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net5opencvdacedetdnn.cs
using System;
using System.Threading;
using System.Windows.Forms;
using OpenCvSharp;
using OpenCvSharp.Dnn;
using OpenCvSharp.Extensions;
using Point = OpenCvSharp.Point;
using Size = OpenCvSharp.Size;
namespace Demo08_WinFormFaceDetectionDNN
{
public partial class Form1 : Form
{
private bool _run = false;
private bool _doFaceDetection = false;
private VideoCapture _capture;
private Mat _image;
private Thread _cameraThread;
private bool _fps = false;
private Net _faceNet;
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 btnFDDNN_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)
{
// download model and prototxt from https://github.com/spmallick/learnopencv/tree/master/FaceDetectionComparison/models
const string configFile = "deploy.prototxt";
const string faceModel = "res10_300x300_ssd_iter_140000_fp16.caffemodel";
_faceNet = CvDnn.ReadNetFromCaffe(configFile, faceModel);
_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)
{
int frameHeight = newImage.Rows;
int frameWidth = newImage.Cols;
using var blob = CvDnn.BlobFromImage(newImage, 1.0, new Size(300, 300),
new Scalar(104, 117, 123), false, false);
_faceNet.SetInput(blob, "data");
using var detection = _faceNet.Forward("detection_out");
using var detectionMat = new Mat(detection.Size(2), detection.Size(3), MatType.CV_32F,
detection.Ptr(0));
for (int i = 0; i < detectionMat.Rows; i++)
{
float confidence = detectionMat.At<float>(i, 2);
if (confidence > 0.7)
{
int x1 = (int)(detectionMat.At<float>(i, 3) * frameWidth);
int y1 = (int)(detectionMat.At<float>(i, 4) * frameHeight);
int x2 = (int)(detectionMat.At<float>(i, 5) * frameWidth);
int y2 = (int)(detectionMat.At<float>(i, 6) * frameHeight);
Cv2.Rectangle(newImage, new Point(x1, y1), new Point(x2, y2), Scalar.Green);
Cv2.PutText(newImage, "Face Dnn", new Point(x1 + 2, y2 + 20),
HersheyFonts.HersheyComplexSmall, 1, Scalar.Green, 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(imageRes, 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;
}
}
}
}
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