/// <summary>
/// This function compares the input image with the existing ones in the dyFace Collection
/// Function Name: "dyFaceRekognition"
/// </summary>
/// <param name="input"></param>
/// <param name="context"></param>
/// <returns></returns>
public async Task <bool> RekognizeFace(string input, ILambdaContext context)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
Image image = new Image()
{
S3Object = new S3Object()
{
Bucket = "dyface-test-bucket",
Name = input
}
};
SearchFacesByImageRequest searchFaceRequest = new SearchFacesByImageRequest()
{
CollectionId = "dyFaceCollection",
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 1
};
SearchFacesByImageResponse searchFaceResponse = await rekognitionClient.SearchFacesByImageAsync(searchFaceRequest);
foreach (FaceMatch face in searchFaceResponse.FaceMatches)
{
if (face.Similarity >= 95)
{
return(true);
}
}
//missing error handling - image does't exist etc
return(false);
}
private SearchFacesByImageResponse SearchPhotosByImage()
{
//var s3ObjectResponse = S3Client.GetObjectAsync("recongimages", _eTag);
var getObjectRequest = new GetObjectRequest();
getObjectRequest.EtagToMatch = _eTag;
getObjectRequest.BucketName = "recongimages";
var s3ObjectResponse = S3Client.GetObjectAsync(getObjectRequest);
//var objectName = s3ObjectResponse.Result.Key;
var rekognitionClient = new Amazon.Rekognition.AmazonRekognitionClient("AKIAJASZFMUMX6B4JUIQ", "4YDS6cYGyTkES76EwwbLU/0KL1O7lO8YQGpsi2zV", Amazon.RegionEndpoint.APSoutheast2);
var requestSearch = new SearchFacesByImageRequest();
requestSearch.MaxFaces = 1;
//requestSearch.CollectionId
var s3Object = new Amazon.Rekognition.Model.S3Object();
s3Object.Name = s3ObjectResponse.Result.Key;
var image = new Image();
image.S3Object = s3Object;
requestSearch.Image = image;
//requestSearch.FaceMatchThreshold
var response = rekognitionClient.SearchFacesByImageAsync(requestSearch);
return(response.Result);
}
internal SearchFacesByImageResponse SearchFacesByImage(SearchFacesByImageRequest request)
{
var marshaller = new SearchFacesByImageRequestMarshaller();
var unmarshaller = SearchFacesByImageResponseUnmarshaller.Instance;
return(Invoke <SearchFacesByImageRequest, SearchFacesByImageResponse>(request, marshaller, unmarshaller));
}
public static string RecogniseFaceMatchFromS3(string collectionId, string bucket, string photo)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(RegionEndpoint.APSouth1);
// Get an image object from S3 bucket.
Image image = new Image()
{
S3Object = new S3Object()
{
Bucket = bucket,
Name = photo
}
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2
};
var searchFacesByImageResponse = rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);
Console.WriteLine("Faces matching largest face in image from " + photo);
foreach (FaceMatch face in searchFacesByImageResponse.Result.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
return(face.Face.Confidence.ToString());
}
return("");
}
public static void Example()
{
String collectionId = "MyCollection";
String bucket = "bucket";
String photo = "input.jpg";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
// Get an image object from S3 bucket.
Image image = new Image()
{
S3Object = new S3Object()
{
Bucket = bucket,
Name = photo
}
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2
};
SearchFacesByImageResponse searchFacesByImageResponse = rekognitionClient.SearchFacesByImage(searchFacesByImageRequest);
Console.WriteLine("Faces matching largest face in image from " + photo);
foreach (FaceMatch face in searchFacesByImageResponse.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
}
}
// snippet-start:[Rekognition.dotnetv3.SearchFacesMatchingImageExample]
public static async Task Main()
{
string collectionId = "MyCollection";
string bucket = "bucket";
string photo = "input.jpg";
var rekognitionClient = new AmazonRekognitionClient();
// Get an image object from S3 bucket.
var image = new Image()
{
S3Object = new S3Object()
{
Bucket = bucket,
Name = photo,
},
};
var searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2,
};
SearchFacesByImageResponse searchFacesByImageResponse = await rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);
Console.WriteLine("Faces matching largest face in image from " + photo);
searchFacesByImageResponse.FaceMatches.ForEach(face =>
{
Console.WriteLine($"FaceId: {face.Face.FaceId}, Similarity: {face.Similarity}");
});
}
/// <summary>
/// Initiates the asynchronous execution of the SearchFacesByImage operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the SearchFacesByImage 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 <SearchFacesByImageResponse> SearchFacesByImageAsync(SearchFacesByImageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var marshaller = new SearchFacesByImageRequestMarshaller();
var unmarshaller = SearchFacesByImageResponseUnmarshaller.Instance;
return(InvokeAsync <SearchFacesByImageRequest, SearchFacesByImageResponse>(request, marshaller,
unmarshaller, cancellationToken));
}
private List <Guid> SearchOneFace(string faceFileName)
{
List <Guid> facesData = null;
try
{
Amazon.Rekognition.Model.Image image = new Amazon.Rekognition.Model.Image()
{
Bytes = new MemoryStream(System.IO.File.ReadAllBytes(faceFileName))
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = awsCollectionId, Image = image, FaceMatchThreshold = awsFaceMatchThreshold, MaxFaces = 1000
};
using (AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(awsAccessKeyId, awsSecretAccessKey, awsRegionEndpoint))
{
SearchFacesByImageResponse searchFacesByImageResponse = rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest).Result;
if (searchFacesByImageResponse != null && searchFacesByImageResponse.FaceMatches.Count > 0)
{
facesData = new List <Guid>();
for (int f = 0; f < searchFacesByImageResponse.FaceMatches.Count; f++)
{
string dateMask = searchFacesByImageResponse.FaceMatches[f].Face.ExternalImageId;
if (dateMask.Length > 7)
{
dateMask = dateMask.Substring(0, 8);
if (dates != null && dates.Contains(dateMask))
{
if (searchFacesByImageResponse.FaceMatches[f].Similarity >= awsSimilarityLevel)
{
Guid faceId;
if (Guid.TryParse(searchFacesByImageResponse.FaceMatches[f].Face.FaceId, out faceId))
{
if (!facesData.Contains(faceId))
{
facesData.Add(faceId);
}
}
}
}
}
}
}
}
}
catch (Exception exc)
{
}
if (facesData != null && facesData.Count == 0)
{
facesData = null;
}
return(facesData);
}
private static async Task <SearchFacesByImageResponse> LookupImage(string collectionId, Image image)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(Amazon.RegionEndpoint.USWest2);
float similarityThreshold = 0F; // set to 0 to see all probability scores
int maxResults = 100;
SearchFacesByImageRequest request = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = similarityThreshold,
MaxFaces = maxResults
};
return(await rekognitionClient.SearchFacesByImageAsync(request));
}
private static void searchFace(Amazon.Rekognition.Model.Image image, AmazonRekognitionClient rekognitionClient)
{
String collectionId = "MyCollection";
SearchFacesByImageRequest request = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image
};
SearchFacesByImageResponse response = rekognitionClient.SearchFacesByImage(request);
foreach (FaceMatch face in response.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
}
}
private List <FaceMatch> SearchCollectionForSourceImageFaces()
{
List <FaceMatch> result = new List <FaceMatch>();
Console.WriteLine("Searching target collection for matching source faces...");
foreach (var entry in DataSet.SourceImages)
{
Console.WriteLine("Attempting to match image {0}.", entry.Key);
MemoryStream stream = new MemoryStream();
entry.Value.Save(stream, System.Drawing.Imaging.ImageFormat.Jpeg);
Image requestImage = new Image()
{
Bytes = stream
};
SearchFacesByImageRequest request = new SearchFacesByImageRequest()
{
Image = requestImage,
CollectionId = CollectionName
};
var watch = Stopwatch.StartNew();
SearchFacesByImageResponse response = Client.SearchFacesByImage(request);
watch.Stop();
TimingResults.Add(new TimingModel("SearchCollectionForSourceImageFaces", entry.Key, watch.ElapsedMilliseconds));
MatchResults.Add(response);
if (response.FaceMatches.Count > 0)
{
Console.WriteLine("Matching target face found for {0} with a confidence level of {1}.", entry.Key, response.SearchedFaceConfidence);
}
else
{
Console.WriteLine("No matching target face found for {0}.", entry.Key);
}
result.AddRange(response.FaceMatches);
}
Console.WriteLine("{0} out of {1} faces successfully matched.", result.Count, DataSet.SourceImages.Count);
return(result);
}
public static string RecogniseFaceMatchFromFileSystem(string collectionId, byte[] photo)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(RegionEndpoint.APSouth1);
// Get an image object from File system.
Image image = new Image()
{
Bytes = new MemoryStream(photo)
};
//using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read))
//{
// byte[] data = null;
// data = new byte[fs.Length];
// fs.Read(data, 0, (int)fs.Length);
// image.Bytes = new MemoryStream(data);
//}
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2
};
var searchFacesByImageResponse = rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);
Console.WriteLine("Faces matching largest face in image from " + photo);
foreach (FaceMatch face in searchFacesByImageResponse.Result.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
return(face.Face.FaceId);
}
return("");
}
public async Task <string> Compare(byte[] imageBytes)
{
try
{
String collectionId = "PiscoMarketFaces";
//Decrypt Keys
var key = "E546C8DF278CD5931069B522E695D4F2";
var rekognitionClient = new AmazonRekognitionClient(EncryptionUtilities.DecryptString(configuration.awsAccessKey, key), EncryptionUtilities.DecryptString(configuration.awsAccessSecret, key), Amazon.RegionEndpoint.USEast2);
var image = new Image()
{
Bytes = new MemoryStream(imageBytes)
};
var searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 1
};
SearchFacesByImageResponse searchFacesByImageResponse =
await rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);
if (searchFacesByImageResponse.FaceMatches.Any())
{
var faceMatch = searchFacesByImageResponse.FaceMatches.First();
return(faceMatch.Face.ExternalImageId);
}
return(null);
}
catch (Exception ex)
{
return(null);
}
}
public async void SearchFace()
{
String collectionId = "faceCollection";
String bucket = "face-identify";
String photo = "BrotherP.jpg";
string accessKey = "AKIAST4HFDODRNXMOAPJ";
string secretKey = "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";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(accessKey, secretKey, Amazon.RegionEndpoint.APSoutheast1);
// Get an image object from S3 bucket.
Image image = new Image()
{
S3Object = new S3Object()
{
Bucket = bucket,
Name = photo
}
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2
};
SearchFacesByImageResponse searchFacesByImageResponse = await rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest);
Console.WriteLine("Faces matching largest face in image from " + photo);
foreach (FaceMatch face in searchFacesByImageResponse.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
}
}
private void searchFacesMatch(Bitmap bitmap, MyDelegate my)
{
Amazon.Rekognition.Model.Image image = Utils.bitmapToAWSImage(bitmap);
SearchFacesByImageRequest request = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image
};
SearchFacesByImageResponse response = null;
try
{
response = rekognitionClient.SearchFacesByImage(request);
}
catch (Exception e)
{
my(e.Message);
//Console.WriteLine("cannot recognize human face");
return;
}
if (response.FaceMatches.Count != 0)
{
String name = response.FaceMatches[0].Face.FaceId;
String similarity = response.FaceMatches[0].Similarity + "";
my(similarity);
}
else
{
my("nobody nobody but you");
}
}
/// <summary>
///
/// </summary>
/// <param name="input"></param>
/// <param name="context"></param>
/// <returns></returns>
public async Task FunctionHandler(S3Event input, ILambdaContext context)
{
try
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
//Debug.WriteLine("Creating collection: " + FACE_COLLECTION_ID);
//CreateCollectionRequest createCollectionRequest = new CreateCollectionRequest()
//{
// CollectionId = FACE_COLLECTION_ID
//};
//CreateCollectionResponse createCollectionResponse = rekognitionClient.CreateCollectionAsync(createCollectionRequest).Result;
//Debug.WriteLine("CollectionArn : " + createCollectionResponse.CollectionArn);
//Debug.WriteLine("Status code : " + createCollectionResponse.StatusCode);
foreach (var record in input.Records)
{
if (!SupportedImageTypes.Contains(Path.GetExtension(record.S3.Object.Key)))
{
Debug.WriteLine($"Object {record.S3.Bucket.Name}:{record.S3.Object.Key} is not a supported image type");
continue;
}
Image image = new Image()
{
S3Object = new Amazon.Rekognition.Model.S3Object
{
Bucket = record.S3.Bucket.Name,
Name = record.S3.Object.Key
}
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = FACE_COLLECTION_ID,
Image = image,
FaceMatchThreshold = 90F,
MaxFaces = 1
};
SearchFacesByImageResponse searchFacesByImageResponse = rekognitionClient.SearchFacesByImageAsync(searchFacesByImageRequest).Result;
Debug.WriteLine("Faces matching largest face in image from " + record.S3.Object.Key);
foreach (FaceMatch match in searchFacesByImageResponse.FaceMatches)
{
Debug.WriteLine("FaceId: " + match.Face.FaceId + ", Similarity: " + match.Similarity);
// Initialize the Amazon Cognito credentials provider
CognitoAWSCredentials credentials = new CognitoAWSCredentials(
"us-east-1:6d711ae9-1084-4a71-9ef6-7551ca74ad0b", // Identity pool ID
RegionEndpoint.USEast1 // Region
);
var dynamoDbClient = new AmazonDynamoDBClient(credentials, RegionEndpoint.USEast1);
Table customersTbl = Table.LoadTable(dynamoDbClient, "Customer");
GetItemOperationConfig config = new GetItemOperationConfig
{
AttributesToGet = new List <string> {
"Id", "CustomerName", "FaceId", "StoreLocation"
},
ConsistentRead = true
};
for (int i = 1; i <= 5; i++)
{
Document retrievedCustomer = customersTbl.GetItemAsync(i, config).Result;
if (retrievedCustomer["FaceId"].AsString() == match.Face.FaceId)//retrieved customer's faceID matches with the faceId currently being searched - we know who's in the store
{
//let us update customer's location
var customer = new Document();
customer["Id"] = Int32.Parse(retrievedCustomer["Id"].AsString());
string location = "";
string cameraFeedFolder = "CAM-Exit";
string[] cameraFeedFolderPath = record.S3.Object.Key.Split("/");
if (cameraFeedFolderPath.Length > 0)
{
cameraFeedFolder = cameraFeedFolderPath[0];
}
switch (cameraFeedFolder)
{
case "CAM-Entrance":
location = "entrance";
break;
case "CAM-Aisle1":
location = "aisle1";
break;
case "CAM-Aisle2":
location = "aisle2";
break;
case "CAM-Aisle3":
location = "aisle3";
break;
case "CAM-Aisle4":
location = "aisle4";
break;
case "CAM-Checkout":
location = "checkout";
break;
default:
location = "entrance";
break;
}
customer["StoreLocation"] = location;
// Optional parameters.
UpdateItemOperationConfig updateConfig = new UpdateItemOperationConfig
{
// Get updated item in response.
ReturnValues = ReturnValues.AllNewAttributes
};
Document updatedCustomer = customersTbl.UpdateItemAsync(customer, updateConfig).Result;
Console.WriteLine("UpdateMultipleAttributes: Printing item after updates ...");
PrintDocument(updatedCustomer);
break;
}
}
}
}
return;
}
catch (Exception ex)
{
throw new Exception("Deloitte Mart Exception " + ex.Message, ex);
}
}
public ActionResult RecoFaceUploadEPI(Arquivo arquivo, string UKFichaDeEPI, string UKEmpregado, string UKProduto)
{
try
{
Guid UKemp = Guid.Parse(UKEmpregado);
Empregado empregado = EmpregadoBusiness.Consulta.FirstOrDefault(a => string.IsNullOrEmpty(a.UsuarioExclusao) &&
a.UniqueKey.Equals(UKemp));
var nome = empregado.Nome.Trim().Replace(" ", "") + ".jpg";
string Semelhanca = string.Empty;
String resultado = string.Empty;
HttpPostedFileBase arquivoPostado = null;
foreach (string fileInputName in Request.Files)
{
arquivoPostado = Request.Files[fileInputName];
var target = new MemoryStream();
arquivoPostado.InputStream.CopyTo(target);
arquivo.Conteudo = target.ToArray();
arquivo.UsuarioInclusao = CustomAuthorizationProvider.UsuarioAutenticado.Login;
arquivo.DataInclusao = DateTime.Now;
arquivo.Extensao = Path.GetExtension(arquivoPostado.FileName);
arquivo.NomeLocal = arquivoPostado.FileName;
byte[] inputImageData = arquivo.Conteudo;
var inputImageStream = new MemoryStream(inputImageData);
var item = arquivo.Conteudo;
var input = arquivo.NomeLocal;
var rekognitionClient = new AmazonRekognitionClient("AKIAIBLZ7KFAN6XG3NNA", "2nukFOTDN0zv/y2tzeCiLrAHM5TwbFgvEqqZA9zn", RegionEndpoint.USWest2);
Image image = new Image()
{
Bytes = inputImageStream
};
SearchFacesByImageRequest searchFacesByImageRequest = new SearchFacesByImageRequest()
{
CollectionId = "GrupoCEI",
Image = image,
FaceMatchThreshold = 70F,
MaxFaces = 2
};
var contaFace = 0;
try
{
SearchFacesByImageResponse searchFacesByImageResponse = rekognitionClient.SearchFacesByImage(searchFacesByImageRequest);
List <FaceMatch> faceMatches = searchFacesByImageResponse.FaceMatches;
BoundingBox searchedFaceBoundingBox = searchFacesByImageResponse.SearchedFaceBoundingBox;
float searchedFaceConfidence = searchFacesByImageResponse.SearchedFaceConfidence;
if (faceMatches.Count == 0)
{
contaFace = 2;
}
if (faceMatches.Count > 0)
{
foreach (FaceMatch face in faceMatches)
{
if (face != null && face.Face.ExternalImageId == nome)
{
//Extensions.GravaCookie("MensagemSucesso", "Empregado identificado com: '" + face.Similarity + "'de semlhança.", 10);
//return Json(new { sucesso = "O arquivo foi anexado com êxito." });
// return Json(new { resultado = new RetornoJSON() { URL = Url.Action("Index", "AnaliseDeRisco") } });
Semelhanca = face.Similarity.ToString();
resultado = face.Face.ExternalImageId.ToString();
contaFace = 1;
var validacao = ValidacoesBusiness.Consulta.FirstOrDefault(a => string.IsNullOrEmpty(a.UsuarioExclusao) &&
a.Registro.Equals(arquivo.NumRegistro) && a.NomeIndex.Equals(face.Face.ExternalImageId));
if (validacao == null)
{
ValidacaoFichaDeEpi val = new ValidacaoFichaDeEpi()
{
UKFichaDeEPI = Convert.ToString(arquivo.UKObjeto),
NomeIndex = face.Face.ExternalImageId,
};
ValidacaoFichaDeEpiBusiness.Inserir(val);
}
else
{
contaFace = 4;
throw new Exception("Empregado já validou este documento!");
}
}
else
{
contaFace = 3;
throw new Exception("Empregado com Nome diferente!");
}
}
Extensions.GravaCookie("MensagemSucesso", "Empregado '" + resultado + "' identificado com: '" + Semelhanca + "' de semelhança.", 10);
}
else
{
throw new Exception("Empregado não encontrado!");
}
}
catch (Exception)
{
if (contaFace == 2)
{
throw new Exception("Empregado não encontrado!");
}
if (contaFace == 3)
{
throw new Exception("A imagem não corresponde com o empregado atual");
}
if (contaFace == 4)
{
throw new Exception("Empregado já validou este documento!");
}
else
{
throw new Exception("Essa não é uma imagem válida!");
}
}
}
if (Semelhanca != null)
{
return(Json(new { sucesso = "O Empregado '" + resultado + "' foi analisado com êxito." }));
}
else
{
return(Json(new { sucesso = "Empregado não encontrado!" }));
}
}
catch (Exception ex)
{
return(Json(new { erro = ex.Message }));
}
}
