#dotnet – Detecting Faces using Cascades from the 🎦 camera feed in a WinForm using #OpenCV and #net5

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Hi !

Let’s do some face detection using one of the most popular methods: Haar Casacades (See references). I won’t write about Cascades, there are almost 20 years of online documentation available.

And, IMHO opinion code is much more useful that long writing, so let’s go there.

1st load the cascade definition file.

_faceCascade = new CascadeClassifier();
_faceCascade.Load("haarcascade_frontalface_default.xml");

And, once we grab the camera frame, let’s perform some face detection:

using var gray = new Mat();
Cv2.CvtColor(newImage, gray, ColorConversionCodes.BGR2GRAY);

var faces = _faceCascade.DetectMultiScale(gray, 1.3, 5);
foreach (var face in faces)
{
  Cv2.Rectangle(newImage, face, Scalar.Red);
  Cv2.PutText(newImage, "Face Cascade", new Point(face.Left + 2, face.Top + face.Width + 20), HersheyFonts.HersheyComplexSmall, 1, Scalar.Red, 2);
}

And, the full code is here

using System;
using System.Threading;
using System.Windows.Forms;
using OpenCvSharp;
using OpenCvSharp.Extensions;
using Point = OpenCvSharp.Point;
using Size = OpenCvSharp.Size;
namespace Demo07_WinFormFaceDetectionCascades
{
public partial class Form1 : Form
{
private bool _run = true;
private bool _doFaceDetection = false;
private VideoCapture _capture;
private Mat _image;
private Thread _cameraThread;
private bool _fps = false;
private CascadeClassifier _faceCascade;
public Form1()
{
InitializeComponent();
Load += Form1_Load;
Closed += Form1_Closed;
}
private void Form1_Closed(object sender, EventArgs e)
{
_cameraThread.Interrupt();
_capture.Release();
}
private void btnStart_Click(object sender, EventArgs e)
{
_run = true;
}
private void btnStop_Click(object sender, EventArgs e)
{
_run = false;
}
private void btnFaceDetectionCascades_Click(object sender, EventArgs e)
{
_doFaceDetection = !_doFaceDetection;
}
private void buttonFPS_Click(object sender, EventArgs e)
{
_fps = !_fps;
}
private void Form1_Load(object sender, EventArgs e)
{
_faceCascade = new CascadeClassifier();
_faceCascade.Load("haarcascade_frontalface_default.xml");
_capture = new VideoCapture(0);
_image = new Mat();
_cameraThread = new Thread(new ThreadStart(CaptureCameraCallback));
_cameraThread.Start();
}
private void CaptureCameraCallback()
{
while (true)
{
if (!_run) continue;
var startTime = DateTime.Now;
_capture.Read(_image);
if (_image.Empty()) return;
var imageRes = new Mat();
Cv2.Resize(_image, imageRes, new Size(320, 240));
var newImage = imageRes.Clone();
if (_doFaceDetection)
{
using var gray = new Mat();
Cv2.CvtColor(newImage, gray, ColorConversionCodes.BGR2GRAY);
var faces = _faceCascade.DetectMultiScale(gray, 1.3, 5);
foreach (var face in faces)
{
Cv2.Rectangle(newImage, face, Scalar.Red);
Cv2.PutText(newImage, "Face Cascade", new Point(face.Left + 2, face.Top + face.Width + 20),
HersheyFonts.HersheyComplexSmall, 1, Scalar.Red, 2);
}
}
if (_fps)
{
var diff = DateTime.Now – startTime;
var fpsInfo = $"FPS: Nan";
if (diff.Milliseconds > 0)
{
var fpsVal = 1.0 / diff.Milliseconds * 1000;
fpsInfo = $"FPS: {fpsVal:00}";
}
Cv2.PutText(newImage, fpsInfo, new Point(10, 20), HersheyFonts.HersheyComplexSmall, 1, Scalar.White);
}
var bmpWebCam = BitmapConverter.ToBitmap(imageRes);
var bmpEffect = BitmapConverter.ToBitmap(newImage);
pictureBoxWebCam.Image = bmpWebCam;
pictureBoxEffect.Image = bmpEffect;
}
}
}
}
view raw net5opencvdacedetcascades.cs hosted with ❤ by GitHub

That’s all for today!

Happy coding!

Greetings

El Bruno

More posts in my blog ElBruno.com.

More info in https://beacons.ai/elbruno

References

Net 5 and OpenCV

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1 comment

  1. Pingback: #dotnet – Detecting Faces using Cascades from the 🎦 camera feed in a WinForm using #OpenCV and #net5 — El Bruno – Mteheran's Blog

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