public async Task <CompareFacesResponse> CompareAsync(MemoryStream srcImg, MemoryStream trgtImg)
{
try
{
var sourceImg = new Image()
{
Bytes = srcImg
};
var targetImg = new Image()
{
Bytes = trgtImg
};
var request = new CompareFacesRequest()
{
SimilarityThreshold = similarityThreshold,
SourceImage = sourceImg,
TargetImage = targetImg
};
return(await rekognitionClient.CompareFacesAsync(request));
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
return(null);
}
internal CompareFacesResponse CompareFaces(CompareFacesRequest request)
{
var marshaller = new CompareFacesRequestMarshaller();
var unmarshaller = CompareFacesResponseUnmarshaller.Instance;
return(Invoke <CompareFacesRequest, CompareFacesResponse>(request, marshaller, unmarshaller));
}
// snippet-start:[Rekognition.dotnetv3.CompareFacesExample]
public static async Task Main()
{
float similarityThreshold = 70F;
string sourceImage = "source.jpg";
string targetImage = "target.jpg";
var rekognitionClient = new AmazonRekognitionClient();
Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();
try
{
using FileStream fs = new FileStream(sourceImage, FileMode.Open, FileAccess.Read);
byte[] data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageSource.Bytes = new MemoryStream(data);
}
catch (Exception)
{
Console.WriteLine($"Failed to load source image: {sourceImage}");
return;
}
Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();
try
{
using FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read);
byte[] data = new byte[fs.Length];
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageTarget.Bytes = new MemoryStream(data);
}
catch (Exception ex)
{
Console.WriteLine($"Failed to load target image: {targetImage}");
Console.WriteLine(ex.Message);
return;
}
var compareFacesRequest = new CompareFacesRequest
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold,
};
// Call operation
var compareFacesResponse = await rekognitionClient.CompareFacesAsync(compareFacesRequest);
// Display results
compareFacesResponse.FaceMatches.ForEach(match =>
{
ComparedFace face = match.Face;
BoundingBox position = face.BoundingBox;
Console.WriteLine($"Face at {position.Left} {position.Top} matches with {match.Similarity}% confidence.");
});
Console.WriteLine($"Found {compareFacesResponse.UnmatchedFaces.Count} face(s) that did not match.");
}
/// <summary>
/// Initiates the asynchronous execution of the CompareFaces operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the CompareFaces operation.</param>
/// <param name="cancellationToken">
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
/// </param>
/// <returns>The task object representing the asynchronous operation.</returns>
public Task <CompareFacesResponse> CompareFacesAsync(CompareFacesRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var marshaller = new CompareFacesRequestMarshaller();
var unmarshaller = CompareFacesResponseUnmarshaller.Instance;
return(InvokeAsync <CompareFacesRequest, CompareFacesResponse>(request, marshaller,
unmarshaller, cancellationToken));
}
public async Task <bool> AuthenticateUserByFace(byte[] targetImage) //FileStream targetImage
{
float similarityThreshold = 90F;
String sourceImage = "https://hackathonimagedump.s3.us-east-2.amazonaws.com/123456.jpeg";
// String targetImage = "https://hackathonimagedump.s3.us-east-2.amazonaws.com/HappyFace.jpeg";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient("AKIAX2ZTBCX4OX6XH77Q", "X/FcCoEFyuIl5+hmwE+IVMk4t1089mgf0jIQI7Xo", RegionEndpoint.USWest2);
Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();
try
{
var webClient = new WebClient();
byte[] imageBytes = webClient.DownloadData(sourceImage);
imageSource.Bytes = new MemoryStream(imageBytes);
}
catch
{
}
Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();
try
{
imageTarget.Bytes = new MemoryStream(targetImage);
}
catch
{
}
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// Call operation
CompareFacesResponse compareFacesResponse = await rekognitionClient.CompareFacesAsync(compareFacesRequest);
if (compareFacesResponse.HttpStatusCode == HttpStatusCode.OK)
{
if (compareFacesResponse.SourceImageFace.Confidence > 90F)
{
return(true);
}
else
{
return(false);
}
}
else
{
return(false);
}
}
public async Task <float> FindFaceOrThrowException(string s3ObjectIdCard, string s3ObjectPhotoToTest, float similarityThreshold, string personName)
{
var imgSrc = GetImageDefinition(s3ObjectIdCard);
var imgTrg = GetImageDefinition(s3ObjectPhotoToTest);
var compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imgSrc,
TargetImage = imgTrg,
SimilarityThreshold = similarityThreshold
};
try
{
var compareFacesResponse = await _client.CompareFacesAsync(compareFacesRequest);
// we are looking for two faces, the card and the actual picture taken by the person.
var matchesWeCareAbout = compareFacesResponse.FaceMatches.OrderByDescending(m => m.Similarity).Take(2);
if (matchesWeCareAbout.Count() < 2)
{
throw new Exception(string.Format("You don't look like {0}.\nPlease ensure that both your card and your face can be seen.", personName));
}
// the card should be the smallest photo of the two with highest similarity
var shouldBeTheCardBySize = compareFacesResponse.FaceMatches.OrderBy(m => m.Face.BoundingBox.Height * m.Face.BoundingBox.Width).Take(1).Single();
// the card similarity should be very high
if (shouldBeTheCardBySize.Similarity <= 95)
{
throw new Exception("Is that your id card?");
}
var shoultBeTheFaceOfThePerson = compareFacesResponse.FaceMatches.OrderBy(m => m.Similarity).Take(1).Single();
return(shoultBeTheFaceOfThePerson.Similarity);
/*var match = shouldBeTheCardBySimilarity;
* var face = match.Face;
* var position = face.BoundingBox;
* System.Diagnostics.Debug.WriteLine("Face at " + position.Left + " " + position.Top + " matches with " + face.Confidence + "% confidence.");
* System.Diagnostics.Debug.WriteLine("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
* System.Diagnostics.Debug.WriteLine("Source image rotation: " + compareFacesResponse.SourceImageOrientationCorrection);
* System.Diagnostics.Debug.WriteLine("Target image rotation: " + compareFacesResponse.TargetImageOrientationCorrection);*/
}
catch (Exception e)
{
System.Diagnostics.Debug.WriteLine(e.Message);
throw;
}
}
public async Task <bool> IsSimillarFaceOnSourceImage(HubConnection hubConnection)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient("AKIA3GGXKFL7TG4ARQ5F", "iXqBARX00AiblMAAfvOIp6tKdwRrd/bQlvTicUcq", Amazon.RegionEndpoint.EUWest1);
Image imageSource = new Image();
using (FileStream fs = new FileStream(sourceImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageSource.Bytes = new MemoryStream(data);
}
Image imageTarget = new Image();
using (FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageTarget.Bytes = new MemoryStream(data);
}
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
try
{
CompareFacesResponse compareFacesResponse = await rekognitionClient.CompareFacesAsync(compareFacesRequest);
foreach (CompareFacesMatch match in compareFacesResponse.FaceMatches)
{
ComparedFace face = match.Face;
BoundingBox position = face.BoundingBox;
Console.WriteLine("Face at " + position.Left
+ " " + position.Top
+ " matches with " + match.Similarity
+ "% confidence.");
await hubConnection.SendAsync("HideWindows");
}
Console.WriteLine("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
return(true);
}
catch (Exception)
{
return(false);
}
}
private static async Task <CompareFacesResponse> Compare(Image image1, Image image2)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(Amazon.RegionEndpoint.USWest2);
float similarityThreshold = 0F; // set to 0 to see all probability scores
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = image1,
TargetImage = image2,
SimilarityThreshold = similarityThreshold
};
return(await rekognitionClient.CompareFacesAsync(compareFacesRequest));
}
private void btn_find_faces_Click(object sender, EventArgs e)
{
var source = ToBytesStream($"{sourceLocation}");
var target = ToBytesStream($"{targetLocation}");
var client = new AmazonRekognitionClient();
var request = new CompareFacesRequest {
SourceImage = source, TargetImage = target, SimilarityThreshold = 90
};
var response = client.CompareFaces(request);
txt_result.Text = $"Found {response.FaceMatches.Count} matched faces with threshold 90%";
}
public async Task <bool> AuthenticateUserByFace(byte[] targetImage)
{
try
{
float similarityThreshold = 90F;
CustomerDetails custInfo = JsonConvert.DeserializeObject <CustomerDetails>(TempData["UserInfo"].ToString());
string sourceImage = custInfo.body.CustomerDetails.ImageUrl;
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(Environment.GetEnvironmentVariable("ACCESS_KEY_ID"), Environment.GetEnvironmentVariable("SECRET_ACCESS_KEY"), RegionEndpoint.USWest2);
Image imageSource = new Image();
var webClient = new WebClient();
byte[] imageBytes = webClient.DownloadData(sourceImage);
imageSource.Bytes = new MemoryStream(imageBytes);
Image imageTarget = new Image();
imageTarget.Bytes = new MemoryStream(targetImage);
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// Call operation
CompareFacesResponse compareFacesResponse = await rekognitionClient.CompareFacesAsync(compareFacesRequest);
if (compareFacesResponse.HttpStatusCode == HttpStatusCode.OK)
{
if (compareFacesResponse.FaceMatches.Count > 0 && compareFacesResponse.FaceMatches.Count < 2)
{
return(true);
}
else
{
return(false);
}
}
else
{
return(false);
}
}
catch
{
throw new Exception();
}
}
private string CompareFaces(string strPersonName, MemoryStream msCapture, MemoryStream msFacePic)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient("", "", Amazon.RegionEndpoint.USEast1);
CompareFacesRequest req = new CompareFacesRequest();
Amazon.Rekognition.Model.Image src = new Amazon.Rekognition.Model.Image();
src.Bytes = msCapture;
req.SourceImage = src;
Amazon.Rekognition.Model.Image trg = new Amazon.Rekognition.Model.Image();
trg.Bytes = msFacePic;
req.TargetImage = trg;
try
{
CompareFacesResponse compareFacesResult = rekognitionClient.CompareFaces(req);
List <CompareFacesMatch> faceDetails = compareFacesResult.FaceMatches;
ComparedFace face = null;
foreach (CompareFacesMatch match in faceDetails)
{
face = match.Face;
BoundingBox position = face.BoundingBox;
System.Diagnostics.Debug.Write("Face at " + position.Left
+ " " + position.Top
+ " matches with " + face.Confidence
+ "% confidence.");
if (face.Confidence > 75)
{
return(strPersonName);
}
}
}
catch (Exception ex)
{
return("Fail");
}
return("Unknown");
}
public CompareFacesResponse CompareFaces(byte[] source, byte[] target)
{
AmazonRekognitionClient rekoClient = new AmazonRekognitionClient(_credentials, Amazon.RegionEndpoint.USWest2);
CompareFacesRequest cfr = new CompareFacesRequest();
Amazon.Rekognition.Model.Image sourceImage = new Amazon.Rekognition.Model.Image();
Amazon.Rekognition.Model.Image targetImage = new Amazon.Rekognition.Model.Image();
var sourceStream = new MemoryStream(source);
var targetStream = new MemoryStream(target);
sourceImage.Bytes = sourceStream;
targetImage.Bytes = targetStream;
cfr.SourceImage = sourceImage;
cfr.TargetImage = targetImage;
return(rekoClient.CompareFaces(cfr));
}
public async Task <FaceMatchResponse> CompareFacesAsync(string sourceImage, string targetImage)
{
// Converte a imagem fonte em um objeto MemoryStream
var imageSource = new Amazon.Rekognition.Model.Image();
imageSource.Bytes = _serviceUtils.ConvertImageToMemoryStream(sourceImage);
// Converte a imagem alvo em um objeto MemoryStream
var imageTarget = new Amazon.Rekognition.Model.Image();
imageTarget.Bytes = _serviceUtils.ConvertImageToMemoryStream(targetImage);
// Configura o objeto que fará o request para o AWS Rekognition
// A propriedade SimilarityThreshold ajusta o nível de similaridade na comparação das imagens
var request = new CompareFacesRequest
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = 80f
};
// Faz a chamada do serviço de CompareFaces
var response = await _rekognitionClient.CompareFacesAsync(request);
// Verifica se houve algum match nas imagens
var hasMatch = response.FaceMatches.Any();
// Se não houve match ele retorna um objeto não encontrado
if (!hasMatch)
{
return(new FaceMatchResponse(hasMatch, null, string.Empty));
}
// Com a imagem fonte e os parâmetros de retorno do match contornamos o rosto encontrado na imagem
var fileName = _serviceUtils.Drawing(imageSource.Bytes, response.SourceImageFace);
// Pega o percentual de similaridade da imagem encontrada
var similarity = response.FaceMatches.FirstOrDefault().Similarity;
// Retorna o objeto com as informações encontradas e com a URL para verificar a imagem
return(new FaceMatchResponse(hasMatch, similarity, fileName));
}
public Solicitudes GetTestAsync(List <Tab_ConfigSys> Tab_ConfigSys, Solicitudes sol)
{
string xClase = string.Format("{0}|{1}", MethodBase.GetCurrentMethod().Module.Name, MethodBase.GetCurrentMethod().DeclaringType.Name);
string xProceso = MethodBase.GetCurrentMethod().Name;
var dto_excepcion = new UTL_TRA_EXCEPCION
{
STR_CLASE = xClase,
STR_EVENTO = xProceso,
STR_PARAMETROS = JsonConvert.SerializeObject(sol),
STR_APLICATIVO = ConfigurationManager.AppSettings["APLICATIVO"].ToString(),
STR_SERVIDOR = System.Net.Dns.GetHostName(),
FEC_CREACION = DateTime.Now
};
Solicitudes _Solicitudes = new Solicitudes();
var options = new CredentialProfileOptions
{
AccessKey = Tab_ConfigSys[0].llave_Config1,
SecretKey = Tab_ConfigSys[0].llave_Config2
};
try
{
var profile = new Amazon.Runtime.CredentialManagement.CredentialProfile("AWSProfileName", options);
profile.Region = RegionEndpoint.USWest1;
var netSDKFile = new NetSDKCredentialsFile();
netSDKFile.RegisterProfile(profile);
float similarityThreshold = 70F;
//String sourceImage = sol.arrImageSelfie;
//String targetImage = sol.UrlFotoCedula;
//using (AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(Tab_ConfigSys[0].llave_Config1, Tab_ConfigSys[0].llave_Config2, RegionEndpoint.USWest1))
using (AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(Tab_ConfigSys[0].llave_Config1, Tab_ConfigSys[0].llave_Config2))
{
Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();
//using (FileStream fs = new FileStream(new MemoryStream(bytes), FileMode.Open, FileAccess.Read))
//{
// byte[] data = new byte[fs.Length];
// fs.Read(data, 0, (int)fs.Length);
imageSource.Bytes = new MemoryStream(sol.arrImageSelfie);
// }
Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();
// using (FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read))
//{
// byte[] data = new byte[fs.Length];
// data = new byte[fs.Length];
// fs.Read(data, 0, (int)fs.Length);
imageTarget.Bytes = new MemoryStream(sol.arrImageCedulaFrontal);
// }
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// Call operation
CompareFacesResponse compareFacesResponse = rekognitionClient.CompareFaces(compareFacesRequest);
// Display results
//foreach (CompareFacesMatch match in compareFacesResponse.FaceMatches)
compareFacesResponse.FaceMatches.ForEach(match =>
{
ComparedFace face = match.Face;
BoundingBox position = face.BoundingBox;
_Solicitudes.PorcentMatched = face.Confidence;
_Solicitudes.PositionLeft = position.Left;
_Solicitudes.PositionTop = position.Top;
});
_Solicitudes.IdTipoIdentificacion = sol.IdTipoIdentificacion;
_Solicitudes.Identificacion = sol.Identificacion;
if (_Solicitudes.PorcentMatched == 0 || _Solicitudes.PorcentMatched == null)
{
_Solicitudes.UnMatchedFace = compareFacesResponse.UnmatchedFaces[0].Confidence;
}
else
{
_Solicitudes.UnMatchedFace = 0;
}
_Solicitudes.ImageRotationSource = compareFacesResponse.SourceImageOrientationCorrection;
_Solicitudes.ImageRotationTarget = compareFacesResponse.TargetImageOrientationCorrection;
}
return(_Solicitudes);
}
catch (Exception ex)
{
dto_excepcion.STR_MENSAJE = ex.Message;
dto_excepcion.IS_TELEGRAM = true;
TwoFunTwoMe_DataAccess.Utility.guardaExcepcion(dto_excepcion, ConfigurationManager.ConnectionStrings["TwoFunTwoMeConnection"].ConnectionString);
_Solicitudes.Mensaje = "ERR_imageTarget";
throw;
}
}
private static async Task Main(string[] args)
{
const string AWS_ACCESS_KEY_ID = "AWS_ACCESS_KEY_ID";
const string AWS_SECRET_ACCESS_KEY = "AWS_SECRET_ACCESS_KEY";
Console.WriteLine("Hello World!");
var self = await File.ReadAllBytesAsync("assets\\self.jpg");
var front = await File.ReadAllBytesAsync("assets\\front.png");
var back = await File.ReadAllBytesAsync("assets\\back.png");
var command = new AnalizeDocumentCommand {
Self = self, Back = back, Front = front
};
var region = RegionEndpoint.USEast1;
var client = new AmazonRekognitionClient(AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, region);
#region Analiza se é documento
using (var stream = new MemoryStream(command.Back))
{
var request = new DetectLabelsRequest {
Image = new Image {
Bytes = stream
}
};
var response = await client.DetectLabelsAsync(request);
var labels = response.Labels;
foreach (var label in labels)
{
var accuracy = Accuracy.GetAccuracy(label.Confidence);
if (DocumentTypes.IsValidDocument(label.Name))
{
if (accuracy.IsLow)
{
Console.WriteLine("Não é um documento");
}
if (accuracy.IsMedium)
{
Console.WriteLine("Pode ser que seja um documento");
}
if (accuracy.IsHigh)
{
Console.WriteLine("É muito provável que seja um documento");
}
break;
}
}
}
#endregion
#region Compara com a self
using (var source = new MemoryStream(command.Self))
using (var target = new MemoryStream(command.Front))
{
var request = new CompareFacesRequest {
SourceImage = new Image {
Bytes = source
}, TargetImage = new Image {
Bytes = target
}
};
var response = await client.CompareFacesAsync(request);
var faces = response.FaceMatches;
if (faces.Count != 1)
{
Console.WriteLine("Resultado inconsistente");
}
var accuracy = Accuracy.GetAccuracy(faces.First().Similarity);
if (accuracy.IsLow)
{
Console.WriteLine("Esse documento não da mesma pessoa");
}
if (accuracy.IsMedium)
{
Console.WriteLine("Pode ser que este documento seja da mesma pessoa");
}
if (accuracy.IsHigh)
{
Console.WriteLine("É muito provável que este documento seja da mesma pessoa");
}
}
#endregion
#region Verifica se é do portador válido
using (var stream = new MemoryStream(command.Back))
{
var request = new DetectTextRequest {
Image = new Image {
Bytes = stream
}
};
var response = await client.DetectTextAsync(request);
var texts = response.TextDetections;
foreach (var text in texts)
{
var accuracy = Accuracy.GetAccuracy(text.Confidence);
if ("CPF".Equals(text.DetectedText, StringComparison.InvariantCultureIgnoreCase))
{
if (accuracy.IsLow)
{
Console.WriteLine("não contém um número de CPF");
}
if (accuracy.IsMedium)
{
Console.WriteLine("Pode ser que contenha um número de CPF");
}
if (accuracy.IsHigh)
{
Console.WriteLine("É muito provável que contenha um número de CPF");
}
break;
}
}
}
#endregion
Console.WriteLine("That's all folks!");
}
static void Main(string[] args)
{
const float MIN_CONFIDENCE = 90F;
try
{
string[] imagesList = GetListOfImages();
if (imagesList == null || imagesList.Length == 0)
{
Console.WriteLine("No images found in the Images folder");
return;
}
// Constructs a SharedCredentialsFile object from the default credentials file.
SharedCredentialsFile sharedCredentialsFile = new SharedCredentialsFile();
// Get the [default] profile from the credentials file.
CredentialProfile defaultProfile = GetDefaultProfile(sharedCredentialsFile);
if (defaultProfile != null)
{
// Get the credentials (access key, secret access key, etc.)
AWSCredentials credentials = AWSCredentialsFactory.GetAWSCredentials(defaultProfile, new SharedCredentialsFile());
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(credentials, RegionEndpoint.USEast1);
CompareFacesRequest detectFacesRequest = new CompareFacesRequest()
{
SourceImage = GetImage(@"C:\Temp\TomCruise1.jpg"),
TargetImage = GetImage(@"C:\Temp\TomCruise2.jpg")
};
CompareFacesResponse response = rekognitionClient.CompareFaces(detectFacesRequest);
List <CompareFacesMatch> list = response.FaceMatches;
foreach (string filePath in imagesList)
{
Image image = GetImage(filePath);
if (image == null)
{
continue;
}
DetectLabelsRequest detectLabelsRequest = new DetectLabelsRequest()
{
Image = image,
MinConfidence = MIN_CONFIDENCE,
};
DetectLabelsResponse detectLabelsResponse = rekognitionClient.DetectLabels(detectLabelsRequest);
Console.WriteLine("Image: {0}\n", filePath);
foreach (Label label in detectLabelsResponse.Labels)
{
Console.WriteLine("\t{0} ({1})", label.Name, label.Confidence);
}
Console.WriteLine();
}
}
else
{
Console.WriteLine("AWS [default] profile not found");
}
}
catch (AmazonRekognitionException ex)
{
Console.WriteLine("AWS Rekognition ERROR: {0}", ex.Message);
}
catch (Exception ex)
{
Console.WriteLine("ERROR: {0}", ex.Message);
}
Console.WriteLine("\nDONE");
Console.ReadLine();
}
public static void Example()
{
float similarityThreshold = 70F;
String sourceImage = "source.jpg";
String targetImage = "target.jpg";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();
try
{
using (FileStream fs = new FileStream(sourceImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageSource.Bytes = new MemoryStream(data);
}
}
catch (Exception)
{
Console.WriteLine("Failed to load source image: " + sourceImage);
return;
}
Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();
try
{
using (FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageTarget.Bytes = new MemoryStream(data);
}
}
catch (Exception)
{
Console.WriteLine("Failed to load target image: " + targetImage);
return;
}
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// Call operation
CompareFacesResponse compareFacesResponse = rekognitionClient.CompareFaces(compareFacesRequest);
// Display results
foreach (CompareFacesMatch match in compareFacesResponse.FaceMatches)
{
ComparedFace face = match.Face;
BoundingBox position = face.BoundingBox;
Console.WriteLine("Face at " + position.Left
+ " " + position.Top
+ " matches with " + face.Confidence
+ "% confidence.");
}
Console.WriteLine("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
Console.WriteLine("Source image rotation: " + compareFacesResponse.SourceImageOrientationCorrection);
Console.WriteLine("Target image rotation: " + compareFacesResponse.TargetImageOrientationCorrection);
}
public static async Task <string> FunctionHandler(String photo)
{
String bucket = "moodanalysis";
//ArrayList result = new ArrayList();
string result = "";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
// Recognizes User's face
CompareFacesRequest CFR = new CompareFacesRequest()
{
//SimilarityThreshold = 50,
SourceImage = new Image()
{
S3Object = new S3Object()
{
Name = "referencePhoto.jpg",
Bucket = bucket
},
},
TargetImage = new Image()
{
S3Object = new S3Object()
{
Name = photo,
Bucket = bucket
},
},
};
CompareFacesResponse compareFacesResponse = await rekognitionClient.CompareFacesAsync(CFR);
string howManyFaces = "";
if (compareFacesResponse.FaceMatches.Count == 0)
{
return("");
}
//int index = 0, bestIndex = 0;
var bestMatch = compareFacesResponse.FaceMatches[0];
float bestMatchResult = compareFacesResponse.FaceMatches[0].Similarity;
BoundingBox bestBoundingBox = compareFacesResponse.FaceMatches[0].Face.BoundingBox;
foreach (var faceMatch in compareFacesResponse.FaceMatches)
{
howManyFaces += faceMatch.Similarity + ",";
if (bestMatchResult < faceMatch.Similarity)
{
bestMatch = faceMatch;
bestBoundingBox = faceMatch.Face.BoundingBox;
bestMatchResult = faceMatch.Similarity;
}
}
// Detects emotions of faces in photo
DetectFacesRequest detectFacesRequest = new DetectFacesRequest()
{
Image = new Image()
{
S3Object = new S3Object()
{
Name = photo,
Bucket = bucket
},
},
Attributes = new List <String>()
{
"ALL"
}
};
DetectFacesResponse detectFacesResponse = await rekognitionClient.DetectFacesAsync(detectFacesRequest);
//int i = 0;
foreach (FaceDetail face in detectFacesResponse.FaceDetails)
{
if (face.BoundingBox.Height == bestBoundingBox.Height &&
face.BoundingBox.Left == bestBoundingBox.Left &&
face.BoundingBox.Top == bestBoundingBox.Top &&
face.BoundingBox.Width == bestBoundingBox.Width)
{
//var emotQuery = FilterEmotions(face, IsLowConfidence);
FilterEmotions filter = delegate(FaceDetail faceFilter, ConfidenceFilterDelegate confFilter)
{
return(faceFilter.Emotions.FindAll(n => confFilter(n)).ToList());
};
var emotQuery = filter(face, IsLowConfidence);
//IEnumerable<Emotion> emotQuery =
// from faceEmotion in face.Emotions
// where faceEmotion.Confidence > 10
// select faceEmotion;
// GRAB THE EMOTION
foreach (Emotion emot in emotQuery)
{
result += emot.Type + ",";
}
break;
}
}
//delete the last ,
if (result.Length != 0)
{
result = result.Substring(0, result.Length - 1);
}
return(result);
}
private void button1_Click(object sender, EventArgs e)
{
float similarityThreshold = 70F;
String sourceImage = "source.jpg";
String targetImage = "target.jpg";
String accessKeyID = "";
String secretKey = "";
AWSCredentials credentials;
credentials = new BasicAWSCredentials(accessKeyID.Trim(), secretKey.Trim());
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(credentials, Amazon.RegionEndpoint.USEast1);
Amazon.Rekognition.Model.Image imageSource = new Amazon.Rekognition.Model.Image();
try
{
using (FileStream fs = new FileStream(sourceImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageSource.Bytes = new MemoryStream(data);
}
}
catch (Exception)
{
//Console.WriteLine("Failed to load source image: " + sourceImage);
listBox1.Items.Add("Failed to load source image: " + sourceImage);
return;
}
Amazon.Rekognition.Model.Image imageTarget = new Amazon.Rekognition.Model.Image();
try
{
using (FileStream fs = new FileStream(targetImage, FileMode.Open, FileAccess.Read))
{
byte[] data = new byte[fs.Length];
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
imageTarget.Bytes = new MemoryStream(data);
}
}
catch (Exception)
{
//Console.WriteLine("Failed to load target image: " + targetImage);
listBox1.Items.Add("Failed to load target image: " + targetImage);
return;
}
CompareFacesRequest compareFacesRequest = new CompareFacesRequest()
{
SourceImage = imageSource,
TargetImage = imageTarget,
SimilarityThreshold = similarityThreshold
};
// Call operation
CompareFacesResponse compareFacesResponse = rekognitionClient.CompareFaces(compareFacesRequest);
// Display results
foreach (CompareFacesMatch match in compareFacesResponse.FaceMatches)
{
ComparedFace face = match.Face;
BoundingBox position = face.BoundingBox;
//Console.WriteLine("Face at " + position.Left
// + " " + position.Top
// + " matches with " + match.Similarity
// + "% confidence.");
listBox1.Items.Add("Face at " + position.Left
+ " " + position.Top
+ " matches with " + match.Similarity
+ "% confidence.");
}
//Console.WriteLine("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
listBox1.Items.Add("There was " + compareFacesResponse.UnmatchedFaces.Count + " face(s) that did not match");
}
// 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);
}
}
