人脸识别EmguCV代码,CSharp代码库,德仔网

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【CSharp】人脸识别EmguCV
作者:水牛叔叔 / 发布于2014/8/4/ 1111
c# 人脸识别EmguCV动态人脸检测。中文名字识别识别后语音播报

	using System;
	using System.Collections.Generic;
	using System.Drawing;
	using System.Windows.Forms;
	using System.Speech.Synthesis;
	using System.Threading;
	using Emgu.CV;
	using Emgu.CV.Structure;
	using Emgu.CV.CvEnum;
	using System.IO;
	using Emgu.CV.UI;
	
	namespace MultiFaceRec
	{
	 public partial class FrmPrincipal : Form
	 {
	 //Declararation of all variables, vectors and haarcascades
	 Image<Bgr, Byte> currentFrame;
	 Capture grabber;
	 HaarCascade face;
	 HaarCascade eye;
	 MCvFont font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
	 Image<Gray, byte> result, TrainedFace = null;
	 Image<Gray, byte> gray = null;
	 List<Image<Gray, byte>> trainingImages = new List<Image<Gray, byte>>();
	 List<string> labels = new List<string>();
	 List<string> NamePersons = new List<string>();
	 int ContTrain, NumLabels, t;
	 string name, namess = null, names = null;
	 Dictionary<string, Rectangle> foundPeople = new Dictionary<string, Rectangle>();
	 float xfactor;
	 float yfactor;
	
	 public FrmPrincipal()
	 {
	 InitializeComponent();
	
	 try
	 {
	 //Initialize the capture device
	 grabber = new Capture();
	 grabber.QueryFrame();
	 //Initialize the FrameGraber event
	 Application.Idle += new EventHandler(FrameGrabber);
	 if (grabber != null)
	 grabber.FlipHorizontal = !grabber.FlipHorizontal;
	 button1.Enabled = false;
	 }
	 catch (Exception)
	 {
	 MessageBox.Show("没有摄像头！");
	 }
	
	 //Load haarcascades for face detection
	 face = new HaarCascade("haarcascade_frontalface_default.xml");
	 //eye = new HaarCascade("haarcascade_eye.xml");
	 try
	 {
	 //Load of previus trainned faces and labels for each image
	 string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
	 string[] Labels = Labelsinfo.Split('%');
	 NumLabels = Convert.ToInt16(Labels[0]);
	 ContTrain = NumLabels;
	 string LoadFaces;
	
	 for (int tf = 1; tf < NumLabels + 1; tf++)
	 {
	 LoadFaces = "face" + tf + ".bmp";
	 trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
	 labels.Add(Labels[tf]);
	 }
	 }
	 catch (Exception e)
	 {
	 //MessageBox.Show(e.ToString());
	 MessageBox.Show("Nothing in binary database, please add at least a face", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
	 }
	 }
	
	
	 private void button1_Click(object sender, EventArgs e)
	 {
	 try
	 {
	 Application.Idle += new EventHandler(FrameGrabber);
	 button1.Enabled = false;
	 }
	 catch (Exception)
	 {
	 }
	 }
	 private void button3_Click(object sender, EventArgs e)
	 {
	 try
	 {
	 Application.Idle -= new EventHandler(FrameGrabber);
	 button1.Enabled = true;
	 }
	 catch (Exception)
	 {
	 }
	 }
	 private void button2_Click(object sender, System.EventArgs e)
	 {
	 try
	 {
	 //Trained face counter
	 ContTrain = ContTrain + 1;
	
	 //Get a gray frame from capture device
	 gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
	
	 //Face Detector
	 MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
	 face,
	 1.2,
	 10,
	 Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
	 new Size(20, 20));
	
	 //Action for each element detected
	 foreach (MCvAvgComp f in facesDetected[0])
	 {
	 TrainedFace = currentFrame.Copy(f.rect).Convert<Gray, byte>();
	 break;
	 }
	
	 //resize face detected image for force to compare the same size with the
	 //test image with cubic interpolation type method
	 TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
	 trainingImages.Add(TrainedFace);
	 labels.Add(textBox1.Text);
	
	 //Show face added in gray scale
	 imageBox1.Image = TrainedFace;
	
	 //Write the number of triained faces in a file text for further load
	 File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");
	
	 //Write the labels of triained faces in a file text for further load
	 for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
	 {
	 trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");
	 File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
	 }
	
	 MessageBox.Show(textBox1.Text + "&acute;s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
	 }
	 catch
	 {
	 MessageBox.Show("Enable the face detection first", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
	 }
	 }
	
	 /// <summary>
	 /// 人脸识别与检测
	 /// </summary>
	 /// <param name="sender"></param>
	 /// <param name="e"></param>
	 private void FrameGrabber(object sender, EventArgs e)
	 {
	 label3.Text = "0";
	 //label4.Text = "";
	 NamePersons.Add("");
	
	
	 //Get the current frame form capture device
	 currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
	
	 //Convert it to Grayscale
	 gray = currentFrame.Convert<Gray, Byte>();
	
	 //Face Detector
	 MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
	 face,
	 1.2,
	 10,
	 Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
	 new Size(20, 20));
	
	 foundPeople.Clear();
	 //Action for each element detected
	 foreach (MCvAvgComp f in facesDetected[0])
	 {
	 t = t + 1;
	 result = currentFrame.Copy(f.rect).Convert<Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
	 //draw the face detected in the 0th (gray) channel with red color
	 currentFrame.Draw(f.rect, new Bgr(Color.Red), 2);
	
	
	 if (trainingImages.ToArray().Length != 0)
	 {
	 //TermCriteria for face recognition with numbers of trained images like maxIteration
	 MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);
	
	 //Eigen face recognizer
	 EigenObjectRecognizer recognizer = new EigenObjectRecognizer(
	 trainingImages.ToArray(),
	 labels.ToArray(),
	 5000,
	 ref termCrit);
	
	 name = recognizer.Recognize(result);
	 foundPeople[name] = f.rect;
	
	 //Draw the label for each face detected and recognized
	 //currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));
	
	 }
	
	 NamePersons[t - 1] = name;
	 NamePersons.Add("");
	
	
	 //Set the number of faces detected on the scene
	 label3.Text = facesDetected[0].Length.ToString();
	
	 }
	 t = 0;
	
	 //Names concatenation of persons recognized
	 for (int nnn = 0; nnn < facesDetected[0].Length; nnn++)
	 {
	 names = names + NamePersons[nnn] + ", ";
	 }
	 //Show the faces procesed and recognized
	 imageBoxFrameGrabber.Image = currentFrame;
	 label4.Text = names;
	 namess = names;
	 names = "";
	 //Clear the list(vector) of names
	 NamePersons.Clear();
	
	 }
	
	 /// <summary>
	 /// 中文显示名字
	 /// </summary>
	 /// <param name="sender"></param>
	 /// <param name="e"></param>
	 private void imageBoxFrameGrabber_Paint(object sender, PaintEventArgs e)
	 {
	 Font ff = new Font("宋体", 15, FontStyle.Bold);
	
	 if (foundPeople.Count > 0)
	 {
	 // 缩放
	 xfactor = (float)imageBoxFrameGrabber.Width / (float)currentFrame.Bitmap.Width;
	 yfactor = (float)imageBoxFrameGrabber.Height / (float)currentFrame.Bitmap.Height;
	
	 foreach (string n in foundPeople.Keys)
	 {
	 e.Graphics.DrawString(
	 n,
	 ff,
	 Brushes.LightGreen,
	 foundPeople[n].X * xfactor,
	 foundPeople[n].Y * yfactor - 30);
	 }
	 }
	
	 e.Graphics.DrawString(
	 "识别人数：" + label3.Text.ToString(),
	 this.Font,
	 Brushes.Red,
	 0, 0);
	
	 e.Graphics.DrawString(
	 foundPeople.Count.ToString(),
	 this.Font,
	 Brushes.BlanchedAlmond,
	 0, 20);
	 }
	
	 private Thread th;
	 private void label4_TextChanged(object sender, EventArgs e)
	 {
	
	 th = new Thread(new ThreadStart(SpeechSound));
	 th.Start();
	 }
	
	 /// <summary>
	 /// 语音播报
	 /// </summary>
	 private void SpeechSound()
	 {
	 if (string.IsNullOrEmpty(label4.Text))
	 {
	 return;
	 }
	
	 SpeechSynthesizer sp = new SpeechSynthesizer();
	 if (namess == label4.Text)
	 {
	 Thread.Sleep(2500);
	 if (foundPeople.Count == 1)
	 sp.SpeakAsync(label4.Text + "你好");
	 if (foundPeople.Count > 1)
	 sp.SpeakAsync(label4.Text + "你们好");
	 }
	 namess = null;
	 th.Abort();
	 }
	
	 private void FrmPrincipal_FormClosing(object sender, FormClosingEventArgs e)
	 {
	 th.Abort();
	 }
	 }
	}
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