FaceRcognizer/FaceRecognizer/MainForm.cs

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 System.IO;

using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Structure;
using Emgu.CV.UI;
using Emgu.Util;
using Emgu.CV.Face;

namespace FaceRecognizer
{
    public partial class MainForm : Form
    {
        LBPHFaceRecognizer reconizer;
        CascadeClassifier faceCascade;
        Image<Gray, byte> temp;
        List<Image<Gray, byte>> imageList = new List<Image<Gray, byte>>();
        List<string> imageLabels = new List<string>();
        List<int> imageIndicies = new List<int>();
        Rectangle[] detectedFaces;
        string trainImagesFolder = Application.StartupPath + "\\Train";

        public MainForm()
        {
            InitializeComponent();
            console.AppendText("Main OK!");            
        }

        void train(string personName)
        {            
            faceCascade = new CascadeClassifier("haarcascade_frontalface_alt_tree.xml");
            reconizer = new LBPHFaceRecognizer();

            foreach (var file in Directory.GetFiles(trainImagesFolder))
            {
                if (file.EndsWith("jpg"))
                {
                    console.AppendText("found: " + Path.GetFileNameWithoutExtension(file));
                    temp = new Image<Gray, byte>(file);
                    console.AppendText("loaded: " + Path.GetFileNameWithoutExtension(file));
                    temp._EqualizeHist();

                    var detected_faces = faceCascade.DetectMultiScale(temp
                        , 1.1
                        , 3
                        , new Size(24, 24)
                        , Size.Empty);

                    if (detected_faces.Length == 0) { console.AppendText("lenght zero"); continue; }
                    temp.ROI = detected_faces[0];                        
                    temp = temp.Copy();
                    temp = temp.Resize(100, 100, Inter.Cubic);
                    imageList.Add(temp);
                    imageLabels.Add(Path.GetFileNameWithoutExtension(file));
                }
            }

            for (int i = 0; i < imageList.Count; i++)
            {
                imageIndicies.Add(i);
            }

            try
            {
                reconizer.Train(imageList.ToArray(), imageIndicies.ToArray());
                reconizer.Write(personName);
                console.AppendText("Training done!\nFile Name: " + personName);
            }
            catch (Exception e) { console.AppendText("Error: " + e.Message); }                            
        }

        void recognize(string personName)
        {
            console.AppendText("Recognizing " + personName + "from local photos");
            try
            {
                reconizer = new LBPHFaceRecognizer(1, 8, 8, 9, 65);
                reconizer = new LBPHFaceRecognizer();
                reconizer.Read(personName);

                foreach (var file in Directory.GetFiles(trainImagesFolder))
                {
                    if (file.EndsWith("jpg"))
                    {
                        Image<Gray, byte> temp2 = new Image<Gray, byte>(file);
                        pictureBox1.Image = temp2.Resize(pictureBox1.Width, pictureBox1.Height, Inter.Cubic).ToBitmap();
                        var result = reconizer.Predict(temp2);
                        console.AppendText(">>result:" + result.Label.ToString());
                    }
                }
            }
            catch (Exception e)
            {
                console.AppendText("Error: " + e.Message);
            }
        }

        private void TrainBtn_Click(object sender, EventArgs e)
        {
            train(nameTxtBx.Text);
        }

        private void RecconizeBtn_Click(object sender, EventArgs e)
        {
            recognize(nameTxtBx.Text);
        }

        private void console_TextChanged(object sender, EventArgs e)
        {
            console.AppendText("\n");
        }

        
    }
}