我正在尝试开发一个应用程序，该应用程序可以通过网络摄像头检测一个人的上半身和下半身。我试着看emgu的人脸检测，下载了"haarcascade_upperbody.xml"和"haarcascade_lowerbody.xml"。我试图编写与给定的人脸检测相同的代码

但问题是它不会检测到我的身体，而且它不再是实时的。它延迟了 3 秒？

这是我的代码。我希望有人可以帮助我：

private void ProcessFrame(object sender, EventArgs arg)
    {
        Image<Bgr, Byte> ImageFrame = capture.QueryFrame();
        FittingBox.Image = ImageFrame;
        long detectionTime;
        List<Rectangle> upper = new List<Rectangle>();
        List<Rectangle> lower = new List<Rectangle>();
        Detect(ImageFrame,"haarcascade_upperbody.xml","haarcascade_lowerbody.xml",upper,lower,out detectionTime);
        foreach (Rectangle up in upper)
            ImageFrame.Draw(up, new Bgr(Color.Red), 2);
        foreach (Rectangle low in lower)
            ImageFrame.Draw(low, new Bgr(Color.Blue), 2);
    }

 public static void Detect(Image<Bgr, Byte> image, String upperFileName, String lowerFileName, List<Rectangle> upperbody, List<Rectangle> lowerbody, out long detectionTime)
    {
        Stopwatch watch;
        if (GpuInvoke.HasCuda)
        {
            using (GpuCascadeClassifier upper = new GpuCascadeClassifier(upperFileName))
            using (GpuCascadeClassifier lower = new GpuCascadeClassifier(lowerFileName))
            {
                watch = Stopwatch.StartNew();
                using (GpuImage<Bgr, Byte> gpuImage = new GpuImage<Bgr, byte>(image))
                using (GpuImage<Gray, Byte> gpuGray = gpuImage.Convert<Gray, Byte>())
                {
                    Rectangle[] upperRegion = upper.DetectMultiScale(gpuGray, 1.1, 10, Size.Empty);
                    upperbody.AddRange(upperRegion);
                    foreach (Rectangle f in upperRegion)
                    {
                        using (GpuImage<Gray, Byte> upperImg = gpuGray.GetSubRect(f))
                        {
                            using (GpuImage<Gray, Byte> clone = upperImg.Clone())
                            {
                                Rectangle[] lowerRegion = lower.DetectMultiScale(clone, 1.1, 10, Size.Empty);
                                foreach (Rectangle e in lowerRegion)
                                {
                                    Rectangle lowerRect = e;
                                    lowerRect.Offset(f.X, f.Y);
                                    lowerbody.Add(lowerRect);
                                }
                            }
                        }
                    }
                }
                watch.Stop();
            }
        }
        else
        {
            using (CascadeClassifier upper = new CascadeClassifier(upperFileName))
            using (CascadeClassifier lower = new CascadeClassifier(lowerFileName))
            {
                watch = Stopwatch.StartNew();
                using (Image<Gray, Byte> gray = image.Convert<Gray, Byte>())
                {
                    gray._EqualizeHist();
                    Rectangle[] upperDeteced = upper.DetectMultiScale(
                        gray,
                        1.1,
                        10,
                        new Size(50, 50),
                        Size.Empty);
                    foreach (Rectangle f in upperDeteced)
                    {
                        gray.ROI = f;
                        Rectangle[] lowerDetected = lower.DetectMultiScale(
                            gray,
                            1.1,
                            10,
                            new Size(50, 50),
                            Size.Empty);
                        gray.ROI = Rectangle.Empty;
                        foreach (Rectangle e in lowerDetected)
                        {
                            Rectangle lowerRect = e;
                            lowerRect.Offset(f.X, f.Y);
                            lowerbody.Add(lowerRect);
                        }
                    }
                }
                watch.Stop();
            }
        }
        detectionTime = watch.ElapsedMilliseconds;
    }