/// <summary>
/// Initiates the asynchronous execution of the DetectFaces operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DetectFaces operation on AmazonRekognitionClient.</param>
/// <param name="callback">An AsyncCallback delegate that is invoked when the operation completes.</param>
/// <param name="state">A user-defined state object that is passed to the callback procedure. Retrieve this object from within the callback
/// procedure using the AsyncState property.</param>
///
/// <returns>An IAsyncResult that can be used to poll or wait for results, or both; this value is also needed when invoking EndDetectFaces
/// operation.</returns>
public IAsyncResult BeginDetectFaces(DetectFacesRequest request, AsyncCallback callback, object state)
{
var marshaller = new DetectFacesRequestMarshaller();
var unmarshaller = DetectFacesResponseUnmarshaller.Instance;
return BeginInvoke<DetectFacesRequest>(request, marshaller, unmarshaller,
callback, state);
}
/// <summary>
/// Detects faces within an image (JPEG or PNG) that is provided as input.
///
///
/// <para>
/// For each face detected, the operation returns face details including a bounding box
/// of the face, a confidence value (that the bounding box contains a face), and a fixed
/// set of attributes such as facial landmarks (for example, coordinates of eye and mouth),
/// gender, presence of beard, sunglasses, etc.
/// </para>
///
/// <para>
/// The face-detection algorithm is most effective on frontal faces. For non-frontal or
/// obscured faces, the algorithm may not detect the faces or might detect faces with
/// lower confidence.
/// </para>
/// <note>
/// <para>
/// This is a stateless API operation. That is, the operation does not persist any data.
/// </para>
/// </note>
/// <para>
/// For an example, see <a>get-started-exercise-detect-faces</a>.
/// </para>
///
/// <para>
/// This operation requires permissions to perform the <code>rekognition:DetectFaces</code>
/// action.
/// </para>
/// </summary>
/// <param name="request">Container for the necessary parameters to execute the DetectFaces service method.</param>
///
/// <returns>The response from the DetectFaces service method, as returned by Rekognition.</returns>
/// <exception cref="Amazon.Rekognition.Model.AccessDeniedException">
/// You are not authorized to perform the action.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.ImageTooLargeException">
/// The input image size exceeds the allowed limit. For more information, see <a>limits</a>.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.InternalServerErrorException">
/// Amazon Rekognition experienced a service issue. Try your call again.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.InvalidImageFormatException">
/// The provided image format is not supported.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.InvalidParameterException">
/// Input parameter violated a constraint. Validate your parameter before calling the
/// API again.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.InvalidS3ObjectException">
/// Amazon Rekognition is unable to access the S3 object specified in the request.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.ProvisionedThroughputExceededException">
/// The number of requests exceeded your throughput limit. If you want to increase this
/// limit, contact Amazon Rekognition.
/// </exception>
/// <exception cref="Amazon.Rekognition.Model.ThrottlingException">
/// Amazon Rekognition is temporarily unable to process the request. Try your call again.
/// </exception>
public DetectFacesResponse DetectFaces(DetectFacesRequest request)
{
var marshaller = new DetectFacesRequestMarshaller();
var unmarshaller = DetectFacesResponseUnmarshaller.Instance;
return Invoke<DetectFacesRequest,DetectFacesResponse>(request, marshaller, unmarshaller);
}
public object Execute(ExecutorContext context)
{
System.IO.MemoryStream _ImageContentStream = null;
try
{
var cmdletContext = context as CmdletContext;
// create request
var request = new Amazon.Rekognition.Model.DetectFacesRequest();
if (cmdletContext.Attribute != null)
{
request.Attributes = cmdletContext.Attribute;
}
// populate Image
var requestImageIsNull = true;
request.Image = new Amazon.Rekognition.Model.Image();
System.IO.MemoryStream requestImage_imageContent = null;
if (cmdletContext.ImageContent != null)
{
_ImageContentStream = new System.IO.MemoryStream(cmdletContext.ImageContent);
requestImage_imageContent = _ImageContentStream;
}
if (requestImage_imageContent != null)
{
request.Image.Bytes = requestImage_imageContent;
requestImageIsNull = false;
}
Amazon.Rekognition.Model.S3Object requestImage_image_S3Object = null;
// populate S3Object
var requestImage_image_S3ObjectIsNull = true;
requestImage_image_S3Object = new Amazon.Rekognition.Model.S3Object();
System.String requestImage_image_S3Object_imageBucket = null;
if (cmdletContext.ImageBucket != null)
{
requestImage_image_S3Object_imageBucket = cmdletContext.ImageBucket;
}
if (requestImage_image_S3Object_imageBucket != null)
{
requestImage_image_S3Object.Bucket = requestImage_image_S3Object_imageBucket;
requestImage_image_S3ObjectIsNull = false;
}
System.String requestImage_image_S3Object_imageName = null;
if (cmdletContext.ImageName != null)
{
requestImage_image_S3Object_imageName = cmdletContext.ImageName;
}
if (requestImage_image_S3Object_imageName != null)
{
requestImage_image_S3Object.Name = requestImage_image_S3Object_imageName;
requestImage_image_S3ObjectIsNull = false;
}
System.String requestImage_image_S3Object_imageVersion = null;
if (cmdletContext.ImageVersion != null)
{
requestImage_image_S3Object_imageVersion = cmdletContext.ImageVersion;
}
if (requestImage_image_S3Object_imageVersion != null)
{
requestImage_image_S3Object.Version = requestImage_image_S3Object_imageVersion;
requestImage_image_S3ObjectIsNull = false;
}
// determine if requestImage_image_S3Object should be set to null
if (requestImage_image_S3ObjectIsNull)
{
requestImage_image_S3Object = null;
}
if (requestImage_image_S3Object != null)
{
request.Image.S3Object = requestImage_image_S3Object;
requestImageIsNull = false;
}
// determine if request.Image should be set to null
if (requestImageIsNull)
{
request.Image = null;
}
CmdletOutput output;
// issue call
var client = Client ?? CreateClient(_CurrentCredentials, _RegionEndpoint);
try
{
var response = CallAWSServiceOperation(client, request);
object pipelineOutput = null;
pipelineOutput = cmdletContext.Select(response, this);
output = new CmdletOutput
{
PipelineOutput = pipelineOutput,
ServiceResponse = response
};
}
catch (Exception e)
{
output = new CmdletOutput {
ErrorResponse = e
};
}
return(output);
}
finally
{
if (_ImageContentStream != null)
{
_ImageContentStream.Dispose();
}
}
}
private Amazon.Rekognition.Model.DetectFacesResponse CallAWSServiceOperation(IAmazonRekognition client, Amazon.Rekognition.Model.DetectFacesRequest request)
{
Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Rekognition", "DetectFaces");
try
{
#if DESKTOP
return(client.DetectFaces(request));
#elif CORECLR
return(client.DetectFacesAsync(request).GetAwaiter().GetResult());
#else
#error "Unknown build edition"
#endif
}
catch (AmazonServiceException exc)
{
var webException = exc.InnerException as System.Net.WebException;
if (webException != null)
{
throw new Exception(Utils.Common.FormatNameResolutionFailureMessage(client.Config, webException.Message), webException);
}
throw;
}
}
/// <summary>
/// Initiates the asynchronous execution of the DetectFaces operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DetectFaces 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<DetectFacesResponse> DetectFacesAsync(DetectFacesRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var marshaller = new DetectFacesRequestMarshaller();
var unmarshaller = DetectFacesResponseUnmarshaller.Instance;
return InvokeAsync<DetectFacesRequest,DetectFacesResponse>(request, marshaller,
unmarshaller, cancellationToken);
}