public BatchClassificationDialog(ref Klu klu, ref TrainingDataSet dataSet, ProcessOptions processOptions)
{
InitializeComponent();
_BackgroundWorker = new BackgroundWorker();
_BackgroundWorker.WorkerReportsProgress = true;
_BackgroundWorker.WorkerSupportsCancellation = true;
_BackgroundWorker.DoWork += new DoWorkEventHandler(DoWork);
_BackgroundWorker.RunWorkerCompleted += new RunWorkerCompletedEventHandler(RunWorkerCompleted);
_BackgroundWorker.ProgressChanged += new ProgressChangedEventHandler(ProgressChanged);
BrowseButton.IsEnabled = true;
CancelButton.IsEnabled = false;
ClassifyButton.IsEnabled = false;
_DataSet = dataSet;
_SelectedFiles = new ArrayList();
_ProcessOptions = processOptions;
// We want the images to be as less distorded as possible, so we disable all the overlays.
_ProcessOptions.DrawAnthropometricPoints = 0;
_ProcessOptions.DrawDetectionTime = 0;
_ProcessOptions.DrawFaceRectangle = 0;
_ProcessOptions.DrawSearchRectangles = 0;
_ProcessOptions.DrawFeaturePoints = 0;
_KLU = klu;
_FFP = new FaceFeaturePoints();
_TempBitmap = new System.Drawing.Bitmap(10, 10);
ExpressionsComboBox.ItemsSource = _DataSet.Expression;
ClassifyButton.Content = "Classify";
}
public BatchClassification(ref Klu klu, ref TrainingDataSet dataSet, ProcessOptions processOptions)
{
InitializeComponent();
_DataSet = dataSet;
_SelectedFiles = new ArrayList();
_ProcessOptions = processOptions;
// We want the images to be as less distorded as possible, so we disable all the overlays.
_ProcessOptions.DrawAnthropometricPoints = 0;
_ProcessOptions.DrawDetectionTime = 0;
_ProcessOptions.DrawFaceRectangle = 0;
_ProcessOptions.DrawSearchRectangles = 0;
_ProcessOptions.DrawFeaturePoints = 0;
_KLU = klu;
_FFP = new FaceFeaturePoints();
_TempBitmap = new System.Drawing.Bitmap(10, 10);
ExpressionsComboBox.ItemsSource = _DataSet.Expression;
ClassifyButton.Content = "Classify";
}
/// <summary>
/// The main entry point for this window.
/// </summary>
public MainWindow()
{
InitializeComponent();
Console.WriteLine("Loc: " + System.Reflection.Assembly.GetExecutingAssembly().Location);
try
{
_CurrentImagePathIndex = 0;
_ImagePathArray = new ArrayList();
_ProcessOptions = new ProcessOptions();
_FFP = new FaceFeaturePoints();
_ProcessOptions.DoEyeProcessing = 1;
_ProcessOptions.DoMouthProcessing = 1;
_ProcessOptions.DrawAnthropometricPoints = 0;
_ProcessOptions.DrawSearchRectangles = 0;
_ProcessOptions.DrawFaceRectangle = 1;
_ProcessOptions.DrawDetectionTime = 1;
_ProcessOptions.DrawFeaturePoints = 1;
_ProcessOptions.DoVisualDebug = 0;
#region Intialize encapsulated OpenCV subsystem
_KLU = new Klu();
_TempBitmap = new System.Drawing.Bitmap(10, 10);
// Create a Timer with a Normal Priority
_CaptureTimer = new DispatcherTimer(DispatcherPriority.ApplicationIdle, this.Dispatcher);
// Set the callback to just show the time ticking away
// NOTE: We are using a control so this has to run on
// the UI thread
_CaptureTimer.Tick += new EventHandler(
delegate(object s, EventArgs a)
{
_KLU.ProcessCaptureImage(ref _ProcessOptions, ref _FFP);
// Ensure the image (bitmap) we are writing to has the correct dimensions
int width = 0, height = 0;
_KLU.GetLastProcessedImageDims(ref width, ref height);
if (_TempBitmap.Width != width || _TempBitmap.Height != height)
{
Console.WriteLine("Need to resize the _TempBitmap to " + width + "x" + height);
_TempBitmap.Dispose();
GC.Collect();
_TempBitmap = new System.Drawing.Bitmap(width, height);
}
_KLU.GetLastProcessedImage(ref _TempBitmap);
_KLU.SetWpfImageFromBitmap(ref image1, ref _TempBitmap);
//_KLU.SetImageBrushFromBitmap(ref imageBrush, ref _TempBitmap);
}
);
#endregion
#region "Connect" to database
_TAM = new TableAdapterManager();
_DataSet = new TrainingDataSet();
// Load data from SQL database and fill our DataSet
_TAM.ExpressionTableAdapter = new ExpressionTableAdapter();
_TAM.TrainingTableAdapter = new TrainingTableAdapter();
LoadData();
#endregion
}
catch (Exception ex)
{
MessageBox.Show(ex.Message, "Error!", MessageBoxButton.OK, MessageBoxImage.Error);
}
}
public static void AddTrainingData(ref TrainingDataSet dataSet, ref FaceFeaturePoints ffp, int expressionOID, ref System.Drawing.Bitmap picture)
{
// Convert facial coordinates to relative face rectangle coordinates.
// We do this because we are not interested in absolute coordinates but in quality of the face.
int x = ffp.FaceRectangle.X;
int y = ffp.FaceRectangle.Y;
int w = ffp.FaceRectangle.Width;
int h = ffp.FaceRectangle.Height;
// Calculate the eye distance (in relative coordinates
float dx = i2r(ffp.RightEye.EyeCenter.X, x, w) - i2r(ffp.LeftEye.EyeCenter.X, x, w);
float dy = i2r(ffp.RightEye.EyeCenter.Y, y, h) - i2r(ffp.LeftEye.EyeCenter.Y, y, h);
//float dx = i2r(ffp.RightEye.EyeCenter.X - ffp.LeftEye.EyeCenter.X, x, w);
//float dy = i2r(ffp.RightEye.EyeCenter.Y - ffp.LeftEye.EyeCenter.Y, y, h);
float eyeDist = (float)Math.Sqrt(dx * dx + dy * dy);
// Construct thumbnail
const int thumbnailWidth = 50;
const int thumbnailHeight = 50;
System.Drawing.Rectangle faceRect = new System.Drawing.Rectangle(x, y, w, h);
System.Drawing.Bitmap faceImg = picture.Clone(faceRect, picture.PixelFormat);
System.Drawing.Image.GetThumbnailImageAbort tc = new System.Drawing.Image.GetThumbnailImageAbort(ThumbnailCallback);
System.Drawing.Image thumbnail = faceImg.GetThumbnailImage(thumbnailWidth, thumbnailHeight, tc, IntPtr.Zero);
System.IO.MemoryStream ms = new System.IO.MemoryStream();
thumbnail.Save(ms, System.Drawing.Imaging.ImageFormat.Png);
TrainingDataSet.TrainingRow row = dataSet.Training.NewTrainingRow();
row.ExpressionOID = expressionOID;
row.LipCornerLeftX = i2r(ffp.Mouth.LipCornerLeft.X, x, w);
row.LipCornerLeftY = i2r(ffp.Mouth.LipCornerLeft.Y, y, h);
row.LipCornerRightX = i2r(ffp.Mouth.LipCornerRight.X, x, w);
row.LipCornerRightY = i2r(ffp.Mouth.LipCornerRight.Y, y, h);
row.LipUpLeftX = i2r(ffp.Mouth.LipUpLeft.X, x, w);
row.LipUpLeftY = i2r(ffp.Mouth.LipUpLeft.Y, y, h);
row.LipUpCenterX = i2r(ffp.Mouth.LipUpCenter.X, x, w);
row.LipUpCenterY = i2r(ffp.Mouth.LipUpCenter.Y, y, h);
row.LipUpRightX = i2r(ffp.Mouth.LipUpRight.X, x, w);
row.LipUpRightY = i2r(ffp.Mouth.LipUpRight.Y, y, h);
row.LipUpRightX = i2r(ffp.Mouth.LipBottomLeft.X, x, w);
row.LipUpRightY = i2r(ffp.Mouth.LipBottomLeft.Y, y, h);
row.LipBottomCenterX = i2r(ffp.Mouth.LipBottomCenter.X, x, w);
row.LipBottomCenterY = i2r(ffp.Mouth.LipBottomCenter.Y, y, h);
row.LipBottomRightX = i2r(ffp.Mouth.LipBottomRight.X, x, w);
row.LipBottomRightY = i2r(ffp.Mouth.LipBottomRight.Y, y, h);
row.LipBottomLeftX = i2r(ffp.Mouth.LipBottomLeft.X, x, w);
row.LipBottomLeftY = i2r(ffp.Mouth.LipBottomLeft.Y, y, h);
row.EyeDistance = eyeDist;
row.LeftEyeCenterX = i2r(ffp.LeftEye.EyeCenter.X, x, w);
row.LeftEyeCenterY = i2r(ffp.LeftEye.EyeCenter.Y, y, h);
row.LeftLidBottomX = i2r(ffp.LeftEye.LidBottomCenter.X, x, w);
row.LeftLidBottomY = i2r(ffp.LeftEye.LidBottomCenter.Y, y, h);
row.LeftLidCornerLeftX = i2r(ffp.LeftEye.LidCornerLeft.X, x, w);
row.LeftLidCornerLeftY = i2r(ffp.LeftEye.LidCornerLeft.Y, y, h);
row.LeftLidCornerRightX = i2r(ffp.LeftEye.LidCornerRight.X, x, w);
row.LeftLidCornerRightY = i2r(ffp.LeftEye.LidCornerRight.Y, y, h);
row.LeftLidUpX = i2r(ffp.LeftEye.LidUpCenter.X, x, w);
row.LeftLidUpY = i2r(ffp.LeftEye.LidUpCenter.Y, y, h);
row.RightEyeCenterX = i2r(ffp.RightEye.EyeCenter.X, x, w);
row.RightEyeCenterY = i2r(ffp.RightEye.EyeCenter.Y, y, h);
row.RightLidBottomX = i2r(ffp.RightEye.LidBottomCenter.X, x, w);
row.RightLidBottomY = i2r(ffp.RightEye.LidBottomCenter.Y, y, h);
row.RightLidCornerLeftX = i2r(ffp.RightEye.LidCornerLeft.X, x, w);
row.RightLidCornerLeftY = i2r(ffp.RightEye.LidCornerLeft.Y, y, h);
row.RightLidCornerRightX = i2r(ffp.RightEye.LidCornerRight.X, x, w);
row.RightLidCornerRightY = i2r(ffp.RightEye.LidCornerRight.Y, y, h);
row.RightLidUpX = i2r(ffp.RightEye.LidUpCenter.X, x, w);
row.RightLidUpY = i2r(ffp.RightEye.LidUpCenter.Y, y, h);
row.MouthCenterX = i2r(ffp.Mouth.MouthCenter.Y, y, h);
row.MouthCenterY = i2r(ffp.Mouth.MouthCenter.Y, y, h);
row.Thumbnail = ms.ToArray();
dataSet.Training.AddTrainingRow(row);
}
