private void SendFrame(string filePath, int detectedFaces)
{
// Using Azure Storage SDK to upload the file is another option
_storageRepo.CreateFileAsync(Path.GetFileName(filePath), System.IO.File.ReadAllBytes(filePath)).Wait();
// IoT Hub has built-in support for blobs upload.
// File will be uploaded to a folder with the device name. This might required some code changes
//_iotHub.UploadFile(Path.GetFileName(filePath), new MemoryStream(System.IO.File.ReadAllBytes(filePath))).Wait();
CognitiveRequest req = new CognitiveRequest
{
CreatedAt = DateTime.UtcNow,
DeviceId = deviceId,
FileUrl = Path.GetFileName(filePath),
Id = Guid.NewGuid().ToString(),
IsActive = true,
IsDeleted = false,
IsProcessed = false,
Origin = "Device.Web.V1.0.0",
Status = "Submitted",
TakenAt = DateTime.UtcNow,
TargetAction = CognitiveTargetAction.CamFrameAnalysis.ToString()
};
Dictionary <string, string> properties = new Dictionary <string, string>
{
{ "DeviceId", deviceId },
{ "DetectedFacesCount", detectedFaces.ToString() }
};
_iotHub.SendEventAsync(JsonConvert.SerializeObject(req), properties).Wait();
}
public void CamFrameAnalysis(CognitiveRequest request)
{
var messageBody = JsonConvert.SerializeObject(request);
var message = new Message(Encoding.UTF8.GetBytes(messageBody));
camFrameAnalyzerServiceBus.PublishMessage(message);
}
public async Task <IActionResult> SubmitDoc(string deviceId, string docType, IFormFile doc)
{
if (doc == null || doc.Length == 0)
{
return(BadRequest("file not selected"));
}
var proposedDocType = CognitiveTargetAction.Unidentified;
var isValidType = Enum.TryParse <CognitiveTargetAction>(docType, out proposedDocType);
if (!isValidType || proposedDocType == CognitiveTargetAction.Unidentified)
{
return(BadRequest("Invalid document type"));
}
long size = doc.Length;
// full path to file in temp location
string docName = "NA";
string docUri = null;
if (size > 0)
{
using (var stream = doc.OpenReadStream())
{
var docExtention = doc.FileName.Substring(doc.FileName.LastIndexOf('.'));
docName = $"{deviceId}-{DateTime.UtcNow.ToString("ddMMyyHHmmss")}{docExtention}";
docUri = await storageRepository.CreateFileAsync(docName, stream);
}
}
else
{
return(BadRequest("Submitted file size is 0"));
}
CognitiveRequest req = new CognitiveRequest
{
CreatedAt = DateTime.UtcNow,
DeviceId = deviceId,
FileUrl = docName,
Id = Guid.NewGuid().ToString(),
IsActive = true,
IsDeleted = false,
IsProcessed = false,
Origin = "CognitiveOrchestrator.API.V1.0.0",
Status = "Submitted",
TakenAt = DateTime.UtcNow,
TargetAction = proposedDocType.ToString()
};
var sbMessage = new Microsoft.Azure.ServiceBus.Message(Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(req)));
var result = await serviceBusRepository.PublishMessage(sbMessage);
return(Ok(req));
}
public async Task Run(
[ServiceBusTrigger(AppConstants.SBTopic, AppConstants.SBSubscription, Connection = "SB_Connection")] string request,
ILogger log)
{
CognitiveRequest cognitiveRequest = null;
try
{
cognitiveRequest = JsonConvert.DeserializeObject <CognitiveRequest>(request);
}
catch (Exception ex)
{
log.LogError($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(request)} with the error: {ex.Message}");
}
try
{
key = GlobalSettings.GetKeyValue("cognitiveKey");
endpoint = GlobalSettings.GetKeyValue("cognitiveEndpoint");
faceClient = new FaceClient(
new Microsoft.Azure.CognitiveServices.Vision.Face.ApiKeyServiceClientCredentials(key),
new System.Net.Http.DelegatingHandler[] { })
{
Endpoint = endpoint
};
var data = await filesStorageRepo.GetFileAsync(cognitiveRequest.FileUrl);
var frameAnalysis = new CamFrameAnalysis();
}
catch (Exception ex)
{
log.LogError($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(cognitiveRequest)} with the error: {ex.Message}");
}
log.LogInformation($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered and processed message: {JsonConvert.SerializeObject(cognitiveRequest)}");
}
public async Task <string> Run(
[ServiceBusTrigger(AppConstants.SBTopic, AppConstants.SBSubscription, Connection = "serviceBusConnection")] string request,
ILogger log)
{
DateTime startTime = DateTime.UtcNow;
log.LogInformation($"FUNC (MaskDetector): camframe-analysis topic triggered processing message: {JsonConvert.SerializeObject(request)}");
CognitiveRequest cognitiveRequest = null;
try
{
cognitiveRequest = JsonConvert.DeserializeObject <CognitiveRequest>(request);
}
catch (Exception ex)
{
log.LogError($"FUNC (MaskDetector): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(request)} with the error: {ex.Message}");
}
//Starting Mask Detection
MaskAnalysis result = new MaskAnalysis
{
Id = $"{Guid.NewGuid()}-{cognitiveRequest.TakenAt.Month}{cognitiveRequest.TakenAt.Year}",
Request = cognitiveRequest,
CreatedAt = startTime,
TimeKey = $"{cognitiveRequest.TakenAt.Month}{cognitiveRequest.TakenAt.Year}",
IsDeleted = false,
IsSuccessful = false,
Origin = "MaskDetector",
Status = ProcessingStatus.Processing.ToString()
};
var fileName = cognitiveRequest.FileUrl.Substring(cognitiveRequest.FileUrl.LastIndexOf("/") + 1);
var data = await filesStorageRepo.GetFileAsync(fileName);
var imageStream = new MemoryStream(data);
try
{
var detectionResult = await maskDetectionApi.DetectImage(new StreamPart(imageStream, "image.jpg", "multipart/form-data"));
result.DetectionResult = detectionResult;
result.DetectionResult.Predictions = detectionResult.Predictions.Where(p => p.Probability >= AppConstants.MaskDetectionThreshold).ToList();
result.IsSuccessful = true;
result.Status = ProcessingStatus.Successful.ToString();
result.TotalDetected = detectionResult.Predictions.Where(p => p.Probability >= AppConstants.MaskDetectionThreshold).Count();
result.TotalDetectedWithMasks = detectionResult.Predictions.Where(p => p.TagName == "MASK" && p.Probability >= AppConstants.MaskDetectionThreshold).Count();
result.TotalDetectedWithoutMasks = detectionResult.Predictions.Where(p => p.TagName == "NOMASK" && p.Probability >= AppConstants.MaskDetectionThreshold).Count();
result.MaskDetectionThreshold = AppConstants.MaskDetectionThreshold;
result.TotalProcessingTime = (int)(DateTime.UtcNow - startTime).TotalMilliseconds;
var dbResult = await maskAnalysisRepo.AddAsync(result);
return(JsonConvert.SerializeObject(dbResult));
}
catch (Exception ex)
{
log.LogError($"FUNC (MaskDetector): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(cognitiveRequest)} with the error: {ex.Message}");
}
return(null);
}
public static void CamFrameAnalysis(CognitiveRequest request)
{
}
public async Task <string> Run(
[ServiceBusTrigger(AppConstants.SBTopic, AppConstants.SBSubscription, Connection = "serviceBusConnection")] string request,
ILogger log)
{
DateTime startTime = DateTime.UtcNow;
log.LogInformation($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered processing message: {JsonConvert.SerializeObject(request)}");
CognitiveRequest cognitiveRequest = null;
try
{
cognitiveRequest = JsonConvert.DeserializeObject <CognitiveRequest>(request);
}
catch (Exception ex)
{
log.LogError($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(request)} with the error: {ex.Message}");
}
try
{
key = GlobalSettings.GetKeyValue("cognitiveKey");
endpoint = GlobalSettings.GetKeyValue("cognitiveEndpoint");
faceWorkspaceDataFilter = GlobalSettings.GetKeyValue("faceWorkspaceDataFilter");
FaceServiceHelper.ApiKey = key;
FaceServiceHelper.ApiEndpoint = endpoint;
FaceListManager.FaceListsUserDataFilter = faceWorkspaceDataFilter;
frameAnalysis = new CamFrameAnalysis
{
Id = $"{Guid.NewGuid()}-{cognitiveRequest.TakenAt.Month}{cognitiveRequest.TakenAt.Year}",
Request = cognitiveRequest,
CreatedAt = startTime,
TimeKey = $"{cognitiveRequest.TakenAt.Month}{cognitiveRequest.TakenAt.Year}",
IsDeleted = false,
IsSuccessful = false,
Origin = "CamFrameAnalyzer",
Status = ProcessingStatus.Processing.ToString()
};
// Get image data. We need only the filename not the FQDN in FileUrl
var fileName = cognitiveRequest.FileUrl.Substring(cognitiveRequest.FileUrl.LastIndexOf("/") + 1);
var data = await filesStorageRepo.GetFileAsync(fileName);
// Load the analyzer with data
CognitiveFacesAnalyzer.PeopleGroupsUserDataFilter = faceWorkspaceDataFilter;
cognitiveFacesAnalyzer = new CognitiveFacesAnalyzer(data);
await AnalyzeCameFrame(log);
UpdateAnalysisSummary();
frameAnalysis.TotalProcessingTime = (int)(DateTime.UtcNow - startTime).TotalMilliseconds;
await SaveAnalysisAsync();
log.LogInformation($"FUNC (CamFrameAnalyzer): camframe-analysis COMPLETED: {JsonConvert.SerializeObject(frameAnalysis)}");
//Only publish a new analysis when face detection was successful with faces
if (frameAnalysis.IsSuccessful)
{
return(JsonConvert.SerializeObject(frameAnalysis));
}
else
{
return(null);
}
}
catch (Exception ex)
{
log.LogError($"FUNC (CamFrameAnalyzer): camframe-analysis topic triggered and failed to parse message: {JsonConvert.SerializeObject(cognitiveRequest)} with the error: {ex.Message}");
}
return(null);
}
