private async Task <SimilarFaceMatch> GetSimilarFace(Face detectedFace)
{
SimilarFaceMatch result = new SimilarFaceMatch();
try
{
Tuple <SimilarPersistedFace, string> similarPersistedFace = await FaceListManager.FindSimilarPersistedFaceAsync(await this.GetImageStreamCallback(), detectedFace.FaceId, detectedFace.FaceRectangle);
if (similarPersistedFace != null)
{
bool isNew = (similarPersistedFace.Item2 == null);
result = new SimilarFaceMatch()
{
Face = detectedFace, SimilarPersistedFace = similarPersistedFace.Item1, isNew = isNew
};
}
}
catch (Exception e)
{
ErrorTrackingHelper.TrackException(e, "FaceListManager.FindSimilarPersistedFaceAsync error");
if (this.ShowDialogOnFaceApiErrors)
{
await ErrorTrackingHelper.GenericApiCallExceptionHandler(e, "Failure finding similar faces");
}
}
return(result);
}
public async Task FindSimilarPersistedFacesAsync()
{
this.SimilarFaceMatches = Enumerable.Empty <SimilarFaceMatch>();
if (this.DetectedFaces == null || !this.DetectedFaces.Any())
{
return;
}
List <SimilarFaceMatch> result = new List <SimilarFaceMatch>();
foreach (DetectedFace detectedFace in this.DetectedFaces)
{
try
{
SimilarFace similarPersistedFace = null;
if (this.ImageUrl != null)
{
similarPersistedFace = await FaceListManager.FindSimilarPersistedFaceAsync(ImageUrl, detectedFace.FaceId.GetValueOrDefault(), detectedFace);
}
else
{
similarPersistedFace = await FaceListManager.FindSimilarPersistedFaceAsync(this.GetImageStreamCallback, detectedFace.FaceId.GetValueOrDefault(), detectedFace);
}
if (similarPersistedFace != null)
{
result.Add(new SimilarFaceMatch {
Face = detectedFace, SimilarPersistedFace = similarPersistedFace
});
}
}
catch (Exception e)
{
ErrorTrackingHelper.TrackException(e, "FaceListManager.FindSimilarPersistedFaceAsync error");
if (this.ShowDialogOnFaceApiErrors)
{
await ErrorTrackingHelper.GenericApiCallExceptionHandler(e, "Failure finding similar faces");
}
}
}
this.SimilarFaceMatches = result;
}
public async Task <List <FaceSendInfo> > FindSimilarPersonWithEmotion()
{
var facesInfo = new List <FaceSendInfo>();
List <SimilarFaceMatch> result = new List <SimilarFaceMatch>();
//Loop thru all detected faces from previous steps and fill the facesInfo array
//For ease of processing in Azure Stream Analytics we create single level object
foreach (var f in this.DetectedFaces)
{
var fsi = new FaceSendInfo();
//Add emotions
var e = CoreUtil.FindEmotionForFace(f, this.DetectedEmotion);
FeedFaceInfo(f, fsi, e);
//We sen also info how many faces in total were recognized on the picture with current face
fsi.facesNo = this.DetectedFaces.Count();
Tuple <SimilarPersistedFace, string> similarPersistedFace = await FaceListManager.FindSimilarPersistedFaceAsync(await this.GetImageStreamCallback(), f.FaceId, f.FaceRectangle);
if (similarPersistedFace != null)
{
result.Add(new SimilarFaceMatch {
Face = f, SimilarPersistedFace = similarPersistedFace.Item1
});
fsi.canid = similarPersistedFace.Item1.PersistedFaceId.ToString();
fsi.canconf = similarPersistedFace.Item1.Confidence;
//In order to get also name we need to obtain Person
//p = await FaceServiceHelper.GetPersonAsync(groupId, can.PersonId);
fsi.canname = similarPersistedFace.Item1.PersistedFaceId.ToString();
}
facesInfo.Add(fsi);
}
SimilarFaceMatches = result;
return(facesInfo);
}
public async Task <List <FaceSendInfo> > IdentifyOrAddPersonWithEmotionsAsync(string groupName, ObservableCollection <IdentifiedFaces> identifiedPersonsIdCollection)
{
var facesInfo = new List <FaceSendInfo>();
//Loop thru all detected faces from previous steps and fill the facesInfo array
//For ease of processing in Azure Stream Analytics we create single level object
foreach (var f in this.DetectedFaces)
{
var fsi = new FaceSendInfo();
//Add emotions
var e = CoreUtil.FindEmotionForFace(f, this.DetectedEmotion);
FeedFaceInfo(f, fsi, e);
//We sen also info how many faces in total were recognized on the picture with current face
fsi.facesNo = this.DetectedFaces.Count();
facesInfo.Add(fsi);
}
//Now we proceed to face recognition/identification
//First we create group if it does not exist
try
{
var g = await FaceServiceHelper.CreatePersonGroupIfNoGroupExists(groupName);
groupId = g.PersonGroupId;
}
catch (Exception e)
{
// Catch errors with individual groups so we can continue looping through all groups. Maybe an answer will come from
// another one.
ErrorTrackingHelper.TrackException(e, "Problem creating group");
if (this.ShowDialogOnFaceApiErrors)
{
await ErrorTrackingHelper.GenericApiCallExceptionHandler(e, "Problem creating group");
}
}
//We need to find candidate for every face
try
{
IdentifyResult[] groupResults = await this.IdentifyFacesAsync(groupId);
//We loop thri all faces again in order to find candidate
foreach (var f in this.DetectedFaces)
{
bool needToRetrain = true;
var fi = facesInfo.Where(fin => fin.faceId == f.FaceId.ToString()).FirstOrDefault();
var newPersonID = Guid.NewGuid();
if (groupResults != null && groupResults.Where(gr => gr.FaceId == f.FaceId).Any() && groupResults.Where(gr => gr.FaceId == f.FaceId).FirstOrDefault().Candidates.Any())
{
var candidates = groupResults.Where(gr => gr.FaceId == f.FaceId).FirstOrDefault().Candidates.OrderByDescending(ca => ca.Confidence);
Person p = new Person();
var can = candidates.FirstOrDefault();
//If we have sufficient confidence, we add Face for person
if (can.Confidence >= SettingsHelper.Instance.Confidence)
{
fi.canid = can.PersonId.ToString();
fi.canconf = can.Confidence;
//In order to get also name we need to obtain Person
p = await FaceServiceHelper.GetPersonAsync(groupId, can.PersonId);
fi.canname = p.Name;
var identifiedPersonFromList = identifiedPersonsIdCollection.Where(ip => ip.Id == can.PersonId.ToString()).FirstOrDefault();
//Check whether we did not added too much photos lately, it is not neccesary to add photo for face every time
if (identifiedPersonFromList == null)
{
await AddFaceToPerson(f, p, can.PersonId);
}
else if (identifiedPersonFromList.NumOfAddedPhotosInLastPeriod < SettingsHelper.Instance.NumberOfPhotoAddsInPeriod)
{
await AddFaceToPerson(f, p, can.PersonId);
identifiedPersonFromList.NumOfAddedPhotosInLastPeriod++;
}
else if ((DateTime.Now - identifiedPersonFromList.FirstPhotoAddedInLastPeriod).Hours > SettingsHelper.Instance.PhotoAddPeriodSize)
{
identifiedPersonFromList.NumOfAddedPhotosInLastPeriod = 1;
identifiedPersonFromList.FirstPhotoAddedInLastPeriod = DateTime.Now;
await AddFaceToPerson(f, p, can.PersonId);
}
else
{
needToRetrain = false;
}
}
else
{
//if not sufficient confidence we also need to check whether there is similar face/ if not create new person
await CreatePrsonIfNoSimilarFaceExistsAsync(facesInfo, newPersonID, f);
}
}
else
{
//if no candidate we also need to check whether there is similar fac,e if not create new person
await CreatePrsonIfNoSimilarFaceExistsAsync(facesInfo, newPersonID, f);
}
try
{
//We need to train after operation on top of group (addition of photo, person etc.)
if (needToRetrain)
{
await FaceServiceHelper.TrainPersonGroupAsync(groupId);
}
}
catch (Exception e)
{
// Catch error with training of group
ErrorTrackingHelper.TrackException(e, "Problem training group");
if (this.ShowDialogOnFaceApiErrors)
{
await ErrorTrackingHelper.GenericApiCallExceptionHandler(e, "Problem training group");
}
}
//Handle the identified persons collection to which we locally save every identified person
if (!identifiedPersonsIdCollection.Where(ip => ip.Id == fi.canid).Any())
{
identifiedPersonsIdCollection.Add(new IdentifiedFaces()
{
Id = fi.canid
});
}
//Increase counter of identifications
else if (identifiedPersonsIdCollection.Where(ip => ip.Id == fi.canid).Any())
{
identifiedPersonsIdCollection.Where(ip => ip.Id == fi.canid).FirstOrDefault().NumberOfIdentifications++;
}
//Find faces which were wrongly learned (small number of identifications)
var tbd = new List <IdentifiedFaces>();
foreach (var ip in identifiedPersonsIdCollection)
{
if (ip.NumberOfIdentifications <= SettingsHelper.Instance.NeededFaceIdentNum && (ip.CreatedAt.AddSeconds(SettingsHelper.Instance.DeleteWindow) < DateTime.Now))
{
var g = (await FaceServiceHelper.GetPersonGroupsAsync()).Where(gr => gr.Name == groupName).FirstOrDefault();
Person pers = await FaceServiceHelper.GetPersonAsync(g.PersonGroupId, new Guid(ip.Id));
//if we saved insufficient number of faces than delete
if (pers.PersistedFaceIds.Length <= SettingsHelper.Instance.NeededFaceIdentNum)
{
await FaceServiceHelper.DeletePersonAsync(g.PersonGroupId, pers.PersonId);
string similarFaceId = "";
using (var db = new KioskDBContext())
{
var sfToDelete = db.SimilarFaces.Where(sf => sf.PersonId == pers.PersonId.ToString()).FirstOrDefault();
similarFaceId = sfToDelete.FaceId.ToString();
db.SimilarFaces.Remove(sfToDelete);
}
await FaceListManager.DeleteFaceFromFaceList(similarFaceId);
await FaceServiceHelper.TrainPersonGroupAsync(g.PersonGroupId);
tbd.Add(ip);
}
}
}
foreach (var iptodelete in tbd)
{
identifiedPersonsIdCollection.Remove(iptodelete);
}
}
}
catch (Exception e)
{
// Catch error with training of group
ErrorTrackingHelper.TrackException(e, "Problem with cognitive services");
if (this.ShowDialogOnFaceApiErrors)
{
await ErrorTrackingHelper.GenericApiCallExceptionHandler(e, "Problem with cognitive services");
}
}
return(facesInfo);
}
