static void Main(string[] args)
{
List <ILayer <NeuralUnit> > layers = new List <ILayer <NeuralUnit> >
{
new Input(2),
new Dense(2, Activation.Sigmoid),
new Dense(2, Activation.Sigmoid),
new Dense(1, Activation.Sigmoid)
};
CognitiveModel model = new CognitiveModel(layers);
model.Compile();
model.Fit((null, null), Cardiff.Fit.Algorithms.BackProp, 100);
}
public async Task <ActionResult> Upload(string userid, CognitiveModel request)
{
CloudStorageAccount storageConnection = CloudStorageAccount.Parse(ConnectionString);
CloudBlobClient blobClient = storageConnection.CreateCloudBlobClient();
CloudBlobContainer container = blobClient.GetContainerReference("faceimages");
if (await container.CreateIfNotExistsAsync())
{
await container.SetPermissionsAsync(new BlobContainerPermissions { PublicAccess = BlobContainerPublicAccessType.Blob });
}
var fileName = Guid.NewGuid().ToString() + ".jpg";
CloudBlockBlob cloudBlockBlob = container.GetBlockBlobReference(string.Format("{0}/{1}", userid, fileName));
cloudBlockBlob.Properties.ContentType = "image/jpg";
await cloudBlockBlob.UploadFromByteArrayAsync(request.ImgData, 0, request.ImgData.Length);
var response = new UploadResponse()
{
FileURL = cloudBlockBlob.Uri.AbsoluteUri,
UserId = userid.ToString()
};
IFaceClient client = Authenticate(ENDPOINT, SUBSCRIPTION_KEY);
var face = await DetectFaceExtract(client, cloudBlockBlob.Uri.AbsoluteUri, RecognitionModel.Recognition02);
if (face != null)
{
response.FaceId = face.FaceId.ToString();
}
var json = JsonConvert.SerializeObject(face);
response.Response = json;
return(Ok(response));
}
