public void DetectLabelsTest()
{
//Arrange
var param = new DetectLabelParams()
{
BucketName = "nvirginiadekanybucket",
PhotoName = "",
PhotoVersion = "1",
MaxLabels = 10,
MinConfidence = 75F
};
//Act
AmazonRekognition service = new AmazonRekognition(awsAccessKeyId, awsSecretAccessKey);
var resp = service.DetectLabels(param);
//Assert
}
public void DetectFacesTest()
{
//Arrange
var param = new DetectFaceParams()
{
BucketName = "nvirginiadekanybucket",
PhotoName = "steve",
PhotoVersion = String.Empty
};
AmazonRekognition service = new AmazonRekognition(awsAccessKeyId, awsSecretAccessKey);
//Act
var resp = service.DetectFaces(param);
bool hasItem = resp.FaceDetails.Any();
//Assert
Assert.AreEqual(true, hasItem);
}
public void RecogniseTest()
{
Stream stream = new MemoryStream(GetFileBytes());
//Arrange
var req = new RecogniseParams()
{
PhotoName = "steve",
PhotoVersion = String.Empty,
BucketName = "nvirginiadekanybucket",
RegEndpoint = RegionEndpoint.USEast1,
InputStream = stream,
ContentType = "image/jpeg"
};
//Act
AmazonRekognition service = new AmazonRekognition(awsAccessKeyId, awsSecretAccessKey);
var resp = service.Recognise(req);
//Assert
Assert.AreEqual(System.Net.HttpStatusCode.OK, resp.HttpStatusCode);
}
//public IHttpActionResult Recognize([FromBody]String base64String)
public IHttpActionResult Recognize(RecognizeParam param)
{
if (String.IsNullOrEmpty(param.Base64String))
{
return(BadRequest("Bad request: base64String parameter must have value."));
}
var stream = new MemoryStream();
var photoBytes = Convert.FromBase64String(param.Base64String);
using (var ms = new MemoryStream(photoBytes, 0, photoBytes.Length))
{
Image image = Image.FromStream(ms, true);
image.Save(stream, ImageFormat.Jpeg);
}
var awsAccessKeyId = ConfigurationManager.AppSettings["awsAccessKeyId"];
var awsSecretAccessKey = ConfigurationManager.AppSettings["awsSecretAccessKey"];
var bucketName = ConfigurationManager.AppSettings["bucketName"];
var photoName = $"{DateTime.Now}_{Guid.NewGuid()}";
var req = new RecogniseParams()
{
PhotoName = photoName,
PhotoVersion = "1",
BucketName = bucketName,
RegEndpoint = RegionEndpoint.USEast1,
InputStream = stream,
ContentType = "image/jpeg"
};
AmazonRekognition service = new AmazonRekognition(awsAccessKeyId, awsSecretAccessKey);
var resp = service.Recognise(req);
return(Ok(resp));
}
// Face detection method
private async Task FacialRecognitionScan(ApplicationUser user, UsersInGymDetail currentFacilityDetail)
{
// initialize similarity threshold for accepting face match, source and target img.
// S3 bucket img, dynamically selected based on user currently logged in.
float similarityThreshold = 70F;
string photo = $"{user.FirstName}_{user.Id}.jpg";
String targetImage = $"{user.FirstName}_{user.Id}_Target.jpg";
try
{
// create image objects
Image imageSource = new Image()
{
S3Object = new S3Object()
{
Name = photo,
Bucket = bucket
},
};
Image imageTarget = new Image()
{
S3Object = new S3Object()
{
Name = targetImage,
Bucket = bucket
},
};
// create a compare face request object
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// detect face features of img scanned
CompareFacesResponse compareFacesResponse = await AmazonRekognition.CompareFacesAsync(compareFacesRequest);
// Display results
foreach (CompareFacesMatch match in compareFacesResponse.FaceMatches)
{
ComparedFace face = match.Face;
// if confidence for similarity is over 90 then grant access
if (match.Similarity > 90)
{
// if there is a match set scan success
user.IsCameraScanSuccessful = true;
}
else
{
ViewBag.MatchResult = "Facial Match Failed!";
}
}
}
catch (Exception e)
{
_logger.LogInformation(e.Message);
}
// now add get facial details to display in the view.
DetectFacesRequest detectFacesRequest = new DetectFacesRequest()
{
Image = new Image()
{
S3Object = new S3Object()
{
Name = targetImage,
Bucket = bucket
},
},
// "DEFAULT": BoundingBox, Confidence, Landmarks, Pose, and Quality.
Attributes = new List <String>()
{
"ALL"
}
};
try
{
DetectFacesResponse detectFacesResponse = await AmazonRekognition.DetectFacesAsync(detectFacesRequest);
bool hasAll = detectFacesRequest.Attributes.Contains("ALL");
foreach (FaceDetail face in detectFacesResponse.FaceDetails)
{
// if the face found has all attributes within a Detect Face object then save these values to the database.
if (hasAll)
{
currentFacilityDetail.IsSmiling = face.Smile.Value;
currentFacilityDetail.Gender = face.Gender.Value.ToString();
currentFacilityDetail.AgeRangeLow = face.AgeRange.Low;
currentFacilityDetail.AgeRangeHigh = face.AgeRange.High;
}
}
}
catch (Exception e)
{
_logger.LogInformation(e.Message);
}
}
