* Note: Do not directly implement this interface, new methods are added to it regularly. Extend from * {@link com.amazonaws.services.rekognition.AbstractAmazonRekognitionAsync} instead. *
**
* This is the API Reference for Amazon * Rekognition Image, Amazon * Rekognition Custom Labels, Amazon * Rekognition Stored Video, Amazon * Rekognition Streaming Video. It provides descriptions of actions, data types, common parameters, and common * errors. *
** Amazon Rekognition Image *
** AssociateFaces *
** CompareFaces *
** CreateCollection *
** CreateUser *
** DeleteCollection *
** DeleteFaces *
** DeleteUser *
** DetectFaces *
** DetectLabels *
** DetectText *
** GetCelebrityInfo *
** IndexFaces *
** ListCollections *
** ListFaces *
** ListUsers *
** SearchFaces *
** SearchUsers *
** Amazon Rekognition Custom Labels *
** CreateDataset *
** CreateProject *
** DeleteDataset *
** DeleteProject *
** DescribeDataset *
** DescribeProjects *
** PutProjectPolicy *
** Amazon Rekognition Video Stored Video *
** GetFaceDetection *
** GetFaceSearch *
** GetTextDetection *
** StartFaceSearch *
** Amazon Rekognition Video Streaming Video *
*
* Associates one or more faces with an existing UserID. Takes an array of FaceIds. Each
* FaceId that are present in the FaceIds list is associated with the provided UserID. The
* maximum number of total FaceIds per UserID is 100.
*
* The UserMatchThreshold parameter specifies the minimum user match confidence required for the face
* to be associated with a UserID that has at least one FaceID already associated. This ensures that
* the FaceIds are associated with the right UserID. The value ranges from 0-100 and default value is
* 75.
*
* If successful, an array of AssociatedFace objects containing the associated FaceIds is
* returned. If a given face is already associated with the given UserID, it will be ignored and will
* not be returned in the response. If a given face is already associated to a different UserID, isn't
* found in the collection, doesn’t meet the UserMatchThreshold, or there are already 100 faces
* associated with the UserID, it will be returned as part of an array of
* UnsuccessfulFaceAssociations.
*
* The UserStatus reflects the status of an operation which updates a UserID representation with a list
* of given faces. The UserStatus can be:
*
* ACTIVE - All associations or disassociations of FaceID(s) for a UserID are complete. *
** CREATED - A UserID has been created, but has no FaceID(s) associated with it. *
** UPDATING - A UserID is being updated and there are current associations or disassociations of FaceID(s) taking * place. *
*
* Associates one or more faces with an existing UserID. Takes an array of FaceIds. Each
* FaceId that are present in the FaceIds list is associated with the provided UserID. The
* maximum number of total FaceIds per UserID is 100.
*
* The UserMatchThreshold parameter specifies the minimum user match confidence required for the face
* to be associated with a UserID that has at least one FaceID already associated. This ensures that
* the FaceIds are associated with the right UserID. The value ranges from 0-100 and default value is
* 75.
*
* If successful, an array of AssociatedFace objects containing the associated FaceIds is
* returned. If a given face is already associated with the given UserID, it will be ignored and will
* not be returned in the response. If a given face is already associated to a different UserID, isn't
* found in the collection, doesn’t meet the UserMatchThreshold, or there are already 100 faces
* associated with the UserID, it will be returned as part of an array of
* UnsuccessfulFaceAssociations.
*
* The UserStatus reflects the status of an operation which updates a UserID representation with a list
* of given faces. The UserStatus can be:
*
* ACTIVE - All associations or disassociations of FaceID(s) for a UserID are complete. *
** CREATED - A UserID has been created, but has no FaceID(s) associated with it. *
** UPDATING - A UserID is being updated and there are current associations or disassociations of FaceID(s) taking * place. *
** Compares a face in the source input image with each of the 100 largest faces detected in the target * input image. *
** If the source image contains multiple faces, the service detects the largest face and compares it with each face * detected in the target image. *
*
* CompareFaces uses machine learning algorithms, which are probabilistic. A false negative is an incorrect
* prediction that a face in the target image has a low similarity confidence score when compared to the face in the
* source image. To reduce the probability of false negatives, we recommend that you compare the target image
* against multiple source images. If you plan to use CompareFaces to make a decision that impacts an
* individual's rights, privacy, or access to services, we recommend that you pass the result to a human for review
* and further validation before taking action.
*
* 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. *
** 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, roll, * 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. *
*
* 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 SimilarityThreshold parameter.
*
* CompareFaces 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.
*
* The QualityFilter 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 QualityFilter to set the
* quality bar by specifying LOW, MEDIUM, or HIGH. If you do not want to
* filter detected faces, specify NONE. The default value is NONE.
*
* If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the
* source and target images. Use these values to display the images with the correct image orientation.
*
* If no faces are detected in the source or target images, CompareFaces returns an
* InvalidParameterException error.
*
* This is a stateless API operation. That is, data returned by this operation doesn't persist. *
** For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:CompareFaces action.
*
* Compares a face in the source input image with each of the 100 largest faces detected in the target * input image. *
** If the source image contains multiple faces, the service detects the largest face and compares it with each face * detected in the target image. *
*
* CompareFaces uses machine learning algorithms, which are probabilistic. A false negative is an incorrect
* prediction that a face in the target image has a low similarity confidence score when compared to the face in the
* source image. To reduce the probability of false negatives, we recommend that you compare the target image
* against multiple source images. If you plan to use CompareFaces to make a decision that impacts an
* individual's rights, privacy, or access to services, we recommend that you pass the result to a human for review
* and further validation before taking action.
*
* 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. *
** 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, roll, * 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. *
*
* 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 SimilarityThreshold parameter.
*
* CompareFaces 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.
*
* The QualityFilter 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 QualityFilter to set the
* quality bar by specifying LOW, MEDIUM, or HIGH. If you do not want to
* filter detected faces, specify NONE. The default value is NONE.
*
* If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the
* source and target images. Use these values to display the images with the correct image orientation.
*
* If no faces are detected in the source or target images, CompareFaces returns an
* InvalidParameterException error.
*
* This is a stateless API operation. That is, data returned by this operation doesn't persist. *
** For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:CompareFaces action.
*
* Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The * source and destination projects can be in different AWS accounts but must be in the same AWS Region. You can't * copy a model to another AWS service. *
** To copy a model version to a different AWS account, you need to create a resource-based policy known as a * project policy. You attach the project policy to the source project by calling PutProjectPolicy. * The project policy gives permission to copy the model version from a trusting AWS account to a trusted account. *
** For more information creating and attaching a project policy, see Attaching a project policy (SDK) in the * Amazon Rekognition Custom Labels Developer Guide. *
** If you are copying a model version to a project in the same AWS account, you don't need to create a project * policy. *
** To copy a model, the destination project, source project, and source model version must already exist. *
*
* Copying a model version takes a while to complete. To get the current status, call DescribeProjectVersions
* and check the value of Status in the ProjectVersionDescription object. The copy operation has
* finished when the value of Status is COPYING_COMPLETED.
*
* This operation requires permissions to perform the rekognition:CopyProjectVersion action.
*
* Copies a version of an Amazon Rekognition Custom Labels model from a source project to a destination project. The * source and destination projects can be in different AWS accounts but must be in the same AWS Region. You can't * copy a model to another AWS service. *
** To copy a model version to a different AWS account, you need to create a resource-based policy known as a * project policy. You attach the project policy to the source project by calling PutProjectPolicy. * The project policy gives permission to copy the model version from a trusting AWS account to a trusted account. *
** For more information creating and attaching a project policy, see Attaching a project policy (SDK) in the * Amazon Rekognition Custom Labels Developer Guide. *
** If you are copying a model version to a project in the same AWS account, you don't need to create a project * policy. *
** To copy a model, the destination project, source project, and source model version must already exist. *
*
* Copying a model version takes a while to complete. To get the current status, call DescribeProjectVersions
* and check the value of Status in the ProjectVersionDescription object. The copy operation has
* finished when the value of Status is COPYING_COMPLETED.
*
* This operation requires permissions to perform the rekognition:CopyProjectVersion action.
*
* Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation. *
*
* For example, you might create collections, one for each of your application users. A user can then index faces
* using the IndexFaces operation and persist results in a specific collection. Then, a user can search
* the collection for faces in the user-specific container.
*
* When you create a collection, it is associated with the latest version of the face model version. *
** Collection names are case-sensitive. *
*
* This operation requires permissions to perform the rekognition:CreateCollection action. If you want
* to tag your collection, you also require permission to perform the rekognition:TagResource
* operation.
*
* Creates a collection in an AWS Region. You can add faces to the collection using the IndexFaces operation. *
*
* For example, you might create collections, one for each of your application users. A user can then index faces
* using the IndexFaces operation and persist results in a specific collection. Then, a user can search
* the collection for faces in the user-specific container.
*
* When you create a collection, it is associated with the latest version of the face model version. *
** Collection names are case-sensitive. *
*
* This operation requires permissions to perform the rekognition:CreateCollection action. If you want
* to tag your collection, you also require permission to perform the rekognition:TagResource
* operation.
*
* Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using an Amazon Sagemaker * format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset. *
*
* To create a training dataset for a project, specify train for the value of DatasetType.
* To create the test dataset for a project, specify test for the value of DatasetType.
*
* The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset. Creating a
* dataset takes a while to complete. Use DescribeDataset to check the current status. The dataset created
* successfully if the value of Status is CREATE_COMPLETE.
*
* To check if any non-terminal errors occurred, call ListDatasetEntries and check for the presence of
* errors lists in the JSON Lines.
*
* Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). Currently,
* you can't access the terminal error information.
*
* For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide. *
*
* This operation requires permissions to perform the rekognition:CreateDataset action. If you want to
* copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries
* action.
*
* Creates a new Amazon Rekognition Custom Labels dataset. You can create a dataset by using an Amazon Sagemaker * format manifest file or by copying an existing Amazon Rekognition Custom Labels dataset. *
*
* To create a training dataset for a project, specify train for the value of DatasetType.
* To create the test dataset for a project, specify test for the value of DatasetType.
*
* The response from CreateDataset is the Amazon Resource Name (ARN) for the dataset. Creating a
* dataset takes a while to complete. Use DescribeDataset to check the current status. The dataset created
* successfully if the value of Status is CREATE_COMPLETE.
*
* To check if any non-terminal errors occurred, call ListDatasetEntries and check for the presence of
* errors lists in the JSON Lines.
*
* Dataset creation fails if a terminal error occurs (Status = CREATE_FAILED). Currently,
* you can't access the terminal error information.
*
* For more information, see Creating dataset in the Amazon Rekognition Custom Labels Developer Guide. *
*
* This operation requires permissions to perform the rekognition:CreateDataset action. If you want to
* copy an existing dataset, you also require permission to perform the rekognition:ListDatasetEntries
* action.
*
* This API operation initiates a Face Liveness session. It returns a SessionId, which you can use to
* start streaming Face Liveness video and get the results for a Face Liveness session. You can use the
* OutputConfig option in the Settings parameter to provide an Amazon S3 bucket location. The Amazon S3
* bucket stores reference images and audit images. You can use AuditImagesLimit to limit the number of
* audit images returned. This number is between 0 and 4. By default, it is set to 0. The limit is best effort and
* based on the duration of the selfie-video.
*
* This API operation initiates a Face Liveness session. It returns a SessionId, which you can use to
* start streaming Face Liveness video and get the results for a Face Liveness session. You can use the
* OutputConfig option in the Settings parameter to provide an Amazon S3 bucket location. The Amazon S3
* bucket stores reference images and audit images. You can use AuditImagesLimit to limit the number of
* audit images returned. This number is between 0 and 4. By default, it is set to 0. The limit is best effort and
* based on the duration of the selfie-video.
*
* Creates a new Amazon Rekognition Custom Labels project. A project is a group of resources (datasets, model * versions) that you use to create and manage Amazon Rekognition Custom Labels models. *
*
* This operation requires permissions to perform the rekognition:CreateProject action.
*
* Creates a new Amazon Rekognition Custom Labels project. A project is a group of resources (datasets, model * versions) that you use to create and manage Amazon Rekognition Custom Labels models. *
*
* This operation requires permissions to perform the rekognition:CreateProject action.
*
* Creates a new version of a model and begins training. Models are managed as part of an Amazon Rekognition Custom
* Labels project. The response from CreateProjectVersion is an Amazon Resource Name (ARN) for the
* version of the model.
*
* Training uses the training and test datasets associated with the project. For more information, see Creating * training and test dataset in the Amazon Rekognition Custom Labels Developer Guide. *
*
* You can train a model in a project that doesn't have associated datasets by specifying manifest files in the
* TrainingData and TestingData fields.
*
* If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates the * datasets for you using the most recent manifest files. You can no longer train a model version for the project by * specifying manifest files. *
** Instead of training with a project without associated datasets, we recommend that you use the manifest files to * create training and test datasets for the project. *
*
* Training takes a while to complete. You can get the current status by calling DescribeProjectVersions.
* Training completed successfully if the value of the Status field is TRAINING_COMPLETED.
*
* If training fails, see Debugging a failed model training in the Amazon Rekognition Custom Labels developer * guide. *
** Once training has successfully completed, call DescribeProjectVersions to get the training results and * evaluate the model. For more information, see Improving a trained Amazon Rekognition Custom Labels model in the * Amazon Rekognition Custom Labels developers guide. *
** After evaluating the model, you start the model by calling StartProjectVersion. *
*
* This operation requires permissions to perform the rekognition:CreateProjectVersion action.
*
* Creates a new version of a model and begins training. Models are managed as part of an Amazon Rekognition Custom
* Labels project. The response from CreateProjectVersion is an Amazon Resource Name (ARN) for the
* version of the model.
*
* Training uses the training and test datasets associated with the project. For more information, see Creating * training and test dataset in the Amazon Rekognition Custom Labels Developer Guide. *
*
* You can train a model in a project that doesn't have associated datasets by specifying manifest files in the
* TrainingData and TestingData fields.
*
* If you open the console after training a model with manifest files, Amazon Rekognition Custom Labels creates the * datasets for you using the most recent manifest files. You can no longer train a model version for the project by * specifying manifest files. *
** Instead of training with a project without associated datasets, we recommend that you use the manifest files to * create training and test datasets for the project. *
*
* Training takes a while to complete. You can get the current status by calling DescribeProjectVersions.
* Training completed successfully if the value of the Status field is TRAINING_COMPLETED.
*
* If training fails, see Debugging a failed model training in the Amazon Rekognition Custom Labels developer * guide. *
** Once training has successfully completed, call DescribeProjectVersions to get the training results and * evaluate the model. For more information, see Improving a trained Amazon Rekognition Custom Labels model in the * Amazon Rekognition Custom Labels developers guide. *
** After evaluating the model, you start the model by calling StartProjectVersion. *
*
* This operation requires permissions to perform the rekognition:CreateProjectVersion action.
*
* Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels * in a streaming video. *
** Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. There are two different * settings for stream processors in Amazon Rekognition: detecting faces and detecting labels. *
*
* If you are creating a stream processor for detecting faces, you provide as input a Kinesis video stream (
* Input) and a Kinesis data stream (Output) stream for receiving the output. You must use
* the FaceSearch option in Settings, specifying the collection that contains the faces
* you want to recognize. After you have finished analyzing a streaming video, use StopStreamProcessor to
* stop processing.
*
* If you are creating a stream processor to detect labels, you provide as input a Kinesis video stream (
* Input), Amazon S3 bucket information (Output), and an Amazon SNS topic ARN (
* NotificationChannel). You can also provide a KMS key ID to encrypt the data sent to your Amazon S3
* bucket. You specify what you want to detect by using the ConnectedHome option in settings, and
* selecting one of the following: PERSON, PET, PACKAGE, ALL You
* can also specify where in the frame you want Amazon Rekognition to monitor with RegionsOfInterest.
* When you run the StartStreamProcessor operation on a label detection stream processor, you input start and
* stop information to determine the length of the processing time.
*
* Use Name to assign an identifier for the stream processor. You use Name to manage the
* stream processor. For example, you can start processing the source video by calling StartStreamProcessor
* with the Name field.
*
* This operation requires permissions to perform the rekognition:CreateStreamProcessor action. If you
* want to tag your stream processor, you also require permission to perform the
* rekognition:TagResource operation.
*
* Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels * in a streaming video. *
** Amazon Rekognition Video is a consumer of live video from Amazon Kinesis Video Streams. There are two different * settings for stream processors in Amazon Rekognition: detecting faces and detecting labels. *
*
* If you are creating a stream processor for detecting faces, you provide as input a Kinesis video stream (
* Input) and a Kinesis data stream (Output) stream for receiving the output. You must use
* the FaceSearch option in Settings, specifying the collection that contains the faces
* you want to recognize. After you have finished analyzing a streaming video, use StopStreamProcessor to
* stop processing.
*
* If you are creating a stream processor to detect labels, you provide as input a Kinesis video stream (
* Input), Amazon S3 bucket information (Output), and an Amazon SNS topic ARN (
* NotificationChannel). You can also provide a KMS key ID to encrypt the data sent to your Amazon S3
* bucket. You specify what you want to detect by using the ConnectedHome option in settings, and
* selecting one of the following: PERSON, PET, PACKAGE, ALL You
* can also specify where in the frame you want Amazon Rekognition to monitor with RegionsOfInterest.
* When you run the StartStreamProcessor operation on a label detection stream processor, you input start and
* stop information to determine the length of the processing time.
*
* Use Name to assign an identifier for the stream processor. You use Name to manage the
* stream processor. For example, you can start processing the source video by calling StartStreamProcessor
* with the Name field.
*
* This operation requires permissions to perform the rekognition:CreateStreamProcessor action. If you
* want to tag your stream processor, you also require permission to perform the
* rekognition:TagResource operation.
*
* Creates a new User within a collection specified by CollectionId. Takes UserId as a
* parameter, which is a user provided ID which should be unique within the collection. The provided
* UserId will alias the system generated UUID to make the UserId more user friendly.
*
* Uses a ClientToken, an idempotency token that ensures a call to CreateUser completes
* only once. If the value is not supplied, the AWS SDK generates an idempotency token for the requests. This
* prevents retries after a network error results from making multiple CreateUser calls.
*
* Creates a new User within a collection specified by CollectionId. Takes UserId as a
* parameter, which is a user provided ID which should be unique within the collection. The provided
* UserId will alias the system generated UUID to make the UserId more user friendly.
*
* Uses a ClientToken, an idempotency token that ensures a call to CreateUser completes
* only once. If the value is not supplied, the AWS SDK generates an idempotency token for the requests. This
* prevents retries after a network error results from making multiple CreateUser calls.
*
* Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, * see Deleting a * collection. *
*
* This operation requires permissions to perform the rekognition:DeleteCollection action.
*
* Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, * see Deleting a * collection. *
*
* This operation requires permissions to perform the rekognition:DeleteCollection action.
*
* Deletes an existing Amazon Rekognition Custom Labels dataset. Deleting a dataset might take while. Use
* DescribeDataset to check the current status. The dataset is still deleting if the value of
* Status is DELETE_IN_PROGRESS. If you try to access the dataset after it is deleted, you
* get a ResourceNotFoundException exception.
*
* You can't delete a dataset while it is creating (Status = CREATE_IN_PROGRESS) or if the
* dataset is updating (Status = UPDATE_IN_PROGRESS).
*
* This operation requires permissions to perform the rekognition:DeleteDataset action.
*
* Deletes an existing Amazon Rekognition Custom Labels dataset. Deleting a dataset might take while. Use
* DescribeDataset to check the current status. The dataset is still deleting if the value of
* Status is DELETE_IN_PROGRESS. If you try to access the dataset after it is deleted, you
* get a ResourceNotFoundException exception.
*
* You can't delete a dataset while it is creating (Status = CREATE_IN_PROGRESS) or if the
* dataset is updating (Status = UPDATE_IN_PROGRESS).
*
* This operation requires permissions to perform the rekognition:DeleteDataset action.
*
* Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the * collection. *
*
* This operation requires permissions to perform the rekognition:DeleteFaces action.
*
* Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the * collection. *
*
* This operation requires permissions to perform the rekognition:DeleteFaces action.
*
* 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 DeleteProjectVersion. *
*
* DeleteProject is an asynchronous operation. To check if the project is deleted, call
* DescribeProjects. The project is deleted when the project no longer appears in the response. Be aware that
* deleting a given project will also delete any ProjectPolicies associated with that project.
*
* This operation requires permissions to perform the rekognition:DeleteProject action.
*
* 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 DeleteProjectVersion. *
*
* DeleteProject is an asynchronous operation. To check if the project is deleted, call
* DescribeProjects. The project is deleted when the project no longer appears in the response. Be aware that
* deleting a given project will also delete any ProjectPolicies associated with that project.
*
* This operation requires permissions to perform the rekognition:DeleteProject action.
*
* Deletes an existing project policy. *
** To get a list of project policies attached to a project, call ListProjectPolicies. To attach a project * policy to a project, call PutProjectPolicy. *
*
* This operation requires permissions to perform the rekognition:DeleteProjectPolicy action.
*
* Deletes an existing project policy. *
** To get a list of project policies attached to a project, call ListProjectPolicies. To attach a project * policy to a project, call PutProjectPolicy. *
*
* This operation requires permissions to perform the rekognition:DeleteProjectPolicy action.
*
* Deletes an Amazon Rekognition Custom Labels model. *
*
* You can't delete a model if it is running or if it is training. To check the status of a model, use the
* Status field returned from DescribeProjectVersions. To stop a running model call
* StopProjectVersion. If the model is training, wait until it finishes.
*
* This operation requires permissions to perform the rekognition:DeleteProjectVersion action.
*
* Deletes an Amazon Rekognition Custom Labels model. *
*
* You can't delete a model if it is running or if it is training. To check the status of a model, use the
* Status field returned from DescribeProjectVersions. To stop a running model call
* StopProjectVersion. If the model is training, wait until it finishes.
*
* This operation requires permissions to perform the rekognition:DeleteProjectVersion action.
*
* Deletes the stream processor identified by Name. You assign the value for Name when you
* create the stream processor with CreateStreamProcessor. You might not be able to use the same name for a
* stream processor for a few seconds after calling DeleteStreamProcessor.
*
* Deletes the stream processor identified by Name. You assign the value for Name when you
* create the stream processor with CreateStreamProcessor. You might not be able to use the same name for a
* stream processor for a few seconds after calling DeleteStreamProcessor.
*
* Deletes the specified UserID within the collection. Faces that are associated with the UserID are disassociated
* from the UserID before deleting the specified UserID. If the specified Collection or
* UserID is already deleted or not found, a ResourceNotFoundException will be thrown. If
* the action is successful with a 200 response, an empty HTTP body is returned.
*
* Deletes the specified UserID within the collection. Faces that are associated with the UserID are disassociated
* from the UserID before deleting the specified UserID. If the specified Collection or
* UserID is already deleted or not found, a ResourceNotFoundException will be thrown. If
* the action is successful with a 200 response, an empty HTTP body is returned.
*
* Describes the specified collection. You can use DescribeCollection 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.
*
* For more information, see Describing a Collection in the Amazon Rekognition Developer Guide. *
* * @param describeCollectionRequest * @return A Java Future containing the result of the DescribeCollection operation returned by the service. * @sample AmazonRekognitionAsync.DescribeCollection */ java.util.concurrent.Future
* Describes the specified collection. You can use DescribeCollection 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.
*
* For more information, see Describing a Collection in the Amazon Rekognition Developer Guide. *
* * @param describeCollectionRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the DescribeCollection operation returned by the service. * @sample AmazonRekognitionAsyncHandler.DescribeCollection */ java.util.concurrent.Future* Describes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a * dataset and statistics about the images and labels in a dataset. *
*
* This operation requires permissions to perform the rekognition:DescribeDataset action.
*
* Describes an Amazon Rekognition Custom Labels dataset. You can get information such as the current status of a * dataset and statistics about the images and labels in a dataset. *
*
* This operation requires permissions to perform the rekognition:DescribeDataset action.
*
* Lists and describes the versions of a model in an Amazon Rekognition Custom Labels project. You can specify up to
* 10 model versions in ProjectVersionArns. If you don't specify a value, descriptions for all model
* versions in the project are returned.
*
* This operation requires permissions to perform the rekognition:DescribeProjectVersions action.
*
* Lists and describes the versions of a model in an Amazon Rekognition Custom Labels project. You can specify up to
* 10 model versions in ProjectVersionArns. If you don't specify a value, descriptions for all model
* versions in the project are returned.
*
* This operation requires permissions to perform the rekognition:DescribeProjectVersions action.
*
* Gets information about your Amazon Rekognition Custom Labels projects. *
*
* This operation requires permissions to perform the rekognition:DescribeProjects action.
*
* Gets information about your Amazon Rekognition Custom Labels projects. *
*
* This operation requires permissions to perform the rekognition:DescribeProjects action.
*
* Provides information about a stream processor created by CreateStreamProcessor. 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. *
* * @param describeStreamProcessorRequest * @return A Java Future containing the result of the DescribeStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsync.DescribeStreamProcessor */ java.util.concurrent.Future* Provides information about a stream processor created by CreateStreamProcessor. 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. *
* * @param describeStreamProcessorRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the DescribeStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsyncHandler.DescribeStreamProcessor */ java.util.concurrent.Future* Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model. *
*
* You specify which version of a model version to use by using the ProjectVersionArn input parameter.
*
* 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. *
*
* For each object that the model version detects on an image, the API returns a (CustomLabel) object
* in an array (CustomLabels). Each CustomLabel object provides the label name (
* Name), the level of confidence that the image contains the object (Confidence), and
* object location information, if it exists, for the label on the image (Geometry).
*
* To filter labels that are returned, specify a value for MinConfidence.
* DetectCustomLabelsLabels only returns labels with a confidence that's higher than the specified
* value. The value of MinConfidence maps to the assumed threshold values created during training. For
* more information, see Assumed threshold in the Amazon Rekognition Custom Labels Developer Guide. Amazon
* Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range
* of MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence responses
* from DetectCustomLabels are also returned as a percentage. You can use MinConfidence to
* change the precision and recall or your model. For more information, see Analyzing an image in the Amazon
* Rekognition Custom Labels Developer Guide.
*
* If you don't specify a value for MinConfidence, DetectCustomLabels returns labels based
* on the assumed threshold of each label.
*
* This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectCustomLabels action.
*
* For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide. *
* * @param detectCustomLabelsRequest * @return A Java Future containing the result of the DetectCustomLabels operation returned by the service. * @sample AmazonRekognitionAsync.DetectCustomLabels */ java.util.concurrent.Future* Detects custom labels in a supplied image by using an Amazon Rekognition Custom Labels model. *
*
* You specify which version of a model version to use by using the ProjectVersionArn input parameter.
*
* 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. *
*
* For each object that the model version detects on an image, the API returns a (CustomLabel) object
* in an array (CustomLabels). Each CustomLabel object provides the label name (
* Name), the level of confidence that the image contains the object (Confidence), and
* object location information, if it exists, for the label on the image (Geometry).
*
* To filter labels that are returned, specify a value for MinConfidence.
* DetectCustomLabelsLabels only returns labels with a confidence that's higher than the specified
* value. The value of MinConfidence maps to the assumed threshold values created during training. For
* more information, see Assumed threshold in the Amazon Rekognition Custom Labels Developer Guide. Amazon
* Rekognition Custom Labels metrics expresses an assumed threshold as a floating point value between 0-1. The range
* of MinConfidence normalizes the threshold value to a percentage value (0-100). Confidence responses
* from DetectCustomLabels are also returned as a percentage. You can use MinConfidence to
* change the precision and recall or your model. For more information, see Analyzing an image in the Amazon
* Rekognition Custom Labels Developer Guide.
*
* If you don't specify a value for MinConfidence, DetectCustomLabels returns labels based
* on the assumed threshold of each label.
*
* This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectCustomLabels action.
*
* For more information, see Analyzing an image in the Amazon Rekognition Custom Labels Developer Guide. *
* * @param detectCustomLabelsRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the DetectCustomLabels operation returned by the service. * @sample AmazonRekognitionAsyncHandler.DetectCustomLabels */ java.util.concurrent.Future* Detects faces within an image that is provided as input. *
*
* DetectFaces 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), pose, presence of facial occlusion, and so on.
*
* 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. *
** 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. *
** This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectFaces action.
*
* Detects faces within an image that is provided as input. *
*
* DetectFaces 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), pose, presence of facial occlusion, and so on.
*
* 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. *
** 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. *
** This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectFaces action.
*
* 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. *
** For an example, see Analyzing images stored in an Amazon S3 bucket in the Amazon Rekognition Developer Guide. *
** 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. *
** Optional Parameters *
*
* You can specify one or both of the GENERAL_LABELS and IMAGE_PROPERTIES feature types
* when calling the DetectLabels API. Including GENERAL_LABELS will ensure the response includes the
* labels detected in the input image, while including IMAGE_PROPERTIES will ensure the response
* includes information about the image quality and color.
*
* When using GENERAL_LABELS and/or IMAGE_PROPERTIES you can provide filtering criteria to
* the Settings parameter. You can filter with sets of individual labels or with label categories. You can specify
* inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information
* on filtering see Detecting Labels in an
* Image.
*
* You can specify MinConfidence to control the confidence threshold for the labels returned. The
* default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned. The
* default and upper limit is 1000 labels.
*
* Response Elements *
** For each object, scene, and concept the API returns one or more labels. The API returns the following types of * information about labels: *
** Name - The name of the detected label. *
** Confidence - The level of confidence in the label assigned to a detected object. *
** Parents - The ancestor labels for a detected label. DetectLabels returns a hierarchical taxonomy of detected * labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle * (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where * every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as * unique labels in the response. *
** Aliases - Possible Aliases for the label. *
** Categories - The label categories that the detected label belongs to. *
** BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an * array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label * on the input image. It also includes the confidence for the accuracy of the detected bounding box. *
** The API returns the following information regarding the image, as part of the ImageProperties structure: *
** Quality - Information about the Sharpness, Brightness, and Contrast of the input image, scored between 0 to 100. * Image quality is returned for the entire image, as well as the background and the foreground. *
** Dominant Color - An array of the dominant colors in the image. *
** Foreground - Information about the sharpness, brightness, and dominant colors of the input image’s foreground. *
** Background - Information about the sharpness, brightness, and dominant colors of the input image’s background. *
** The list of returned labels will include at least one label for every detected object, along with information * about that label. In the following example, suppose the input image has a lighthouse, the sea, and a rock. The * response includes all three labels, one for each object, as well as the confidence in the label: *
*
* {Name: lighthouse, Confidence: 98.4629}
*
* {Name: rock,Confidence: 79.2097}
*
* {Name: sea,Confidence: 75.061}
*
* The list of labels can include multiple labels for the same object. For example, if the input image shows a * flower (for example, a tulip), the operation might return the following three labels. *
*
* {Name: flower,Confidence: 99.0562}
*
* {Name: plant,Confidence: 99.0562}
*
* {Name: tulip,Confidence: 99.0562}
*
* In this example, the detection algorithm more precisely identifies the flower as a tulip. *
** If the object detected is a person, the operation doesn't provide the same facial details that the * DetectFaces operation provides. *
** This is a stateless API operation that doesn't return any data. *
*
* This operation requires permissions to perform the rekognition:DetectLabels action.
*
* 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. *
** For an example, see Analyzing images stored in an Amazon S3 bucket in the Amazon Rekognition Developer Guide. *
** 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. *
** Optional Parameters *
*
* You can specify one or both of the GENERAL_LABELS and IMAGE_PROPERTIES feature types
* when calling the DetectLabels API. Including GENERAL_LABELS will ensure the response includes the
* labels detected in the input image, while including IMAGE_PROPERTIES will ensure the response
* includes information about the image quality and color.
*
* When using GENERAL_LABELS and/or IMAGE_PROPERTIES you can provide filtering criteria to
* the Settings parameter. You can filter with sets of individual labels or with label categories. You can specify
* inclusive filters, exclusive filters, or a combination of inclusive and exclusive filters. For more information
* on filtering see Detecting Labels in an
* Image.
*
* You can specify MinConfidence to control the confidence threshold for the labels returned. The
* default is 55%. You can also add the MaxLabels parameter to limit the number of labels returned. The
* default and upper limit is 1000 labels.
*
* Response Elements *
** For each object, scene, and concept the API returns one or more labels. The API returns the following types of * information about labels: *
** Name - The name of the detected label. *
** Confidence - The level of confidence in the label assigned to a detected object. *
** Parents - The ancestor labels for a detected label. DetectLabels returns a hierarchical taxonomy of detected * labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle * (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where * every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as * unique labels in the response. *
** Aliases - Possible Aliases for the label. *
** Categories - The label categories that the detected label belongs to. *
** BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an * array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label * on the input image. It also includes the confidence for the accuracy of the detected bounding box. *
** The API returns the following information regarding the image, as part of the ImageProperties structure: *
** Quality - Information about the Sharpness, Brightness, and Contrast of the input image, scored between 0 to 100. * Image quality is returned for the entire image, as well as the background and the foreground. *
** Dominant Color - An array of the dominant colors in the image. *
** Foreground - Information about the sharpness, brightness, and dominant colors of the input image’s foreground. *
** Background - Information about the sharpness, brightness, and dominant colors of the input image’s background. *
** The list of returned labels will include at least one label for every detected object, along with information * about that label. In the following example, suppose the input image has a lighthouse, the sea, and a rock. The * response includes all three labels, one for each object, as well as the confidence in the label: *
*
* {Name: lighthouse, Confidence: 98.4629}
*
* {Name: rock,Confidence: 79.2097}
*
* {Name: sea,Confidence: 75.061}
*
* The list of labels can include multiple labels for the same object. For example, if the input image shows a * flower (for example, a tulip), the operation might return the following three labels. *
*
* {Name: flower,Confidence: 99.0562}
*
* {Name: plant,Confidence: 99.0562}
*
* {Name: tulip,Confidence: 99.0562}
*
* In this example, the detection algorithm more precisely identifies the flower as a tulip. *
** If the object detected is a person, the operation doesn't provide the same facial details that the * DetectFaces operation provides. *
** This is a stateless API operation that doesn't return any data. *
*
* This operation requires permissions to perform the rekognition:DetectLabels action.
*
* Detects unsafe content in a specified JPEG or PNG format image. Use DetectModerationLabels to
* moderate images depending on your requirements. For example, you might want to filter images that contain nudity,
* but not images containing suggestive content.
*
* To filter images, use the labels returned by DetectModerationLabels to determine which types of
* content are appropriate.
*
* For information about moderation labels, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide. *
** 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. *
* * @param detectModerationLabelsRequest * @return A Java Future containing the result of the DetectModerationLabels operation returned by the service. * @sample AmazonRekognitionAsync.DetectModerationLabels */ java.util.concurrent.Future
* Detects unsafe content in a specified JPEG or PNG format image. Use DetectModerationLabels to
* moderate images depending on your requirements. For example, you might want to filter images that contain nudity,
* but not images containing suggestive content.
*
* To filter images, use the labels returned by DetectModerationLabels to determine which types of
* content are appropriate.
*
* For information about moderation labels, see Detecting Unsafe Content in the Amazon Rekognition Developer Guide. *
** 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. *
* * @param detectModerationLabelsRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the DetectModerationLabels operation returned by the service. * @sample AmazonRekognitionAsyncHandler.DetectModerationLabels */ java.util.concurrent.Future* Detects Personal Protective Equipment (PPE) worn by people detected in an image. Amazon Rekognition can detect * the following types of PPE. *
** Face cover *
** Hand cover *
** Head cover *
** You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. The * image must be either a PNG or JPG formatted file. *
*
* DetectProtectiveEquipment detects PPE worn by up to 15 persons detected in an image.
*
* For each person detected in the image the API returns an array of body parts (face, head, left-hand, right-hand). * For each body part, an array of detected items of PPE is returned, including an indicator of whether or not the * PPE covers the body part. The API returns the confidence it has in each detection (person, PPE, body part and * body part coverage). It also returns a bounding box (BoundingBox) for each detected person and each * detected item of PPE. *
*
* You can optionally request a summary of detected PPE items with the SummarizationAttributes input
* parameter. The summary provides the following information.
*
* The persons detected as wearing all of the types of PPE that you specify. *
** The persons detected as not wearing all of the types PPE that you specify. *
** The persons detected where PPE adornment could not be determined. *
** This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectProtectiveEquipment action.
*
* Detects Personal Protective Equipment (PPE) worn by people detected in an image. Amazon Rekognition can detect * the following types of PPE. *
** Face cover *
** Hand cover *
** Head cover *
** You pass the input image as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. The * image must be either a PNG or JPG formatted file. *
*
* DetectProtectiveEquipment detects PPE worn by up to 15 persons detected in an image.
*
* For each person detected in the image the API returns an array of body parts (face, head, left-hand, right-hand). * For each body part, an array of detected items of PPE is returned, including an indicator of whether or not the * PPE covers the body part. The API returns the confidence it has in each detection (person, PPE, body part and * body part coverage). It also returns a bounding box (BoundingBox) for each detected person and each * detected item of PPE. *
*
* You can optionally request a summary of detected PPE items with the SummarizationAttributes input
* parameter. The summary provides the following information.
*
* The persons detected as wearing all of the types of PPE that you specify. *
** The persons detected as not wearing all of the types PPE that you specify. *
** The persons detected where PPE adornment could not be determined. *
** This is a stateless API operation. That is, the operation does not persist any data. *
*
* This operation requires permissions to perform the rekognition:DetectProtectiveEquipment action.
*
* Detects text in the input image and converts it into machine-readable text. *
** 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. *
*
* The DetectText operation returns text in an array of TextDetection elements,
* TextDetections. Each TextDetection element provides information about a single word or
* line of text that was detected in the image.
*
* A word is one or more script characters that are not separated by spaces. DetectText can detect up
* to 100 words in an image.
*
* 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 DetectText operation returns
* multiple lines.
*
* To determine whether a TextDetection element is a line of text or a word, use the
* TextDetection object Type field.
*
* To be detected, text must be within +/- 90 degrees orientation of the horizontal axis. *
** For more information, see Detecting text in the Amazon Rekognition Developer Guide. *
* * @param detectTextRequest * @return A Java Future containing the result of the DetectText operation returned by the service. * @sample AmazonRekognitionAsync.DetectText */ java.util.concurrent.Future* Detects text in the input image and converts it into machine-readable text. *
** 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. *
*
* The DetectText operation returns text in an array of TextDetection elements,
* TextDetections. Each TextDetection element provides information about a single word or
* line of text that was detected in the image.
*
* A word is one or more script characters that are not separated by spaces. DetectText can detect up
* to 100 words in an image.
*
* 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 DetectText operation returns
* multiple lines.
*
* To determine whether a TextDetection element is a line of text or a word, use the
* TextDetection object Type field.
*
* To be detected, text must be within +/- 90 degrees orientation of the horizontal axis. *
** For more information, see Detecting text in the Amazon Rekognition Developer Guide. *
* * @param detectTextRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the DetectText operation returned by the service. * @sample AmazonRekognitionAsyncHandler.DetectText */ java.util.concurrent.Future
* Removes the association between a Face supplied in an array of FaceIds and the User. If
* the User is not present already, then a ResourceNotFound exception is thrown. If successful, an
* array of faces that are disassociated from the User is returned. If a given face is already disassociated from
* the given UserID, it will be ignored and not be returned in the response. If a given face is already associated
* with a different User or not found in the collection it will be returned as part of
* UnsuccessfulDisassociations. You can remove 1 - 100 face IDs from a user at one time.
*
* Removes the association between a Face supplied in an array of FaceIds and the User. If
* the User is not present already, then a ResourceNotFound exception is thrown. If successful, an
* array of faces that are disassociated from the User is returned. If a given face is already disassociated from
* the given UserID, it will be ignored and not be returned in the response. If a given face is already associated
* with a different User or not found in the collection it will be returned as part of
* UnsuccessfulDisassociations. You can remove 1 - 100 face IDs from a user at one time.
*
* Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a
* project. DistributeDatasetEntries moves 20% of the training dataset images to the test dataset. An
* entry is a JSON Line that describes an image.
*
* You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset. The training dataset * must contain the images that you want to split. The test dataset must be empty. The datasets must belong to the * same project. To create training and test datasets for a project, call CreateDataset. *
*
* Distributing a dataset takes a while to complete. To check the status call DescribeDataset. The
* operation is complete when the Status field for the training dataset and the test dataset is
* UPDATE_COMPLETE. If the dataset split fails, the value of Status is
* UPDATE_FAILED.
*
* This operation requires permissions to perform the rekognition:DistributeDatasetEntries action.
*
* Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a
* project. DistributeDatasetEntries moves 20% of the training dataset images to the test dataset. An
* entry is a JSON Line that describes an image.
*
* You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset. The training dataset * must contain the images that you want to split. The test dataset must be empty. The datasets must belong to the * same project. To create training and test datasets for a project, call CreateDataset. *
*
* Distributing a dataset takes a while to complete. To check the status call DescribeDataset. The
* operation is complete when the Status field for the training dataset and the test dataset is
* UPDATE_COMPLETE. If the dataset split fails, the value of Status is
* UPDATE_FAILED.
*
* This operation requires permissions to perform the rekognition:DistributeDatasetEntries action.
*
* Gets the name and additional information about a celebrity based on their 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. *
** For more information, see Getting information about a celebrity in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:GetCelebrityInfo action.
*
* Gets the name and additional information about a celebrity based on their 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. *
** For more information, see Getting information about a celebrity in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:GetCelebrityInfo action.
*
* Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by * StartCelebrityRecognition. *
*
* Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to
* StartCelebrityRecognition which returns a job identifier (JobId).
*
* 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 StartCelebrityRecognition
* . To get the results of the celebrity recognition analysis, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityDetection and pass the job
* identifier (JobId) from the initial call to StartCelebrityDetection.
*
* For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide. *
*
* GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (
* Celebrities) of CelebrityRecognition objects. Each CelebrityRecognition contains
* information about the celebrity in a CelebrityDetail object and the time, Timestamp, the
* celebrity was detected. This CelebrityDetail object stores information about the detected celebrity's face
* attributes, a face bounding box, known gender, the celebrity's name, and a confidence estimate.
*
* GetCelebrityRecognition only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The
* BoundingBox field only applies to the detected face instance. The other facial attributes listed in
* the Face object of the following response syntax are not returned. For more information, see
* FaceDetail in the Amazon Rekognition Developer Guide.
*
* By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You
* can also sort the array by celebrity by specifying the value ID in the SortBy input
* parameter.
*
* The CelebrityDetail 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 GetCelebrityInfo with the
* celebrity identifer.
*
* No information is returned for faces not recognized as celebrities. *
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in
* MaxResults, the value of NextToken in the operation response contains a pagination
* token for getting the next set of results. To get the next page of results, call
* GetCelebrityDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetCelebrityRecognition.
*
* Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by * StartCelebrityRecognition. *
*
* Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to
* StartCelebrityRecognition which returns a job identifier (JobId).
*
* 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 StartCelebrityRecognition
* . To get the results of the celebrity recognition analysis, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetCelebrityDetection and pass the job
* identifier (JobId) from the initial call to StartCelebrityDetection.
*
* For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide. *
*
* GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (
* Celebrities) of CelebrityRecognition objects. Each CelebrityRecognition contains
* information about the celebrity in a CelebrityDetail object and the time, Timestamp, the
* celebrity was detected. This CelebrityDetail object stores information about the detected celebrity's face
* attributes, a face bounding box, known gender, the celebrity's name, and a confidence estimate.
*
* GetCelebrityRecognition only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The
* BoundingBox field only applies to the detected face instance. The other facial attributes listed in
* the Face object of the following response syntax are not returned. For more information, see
* FaceDetail in the Amazon Rekognition Developer Guide.
*
* By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You
* can also sort the array by celebrity by specifying the value ID in the SortBy input
* parameter.
*
* The CelebrityDetail 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 GetCelebrityInfo with the
* celebrity identifer.
*
* No information is returned for faces not recognized as celebrities. *
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in
* MaxResults, the value of NextToken in the operation response contains a pagination
* token for getting the next set of results. To get the next page of results, call
* GetCelebrityDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetCelebrityRecognition.
*
* Gets the inappropriate, unwanted, or offensive content analysis results for a Amazon Rekognition Video analysis * started by StartContentModeration. For a list of moderation labels in Amazon Rekognition, see Using the image and video * moderation APIs. *
*
* Amazon Rekognition Video inappropriate or offensive content detection in a stored video is an asynchronous
* operation. You start analysis by calling StartContentModeration which returns a job identifier (
* JobId). When analysis finishes, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic registered in the initial call to StartContentModeration. To get
* the results of the content analysis, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. If so, call GetContentModeration and pass the job identifier (
* JobId) from the initial call to StartContentModeration.
*
* For more information, see Working with Stored Videos in the Amazon Rekognition Devlopers Guide. *
*
* GetContentModeration returns detected inappropriate, unwanted, or offensive content moderation
* labels, and the time they are detected, in an array, ModerationLabels, of
* ContentModerationDetection objects.
*
* 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 NAME for the SortBy input
* parameter.
*
* Since video analysis can return a large number of results, use the MaxResults parameter to limit the
* number of labels returned in a single call to GetContentModeration. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetContentModeration and populate the NextToken request parameter with the value of
* NextToken returned from the previous call to GetContentModeration.
*
* For more information, see moderating content in the Amazon Rekognition Developer Guide. *
* * @param getContentModerationRequest * @return A Java Future containing the result of the GetContentModeration operation returned by the service. * @sample AmazonRekognitionAsync.GetContentModeration */ java.util.concurrent.Future* Gets the inappropriate, unwanted, or offensive content analysis results for a Amazon Rekognition Video analysis * started by StartContentModeration. For a list of moderation labels in Amazon Rekognition, see Using the image and video * moderation APIs. *
*
* Amazon Rekognition Video inappropriate or offensive content detection in a stored video is an asynchronous
* operation. You start analysis by calling StartContentModeration which returns a job identifier (
* JobId). When analysis finishes, Amazon Rekognition Video publishes a completion status to the Amazon
* Simple Notification Service topic registered in the initial call to StartContentModeration. To get
* the results of the content analysis, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. If so, call GetContentModeration and pass the job identifier (
* JobId) from the initial call to StartContentModeration.
*
* For more information, see Working with Stored Videos in the Amazon Rekognition Devlopers Guide. *
*
* GetContentModeration returns detected inappropriate, unwanted, or offensive content moderation
* labels, and the time they are detected, in an array, ModerationLabels, of
* ContentModerationDetection objects.
*
* 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 NAME for the SortBy input
* parameter.
*
* Since video analysis can return a large number of results, use the MaxResults parameter to limit the
* number of labels returned in a single call to GetContentModeration. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetContentModeration and populate the NextToken request parameter with the value of
* NextToken returned from the previous call to GetContentModeration.
*
* For more information, see moderating content in the Amazon Rekognition Developer Guide. *
* * @param getContentModerationRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the GetContentModeration operation returned by the service. * @sample AmazonRekognitionAsyncHandler.GetContentModeration */ java.util.concurrent.Future* Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection. *
*
* Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling
* StartFaceDetection which returns a job identifier (JobId). 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 StartFaceDetection. To get the results of the face detection
* operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so,
* call GetFaceDetection and pass the job identifier (JobId) from the initial call to
* StartFaceDetection.
*
* GetFaceDetection returns an array of detected faces (Faces) sorted by the time the
* faces were detected.
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in
* MaxResults, the value of NextToken in the operation response contains a pagination
* token for getting the next set of results. To get the next page of results, call GetFaceDetection
* and populate the NextToken request parameter with the token value returned from the previous call to
* GetFaceDetection.
*
* Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection. *
*
* Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling
* StartFaceDetection which returns a job identifier (JobId). 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 StartFaceDetection. To get the results of the face detection
* operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. If so,
* call GetFaceDetection and pass the job identifier (JobId) from the initial call to
* StartFaceDetection.
*
* GetFaceDetection returns an array of detected faces (Faces) sorted by the time the
* faces were detected.
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in
* MaxResults, the value of NextToken in the operation response contains a pagination
* token for getting the next set of results. To get the next page of results, call GetFaceDetection
* and populate the NextToken request parameter with the token value returned from the previous call to
* GetFaceDetection.
*
* Retrieves the results of a specific Face Liveness session. It requires the sessionId as input, which
* was created using CreateFaceLivenessSession. Returns the corresponding Face Liveness confidence
* score, a reference image that includes a face bounding box, and audit images that also contain face bounding
* boxes. The Face Liveness confidence score ranges from 0 to 100. The reference image can optionally be returned.
*
* Retrieves the results of a specific Face Liveness session. It requires the sessionId as input, which
* was created using CreateFaceLivenessSession. Returns the corresponding Face Liveness confidence
* score, a reference image that includes a face bounding box, and audit images that also contain face bounding
* boxes. The Face Liveness confidence score ranges from 0 to 100. The reference image can optionally be returned.
*
* Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch. 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. *
*
* Face search in a video is an asynchronous operation. You start face search by calling to StartFaceSearch
* which returns a job identifier (JobId). 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
* StartFaceSearch. To get the search results, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (
* JobId) from the initial call to StartFaceSearch.
*
* For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide. *
*
* The search results are retured in an array, Persons, of PersonMatch objects. Each
* PersonMatch 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.
*
* GetFaceSearch only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The other facial
* attributes listed in the Face object of the following response syntax are not returned. For more
* information, see FaceDetail in the Amazon Rekognition Developer Guide.
*
* By default, the Persons 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 INDEX for the SORTBY
* input parameter.
*
* Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch. 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. *
*
* Face search in a video is an asynchronous operation. You start face search by calling to StartFaceSearch
* which returns a job identifier (JobId). 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
* StartFaceSearch. To get the search results, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (
* JobId) from the initial call to StartFaceSearch.
*
* For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide. *
*
* The search results are retured in an array, Persons, of PersonMatch objects. Each
* PersonMatch 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.
*
* GetFaceSearch only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The other facial
* attributes listed in the Face object of the following response syntax are not returned. For more
* information, see FaceDetail in the Amazon Rekognition Developer Guide.
*
* By default, the Persons 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 INDEX for the SORTBY
* input parameter.
*
* Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection. *
*
* The label detection operation is started by a call to StartLabelDetection which returns a job identifier (
* JobId). 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
* StartlabelDetection.
*
* To get the results of the label detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (
* JobId) from the initial call to StartLabelDetection.
*
* GetLabelDetection returns an array of detected labels (Labels) sorted by the time the
* labels were detected. You can also sort by the label name by specifying NAME for the
* SortBy input parameter. If there is no NAME specified, the default sort is by
* timestamp.
*
* You can select how results are aggregated by using the AggregateBy input parameter. The default
* aggregation method is TIMESTAMPS. You can also aggregate by SEGMENTS, which aggregates
* all instances of labels detected in a given segment.
*
* The returned Labels array may include the following attributes: *
** Name - The name of the detected label. *
** Confidence - The level of confidence in the label assigned to a detected object. *
** Parents - The ancestor labels for a detected label. GetLabelDetection returns a hierarchical taxonomy of detected * labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle * (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where * every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as * unique labels in the response. *
** Aliases - Possible Aliases for the label. *
** Categories - The label categories that the detected label belongs to. *
** BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an * array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label * on the input image. It also includes the confidence for the accuracy of the detected bounding box. *
*
* Timestamp - Time, in milliseconds from the start of the video, that the label was detected. For aggregation by
* SEGMENTS, the StartTimestampMillis, EndTimestampMillis, and
* DurationMillis structures are what define a segment. Although the “Timestamp” structure is still
* returned with each label, its value is set to be the same as StartTimestampMillis.
*
* Timestamp and Bounding box information are returned for detected Instances, only if aggregation is done by
* TIMESTAMPS. If aggregating by SEGMENTS, information about detected instances isn’t
* returned.
*
* The version of the label model used for the detection is also returned. *
*
* Note DominantColors isn't returned for Instances, although it is shown as part of
* the response in the sample seen below.
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetlabelDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetLabelDetection.
*
* Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection. *
*
* The label detection operation is started by a call to StartLabelDetection which returns a job identifier (
* JobId). 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
* StartlabelDetection.
*
* To get the results of the label detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (
* JobId) from the initial call to StartLabelDetection.
*
* GetLabelDetection returns an array of detected labels (Labels) sorted by the time the
* labels were detected. You can also sort by the label name by specifying NAME for the
* SortBy input parameter. If there is no NAME specified, the default sort is by
* timestamp.
*
* You can select how results are aggregated by using the AggregateBy input parameter. The default
* aggregation method is TIMESTAMPS. You can also aggregate by SEGMENTS, which aggregates
* all instances of labels detected in a given segment.
*
* The returned Labels array may include the following attributes: *
** Name - The name of the detected label. *
** Confidence - The level of confidence in the label assigned to a detected object. *
** Parents - The ancestor labels for a detected label. GetLabelDetection returns a hierarchical taxonomy of detected * labels. For example, a detected car might be assigned the label car. The label car has two parent labels: Vehicle * (its parent) and Transportation (its grandparent). The response includes the all ancestors for a label, where * every ancestor is a unique label. In the previous example, Car, Vehicle, and Transportation are returned as * unique labels in the response. *
** Aliases - Possible Aliases for the label. *
** Categories - The label categories that the detected label belongs to. *
** BoundingBox — Bounding boxes are described for all instances of detected common object labels, returned in an * array of Instance objects. An Instance object contains a BoundingBox object, describing the location of the label * on the input image. It also includes the confidence for the accuracy of the detected bounding box. *
*
* Timestamp - Time, in milliseconds from the start of the video, that the label was detected. For aggregation by
* SEGMENTS, the StartTimestampMillis, EndTimestampMillis, and
* DurationMillis structures are what define a segment. Although the “Timestamp” structure is still
* returned with each label, its value is set to be the same as StartTimestampMillis.
*
* Timestamp and Bounding box information are returned for detected Instances, only if aggregation is done by
* TIMESTAMPS. If aggregating by SEGMENTS, information about detected instances isn’t
* returned.
*
* The version of the label model used for the detection is also returned. *
*
* Note DominantColors isn't returned for Instances, although it is shown as part of
* the response in the sample seen below.
*
* Use MaxResults parameter to limit the number of labels returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetlabelDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetLabelDetection.
*
* Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking. *
*
* The person path tracking operation is started by a call to StartPersonTracking which returns a job
* identifier (JobId). When the operation finishes, Amazon Rekognition Video publishes a completion
* status to the Amazon Simple Notification Service topic registered in the initial call to
* StartPersonTracking.
*
* To get the results of the person path tracking operation, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (
* JobId) from the initial call to StartPersonTracking.
*
* GetPersonTracking returns an array, Persons, of tracked persons and the time(s) their
* paths were tracked in the video.
*
* GetPersonTracking only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The other facial
* attributes listed in the Face object of the following response syntax are not returned.
*
* For more information, see FaceDetail in the Amazon Rekognition Developer Guide. *
*
* 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 INDEX for the SortBy input parameter.
*
* Use the MaxResults parameter to limit the number of items returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetPersonTracking and populate the NextToken request parameter with the token value
* returned from the previous call to GetPersonTracking.
*
* Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking. *
*
* The person path tracking operation is started by a call to StartPersonTracking which returns a job
* identifier (JobId). When the operation finishes, Amazon Rekognition Video publishes a completion
* status to the Amazon Simple Notification Service topic registered in the initial call to
* StartPersonTracking.
*
* To get the results of the person path tracking operation, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (
* JobId) from the initial call to StartPersonTracking.
*
* GetPersonTracking returns an array, Persons, of tracked persons and the time(s) their
* paths were tracked in the video.
*
* GetPersonTracking only returns the default facial attributes (BoundingBox,
* Confidence, Landmarks, Pose, and Quality). The other facial
* attributes listed in the Face object of the following response syntax are not returned.
*
* For more information, see FaceDetail in the Amazon Rekognition Developer Guide. *
*
* 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 INDEX for the SortBy input parameter.
*
* Use the MaxResults parameter to limit the number of items returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetPersonTracking and populate the NextToken request parameter with the token value
* returned from the previous call to GetPersonTracking.
*
* Gets the segment detection results of a Amazon Rekognition Video analysis started by * StartSegmentDetection. *
*
* Segment detection with Amazon Rekognition Video is an asynchronous operation. You start segment detection by
* calling StartSegmentDetection which returns a job identifier (JobId). 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 StartSegmentDetection. To get the results of the
* segment detection operation, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (
* JobId) from the initial call of StartSegmentDetection.
*
* GetSegmentDetection returns detected segments in an array (Segments) of
* SegmentDetection objects. Segments is sorted by the segment types specified in the
* SegmentTypes input parameter of StartSegmentDetection. 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.
*
* Use SelectedSegmentTypes to find out the type of segment detection requested in the call to
* StartSegmentDetection.
*
* Use the MaxResults parameter to limit the number of segment detections returned. If there are more
* results than specified in MaxResults, the value of NextToken in the operation response
* contains a pagination token for getting the next set of results. To get the next page of results, call
* GetSegmentDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetSegmentDetection.
*
* For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide. *
* * @param getSegmentDetectionRequest * @return A Java Future containing the result of the GetSegmentDetection operation returned by the service. * @sample AmazonRekognitionAsync.GetSegmentDetection */ java.util.concurrent.Future* Gets the segment detection results of a Amazon Rekognition Video analysis started by * StartSegmentDetection. *
*
* Segment detection with Amazon Rekognition Video is an asynchronous operation. You start segment detection by
* calling StartSegmentDetection which returns a job identifier (JobId). 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 StartSegmentDetection. To get the results of the
* segment detection operation, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (
* JobId) from the initial call of StartSegmentDetection.
*
* GetSegmentDetection returns detected segments in an array (Segments) of
* SegmentDetection objects. Segments is sorted by the segment types specified in the
* SegmentTypes input parameter of StartSegmentDetection. 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.
*
* Use SelectedSegmentTypes to find out the type of segment detection requested in the call to
* StartSegmentDetection.
*
* Use the MaxResults parameter to limit the number of segment detections returned. If there are more
* results than specified in MaxResults, the value of NextToken in the operation response
* contains a pagination token for getting the next set of results. To get the next page of results, call
* GetSegmentDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetSegmentDetection.
*
* For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide. *
* * @param getSegmentDetectionRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the GetSegmentDetection operation returned by the service. * @sample AmazonRekognitionAsyncHandler.GetSegmentDetection */ java.util.concurrent.Future* Gets the text detection results of a Amazon Rekognition Video analysis started by StartTextDetection. *
*
* Text detection with Amazon Rekognition Video is an asynchronous operation. You start text detection by calling
* StartTextDetection which returns a job identifier (JobId) 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 StartTextDetection. To get the results of the text detection
* operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so,
* call GetTextDetection and pass the job identifier (JobId) from the initial call of
* StartLabelDetection.
*
* GetTextDetection returns an array of detected text (TextDetections) sorted by the time
* the text was detected, up to 50 words per frame of video.
*
* 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. *
*
* Use MaxResults parameter to limit the number of text detections returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetTextDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetTextDetection.
*
* Gets the text detection results of a Amazon Rekognition Video analysis started by StartTextDetection. *
*
* Text detection with Amazon Rekognition Video is an asynchronous operation. You start text detection by calling
* StartTextDetection which returns a job identifier (JobId) 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 StartTextDetection. To get the results of the text detection
* operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED. if so,
* call GetTextDetection and pass the job identifier (JobId) from the initial call of
* StartLabelDetection.
*
* GetTextDetection returns an array of detected text (TextDetections) sorted by the time
* the text was detected, up to 50 words per frame of video.
*
* 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. *
*
* Use MaxResults parameter to limit the number of text detections returned. If there are more results than
* specified in MaxResults, the value of NextToken in the operation response contains a
* pagination token for getting the next set of results. To get the next page of results, call
* GetTextDetection and populate the NextToken request parameter with the token value
* returned from the previous call to GetTextDetection.
*
* Detects faces in the input image and adds them to the specified collection. *
** 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 SearchFaces and SearchFacesByImage operations. *
** For more information, see Adding faces to a collection in the Amazon Rekognition Developer Guide. *
** To get the number of faces in a collection, call DescribeCollection. *
*
* If you're using version 1.0 of the face detection model, IndexFaces 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.
*
* If you're using version 4 or later of the face model, image orientation information is not returned in the
* OrientationCorrection field.
*
* To determine which version of the model you're using, call DescribeCollection and supply the collection
* ID. You can also get the model version from the value of FaceModelVersion in the response from
* IndexFaces
*
* For more information, see Model Versioning in the Amazon Rekognition Developer Guide. *
*
* If you provide the optional ExternalImageId for the input image you provided, Amazon Rekognition
* associates this ID with all faces that it detects. When you call the ListFaces 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.
*
* You can specify the maximum number of faces to index with the MaxFaces 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.
*
* The QualityFilter 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, IndexFaces
* chooses the quality bar that's used to filter faces. You can also explicitly choose the quality bar. Use
* QualityFilter, to set the quality bar by specifying LOW, MEDIUM, or
* HIGH. If you do not want to filter detected faces, specify NONE.
*
* 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 DescribeCollection. *
*
* Information about faces detected in an image, but not indexed, is returned in an array of UnindexedFace
* objects, UnindexedFaces. Faces aren't indexed for reasons such as:
*
* The number of faces detected exceeds the value of the MaxFaces request parameter.
*
* The face is too small compared to the image dimensions. *
** The face is too blurry. *
** The image is too dark. *
** The face has an extreme pose. *
** The face doesn’t have enough detail to be suitable for face search. *
*
* In response, the IndexFaces operation returns an array of metadata for all detected faces,
* FaceRecords. This includes:
*
* The bounding box, BoundingBox, of the detected face.
*
* A confidence value, Confidence, which indicates the confidence that the bounding box contains a
* face.
*
* A face ID, FaceId, assigned by the service for each face that's detected and stored.
*
* An image ID, ImageId, assigned by the service for the input image.
*
* If you request ALL or specific facial attributes (e.g., FACE_OCCLUDED) by using the
* detectionAttributes parameter, Amazon Rekognition returns detailed facial attributes, such as facial landmarks
* (for example, location of eye and mouth), facial occlusion, and other facial attributes.
*
* If you provide the same image, specify the same collection, and use the same external ID in the
* IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata.
*
* 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. *
*
* This operation requires permissions to perform the rekognition:IndexFaces action.
*
* Detects faces in the input image and adds them to the specified collection. *
** 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 SearchFaces and SearchFacesByImage operations. *
** For more information, see Adding faces to a collection in the Amazon Rekognition Developer Guide. *
** To get the number of faces in a collection, call DescribeCollection. *
*
* If you're using version 1.0 of the face detection model, IndexFaces 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.
*
* If you're using version 4 or later of the face model, image orientation information is not returned in the
* OrientationCorrection field.
*
* To determine which version of the model you're using, call DescribeCollection and supply the collection
* ID. You can also get the model version from the value of FaceModelVersion in the response from
* IndexFaces
*
* For more information, see Model Versioning in the Amazon Rekognition Developer Guide. *
*
* If you provide the optional ExternalImageId for the input image you provided, Amazon Rekognition
* associates this ID with all faces that it detects. When you call the ListFaces 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.
*
* You can specify the maximum number of faces to index with the MaxFaces 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.
*
* The QualityFilter 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, IndexFaces
* chooses the quality bar that's used to filter faces. You can also explicitly choose the quality bar. Use
* QualityFilter, to set the quality bar by specifying LOW, MEDIUM, or
* HIGH. If you do not want to filter detected faces, specify NONE.
*
* 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 DescribeCollection. *
*
* Information about faces detected in an image, but not indexed, is returned in an array of UnindexedFace
* objects, UnindexedFaces. Faces aren't indexed for reasons such as:
*
* The number of faces detected exceeds the value of the MaxFaces request parameter.
*
* The face is too small compared to the image dimensions. *
** The face is too blurry. *
** The image is too dark. *
** The face has an extreme pose. *
** The face doesn’t have enough detail to be suitable for face search. *
*
* In response, the IndexFaces operation returns an array of metadata for all detected faces,
* FaceRecords. This includes:
*
* The bounding box, BoundingBox, of the detected face.
*
* A confidence value, Confidence, which indicates the confidence that the bounding box contains a
* face.
*
* A face ID, FaceId, assigned by the service for each face that's detected and stored.
*
* An image ID, ImageId, assigned by the service for the input image.
*
* If you request ALL or specific facial attributes (e.g., FACE_OCCLUDED) by using the
* detectionAttributes parameter, Amazon Rekognition returns detailed facial attributes, such as facial landmarks
* (for example, location of eye and mouth), facial occlusion, and other facial attributes.
*
* If you provide the same image, specify the same collection, and use the same external ID in the
* IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata.
*
* 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. *
*
* This operation requires permissions to perform the rekognition:IndexFaces action.
*
* Returns list of collection IDs in your account. If the result is truncated, the response also provides a
* NextToken that you can use in the subsequent request to fetch the next set of collection IDs.
*
* For an example, see Listing collections in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:ListCollections action.
*
* Returns list of collection IDs in your account. If the result is truncated, the response also provides a
* NextToken that you can use in the subsequent request to fetch the next set of collection IDs.
*
* For an example, see Listing collections in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:ListCollections action.
*
* Lists the entries (images) within a dataset. An entry is a JSON Line that contains the information for a single * image, including the image location, assigned labels, and object location bounding boxes. For more information, * see Creating a * manifest file. *
*
* JSON Lines in the response include information about non-terminal errors found in the dataset. Non terminal
* errors are reported in errors lists within each JSON Line. The same information is reported in the
* training and testing validation result manifests that Amazon Rekognition Custom Labels creates during model
* training.
*
* You can filter the response in variety of ways, such as choosing which labels to return and returning JSON Lines * created after a specific date. *
*
* This operation requires permissions to perform the rekognition:ListDatasetEntries action.
*
* Lists the entries (images) within a dataset. An entry is a JSON Line that contains the information for a single * image, including the image location, assigned labels, and object location bounding boxes. For more information, * see Creating a * manifest file. *
*
* JSON Lines in the response include information about non-terminal errors found in the dataset. Non terminal
* errors are reported in errors lists within each JSON Line. The same information is reported in the
* training and testing validation result manifests that Amazon Rekognition Custom Labels creates during model
* training.
*
* You can filter the response in variety of ways, such as choosing which labels to return and returning JSON Lines * created after a specific date. *
*
* This operation requires permissions to perform the rekognition:ListDatasetEntries action.
*
* Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more * information, see Labeling * images. *
** Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more * information, see Labeling images in the Amazon Rekognition Custom Labels Developer Guide. *
* * @param listDatasetLabelsRequest * @return A Java Future containing the result of the ListDatasetLabels operation returned by the service. * @sample AmazonRekognitionAsync.ListDatasetLabels */ java.util.concurrent.Future* Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more * information, see Labeling * images. *
** Lists the labels in a dataset. Amazon Rekognition Custom Labels uses labels to describe images. For more * information, see Labeling images in the Amazon Rekognition Custom Labels Developer Guide. *
* * @param listDatasetLabelsRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the ListDatasetLabels operation returned by the service. * @sample AmazonRekognitionAsyncHandler.ListDatasetLabels */ java.util.concurrent.Future* 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. *
*
* This operation requires permissions to perform the rekognition:ListFaces action.
*
* 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. *
*
* This operation requires permissions to perform the rekognition:ListFaces action.
*
* Gets a list of the project policies attached to a project. *
** To attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, * call DeleteProjectPolicy. *
*
* This operation requires permissions to perform the rekognition:ListProjectPolicies action.
*
* Gets a list of the project policies attached to a project. *
** To attach a project policy to a project, call PutProjectPolicy. To remove a project policy from a project, * call DeleteProjectPolicy. *
*
* This operation requires permissions to perform the rekognition:ListProjectPolicies action.
*
* Gets a list of stream processors that you have created with CreateStreamProcessor. *
* * @param listStreamProcessorsRequest * @return A Java Future containing the result of the ListStreamProcessors operation returned by the service. * @sample AmazonRekognitionAsync.ListStreamProcessors */ java.util.concurrent.Future* Gets a list of stream processors that you have created with CreateStreamProcessor. *
* * @param listStreamProcessorsRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the ListStreamProcessors operation returned by the service. * @sample AmazonRekognitionAsyncHandler.ListStreamProcessors */ java.util.concurrent.Future* Returns a list of tags in an Amazon Rekognition collection, stream processor, or Custom Labels model. *
*
* This operation requires permissions to perform the rekognition:ListTagsForResource action.
*
* Returns a list of tags in an Amazon Rekognition collection, stream processor, or Custom Labels model. *
*
* This operation requires permissions to perform the rekognition:ListTagsForResource action.
*
* Returns metadata of the User such as UserID in the specified collection. Anonymous User (to reserve
* faces without any identity) is not returned as part of this request. The results are sorted by system generated
* primary key ID. If the response is truncated, NextToken is returned in the response that can be used
* in the subsequent request to retrieve the next set of identities.
*
* Returns metadata of the User such as UserID in the specified collection. Anonymous User (to reserve
* faces without any identity) is not returned as part of this request. The results are sorted by system generated
* primary key ID. If the response is truncated, NextToken is returned in the response that can be used
* in the subsequent request to retrieve the next set of identities.
*
* Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A project * policy specifies that a trusted AWS account can copy a model version from a trusting AWS account to a project in * the trusted AWS account. To copy a model version you use the CopyProjectVersion operation. *
** For more information about the format of a project policy document, see Attaching a project policy (SDK) in the * Amazon Rekognition Custom Labels Developer Guide. *
*
* The response from PutProjectPolicy is a revision ID for the project policy. You can attach multiple
* project policies to a project. You can also update an existing project policy by specifying the policy revision
* ID of the existing policy.
*
* To remove a project policy from a project, call DeleteProjectPolicy. To get a list of project policies * attached to a project, call ListProjectPolicies. *
** You copy a model version by calling CopyProjectVersion. *
*
* This operation requires permissions to perform the rekognition:PutProjectPolicy action.
*
* Attaches a project policy to a Amazon Rekognition Custom Labels project in a trusting AWS account. A project * policy specifies that a trusted AWS account can copy a model version from a trusting AWS account to a project in * the trusted AWS account. To copy a model version you use the CopyProjectVersion operation. *
** For more information about the format of a project policy document, see Attaching a project policy (SDK) in the * Amazon Rekognition Custom Labels Developer Guide. *
*
* The response from PutProjectPolicy is a revision ID for the project policy. You can attach multiple
* project policies to a project. You can also update an existing project policy by specifying the policy revision
* ID of the existing policy.
*
* To remove a project policy from a project, call DeleteProjectPolicy. To get a list of project policies * attached to a project, call ListProjectPolicies. *
** You copy a model version by calling CopyProjectVersion. *
*
* This operation requires permissions to perform the rekognition:PutProjectPolicy action.
*
* Returns an array of celebrities recognized in the input image. For more information, see Recognizing celebrities * in the Amazon Rekognition Developer Guide. *
*
* RecognizeCelebrities returns the 64 largest faces in the image. It lists the recognized celebrities
* in the CelebrityFaces array and any unrecognized faces in the UnrecognizedFaces array.
* RecognizeCelebrities doesn't return celebrities whose faces aren't among the largest 64 faces in the
* image.
*
* For each celebrity recognized, RecognizeCelebrities returns a Celebrity object. The
* Celebrity object contains the celebrity name, ID, URL links to additional information, match
* confidence, and a ComparedFace object that you can use to locate the celebrity's face on the image.
*
* Amazon Rekognition doesn't retain information about which images a celebrity has been recognized in. Your
* application must store this information and use the Celebrity ID property as a unique identifier for
* the celebrity. If you don't store the celebrity name or additional information URLs returned by
* RecognizeCelebrities, you will need the ID to identify the celebrity in a call to the
* GetCelebrityInfo operation.
*
* 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. *
** For an example, see Recognizing celebrities in an image in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:RecognizeCelebrities operation.
*
* Returns an array of celebrities recognized in the input image. For more information, see Recognizing celebrities * in the Amazon Rekognition Developer Guide. *
*
* RecognizeCelebrities returns the 64 largest faces in the image. It lists the recognized celebrities
* in the CelebrityFaces array and any unrecognized faces in the UnrecognizedFaces array.
* RecognizeCelebrities doesn't return celebrities whose faces aren't among the largest 64 faces in the
* image.
*
* For each celebrity recognized, RecognizeCelebrities returns a Celebrity object. The
* Celebrity object contains the celebrity name, ID, URL links to additional information, match
* confidence, and a ComparedFace object that you can use to locate the celebrity's face on the image.
*
* Amazon Rekognition doesn't retain information about which images a celebrity has been recognized in. Your
* application must store this information and use the Celebrity ID property as a unique identifier for
* the celebrity. If you don't store the celebrity name or additional information URLs returned by
* RecognizeCelebrities, you will need the ID to identify the celebrity in a call to the
* GetCelebrityInfo operation.
*
* 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. *
** For an example, see Recognizing celebrities in an image in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:RecognizeCelebrities operation.
*
* 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 IndexFaces operation. The operation compares the features * of the input face with faces in the specified collection. *
*
* You can also search faces without indexing faces by using the SearchFacesByImage operation.
*
* 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 confidence value for each face match, indicating the
* confidence that the specific face matches the input face.
*
* For an example, see Searching for a face using its face ID in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:SearchFaces action.
*
* 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 IndexFaces operation. The operation compares the features * of the input face with faces in the specified collection. *
*
* You can also search faces without indexing faces by using the SearchFacesByImage operation.
*
* 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 confidence value for each face match, indicating the
* confidence that the specific face matches the input face.
*
* For an example, see Searching for a face using its face ID in the Amazon Rekognition Developer Guide. *
*
* This operation requires permissions to perform the rekognition:SearchFaces action.
*
* 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. *
** To search for all faces in an input image, you might first call the IndexFaces operation, and then use the * face IDs returned in subsequent calls to the SearchFaces operation. *
*
* You can also call the DetectFaces operation and use the bounding boxes in the response to make face
* crops, which then you can pass in to the SearchFacesByImage operation.
*
* 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. *
*
* 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 similarity 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.
*
* If no faces are detected in the input image, SearchFacesByImage returns an
* InvalidParameterException error.
*
* For an example, Searching for a Face Using an Image in the Amazon Rekognition Developer Guide. *
*
* The QualityFilter 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 QualityFilter to set the
* quality bar for filtering by specifying LOW, MEDIUM, or HIGH. If you do
* not want to filter detected faces, specify NONE. The default value is NONE.
*
* 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 DescribeCollection. *
*
* This operation requires permissions to perform the rekognition:SearchFacesByImage action.
*
* 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. *
** To search for all faces in an input image, you might first call the IndexFaces operation, and then use the * face IDs returned in subsequent calls to the SearchFaces operation. *
*
* You can also call the DetectFaces operation and use the bounding boxes in the response to make face
* crops, which then you can pass in to the SearchFacesByImage operation.
*
* 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. *
*
* 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 similarity 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.
*
* If no faces are detected in the input image, SearchFacesByImage returns an
* InvalidParameterException error.
*
* For an example, Searching for a Face Using an Image in the Amazon Rekognition Developer Guide. *
*
* The QualityFilter 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 QualityFilter to set the
* quality bar for filtering by specifying LOW, MEDIUM, or HIGH. If you do
* not want to filter detected faces, specify NONE. The default value is NONE.
*
* 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 DescribeCollection. *
*
* This operation requires permissions to perform the rekognition:SearchFacesByImage action.
*
* Searches for UserIDs within a collection based on a FaceId or UserId. This API can be
* used to find the closest UserID (with a highest similarity) to associate a face. The request must be provided
* with either FaceId or UserId. The operation returns an array of UserID that match the
* FaceId or UserId, ordered by similarity score with the highest similarity first.
*
* Searches for UserIDs within a collection based on a FaceId or UserId. This API can be
* used to find the closest UserID (with a highest similarity) to associate a face. The request must be provided
* with either FaceId or UserId. The operation returns an array of UserID that match the
* FaceId or UserId, ordered by similarity score with the highest similarity first.
*
* Searches for UserIDs using a supplied image. It first detects the largest face in the image, and then searches a * specified collection for matching UserIDs. *
** The operation returns an array of UserIDs that match the face in the supplied image, ordered by similarity score * with the highest similarity first. It also returns a bounding box for the face found in the input image. *
*
* Information about faces detected in the supplied image, but not used for the search, is returned in an array of
* UnsearchedFace objects. If no valid face is detected in the image, the response will contain an
* empty UserMatches list and no SearchedFace object.
*
* Searches for UserIDs using a supplied image. It first detects the largest face in the image, and then searches a * specified collection for matching UserIDs. *
** The operation returns an array of UserIDs that match the face in the supplied image, ordered by similarity score * with the highest similarity first. It also returns a bounding box for the face found in the input image. *
*
* Information about faces detected in the supplied image, but not used for the search, is returned in an array of
* UnsearchedFace objects. If no valid face is detected in the image, the response will contain an
* empty UserMatches list and no SearchedFace object.
*
* Starts asynchronous recognition of celebrities in a stored video. *
*
* Amazon Rekognition Video can detect celebrities in a video must be stored in an Amazon S3 bucket. Use
* Video to specify the bucket name and the filename of the video. StartCelebrityRecognition
* returns a job identifier (JobId) 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 NotificationChannel. To get the results of the
* celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. If so, call GetCelebrityRecognition and pass the job identifier (
* JobId) from the initial call to StartCelebrityRecognition.
*
* For more information, see Recognizing celebrities in the Amazon Rekognition Developer Guide. *
* * @param startCelebrityRecognitionRequest * @return A Java Future containing the result of the StartCelebrityRecognition operation returned by the service. * @sample AmazonRekognitionAsync.StartCelebrityRecognition */ java.util.concurrent.Future* Starts asynchronous recognition of celebrities in a stored video. *
*
* Amazon Rekognition Video can detect celebrities in a video must be stored in an Amazon S3 bucket. Use
* Video to specify the bucket name and the filename of the video. StartCelebrityRecognition
* returns a job identifier (JobId) 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 NotificationChannel. To get the results of the
* celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is
* SUCCEEDED. If so, call GetCelebrityRecognition and pass the job identifier (
* JobId) from the initial call to StartCelebrityRecognition.
*
* For more information, see Recognizing celebrities in the Amazon Rekognition Developer Guide. *
* * @param startCelebrityRecognitionRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the StartCelebrityRecognition operation returned by the service. * @sample AmazonRekognitionAsyncHandler.StartCelebrityRecognition */ java.util.concurrent.Future* Starts asynchronous detection of inappropriate, unwanted, or offensive content in a stored video. For a list of * moderation labels in Amazon Rekognition, see Using the image and video * moderation APIs. *
*
* Amazon Rekognition Video can moderate content in a video stored in an Amazon S3 bucket. Use Video to
* specify the bucket name and the filename of the video. StartContentModeration returns a job
* identifier (JobId) which you use to get the results of the analysis. When content analysis is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic
* that you specify in NotificationChannel.
*
* To get the results of the content analysis, first check that the status value published to the Amazon SNS topic
* is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (
* JobId) from the initial call to StartContentModeration.
*
* For more information, see Moderating content in the Amazon Rekognition Developer Guide. *
* * @param startContentModerationRequest * @return A Java Future containing the result of the StartContentModeration operation returned by the service. * @sample AmazonRekognitionAsync.StartContentModeration */ java.util.concurrent.Future* Starts asynchronous detection of inappropriate, unwanted, or offensive content in a stored video. For a list of * moderation labels in Amazon Rekognition, see Using the image and video * moderation APIs. *
*
* Amazon Rekognition Video can moderate content in a video stored in an Amazon S3 bucket. Use Video to
* specify the bucket name and the filename of the video. StartContentModeration returns a job
* identifier (JobId) which you use to get the results of the analysis. When content analysis is
* finished, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic
* that you specify in NotificationChannel.
*
* To get the results of the content analysis, first check that the status value published to the Amazon SNS topic
* is SUCCEEDED. If so, call GetContentModeration and pass the job identifier (
* JobId) from the initial call to StartContentModeration.
*
* For more information, see Moderating content in the Amazon Rekognition Developer Guide. *
* * @param startContentModerationRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the StartContentModeration operation returned by the service. * @sample AmazonRekognitionAsyncHandler.StartContentModeration */ java.util.concurrent.Future* Starts asynchronous detection of faces in a stored video. *
*
* Amazon Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use Video to specify
* the bucket name and the filename of the video. StartFaceDetection returns a job identifier (
* JobId) 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 NotificationChannel. To get the results of the face detection operation, first check that the
* status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and
* pass the job identifier (JobId) from the initial call to StartFaceDetection.
*
* For more information, see Detecting faces in a stored video in the Amazon Rekognition Developer Guide. *
* * @param startFaceDetectionRequest * @return A Java Future containing the result of the StartFaceDetection operation returned by the service. * @sample AmazonRekognitionAsync.StartFaceDetection */ java.util.concurrent.Future* Starts asynchronous detection of faces in a stored video. *
*
* Amazon Rekognition Video can detect faces in a video stored in an Amazon S3 bucket. Use Video to specify
* the bucket name and the filename of the video. StartFaceDetection returns a job identifier (
* JobId) 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 NotificationChannel. To get the results of the face detection operation, first check that the
* status value published to the Amazon SNS topic is SUCCEEDED. If so, call GetFaceDetection and
* pass the job identifier (JobId) from the initial call to StartFaceDetection.
*
* For more information, see Detecting faces in a stored video in the Amazon Rekognition Developer Guide. *
* * @param startFaceDetectionRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the StartFaceDetection operation returned by the service. * @sample AmazonRekognitionAsyncHandler.StartFaceDetection */ java.util.concurrent.Future* Starts the asynchronous search for faces in a collection that match the faces of persons detected in a stored * video. *
*
* The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of
* the video. StartFaceSearch returns a job identifier (JobId) 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
* NotificationChannel. To get the search results, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (
* JobId) from the initial call to StartFaceSearch. For more information, see Searching stored
* videos for faces.
*
* Starts the asynchronous search for faces in a collection that match the faces of persons detected in a stored * video. *
*
* The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of
* the video. StartFaceSearch returns a job identifier (JobId) 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
* NotificationChannel. To get the search results, first check that the status value published to the
* Amazon SNS topic is SUCCEEDED. If so, call GetFaceSearch and pass the job identifier (
* JobId) from the initial call to StartFaceSearch. For more information, see Searching stored
* videos for faces.
*
* Starts asynchronous detection of labels in a stored video. *
** 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. *
*
* The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of
* the video. StartLabelDetection returns a job identifier (JobId) 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 NotificationChannel.
*
* To get the results of the label detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (
* JobId) from the initial call to StartLabelDetection.
*
* Optional Parameters *
*
* StartLabelDetection has the GENERAL_LABELS Feature applied by default. This feature
* allows you to provide filtering criteria to the Settings parameter. You can filter with sets of
* individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a
* combination of inclusive and exclusive filters. For more information on filtering, see Detecting labels in a
* video.
*
* You can specify MinConfidence to control the confidence threshold for the labels returned. The
* default is 50.
*
* Starts asynchronous detection of labels in a stored video. *
** 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. *
*
* The video must be stored in an Amazon S3 bucket. Use Video to specify the bucket name and the filename of
* the video. StartLabelDetection returns a job identifier (JobId) 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 NotificationChannel.
*
* To get the results of the label detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetLabelDetection and pass the job identifier (
* JobId) from the initial call to StartLabelDetection.
*
* Optional Parameters *
*
* StartLabelDetection has the GENERAL_LABELS Feature applied by default. This feature
* allows you to provide filtering criteria to the Settings parameter. You can filter with sets of
* individual labels or with label categories. You can specify inclusive filters, exclusive filters, or a
* combination of inclusive and exclusive filters. For more information on filtering, see Detecting labels in a
* video.
*
* You can specify MinConfidence to control the confidence threshold for the labels returned. The
* default is 50.
*
* Starts the asynchronous tracking of a person's path in a stored video. *
*
* Amazon Rekognition Video can track the path of people in a video stored in an Amazon S3 bucket. Use Video
* to specify the bucket name and the filename of the video. StartPersonTracking returns a job
* identifier (JobId) 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 NotificationChannel.
*
* To get the results of the person detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (
* JobId) from the initial call to StartPersonTracking.
*
* Starts the asynchronous tracking of a person's path in a stored video. *
*
* Amazon Rekognition Video can track the path of people in a video stored in an Amazon S3 bucket. Use Video
* to specify the bucket name and the filename of the video. StartPersonTracking returns a job
* identifier (JobId) 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 NotificationChannel.
*
* To get the results of the person detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. If so, call GetPersonTracking and pass the job identifier (
* JobId) from the initial call to StartPersonTracking.
*
* 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 DescribeProjectVersions. *
** Once the model is running, you can detect custom labels in new images by calling DetectCustomLabels. *
** You are charged for the amount of time that the model is running. To stop a running model, call * StopProjectVersion. *
** For more information, see Running a trained Amazon Rekognition Custom Labels model in the Amazon * Rekognition Custom Labels Guide. *
*
* This operation requires permissions to perform the rekognition:StartProjectVersion action.
*
* 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 DescribeProjectVersions. *
** Once the model is running, you can detect custom labels in new images by calling DetectCustomLabels. *
** You are charged for the amount of time that the model is running. To stop a running model, call * StopProjectVersion. *
** For more information, see Running a trained Amazon Rekognition Custom Labels model in the Amazon * Rekognition Custom Labels Guide. *
*
* This operation requires permissions to perform the rekognition:StartProjectVersion action.
*
* Starts asynchronous detection of segment detection in a stored video. *
*
* Amazon Rekognition Video can detect segments in a video stored in an Amazon S3 bucket. Use Video to
* specify the bucket name and the filename of the video. StartSegmentDetection returns a job
* identifier (JobId) 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 NotificationChannel.
*
* You can use the Filters (StartSegmentDetectionFilters) input parameter to specify the minimum
* detection confidence returned in the response. Within Filters, use ShotFilter
* (StartShotDetectionFilter) to filter detected shots. Use TechnicalCueFilter
* (StartTechnicalCueDetectionFilter) to filter technical cues.
*
* To get the results of the segment detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (
* JobId) from the initial call to StartSegmentDetection.
*
* For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide. *
* * @param startSegmentDetectionRequest * @return A Java Future containing the result of the StartSegmentDetection operation returned by the service. * @sample AmazonRekognitionAsync.StartSegmentDetection */ java.util.concurrent.Future* Starts asynchronous detection of segment detection in a stored video. *
*
* Amazon Rekognition Video can detect segments in a video stored in an Amazon S3 bucket. Use Video to
* specify the bucket name and the filename of the video. StartSegmentDetection returns a job
* identifier (JobId) 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 NotificationChannel.
*
* You can use the Filters (StartSegmentDetectionFilters) input parameter to specify the minimum
* detection confidence returned in the response. Within Filters, use ShotFilter
* (StartShotDetectionFilter) to filter detected shots. Use TechnicalCueFilter
* (StartTechnicalCueDetectionFilter) to filter technical cues.
*
* To get the results of the segment detection operation, first check that the status value published to the Amazon
* SNS topic is SUCCEEDED. if so, call GetSegmentDetection and pass the job identifier (
* JobId) from the initial call to StartSegmentDetection.
*
* For more information, see Detecting video segments in stored video in the Amazon Rekognition Developer Guide. *
* * @param startSegmentDetectionRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the StartSegmentDetection operation returned by the service. * @sample AmazonRekognitionAsyncHandler.StartSegmentDetection */ java.util.concurrent.Future
* Starts processing a stream processor. You create a stream processor by calling CreateStreamProcessor. To
* tell StartStreamProcessor which stream processor to start, use the value of the Name
* field specified in the call to CreateStreamProcessor.
*
* If you are using a label detection stream processor to detect labels, you need to provide a
* Start selector and a Stop selector to determine the length of the stream processing
* time.
*
* Starts processing a stream processor. You create a stream processor by calling CreateStreamProcessor. To
* tell StartStreamProcessor which stream processor to start, use the value of the Name
* field specified in the call to CreateStreamProcessor.
*
* If you are using a label detection stream processor to detect labels, you need to provide a
* Start selector and a Stop selector to determine the length of the stream processing
* time.
*
* Starts asynchronous detection of text in a stored video. *
*
* Amazon Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use Video to specify
* the bucket name and the filename of the video. StartTextDetection returns a job identifier (
* JobId) 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 NotificationChannel.
*
* To get the results of the text detection operation, first check that the status value published to the Amazon SNS
* topic is SUCCEEDED. if so, call GetTextDetection and pass the job identifier (
* JobId) from the initial call to StartTextDetection.
*
* Starts asynchronous detection of text in a stored video. *
*
* Amazon Rekognition Video can detect text in a video stored in an Amazon S3 bucket. Use Video to specify
* the bucket name and the filename of the video. StartTextDetection returns a job identifier (
* JobId) 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 NotificationChannel.
*
* To get the results of the text detection operation, first check that the status value published to the Amazon SNS
* topic is SUCCEEDED. if so, call GetTextDetection and pass the job identifier (
* JobId) from the initial call to StartTextDetection.
*
* Stops a running model. The operation might take a while to complete. To check the current status, call * DescribeProjectVersions. *
*
* This operation requires permissions to perform the rekognition:StopProjectVersion action.
*
* Stops a running model. The operation might take a while to complete. To check the current status, call * DescribeProjectVersions. *
*
* This operation requires permissions to perform the rekognition:StopProjectVersion action.
*
* Stops a running stream processor that was created by CreateStreamProcessor. *
* * @param stopStreamProcessorRequest * @return A Java Future containing the result of the StopStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsync.StopStreamProcessor */ java.util.concurrent.Future* Stops a running stream processor that was created by CreateStreamProcessor. *
* * @param stopStreamProcessorRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the StopStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsyncHandler.StopStreamProcessor */ java.util.concurrent.Future* Adds one or more key-value tags to an Amazon Rekognition collection, stream processor, or Custom Labels model. * For more information, see Tagging AWS * Resources. *
*
* This operation requires permissions to perform the rekognition:TagResource action.
*
* Adds one or more key-value tags to an Amazon Rekognition collection, stream processor, or Custom Labels model. * For more information, see Tagging AWS * Resources. *
*
* This operation requires permissions to perform the rekognition:TagResource action.
*
* Removes one or more tags from an Amazon Rekognition collection, stream processor, or Custom Labels model. *
*
* This operation requires permissions to perform the rekognition:UntagResource action.
*
* Removes one or more tags from an Amazon Rekognition collection, stream processor, or Custom Labels model. *
*
* This operation requires permissions to perform the rekognition:UntagResource action.
*
* Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the information * for a single image, including the image location, assigned labels, and object location bounding boxes. For more * information, see Image-Level labels in manifest files and Object localization in manifest files in the Amazon * Rekognition Custom Labels Developer Guide. *
*
* If the source-ref field in the JSON line references an existing image, the existing image in the
* dataset is updated. If source-ref field doesn't reference an existing image, the image is added as a
* new image to the dataset.
*
* You specify the changes that you want to make in the Changes input parameter. There isn't a limit to
* the number JSON Lines that you can change, but the size of Changes must be less than 5MB.
*
* UpdateDatasetEntries returns immediatly, but the dataset update might take a while to complete. Use
* DescribeDataset to check the current status. The dataset updated successfully if the value of
* Status is UPDATE_COMPLETE.
*
* To check if any non-terminal errors occured, call ListDatasetEntries and check for the presence of
* errors lists in the JSON Lines.
*
* Dataset update fails if a terminal error occurs (Status = UPDATE_FAILED). Currently,
* you can't access the terminal error information from the Amazon Rekognition Custom Labels SDK.
*
* This operation requires permissions to perform the rekognition:UpdateDatasetEntries action.
*
* Adds or updates one or more entries (images) in a dataset. An entry is a JSON Line which contains the information * for a single image, including the image location, assigned labels, and object location bounding boxes. For more * information, see Image-Level labels in manifest files and Object localization in manifest files in the Amazon * Rekognition Custom Labels Developer Guide. *
*
* If the source-ref field in the JSON line references an existing image, the existing image in the
* dataset is updated. If source-ref field doesn't reference an existing image, the image is added as a
* new image to the dataset.
*
* You specify the changes that you want to make in the Changes input parameter. There isn't a limit to
* the number JSON Lines that you can change, but the size of Changes must be less than 5MB.
*
* UpdateDatasetEntries returns immediatly, but the dataset update might take a while to complete. Use
* DescribeDataset to check the current status. The dataset updated successfully if the value of
* Status is UPDATE_COMPLETE.
*
* To check if any non-terminal errors occured, call ListDatasetEntries and check for the presence of
* errors lists in the JSON Lines.
*
* Dataset update fails if a terminal error occurs (Status = UPDATE_FAILED). Currently,
* you can't access the terminal error information from the Amazon Rekognition Custom Labels SDK.
*
* This operation requires permissions to perform the rekognition:UpdateDatasetEntries action.
*
* Allows you to update a stream processor. You can change some settings and regions of interest and delete certain * parameters. *
* * @param updateStreamProcessorRequest * @return A Java Future containing the result of the UpdateStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsync.UpdateStreamProcessor */ java.util.concurrent.Future* Allows you to update a stream processor. You can change some settings and regions of interest and delete certain * parameters. *
* * @param updateStreamProcessorRequest * @param asyncHandler * Asynchronous callback handler for events in the lifecycle of the request. Users can provide an * implementation of the callback methods in this interface to receive notification of successful or * unsuccessful completion of the operation. * @return A Java Future containing the result of the UpdateStreamProcessor operation returned by the service. * @sample AmazonRekognitionAsyncHandler.UpdateStreamProcessor */ java.util.concurrent.Future