private void train_Click(object sender, EventArgs e)
{
//string line;
//DirectoryInfo dir = new DirectoryInfo("E:/libbs");
//dir.Create();
//StreamReader file = new StreamReader("SystemLibPath.txt");
//while ((line = file.ReadLine()) != null)
//{
// Console.WriteLine(line);
// FileInfo f = new FileInfo(line);
// File.Copy(line, dir.FullName + "/" + f.Name);
//}
EDRIPMain.getInstance().loadPredictor();
FolderBrowserDialog fbd = new FolderBrowserDialog();
DialogResult result = fbd.ShowDialog();
string[] files = { };
if (result == System.Windows.Forms.DialogResult.OK)
{
files = Directory.GetFiles(fbd.SelectedPath, "*", SearchOption.AllDirectories);
}
if (Methodology.SelectedIndex == 1)
{
EDRIPMainDistanceAndWrinkledBased.getInstance().TrainSystemForEmotionDistanceAndWrinkledBased(files);
}
else if (Methodology.SelectedIndex == 0)
{
EDRIPMainDistanceBased.getInstance().TrainSystemForEmotionDistancedBased(files);
}
else if (Methodology.SelectedIndex == 2)
{
EDRIPMainReducedDimensionsBased.getInstance().TrainSystemForEmotionReducedDimentionsBased(files);
}
else if (Methodology.SelectedIndex == 3)
{
OpticalflowViewTrain(files);
}
else if (Methodology.SelectedIndex == 4)
{
EDRIPHybridMethodologyBasedMain.getInstance().TrainSystemForEmotionHybrid(files);
}
}
private void ProcessFrame(object sender, EventArgs arg)
{
#region Face Detection Region
if (captureInProgress)
{
//FileInfo file = new FileInfo("E:\\training2\\1.jpg");
// Mat ImageMat = new Mat(file.FullName);
Mat ImageMat = capt.QueryFrame();
imageList.Images.Add(ImageMat.ToImage <Bgr, byte>().ToBitmap());
for (int j = 0; j < imageList.Images.Count; j++)
{
ListViewItem item = new ListViewItem();
item.ImageIndex = j;
imageListView.Items.Add(item);
}
string emotions = "";
if (Methodology.SelectedIndex == 1)
{
emotions = EDRIPMainDistanceAndWrinkledBased.getInstance().DetectEmotionsDistanceAndWrinkledBased(new Mat[] { ImageMat }, FDIPMAin.DetectFace(ImageMat)).outputResult;
}
else if (Methodology.SelectedIndex == 0)
{
emotions = EDRIPMainDistanceBased.getInstance().DetectEmotionsDistanceBased(new Mat[] { ImageMat }).outputResult;
}
if (emotions != null)
{
List <double> dfs = distributionsEmotions.dists;
foreach (var series in chart2.Series)
{
series.Points.Clear();
}
chart2.Series["Conf"].Points.AddXY("anger", dfs[0]);
chart2.Series["Conf"].Points.AddXY("smile", dfs[1]);
chart2.Series["Conf"].Points.AddXY("sad", dfs[2]);
chart2.Series["Conf"].Points.AddXY("surprise", dfs[3]);
chart2.Series["Conf"].Points.AddXY("neutral", dfs[4]);
chart2.Series["Conf"].Points.AddXY("fear", dfs[5]);
chart2.Series["Conf"].Points.AddXY("disgust", dfs[6]);
}
List <Rectangle> faces = new List <Rectangle>();
faces = FDIPMAin.DetectFace(ImageMat);
Mat shortImage = faces.Count > 0 ? new Mat(ImageMat, faces[0]) : ImageMat;
CvInvoke.Resize(shortImage, shortImage, new Size(320, 240), 0, 0, Inter.Linear);
shortImage = ImageMat;
//if(faces.Count>0&&i%3==0)
//{
// ImageMat.Save("E:\\dataset\\smile\\" + i/3 + ".jpg");
//}
//CvInvoke.Imshow("Orignal Face", shortImage);
faces = new List <Rectangle>();
faces.Add(new Rectangle(0, 0, shortImage.Width, shortImage.Height));
Image <Bgr, byte> I2 = shortImage.ToImage <Bgr, byte>();
GC.Collect();
Logger log = new Logger();
log.LogIntoFile(Log.logType.INFO, "message to be written");
//I2.Draw(emotions, new Point(10, 30), FontFace.HersheyPlain, 2.0, new Bgr(10, 0, 255));
imageBox1.Image = I2;
i++;
}
#endregion
else
{
imageBox1.Image = capt.QueryFrame();
}
if (FrameCount <= TotalFrames && Video.Checked)
{
trackBar1.Value = FrameCount;
FrameCount++;
}
else if (Video.Checked)
{
FrameCount = 0;
trackBar1.Value = FrameCount;
Play.Text = "Play";
Application.Idle -= ProcessFrame;
}
}