public Algorithm ToAlgorithm(string PluginUUID, bool enabled = true, string elp = "")
{
var setEnabled = Enabled.HasValue ? Enabled.Value : enabled;
var setElp = ExtraLaunchParameters != null ? ExtraLaunchParameters : elp;
var ret = new Algorithm(PluginUUID, IDs.ToArray())
{
Enabled = setEnabled, ExtraLaunchParameters = setElp
};
return(ret);
}
private void Timer_Tick(object sender, EventArgs e)
{
webCam.Retrieve(frame);
var imageFrame = frame.ToImage <Gray, byte>();
if (TimerCounter < TimeLimit)
{
TimerCounter++;
if (imageFrame != null)
{
var faces = faceDetection.DetectMultiScale(imageFrame, 1.3, 5);
if (faces.Count() > 0)
{
var processedImage = imageFrame.Copy(faces[0]).Resize(ProcessedImageWidth, ProcessedImageHeight, Emgu.CV.CvEnum.Inter.Cubic);
Faces.Add(processedImage);
IDs.Add(Convert.ToInt32(IdBox.Text));
ScanCounter++;
OutPutBox.AppendText($"{ScanCounter} Success Scan Taken... {Environment.NewLine}");
OutPutBox.ScrollToCaret();
}
}
}
else
{
Mat[] faceImages = new Mat[Faces.Count];
faceImages = Faces.Select(c => c.Mat).ToArray();
faceRecognition.Train(faceImages, IDs.ToArray());
faceRecognition.Write(YMLPath);
timer.Stop();
Trainbottom.Enabled = !Trainbottom.Enabled;
IdBox.Enabled = !IdBox.Enabled;
OutPutBox.AppendText($"Training Complete!{Environment.NewLine}");
MessageBox.Show("Training Completed!");
PredictButton.Enabled = true;
}
}
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();
}
}
