I am making a face recognition and identification program using C# and EMGU. I got this error that I don't know why it occurs. The error occurs on (var result = recognizer.Predict(grayFacesResult);) This code should detect face, save images of detected faces and identify a person using the saved images. Please someone help me what I missed or what was the mistake here.
using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Face;
using Emgu.CV.CvEnum;
using System.IO;
using System.Threading;
using System.Diagnostics;
namespace Version1
{
public partial class Form1 : Form
{
#region Variables
// for camera capture
private Capture videoCapture = null;
private Image<Bgr, Byte> currentFrame = null;
Mat frame = new Mat();
// for toggle camera capture
private bool facesDetectionEnabled = false;
// for saving face images
bool EnabledSaveImage = false;
Image<Bgr, Byte> faceResult = null;
List<Image<Gray, Byte>> TrainedFaces = new List<Image<Gray, byte>>();
List<int> PersonsLabels = new List<int>();
// ???
private static bool isTrained = false;
EigenFaceRecognizer recognizer;
List<string> PersonsNames = new List<string>();
// load cascade file
CascadeClassifier faceCascadeClassifier = new CascadeClassifier("haarcascade_frontalface_alt.xml");
#endregion
public Form1()
{
InitializeComponent();
}
private void btnCapture_Click(object sender, EventArgs e)
{
// start camera capture
videoCapture = new Capture();
videoCapture.ImageGrabbed += ProcessFrame;
videoCapture.Start();
}
private void ProcessFrame(object sender, EventArgs e)
{
// video capture
videoCapture.Retrieve(frame, 0);
currentFrame = frame.ToImage<Bgr, Byte>().Resize(picCapture.Width, picCapture.Height, Inter.Cubic);
// render captured frame into the picture box picCapture2
picCapture.Image = currentFrame.Bitmap;
// toggle start camera capture
if (facesDetectionEnabled)
{
Mat grayImage = new Mat();
CvInvoke.CvtColor(currentFrame, grayImage, ColorConversion.Bgr2Gray);
CvInvoke.EqualizeHist(grayImage, grayImage);
Rectangle[] faces = faceCascadeClassifier.DetectMultiScale(grayImage, 1.1, 3, Size.Empty, Size.Empty);
if (faces.Length > 0)
{
foreach (var face in faces) {
// draw square around each faces
CvInvoke.Rectangle(currentFrame, face, new Bgr(Color.Red).MCvScalar, 2);
// display face on picDetected
Image<Bgr, Byte> resultImage = currentFrame.Convert<Bgr, Byte>();
resultImage.ROI = face;
picDetected.SizeMode = PictureBoxSizeMode.StretchImage;
picDetected.Image = resultImage.Bitmap;
if (EnabledSaveImage)
{
string path = Directory.GetCurrentDirectory() + @"\TrainedImages";
// check and create the directory if not exists
if (!Directory.Exists(path))
{
Directory.CreateDirectory(path);
}
// save 10 images
for (int i = 0; i < 10; i++)
{
resultImage.Resize(200, 200, Inter.Cubic).Save(path + @"\" + txtPersonName.Text + "_" + DateTime.Now.ToString("dd-mm-yyyy-hh-mm-ss") + ".jpg");
Thread.Sleep(1000);
}
// disable saving images
EnabledSaveImage = false;
if (btnAddPerson.InvokeRequired)
{
btnAddPerson.Invoke(new ThreadStart(delegate {
btnAddPerson.Enabled = true;
}));
}
// recognize face
Image<Gray, Byte> grayFacesResult = resultImage.Convert<Gray, Byte>().Resize(200, 200, Inter.Cubic);
var result = recognizer.Predict(grayFacesResult); // here is the error
if (result.Label > 0)
{
CvInvoke.PutText(currentFrame, PersonsNames[result.Label], new Point(face.X - 2, face.Y - 2), FontFace.HersheyComplex, 1.0, new Bgr(Color.Orange).MCvScalar);
CvInvoke.Rectangle(currentFrame, face, new Bgr(Color.Green).MCvScalar, 2);
}
else
{
CvInvoke.PutText(currentFrame, "Unknown", new Point(face.X - 2, face.Y - 2), FontFace.HersheyComplex, 1.0, new Bgr(Color.Orange).MCvScalar);
CvInvoke.Rectangle(currentFrame, face, new Bgr(Color.Green).MCvScalar, 2);
}
}
}
}
}
// render captured frame into the picture box picCapture2
picCapture2.Image = currentFrame.Bitmap;
}
private void btnDetect_Click(object sender, EventArgs e)
{
facesDetectionEnabled = true;
}
private void btnAddPerson_Click(object sender, EventArgs e)
{
btnSave.Enabled = false;
btnAddPerson.Enabled = true;
EnabledSaveImage = false;
}
private void btnSave_Click(object sender, EventArgs e)
{
btnSave.Enabled = true;
btnAddPerson.Enabled = false;
EnabledSaveImage = true;
}
private void btnTrain_Click(object sender, EventArgs e)
{
TrainImagesFromDir();
}
private bool TrainImagesFromDir()
{
int ImagesCount = 0;
int Threshold = -1;
TrainedFaces.Clear();
PersonsLabels.Clear();
PersonsNames.Clear();
try
{
string path = Directory.GetCurrentDirectory() + @"\TrainedImages";
string[] files = Directory.GetFiles(path, "*.jpg", SearchOption.AllDirectories);
foreach (var file in files)
{
Image<Gray, Byte> trainedImage = new Image<Gray, byte>(file);
TrainedFaces.Add(trainedImage);
PersonsLabels.Add(ImagesCount);
string name = file.Split('\\').Last().Split('_')[0];
PersonsNames.Add(name);
ImagesCount++;
Debug.WriteLine(ImagesCount + ". " + name);
}
recognizer = new EigenFaceRecognizer(ImagesCount, Threshold);
recognizer.Train(TrainedFaces.ToArray(), PersonsLabels.ToArray());
isTrained = true;
Debug.WriteLine(ImagesCount);
Debug.WriteLine(isTrained);
return isTrained;
}
catch (Exception ex)
{
isTrained = false;
MessageBox.Show("Error in Train Images: " + ex.Message);
return isTrained;
}
}
}
}
