public MeshData Convert()
{
MeshData instance = new MeshData();
instance.Faces = Faces.ToArray();
instance.Strips = Strips.ToArray();
return(instance);
}
private void Timer_Tick(object sender, EventArgs e)
{
Webcam.Retrieve(Frame);
var imageFrame = Frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (imageFrame != null)
{
Rectangle[] faces = FaceDetection.DetectMultiScale(imageFrame, 1.3, 5);
if (faces.Any())
{
var processedImage = imageFrame.Copy(faces[0]).Resize(ProcessedImageWidth, ProcessedImageHeight, Inter.Cubic); // Will zoom into the rectangle it finds to only see that.
Faces.Add(processedImage.Mat);
IDs.Add(userId);
ScanCounter++;
OutputBox.AppendText($"{ScanCounter} Successful Scans Taken...{Environment.NewLine}");
OutputBox.ScrollToCaret();
}
}
}
else
{
FaceRecognition.Train(new VectorOfMat(Faces.ToArray()), new VectorOfInt(IDs.ToArray())); // Here we finally train on face and ID collection we just captures and is written to the pathfile "YMLPath"
FaceRecognition.Write(YMLPath);
Timer.Stop();
TimerCounter = 0;
//IDBox.Clear();
nameBox.Clear();
TrainButton.Enabled = !TrainButton.Enabled;
//IDBox.Enabled = !IDBox.Enabled;
nameBox.Enabled = !nameBox.Enabled;
OutputBox.AppendText($"Training Complete! {Environment.NewLine}");
//MessageBox.Show("Training Complete");
doneTraining = true;
Timer = new Timer();
Timer.Interval = 500; // ticks every 0.5 sec
Timer.Tick += Timer_Tick1; // this method gets called every time the timer fires.
Timer.Start();
}
}
private void Timer_Tick(object sender, EventArgs e)
{
WebCam.Retrieve(Frame);
var imageFrame = Frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (imageFrame != null)
{
//imageBox1.Image = imageFrame;
var faces = FaceDetection.DetectMultiScale(imageFrame, 1.3, 5);
if (faces.Count() > 0)
{
var procImage = imageFrame.Copy(faces[0]).Resize(ProcessImageWidth, ProcessImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
Faces.Add(procImage);
//Ids.Add(Convert.ToInt32(tbID.Text));
//Names.Add(tbName.Text);
ScanCounter++;
//tbOutput.AppendText($"{ScanCounter} successfull scabs taken .. {Environment.NewLine}");
//tbOutput.ScrollToCaret();
}
}
}
else
{
// train faces !!!
FaceRecognition.Train(Faces.ToArray(), Ids.ToArray());
FaceRecognition.Write(YMLPath);
//foreach (var face in Faces)
//{
//}
Timer.Stop();
TimerCounter = 0;
//tbID.Enabled = true;
//btnBeginTraining.Enabled = true;
//tbOutput.AppendText($"Taining Complete {Environment.NewLine}");
MessageBox.Show("Training completed");
}
}
private void Timer_Tick(object sender, EventArgs e)
{
Camera.Retrieve(Frame);
var ImgFrame = Frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (ImgFrame != null)
{
var faces = FaceDetection.DetectMultiScale(ImgFrame, 1.3, 5);
if (faces.Count() > 0)
{
var processedImage = ImgFrame.Copy(faces[0]).Resize(ProcessedImageWidth, ProcessedImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
Faces.Add(processedImage);
Ids.Add(Convert.ToInt32(IdBox.Text));
ScanCounter++;
OutputBox.AppendText($"{ScanCounter} Succesful Scans Taken...{Environment.NewLine}");
OutputBox.ScrollToCaret();
}
}
}
else
{
FacialRecognition.Train(Faces.ToArray(), Ids.ToArray());
FacialRecognition.Write(YMLPath);
Timer.Stop();
TimerCounter = 0;
btnTrain.Enabled = !btnTrain.Enabled;
IdBox.Enabled = !IdBox.Enabled;
OutputBox.AppendText($"Training Complete! {Environment.NewLine}");
MessageBox.Show("Training Complete");
}
}
public override void GetObjectData(SerializationInfo info, StreamingContext context)
{
base.GetObjectData(info, context);
info.AddValue("Faces", Faces.ToArray());
}
public MeshData GetMesh()
{
return(new MeshData(Faces.ToArray(), Vertices.ToArray(), VertexNomals.ToArray(), TextureCoords.ToArray()));
}