/*
 * Created by SharpDevelop.
 * User: Janphil Garay
 * Date: 16/02/2012
 * Time: 12:52 AM
 * 
 * To change this template use Tools | Options | Coding | Edit Standard Headers.
 */
using System;
using System.Collections.Generic;
using System.Drawing;
using System.IO;
using System.Windows.Forms;

using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Structure;

namespace FaceRecognition
{
	/// <summary>
	/// Description of frmEnrollment.
	/// </summary>
	public partial class frmEnrollment : Form
	{
		Image<Bgr, Byte> currentFrame;
        Capture grabber;
        HaarCascade face;
        HaarCascade eye;
        MCvFont font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
        Image<Gray, byte> result, TrainedFace = null;
        Image<Gray, byte> gray = null;
        List<Image<Gray, byte>> trainingImages = new List<Image<Gray, byte>>();
        List<string> labels= new List<string>();
        List<string> NamePersons = new List<string>();
        int ContTrain, NumLabels, t;
        string name, names = null;
		
		public frmEnrollment()
		{
			InitializeComponent();
			
			face = new HaarCascade("haarcascade_frontalface_alt_tree.xml");
            eye = new HaarCascade("haarcascade_eye.xml");
            try
            {
                string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
                string[] Labels = Labelsinfo.Split('%');
                NumLabels = Convert.ToInt16(Labels[0]);
                ContTrain = NumLabels;
                string LoadFaces;

                for (int tf = 1; tf < NumLabels+1; tf++)
                {
                    LoadFaces = "face" + tf + ".bmp";
                    trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
                    labels.Add(Labels[tf]);
                }
            
            }
            catch(Exception e)
            {
                MessageBox.Show("Nothing in binary database, please add at least a face", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
            }

		}
		
		void Button2Click(object sender, EventArgs e)
		{
			if (textBox1.Text.Equals(""))
            {
                MessageBox.Show("Please Enter Name before saving....");
                return;
            }
            else
            {
                try
                {

                    ContTrain = ContTrain + 1;


                    gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);

                   
                    MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
                    face,
                    1.2,
                    10,
                    Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
                    new Size(20, 20));

                    
                    foreach (MCvAvgComp f in facesDetected[0])
                    {
                        TrainedFace = currentFrame.Copy(f.rect).Convert<Gray, byte>();
                        break;
                    }

                    TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
                    trainingImages.Add(TrainedFace);
                    labels.Add(textBox1.Text);

                   
                    imageBox1.Image = TrainedFace;

                    File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");

                    for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
                    {
                        trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");
                        File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
                    }

                    MessageBox.Show(textBox1.Text + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
                }
                catch
                {
                    MessageBox.Show("Enable the face detection first", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
                }
            }

		}
		
		void FrmEnrollmentLoad(object sender, EventArgs e)
		{
			grabber = new Capture();
            grabber.QueryFrame();
            Application.Idle += new EventHandler(FrameGrabber);
		}
		void FrameGrabber(object sender, EventArgs e)
        {
            
            NamePersons.Add("");


            currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);

                    gray = currentFrame.Convert<Gray, Byte>();

                    MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
                  face,
                  1.2,
                  10,
                  Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
                  new Size(20, 20));

                    foreach (MCvAvgComp f in facesDetected[0])
                    {
                        t = t + 1;
                        result = currentFrame.Copy(f.rect).Convert<Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
                        currentFrame.Draw(f.rect, new Bgr(Color.Red), 2);


                        if (trainingImages.ToArray().Length != 0)
                        {
                        MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);

                         EigenObjectRecognizer recognizer = new EigenObjectRecognizer(
                           trainingImages.ToArray(),
                           labels.ToArray(),
                           5000,
                           ref termCrit);

                        name = recognizer.Recognize(result);

                        currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));

                        }

                            NamePersons[t-1] = name;
                            NamePersons.Add("");
                        /*                        
                        gray.ROI = f.rect;
                        MCvAvgComp[][] eyesDetected = gray.DetectHaarCascade(
                           eye,
                           1.1,
                           10,
                           Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
                           new Size(20, 20));
                        gray.ROI = Rectangle.Empty;

                        foreach (MCvAvgComp ey in eyesDetected[0])
                        {
                            Rectangle eyeRect = ey.rect;
                            eyeRect.Offset(f.rect.X, f.rect.Y);
                            currentFrame.Draw(eyeRect, new Bgr(Color.Blue), 2);
                        }
                         */

                    }
                        t = 0;

                    for (int nnn = 0; nnn < facesDetected[0].Length; nnn++)
                    {
                        names = names + NamePersons[nnn] + ", ";
                    }
                    
                    imageBoxFrameGrabber.Image = currentFrame;
                   
                    NamePersons.Clear();

                }

	}
}
