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pxz-hos-client-cpp-module/support/aws-sdk-cpp-master/aws-cpp-sdk-rekognition/include/aws/rekognition/RekognitionClient.h

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/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include <aws/rekognition/Rekognition_EXPORTS.h>
#include <aws/rekognition/RekognitionErrors.h>
#include <aws/core/client/AWSError.h>
#include <aws/core/client/ClientConfiguration.h>
#include <aws/core/client/AWSClient.h>
#include <aws/core/utils/memory/stl/AWSString.h>
#include <aws/core/utils/json/JsonSerializer.h>
#include <aws/rekognition/model/CompareFacesResult.h>
#include <aws/rekognition/model/CreateCollectionResult.h>
#include <aws/rekognition/model/CreateProjectResult.h>
#include <aws/rekognition/model/CreateProjectVersionResult.h>
#include <aws/rekognition/model/CreateStreamProcessorResult.h>
#include <aws/rekognition/model/DeleteCollectionResult.h>
#include <aws/rekognition/model/DeleteFacesResult.h>
#include <aws/rekognition/model/DeleteProjectResult.h>
#include <aws/rekognition/model/DeleteProjectVersionResult.h>
#include <aws/rekognition/model/DeleteStreamProcessorResult.h>
#include <aws/rekognition/model/DescribeCollectionResult.h>
#include <aws/rekognition/model/DescribeProjectVersionsResult.h>
#include <aws/rekognition/model/DescribeProjectsResult.h>
#include <aws/rekognition/model/DescribeStreamProcessorResult.h>
#include <aws/rekognition/model/DetectCustomLabelsResult.h>
#include <aws/rekognition/model/DetectFacesResult.h>
#include <aws/rekognition/model/DetectLabelsResult.h>
#include <aws/rekognition/model/DetectModerationLabelsResult.h>
#include <aws/rekognition/model/DetectTextResult.h>
#include <aws/rekognition/model/GetCelebrityInfoResult.h>
#include <aws/rekognition/model/GetCelebrityRecognitionResult.h>
#include <aws/rekognition/model/GetContentModerationResult.h>
#include <aws/rekognition/model/GetFaceDetectionResult.h>
#include <aws/rekognition/model/GetFaceSearchResult.h>
#include <aws/rekognition/model/GetLabelDetectionResult.h>
#include <aws/rekognition/model/GetPersonTrackingResult.h>
#include <aws/rekognition/model/GetSegmentDetectionResult.h>
#include <aws/rekognition/model/GetTextDetectionResult.h>
#include <aws/rekognition/model/IndexFacesResult.h>
#include <aws/rekognition/model/ListCollectionsResult.h>
#include <aws/rekognition/model/ListFacesResult.h>
#include <aws/rekognition/model/ListStreamProcessorsResult.h>
#include <aws/rekognition/model/RecognizeCelebritiesResult.h>
#include <aws/rekognition/model/SearchFacesResult.h>
#include <aws/rekognition/model/SearchFacesByImageResult.h>
#include <aws/rekognition/model/StartCelebrityRecognitionResult.h>
#include <aws/rekognition/model/StartContentModerationResult.h>
#include <aws/rekognition/model/StartFaceDetectionResult.h>
#include <aws/rekognition/model/StartFaceSearchResult.h>
#include <aws/rekognition/model/StartLabelDetectionResult.h>
#include <aws/rekognition/model/StartPersonTrackingResult.h>
#include <aws/rekognition/model/StartProjectVersionResult.h>
#include <aws/rekognition/model/StartSegmentDetectionResult.h>
#include <aws/rekognition/model/StartStreamProcessorResult.h>
#include <aws/rekognition/model/StartTextDetectionResult.h>
#include <aws/rekognition/model/StopProjectVersionResult.h>
#include <aws/rekognition/model/StopStreamProcessorResult.h>
#include <aws/core/client/AsyncCallerContext.h>
#include <aws/core/http/HttpTypes.h>
#include <future>
#include <functional>
namespace Aws
{
namespace Http
{
class HttpClient;
class HttpClientFactory;
} // namespace Http
namespace Utils
{
template< typename R, typename E> class Outcome;
namespace Threading
{
class Executor;
} // namespace Threading
} // namespace Utils
namespace Auth
{
class AWSCredentials;
class AWSCredentialsProvider;
} // namespace Auth
namespace Client
{
class RetryStrategy;
} // namespace Client
namespace Rekognition
{
namespace Model
{
class CompareFacesRequest;
class CreateCollectionRequest;
class CreateProjectRequest;
class CreateProjectVersionRequest;
class CreateStreamProcessorRequest;
class DeleteCollectionRequest;
class DeleteFacesRequest;
class DeleteProjectRequest;
class DeleteProjectVersionRequest;
class DeleteStreamProcessorRequest;
class DescribeCollectionRequest;
class DescribeProjectVersionsRequest;
class DescribeProjectsRequest;
class DescribeStreamProcessorRequest;
class DetectCustomLabelsRequest;
class DetectFacesRequest;
class DetectLabelsRequest;
class DetectModerationLabelsRequest;
class DetectTextRequest;
class GetCelebrityInfoRequest;
class GetCelebrityRecognitionRequest;
class GetContentModerationRequest;
class GetFaceDetectionRequest;
class GetFaceSearchRequest;
class GetLabelDetectionRequest;
class GetPersonTrackingRequest;
class GetSegmentDetectionRequest;
class GetTextDetectionRequest;
class IndexFacesRequest;
class ListCollectionsRequest;
class ListFacesRequest;
class ListStreamProcessorsRequest;
class RecognizeCelebritiesRequest;
class SearchFacesRequest;
class SearchFacesByImageRequest;
class StartCelebrityRecognitionRequest;
class StartContentModerationRequest;
class StartFaceDetectionRequest;
class StartFaceSearchRequest;
class StartLabelDetectionRequest;
class StartPersonTrackingRequest;
class StartProjectVersionRequest;
class StartSegmentDetectionRequest;
class StartStreamProcessorRequest;
class StartTextDetectionRequest;
class StopProjectVersionRequest;
class StopStreamProcessorRequest;
typedef Aws::Utils::Outcome<CompareFacesResult, RekognitionError> CompareFacesOutcome;
typedef Aws::Utils::Outcome<CreateCollectionResult, RekognitionError> CreateCollectionOutcome;
typedef Aws::Utils::Outcome<CreateProjectResult, RekognitionError> CreateProjectOutcome;
typedef Aws::Utils::Outcome<CreateProjectVersionResult, RekognitionError> CreateProjectVersionOutcome;
typedef Aws::Utils::Outcome<CreateStreamProcessorResult, RekognitionError> CreateStreamProcessorOutcome;
typedef Aws::Utils::Outcome<DeleteCollectionResult, RekognitionError> DeleteCollectionOutcome;
typedef Aws::Utils::Outcome<DeleteFacesResult, RekognitionError> DeleteFacesOutcome;
typedef Aws::Utils::Outcome<DeleteProjectResult, RekognitionError> DeleteProjectOutcome;
typedef Aws::Utils::Outcome<DeleteProjectVersionResult, RekognitionError> DeleteProjectVersionOutcome;
typedef Aws::Utils::Outcome<DeleteStreamProcessorResult, RekognitionError> DeleteStreamProcessorOutcome;
typedef Aws::Utils::Outcome<DescribeCollectionResult, RekognitionError> DescribeCollectionOutcome;
typedef Aws::Utils::Outcome<DescribeProjectVersionsResult, RekognitionError> DescribeProjectVersionsOutcome;
typedef Aws::Utils::Outcome<DescribeProjectsResult, RekognitionError> DescribeProjectsOutcome;
typedef Aws::Utils::Outcome<DescribeStreamProcessorResult, RekognitionError> DescribeStreamProcessorOutcome;
typedef Aws::Utils::Outcome<DetectCustomLabelsResult, RekognitionError> DetectCustomLabelsOutcome;
typedef Aws::Utils::Outcome<DetectFacesResult, RekognitionError> DetectFacesOutcome;
typedef Aws::Utils::Outcome<DetectLabelsResult, RekognitionError> DetectLabelsOutcome;
typedef Aws::Utils::Outcome<DetectModerationLabelsResult, RekognitionError> DetectModerationLabelsOutcome;
typedef Aws::Utils::Outcome<DetectTextResult, RekognitionError> DetectTextOutcome;
typedef Aws::Utils::Outcome<GetCelebrityInfoResult, RekognitionError> GetCelebrityInfoOutcome;
typedef Aws::Utils::Outcome<GetCelebrityRecognitionResult, RekognitionError> GetCelebrityRecognitionOutcome;
typedef Aws::Utils::Outcome<GetContentModerationResult, RekognitionError> GetContentModerationOutcome;
typedef Aws::Utils::Outcome<GetFaceDetectionResult, RekognitionError> GetFaceDetectionOutcome;
typedef Aws::Utils::Outcome<GetFaceSearchResult, RekognitionError> GetFaceSearchOutcome;
typedef Aws::Utils::Outcome<GetLabelDetectionResult, RekognitionError> GetLabelDetectionOutcome;
typedef Aws::Utils::Outcome<GetPersonTrackingResult, RekognitionError> GetPersonTrackingOutcome;
typedef Aws::Utils::Outcome<GetSegmentDetectionResult, RekognitionError> GetSegmentDetectionOutcome;
typedef Aws::Utils::Outcome<GetTextDetectionResult, RekognitionError> GetTextDetectionOutcome;
typedef Aws::Utils::Outcome<IndexFacesResult, RekognitionError> IndexFacesOutcome;
typedef Aws::Utils::Outcome<ListCollectionsResult, RekognitionError> ListCollectionsOutcome;
typedef Aws::Utils::Outcome<ListFacesResult, RekognitionError> ListFacesOutcome;
typedef Aws::Utils::Outcome<ListStreamProcessorsResult, RekognitionError> ListStreamProcessorsOutcome;
typedef Aws::Utils::Outcome<RecognizeCelebritiesResult, RekognitionError> RecognizeCelebritiesOutcome;
typedef Aws::Utils::Outcome<SearchFacesResult, RekognitionError> SearchFacesOutcome;
typedef Aws::Utils::Outcome<SearchFacesByImageResult, RekognitionError> SearchFacesByImageOutcome;
typedef Aws::Utils::Outcome<StartCelebrityRecognitionResult, RekognitionError> StartCelebrityRecognitionOutcome;
typedef Aws::Utils::Outcome<StartContentModerationResult, RekognitionError> StartContentModerationOutcome;
typedef Aws::Utils::Outcome<StartFaceDetectionResult, RekognitionError> StartFaceDetectionOutcome;
typedef Aws::Utils::Outcome<StartFaceSearchResult, RekognitionError> StartFaceSearchOutcome;
typedef Aws::Utils::Outcome<StartLabelDetectionResult, RekognitionError> StartLabelDetectionOutcome;
typedef Aws::Utils::Outcome<StartPersonTrackingResult, RekognitionError> StartPersonTrackingOutcome;
typedef Aws::Utils::Outcome<StartProjectVersionResult, RekognitionError> StartProjectVersionOutcome;
typedef Aws::Utils::Outcome<StartSegmentDetectionResult, RekognitionError> StartSegmentDetectionOutcome;
typedef Aws::Utils::Outcome<StartStreamProcessorResult, RekognitionError> StartStreamProcessorOutcome;
typedef Aws::Utils::Outcome<StartTextDetectionResult, RekognitionError> StartTextDetectionOutcome;
typedef Aws::Utils::Outcome<StopProjectVersionResult, RekognitionError> StopProjectVersionOutcome;
typedef Aws::Utils::Outcome<StopStreamProcessorResult, RekognitionError> StopStreamProcessorOutcome;
typedef std::future<CompareFacesOutcome> CompareFacesOutcomeCallable;
typedef std::future<CreateCollectionOutcome> CreateCollectionOutcomeCallable;
typedef std::future<CreateProjectOutcome> CreateProjectOutcomeCallable;
typedef std::future<CreateProjectVersionOutcome> CreateProjectVersionOutcomeCallable;
typedef std::future<CreateStreamProcessorOutcome> CreateStreamProcessorOutcomeCallable;
typedef std::future<DeleteCollectionOutcome> DeleteCollectionOutcomeCallable;
typedef std::future<DeleteFacesOutcome> DeleteFacesOutcomeCallable;
typedef std::future<DeleteProjectOutcome> DeleteProjectOutcomeCallable;
typedef std::future<DeleteProjectVersionOutcome> DeleteProjectVersionOutcomeCallable;
typedef std::future<DeleteStreamProcessorOutcome> DeleteStreamProcessorOutcomeCallable;
typedef std::future<DescribeCollectionOutcome> DescribeCollectionOutcomeCallable;
typedef std::future<DescribeProjectVersionsOutcome> DescribeProjectVersionsOutcomeCallable;
typedef std::future<DescribeProjectsOutcome> DescribeProjectsOutcomeCallable;
typedef std::future<DescribeStreamProcessorOutcome> DescribeStreamProcessorOutcomeCallable;
typedef std::future<DetectCustomLabelsOutcome> DetectCustomLabelsOutcomeCallable;
typedef std::future<DetectFacesOutcome> DetectFacesOutcomeCallable;
typedef std::future<DetectLabelsOutcome> DetectLabelsOutcomeCallable;
typedef std::future<DetectModerationLabelsOutcome> DetectModerationLabelsOutcomeCallable;
typedef std::future<DetectTextOutcome> DetectTextOutcomeCallable;
typedef std::future<GetCelebrityInfoOutcome> GetCelebrityInfoOutcomeCallable;
typedef std::future<GetCelebrityRecognitionOutcome> GetCelebrityRecognitionOutcomeCallable;
typedef std::future<GetContentModerationOutcome> GetContentModerationOutcomeCallable;
typedef std::future<GetFaceDetectionOutcome> GetFaceDetectionOutcomeCallable;
typedef std::future<GetFaceSearchOutcome> GetFaceSearchOutcomeCallable;
typedef std::future<GetLabelDetectionOutcome> GetLabelDetectionOutcomeCallable;
typedef std::future<GetPersonTrackingOutcome> GetPersonTrackingOutcomeCallable;
typedef std::future<GetSegmentDetectionOutcome> GetSegmentDetectionOutcomeCallable;
typedef std::future<GetTextDetectionOutcome> GetTextDetectionOutcomeCallable;
typedef std::future<IndexFacesOutcome> IndexFacesOutcomeCallable;
typedef std::future<ListCollectionsOutcome> ListCollectionsOutcomeCallable;
typedef std::future<ListFacesOutcome> ListFacesOutcomeCallable;
typedef std::future<ListStreamProcessorsOutcome> ListStreamProcessorsOutcomeCallable;
typedef std::future<RecognizeCelebritiesOutcome> RecognizeCelebritiesOutcomeCallable;
typedef std::future<SearchFacesOutcome> SearchFacesOutcomeCallable;
typedef std::future<SearchFacesByImageOutcome> SearchFacesByImageOutcomeCallable;
typedef std::future<StartCelebrityRecognitionOutcome> StartCelebrityRecognitionOutcomeCallable;
typedef std::future<StartContentModerationOutcome> StartContentModerationOutcomeCallable;
typedef std::future<StartFaceDetectionOutcome> StartFaceDetectionOutcomeCallable;
typedef std::future<StartFaceSearchOutcome> StartFaceSearchOutcomeCallable;
typedef std::future<StartLabelDetectionOutcome> StartLabelDetectionOutcomeCallable;
typedef std::future<StartPersonTrackingOutcome> StartPersonTrackingOutcomeCallable;
typedef std::future<StartProjectVersionOutcome> StartProjectVersionOutcomeCallable;
typedef std::future<StartSegmentDetectionOutcome> StartSegmentDetectionOutcomeCallable;
typedef std::future<StartStreamProcessorOutcome> StartStreamProcessorOutcomeCallable;
typedef std::future<StartTextDetectionOutcome> StartTextDetectionOutcomeCallable;
typedef std::future<StopProjectVersionOutcome> StopProjectVersionOutcomeCallable;
typedef std::future<StopStreamProcessorOutcome> StopStreamProcessorOutcomeCallable;
} // namespace Model
class RekognitionClient;
typedef std::function<void(const RekognitionClient*, const Model::CompareFacesRequest&, const Model::CompareFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CompareFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::CreateCollectionRequest&, const Model::CreateCollectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateCollectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::CreateProjectRequest&, const Model::CreateProjectOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateProjectResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::CreateProjectVersionRequest&, const Model::CreateProjectVersionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateProjectVersionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::CreateStreamProcessorRequest&, const Model::CreateStreamProcessorOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateStreamProcessorResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DeleteCollectionRequest&, const Model::DeleteCollectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteCollectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DeleteFacesRequest&, const Model::DeleteFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DeleteProjectRequest&, const Model::DeleteProjectOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteProjectResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DeleteProjectVersionRequest&, const Model::DeleteProjectVersionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteProjectVersionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DeleteStreamProcessorRequest&, const Model::DeleteStreamProcessorOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteStreamProcessorResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DescribeCollectionRequest&, const Model::DescribeCollectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeCollectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DescribeProjectVersionsRequest&, const Model::DescribeProjectVersionsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeProjectVersionsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DescribeProjectsRequest&, const Model::DescribeProjectsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeProjectsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DescribeStreamProcessorRequest&, const Model::DescribeStreamProcessorOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeStreamProcessorResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DetectCustomLabelsRequest&, const Model::DetectCustomLabelsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectCustomLabelsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DetectFacesRequest&, const Model::DetectFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DetectLabelsRequest&, const Model::DetectLabelsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectLabelsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DetectModerationLabelsRequest&, const Model::DetectModerationLabelsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectModerationLabelsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::DetectTextRequest&, const Model::DetectTextOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DetectTextResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetCelebrityInfoRequest&, const Model::GetCelebrityInfoOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetCelebrityInfoResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetCelebrityRecognitionRequest&, const Model::GetCelebrityRecognitionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetCelebrityRecognitionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetContentModerationRequest&, const Model::GetContentModerationOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetContentModerationResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetFaceDetectionRequest&, const Model::GetFaceDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetFaceDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetFaceSearchRequest&, const Model::GetFaceSearchOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetFaceSearchResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetLabelDetectionRequest&, const Model::GetLabelDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetLabelDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetPersonTrackingRequest&, const Model::GetPersonTrackingOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetPersonTrackingResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetSegmentDetectionRequest&, const Model::GetSegmentDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetSegmentDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::GetTextDetectionRequest&, const Model::GetTextDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetTextDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::IndexFacesRequest&, const Model::IndexFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > IndexFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::ListCollectionsRequest&, const Model::ListCollectionsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListCollectionsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::ListFacesRequest&, const Model::ListFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::ListStreamProcessorsRequest&, const Model::ListStreamProcessorsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListStreamProcessorsResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::RecognizeCelebritiesRequest&, const Model::RecognizeCelebritiesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > RecognizeCelebritiesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::SearchFacesRequest&, const Model::SearchFacesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > SearchFacesResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::SearchFacesByImageRequest&, const Model::SearchFacesByImageOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > SearchFacesByImageResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartCelebrityRecognitionRequest&, const Model::StartCelebrityRecognitionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartCelebrityRecognitionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartContentModerationRequest&, const Model::StartContentModerationOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartContentModerationResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartFaceDetectionRequest&, const Model::StartFaceDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartFaceDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartFaceSearchRequest&, const Model::StartFaceSearchOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartFaceSearchResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartLabelDetectionRequest&, const Model::StartLabelDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartLabelDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartPersonTrackingRequest&, const Model::StartPersonTrackingOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartPersonTrackingResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartProjectVersionRequest&, const Model::StartProjectVersionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartProjectVersionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartSegmentDetectionRequest&, const Model::StartSegmentDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartSegmentDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartStreamProcessorRequest&, const Model::StartStreamProcessorOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartStreamProcessorResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StartTextDetectionRequest&, const Model::StartTextDetectionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartTextDetectionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StopProjectVersionRequest&, const Model::StopProjectVersionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopProjectVersionResponseReceivedHandler;
typedef std::function<void(const RekognitionClient*, const Model::StopStreamProcessorRequest&, const Model::StopStreamProcessorOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopStreamProcessorResponseReceivedHandler;
/**
* <p>This is the Amazon Rekognition API reference.</p>
*/
class AWS_REKOGNITION_API RekognitionClient : public Aws::Client::AWSJsonClient
{
public:
typedef Aws::Client::AWSJsonClient BASECLASS;
/**
* Initializes client to use DefaultCredentialProviderChain, with default http client factory, and optional client config. If client config
* is not specified, it will be initialized to default values.
*/
RekognitionClient(const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
/**
* Initializes client to use SimpleAWSCredentialsProvider, with default http client factory, and optional client config. If client config
* is not specified, it will be initialized to default values.
*/
RekognitionClient(const Aws::Auth::AWSCredentials& credentials, const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
/**
* Initializes client to use specified credentials provider with specified client config. If http client factory is not supplied,
* the default http client factory will be used
*/
RekognitionClient(const std::shared_ptr<Aws::Auth::AWSCredentialsProvider>& credentialsProvider,
const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
virtual ~RekognitionClient();
/**
* <p>Compares a face in the <i>source</i> input image with each of the 100 largest
* faces detected in the <i>target</i> input image. </p> <p> If the source
* image contains multiple faces, the service detects the largest face and compares
* it with each face detected in the target image. </p> <p>You pass the
* input and target images either as base64-encoded image bytes or as references to
* images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes isn't supported. The image must be formatted as
* a PNG or JPEG file. </p> <p>In response, the operation returns an array of face
* matches ordered by similarity score in descending order. For each face match,
* the response provides a bounding box of the face, facial landmarks, pose details
* (pitch, role, and yaw), quality (brightness and sharpness), and confidence value
* (indicating the level of confidence that the bounding box contains a face). The
* response also provides a similarity score, which indicates how closely the faces
* match. </p> <p>By default, only faces with a similarity score of greater
* than or equal to 80% are returned in the response. You can change this value by
* specifying the <code>SimilarityThreshold</code> parameter.</p> <p>
* <code>CompareFaces</code> also returns an array of faces that don't match the
* source image. For each face, it returns a bounding box, confidence value,
* landmarks, pose details, and quality. The response also returns information
* about the face in the source image, including the bounding box of the face and
* confidence value.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>. </p> <p>To use quality filtering, you need a
* collection associated with version 3 of the face model or higher. To get the
* version of the face model associated with a collection, call
* <a>DescribeCollection</a>. </p> <p>If the image doesn't contain Exif
* metadata, <code>CompareFaces</code> returns orientation information for the
* source and target images. Use these values to display the images with the
* correct image orientation.</p> <p>If no faces are detected in the source or
* target images, <code>CompareFaces</code> returns an
* <code>InvalidParameterException</code> error. </p> <p> This is a
* stateless API operation. That is, data returned by this operation doesn't
* persist.</p> <p>For an example, see Comparing Faces in Images in the
* Amazon Rekognition Developer Guide.</p> <p>This operation requires permissions
* to perform the <code>rekognition:CompareFaces</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CompareFaces">AWS
* API Reference</a></p>
*/
virtual Model::CompareFacesOutcome CompareFaces(const Model::CompareFacesRequest& request) const;
/**
* <p>Compares a face in the <i>source</i> input image with each of the 100 largest
* faces detected in the <i>target</i> input image. </p> <p> If the source
* image contains multiple faces, the service detects the largest face and compares
* it with each face detected in the target image. </p> <p>You pass the
* input and target images either as base64-encoded image bytes or as references to
* images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes isn't supported. The image must be formatted as
* a PNG or JPEG file. </p> <p>In response, the operation returns an array of face
* matches ordered by similarity score in descending order. For each face match,
* the response provides a bounding box of the face, facial landmarks, pose details
* (pitch, role, and yaw), quality (brightness and sharpness), and confidence value
* (indicating the level of confidence that the bounding box contains a face). The
* response also provides a similarity score, which indicates how closely the faces
* match. </p> <p>By default, only faces with a similarity score of greater
* than or equal to 80% are returned in the response. You can change this value by
* specifying the <code>SimilarityThreshold</code> parameter.</p> <p>
* <code>CompareFaces</code> also returns an array of faces that don't match the
* source image. For each face, it returns a bounding box, confidence value,
* landmarks, pose details, and quality. The response also returns information
* about the face in the source image, including the bounding box of the face and
* confidence value.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>. </p> <p>To use quality filtering, you need a
* collection associated with version 3 of the face model or higher. To get the
* version of the face model associated with a collection, call
* <a>DescribeCollection</a>. </p> <p>If the image doesn't contain Exif
* metadata, <code>CompareFaces</code> returns orientation information for the
* source and target images. Use these values to display the images with the
* correct image orientation.</p> <p>If no faces are detected in the source or
* target images, <code>CompareFaces</code> returns an
* <code>InvalidParameterException</code> error. </p> <p> This is a
* stateless API operation. That is, data returned by this operation doesn't
* persist.</p> <p>For an example, see Comparing Faces in Images in the
* Amazon Rekognition Developer Guide.</p> <p>This operation requires permissions
* to perform the <code>rekognition:CompareFaces</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CompareFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CompareFacesOutcomeCallable CompareFacesCallable(const Model::CompareFacesRequest& request) const;
/**
* <p>Compares a face in the <i>source</i> input image with each of the 100 largest
* faces detected in the <i>target</i> input image. </p> <p> If the source
* image contains multiple faces, the service detects the largest face and compares
* it with each face detected in the target image. </p> <p>You pass the
* input and target images either as base64-encoded image bytes or as references to
* images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes isn't supported. The image must be formatted as
* a PNG or JPEG file. </p> <p>In response, the operation returns an array of face
* matches ordered by similarity score in descending order. For each face match,
* the response provides a bounding box of the face, facial landmarks, pose details
* (pitch, role, and yaw), quality (brightness and sharpness), and confidence value
* (indicating the level of confidence that the bounding box contains a face). The
* response also provides a similarity score, which indicates how closely the faces
* match. </p> <p>By default, only faces with a similarity score of greater
* than or equal to 80% are returned in the response. You can change this value by
* specifying the <code>SimilarityThreshold</code> parameter.</p> <p>
* <code>CompareFaces</code> also returns an array of faces that don't match the
* source image. For each face, it returns a bounding box, confidence value,
* landmarks, pose details, and quality. The response also returns information
* about the face in the source image, including the bounding box of the face and
* confidence value.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>. </p> <p>To use quality filtering, you need a
* collection associated with version 3 of the face model or higher. To get the
* version of the face model associated with a collection, call
* <a>DescribeCollection</a>. </p> <p>If the image doesn't contain Exif
* metadata, <code>CompareFaces</code> returns orientation information for the
* source and target images. Use these values to display the images with the
* correct image orientation.</p> <p>If no faces are detected in the source or
* target images, <code>CompareFaces</code> returns an
* <code>InvalidParameterException</code> error. </p> <p> This is a
* stateless API operation. That is, data returned by this operation doesn't
* persist.</p> <p>For an example, see Comparing Faces in Images in the
* Amazon Rekognition Developer Guide.</p> <p>This operation requires permissions
* to perform the <code>rekognition:CompareFaces</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CompareFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CompareFacesAsync(const Model::CompareFacesRequest& request, const CompareFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a collection in an AWS Region. You can add faces to the collection
* using the <a>IndexFaces</a> operation. </p> <p>For example, you might create
* collections, one for each of your application users. A user can then index faces
* using the <code>IndexFaces</code> operation and persist results in a specific
* collection. Then, a user can search the collection for faces in the
* user-specific container. </p> <p>When you create a collection, it is associated
* with the latest version of the face model version.</p> <p>Collection
* names are case-sensitive.</p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateCollection</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateCollection">AWS
* API Reference</a></p>
*/
virtual Model::CreateCollectionOutcome CreateCollection(const Model::CreateCollectionRequest& request) const;
/**
* <p>Creates a collection in an AWS Region. You can add faces to the collection
* using the <a>IndexFaces</a> operation. </p> <p>For example, you might create
* collections, one for each of your application users. A user can then index faces
* using the <code>IndexFaces</code> operation and persist results in a specific
* collection. Then, a user can search the collection for faces in the
* user-specific container. </p> <p>When you create a collection, it is associated
* with the latest version of the face model version.</p> <p>Collection
* names are case-sensitive.</p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateCollection</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateCollection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateCollectionOutcomeCallable CreateCollectionCallable(const Model::CreateCollectionRequest& request) const;
/**
* <p>Creates a collection in an AWS Region. You can add faces to the collection
* using the <a>IndexFaces</a> operation. </p> <p>For example, you might create
* collections, one for each of your application users. A user can then index faces
* using the <code>IndexFaces</code> operation and persist results in a specific
* collection. Then, a user can search the collection for faces in the
* user-specific container. </p> <p>When you create a collection, it is associated
* with the latest version of the face model version.</p> <p>Collection
* names are case-sensitive.</p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateCollection</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateCollection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateCollectionAsync(const Model::CreateCollectionRequest& request, const CreateCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a new Amazon Rekognition Custom Labels project. A project is a
* logical grouping of resources (images, Labels, models) and operations (training,
* evaluation and detection). </p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateProject</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProject">AWS
* API Reference</a></p>
*/
virtual Model::CreateProjectOutcome CreateProject(const Model::CreateProjectRequest& request) const;
/**
* <p>Creates a new Amazon Rekognition Custom Labels project. A project is a
* logical grouping of resources (images, Labels, models) and operations (training,
* evaluation and detection). </p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateProject</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProject">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateProjectOutcomeCallable CreateProjectCallable(const Model::CreateProjectRequest& request) const;
/**
* <p>Creates a new Amazon Rekognition Custom Labels project. A project is a
* logical grouping of resources (images, Labels, models) and operations (training,
* evaluation and detection). </p> <p>This operation requires permissions to
* perform the <code>rekognition:CreateProject</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProject">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateProjectAsync(const Model::CreateProjectRequest& request, const CreateProjectResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a new version of a model and begins training. Models are managed as
* part of an Amazon Rekognition Custom Labels project. You can specify one
* training dataset and one testing dataset. The response from
* <code>CreateProjectVersion</code> is an Amazon Resource Name (ARN) for the
* version of the model. </p> <p>Training takes a while to complete. You can get
* the current status by calling <a>DescribeProjectVersions</a>.</p> <p>Once
* training has successfully completed, call <a>DescribeProjectVersions</a> to get
* the training results and evaluate the model. </p> <p>After evaluating the model,
* you start the model by calling <a>StartProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:CreateProjectVersion</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProjectVersion">AWS
* API Reference</a></p>
*/
virtual Model::CreateProjectVersionOutcome CreateProjectVersion(const Model::CreateProjectVersionRequest& request) const;
/**
* <p>Creates a new version of a model and begins training. Models are managed as
* part of an Amazon Rekognition Custom Labels project. You can specify one
* training dataset and one testing dataset. The response from
* <code>CreateProjectVersion</code> is an Amazon Resource Name (ARN) for the
* version of the model. </p> <p>Training takes a while to complete. You can get
* the current status by calling <a>DescribeProjectVersions</a>.</p> <p>Once
* training has successfully completed, call <a>DescribeProjectVersions</a> to get
* the training results and evaluate the model. </p> <p>After evaluating the model,
* you start the model by calling <a>StartProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:CreateProjectVersion</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProjectVersion">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateProjectVersionOutcomeCallable CreateProjectVersionCallable(const Model::CreateProjectVersionRequest& request) const;
/**
* <p>Creates a new version of a model and begins training. Models are managed as
* part of an Amazon Rekognition Custom Labels project. You can specify one
* training dataset and one testing dataset. The response from
* <code>CreateProjectVersion</code> is an Amazon Resource Name (ARN) for the
* version of the model. </p> <p>Training takes a while to complete. You can get
* the current status by calling <a>DescribeProjectVersions</a>.</p> <p>Once
* training has successfully completed, call <a>DescribeProjectVersions</a> to get
* the training results and evaluate the model. </p> <p>After evaluating the model,
* you start the model by calling <a>StartProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:CreateProjectVersion</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateProjectVersion">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateProjectVersionAsync(const Model::CreateProjectVersionRequest& request, const CreateProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates an Amazon Rekognition stream processor that you can use to detect and
* recognize faces in a streaming video.</p> <p>Amazon Rekognition Video is a
* consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition
* Video sends analysis results to Amazon Kinesis Data Streams.</p> <p>You provide
* as input a Kinesis video stream (<code>Input</code>) and a Kinesis data stream
* (<code>Output</code>) stream. You also specify the face recognition criteria in
* <code>Settings</code>. For example, the collection containing faces that you
* want to recognize. Use <code>Name</code> to assign an identifier for the stream
* processor. You use <code>Name</code> to manage the stream processor. For
* example, you can start processing the source video by calling
* <a>StartStreamProcessor</a> with the <code>Name</code> field. </p> <p>After you
* have finished analyzing a streaming video, use <a>StopStreamProcessor</a> to
* stop processing. You can delete the stream processor by calling
* <a>DeleteStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateStreamProcessor">AWS
* API Reference</a></p>
*/
virtual Model::CreateStreamProcessorOutcome CreateStreamProcessor(const Model::CreateStreamProcessorRequest& request) const;
/**
* <p>Creates an Amazon Rekognition stream processor that you can use to detect and
* recognize faces in a streaming video.</p> <p>Amazon Rekognition Video is a
* consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition
* Video sends analysis results to Amazon Kinesis Data Streams.</p> <p>You provide
* as input a Kinesis video stream (<code>Input</code>) and a Kinesis data stream
* (<code>Output</code>) stream. You also specify the face recognition criteria in
* <code>Settings</code>. For example, the collection containing faces that you
* want to recognize. Use <code>Name</code> to assign an identifier for the stream
* processor. You use <code>Name</code> to manage the stream processor. For
* example, you can start processing the source video by calling
* <a>StartStreamProcessor</a> with the <code>Name</code> field. </p> <p>After you
* have finished analyzing a streaming video, use <a>StopStreamProcessor</a> to
* stop processing. You can delete the stream processor by calling
* <a>DeleteStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateStreamProcessor">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateStreamProcessorOutcomeCallable CreateStreamProcessorCallable(const Model::CreateStreamProcessorRequest& request) const;
/**
* <p>Creates an Amazon Rekognition stream processor that you can use to detect and
* recognize faces in a streaming video.</p> <p>Amazon Rekognition Video is a
* consumer of live video from Amazon Kinesis Video Streams. Amazon Rekognition
* Video sends analysis results to Amazon Kinesis Data Streams.</p> <p>You provide
* as input a Kinesis video stream (<code>Input</code>) and a Kinesis data stream
* (<code>Output</code>) stream. You also specify the face recognition criteria in
* <code>Settings</code>. For example, the collection containing faces that you
* want to recognize. Use <code>Name</code> to assign an identifier for the stream
* processor. You use <code>Name</code> to manage the stream processor. For
* example, you can start processing the source video by calling
* <a>StartStreamProcessor</a> with the <code>Name</code> field. </p> <p>After you
* have finished analyzing a streaming video, use <a>StopStreamProcessor</a> to
* stop processing. You can delete the stream processor by calling
* <a>DeleteStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/CreateStreamProcessor">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateStreamProcessorAsync(const Model::CreateStreamProcessorRequest& request, const CreateStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the specified collection. Note that this operation removes all faces
* in the collection. For an example, see <a>delete-collection-procedure</a>.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:DeleteCollection</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteCollection">AWS
* API Reference</a></p>
*/
virtual Model::DeleteCollectionOutcome DeleteCollection(const Model::DeleteCollectionRequest& request) const;
/**
* <p>Deletes the specified collection. Note that this operation removes all faces
* in the collection. For an example, see <a>delete-collection-procedure</a>.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:DeleteCollection</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteCollection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteCollectionOutcomeCallable DeleteCollectionCallable(const Model::DeleteCollectionRequest& request) const;
/**
* <p>Deletes the specified collection. Note that this operation removes all faces
* in the collection. For an example, see <a>delete-collection-procedure</a>.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:DeleteCollection</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteCollection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteCollectionAsync(const Model::DeleteCollectionRequest& request, const DeleteCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes faces from a collection. You specify a collection ID and an array of
* face IDs to remove from the collection.</p> <p>This operation requires
* permissions to perform the <code>rekognition:DeleteFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteFaces">AWS
* API Reference</a></p>
*/
virtual Model::DeleteFacesOutcome DeleteFaces(const Model::DeleteFacesRequest& request) const;
/**
* <p>Deletes faces from a collection. You specify a collection ID and an array of
* face IDs to remove from the collection.</p> <p>This operation requires
* permissions to perform the <code>rekognition:DeleteFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteFacesOutcomeCallable DeleteFacesCallable(const Model::DeleteFacesRequest& request) const;
/**
* <p>Deletes faces from a collection. You specify a collection ID and an array of
* face IDs to remove from the collection.</p> <p>This operation requires
* permissions to perform the <code>rekognition:DeleteFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteFacesAsync(const Model::DeleteFacesRequest& request, const DeleteFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels project. To delete a project you
* must first delete all models associated with the project. To delete a model, see
* <a>DeleteProjectVersion</a>.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DeleteProject</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProject">AWS
* API Reference</a></p>
*/
virtual Model::DeleteProjectOutcome DeleteProject(const Model::DeleteProjectRequest& request) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels project. To delete a project you
* must first delete all models associated with the project. To delete a model, see
* <a>DeleteProjectVersion</a>.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DeleteProject</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProject">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteProjectOutcomeCallable DeleteProjectCallable(const Model::DeleteProjectRequest& request) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels project. To delete a project you
* must first delete all models associated with the project. To delete a model, see
* <a>DeleteProjectVersion</a>.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DeleteProject</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProject">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteProjectAsync(const Model::DeleteProjectRequest& request, const DeleteProjectResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels model. </p> <p>You can't delete a
* model if it is running or if it is training. To check the status of a model, use
* the <code>Status</code> field returned from <a>DescribeProjectVersions</a>. To
* stop a running model call <a>StopProjectVersion</a>. If the model is training,
* wait until it finishes.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DeleteProjectVersion</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProjectVersion">AWS
* API Reference</a></p>
*/
virtual Model::DeleteProjectVersionOutcome DeleteProjectVersion(const Model::DeleteProjectVersionRequest& request) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels model. </p> <p>You can't delete a
* model if it is running or if it is training. To check the status of a model, use
* the <code>Status</code> field returned from <a>DescribeProjectVersions</a>. To
* stop a running model call <a>StopProjectVersion</a>. If the model is training,
* wait until it finishes.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DeleteProjectVersion</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProjectVersion">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteProjectVersionOutcomeCallable DeleteProjectVersionCallable(const Model::DeleteProjectVersionRequest& request) const;
/**
* <p>Deletes an Amazon Rekognition Custom Labels model. </p> <p>You can't delete a
* model if it is running or if it is training. To check the status of a model, use
* the <code>Status</code> field returned from <a>DescribeProjectVersions</a>. To
* stop a running model call <a>StopProjectVersion</a>. If the model is training,
* wait until it finishes.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DeleteProjectVersion</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteProjectVersion">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteProjectVersionAsync(const Model::DeleteProjectVersionRequest& request, const DeleteProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the stream processor identified by <code>Name</code>. You assign the
* value for <code>Name</code> when you create the stream processor with
* <a>CreateStreamProcessor</a>. You might not be able to use the same name for a
* stream processor for a few seconds after calling
* <code>DeleteStreamProcessor</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteStreamProcessor">AWS
* API Reference</a></p>
*/
virtual Model::DeleteStreamProcessorOutcome DeleteStreamProcessor(const Model::DeleteStreamProcessorRequest& request) const;
/**
* <p>Deletes the stream processor identified by <code>Name</code>. You assign the
* value for <code>Name</code> when you create the stream processor with
* <a>CreateStreamProcessor</a>. You might not be able to use the same name for a
* stream processor for a few seconds after calling
* <code>DeleteStreamProcessor</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteStreamProcessor">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteStreamProcessorOutcomeCallable DeleteStreamProcessorCallable(const Model::DeleteStreamProcessorRequest& request) const;
/**
* <p>Deletes the stream processor identified by <code>Name</code>. You assign the
* value for <code>Name</code> when you create the stream processor with
* <a>CreateStreamProcessor</a>. You might not be able to use the same name for a
* stream processor for a few seconds after calling
* <code>DeleteStreamProcessor</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DeleteStreamProcessor">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteStreamProcessorAsync(const Model::DeleteStreamProcessorRequest& request, const DeleteStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Describes the specified collection. You can use
* <code>DescribeCollection</code> to get information, such as the number of faces
* indexed into a collection and the version of the model used by the collection
* for face detection.</p> <p>For more information, see Describing a Collection in
* the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeCollection">AWS
* API Reference</a></p>
*/
virtual Model::DescribeCollectionOutcome DescribeCollection(const Model::DescribeCollectionRequest& request) const;
/**
* <p>Describes the specified collection. You can use
* <code>DescribeCollection</code> to get information, such as the number of faces
* indexed into a collection and the version of the model used by the collection
* for face detection.</p> <p>For more information, see Describing a Collection in
* the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeCollection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeCollectionOutcomeCallable DescribeCollectionCallable(const Model::DescribeCollectionRequest& request) const;
/**
* <p>Describes the specified collection. You can use
* <code>DescribeCollection</code> to get information, such as the number of faces
* indexed into a collection and the version of the model used by the collection
* for face detection.</p> <p>For more information, see Describing a Collection in
* the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeCollection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeCollectionAsync(const Model::DescribeCollectionRequest& request, const DescribeCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists and describes the models in an Amazon Rekognition Custom Labels
* project. You can specify up to 10 model versions in
* <code>ProjectVersionArns</code>. If you don't specify a value, descriptions for
* all models are returned.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DescribeProjectVersions</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjectVersions">AWS
* API Reference</a></p>
*/
virtual Model::DescribeProjectVersionsOutcome DescribeProjectVersions(const Model::DescribeProjectVersionsRequest& request) const;
/**
* <p>Lists and describes the models in an Amazon Rekognition Custom Labels
* project. You can specify up to 10 model versions in
* <code>ProjectVersionArns</code>. If you don't specify a value, descriptions for
* all models are returned.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DescribeProjectVersions</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjectVersions">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeProjectVersionsOutcomeCallable DescribeProjectVersionsCallable(const Model::DescribeProjectVersionsRequest& request) const;
/**
* <p>Lists and describes the models in an Amazon Rekognition Custom Labels
* project. You can specify up to 10 model versions in
* <code>ProjectVersionArns</code>. If you don't specify a value, descriptions for
* all models are returned.</p> <p>This operation requires permissions to perform
* the <code>rekognition:DescribeProjectVersions</code> action.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjectVersions">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeProjectVersionsAsync(const Model::DescribeProjectVersionsRequest& request, const DescribeProjectVersionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists and gets information about your Amazon Rekognition Custom Labels
* projects.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DescribeProjects</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjects">AWS
* API Reference</a></p>
*/
virtual Model::DescribeProjectsOutcome DescribeProjects(const Model::DescribeProjectsRequest& request) const;
/**
* <p>Lists and gets information about your Amazon Rekognition Custom Labels
* projects.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DescribeProjects</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjects">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeProjectsOutcomeCallable DescribeProjectsCallable(const Model::DescribeProjectsRequest& request) const;
/**
* <p>Lists and gets information about your Amazon Rekognition Custom Labels
* projects.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DescribeProjects</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeProjects">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeProjectsAsync(const Model::DescribeProjectsRequest& request, const DescribeProjectsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Provides information about a stream processor created by
* <a>CreateStreamProcessor</a>. You can get information about the input and output
* streams, the input parameters for the face recognition being performed, and the
* current status of the stream processor.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeStreamProcessor">AWS
* API Reference</a></p>
*/
virtual Model::DescribeStreamProcessorOutcome DescribeStreamProcessor(const Model::DescribeStreamProcessorRequest& request) const;
/**
* <p>Provides information about a stream processor created by
* <a>CreateStreamProcessor</a>. You can get information about the input and output
* streams, the input parameters for the face recognition being performed, and the
* current status of the stream processor.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeStreamProcessor">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeStreamProcessorOutcomeCallable DescribeStreamProcessorCallable(const Model::DescribeStreamProcessorRequest& request) const;
/**
* <p>Provides information about a stream processor created by
* <a>CreateStreamProcessor</a>. You can get information about the input and output
* streams, the input parameters for the face recognition being performed, and the
* current status of the stream processor.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DescribeStreamProcessor">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeStreamProcessorAsync(const Model::DescribeStreamProcessorRequest& request, const DescribeStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects custom labels in a supplied image by using an Amazon Rekognition
* Custom Labels model. </p> <p>You specify which version of a model version to use
* by using the <code>ProjectVersionArn</code> input parameter. </p> <p>You pass
* the input image as base64-encoded image bytes or as a reference to an image in
* an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p> For each object that the model version detects
* on an image, the API returns a (<code>CustomLabel</code>) object in an array
* (<code>CustomLabels</code>). Each <code>CustomLabel</code> object provides the
* label name (<code>Name</code>), the level of confidence that the image contains
* the object (<code>Confidence</code>), and object location information, if it
* exists, for the label on the image (<code>Geometry</code>). </p> <p>During
* training model calculates a threshold value that determines if a prediction for
* a label is true. By default, <code>DetectCustomLabels</code> doesn't return
* labels whose confidence value is below the model's calculated threshold value.
* To filter labels that are returned, specify a value for
* <code>MinConfidence</code> that is higher than the model's calculated threshold.
* You can get the model's calculated threshold from the model's training results
* shown in the Amazon Rekognition Custom Labels console. To get all labels,
* regardless of confidence, specify a <code>MinConfidence</code> value of 0. </p>
* <p>You can also add the <code>MaxResults</code> parameter to limit the number of
* labels returned. </p> <p>This is a stateless API operation. That is, the
* operation does not persist any data.</p> <p>This operation requires permissions
* to perform the <code>rekognition:DetectCustomLabels</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectCustomLabels">AWS
* API Reference</a></p>
*/
virtual Model::DetectCustomLabelsOutcome DetectCustomLabels(const Model::DetectCustomLabelsRequest& request) const;
/**
* <p>Detects custom labels in a supplied image by using an Amazon Rekognition
* Custom Labels model. </p> <p>You specify which version of a model version to use
* by using the <code>ProjectVersionArn</code> input parameter. </p> <p>You pass
* the input image as base64-encoded image bytes or as a reference to an image in
* an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p> For each object that the model version detects
* on an image, the API returns a (<code>CustomLabel</code>) object in an array
* (<code>CustomLabels</code>). Each <code>CustomLabel</code> object provides the
* label name (<code>Name</code>), the level of confidence that the image contains
* the object (<code>Confidence</code>), and object location information, if it
* exists, for the label on the image (<code>Geometry</code>). </p> <p>During
* training model calculates a threshold value that determines if a prediction for
* a label is true. By default, <code>DetectCustomLabels</code> doesn't return
* labels whose confidence value is below the model's calculated threshold value.
* To filter labels that are returned, specify a value for
* <code>MinConfidence</code> that is higher than the model's calculated threshold.
* You can get the model's calculated threshold from the model's training results
* shown in the Amazon Rekognition Custom Labels console. To get all labels,
* regardless of confidence, specify a <code>MinConfidence</code> value of 0. </p>
* <p>You can also add the <code>MaxResults</code> parameter to limit the number of
* labels returned. </p> <p>This is a stateless API operation. That is, the
* operation does not persist any data.</p> <p>This operation requires permissions
* to perform the <code>rekognition:DetectCustomLabels</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectCustomLabels">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DetectCustomLabelsOutcomeCallable DetectCustomLabelsCallable(const Model::DetectCustomLabelsRequest& request) const;
/**
* <p>Detects custom labels in a supplied image by using an Amazon Rekognition
* Custom Labels model. </p> <p>You specify which version of a model version to use
* by using the <code>ProjectVersionArn</code> input parameter. </p> <p>You pass
* the input image as base64-encoded image bytes or as a reference to an image in
* an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p> For each object that the model version detects
* on an image, the API returns a (<code>CustomLabel</code>) object in an array
* (<code>CustomLabels</code>). Each <code>CustomLabel</code> object provides the
* label name (<code>Name</code>), the level of confidence that the image contains
* the object (<code>Confidence</code>), and object location information, if it
* exists, for the label on the image (<code>Geometry</code>). </p> <p>During
* training model calculates a threshold value that determines if a prediction for
* a label is true. By default, <code>DetectCustomLabels</code> doesn't return
* labels whose confidence value is below the model's calculated threshold value.
* To filter labels that are returned, specify a value for
* <code>MinConfidence</code> that is higher than the model's calculated threshold.
* You can get the model's calculated threshold from the model's training results
* shown in the Amazon Rekognition Custom Labels console. To get all labels,
* regardless of confidence, specify a <code>MinConfidence</code> value of 0. </p>
* <p>You can also add the <code>MaxResults</code> parameter to limit the number of
* labels returned. </p> <p>This is a stateless API operation. That is, the
* operation does not persist any data.</p> <p>This operation requires permissions
* to perform the <code>rekognition:DetectCustomLabels</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectCustomLabels">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DetectCustomLabelsAsync(const Model::DetectCustomLabelsRequest& request, const DetectCustomLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects faces within an image that is provided as input.</p> <p>
* <code>DetectFaces</code> detects the 100 largest faces in the image. For each
* face detected, the operation returns face details. These details include 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), presence of beard, sunglasses, and so on. </p>
* <p>The face-detection algorithm is most effective on frontal faces. For
* non-frontal or obscured faces, the algorithm might not detect the faces or might
* detect faces with lower confidence. </p> <p>You pass the input image either as
* base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket.
* If you use the AWS CLI to call Amazon Rekognition operations, passing image
* bytes is not supported. The image must be either a PNG or JPEG formatted file.
* </p> <p>This is a stateless API operation. That is, the operation does
* not persist any data.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DetectFaces</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectFaces">AWS
* API Reference</a></p>
*/
virtual Model::DetectFacesOutcome DetectFaces(const Model::DetectFacesRequest& request) const;
/**
* <p>Detects faces within an image that is provided as input.</p> <p>
* <code>DetectFaces</code> detects the 100 largest faces in the image. For each
* face detected, the operation returns face details. These details include 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), presence of beard, sunglasses, and so on. </p>
* <p>The face-detection algorithm is most effective on frontal faces. For
* non-frontal or obscured faces, the algorithm might not detect the faces or might
* detect faces with lower confidence. </p> <p>You pass the input image either as
* base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket.
* If you use the AWS CLI to call Amazon Rekognition operations, passing image
* bytes is not supported. The image must be either a PNG or JPEG formatted file.
* </p> <p>This is a stateless API operation. That is, the operation does
* not persist any data.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DetectFaces</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DetectFacesOutcomeCallable DetectFacesCallable(const Model::DetectFacesRequest& request) const;
/**
* <p>Detects faces within an image that is provided as input.</p> <p>
* <code>DetectFaces</code> detects the 100 largest faces in the image. For each
* face detected, the operation returns face details. These details include 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), presence of beard, sunglasses, and so on. </p>
* <p>The face-detection algorithm is most effective on frontal faces. For
* non-frontal or obscured faces, the algorithm might not detect the faces or might
* detect faces with lower confidence. </p> <p>You pass the input image either as
* base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket.
* If you use the AWS CLI to call Amazon Rekognition operations, passing image
* bytes is not supported. The image must be either a PNG or JPEG formatted file.
* </p> <p>This is a stateless API operation. That is, the operation does
* not persist any data.</p> <p>This operation requires permissions to
* perform the <code>rekognition:DetectFaces</code> action. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DetectFacesAsync(const Model::DetectFacesRequest& request, const DetectFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects instances of real-world entities 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. </p> <p>For an example, see Analyzing Images Stored in an
* Amazon S3 Bucket in the Amazon Rekognition Developer Guide.</p> <p>
* <code>DetectLabels</code> does not support the detection of activities. However,
* activity detection is supported for label detection in videos. For more
* information, see StartLabelDetection in the Amazon Rekognition Developer
* Guide.</p> <p>You pass the input image as base64-encoded image bytes or
* as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to
* call Amazon Rekognition operations, passing image bytes is not supported. The
* image must be either a PNG or JPEG formatted file. </p> <p> 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 includes all three labels, one for each object. </p> <p> <code>{Name:
* lighthouse, Confidence: 98.4629}</code> </p> <p> <code>{Name: rock,Confidence:
* 79.2097}</code> </p> <p> <code> {Name: sea,Confidence: 75.061}</code> </p> <p>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. </p> <p>
* <code>{Name: flower,Confidence: 99.0562}</code> </p> <p> <code>{Name:
* plant,Confidence: 99.0562}</code> </p> <p> <code>{Name: tulip,Confidence:
* 99.0562}</code> </p> <p>In this example, the detection algorithm more precisely
* identifies the flower as a tulip.</p> <p>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 55%. You can also add the
* <code>MaxLabels</code> parameter to limit the number of labels returned. </p>
* <p>If the object detected is a person, the operation doesn't provide the
* same facial details that the <a>DetectFaces</a> operation provides.</p>
* <p> <code>DetectLabels</code> returns bounding boxes for instances of common
* object labels in an array of <a>Instance</a> objects. An <code>Instance</code>
* object contains a <a>BoundingBox</a> object, for the location of the label on
* the image. It also includes the confidence by which the bounding box was
* detected.</p> <p> <code>DetectLabels</code> also returns a hierarchical taxonomy
* of detected labels. For example, a detected car might be assigned the label
* <i>car</i>. The label <i>car</i> has two parent labels: <i>Vehicle</i> (its
* parent) and <i>Transportation</i> (its grandparent). The response returns the
* entire list of ancestors for a label. Each ancestor is a unique label in the
* response. In the previous example, <i>Car</i>, <i>Vehicle</i>, and
* <i>Transportation</i> are returned as unique labels in the response. </p>
* <p>This is a stateless API operation. That is, the operation does not persist
* any data.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DetectLabels</code> action. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectLabels">AWS
* API Reference</a></p>
*/
virtual Model::DetectLabelsOutcome DetectLabels(const Model::DetectLabelsRequest& request) const;
/**
* <p>Detects instances of real-world entities 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. </p> <p>For an example, see Analyzing Images Stored in an
* Amazon S3 Bucket in the Amazon Rekognition Developer Guide.</p> <p>
* <code>DetectLabels</code> does not support the detection of activities. However,
* activity detection is supported for label detection in videos. For more
* information, see StartLabelDetection in the Amazon Rekognition Developer
* Guide.</p> <p>You pass the input image as base64-encoded image bytes or
* as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to
* call Amazon Rekognition operations, passing image bytes is not supported. The
* image must be either a PNG or JPEG formatted file. </p> <p> 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 includes all three labels, one for each object. </p> <p> <code>{Name:
* lighthouse, Confidence: 98.4629}</code> </p> <p> <code>{Name: rock,Confidence:
* 79.2097}</code> </p> <p> <code> {Name: sea,Confidence: 75.061}</code> </p> <p>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. </p> <p>
* <code>{Name: flower,Confidence: 99.0562}</code> </p> <p> <code>{Name:
* plant,Confidence: 99.0562}</code> </p> <p> <code>{Name: tulip,Confidence:
* 99.0562}</code> </p> <p>In this example, the detection algorithm more precisely
* identifies the flower as a tulip.</p> <p>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 55%. You can also add the
* <code>MaxLabels</code> parameter to limit the number of labels returned. </p>
* <p>If the object detected is a person, the operation doesn't provide the
* same facial details that the <a>DetectFaces</a> operation provides.</p>
* <p> <code>DetectLabels</code> returns bounding boxes for instances of common
* object labels in an array of <a>Instance</a> objects. An <code>Instance</code>
* object contains a <a>BoundingBox</a> object, for the location of the label on
* the image. It also includes the confidence by which the bounding box was
* detected.</p> <p> <code>DetectLabels</code> also returns a hierarchical taxonomy
* of detected labels. For example, a detected car might be assigned the label
* <i>car</i>. The label <i>car</i> has two parent labels: <i>Vehicle</i> (its
* parent) and <i>Transportation</i> (its grandparent). The response returns the
* entire list of ancestors for a label. Each ancestor is a unique label in the
* response. In the previous example, <i>Car</i>, <i>Vehicle</i>, and
* <i>Transportation</i> are returned as unique labels in the response. </p>
* <p>This is a stateless API operation. That is, the operation does not persist
* any data.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DetectLabels</code> action. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectLabels">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DetectLabelsOutcomeCallable DetectLabelsCallable(const Model::DetectLabelsRequest& request) const;
/**
* <p>Detects instances of real-world entities 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. </p> <p>For an example, see Analyzing Images Stored in an
* Amazon S3 Bucket in the Amazon Rekognition Developer Guide.</p> <p>
* <code>DetectLabels</code> does not support the detection of activities. However,
* activity detection is supported for label detection in videos. For more
* information, see StartLabelDetection in the Amazon Rekognition Developer
* Guide.</p> <p>You pass the input image as base64-encoded image bytes or
* as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to
* call Amazon Rekognition operations, passing image bytes is not supported. The
* image must be either a PNG or JPEG formatted file. </p> <p> 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 includes all three labels, one for each object. </p> <p> <code>{Name:
* lighthouse, Confidence: 98.4629}</code> </p> <p> <code>{Name: rock,Confidence:
* 79.2097}</code> </p> <p> <code> {Name: sea,Confidence: 75.061}</code> </p> <p>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. </p> <p>
* <code>{Name: flower,Confidence: 99.0562}</code> </p> <p> <code>{Name:
* plant,Confidence: 99.0562}</code> </p> <p> <code>{Name: tulip,Confidence:
* 99.0562}</code> </p> <p>In this example, the detection algorithm more precisely
* identifies the flower as a tulip.</p> <p>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 55%. You can also add the
* <code>MaxLabels</code> parameter to limit the number of labels returned. </p>
* <p>If the object detected is a person, the operation doesn't provide the
* same facial details that the <a>DetectFaces</a> operation provides.</p>
* <p> <code>DetectLabels</code> returns bounding boxes for instances of common
* object labels in an array of <a>Instance</a> objects. An <code>Instance</code>
* object contains a <a>BoundingBox</a> object, for the location of the label on
* the image. It also includes the confidence by which the bounding box was
* detected.</p> <p> <code>DetectLabels</code> also returns a hierarchical taxonomy
* of detected labels. For example, a detected car might be assigned the label
* <i>car</i>. The label <i>car</i> has two parent labels: <i>Vehicle</i> (its
* parent) and <i>Transportation</i> (its grandparent). The response returns the
* entire list of ancestors for a label. Each ancestor is a unique label in the
* response. In the previous example, <i>Car</i>, <i>Vehicle</i>, and
* <i>Transportation</i> are returned as unique labels in the response. </p>
* <p>This is a stateless API operation. That is, the operation does not persist
* any data.</p> <p>This operation requires permissions to perform the
* <code>rekognition:DetectLabels</code> action. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectLabels">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DetectLabelsAsync(const Model::DetectLabelsRequest& request, const DetectLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects unsafe content in a specified JPEG or PNG format image. Use
* <code>DetectModerationLabels</code> to moderate images depending on your
* requirements. For example, you might want to filter images that contain nudity,
* but not images containing suggestive content.</p> <p>To filter images, use the
* labels returned by <code>DetectModerationLabels</code> to determine which types
* of content are appropriate.</p> <p>For information about moderation labels, see
* Detecting Unsafe Content in the Amazon Rekognition Developer Guide.</p> <p>You
* pass the input image either as base64-encoded image bytes or as a reference to
* an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon
* Rekognition operations, passing image bytes is not supported. The image must be
* either a PNG or JPEG formatted file. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectModerationLabels">AWS
* API Reference</a></p>
*/
virtual Model::DetectModerationLabelsOutcome DetectModerationLabels(const Model::DetectModerationLabelsRequest& request) const;
/**
* <p>Detects unsafe content in a specified JPEG or PNG format image. Use
* <code>DetectModerationLabels</code> to moderate images depending on your
* requirements. For example, you might want to filter images that contain nudity,
* but not images containing suggestive content.</p> <p>To filter images, use the
* labels returned by <code>DetectModerationLabels</code> to determine which types
* of content are appropriate.</p> <p>For information about moderation labels, see
* Detecting Unsafe Content in the Amazon Rekognition Developer Guide.</p> <p>You
* pass the input image either as base64-encoded image bytes or as a reference to
* an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon
* Rekognition operations, passing image bytes is not supported. The image must be
* either a PNG or JPEG formatted file. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectModerationLabels">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DetectModerationLabelsOutcomeCallable DetectModerationLabelsCallable(const Model::DetectModerationLabelsRequest& request) const;
/**
* <p>Detects unsafe content in a specified JPEG or PNG format image. Use
* <code>DetectModerationLabels</code> to moderate images depending on your
* requirements. For example, you might want to filter images that contain nudity,
* but not images containing suggestive content.</p> <p>To filter images, use the
* labels returned by <code>DetectModerationLabels</code> to determine which types
* of content are appropriate.</p> <p>For information about moderation labels, see
* Detecting Unsafe Content in the Amazon Rekognition Developer Guide.</p> <p>You
* pass the input image either as base64-encoded image bytes or as a reference to
* an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon
* Rekognition operations, passing image bytes is not supported. The image must be
* either a PNG or JPEG formatted file. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectModerationLabels">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DetectModerationLabelsAsync(const Model::DetectModerationLabelsRequest& request, const DetectModerationLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects text in the input image and converts it into machine-readable
* text.</p> <p>Pass the input image as base64-encoded image bytes or as a
* reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call
* Amazon Rekognition operations, you must pass it as a reference to an image in an
* Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The
* image must be either a .png or .jpeg formatted file. </p> <p>The
* <code>DetectText</code> operation returns text in an array of
* <a>TextDetection</a> elements, <code>TextDetections</code>. Each
* <code>TextDetection</code> element provides information about a single word or
* line of text that was detected in the image. </p> <p>A word is one or more ISO
* basic latin script characters that are not separated by spaces.
* <code>DetectText</code> can detect up to 50 words in an image.</p> <p>A line is
* a string of equally spaced words. A line isn't necessarily a complete sentence.
* For example, a driver's license number is detected as a line. A line ends when
* there is no aligned text after it. Also, a line ends when there is a large gap
* between words, relative to the length of the words. This means, depending on the
* gap between words, Amazon Rekognition may detect multiple lines in text aligned
* in the same direction. Periods don't represent the end of a line. If a sentence
* spans multiple lines, the <code>DetectText</code> operation returns multiple
* lines.</p> <p>To determine whether a <code>TextDetection</code> element is a
* line of text or a word, use the <code>TextDetection</code> object
* <code>Type</code> field. </p> <p>To be detected, text must be within +/- 90
* degrees orientation of the horizontal axis.</p> <p>For more information, see
* DetectText in the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectText">AWS
* API Reference</a></p>
*/
virtual Model::DetectTextOutcome DetectText(const Model::DetectTextRequest& request) const;
/**
* <p>Detects text in the input image and converts it into machine-readable
* text.</p> <p>Pass the input image as base64-encoded image bytes or as a
* reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call
* Amazon Rekognition operations, you must pass it as a reference to an image in an
* Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The
* image must be either a .png or .jpeg formatted file. </p> <p>The
* <code>DetectText</code> operation returns text in an array of
* <a>TextDetection</a> elements, <code>TextDetections</code>. Each
* <code>TextDetection</code> element provides information about a single word or
* line of text that was detected in the image. </p> <p>A word is one or more ISO
* basic latin script characters that are not separated by spaces.
* <code>DetectText</code> can detect up to 50 words in an image.</p> <p>A line is
* a string of equally spaced words. A line isn't necessarily a complete sentence.
* For example, a driver's license number is detected as a line. A line ends when
* there is no aligned text after it. Also, a line ends when there is a large gap
* between words, relative to the length of the words. This means, depending on the
* gap between words, Amazon Rekognition may detect multiple lines in text aligned
* in the same direction. Periods don't represent the end of a line. If a sentence
* spans multiple lines, the <code>DetectText</code> operation returns multiple
* lines.</p> <p>To determine whether a <code>TextDetection</code> element is a
* line of text or a word, use the <code>TextDetection</code> object
* <code>Type</code> field. </p> <p>To be detected, text must be within +/- 90
* degrees orientation of the horizontal axis.</p> <p>For more information, see
* DetectText in the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectText">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DetectTextOutcomeCallable DetectTextCallable(const Model::DetectTextRequest& request) const;
/**
* <p>Detects text in the input image and converts it into machine-readable
* text.</p> <p>Pass the input image as base64-encoded image bytes or as a
* reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call
* Amazon Rekognition operations, you must pass it as a reference to an image in an
* Amazon S3 bucket. For the AWS CLI, passing image bytes is not supported. The
* image must be either a .png or .jpeg formatted file. </p> <p>The
* <code>DetectText</code> operation returns text in an array of
* <a>TextDetection</a> elements, <code>TextDetections</code>. Each
* <code>TextDetection</code> element provides information about a single word or
* line of text that was detected in the image. </p> <p>A word is one or more ISO
* basic latin script characters that are not separated by spaces.
* <code>DetectText</code> can detect up to 50 words in an image.</p> <p>A line is
* a string of equally spaced words. A line isn't necessarily a complete sentence.
* For example, a driver's license number is detected as a line. A line ends when
* there is no aligned text after it. Also, a line ends when there is a large gap
* between words, relative to the length of the words. This means, depending on the
* gap between words, Amazon Rekognition may detect multiple lines in text aligned
* in the same direction. Periods don't represent the end of a line. If a sentence
* spans multiple lines, the <code>DetectText</code> operation returns multiple
* lines.</p> <p>To determine whether a <code>TextDetection</code> element is a
* line of text or a word, use the <code>TextDetection</code> object
* <code>Type</code> field. </p> <p>To be detected, text must be within +/- 90
* degrees orientation of the horizontal axis.</p> <p>For more information, see
* DetectText in the Amazon Rekognition Developer Guide.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/DetectText">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DetectTextAsync(const Model::DetectTextRequest& request, const DetectTextResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the name and additional information about a celebrity based on his or
* her Amazon Rekognition ID. The additional information is returned as an array of
* URLs. If there is no additional information about the celebrity, this list is
* empty.</p> <p>For more information, see Recognizing Celebrities in an Image in
* the Amazon Rekognition Developer Guide.</p> <p>This operation requires
* permissions to perform the <code>rekognition:GetCelebrityInfo</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityInfo">AWS
* API Reference</a></p>
*/
virtual Model::GetCelebrityInfoOutcome GetCelebrityInfo(const Model::GetCelebrityInfoRequest& request) const;
/**
* <p>Gets the name and additional information about a celebrity based on his or
* her Amazon Rekognition ID. The additional information is returned as an array of
* URLs. If there is no additional information about the celebrity, this list is
* empty.</p> <p>For more information, see Recognizing Celebrities in an Image in
* the Amazon Rekognition Developer Guide.</p> <p>This operation requires
* permissions to perform the <code>rekognition:GetCelebrityInfo</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityInfo">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetCelebrityInfoOutcomeCallable GetCelebrityInfoCallable(const Model::GetCelebrityInfoRequest& request) const;
/**
* <p>Gets the name and additional information about a celebrity based on his or
* her Amazon Rekognition ID. The additional information is returned as an array of
* URLs. If there is no additional information about the celebrity, this list is
* empty.</p> <p>For more information, see Recognizing Celebrities in an Image in
* the Amazon Rekognition Developer Guide.</p> <p>This operation requires
* permissions to perform the <code>rekognition:GetCelebrityInfo</code> action.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityInfo">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetCelebrityInfoAsync(const Model::GetCelebrityInfoRequest& request, const GetCelebrityInfoResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the celebrity recognition results for a Amazon Rekognition Video
* analysis started by <a>StartCelebrityRecognition</a>.</p> <p>Celebrity
* recognition in a video is an asynchronous operation. Analysis is started by a
* call to <a>StartCelebrityRecognition</a> which returns a job identifier
* (<code>JobId</code>). When the celebrity recognition operation finishes, Amazon
* Rekognition Video publishes a completion status to the Amazon Simple
* Notification Service topic registered in the initial call to
* <code>StartCelebrityRecognition</code>. To get the results of the celebrity
* recognition analysis, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetCelebrityDetection</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartCelebrityDetection</code>. </p> <p>For more information, see Working
* With Stored Videos in the Amazon Rekognition Developer Guide.</p> <p>
* <code>GetCelebrityRecognition</code> returns detected celebrities and the
* time(s) they are detected in an array (<code>Celebrities</code>) of
* <a>CelebrityRecognition</a> objects. Each <code>CelebrityRecognition</code>
* contains information about the celebrity in a <a>CelebrityDetail</a> object and
* the time, <code>Timestamp</code>, the celebrity was detected. </p> <p>
* <code>GetCelebrityRecognition</code> only returns the default facial attributes
* (<code>BoundingBox</code>, <code>Confidence</code>, <code>Landmarks</code>,
* <code>Pose</code>, and <code>Quality</code>). The other facial attributes listed
* in the <code>Face</code> object of the following response syntax are not
* returned. For more information, see FaceDetail in the Amazon Rekognition
* Developer Guide. </p> <p>By default, the <code>Celebrities</code> array
* is sorted by time (milliseconds from the start of the video). You can also sort
* the array by celebrity by specifying the value <code>ID</code> in the
* <code>SortBy</code> input parameter.</p> <p>The <code>CelebrityDetail</code>
* object includes the celebrity identifer and additional information urls. If you
* don't store the additional information urls, you can get them later by calling
* <a>GetCelebrityInfo</a> with the celebrity identifer.</p> <p>No information is
* returned for faces not recognized as celebrities.</p> <p>Use MaxResults
* parameter to limit the number of labels returned. If there are more results than
* specified in <code>MaxResults</code>, the value of <code>NextToken</code> in the
* operation response contains a pagination token for getting the next set of
* results. To get the next page of results, call
* <code>GetCelebrityDetection</code> and populate the <code>NextToken</code>
* request parameter with the token value returned from the previous call to
* <code>GetCelebrityRecognition</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityRecognition">AWS
* API Reference</a></p>
*/
virtual Model::GetCelebrityRecognitionOutcome GetCelebrityRecognition(const Model::GetCelebrityRecognitionRequest& request) const;
/**
* <p>Gets the celebrity recognition results for a Amazon Rekognition Video
* analysis started by <a>StartCelebrityRecognition</a>.</p> <p>Celebrity
* recognition in a video is an asynchronous operation. Analysis is started by a
* call to <a>StartCelebrityRecognition</a> which returns a job identifier
* (<code>JobId</code>). When the celebrity recognition operation finishes, Amazon
* Rekognition Video publishes a completion status to the Amazon Simple
* Notification Service topic registered in the initial call to
* <code>StartCelebrityRecognition</code>. To get the results of the celebrity
* recognition analysis, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetCelebrityDetection</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartCelebrityDetection</code>. </p> <p>For more information, see Working
* With Stored Videos in the Amazon Rekognition Developer Guide.</p> <p>
* <code>GetCelebrityRecognition</code> returns detected celebrities and the
* time(s) they are detected in an array (<code>Celebrities</code>) of
* <a>CelebrityRecognition</a> objects. Each <code>CelebrityRecognition</code>
* contains information about the celebrity in a <a>CelebrityDetail</a> object and
* the time, <code>Timestamp</code>, the celebrity was detected. </p> <p>
* <code>GetCelebrityRecognition</code> only returns the default facial attributes
* (<code>BoundingBox</code>, <code>Confidence</code>, <code>Landmarks</code>,
* <code>Pose</code>, and <code>Quality</code>). The other facial attributes listed
* in the <code>Face</code> object of the following response syntax are not
* returned. For more information, see FaceDetail in the Amazon Rekognition
* Developer Guide. </p> <p>By default, the <code>Celebrities</code> array
* is sorted by time (milliseconds from the start of the video). You can also sort
* the array by celebrity by specifying the value <code>ID</code> in the
* <code>SortBy</code> input parameter.</p> <p>The <code>CelebrityDetail</code>
* object includes the celebrity identifer and additional information urls. If you
* don't store the additional information urls, you can get them later by calling
* <a>GetCelebrityInfo</a> with the celebrity identifer.</p> <p>No information is
* returned for faces not recognized as celebrities.</p> <p>Use MaxResults
* parameter to limit the number of labels returned. If there are more results than
* specified in <code>MaxResults</code>, the value of <code>NextToken</code> in the
* operation response contains a pagination token for getting the next set of
* results. To get the next page of results, call
* <code>GetCelebrityDetection</code> and populate the <code>NextToken</code>
* request parameter with the token value returned from the previous call to
* <code>GetCelebrityRecognition</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityRecognition">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetCelebrityRecognitionOutcomeCallable GetCelebrityRecognitionCallable(const Model::GetCelebrityRecognitionRequest& request) const;
/**
* <p>Gets the celebrity recognition results for a Amazon Rekognition Video
* analysis started by <a>StartCelebrityRecognition</a>.</p> <p>Celebrity
* recognition in a video is an asynchronous operation. Analysis is started by a
* call to <a>StartCelebrityRecognition</a> which returns a job identifier
* (<code>JobId</code>). When the celebrity recognition operation finishes, Amazon
* Rekognition Video publishes a completion status to the Amazon Simple
* Notification Service topic registered in the initial call to
* <code>StartCelebrityRecognition</code>. To get the results of the celebrity
* recognition analysis, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetCelebrityDetection</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartCelebrityDetection</code>. </p> <p>For more information, see Working
* With Stored Videos in the Amazon Rekognition Developer Guide.</p> <p>
* <code>GetCelebrityRecognition</code> returns detected celebrities and the
* time(s) they are detected in an array (<code>Celebrities</code>) of
* <a>CelebrityRecognition</a> objects. Each <code>CelebrityRecognition</code>
* contains information about the celebrity in a <a>CelebrityDetail</a> object and
* the time, <code>Timestamp</code>, the celebrity was detected. </p> <p>
* <code>GetCelebrityRecognition</code> only returns the default facial attributes
* (<code>BoundingBox</code>, <code>Confidence</code>, <code>Landmarks</code>,
* <code>Pose</code>, and <code>Quality</code>). The other facial attributes listed
* in the <code>Face</code> object of the following response syntax are not
* returned. For more information, see FaceDetail in the Amazon Rekognition
* Developer Guide. </p> <p>By default, the <code>Celebrities</code> array
* is sorted by time (milliseconds from the start of the video). You can also sort
* the array by celebrity by specifying the value <code>ID</code> in the
* <code>SortBy</code> input parameter.</p> <p>The <code>CelebrityDetail</code>
* object includes the celebrity identifer and additional information urls. If you
* don't store the additional information urls, you can get them later by calling
* <a>GetCelebrityInfo</a> with the celebrity identifer.</p> <p>No information is
* returned for faces not recognized as celebrities.</p> <p>Use MaxResults
* parameter to limit the number of labels returned. If there are more results than
* specified in <code>MaxResults</code>, the value of <code>NextToken</code> in the
* operation response contains a pagination token for getting the next set of
* results. To get the next page of results, call
* <code>GetCelebrityDetection</code> and populate the <code>NextToken</code>
* request parameter with the token value returned from the previous call to
* <code>GetCelebrityRecognition</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetCelebrityRecognition">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetCelebrityRecognitionAsync(const Model::GetCelebrityRecognitionRequest& request, const GetCelebrityRecognitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the unsafe content analysis results for a Amazon Rekognition Video
* analysis started by <a>StartContentModeration</a>.</p> <p>Unsafe content
* analysis of a video is an asynchronous operation. You start analysis by calling
* <a>StartContentModeration</a> which returns a job identifier
* (<code>JobId</code>). When analysis finishes, Amazon Rekognition Video publishes
* a completion status to the Amazon Simple Notification Service topic registered
* in the initial call to <code>StartContentModeration</code>. To get the results
* of the unsafe content analysis, first check that the status value published to
* the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetContentModeration</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartContentModeration</code>. </p> <p>For more information, see Working
* with Stored Videos in the Amazon Rekognition Devlopers Guide.</p> <p>
* <code>GetContentModeration</code> returns detected unsafe content labels, and
* the time they are detected, in an array, <code>ModerationLabels</code>, of
* <a>ContentModerationDetection</a> objects. </p> <p>By default, the moderated
* labels are returned sorted by time, in milliseconds from the start of the video.
* You can also sort them by moderated label by specifying <code>NAME</code> for
* the <code>SortBy</code> input parameter. </p> <p>Since video analysis can return
* a large number of results, use the <code>MaxResults</code> parameter to limit
* the number of labels returned in a single call to
* <code>GetContentModeration</code>. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetContentModeration</code> and populate
* the <code>NextToken</code> request parameter with the value of
* <code>NextToken</code> returned from the previous call to
* <code>GetContentModeration</code>.</p> <p>For more information, see Detecting
* Unsafe Content in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetContentModeration">AWS
* API Reference</a></p>
*/
virtual Model::GetContentModerationOutcome GetContentModeration(const Model::GetContentModerationRequest& request) const;
/**
* <p>Gets the unsafe content analysis results for a Amazon Rekognition Video
* analysis started by <a>StartContentModeration</a>.</p> <p>Unsafe content
* analysis of a video is an asynchronous operation. You start analysis by calling
* <a>StartContentModeration</a> which returns a job identifier
* (<code>JobId</code>). When analysis finishes, Amazon Rekognition Video publishes
* a completion status to the Amazon Simple Notification Service topic registered
* in the initial call to <code>StartContentModeration</code>. To get the results
* of the unsafe content analysis, first check that the status value published to
* the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetContentModeration</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartContentModeration</code>. </p> <p>For more information, see Working
* with Stored Videos in the Amazon Rekognition Devlopers Guide.</p> <p>
* <code>GetContentModeration</code> returns detected unsafe content labels, and
* the time they are detected, in an array, <code>ModerationLabels</code>, of
* <a>ContentModerationDetection</a> objects. </p> <p>By default, the moderated
* labels are returned sorted by time, in milliseconds from the start of the video.
* You can also sort them by moderated label by specifying <code>NAME</code> for
* the <code>SortBy</code> input parameter. </p> <p>Since video analysis can return
* a large number of results, use the <code>MaxResults</code> parameter to limit
* the number of labels returned in a single call to
* <code>GetContentModeration</code>. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetContentModeration</code> and populate
* the <code>NextToken</code> request parameter with the value of
* <code>NextToken</code> returned from the previous call to
* <code>GetContentModeration</code>.</p> <p>For more information, see Detecting
* Unsafe Content in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetContentModeration">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetContentModerationOutcomeCallable GetContentModerationCallable(const Model::GetContentModerationRequest& request) const;
/**
* <p>Gets the unsafe content analysis results for a Amazon Rekognition Video
* analysis started by <a>StartContentModeration</a>.</p> <p>Unsafe content
* analysis of a video is an asynchronous operation. You start analysis by calling
* <a>StartContentModeration</a> which returns a job identifier
* (<code>JobId</code>). When analysis finishes, Amazon Rekognition Video publishes
* a completion status to the Amazon Simple Notification Service topic registered
* in the initial call to <code>StartContentModeration</code>. To get the results
* of the unsafe content analysis, first check that the status value published to
* the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <code>GetContentModeration</code> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartContentModeration</code>. </p> <p>For more information, see Working
* with Stored Videos in the Amazon Rekognition Devlopers Guide.</p> <p>
* <code>GetContentModeration</code> returns detected unsafe content labels, and
* the time they are detected, in an array, <code>ModerationLabels</code>, of
* <a>ContentModerationDetection</a> objects. </p> <p>By default, the moderated
* labels are returned sorted by time, in milliseconds from the start of the video.
* You can also sort them by moderated label by specifying <code>NAME</code> for
* the <code>SortBy</code> input parameter. </p> <p>Since video analysis can return
* a large number of results, use the <code>MaxResults</code> parameter to limit
* the number of labels returned in a single call to
* <code>GetContentModeration</code>. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetContentModeration</code> and populate
* the <code>NextToken</code> request parameter with the value of
* <code>NextToken</code> returned from the previous call to
* <code>GetContentModeration</code>.</p> <p>For more information, see Detecting
* Unsafe Content in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetContentModeration">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetContentModerationAsync(const Model::GetContentModerationRequest& request, const GetContentModerationResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets face detection results for a Amazon Rekognition Video analysis started
* by <a>StartFaceDetection</a>.</p> <p>Face detection with Amazon Rekognition
* Video is an asynchronous operation. You start face detection by calling
* <a>StartFaceDetection</a> which returns a job identifier (<code>JobId</code>).
* When the face detection operation finishes, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic registered in
* the initial call to <code>StartFaceDetection</code>. To get the results of the
* face detection operation, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a>
* and pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p> <code>GetFaceDetection</code> returns
* an array of detected faces (<code>Faces</code>) sorted by the time the faces
* were detected. </p> <p>Use MaxResults parameter to limit the number of labels
* returned. If there are more results than specified in <code>MaxResults</code>,
* the value of <code>NextToken</code> in the operation response contains a
* pagination token for getting the next set of results. To get the next page of
* results, call <code>GetFaceDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetFaceDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceDetection">AWS
* API Reference</a></p>
*/
virtual Model::GetFaceDetectionOutcome GetFaceDetection(const Model::GetFaceDetectionRequest& request) const;
/**
* <p>Gets face detection results for a Amazon Rekognition Video analysis started
* by <a>StartFaceDetection</a>.</p> <p>Face detection with Amazon Rekognition
* Video is an asynchronous operation. You start face detection by calling
* <a>StartFaceDetection</a> which returns a job identifier (<code>JobId</code>).
* When the face detection operation finishes, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic registered in
* the initial call to <code>StartFaceDetection</code>. To get the results of the
* face detection operation, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a>
* and pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p> <code>GetFaceDetection</code> returns
* an array of detected faces (<code>Faces</code>) sorted by the time the faces
* were detected. </p> <p>Use MaxResults parameter to limit the number of labels
* returned. If there are more results than specified in <code>MaxResults</code>,
* the value of <code>NextToken</code> in the operation response contains a
* pagination token for getting the next set of results. To get the next page of
* results, call <code>GetFaceDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetFaceDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetFaceDetectionOutcomeCallable GetFaceDetectionCallable(const Model::GetFaceDetectionRequest& request) const;
/**
* <p>Gets face detection results for a Amazon Rekognition Video analysis started
* by <a>StartFaceDetection</a>.</p> <p>Face detection with Amazon Rekognition
* Video is an asynchronous operation. You start face detection by calling
* <a>StartFaceDetection</a> which returns a job identifier (<code>JobId</code>).
* When the face detection operation finishes, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic registered in
* the initial call to <code>StartFaceDetection</code>. To get the results of the
* face detection operation, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a>
* and pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p> <code>GetFaceDetection</code> returns
* an array of detected faces (<code>Faces</code>) sorted by the time the faces
* were detected. </p> <p>Use MaxResults parameter to limit the number of labels
* returned. If there are more results than specified in <code>MaxResults</code>,
* the value of <code>NextToken</code> in the operation response contains a
* pagination token for getting the next set of results. To get the next page of
* results, call <code>GetFaceDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetFaceDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetFaceDetectionAsync(const Model::GetFaceDetectionRequest& request, const GetFaceDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the face search results for Amazon Rekognition Video face search started
* by <a>StartFaceSearch</a>. The search returns faces in a collection that match
* the faces of persons detected in a video. It also includes the time(s) that
* faces are matched in the video.</p> <p>Face search in a video is an asynchronous
* operation. You start face search by calling to <a>StartFaceSearch</a> which
* returns a job identifier (<code>JobId</code>). When the search operation
* finishes, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic registered in the initial call to
* <code>StartFaceSearch</code>. To get the search results, first check that the
* status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so,
* call <code>GetFaceSearch</code> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartFaceSearch</code>.</p> <p>For more
* information, see Searching Faces in a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>The search results are retured in an array,
* <code>Persons</code>, of <a>PersonMatch</a> objects.
* Each<code>PersonMatch</code> element contains details about the matching faces
* in the input collection, person information (facial attributes, bounding boxes,
* and person identifer) for the matched person, and the time the person was
* matched in the video.</p> <p> <code>GetFaceSearch</code> only returns the
* default facial attributes (<code>BoundingBox</code>, <code>Confidence</code>,
* <code>Landmarks</code>, <code>Pose</code>, and <code>Quality</code>). The other
* facial attributes listed in the <code>Face</code> object of the following
* response syntax are not returned. For more information, see FaceDetail in the
* Amazon Rekognition Developer Guide. </p> <p>By default, the
* <code>Persons</code> array is sorted by the time, in milliseconds from the start
* of the video, persons are matched. You can also sort by persons by specifying
* <code>INDEX</code> for the <code>SORTBY</code> input parameter.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceSearch">AWS
* API Reference</a></p>
*/
virtual Model::GetFaceSearchOutcome GetFaceSearch(const Model::GetFaceSearchRequest& request) const;
/**
* <p>Gets the face search results for Amazon Rekognition Video face search started
* by <a>StartFaceSearch</a>. The search returns faces in a collection that match
* the faces of persons detected in a video. It also includes the time(s) that
* faces are matched in the video.</p> <p>Face search in a video is an asynchronous
* operation. You start face search by calling to <a>StartFaceSearch</a> which
* returns a job identifier (<code>JobId</code>). When the search operation
* finishes, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic registered in the initial call to
* <code>StartFaceSearch</code>. To get the search results, first check that the
* status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so,
* call <code>GetFaceSearch</code> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartFaceSearch</code>.</p> <p>For more
* information, see Searching Faces in a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>The search results are retured in an array,
* <code>Persons</code>, of <a>PersonMatch</a> objects.
* Each<code>PersonMatch</code> element contains details about the matching faces
* in the input collection, person information (facial attributes, bounding boxes,
* and person identifer) for the matched person, and the time the person was
* matched in the video.</p> <p> <code>GetFaceSearch</code> only returns the
* default facial attributes (<code>BoundingBox</code>, <code>Confidence</code>,
* <code>Landmarks</code>, <code>Pose</code>, and <code>Quality</code>). The other
* facial attributes listed in the <code>Face</code> object of the following
* response syntax are not returned. For more information, see FaceDetail in the
* Amazon Rekognition Developer Guide. </p> <p>By default, the
* <code>Persons</code> array is sorted by the time, in milliseconds from the start
* of the video, persons are matched. You can also sort by persons by specifying
* <code>INDEX</code> for the <code>SORTBY</code> input parameter.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceSearch">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetFaceSearchOutcomeCallable GetFaceSearchCallable(const Model::GetFaceSearchRequest& request) const;
/**
* <p>Gets the face search results for Amazon Rekognition Video face search started
* by <a>StartFaceSearch</a>. The search returns faces in a collection that match
* the faces of persons detected in a video. It also includes the time(s) that
* faces are matched in the video.</p> <p>Face search in a video is an asynchronous
* operation. You start face search by calling to <a>StartFaceSearch</a> which
* returns a job identifier (<code>JobId</code>). When the search operation
* finishes, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic registered in the initial call to
* <code>StartFaceSearch</code>. To get the search results, first check that the
* status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so,
* call <code>GetFaceSearch</code> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartFaceSearch</code>.</p> <p>For more
* information, see Searching Faces in a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>The search results are retured in an array,
* <code>Persons</code>, of <a>PersonMatch</a> objects.
* Each<code>PersonMatch</code> element contains details about the matching faces
* in the input collection, person information (facial attributes, bounding boxes,
* and person identifer) for the matched person, and the time the person was
* matched in the video.</p> <p> <code>GetFaceSearch</code> only returns the
* default facial attributes (<code>BoundingBox</code>, <code>Confidence</code>,
* <code>Landmarks</code>, <code>Pose</code>, and <code>Quality</code>). The other
* facial attributes listed in the <code>Face</code> object of the following
* response syntax are not returned. For more information, see FaceDetail in the
* Amazon Rekognition Developer Guide. </p> <p>By default, the
* <code>Persons</code> array is sorted by the time, in milliseconds from the start
* of the video, persons are matched. You can also sort by persons by specifying
* <code>INDEX</code> for the <code>SORTBY</code> input parameter.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetFaceSearch">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetFaceSearchAsync(const Model::GetFaceSearchRequest& request, const GetFaceSearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the label detection results of a Amazon Rekognition Video analysis
* started by <a>StartLabelDetection</a>. </p> <p>The label detection operation is
* started by a call to <a>StartLabelDetection</a> which returns a job identifier
* (<code>JobId</code>). When the label detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartlabelDetection</code>. To get the results of the label detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p> <code>GetLabelDetection</code> returns
* an array of detected labels (<code>Labels</code>) sorted by the time the labels
* were detected. You can also sort by the label name by specifying
* <code>NAME</code> for the <code>SortBy</code> input parameter.</p> <p>The labels
* returned include the label name, the percentage confidence in the accuracy of
* the detected label, and the time the label was detected in the video.</p> <p>The
* returned labels also include bounding box information for common objects, a
* hierarchical taxonomy of detected labels, and the version of the label model
* used for detection.</p> <p>Use MaxResults parameter to limit the number of
* labels returned. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetlabelDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetLabelDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetLabelDetection">AWS
* API Reference</a></p>
*/
virtual Model::GetLabelDetectionOutcome GetLabelDetection(const Model::GetLabelDetectionRequest& request) const;
/**
* <p>Gets the label detection results of a Amazon Rekognition Video analysis
* started by <a>StartLabelDetection</a>. </p> <p>The label detection operation is
* started by a call to <a>StartLabelDetection</a> which returns a job identifier
* (<code>JobId</code>). When the label detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartlabelDetection</code>. To get the results of the label detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p> <code>GetLabelDetection</code> returns
* an array of detected labels (<code>Labels</code>) sorted by the time the labels
* were detected. You can also sort by the label name by specifying
* <code>NAME</code> for the <code>SortBy</code> input parameter.</p> <p>The labels
* returned include the label name, the percentage confidence in the accuracy of
* the detected label, and the time the label was detected in the video.</p> <p>The
* returned labels also include bounding box information for common objects, a
* hierarchical taxonomy of detected labels, and the version of the label model
* used for detection.</p> <p>Use MaxResults parameter to limit the number of
* labels returned. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetlabelDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetLabelDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetLabelDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetLabelDetectionOutcomeCallable GetLabelDetectionCallable(const Model::GetLabelDetectionRequest& request) const;
/**
* <p>Gets the label detection results of a Amazon Rekognition Video analysis
* started by <a>StartLabelDetection</a>. </p> <p>The label detection operation is
* started by a call to <a>StartLabelDetection</a> which returns a job identifier
* (<code>JobId</code>). When the label detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartlabelDetection</code>. To get the results of the label detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p> <code>GetLabelDetection</code> returns
* an array of detected labels (<code>Labels</code>) sorted by the time the labels
* were detected. You can also sort by the label name by specifying
* <code>NAME</code> for the <code>SortBy</code> input parameter.</p> <p>The labels
* returned include the label name, the percentage confidence in the accuracy of
* the detected label, and the time the label was detected in the video.</p> <p>The
* returned labels also include bounding box information for common objects, a
* hierarchical taxonomy of detected labels, and the version of the label model
* used for detection.</p> <p>Use MaxResults parameter to limit the number of
* labels returned. If there are more results than specified in
* <code>MaxResults</code>, the value of <code>NextToken</code> in the operation
* response contains a pagination token for getting the next set of results. To get
* the next page of results, call <code>GetlabelDetection</code> and populate the
* <code>NextToken</code> request parameter with the token value returned from the
* previous call to <code>GetLabelDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetLabelDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetLabelDetectionAsync(const Model::GetLabelDetectionRequest& request, const GetLabelDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the path tracking results of a Amazon Rekognition Video analysis started
* by <a>StartPersonTracking</a>.</p> <p>The person path tracking operation is
* started by a call to <code>StartPersonTracking</code> which returns a job
* identifier (<code>JobId</code>). When the operation finishes, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic registered in the initial call to <code>StartPersonTracking</code>.</p>
* <p>To get the results of the person path tracking operation, first check that
* the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If
* so, call <a>GetPersonTracking</a> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p> <p> <code>GetPersonTracking</code> returns
* an array, <code>Persons</code>, of tracked persons and the time(s) their paths
* were tracked in the video. </p> <p> <code>GetPersonTracking</code> only
* returns the default facial attributes (<code>BoundingBox</code>,
* <code>Confidence</code>, <code>Landmarks</code>, <code>Pose</code>, and
* <code>Quality</code>). The other facial attributes listed in the
* <code>Face</code> object of the following response syntax are not returned. </p>
* <p>For more information, see FaceDetail in the Amazon Rekognition Developer
* Guide.</p> <p>By default, the array is sorted by the time(s) a person's
* path is tracked in the video. You can sort by tracked persons by specifying
* <code>INDEX</code> for the <code>SortBy</code> input parameter.</p> <p>Use the
* <code>MaxResults</code> parameter to limit the number of items returned. If
* there are more results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetPersonTracking</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetPersonTracking">AWS
* API Reference</a></p>
*/
virtual Model::GetPersonTrackingOutcome GetPersonTracking(const Model::GetPersonTrackingRequest& request) const;
/**
* <p>Gets the path tracking results of a Amazon Rekognition Video analysis started
* by <a>StartPersonTracking</a>.</p> <p>The person path tracking operation is
* started by a call to <code>StartPersonTracking</code> which returns a job
* identifier (<code>JobId</code>). When the operation finishes, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic registered in the initial call to <code>StartPersonTracking</code>.</p>
* <p>To get the results of the person path tracking operation, first check that
* the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If
* so, call <a>GetPersonTracking</a> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p> <p> <code>GetPersonTracking</code> returns
* an array, <code>Persons</code>, of tracked persons and the time(s) their paths
* were tracked in the video. </p> <p> <code>GetPersonTracking</code> only
* returns the default facial attributes (<code>BoundingBox</code>,
* <code>Confidence</code>, <code>Landmarks</code>, <code>Pose</code>, and
* <code>Quality</code>). The other facial attributes listed in the
* <code>Face</code> object of the following response syntax are not returned. </p>
* <p>For more information, see FaceDetail in the Amazon Rekognition Developer
* Guide.</p> <p>By default, the array is sorted by the time(s) a person's
* path is tracked in the video. You can sort by tracked persons by specifying
* <code>INDEX</code> for the <code>SortBy</code> input parameter.</p> <p>Use the
* <code>MaxResults</code> parameter to limit the number of items returned. If
* there are more results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetPersonTracking</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetPersonTracking">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetPersonTrackingOutcomeCallable GetPersonTrackingCallable(const Model::GetPersonTrackingRequest& request) const;
/**
* <p>Gets the path tracking results of a Amazon Rekognition Video analysis started
* by <a>StartPersonTracking</a>.</p> <p>The person path tracking operation is
* started by a call to <code>StartPersonTracking</code> which returns a job
* identifier (<code>JobId</code>). When the operation finishes, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic registered in the initial call to <code>StartPersonTracking</code>.</p>
* <p>To get the results of the person path tracking operation, first check that
* the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If
* so, call <a>GetPersonTracking</a> and pass the job identifier
* (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p> <p> <code>GetPersonTracking</code> returns
* an array, <code>Persons</code>, of tracked persons and the time(s) their paths
* were tracked in the video. </p> <p> <code>GetPersonTracking</code> only
* returns the default facial attributes (<code>BoundingBox</code>,
* <code>Confidence</code>, <code>Landmarks</code>, <code>Pose</code>, and
* <code>Quality</code>). The other facial attributes listed in the
* <code>Face</code> object of the following response syntax are not returned. </p>
* <p>For more information, see FaceDetail in the Amazon Rekognition Developer
* Guide.</p> <p>By default, the array is sorted by the time(s) a person's
* path is tracked in the video. You can sort by tracked persons by specifying
* <code>INDEX</code> for the <code>SortBy</code> input parameter.</p> <p>Use the
* <code>MaxResults</code> parameter to limit the number of items returned. If
* there are more results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetPersonTracking</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetPersonTracking">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetPersonTrackingAsync(const Model::GetPersonTrackingRequest& request, const GetPersonTrackingResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the segment detection results of a Amazon Rekognition Video analysis
* started by <a>StartSegmentDetection</a>.</p> <p>Segment detection with Amazon
* Rekognition Video is an asynchronous operation. You start segment detection by
* calling <a>StartSegmentDetection</a> which returns a job identifier
* (<code>JobId</code>). When the segment detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartSegmentDetection</code>. To get the results of the segment detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. if so, call <code>GetSegmentDetection</code> and pass
* the job identifier (<code>JobId</code>) from the initial call of
* <code>StartSegmentDetection</code>.</p> <p> <code>GetSegmentDetection</code>
* returns detected segments in an array (<code>Segments</code>) of
* <a>SegmentDetection</a> objects. <code>Segments</code> is sorted by the segment
* types specified in the <code>SegmentTypes</code> input parameter of
* <code>StartSegmentDetection</code>. Each element of the array includes the
* detected segment, the precentage confidence in the acuracy of the detected
* segment, the type of the segment, and the frame in which the segment was
* detected.</p> <p>Use <code>SelectedSegmentTypes</code> to find out the type of
* segment detection requested in the call to
* <code>StartSegmentDetection</code>.</p> <p>Use the <code>MaxResults</code>
* parameter to limit the number of segment detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetSegmentDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetSegmentDetection</code>.</p> <p>For more information, see Detecting
* Video Segments in Stored Video in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetSegmentDetection">AWS
* API Reference</a></p>
*/
virtual Model::GetSegmentDetectionOutcome GetSegmentDetection(const Model::GetSegmentDetectionRequest& request) const;
/**
* <p>Gets the segment detection results of a Amazon Rekognition Video analysis
* started by <a>StartSegmentDetection</a>.</p> <p>Segment detection with Amazon
* Rekognition Video is an asynchronous operation. You start segment detection by
* calling <a>StartSegmentDetection</a> which returns a job identifier
* (<code>JobId</code>). When the segment detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartSegmentDetection</code>. To get the results of the segment detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. if so, call <code>GetSegmentDetection</code> and pass
* the job identifier (<code>JobId</code>) from the initial call of
* <code>StartSegmentDetection</code>.</p> <p> <code>GetSegmentDetection</code>
* returns detected segments in an array (<code>Segments</code>) of
* <a>SegmentDetection</a> objects. <code>Segments</code> is sorted by the segment
* types specified in the <code>SegmentTypes</code> input parameter of
* <code>StartSegmentDetection</code>. Each element of the array includes the
* detected segment, the precentage confidence in the acuracy of the detected
* segment, the type of the segment, and the frame in which the segment was
* detected.</p> <p>Use <code>SelectedSegmentTypes</code> to find out the type of
* segment detection requested in the call to
* <code>StartSegmentDetection</code>.</p> <p>Use the <code>MaxResults</code>
* parameter to limit the number of segment detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetSegmentDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetSegmentDetection</code>.</p> <p>For more information, see Detecting
* Video Segments in Stored Video in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetSegmentDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetSegmentDetectionOutcomeCallable GetSegmentDetectionCallable(const Model::GetSegmentDetectionRequest& request) const;
/**
* <p>Gets the segment detection results of a Amazon Rekognition Video analysis
* started by <a>StartSegmentDetection</a>.</p> <p>Segment detection with Amazon
* Rekognition Video is an asynchronous operation. You start segment detection by
* calling <a>StartSegmentDetection</a> which returns a job identifier
* (<code>JobId</code>). When the segment detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to
* <code>StartSegmentDetection</code>. To get the results of the segment detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. if so, call <code>GetSegmentDetection</code> and pass
* the job identifier (<code>JobId</code>) from the initial call of
* <code>StartSegmentDetection</code>.</p> <p> <code>GetSegmentDetection</code>
* returns detected segments in an array (<code>Segments</code>) of
* <a>SegmentDetection</a> objects. <code>Segments</code> is sorted by the segment
* types specified in the <code>SegmentTypes</code> input parameter of
* <code>StartSegmentDetection</code>. Each element of the array includes the
* detected segment, the precentage confidence in the acuracy of the detected
* segment, the type of the segment, and the frame in which the segment was
* detected.</p> <p>Use <code>SelectedSegmentTypes</code> to find out the type of
* segment detection requested in the call to
* <code>StartSegmentDetection</code>.</p> <p>Use the <code>MaxResults</code>
* parameter to limit the number of segment detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetSegmentDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetSegmentDetection</code>.</p> <p>For more information, see Detecting
* Video Segments in Stored Video in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetSegmentDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetSegmentDetectionAsync(const Model::GetSegmentDetectionRequest& request, const GetSegmentDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets the text detection results of a Amazon Rekognition Video analysis
* started by <a>StartTextDetection</a>.</p> <p>Text detection with Amazon
* Rekognition Video is an asynchronous operation. You start text detection by
* calling <a>StartTextDetection</a> which returns a job identifier
* (<code>JobId</code>) When the text detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to <code>StartTextDetection</code>.
* To get the results of the text detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <code>GetTextDetection</code> and pass the job identifier (<code>JobId</code>)
* from the initial call of <code>StartLabelDetection</code>.</p> <p>
* <code>GetTextDetection</code> returns an array of detected text
* (<code>TextDetections</code>) sorted by the time the text was detected, up to 50
* words per frame of video.</p> <p>Each element of the array includes the detected
* text, the precentage confidence in the acuracy of the detected text, the time
* the text was detected, bounding box information for where the text was located,
* and unique identifiers for words and their lines.</p> <p>Use MaxResults
* parameter to limit the number of text detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetTextDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetTextDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetTextDetection">AWS
* API Reference</a></p>
*/
virtual Model::GetTextDetectionOutcome GetTextDetection(const Model::GetTextDetectionRequest& request) const;
/**
* <p>Gets the text detection results of a Amazon Rekognition Video analysis
* started by <a>StartTextDetection</a>.</p> <p>Text detection with Amazon
* Rekognition Video is an asynchronous operation. You start text detection by
* calling <a>StartTextDetection</a> which returns a job identifier
* (<code>JobId</code>) When the text detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to <code>StartTextDetection</code>.
* To get the results of the text detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <code>GetTextDetection</code> and pass the job identifier (<code>JobId</code>)
* from the initial call of <code>StartLabelDetection</code>.</p> <p>
* <code>GetTextDetection</code> returns an array of detected text
* (<code>TextDetections</code>) sorted by the time the text was detected, up to 50
* words per frame of video.</p> <p>Each element of the array includes the detected
* text, the precentage confidence in the acuracy of the detected text, the time
* the text was detected, bounding box information for where the text was located,
* and unique identifiers for words and their lines.</p> <p>Use MaxResults
* parameter to limit the number of text detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetTextDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetTextDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetTextDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetTextDetectionOutcomeCallable GetTextDetectionCallable(const Model::GetTextDetectionRequest& request) const;
/**
* <p>Gets the text detection results of a Amazon Rekognition Video analysis
* started by <a>StartTextDetection</a>.</p> <p>Text detection with Amazon
* Rekognition Video is an asynchronous operation. You start text detection by
* calling <a>StartTextDetection</a> which returns a job identifier
* (<code>JobId</code>) When the text detection operation finishes, Amazon
* Rekognition publishes a completion status to the Amazon Simple Notification
* Service topic registered in the initial call to <code>StartTextDetection</code>.
* To get the results of the text detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <code>GetTextDetection</code> and pass the job identifier (<code>JobId</code>)
* from the initial call of <code>StartLabelDetection</code>.</p> <p>
* <code>GetTextDetection</code> returns an array of detected text
* (<code>TextDetections</code>) sorted by the time the text was detected, up to 50
* words per frame of video.</p> <p>Each element of the array includes the detected
* text, the precentage confidence in the acuracy of the detected text, the time
* the text was detected, bounding box information for where the text was located,
* and unique identifiers for words and their lines.</p> <p>Use MaxResults
* parameter to limit the number of text detections returned. If there are more
* results than specified in <code>MaxResults</code>, the value of
* <code>NextToken</code> in the operation response contains a pagination token for
* getting the next set of results. To get the next page of results, call
* <code>GetTextDetection</code> and populate the <code>NextToken</code> request
* parameter with the token value returned from the previous call to
* <code>GetTextDetection</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/GetTextDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetTextDetectionAsync(const Model::GetTextDetectionRequest& request, const GetTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Detects faces in the input image and adds them to the specified collection.
* </p> <p>Amazon Rekognition doesn't save the actual faces that are detected.
* Instead, the underlying detection algorithm first detects the faces in the input
* image. For each face, the algorithm extracts facial features into a feature
* vector, and stores it in the backend database. Amazon Rekognition uses feature
* vectors when it performs face match and search operations using the
* <a>SearchFaces</a> and <a>SearchFacesByImage</a> operations.</p> <p>For more
* information, see Adding Faces to a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>To get the number of faces in a collection, call
* <a>DescribeCollection</a>. </p> <p>If you're using version 1.0 of the face
* detection model, <code>IndexFaces</code> indexes the 15 largest faces in the
* input image. Later versions of the face detection model index the 100 largest
* faces in the input image. </p> <p>If you're using version 4 or later of the face
* model, image orientation information is not returned in the
* <code>OrientationCorrection</code> field. </p> <p>To determine which version of
* the model you're using, call <a>DescribeCollection</a> and supply the collection
* ID. You can also get the model version from the value of
* <code>FaceModelVersion</code> in the response from <code>IndexFaces</code> </p>
* <p>For more information, see Model Versioning in the Amazon Rekognition
* Developer Guide.</p> <p>If you provide the optional <code>ExternalImageId</code>
* for the input image you provided, Amazon Rekognition associates this ID with all
* faces that it detects. When you call the <a>ListFaces</a> operation, the
* response returns the external ID. You can use this external image ID to create a
* client-side index to associate the faces with each image. You can then use the
* index to find all faces in an image.</p> <p>You can specify the maximum number
* of faces to index with the <code>MaxFaces</code> input parameter. This is useful
* when you want to index the largest faces in an image and don't want to index
* smaller faces, such as those belonging to people standing in the background.</p>
* <p>The <code>QualityFilter</code> input parameter allows you to filter out
* detected faces that don’t meet a required quality bar. The quality bar is based
* on a variety of common use cases. By default, <code>IndexFaces</code> chooses
* the quality bar that's used to filter faces. You can also explicitly choose the
* quality bar. Use <code>QualityFilter</code>, to set the quality bar by
* specifying <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you
* do not want to filter detected faces, specify <code>NONE</code>. </p>
* <p>To use quality filtering, you need a collection associated with version 3 of
* the face model or higher. To get the version of the face model associated with a
* collection, call <a>DescribeCollection</a>. </p> <p>Information about
* faces detected in an image, but not indexed, is returned in an array of
* <a>UnindexedFace</a> objects, <code>UnindexedFaces</code>. Faces aren't indexed
* for reasons such as:</p> <ul> <li> <p>The number of faces detected exceeds the
* value of the <code>MaxFaces</code> request parameter.</p> </li> <li> <p>The face
* is too small compared to the image dimensions.</p> </li> <li> <p>The face is too
* blurry.</p> </li> <li> <p>The image is too dark.</p> </li> <li> <p>The face has
* an extreme pose.</p> </li> <li> <p>The face doesn’t have enough detail to be
* suitable for face search.</p> </li> </ul> <p>In response, the
* <code>IndexFaces</code> operation returns an array of metadata for all detected
* faces, <code>FaceRecords</code>. This includes: </p> <ul> <li> <p>The bounding
* box, <code>BoundingBox</code>, of the detected face. </p> </li> <li> <p>A
* confidence value, <code>Confidence</code>, which indicates the confidence that
* the bounding box contains a face.</p> </li> <li> <p>A face ID,
* <code>FaceId</code>, assigned by the service for each face that's detected and
* stored.</p> </li> <li> <p>An image ID, <code>ImageId</code>, assigned by the
* service for the input image.</p> </li> </ul> <p>If you request all facial
* attributes (by using the <code>detectionAttributes</code> parameter), Amazon
* Rekognition returns detailed facial attributes, such as facial landmarks (for
* example, location of eye and mouth) and other facial attributes. If you provide
* the same image, specify the same collection, and use the same external ID in the
* <code>IndexFaces</code> operation, Amazon Rekognition doesn't save duplicate
* face metadata.</p> <p/> <p>The input image is passed either as base64-encoded
* image bytes, or as a reference to an image in an Amazon S3 bucket. If you use
* the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't
* supported. The image must be formatted as a PNG or JPEG file. </p> <p>This
* operation requires permissions to perform the
* <code>rekognition:IndexFaces</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/IndexFaces">AWS
* API Reference</a></p>
*/
virtual Model::IndexFacesOutcome IndexFaces(const Model::IndexFacesRequest& request) const;
/**
* <p>Detects faces in the input image and adds them to the specified collection.
* </p> <p>Amazon Rekognition doesn't save the actual faces that are detected.
* Instead, the underlying detection algorithm first detects the faces in the input
* image. For each face, the algorithm extracts facial features into a feature
* vector, and stores it in the backend database. Amazon Rekognition uses feature
* vectors when it performs face match and search operations using the
* <a>SearchFaces</a> and <a>SearchFacesByImage</a> operations.</p> <p>For more
* information, see Adding Faces to a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>To get the number of faces in a collection, call
* <a>DescribeCollection</a>. </p> <p>If you're using version 1.0 of the face
* detection model, <code>IndexFaces</code> indexes the 15 largest faces in the
* input image. Later versions of the face detection model index the 100 largest
* faces in the input image. </p> <p>If you're using version 4 or later of the face
* model, image orientation information is not returned in the
* <code>OrientationCorrection</code> field. </p> <p>To determine which version of
* the model you're using, call <a>DescribeCollection</a> and supply the collection
* ID. You can also get the model version from the value of
* <code>FaceModelVersion</code> in the response from <code>IndexFaces</code> </p>
* <p>For more information, see Model Versioning in the Amazon Rekognition
* Developer Guide.</p> <p>If you provide the optional <code>ExternalImageId</code>
* for the input image you provided, Amazon Rekognition associates this ID with all
* faces that it detects. When you call the <a>ListFaces</a> operation, the
* response returns the external ID. You can use this external image ID to create a
* client-side index to associate the faces with each image. You can then use the
* index to find all faces in an image.</p> <p>You can specify the maximum number
* of faces to index with the <code>MaxFaces</code> input parameter. This is useful
* when you want to index the largest faces in an image and don't want to index
* smaller faces, such as those belonging to people standing in the background.</p>
* <p>The <code>QualityFilter</code> input parameter allows you to filter out
* detected faces that don’t meet a required quality bar. The quality bar is based
* on a variety of common use cases. By default, <code>IndexFaces</code> chooses
* the quality bar that's used to filter faces. You can also explicitly choose the
* quality bar. Use <code>QualityFilter</code>, to set the quality bar by
* specifying <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you
* do not want to filter detected faces, specify <code>NONE</code>. </p>
* <p>To use quality filtering, you need a collection associated with version 3 of
* the face model or higher. To get the version of the face model associated with a
* collection, call <a>DescribeCollection</a>. </p> <p>Information about
* faces detected in an image, but not indexed, is returned in an array of
* <a>UnindexedFace</a> objects, <code>UnindexedFaces</code>. Faces aren't indexed
* for reasons such as:</p> <ul> <li> <p>The number of faces detected exceeds the
* value of the <code>MaxFaces</code> request parameter.</p> </li> <li> <p>The face
* is too small compared to the image dimensions.</p> </li> <li> <p>The face is too
* blurry.</p> </li> <li> <p>The image is too dark.</p> </li> <li> <p>The face has
* an extreme pose.</p> </li> <li> <p>The face doesn’t have enough detail to be
* suitable for face search.</p> </li> </ul> <p>In response, the
* <code>IndexFaces</code> operation returns an array of metadata for all detected
* faces, <code>FaceRecords</code>. This includes: </p> <ul> <li> <p>The bounding
* box, <code>BoundingBox</code>, of the detected face. </p> </li> <li> <p>A
* confidence value, <code>Confidence</code>, which indicates the confidence that
* the bounding box contains a face.</p> </li> <li> <p>A face ID,
* <code>FaceId</code>, assigned by the service for each face that's detected and
* stored.</p> </li> <li> <p>An image ID, <code>ImageId</code>, assigned by the
* service for the input image.</p> </li> </ul> <p>If you request all facial
* attributes (by using the <code>detectionAttributes</code> parameter), Amazon
* Rekognition returns detailed facial attributes, such as facial landmarks (for
* example, location of eye and mouth) and other facial attributes. If you provide
* the same image, specify the same collection, and use the same external ID in the
* <code>IndexFaces</code> operation, Amazon Rekognition doesn't save duplicate
* face metadata.</p> <p/> <p>The input image is passed either as base64-encoded
* image bytes, or as a reference to an image in an Amazon S3 bucket. If you use
* the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't
* supported. The image must be formatted as a PNG or JPEG file. </p> <p>This
* operation requires permissions to perform the
* <code>rekognition:IndexFaces</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/IndexFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::IndexFacesOutcomeCallable IndexFacesCallable(const Model::IndexFacesRequest& request) const;
/**
* <p>Detects faces in the input image and adds them to the specified collection.
* </p> <p>Amazon Rekognition doesn't save the actual faces that are detected.
* Instead, the underlying detection algorithm first detects the faces in the input
* image. For each face, the algorithm extracts facial features into a feature
* vector, and stores it in the backend database. Amazon Rekognition uses feature
* vectors when it performs face match and search operations using the
* <a>SearchFaces</a> and <a>SearchFacesByImage</a> operations.</p> <p>For more
* information, see Adding Faces to a Collection in the Amazon Rekognition
* Developer Guide.</p> <p>To get the number of faces in a collection, call
* <a>DescribeCollection</a>. </p> <p>If you're using version 1.0 of the face
* detection model, <code>IndexFaces</code> indexes the 15 largest faces in the
* input image. Later versions of the face detection model index the 100 largest
* faces in the input image. </p> <p>If you're using version 4 or later of the face
* model, image orientation information is not returned in the
* <code>OrientationCorrection</code> field. </p> <p>To determine which version of
* the model you're using, call <a>DescribeCollection</a> and supply the collection
* ID. You can also get the model version from the value of
* <code>FaceModelVersion</code> in the response from <code>IndexFaces</code> </p>
* <p>For more information, see Model Versioning in the Amazon Rekognition
* Developer Guide.</p> <p>If you provide the optional <code>ExternalImageId</code>
* for the input image you provided, Amazon Rekognition associates this ID with all
* faces that it detects. When you call the <a>ListFaces</a> operation, the
* response returns the external ID. You can use this external image ID to create a
* client-side index to associate the faces with each image. You can then use the
* index to find all faces in an image.</p> <p>You can specify the maximum number
* of faces to index with the <code>MaxFaces</code> input parameter. This is useful
* when you want to index the largest faces in an image and don't want to index
* smaller faces, such as those belonging to people standing in the background.</p>
* <p>The <code>QualityFilter</code> input parameter allows you to filter out
* detected faces that don’t meet a required quality bar. The quality bar is based
* on a variety of common use cases. By default, <code>IndexFaces</code> chooses
* the quality bar that's used to filter faces. You can also explicitly choose the
* quality bar. Use <code>QualityFilter</code>, to set the quality bar by
* specifying <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you
* do not want to filter detected faces, specify <code>NONE</code>. </p>
* <p>To use quality filtering, you need a collection associated with version 3 of
* the face model or higher. To get the version of the face model associated with a
* collection, call <a>DescribeCollection</a>. </p> <p>Information about
* faces detected in an image, but not indexed, is returned in an array of
* <a>UnindexedFace</a> objects, <code>UnindexedFaces</code>. Faces aren't indexed
* for reasons such as:</p> <ul> <li> <p>The number of faces detected exceeds the
* value of the <code>MaxFaces</code> request parameter.</p> </li> <li> <p>The face
* is too small compared to the image dimensions.</p> </li> <li> <p>The face is too
* blurry.</p> </li> <li> <p>The image is too dark.</p> </li> <li> <p>The face has
* an extreme pose.</p> </li> <li> <p>The face doesn’t have enough detail to be
* suitable for face search.</p> </li> </ul> <p>In response, the
* <code>IndexFaces</code> operation returns an array of metadata for all detected
* faces, <code>FaceRecords</code>. This includes: </p> <ul> <li> <p>The bounding
* box, <code>BoundingBox</code>, of the detected face. </p> </li> <li> <p>A
* confidence value, <code>Confidence</code>, which indicates the confidence that
* the bounding box contains a face.</p> </li> <li> <p>A face ID,
* <code>FaceId</code>, assigned by the service for each face that's detected and
* stored.</p> </li> <li> <p>An image ID, <code>ImageId</code>, assigned by the
* service for the input image.</p> </li> </ul> <p>If you request all facial
* attributes (by using the <code>detectionAttributes</code> parameter), Amazon
* Rekognition returns detailed facial attributes, such as facial landmarks (for
* example, location of eye and mouth) and other facial attributes. If you provide
* the same image, specify the same collection, and use the same external ID in the
* <code>IndexFaces</code> operation, Amazon Rekognition doesn't save duplicate
* face metadata.</p> <p/> <p>The input image is passed either as base64-encoded
* image bytes, or as a reference to an image in an Amazon S3 bucket. If you use
* the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't
* supported. The image must be formatted as a PNG or JPEG file. </p> <p>This
* operation requires permissions to perform the
* <code>rekognition:IndexFaces</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/IndexFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void IndexFacesAsync(const Model::IndexFacesRequest& request, const IndexFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns list of collection IDs in your account. If the result is truncated,
* the response also provides a <code>NextToken</code> that you can use in the
* subsequent request to fetch the next set of collection IDs.</p> <p>For an
* example, see Listing Collections in the Amazon Rekognition Developer Guide.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:ListCollections</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListCollections">AWS
* API Reference</a></p>
*/
virtual Model::ListCollectionsOutcome ListCollections(const Model::ListCollectionsRequest& request) const;
/**
* <p>Returns list of collection IDs in your account. If the result is truncated,
* the response also provides a <code>NextToken</code> that you can use in the
* subsequent request to fetch the next set of collection IDs.</p> <p>For an
* example, see Listing Collections in the Amazon Rekognition Developer Guide.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:ListCollections</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListCollections">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListCollectionsOutcomeCallable ListCollectionsCallable(const Model::ListCollectionsRequest& request) const;
/**
* <p>Returns list of collection IDs in your account. If the result is truncated,
* the response also provides a <code>NextToken</code> that you can use in the
* subsequent request to fetch the next set of collection IDs.</p> <p>For an
* example, see Listing Collections in the Amazon Rekognition Developer Guide.</p>
* <p>This operation requires permissions to perform the
* <code>rekognition:ListCollections</code> action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListCollections">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListCollectionsAsync(const Model::ListCollectionsRequest& request, const ListCollectionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns metadata for faces in the specified collection. This metadata
* includes information such as the bounding box coordinates, the confidence (that
* the bounding box contains a face), and face ID. For an example, see Listing
* Faces in a Collection in the Amazon Rekognition Developer Guide.</p> <p>This
* operation requires permissions to perform the <code>rekognition:ListFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListFaces">AWS
* API Reference</a></p>
*/
virtual Model::ListFacesOutcome ListFaces(const Model::ListFacesRequest& request) const;
/**
* <p>Returns metadata for faces in the specified collection. This metadata
* includes information such as the bounding box coordinates, the confidence (that
* the bounding box contains a face), and face ID. For an example, see Listing
* Faces in a Collection in the Amazon Rekognition Developer Guide.</p> <p>This
* operation requires permissions to perform the <code>rekognition:ListFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListFacesOutcomeCallable ListFacesCallable(const Model::ListFacesRequest& request) const;
/**
* <p>Returns metadata for faces in the specified collection. This metadata
* includes information such as the bounding box coordinates, the confidence (that
* the bounding box contains a face), and face ID. For an example, see Listing
* Faces in a Collection in the Amazon Rekognition Developer Guide.</p> <p>This
* operation requires permissions to perform the <code>rekognition:ListFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListFacesAsync(const Model::ListFacesRequest& request, const ListFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of stream processors that you have created with
* <a>CreateStreamProcessor</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListStreamProcessors">AWS
* API Reference</a></p>
*/
virtual Model::ListStreamProcessorsOutcome ListStreamProcessors(const Model::ListStreamProcessorsRequest& request) const;
/**
* <p>Gets a list of stream processors that you have created with
* <a>CreateStreamProcessor</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListStreamProcessors">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListStreamProcessorsOutcomeCallable ListStreamProcessorsCallable(const Model::ListStreamProcessorsRequest& request) const;
/**
* <p>Gets a list of stream processors that you have created with
* <a>CreateStreamProcessor</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/ListStreamProcessors">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListStreamProcessorsAsync(const Model::ListStreamProcessorsRequest& request, const ListStreamProcessorsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns an array of celebrities recognized in the input image. For more
* information, see Recognizing Celebrities in the Amazon Rekognition Developer
* Guide. </p> <p> <code>RecognizeCelebrities</code> returns the 100 largest faces
* in the image. It lists recognized celebrities in the <code>CelebrityFaces</code>
* array and unrecognized faces in the <code>UnrecognizedFaces</code> array.
* <code>RecognizeCelebrities</code> doesn't return celebrities whose faces aren't
* among the largest 100 faces in the image.</p> <p>For each celebrity recognized,
* <code>RecognizeCelebrities</code> returns a <code>Celebrity</code> object. The
* <code>Celebrity</code> object contains the celebrity name, ID, URL links to
* additional information, match confidence, and a <code>ComparedFace</code> object
* that you can use to locate the celebrity's face on the image.</p> <p>Amazon
* Rekognition doesn't retain information about which images a celebrity has been
* recognized in. Your application must store this information and use the
* <code>Celebrity</code> ID property as a unique identifier for the celebrity. If
* you don't store the celebrity name or additional information URLs returned by
* <code>RecognizeCelebrities</code>, you will need the ID to identify the
* celebrity in a call to the <a>GetCelebrityInfo</a> operation.</p> <p>You pass
* the input image either as base64-encoded image bytes or as a reference to an
* image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p>For an example, see Recognizing Celebrities in
* an Image in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:RecognizeCelebrities</code> operation.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/RecognizeCelebrities">AWS
* API Reference</a></p>
*/
virtual Model::RecognizeCelebritiesOutcome RecognizeCelebrities(const Model::RecognizeCelebritiesRequest& request) const;
/**
* <p>Returns an array of celebrities recognized in the input image. For more
* information, see Recognizing Celebrities in the Amazon Rekognition Developer
* Guide. </p> <p> <code>RecognizeCelebrities</code> returns the 100 largest faces
* in the image. It lists recognized celebrities in the <code>CelebrityFaces</code>
* array and unrecognized faces in the <code>UnrecognizedFaces</code> array.
* <code>RecognizeCelebrities</code> doesn't return celebrities whose faces aren't
* among the largest 100 faces in the image.</p> <p>For each celebrity recognized,
* <code>RecognizeCelebrities</code> returns a <code>Celebrity</code> object. The
* <code>Celebrity</code> object contains the celebrity name, ID, URL links to
* additional information, match confidence, and a <code>ComparedFace</code> object
* that you can use to locate the celebrity's face on the image.</p> <p>Amazon
* Rekognition doesn't retain information about which images a celebrity has been
* recognized in. Your application must store this information and use the
* <code>Celebrity</code> ID property as a unique identifier for the celebrity. If
* you don't store the celebrity name or additional information URLs returned by
* <code>RecognizeCelebrities</code>, you will need the ID to identify the
* celebrity in a call to the <a>GetCelebrityInfo</a> operation.</p> <p>You pass
* the input image either as base64-encoded image bytes or as a reference to an
* image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p>For an example, see Recognizing Celebrities in
* an Image in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:RecognizeCelebrities</code> operation.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/RecognizeCelebrities">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::RecognizeCelebritiesOutcomeCallable RecognizeCelebritiesCallable(const Model::RecognizeCelebritiesRequest& request) const;
/**
* <p>Returns an array of celebrities recognized in the input image. For more
* information, see Recognizing Celebrities in the Amazon Rekognition Developer
* Guide. </p> <p> <code>RecognizeCelebrities</code> returns the 100 largest faces
* in the image. It lists recognized celebrities in the <code>CelebrityFaces</code>
* array and unrecognized faces in the <code>UnrecognizedFaces</code> array.
* <code>RecognizeCelebrities</code> doesn't return celebrities whose faces aren't
* among the largest 100 faces in the image.</p> <p>For each celebrity recognized,
* <code>RecognizeCelebrities</code> returns a <code>Celebrity</code> object. The
* <code>Celebrity</code> object contains the celebrity name, ID, URL links to
* additional information, match confidence, and a <code>ComparedFace</code> object
* that you can use to locate the celebrity's face on the image.</p> <p>Amazon
* Rekognition doesn't retain information about which images a celebrity has been
* recognized in. Your application must store this information and use the
* <code>Celebrity</code> ID property as a unique identifier for the celebrity. If
* you don't store the celebrity name or additional information URLs returned by
* <code>RecognizeCelebrities</code>, you will need the ID to identify the
* celebrity in a call to the <a>GetCelebrityInfo</a> operation.</p> <p>You pass
* the input image either as base64-encoded image bytes or as a reference to an
* image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition
* operations, passing image bytes is not supported. The image must be either a PNG
* or JPEG formatted file. </p> <p>For an example, see Recognizing Celebrities in
* an Image in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the
* <code>rekognition:RecognizeCelebrities</code> operation.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/RecognizeCelebrities">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void RecognizeCelebritiesAsync(const Model::RecognizeCelebritiesRequest& request, const RecognizeCelebritiesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>For a given input face ID, searches for matching faces in the collection the
* face belongs to. You get a face ID when you add a face to the collection using
* the <a>IndexFaces</a> operation. The operation compares the features of the
* input face with faces in the specified collection. </p> <p>You can also
* search faces without indexing faces by using the <code>SearchFacesByImage</code>
* operation.</p> <p> The operation response returns an array of faces that
* match, ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match that is found.
* Along with the metadata, the response also includes a <code>confidence</code>
* value for each face match, indicating the confidence that the specific face
* matches the input face. </p> <p>For an example, see Searching for a Face Using
* Its Face ID in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the <code>rekognition:SearchFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFaces">AWS
* API Reference</a></p>
*/
virtual Model::SearchFacesOutcome SearchFaces(const Model::SearchFacesRequest& request) const;
/**
* <p>For a given input face ID, searches for matching faces in the collection the
* face belongs to. You get a face ID when you add a face to the collection using
* the <a>IndexFaces</a> operation. The operation compares the features of the
* input face with faces in the specified collection. </p> <p>You can also
* search faces without indexing faces by using the <code>SearchFacesByImage</code>
* operation.</p> <p> The operation response returns an array of faces that
* match, ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match that is found.
* Along with the metadata, the response also includes a <code>confidence</code>
* value for each face match, indicating the confidence that the specific face
* matches the input face. </p> <p>For an example, see Searching for a Face Using
* Its Face ID in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the <code>rekognition:SearchFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFaces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::SearchFacesOutcomeCallable SearchFacesCallable(const Model::SearchFacesRequest& request) const;
/**
* <p>For a given input face ID, searches for matching faces in the collection the
* face belongs to. You get a face ID when you add a face to the collection using
* the <a>IndexFaces</a> operation. The operation compares the features of the
* input face with faces in the specified collection. </p> <p>You can also
* search faces without indexing faces by using the <code>SearchFacesByImage</code>
* operation.</p> <p> The operation response returns an array of faces that
* match, ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match that is found.
* Along with the metadata, the response also includes a <code>confidence</code>
* value for each face match, indicating the confidence that the specific face
* matches the input face. </p> <p>For an example, see Searching for a Face Using
* Its Face ID in the Amazon Rekognition Developer Guide.</p> <p>This operation
* requires permissions to perform the <code>rekognition:SearchFaces</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFaces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void SearchFacesAsync(const Model::SearchFacesRequest& request, const SearchFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>For a given input image, first detects the largest face in the image, and
* then searches the specified collection for matching faces. The operation
* compares the features of the input face with faces in the specified collection.
* </p> <p>To search for all faces in an input image, you might first call
* the <a>IndexFaces</a> operation, and then use the face IDs returned in
* subsequent calls to the <a>SearchFaces</a> operation. </p> <p> You can also call
* the <code>DetectFaces</code> operation and use the bounding boxes in the
* response to make face crops, which then you can pass in to the
* <code>SearchFacesByImage</code> operation. </p> <p>You pass the input
* image either as base64-encoded image bytes or as a reference to an image in an
* Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations,
* passing image bytes is not supported. The image must be either a PNG or JPEG
* formatted file. </p> <p> The response returns an array of faces that match,
* ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match found. Along with
* the metadata, the response also includes a <code>similarity</code> indicating
* how similar the face is to the input face. In the response, the operation also
* returns the bounding box (and a confidence level that the bounding box contains
* a face) of the face that Amazon Rekognition used for the input image. </p>
* <p>For an example, Searching for a Face Using an Image in the Amazon Rekognition
* Developer Guide.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar for filtering by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>.</p> <p>To use quality filtering, you need a collection
* associated with version 3 of the face model or higher. To get the version of the
* face model associated with a collection, call <a>DescribeCollection</a>. </p>
* <p>This operation requires permissions to perform the
* <code>rekognition:SearchFacesByImage</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFacesByImage">AWS
* API Reference</a></p>
*/
virtual Model::SearchFacesByImageOutcome SearchFacesByImage(const Model::SearchFacesByImageRequest& request) const;
/**
* <p>For a given input image, first detects the largest face in the image, and
* then searches the specified collection for matching faces. The operation
* compares the features of the input face with faces in the specified collection.
* </p> <p>To search for all faces in an input image, you might first call
* the <a>IndexFaces</a> operation, and then use the face IDs returned in
* subsequent calls to the <a>SearchFaces</a> operation. </p> <p> You can also call
* the <code>DetectFaces</code> operation and use the bounding boxes in the
* response to make face crops, which then you can pass in to the
* <code>SearchFacesByImage</code> operation. </p> <p>You pass the input
* image either as base64-encoded image bytes or as a reference to an image in an
* Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations,
* passing image bytes is not supported. The image must be either a PNG or JPEG
* formatted file. </p> <p> The response returns an array of faces that match,
* ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match found. Along with
* the metadata, the response also includes a <code>similarity</code> indicating
* how similar the face is to the input face. In the response, the operation also
* returns the bounding box (and a confidence level that the bounding box contains
* a face) of the face that Amazon Rekognition used for the input image. </p>
* <p>For an example, Searching for a Face Using an Image in the Amazon Rekognition
* Developer Guide.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar for filtering by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>.</p> <p>To use quality filtering, you need a collection
* associated with version 3 of the face model or higher. To get the version of the
* face model associated with a collection, call <a>DescribeCollection</a>. </p>
* <p>This operation requires permissions to perform the
* <code>rekognition:SearchFacesByImage</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFacesByImage">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::SearchFacesByImageOutcomeCallable SearchFacesByImageCallable(const Model::SearchFacesByImageRequest& request) const;
/**
* <p>For a given input image, first detects the largest face in the image, and
* then searches the specified collection for matching faces. The operation
* compares the features of the input face with faces in the specified collection.
* </p> <p>To search for all faces in an input image, you might first call
* the <a>IndexFaces</a> operation, and then use the face IDs returned in
* subsequent calls to the <a>SearchFaces</a> operation. </p> <p> You can also call
* the <code>DetectFaces</code> operation and use the bounding boxes in the
* response to make face crops, which then you can pass in to the
* <code>SearchFacesByImage</code> operation. </p> <p>You pass the input
* image either as base64-encoded image bytes or as a reference to an image in an
* Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations,
* passing image bytes is not supported. The image must be either a PNG or JPEG
* formatted file. </p> <p> The response returns an array of faces that match,
* ordered by similarity score with the highest similarity first. More
* specifically, it is an array of metadata for each face match found. Along with
* the metadata, the response also includes a <code>similarity</code> indicating
* how similar the face is to the input face. In the response, the operation also
* returns the bounding box (and a confidence level that the bounding box contains
* a face) of the face that Amazon Rekognition used for the input image. </p>
* <p>For an example, Searching for a Face Using an Image in the Amazon Rekognition
* Developer Guide.</p> <p>The <code>QualityFilter</code> input parameter allows
* you to filter out detected faces that don’t meet a required quality bar. The
* quality bar is based on a variety of common use cases. Use
* <code>QualityFilter</code> to set the quality bar for filtering by specifying
* <code>LOW</code>, <code>MEDIUM</code>, or <code>HIGH</code>. If you do not want
* to filter detected faces, specify <code>NONE</code>. The default value is
* <code>NONE</code>.</p> <p>To use quality filtering, you need a collection
* associated with version 3 of the face model or higher. To get the version of the
* face model associated with a collection, call <a>DescribeCollection</a>. </p>
* <p>This operation requires permissions to perform the
* <code>rekognition:SearchFacesByImage</code> action.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/SearchFacesByImage">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void SearchFacesByImageAsync(const Model::SearchFacesByImageRequest& request, const SearchFacesByImageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts asynchronous recognition of celebrities in a stored video.</p>
* <p>Amazon Rekognition Video can detect celebrities in a video must be stored in
* an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the
* filename of the video. <code>StartCelebrityRecognition</code> returns a job
* identifier (<code>JobId</code>) which you use to get the results of the
* analysis. When celebrity recognition analysis is finished, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic that you specify in <code>NotificationChannel</code>. To get the results
* of the celebrity recognition analysis, first check that the status value
* published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetCelebrityRecognition</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartCelebrityRecognition</code>. </p> <p>For
* more information, see Recognizing Celebrities in the Amazon Rekognition
* Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartCelebrityRecognition">AWS
* API Reference</a></p>
*/
virtual Model::StartCelebrityRecognitionOutcome StartCelebrityRecognition(const Model::StartCelebrityRecognitionRequest& request) const;
/**
* <p>Starts asynchronous recognition of celebrities in a stored video.</p>
* <p>Amazon Rekognition Video can detect celebrities in a video must be stored in
* an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the
* filename of the video. <code>StartCelebrityRecognition</code> returns a job
* identifier (<code>JobId</code>) which you use to get the results of the
* analysis. When celebrity recognition analysis is finished, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic that you specify in <code>NotificationChannel</code>. To get the results
* of the celebrity recognition analysis, first check that the status value
* published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetCelebrityRecognition</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartCelebrityRecognition</code>. </p> <p>For
* more information, see Recognizing Celebrities in the Amazon Rekognition
* Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartCelebrityRecognition">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartCelebrityRecognitionOutcomeCallable StartCelebrityRecognitionCallable(const Model::StartCelebrityRecognitionRequest& request) const;
/**
* <p>Starts asynchronous recognition of celebrities in a stored video.</p>
* <p>Amazon Rekognition Video can detect celebrities in a video must be stored in
* an Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the
* filename of the video. <code>StartCelebrityRecognition</code> returns a job
* identifier (<code>JobId</code>) which you use to get the results of the
* analysis. When celebrity recognition analysis is finished, Amazon Rekognition
* Video publishes a completion status to the Amazon Simple Notification Service
* topic that you specify in <code>NotificationChannel</code>. To get the results
* of the celebrity recognition analysis, first check that the status value
* published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetCelebrityRecognition</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartCelebrityRecognition</code>. </p> <p>For
* more information, see Recognizing Celebrities in the Amazon Rekognition
* Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartCelebrityRecognition">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartCelebrityRecognitionAsync(const Model::StartCelebrityRecognitionRequest& request, const StartCelebrityRecognitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p> Starts asynchronous detection of unsafe content in a stored video.</p>
* <p>Amazon Rekognition Video can moderate content in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartContentModeration</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the analysis. When
* unsafe content analysis is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>.</p> <p>To get the results of the
* unsafe content analysis, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetContentModeration</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartContentModeration</code>. </p> <p>For more
* information, see Detecting Unsafe Content in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartContentModeration">AWS
* API Reference</a></p>
*/
virtual Model::StartContentModerationOutcome StartContentModeration(const Model::StartContentModerationRequest& request) const;
/**
* <p> Starts asynchronous detection of unsafe content in a stored video.</p>
* <p>Amazon Rekognition Video can moderate content in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartContentModeration</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the analysis. When
* unsafe content analysis is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>.</p> <p>To get the results of the
* unsafe content analysis, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetContentModeration</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartContentModeration</code>. </p> <p>For more
* information, see Detecting Unsafe Content in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartContentModeration">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartContentModerationOutcomeCallable StartContentModerationCallable(const Model::StartContentModerationRequest& request) const;
/**
* <p> Starts asynchronous detection of unsafe content in a stored video.</p>
* <p>Amazon Rekognition Video can moderate content in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartContentModeration</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the analysis. When
* unsafe content analysis is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>.</p> <p>To get the results of the
* unsafe content analysis, first check that the status value published to the
* Amazon SNS topic is <code>SUCCEEDED</code>. If so, call
* <a>GetContentModeration</a> and pass the job identifier (<code>JobId</code>)
* from the initial call to <code>StartContentModeration</code>. </p> <p>For more
* information, see Detecting Unsafe Content in the Amazon Rekognition Developer
* Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartContentModeration">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartContentModerationAsync(const Model::StartContentModerationRequest& request, const StartContentModerationResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts asynchronous detection of faces in a stored video.</p> <p>Amazon
* Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartFaceDetection</code> returns a job identifier (<code>JobId</code>)
* that you use to get the results of the operation. When face detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. To get the results of the face detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p>For more information, see Detecting
* Faces in a Stored Video in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceDetection">AWS
* API Reference</a></p>
*/
virtual Model::StartFaceDetectionOutcome StartFaceDetection(const Model::StartFaceDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of faces in a stored video.</p> <p>Amazon
* Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartFaceDetection</code> returns a job identifier (<code>JobId</code>)
* that you use to get the results of the operation. When face detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. To get the results of the face detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p>For more information, see Detecting
* Faces in a Stored Video in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartFaceDetectionOutcomeCallable StartFaceDetectionCallable(const Model::StartFaceDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of faces in a stored video.</p> <p>Amazon
* Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartFaceDetection</code> returns a job identifier (<code>JobId</code>)
* that you use to get the results of the operation. When face detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. To get the results of the face detection
* operation, first check that the status value published to the Amazon SNS topic
* is <code>SUCCEEDED</code>. If so, call <a>GetFaceDetection</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceDetection</code>.</p> <p>For more information, see Detecting
* Faces in a Stored Video in the Amazon Rekognition Developer Guide.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartFaceDetectionAsync(const Model::StartFaceDetectionRequest& request, const StartFaceDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts the asynchronous search for faces in a collection that match the faces
* of persons detected in a stored video.</p> <p>The video must be stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartFaceSearch</code> returns a job identifier
* (<code>JobId</code>) which you use to get the search results once the search has
* completed. When searching is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>. To get the search results, first
* check that the status value published to the Amazon SNS topic is
* <code>SUCCEEDED</code>. If so, call <a>GetFaceSearch</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceSearch</code>. For more information, see
* <a>procedure-person-search-videos</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceSearch">AWS
* API Reference</a></p>
*/
virtual Model::StartFaceSearchOutcome StartFaceSearch(const Model::StartFaceSearchRequest& request) const;
/**
* <p>Starts the asynchronous search for faces in a collection that match the faces
* of persons detected in a stored video.</p> <p>The video must be stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartFaceSearch</code> returns a job identifier
* (<code>JobId</code>) which you use to get the search results once the search has
* completed. When searching is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>. To get the search results, first
* check that the status value published to the Amazon SNS topic is
* <code>SUCCEEDED</code>. If so, call <a>GetFaceSearch</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceSearch</code>. For more information, see
* <a>procedure-person-search-videos</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceSearch">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartFaceSearchOutcomeCallable StartFaceSearchCallable(const Model::StartFaceSearchRequest& request) const;
/**
* <p>Starts the asynchronous search for faces in a collection that match the faces
* of persons detected in a stored video.</p> <p>The video must be stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartFaceSearch</code> returns a job identifier
* (<code>JobId</code>) which you use to get the search results once the search has
* completed. When searching is finished, Amazon Rekognition Video publishes a
* completion status to the Amazon Simple Notification Service topic that you
* specify in <code>NotificationChannel</code>. To get the search results, first
* check that the status value published to the Amazon SNS topic is
* <code>SUCCEEDED</code>. If so, call <a>GetFaceSearch</a> and pass the job
* identifier (<code>JobId</code>) from the initial call to
* <code>StartFaceSearch</code>. For more information, see
* <a>procedure-person-search-videos</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartFaceSearch">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartFaceSearchAsync(const Model::StartFaceSearchRequest& request, const StartFaceSearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon
* Rekognition Video can detect labels in a video. Labels are instances of
* real-world entities. This includes objects like flower, tree, and table; events
* like wedding, graduation, and birthday party; concepts like landscape, evening,
* and nature; and activities like a person getting out of a car or a person
* skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a>
* to specify the bucket name and the filename of the video.
* <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When label detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the label
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p/><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartLabelDetection">AWS
* API Reference</a></p>
*/
virtual Model::StartLabelDetectionOutcome StartLabelDetection(const Model::StartLabelDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon
* Rekognition Video can detect labels in a video. Labels are instances of
* real-world entities. This includes objects like flower, tree, and table; events
* like wedding, graduation, and birthday party; concepts like landscape, evening,
* and nature; and activities like a person getting out of a car or a person
* skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a>
* to specify the bucket name and the filename of the video.
* <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When label detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the label
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p/><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartLabelDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartLabelDetectionOutcomeCallable StartLabelDetectionCallable(const Model::StartLabelDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of labels in a stored video.</p> <p>Amazon
* Rekognition Video can detect labels in a video. Labels are instances of
* real-world entities. This includes objects like flower, tree, and table; events
* like wedding, graduation, and birthday party; concepts like landscape, evening,
* and nature; and activities like a person getting out of a car or a person
* skiing.</p> <p>The video must be stored in an Amazon S3 bucket. Use <a>Video</a>
* to specify the bucket name and the filename of the video.
* <code>StartLabelDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When label detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the label
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetLabelDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartLabelDetection</code>.</p> <p/><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartLabelDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartLabelDetectionAsync(const Model::StartLabelDetectionRequest& request, const StartLabelDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts the asynchronous tracking of a person's path in a stored video.</p>
* <p>Amazon Rekognition Video can track the path of people in a video stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartPersonTracking</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* label detection is finished, Amazon Rekognition publishes a completion status to
* the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. </p> <p>To get the results of the person
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetPersonTracking</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartPersonTracking">AWS
* API Reference</a></p>
*/
virtual Model::StartPersonTrackingOutcome StartPersonTracking(const Model::StartPersonTrackingRequest& request) const;
/**
* <p>Starts the asynchronous tracking of a person's path in a stored video.</p>
* <p>Amazon Rekognition Video can track the path of people in a video stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartPersonTracking</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* label detection is finished, Amazon Rekognition publishes a completion status to
* the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. </p> <p>To get the results of the person
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetPersonTracking</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartPersonTracking">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartPersonTrackingOutcomeCallable StartPersonTrackingCallable(const Model::StartPersonTrackingRequest& request) const;
/**
* <p>Starts the asynchronous tracking of a person's path in a stored video.</p>
* <p>Amazon Rekognition Video can track the path of people in a video stored in an
* Amazon S3 bucket. Use <a>Video</a> to specify the bucket name and the filename
* of the video. <code>StartPersonTracking</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* label detection is finished, Amazon Rekognition publishes a completion status to
* the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>. </p> <p>To get the results of the person
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. If so, call <a>GetPersonTracking</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartPersonTracking</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartPersonTracking">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartPersonTrackingAsync(const Model::StartPersonTrackingRequest& request, const StartPersonTrackingResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts the running of the version of a model. Starting a model takes a while
* to complete. To check the current state of the model, use
* <a>DescribeProjectVersions</a>.</p> <p>Once the model is running, you can detect
* custom labels in new images by calling <a>DetectCustomLabels</a>.</p>
* <p>You are charged for the amount of time that the model is running. To stop a
* running model, call <a>StopProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the <code>rekognition:StartProjectVersion</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartProjectVersion">AWS
* API Reference</a></p>
*/
virtual Model::StartProjectVersionOutcome StartProjectVersion(const Model::StartProjectVersionRequest& request) const;
/**
* <p>Starts the running of the version of a model. Starting a model takes a while
* to complete. To check the current state of the model, use
* <a>DescribeProjectVersions</a>.</p> <p>Once the model is running, you can detect
* custom labels in new images by calling <a>DetectCustomLabels</a>.</p>
* <p>You are charged for the amount of time that the model is running. To stop a
* running model, call <a>StopProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the <code>rekognition:StartProjectVersion</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartProjectVersion">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartProjectVersionOutcomeCallable StartProjectVersionCallable(const Model::StartProjectVersionRequest& request) const;
/**
* <p>Starts the running of the version of a model. Starting a model takes a while
* to complete. To check the current state of the model, use
* <a>DescribeProjectVersions</a>.</p> <p>Once the model is running, you can detect
* custom labels in new images by calling <a>DetectCustomLabels</a>.</p>
* <p>You are charged for the amount of time that the model is running. To stop a
* running model, call <a>StopProjectVersion</a>.</p> <p>This operation
* requires permissions to perform the <code>rekognition:StartProjectVersion</code>
* action.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartProjectVersion">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartProjectVersionAsync(const Model::StartProjectVersionRequest& request, const StartProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts asynchronous detection of segment detection in a stored video.</p>
* <p>Amazon Rekognition Video can detect segments in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartSegmentDetection</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* segment detection is finished, Amazon Rekognition Video publishes a completion
* status to the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>You can use the <code>Filters</code>
* (<a>StartSegmentDetectionFilters</a>) input parameter to specify the minimum
* detection confidence returned in the response. Within <code>Filters</code>, use
* <code>ShotFilter</code> (<a>StartShotDetectionFilter</a>) to filter detected
* shots. Use <code>TechnicalCueFilter</code>
* (<a>StartTechnicalCueDetectionFilter</a>) to filter technical cues. </p> <p>To
* get the results of the segment detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <a>GetSegmentDetection</a> and pass the job identifier (<code>JobId</code>) from
* the initial call to <code>StartSegmentDetection</code>. </p> <p>For more
* information, see Detecting Video Segments in Stored Video in the Amazon
* Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartSegmentDetection">AWS
* API Reference</a></p>
*/
virtual Model::StartSegmentDetectionOutcome StartSegmentDetection(const Model::StartSegmentDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of segment detection in a stored video.</p>
* <p>Amazon Rekognition Video can detect segments in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartSegmentDetection</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* segment detection is finished, Amazon Rekognition Video publishes a completion
* status to the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>You can use the <code>Filters</code>
* (<a>StartSegmentDetectionFilters</a>) input parameter to specify the minimum
* detection confidence returned in the response. Within <code>Filters</code>, use
* <code>ShotFilter</code> (<a>StartShotDetectionFilter</a>) to filter detected
* shots. Use <code>TechnicalCueFilter</code>
* (<a>StartTechnicalCueDetectionFilter</a>) to filter technical cues. </p> <p>To
* get the results of the segment detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <a>GetSegmentDetection</a> and pass the job identifier (<code>JobId</code>) from
* the initial call to <code>StartSegmentDetection</code>. </p> <p>For more
* information, see Detecting Video Segments in Stored Video in the Amazon
* Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartSegmentDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartSegmentDetectionOutcomeCallable StartSegmentDetectionCallable(const Model::StartSegmentDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of segment detection in a stored video.</p>
* <p>Amazon Rekognition Video can detect segments in a video stored in an Amazon
* S3 bucket. Use <a>Video</a> to specify the bucket name and the filename of the
* video. <code>StartSegmentDetection</code> returns a job identifier
* (<code>JobId</code>) which you use to get the results of the operation. When
* segment detection is finished, Amazon Rekognition Video publishes a completion
* status to the Amazon Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>You can use the <code>Filters</code>
* (<a>StartSegmentDetectionFilters</a>) input parameter to specify the minimum
* detection confidence returned in the response. Within <code>Filters</code>, use
* <code>ShotFilter</code> (<a>StartShotDetectionFilter</a>) to filter detected
* shots. Use <code>TechnicalCueFilter</code>
* (<a>StartTechnicalCueDetectionFilter</a>) to filter technical cues. </p> <p>To
* get the results of the segment detection operation, first check that the status
* value published to the Amazon SNS topic is <code>SUCCEEDED</code>. if so, call
* <a>GetSegmentDetection</a> and pass the job identifier (<code>JobId</code>) from
* the initial call to <code>StartSegmentDetection</code>. </p> <p>For more
* information, see Detecting Video Segments in Stored Video in the Amazon
* Rekognition Developer Guide.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartSegmentDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartSegmentDetectionAsync(const Model::StartSegmentDetectionRequest& request, const StartSegmentDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts processing a stream processor. You create a stream processor by
* calling <a>CreateStreamProcessor</a>. To tell <code>StartStreamProcessor</code>
* which stream processor to start, use the value of the <code>Name</code> field
* specified in the call to <code>CreateStreamProcessor</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartStreamProcessor">AWS
* API Reference</a></p>
*/
virtual Model::StartStreamProcessorOutcome StartStreamProcessor(const Model::StartStreamProcessorRequest& request) const;
/**
* <p>Starts processing a stream processor. You create a stream processor by
* calling <a>CreateStreamProcessor</a>. To tell <code>StartStreamProcessor</code>
* which stream processor to start, use the value of the <code>Name</code> field
* specified in the call to <code>CreateStreamProcessor</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartStreamProcessor">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartStreamProcessorOutcomeCallable StartStreamProcessorCallable(const Model::StartStreamProcessorRequest& request) const;
/**
* <p>Starts processing a stream processor. You create a stream processor by
* calling <a>CreateStreamProcessor</a>. To tell <code>StartStreamProcessor</code>
* which stream processor to start, use the value of the <code>Name</code> field
* specified in the call to <code>CreateStreamProcessor</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartStreamProcessor">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartStreamProcessorAsync(const Model::StartStreamProcessorRequest& request, const StartStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts asynchronous detection of text in a stored video.</p> <p>Amazon
* Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartTextDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When text detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the text
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. if so, call <a>GetTextDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartTextDetection</code>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartTextDetection">AWS
* API Reference</a></p>
*/
virtual Model::StartTextDetectionOutcome StartTextDetection(const Model::StartTextDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of text in a stored video.</p> <p>Amazon
* Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartTextDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When text detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the text
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. if so, call <a>GetTextDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartTextDetection</code>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartTextDetection">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartTextDetectionOutcomeCallable StartTextDetectionCallable(const Model::StartTextDetectionRequest& request) const;
/**
* <p>Starts asynchronous detection of text in a stored video.</p> <p>Amazon
* Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use
* <a>Video</a> to specify the bucket name and the filename of the video.
* <code>StartTextDetection</code> returns a job identifier (<code>JobId</code>)
* which you use to get the results of the operation. When text detection is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic that you specify in
* <code>NotificationChannel</code>.</p> <p>To get the results of the text
* detection operation, first check that the status value published to the Amazon
* SNS topic is <code>SUCCEEDED</code>. if so, call <a>GetTextDetection</a> and
* pass the job identifier (<code>JobId</code>) from the initial call to
* <code>StartTextDetection</code>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StartTextDetection">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartTextDetectionAsync(const Model::StartTextDetectionRequest& request, const StartTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a running model. The operation might take a while to complete. To check
* the current status, call <a>DescribeProjectVersions</a>. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopProjectVersion">AWS
* API Reference</a></p>
*/
virtual Model::StopProjectVersionOutcome StopProjectVersion(const Model::StopProjectVersionRequest& request) const;
/**
* <p>Stops a running model. The operation might take a while to complete. To check
* the current status, call <a>DescribeProjectVersions</a>. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopProjectVersion">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopProjectVersionOutcomeCallable StopProjectVersionCallable(const Model::StopProjectVersionRequest& request) const;
/**
* <p>Stops a running model. The operation might take a while to complete. To check
* the current status, call <a>DescribeProjectVersions</a>. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopProjectVersion">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopProjectVersionAsync(const Model::StopProjectVersionRequest& request, const StopProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a running stream processor that was created by
* <a>CreateStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopStreamProcessor">AWS
* API Reference</a></p>
*/
virtual Model::StopStreamProcessorOutcome StopStreamProcessor(const Model::StopStreamProcessorRequest& request) const;
/**
* <p>Stops a running stream processor that was created by
* <a>CreateStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopStreamProcessor">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopStreamProcessorOutcomeCallable StopStreamProcessorCallable(const Model::StopStreamProcessorRequest& request) const;
/**
* <p>Stops a running stream processor that was created by
* <a>CreateStreamProcessor</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/rekognition-2016-06-27/StopStreamProcessor">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopStreamProcessorAsync(const Model::StopStreamProcessorRequest& request, const StopStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
void OverrideEndpoint(const Aws::String& endpoint);
private:
void init(const Aws::Client::ClientConfiguration& clientConfiguration);
void CompareFacesAsyncHelper(const Model::CompareFacesRequest& request, const CompareFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateCollectionAsyncHelper(const Model::CreateCollectionRequest& request, const CreateCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateProjectAsyncHelper(const Model::CreateProjectRequest& request, const CreateProjectResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateProjectVersionAsyncHelper(const Model::CreateProjectVersionRequest& request, const CreateProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateStreamProcessorAsyncHelper(const Model::CreateStreamProcessorRequest& request, const CreateStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteCollectionAsyncHelper(const Model::DeleteCollectionRequest& request, const DeleteCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteFacesAsyncHelper(const Model::DeleteFacesRequest& request, const DeleteFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteProjectAsyncHelper(const Model::DeleteProjectRequest& request, const DeleteProjectResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteProjectVersionAsyncHelper(const Model::DeleteProjectVersionRequest& request, const DeleteProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteStreamProcessorAsyncHelper(const Model::DeleteStreamProcessorRequest& request, const DeleteStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeCollectionAsyncHelper(const Model::DescribeCollectionRequest& request, const DescribeCollectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeProjectVersionsAsyncHelper(const Model::DescribeProjectVersionsRequest& request, const DescribeProjectVersionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeProjectsAsyncHelper(const Model::DescribeProjectsRequest& request, const DescribeProjectsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeStreamProcessorAsyncHelper(const Model::DescribeStreamProcessorRequest& request, const DescribeStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DetectCustomLabelsAsyncHelper(const Model::DetectCustomLabelsRequest& request, const DetectCustomLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DetectFacesAsyncHelper(const Model::DetectFacesRequest& request, const DetectFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DetectLabelsAsyncHelper(const Model::DetectLabelsRequest& request, const DetectLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DetectModerationLabelsAsyncHelper(const Model::DetectModerationLabelsRequest& request, const DetectModerationLabelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DetectTextAsyncHelper(const Model::DetectTextRequest& request, const DetectTextResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetCelebrityInfoAsyncHelper(const Model::GetCelebrityInfoRequest& request, const GetCelebrityInfoResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetCelebrityRecognitionAsyncHelper(const Model::GetCelebrityRecognitionRequest& request, const GetCelebrityRecognitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetContentModerationAsyncHelper(const Model::GetContentModerationRequest& request, const GetContentModerationResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetFaceDetectionAsyncHelper(const Model::GetFaceDetectionRequest& request, const GetFaceDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetFaceSearchAsyncHelper(const Model::GetFaceSearchRequest& request, const GetFaceSearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetLabelDetectionAsyncHelper(const Model::GetLabelDetectionRequest& request, const GetLabelDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetPersonTrackingAsyncHelper(const Model::GetPersonTrackingRequest& request, const GetPersonTrackingResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetSegmentDetectionAsyncHelper(const Model::GetSegmentDetectionRequest& request, const GetSegmentDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetTextDetectionAsyncHelper(const Model::GetTextDetectionRequest& request, const GetTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void IndexFacesAsyncHelper(const Model::IndexFacesRequest& request, const IndexFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListCollectionsAsyncHelper(const Model::ListCollectionsRequest& request, const ListCollectionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListFacesAsyncHelper(const Model::ListFacesRequest& request, const ListFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListStreamProcessorsAsyncHelper(const Model::ListStreamProcessorsRequest& request, const ListStreamProcessorsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void RecognizeCelebritiesAsyncHelper(const Model::RecognizeCelebritiesRequest& request, const RecognizeCelebritiesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void SearchFacesAsyncHelper(const Model::SearchFacesRequest& request, const SearchFacesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void SearchFacesByImageAsyncHelper(const Model::SearchFacesByImageRequest& request, const SearchFacesByImageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartCelebrityRecognitionAsyncHelper(const Model::StartCelebrityRecognitionRequest& request, const StartCelebrityRecognitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartContentModerationAsyncHelper(const Model::StartContentModerationRequest& request, const StartContentModerationResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartFaceDetectionAsyncHelper(const Model::StartFaceDetectionRequest& request, const StartFaceDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartFaceSearchAsyncHelper(const Model::StartFaceSearchRequest& request, const StartFaceSearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartLabelDetectionAsyncHelper(const Model::StartLabelDetectionRequest& request, const StartLabelDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartPersonTrackingAsyncHelper(const Model::StartPersonTrackingRequest& request, const StartPersonTrackingResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartProjectVersionAsyncHelper(const Model::StartProjectVersionRequest& request, const StartProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartSegmentDetectionAsyncHelper(const Model::StartSegmentDetectionRequest& request, const StartSegmentDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartStreamProcessorAsyncHelper(const Model::StartStreamProcessorRequest& request, const StartStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartTextDetectionAsyncHelper(const Model::StartTextDetectionRequest& request, const StartTextDetectionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopProjectVersionAsyncHelper(const Model::StopProjectVersionRequest& request, const StopProjectVersionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopStreamProcessorAsyncHelper(const Model::StopStreamProcessorRequest& request, const StopStreamProcessorResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
Aws::String m_uri;
Aws::String m_configScheme;
std::shared_ptr<Aws::Utils::Threading::Executor> m_executor;
};
} // namespace Rekognition
} // namespace Aws
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