无法从 emgucv 中的视频中检测到人脸

Posted 2023-03-16

【中文标题】无法从 emgucv 中的视频中检测到人脸

【英文标题】：Not able to detect face from video in emgucv

【发布时间】：2018-10-15 01:59:00

【问题描述】：

通过在 C# 中使用 Emgucv，我能够从图像中检测人脸，但无法从视频中检测人脸。在我的解决方案中，视频正在播放，但未检测到人脸。

我的代码如下：

namespace Emgucv33Apps

    public partial class FormFaceDetection : Form
    
        VideoCapture capture;
        bool Pause = false;

      //  Image<Bgr, byte> imgInput;
        public FormFaceDetection()
        
            InitializeComponent();
        

        private void openToolStripMenuItem_Click(object sender, EventArgs e)
        
            OpenFileDialog ofd = new OpenFileDialog();

            if (ofd.ShowDialog() == DialogResult.OK)
            
                capture = new VideoCapture(ofd.FileName);
                Mat m = new Mat();
                capture.Read(m);
                pictureBox1.Image = m.Bitmap;
            
        

        private void DetectFaceHaar(Image<Bgr, byte> img)
        
            try
            
                string facePath = Path.GetFullPath(@"../../data/haarcascade_frontalface_default.xml");
                string eyePath = Path.GetFullPath(@"../../data/haarcascade_eye.xml");

                CascadeClassifier classifierFace = new CascadeClassifier(facePath);
                CascadeClassifier classifierEye = new CascadeClassifier(eyePath);

                   var imgGray = img.Convert<Gray, byte>().Clone();
                   Rectangle[] faces = classifierFace.DetectMultiScale(imgGray, 1.1, 4);
                   foreach (var face in faces)
                   
                    img.Draw(face, new Bgr(0, 0, 255), 2);

                       imgGray.ROI = face;

                    Rectangle[]eyes=   classifierEye.DetectMultiScale(imgGray, 1.1, 4);
                    foreach (var eye in eyes)
                       
                           var e = eye;
                           e.X += face.X;
                           e.Y += face.Y;
                        img.Draw(e, new Bgr(0, 255, 0), 2);
                       
                   

                pictureBox1.Image = img.Bitmap;
                pictureBox2.Image = img.Bitmap;
            
               catch (Exception ex)
               
                   throw new Exception(ex.Message);
                
        

        private async void pauseToolStripMenuItem_Click(object sender, EventArgs e)
        
            if (capture == null)
            
                return;
            

            try
            
                while (true)
                
                    Mat m = new Mat();
                    capture.Read(m);

                    if (!m.IsEmpty)
                    
                        pictureBox1.Image = m.Bitmap;
                        DetectFaceHaar(m.ToImage<Bgr, byte>());
                        double fps = capture.GetCaptureProperty(Emgu.CV.CvEnum.CapProp.Fps);
                        await Task.Delay(1000 / Convert.ToInt32(fps));
                    
                    else
                    
                        break;
                    
                
            
            catch (Exception ex)
            
                MessageBox.Show(ex.Message);
            
        
    

提前致谢！！

【问题讨论】：

请描述您的具体和孤立问题。你试过调试这个吗？有什么例外吗？您的算法是否按预期工作？

【参考方案1】：

首先，您必须为此过程创建一个事件，并且您需要获取视频的每一帧并检查每一帧以进行人脸检测。使用 VideoCapture 类中的 QueryFrame 方法，您可以将每个帧作为图像处理并检测人脸。

例子

    private VideoCapture m_videoCapture;

    public MainWindow()
    
        InitializeComponent();
        try
        
            m_videoCapture = new VideoCapture("controlcam.avi");
            Application.Idle += onProcessFrame;
        
        catch (NullReferenceException ex)
        
            MessageBox.Show(ex.Message);
        
    

    private void onProcessFrame(Object sender, EventArgs e)
    
        Image<Bgr, Byte> frameImage = m_videoCapture.QueryFrame().ToImage<Bgr, Byte>();

        // Call your function or write your code here.
        DetectFaceHaar(frameImage);
    

    private void DetectFaceHaar(Image<Bgr, byte> img)
    
        try
        
            string facePath = Path.GetFullPath(@"../../data/haarcascade_frontalface_default.xml");
            string eyePath = Path.GetFullPath(@"../../data/haarcascade_eye.xml");

            CascadeClassifier classifierFace = new CascadeClassifier(facePath);
            CascadeClassifier classifierEye = new CascadeClassifier(eyePath);

            var imgGray = img.Convert<Gray, byte>().Clone();
            Rectangle[] faces = classifierFace.DetectMultiScale(imgGray, 1.1, 4);
            foreach (var face in faces)
            
                img.Draw(face, new Bgr(0, 0, 255), 2);

                imgGray.ROI = face;

                Rectangle[] eyes = classifierEye.DetectMultiScale(imgGray, 1.1, 4);
                foreach (var eye in eyes)
                
                    var e = eye;
                    e.X += face.X;
                    e.Y += face.Y;
                    img.Draw(e, new Bgr(0, 255, 0), 2);
                
            

            pictureBox1.Image = img.Bitmap;
            pictureBox2.Image = img.Bitmap;
        
        catch (Exception ex)
        
            throw new Exception(ex.Message);