【人脸识别EmguCV】动态人脸检测。中文名字识别

**wtujoxk** · 发表于 2014-8-8 09:44:47

人脸识别EmguCV
动态人脸检测。中文名字识别
识别后语音播报

emgu支持库，装完后需配置下环境
http://sourceforge.net/projects/emgucv/

[C#] 纯文本查看 复制代码

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 + "´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();
 
        ｝
    }
}

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