Exemplo n.º 1
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        internal DetectLabelsResponse DetectLabels(DetectLabelsRequest request)
        {
            var marshaller   = new DetectLabelsRequestMarshaller();
            var unmarshaller = DetectLabelsResponseUnmarshaller.Instance;

            return(Invoke <DetectLabelsRequest, DetectLabelsResponse>(request, marshaller, unmarshaller));
        }
        public void DetectLabelsMarshallTest()
        {
            var request    = InstantiateClassGenerator.Execute <DetectLabelsRequest>();
            var marshaller = new DetectLabelsRequestMarshaller();

            var internalRequest = marshaller.Marshall(request);
            var jsonRequest     = UTF8Encoding.UTF8.GetString(internalRequest.Content);

            Comparer.CompareObjectToJson <DetectLabelsRequest>(request, jsonRequest);

            var webResponse = new WebResponseData
            {
                Headers =
                {
                    { "x-amzn-RequestId", Guid.NewGuid().ToString() },
                    { "x-amz-crc32",      "0"                       }
                }
            };
            var jsonResponse = new JsonSampleGenerator(service_model, service_model.FindOperation("DetectLabels").ResponseStructure).Execute();

            webResponse.Headers.Add("Content-Length", UTF8Encoding.UTF8.GetBytes(jsonResponse).Length.ToString());
            UnmarshallerContext context = new JsonUnmarshallerContext(Utils.CreateStreamFromString(jsonResponse), false, webResponse);
            var response = DetectLabelsResponseUnmarshaller.Instance.Unmarshall(context)
                           as DetectLabelsResponse;

            InstantiateClassGenerator.ValidateObjectFullyInstantiated(response);
        }
Exemplo n.º 3
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        /// <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));
        }
        public void DetectLabelsMarshallTest()
        {
            var request = InstantiateClassGenerator.Execute<DetectLabelsRequest>();
            var marshaller = new DetectLabelsRequestMarshaller();

            var internalRequest = marshaller.Marshall(request);
            var jsonRequest = UTF8Encoding.UTF8.GetString(internalRequest.Content);                        
            Comparer.CompareObjectToJson<DetectLabelsRequest>(request,jsonRequest);

            var webResponse = new WebResponseData
            {
                Headers = {
                    {"x-amzn-RequestId", Guid.NewGuid().ToString()},
                    {"x-amz-crc32","0"}
                }
            };
            var jsonResponse = new JsonSampleGenerator(service_model, service_model.FindOperation("DetectLabels").ResponseStructure).Execute();
            webResponse.Headers.Add("Content-Length", UTF8Encoding.UTF8.GetBytes(jsonResponse).Length.ToString());
            UnmarshallerContext context = new JsonUnmarshallerContext(Utils.CreateStreamFromString(jsonResponse), false, webResponse);
            var response = DetectLabelsResponseUnmarshaller.Instance.Unmarshall(context)
                as DetectLabelsResponse;
            InstantiateClassGenerator.ValidateObjectFullyInstantiated(response);
        }
Exemplo n.º 5
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        /// <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);
        }
Exemplo n.º 6
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        /// <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);
        }
Exemplo n.º 7
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        /// <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);
        }