//private void Process(FaceRecognitionResult obj)
//{
// var filePath = _fileService.SaveImage(obj.Image);
// _slackClient.SlackSendFile(filePath);
//}
private void Process(FaceDetectionResult obj)
{
if (!_config.ScreenLocked || _alertSended)
{
return;
}
if (obj.Result == FaceDetectionResultType.OneFaceFound)
{
_faceDetectedInRow++;
}
else
{
_faceDetectedInRow = 0;
}
if (_faceDetectedInRow < 2)
{
return;
}
var filePath = _fileService.SaveImage(obj.Image);
_slackClient.SlackSendFile(filePath);
_alertSended = true;
}
private void FaceDetectionResultHandler(FaceDetectionResult args)
{
if (_applicationConfiguration.ScreenLocked)
{
return;
}
if (args.Result == FaceDetectionResultType.FaceNotFound)
{
_faceNotDetectedInRow++;
}
else
{
_faceNotDetectedInRow = 0;
}
if (_faceNotDetectedInRow < _applicationConfiguration.FaceNotDetectedLimit)
{
return;
}
if (DateTime.Now - _mouseService.LastDeviceActivityTime < _applicationConfiguration.DeviceInactivityLimit ||
DateTime.Now - _keyboardService.LastDeviceActivityTime < _applicationConfiguration.DeviceInactivityLimit)
{
return;
}
_faceNotDetectedInRow = 0;
NewThreadScheduler.Default.Schedule(_applicationConfiguration.CommandDelayInterval,
() => _dispatcherService.Invoke(LockWorkstation));
_notificationService.SendMessage("Screen will be locked within 5 seconds. Press any key or move mouse");
}
public void Invalid()
{
var result = new FaceDetectionResult("errors");
Assert.False(result.IsValid);
Assert.Equal("errors", result.Errors);
}
private Dictionary <int, List <CoolEvent> > GetCoolEvents(FaceDetectionResult faceDetectionTracking)
{
//Only fragments where Events are not null
var Fragments = faceDetectionTracking.Fragments.Where(x => x.Events != null).ToArray();
var idDict = GetDictionary(Fragments);
return(idDict);
}
public async Task ValidateProfileImage_MoreThan1Faces()
{
var faceDetectionClient = Create();
faceDetectionClientFake.Setup(f => f.DetectAsync(It.IsAny <string>(), false, false, null)).ReturnsAsync(new[] { new Face(), new Face() });
var expected = new FaceDetectionResult("Fant flere ansikter i bildet litt. Last opp et profilbilde av deg selv.");
var faceDetectionResult = await faceDetectionClient.ValidateProfileImage(new SlackUser { Id = "id", Image = "http://image.jpg" });
Assert.Equal(expected, faceDetectionResult);
}
public void Equals()
{
var first = FaceDetectionResult.Valid;
var other = FaceDetectionResult.Valid;
Assert.Equal(first, other);
Assert.True(first.Equals((object)other));
Assert.False(first.Equals(null));
Assert.False(first.Equals(new object()));
other = new FaceDetectionResult("errors");
Assert.NotEqual(first, other);
}
private async void TakePictureButton_Clicked(object sender, EventArgs e)
{
try
{
// Initialize the camera and then allows for taking a picture
// (check if this is supported)
await CrossMedia.Current.Initialize();
if (!CrossMedia.Current.IsCameraAvailable || !CrossMedia.Current.
IsTakePhotoSupported)
{
await DisplayAlert("No Camera", "No camera available.", "OK");
return;
}
//Take the picture and save it to the camera roll
var file = await CrossMedia.Current.TakePhotoAsync(new StoreCameraMediaOptions
{
SaveToAlbum = true,
Name = "test.jpg"
});
if (file == null)
{
return;
}
this.Indicator1.IsVisible = true;
this.Indicator1.IsRunning = true;
// Get a stream from the image file
Image1.Source = ImageSource.FromStream(() => file.GetStream());
// Analyze the specified image and then bind
// the result to the UI
FaceDetectionResult theData = await DetectFacesAsync(file.GetStream());
this.BindingContext = theData;
this.Indicator1.IsRunning = false;
this.Indicator1.IsVisible = false;
}
catch (Exception ex)
{
Debug.WriteLine("Error taking photo: " + ex);
Result.Text = "Error taking photo...: " + ex;
}
}
public async Task <IEnumerable <FaceDetectionResult> > DetectFacesAsync(ImageRequest request)
{
try
{
// .NET の FaceAPI を呼ぶためのクラスを生成
var client = new FaceServiceClient(subscriptionKey: Secrets.CongnitiveServiceFaceApiKey, apiRoot: Consts.CognitiveServiceFaceApiEndPoint);
// DetectAsync で、画像のどこに顔があって、その顔は何歳か、という情報を取得している
var results = await client.DetectAsync(imageStream : new MemoryStream(request.Image), returnFaceAttributes : new[]
{
FaceAttributeType.Age,
});
var personListId = await this.PersonListIdRepository.GetIdAsync();
// 取得した顔が誰の顔かを認識している
var identifyResults = (await client.IdentifyAsync(personListId, results.Select(x => x.FaceId).ToArray()))
.ToDictionary(x => x.FaceId);
var l = new List <FaceDetectionResult>();
foreach (var r in results)
{
IdentifyResult identifyResult = null;
identifyResults.TryGetValue(r.FaceId, out identifyResult);
var faceDetectionResult = new FaceDetectionResult
{
FaceId = identifyResult?.Candidates.FirstOrDefault()?.PersonId.ToString() ?? new Guid().ToString(),
Age = (int)r.FaceAttributes.Age,
Rectangle = new BusinessObjects.FaceRectangle
{
Top = r.FaceRectangle.Top,
Left = r.FaceRectangle.Left,
Width = r.FaceRectangle.Width,
Height = r.FaceRectangle.Height,
}
};
l.Add(faceDetectionResult);
}
return(l);
}
catch (FaceAPIException)
{
return(Enumerable.Empty <FaceDetectionResult>());
}
}
private async void UploadPictureButton_Clicked(object sender, EventArgs e)
{
try
{
// Select an existing picture
// (check if this is supported)
if (!CrossMedia.Current.IsPickPhotoSupported)
{
await DisplayAlert("No upload", "Picking a photo is not supported.", "OK");
return;
}
// Get a reference to the image file
var file = await CrossMedia.Current.PickPhotoAsync();
if (file == null)
{
return;
}
this.Indicator1.IsVisible = true;
this.Indicator1.IsRunning = true;
// Get a stream from the image file
Image1.Source = ImageSource.FromStream(() => file.GetStream());
// Analyze the specified image and then bind
// the result to the UI
FaceDetectionResult theData = await DetectFacesAsync(file.GetStream());
this.BindingContext = theData;
this.Indicator1.IsRunning = false;
this.Indicator1.IsVisible = false;
}
catch (Exception ex)
{
Debug.WriteLine("Error in upload picture: " + ex);
Result.Text = "Error in upload picture...: " + ex;
}
}
private void CallDLL(string fileName)
{
int[] top = new int[32];
int[] left = new int[32];
int[] right = new int[32];
int[] bottom = new int[32];
var size = Detect(fileName, top, left, right, bottom);
Debug.LogFormat("Detect: {0} faces.", size);
IList <FaceDetectionResult> list = new List <FaceDetectionResult>();
for (int i = 0; i < size; i++)
{
var rectangle = new FaceDetectionResult(top[i], left[i], right[i], bottom[i]);
list.Add(rectangle);
Debug.LogFormat("Face[{0}]: \n{1}", i, rectangle);
}
isDetectingFaces = false;
}
public async Task <Dictionary <int, List <Image> > > GetFacesFromVideo(string path)
{
SetVideoResol(path);
FaceDetectionResult faceDetectionResult = await GetFaceDetectionAsync(path);
MessageManager.MsgManagerInstance.ReportProgress();
MessageManager.MsgManagerInstance.WriteMessage("Got Face Detection Result!!!!)))");
Dictionary <int, List <CoolEvent> > FaceIds = GetCoolEvents(faceDetectionResult);
Dictionary <int, List <Image> > resultImages = new Dictionary <int, List <Image> >();
//Choose 1 first and 5 random CoolEvents
FaceIds = ChooseFive(FaceIds);
//Cropping faces of each person. id - unique person's number
foreach (int id in FaceIds.Keys)
{
resultImages[id] = new List <Image>();
foreach (var curEvent in FaceIds[id])
{
try
{
var startTimeMili = curEvent.startTime / _timeScale * 1000;
GetFrame(path, startTimeMili, id);
var img = ImageProcessing.ImageProcessingInstance.LoadImageFromFile($@"TempData/{id}.{(long)startTimeMili}.png");
img = ImageProcessing.ImageProcessingInstance.CropImage(img, curEvent.rec);
//ImageProcessing.ImageProcessingInstance.SaveImageToFile($@"TempData/{id}.{(long)startTimeMili}Face", img, System.Drawing.Imaging.ImageFormat.Png);
resultImages[id].Add(img);
}
catch
{
MessageManager.MsgManagerInstance.WriteMessage("Error with cropping");
}
}
}
MessageManager.MsgManagerInstance.ReportProgress();
return(resultImages);
}
private void FaceDetectionResultHandler(FaceDetectionResult args)
{
Debug.WriteLine(args.ToString());
if (args == FaceDetectionResult.FaceNotFound)
{
_faceNotDetectedInRow++;
}
else
{
_faceNotDetectedInRow = 0;
}
if (_faceNotDetectedInRow < _applicationConfiguration.FaceNotDetectedLimit)
{
return;
}
if (DateTime.Now - _mouseService.LastDeviceActivityTime < _applicationConfiguration.DeviceInactivityLimit ||
DateTime.Now - _keyboardService.LastDeviceActivityTime < _applicationConfiguration.DeviceInactivityLimit)
{
return;
}
LockWorkstation();
_faceNotDetectedInRow = 0;
}
private async Task <FaceDetectionResult> DetectFacesAsync(Stream image)
{
Result.Text = "";
FaceServiceClient faceService = new FaceServiceClient("2bddec152651472a8cb690e00db31a43");
FaceDetectionResult faceDetectionResult = new FaceDetectionResult();
var requiredFaceAttributes = new FaceAttributeType[]
{
FaceAttributeType.Age, FaceAttributeType.Gender, FaceAttributeType.Glasses
};
Face[] faces = await faceService.DetectAsync(image, returnFaceLandmarks : true, returnFaceAttributes : requiredFaceAttributes);
if (faces.Length >= 1)
{
var edad = faces[0].FaceAttributes.Age;
var genero = faces[0].FaceAttributes.Gender;
int roundedAge = (int)Math.Round(edad);
faceDetectionResult.FaceId = faces[0].FaceId.ToString();
faceDetectionResult.Age = faces[0].FaceAttributes.Age;
faceDetectionResult.Glasses = faces[0].FaceAttributes.Glasses.ToString();
Debug.WriteLine("ID de rostro: " + faces[0].FaceId);
Debug.WriteLine("Edad: " + edad);
Debug.WriteLine("Género: " + genero);
Debug.WriteLine("Lentes: " + faces[0].FaceAttributes.Glasses);
if (faceDetectionResult.Glasses == "NoGlasses")
{
Guid idGuid = Guid.Parse(faces[0].FaceId.ToString());
SimilarPersistedFace[] facescomp = await faceService.FindSimilarAsync(idGuid, "21122011", 1);
double conf = Double.Parse(facescomp[0].Confidence.ToString());
string pid = facescomp[0].PersistedFaceId.ToString();
Debug.WriteLine("conf: " + conf);
if (conf >= .67)
{
Result.Text = "Posible coincidencia";
try
{
Query(pid);
}
catch (Exception ex)
{
Debug.WriteLine(" ex: " + ex);
}
}
else
{
Result.Text = "No hay coincidencias";
}
}
else
{
Result.Text = "Try again without glasses!";
}
}
else
{
Debug.WriteLine("No faces detected: {0} ", faces.Length);
Result.Text = faces.Length + " faces detected";
}
return(faceDetectionResult);
}
