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);
}
// 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.");
}
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 <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));
}
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();
}
}
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));
}
/// <summary>
/// A simple function that takes a string and does a ToUpper
/// </summary>
/// <param name="input"></param>
/// <param name="context"></param>
/// <returns></returns>
public async Task <bool> FunctionHandler(String input, ILambdaContext context)
{
var rekognitionClient = new AmazonRekognitionClient();
var array = input.Split(new char[] { '#' }, StringSplitOptions.RemoveEmptyEntries);
string name = (array[0] + "/" + array[0] + ".jpg");
var response = await rekognitionClient.CompareFacesAsync(new CompareFacesRequest
{
SimilarityThreshold = 90,
SourceImage = new Image
{
S3Object = new S3Object
{
Bucket = "s3rekognition",
Name = name
}
},
TargetImage = new Image
{
S3Object = new S3Object
{
Bucket = "s3rekognition",
Name = array[1]
}
}
});
foreach (CompareFacesMatch mach in response.FaceMatches)
{
if (mach.Similarity > 90)
{
return(true);
}
return(false);
}
return(false);
}
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!");
}
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);
}
