private static void Run(string filename)
{
int timePerFrame;
VideoCapture capture;
if (!string.IsNullOrWhiteSpace(filename) && File.Exists(filename))
{
// If filename exists, use that as a source of video.
capture = InitializeVideoCapture(filename);
// Allow just enough time to paint the frame on the window.
timePerFrame = 1;
}
else
{
// Otherwise use the webcam.
capture = InitializeCapture();
// Time required to wait until next frame.
timePerFrame = (int)Math.Round(1000 / capture.Fps);
}
// Input was not initialized.
if (capture == null)
{
Console.ReadKey();
return;
}
// Initialize face detection algorithm.
CascadeClassifier haarCascade = InitializeFaceClassifier();
// List of simple face filtering algorithms.
var filtering = new SimpleFaceFiltering(new IFaceFilter[]
{
new TooSmallFacesFilter(20, 20)
});
// List of simple face tracking algorithms.
var trackingChanges = new SimpleFaceTracking(new IFaceTrackingChanged[]
{
new TrackNumberOfFaces(),
new TrackDistanceOfFaces {
Threshold = 2000
}
});
// Open a new window via OpenCV.
using (Window window = new Window("capture"))
{
using (Mat image = new Mat())
{
while (true)
{
// Get current frame.
capture.Read(image);
if (image.Empty())
{
continue;
}
// Detect faces
var faces = DetectFaces(haarCascade, image);
// Filter faces
var state = faces.ToImageState();
state = filtering.FilterFaces(state);
// Determine change
var hasChange = trackingChanges.ShouldUpdateRecognition(state);
if (hasChange)
{
Console.WriteLine("Changes detected...");
// Identify faces if changed and previous identification finished.
if (_faceRecognitionTask == null && !string.IsNullOrWhiteSpace(FaceSubscriptionKey))
{
_faceRecognitionTask = StartRecognizing(image);
}
}
using (var renderedFaces = RenderFaces(state, image))
{
// Update popup window.
window.ShowImage(renderedFaces);
}
// Wait for next frame and allow Window to be repainted.
Cv2.WaitKey(timePerFrame);
}
}
}
}
private static void Run(string filename)
{
string personGroupId = "nbgaccn";
_faceClient.PersonGroup.CreateAsync(personGroupId, "NBG Accenture");
Task <Person> ZachariasSiatris = _faceClient.PersonGroupPerson.CreateAsync(personGroupId, "Zacharias Siatris");
List <ZSPerson> ZSPersonsList = new List <ZSPerson>();
//Zacharias Siatris
ZSPerson zachariasSiatris = new ZSPerson();
zachariasSiatris.name = "Zacharias Siatris";
zachariasSiatris.company = " Accenture Inc.";
zachariasSiatris.description = " ROTATING TO THE NEW!!";
zachariasSiatris.id = " 1123456979";
zachariasSiatris.isDangerous = true;
zachariasSiatris.projectTeam = " AI - Innovation Team";
zachariasSiatris.nbgSection = " In the \"NEW\" Management";
zachariasSiatris.photoPathId = @"C:\Users\zacharias.siatris\Desktop\FaceAppPhotos\ZachariasSiatris\ZackID.jpg";
ZSPersonsList.Add(zachariasSiatris);
const string zachariasSiatrisImageDir = @"C:\Users\zacharias.siatris\Desktop\FaceAppPhotos\ZachariasSiatris";
foreach (string imagePath in Directory.GetFiles(zachariasSiatrisImageDir, "*.jpg"))
{
using (Stream s = File.OpenRead(imagePath))
{
_faceClient.PersonGroupPerson.AddFaceFromStreamAsync(
personGroupId, ZachariasSiatris.Result.PersonId, s);
}
}
_faceClient.PersonGroup.TrainAsync(personGroupId);
TrainingStatus trainingStatus = null;
while (true)
{
trainingStatus = _faceClient.PersonGroup.GetTrainingStatusAsync(personGroupId).Result;
if (trainingStatus.Status != TrainingStatusType.Running)
{
break;
}
Task.Delay(1000);
}
int timePerFrame;
VideoCapture capture;
if (!string.IsNullOrWhiteSpace(filename) && File.Exists(filename))
{
// If filename exists, use that as a source of video.
capture = InitializeVideoCapture(filename);
// Allow just enough time to paint the frame on the window.
timePerFrame = 1;
}
else
{
// Otherwise use the webcam.
capture = InitializeCapture(0);
// Time required to wait until next frame.
timePerFrame = (int)Math.Round(1000 / capture.Fps);
}
// Input was not initialized.
if (capture == null)
{
Console.ReadKey();
return;
}
// Initialize face detection algorithm.
CascadeClassifier haarCascade = InitializeFaceClassifier();
// List of simple face filtering algorithms.
var filtering = new SimpleFaceFiltering(new IFaceFilter[]
{
new TooSmallFacesFilter(20, 20)
});
// List of simple face tracking algorithms.
var trackingChanges = new SimpleFaceTracking(new IFaceTrackingChanged[]
{
new TrackNumberOfFaces(),
new TrackDistanceOfFaces {
Threshold = 2000
}
});
InfoPanel panel = new InfoPanel();
panel.Show();
// Open a new window via OpenCV.
using (Window window = new Window("capture"))
{
using (Mat image = new Mat())
{
while (true)
{
// Get current frame.
capture.Read(image);
if (image.Empty())
{
continue;
}
// Detect faces
var faces = DetectFaces(haarCascade, image);
// Filter faces
var state = faces.ToImageState();
state = filtering.FilterFaces(state);
// Determine change
var hasChange = trackingChanges.ShouldUpdateRecognition(state);
if (hasChange)
{
Console.WriteLine("Changes detected...");
Random random = new Random();
Font currentFont = panel.richTextBox1.SelectionFont;
FontStyle newFontStyle = (FontStyle)(currentFont.Style | FontStyle.Bold);
panel.richTextBox1.SelectionFont = new Font(currentFont.FontFamily, 12, newFontStyle);
panel.richTextBox1.AppendText("\n- Changes detected...");
for (int i = 0; i < 20; i++)
{
panel.richTextBox5.AppendText(random.Next(0, 2).ToString());
}
// Identify faces if changed and previous identification finished.
if (_faceRecognitionTask == null && !string.IsNullOrWhiteSpace(FaceSubscriptionKey))
{
_faceRecognitionTask = StartRecognizing(image, panel, ZSPersonsList);
}
}
using (var renderedFaces = RenderFaces(state, image))
{
// Update popup window.
window.ShowImage(renderedFaces);
}
// Wait for next frame and allow Window to be repainted.
Cv2.WaitKey(timePerFrame);
}
}
}
}
