.xml",
faces, eyes,
tryUseCuda,
tryUseOpenCL,
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);
}
return(image);
}
public List <Bitmap> Search(List <Bitmap> images)
{
imageList.Clear();
for (int i = 0; i < images.Count; i++)
{
Image <Bgr, Byte> image = new Image <Bgr, byte>(images[i]);
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);
if (faces.Count > 0)
{
//foreach (Rectangle face in faces)
// image.Draw(face, new Bgr(Color.Red), 2);
// foreach (Rectangle eye in eyes)
// image.Draw(eye, new Bgr(Color.Blue), 2);
Image <Bgr, byte> resizedImage = image.Resize(300, 300, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR);
imageList.Add(resizedImage.ToBitmap());
}
//pictureboxview.Image = resizedImage.ToBitmap();
}
//Read the files as an 8-bit Bgr image
//Graphics g = Graphics.FromImage(image);
return(imageList);
//if (faces.Count > 0)
//{
// using (ExifReader reader = new ExifReader(@"C:\test\test4face.jpg"))
// {
// // Extract the tag data using the ExifTags enumeration
// DateTime datePictureTaken;
// if (reader.GetTagValue<DateTime>(ExifTags.DateTimeDigitized,
// out datePictureTaken))
// {
// // Do whatever is required with the extracted information
// String imageCommnets = string.Format("The picture was taken on {0}", datePictureTaken);
// MCvFont f = new MCvFont(Emgu.CV.CvEnum.FONT.CV_FONT_HERSHEY_PLAIN, 3.0, 3.0);
// image.Draw(imageCommnets, ref f, new Point(150, 150), new Emgu.CV.Structure.Bgr(255.0, 0, 0));
// }
// }
//}
//display the image
//Emgu.CV.UI.ImageViewer.Show(image, String.Format(
//"Completed face and eye detection using {0} in {1} milliseconds",
//GpuInvoke.HasCuda ? "GPU" : "CPU",
//detectionTime));
}
private void process(object sender, EventArgs args)
{
Image <Bgr, Byte> image = camera.RetrieveBgrFrame();
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)
{
image.Draw(face, new Bgr(Color.Red), 2);
}
foreach (Rectangle eye in eyes)
{
image.Draw(eye, new Bgr(Color.Blue), 2);
}
pictureBox1.Image = image.ToBitmap();
}
private void detectButton_Click(object sender, EventArgs e)
{
if (pictureBox.Image == null)
{
return;
}
if (loadFileCheckBox.Checked && openImageCheckBox.Checked)
{
pictureBox.Image = DetectFace.Detect((Mat)pictureBox.Image, _selectedAlgorithmIndex, eyesCheckBox.Checked, mouthCheckBox.Checked, noseCheckBox.Checked);
return;
}
_detect = !_detect;
if (!loadFileCheckBox.Checked)
{
detectButton.Text = _detect ? "Stop detection" : "Start detection";
}
}
static void ProcessImage(IImage image, out 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);
}
}
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));
}
}
public static Bitmap detectFace(Bitmap bitImage)
{
Image <Bgr, Byte> image = new Image <Bgr, byte>(bitImage); //Read the files as an 8-bit Bgr image
Console.WriteLine("face");
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)
{
image.Draw(face, new Bgr(Color.Red), 2);
}
foreach (Rectangle eye in eyes)
{
image.Draw(eye, new Bgr(Color.Blue), 2);
}
return(image.Bitmap);
}
private void ProcessFrame(object sender, EventArgs arg)
{
if (webcamCheckBox.Checked)
{
var frame = new Mat();
_capture.Retrieve(frame, 0);
pictureBox.Image = _detect
? DetectFace.Detect(frame, _selectedAlgorithmIndex, eyesCheckBox.Checked, mouthCheckBox.Checked,
noseCheckBox.Checked)
: frame;
}
else if (loadFileCheckBox.Checked)
{
var frame = _capture.QueryFrame();
pictureBox.Image = _detect
? DetectFace.Detect(frame, _selectedAlgorithmIndex, eyesCheckBox.Checked, mouthCheckBox.Checked,
noseCheckBox.Checked)
: frame;
Thread.Sleep((int)(1000.0 / _frameRate));
}
GC.Collect();
}
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));
}
}
static void Run()
{
Image <Bgr, Byte> image = new Image <Bgr, byte>("lena.jpg"); //Read the files as an 8-bit Bgr image
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)
{
image.Draw(face, new Bgr(Color.Red), 2);
}
foreach (Rectangle eye in eyes)
{
image.Draw(eye, new Bgr(Color.Blue), 2);
}
//display the image
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
GpuInvoke.HasCuda ? "GPU": "CPU",
detectionTime));
}
void Process()
{
/*var context = CIContext.FromOptions(null);
* var detector = CIDetector.CreateFaceDetector (context, true);
* var ciImage = CIImage.FromCGImage(imageView.Image.CGImage);
* CIFeature[] features = detector.FeaturesInImage(ciImage);
*
* using (Image<Bgr, Byte> image = new Image<Bgr, Byte>(imageView.Image.CGImage))
* {
* if (features != null)
* {
* foreach (CIFaceFeature face in features)
* {
* CGPoint pTest = FlipForBottomOrigin(face.LeftEyePosition, 960);
* image.Draw(new Rectangle((int)pTest.X, (int)pTest.Y, 200, 200), new Bgr(Color.Blue), 3);
* }
* }
*/
faces = new List <Rectangle>();
leftEyes = new List <Rectangle>();
rightEyes = new List <Rectangle>();
upperBodies = new List <Rectangle>();
lowerBodies = new List <Rectangle>();
mouths = new List <Rectangle>();
noses = new List <Rectangle>();
people = new List <Rectangle>();
bodies = new List <Rectangle>();
CGImage myImage = imageView.Image.CGImage;
long processingTime;
using (Image <Bgr, Byte> image = new Image <Bgr, Byte>(myImage))
{
CGRect p = imageView.Frame;
Dictionary <String, List <Rectangle> > recObjects = new Dictionary <string, List <Rectangle> >();
recObjects.Add("faces", faces);
recObjects.Add("leftEyes", leftEyes);
recObjects.Add("rightEyes", rightEyes);
recObjects.Add("upperBodies", upperBodies);
recObjects.Add("lowerBodies", lowerBodies);
recObjects.Add("mouths", mouths);
recObjects.Add("noses", noses);
recObjects.Add("people", people);
recObjects.Add("bodies", bodies);
Dictionary <String, String> facialFeatures = new Dictionary <string, string>();
facialFeatures.Add("face", "haarcascade_frontalface_alt.xml");
facialFeatures.Add("reye", "haarcascade_righteye_2splits.xml");
facialFeatures.Add("leye", "haarcascade_lefteye_2splits.xml");
facialFeatures.Add("mouth", "Mouth.xml");
facialFeatures.Add("nose", "Nariz.xml");
facialFeatures.Add("ubody", "haarcascade_mcs_upperbody.xml");
facialFeatures.Add("lbody", "haarcascade_lowerbody.xml");
facialFeatures.Add("body", "haarcascade_fullbody.xml");
DetectFace.Detect(
image.Mat,
facialFeatures,
recObjects,
out processingTime
);
/*foreach (Rectangle body in upperBodies)
* image.Draw(body, new Bgr(Color.LimeGreen), 3);
* foreach (Rectangle body in lowerBodies)
* image.Draw(body, new Bgr(Color.LimeGreen), 3);
* foreach (Rectangle body in bodies)
* image.Draw(body, new Bgr(Color.Yellow), 3);
* //foreach (Rectangle person in people)
* // image.Draw(person, new Bgr(Color.Blue), 5);
* foreach (Rectangle face in faces)
* image.Draw(face, new Bgr(Color.Red), 3);
* foreach (Rectangle eye in leftEyes)
* image.Draw(eye, new Bgr(Color.LightBlue), 3);
* foreach (Rectangle eye in rightEyes)
* image.Draw(eye, new Bgr(Color.DarkBlue), 3);
* foreach (Rectangle mouth in mouths)
* image.Draw(mouth, new Bgr(Color.Yellow), 3);
* foreach (Rectangle nose in noses)
* image.Draw(nose, new Bgr(Color.Violet), 3);*/
//using (Image<Bgr, Byte> resized = image.Resize((int)Window.Frame.Width, (int)Window.Frame.Height, Emgu.CV.CvEnum.Inter.Linear, true))
//{
//imageView.Frame = new RectangleF(PointF.Empty, resized.Size);
imageView.Image = image.ToUIImage();
if (faces.Count > 0)
{
using (CGImage cr = imageView.Image.CGImage.WithImageInRect(faces[0]))
{
UIImage cropped = UIImage.FromImage(cr);
//imageView.Image = cropped;
}
}
//}
//messageLabel.Text = String.Format("Face: (x: {0}, y: {1}, h: {2}, w: {3}", faces[0].X, faces[0].Y, faces[0].Height, faces[0].Width);
//messageLabel.Text = String.Format("Processing Time: {0} milliseconds.", processingTime);
//messageElement.GetImmediateRootElement().Reload(messageElement, UITableViewRowAnimation.Automatic);
imageView.SetNeedsDisplay();
}
}