private Amazon.Rekognition.Model.DetectLabelsResponse CallAWSServiceOperation(IAmazonRekognition client, Amazon.Rekognition.Model.DetectLabelsRequest request)
{
Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Rekognition", "DetectLabels");
try
{
#if DESKTOP
return(client.DetectLabels(request));
#elif CORECLR
return(client.DetectLabelsAsync(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;
}
}
public object Execute(ExecutorContext context)
{
System.IO.MemoryStream _ImageContentStream = null;
try
{
var cmdletContext = context as CmdletContext;
// create request
var request = new Amazon.Rekognition.Model.DetectLabelsRequest();
// 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;
}
if (cmdletContext.MaxLabel != null)
{
request.MaxLabels = cmdletContext.MaxLabel.Value;
}
if (cmdletContext.MinConfidence != null)
{
request.MinConfidence = cmdletContext.MinConfidence.Value;
}
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();
}
}
}
/// <summary>
/// Detects instances of real-world labels within an image (JPEG or PNG) provided as input.
/// This includes objects like flower, tree, and table; events like wedding, graduation,
/// and birthday party; and concepts like landscape, evening, and nature. For an example,
/// see <a>get-started-exercise-detect-labels</a>.
///
///
/// <para>
/// For each object, scene, and concept the API returns one or more labels. Each label
/// provides the object name, and the level of confidence that the image contains the
/// object. For example, suppose the input image has a lighthouse, the sea, and a rock.
/// The response will include all three labels, one for each object.
/// </para>
///
/// <para>
/// <code>{Name: lighthouse, Confidence: 98.4629}</code>
/// </para>
///
/// <para>
/// <code>{Name: rock,Confidence: 79.2097}</code>
/// </para>
///
/// <para>
/// <code> {Name: sea,Confidence: 75.061}</code>
/// </para>
///
/// <para>
/// In the preceding example, the operation returns one label for each of the three objects.
/// The operation can also return multiple labels for the same object in the image. For
/// example, if the input image shows a flower (for example, a tulip), the operation might
/// return the following three labels.
/// </para>
///
/// <para>
/// <code>{Name: flower,Confidence: 99.0562}</code>
/// </para>
///
/// <para>
/// <code>{Name: plant,Confidence: 99.0562}</code>
/// </para>
///
/// <para>
/// <code>{Name: tulip,Confidence: 99.0562}</code>
/// </para>
///
/// <para>
/// In this example, the detection algorithm more precisely identifies the flower as a
/// tulip.
/// </para>
///
/// <para>
/// You can provide the input image as an S3 object or as base64-encoded bytes. In response,
/// the API returns an array of labels. In addition, the response also includes the orientation
/// correction. Optionally, you can specify <code>MinConfidence</code> to control the
/// confidence threshold for the labels returned. The default is 50%. You can also add
/// the <code>MaxLabels</code> parameter to limit the number of labels returned.
/// </para>
/// <note>
/// <para>
/// If the object detected is a person, the operation doesn't provide the same facial
/// details that the <a>DetectFaces</a> operation provides.
/// </para>
/// </note>
/// <para>
/// This is a stateless API operation. That is, the operation does not persist any data.
/// </para>
///
/// <para>
/// This operation requires permissions to perform the <code>rekognition:DetectLabels</code>
/// action.
/// </para>
/// </summary>
/// <param name="request">Container for the necessary parameters to execute the DetectLabels service method.</param>
///
/// <returns>The response from the DetectLabels 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 DetectLabelsResponse DetectLabels(DetectLabelsRequest request)
{
var marshaller = new DetectLabelsRequestMarshaller();
var unmarshaller = DetectLabelsResponseUnmarshaller.Instance;
return Invoke<DetectLabelsRequest,DetectLabelsResponse>(request, marshaller, unmarshaller);
}
/// <summary>
/// Initiates the asynchronous execution of the DetectLabels operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DetectLabels 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 EndDetectLabels
/// operation.</returns>
public IAsyncResult BeginDetectLabels(DetectLabelsRequest request, AsyncCallback callback, object state)
{
var marshaller = new DetectLabelsRequestMarshaller();
var unmarshaller = DetectLabelsResponseUnmarshaller.Instance;
return BeginInvoke<DetectLabelsRequest>(request, marshaller, unmarshaller,
callback, state);
}
/// <summary>
/// Initiates the asynchronous execution of the DetectLabels operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DetectLabels 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<DetectLabelsResponse> DetectLabelsAsync(DetectLabelsRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var marshaller = new DetectLabelsRequestMarshaller();
var unmarshaller = DetectLabelsResponseUnmarshaller.Instance;
return InvokeAsync<DetectLabelsRequest,DetectLabelsResponse>(request, marshaller,
unmarshaller, cancellationToken);
}