* 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 *
** Callers can pass in just the endpoint (ex: * "rekognition.us-east-1.amazonaws.com") or a full URL, including the * protocol (ex: "https://rekognition.us-east-1.amazonaws.com"). If the * protocol is not specified here, the default protocol from this client's * {@link ClientConfiguration} will be used, which by default is HTTPS. *
* For more information on using AWS regions with the AWS SDK for Java, and * a complete list of all available endpoints for all AWS services, see: http://developer.amazonwebservices.com/connect/entry.jspa?externalID= * 3912 *
* This method is not threadsafe. An endpoint should be configured when * the client is created and before any service requests are made. Changing * it afterwards creates inevitable race conditions for any service requests * in transit or retrying. * * @param endpoint The endpoint (ex: "rekognition.us-east-1.amazonaws.com") * or a full URL, including the protocol (ex: * "https://rekognition.us-east-1.amazonaws.com") of the region * specific AWS endpoint this client will communicate with. * @throws IllegalArgumentException If any problems are detected with the * specified endpoint. */ public void setEndpoint(String endpoint) throws java.lang.IllegalArgumentException; /** * An alternative to {@link AmazonRekognition#setEndpoint(String)}, sets the * regional endpoint for this client's service calls. Callers can use this * method to control which AWS region they want to work with. *
* By default, all service endpoints in all regions use the https protocol. * To use http instead, specify it in the {@link ClientConfiguration} * supplied at construction. *
* This method is not threadsafe. A region should be configured when the * client is created and before any service requests are made. Changing it * afterwards creates inevitable race conditions for any service requests in * transit or retrying. * * @param region The region this client will communicate with. See * {@link Region#getRegion(com.amazonaws.regions.Regions)} for * accessing a given region. * @throws java.lang.IllegalArgumentException If the given region is null, * or if this service isn't available in the given region. See * {@link Region#isServiceSupported(String)} * @see Region#getRegion(com.amazonaws.regions.Regions) * @see Region#createClient(Class, * com.amazonaws.auth.AWSCredentialsProvider, ClientConfiguration) */ public void setRegion(Region region) throws java.lang.IllegalArgumentException; /** *
* 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.
*
* 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 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.
*
* 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 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.
*
* 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 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 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 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.
*
* 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 describeCollectionResult The response from the DescribeCollection * service method, as returned by Amazon Rekognition. * @throws InvalidParameterException * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws ProvisionedThroughputExceededException * @throws ResourceNotFoundException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ DescribeCollectionResult describeCollection(DescribeCollectionRequest describeCollectionRequest) throws AmazonClientException, AmazonServiceException; /** ** 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.
*
* 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 describeStreamProcessorResult The response from the * DescribeStreamProcessor service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws InvalidParameterException * @throws ResourceNotFoundException * @throws ProvisionedThroughputExceededException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ DescribeStreamProcessorResult describeStreamProcessor( DescribeStreamProcessorRequest describeStreamProcessorRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 detectCustomLabelsResult The response from the DetectCustomLabels * service method, as returned by Amazon Rekognition. * @throws ResourceNotFoundException * @throws ResourceNotReadyException * @throws InvalidS3ObjectException * @throws InvalidParameterException * @throws ImageTooLargeException * @throws LimitExceededException * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws ProvisionedThroughputExceededException * @throws InvalidImageFormatException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ DetectCustomLabelsResult detectCustomLabels(DetectCustomLabelsRequest detectCustomLabelsRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 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 detectModerationLabelsResult The response from the * DetectModerationLabels service method, as returned by Amazon * Rekognition. * @throws InvalidS3ObjectException * @throws InvalidParameterException * @throws ImageTooLargeException * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws ProvisionedThroughputExceededException * @throws InvalidImageFormatException * @throws HumanLoopQuotaExceededException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ DetectModerationLabelsResult detectModerationLabels( DetectModerationLabelsRequest detectModerationLabelsRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 detectTextResult The response from the DetectText service method, * as returned by Amazon Rekognition. * @throws InvalidS3ObjectException * @throws InvalidParameterException * @throws ImageTooLargeException * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws ProvisionedThroughputExceededException * @throws InvalidImageFormatException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ DetectTextResult detectText(DetectTextRequest detectTextRequest) throws AmazonClientException, AmazonServiceException; /** *
* 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.
*
* 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 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 getContentModerationResult The response from the * GetContentModeration service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws InvalidParameterException * @throws InvalidPaginationTokenException * @throws ProvisionedThroughputExceededException * @throws ResourceNotFoundException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ GetContentModerationResult getContentModeration( GetContentModerationRequest getContentModerationRequest) throws AmazonClientException, AmazonServiceException; /** ** 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.
*
* 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. EachPersonMatch 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 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 getSegmentDetectionResult The response from the * GetSegmentDetection service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws InvalidParameterException * @throws InvalidPaginationTokenException * @throws ProvisionedThroughputExceededException * @throws ResourceNotFoundException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ GetSegmentDetectionResult getSegmentDetection( GetSegmentDetectionRequest getSegmentDetectionRequest) throws AmazonClientException, AmazonServiceException; /** ** 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.
*
* 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 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 listDatasetLabelsResult The response from the ListDatasetLabels * service method, as returned by Amazon Rekognition. * @throws InternalServerErrorException * @throws ThrottlingException * @throws ProvisionedThroughputExceededException * @throws InvalidParameterException * @throws AccessDeniedException * @throws ResourceInUseException * @throws InvalidPaginationTokenException * @throws ResourceNotFoundException * @throws ResourceNotReadyException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ ListDatasetLabelsResult listDatasetLabels(ListDatasetLabelsRequest listDatasetLabelsRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 stream processors that you have created with * CreateStreamProcessor. *
* * @param listStreamProcessorsRequest * @return listStreamProcessorsResult The response from the * ListStreamProcessors service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws InvalidParameterException * @throws InvalidPaginationTokenException * @throws ProvisionedThroughputExceededException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ ListStreamProcessorsResult listStreamProcessors( ListStreamProcessorsRequest listStreamProcessorsRequest) throws AmazonClientException, AmazonServiceException; /** ** 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.
*
* 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.
*
* 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.
*
* 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.
*
* 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 startCelebrityRecognitionResult The response from the * StartCelebrityRecognition service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws IdempotentParameterMismatchException * @throws InvalidParameterException * @throws InvalidS3ObjectException * @throws InternalServerErrorException * @throws VideoTooLargeException * @throws ProvisionedThroughputExceededException * @throws LimitExceededException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ StartCelebrityRecognitionResult startCelebrityRecognition( StartCelebrityRecognitionRequest startCelebrityRecognitionRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 startContentModerationResult The response from the * StartContentModeration service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws IdempotentParameterMismatchException * @throws InvalidParameterException * @throws InvalidS3ObjectException * @throws InternalServerErrorException * @throws VideoTooLargeException * @throws ProvisionedThroughputExceededException * @throws LimitExceededException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ StartContentModerationResult startContentModeration( StartContentModerationRequest startContentModerationRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 startFaceDetectionResult The response from the StartFaceDetection * service method, as returned by Amazon Rekognition. * @throws AccessDeniedException * @throws IdempotentParameterMismatchException * @throws InvalidParameterException * @throws InvalidS3ObjectException * @throws InternalServerErrorException * @throws VideoTooLargeException * @throws ProvisionedThroughputExceededException * @throws LimitExceededException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ StartFaceDetectionResult startFaceDetection(StartFaceDetectionRequest startFaceDetectionRequest) throws AmazonClientException, AmazonServiceException; /** ** 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 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 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 startSegmentDetectionResult The response from the * StartSegmentDetection service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws IdempotentParameterMismatchException * @throws InvalidParameterException * @throws InvalidS3ObjectException * @throws InternalServerErrorException * @throws VideoTooLargeException * @throws ProvisionedThroughputExceededException * @throws LimitExceededException * @throws ThrottlingException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ StartSegmentDetectionResult startSegmentDetection( StartSegmentDetectionRequest startSegmentDetectionRequest) throws AmazonClientException, AmazonServiceException; /** *
* 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.
*
* 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 stopStreamProcessorResult The response from the * StopStreamProcessor service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws InvalidParameterException * @throws ResourceNotFoundException * @throws ResourceInUseException * @throws ProvisionedThroughputExceededException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ StopStreamProcessorResult stopStreamProcessor( StopStreamProcessorRequest stopStreamProcessorRequest) throws AmazonClientException, AmazonServiceException; /** ** 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.
*
* 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 updateStreamProcessorResult The response from the * UpdateStreamProcessor service method, as returned by Amazon * Rekognition. * @throws AccessDeniedException * @throws InternalServerErrorException * @throws ThrottlingException * @throws InvalidParameterException * @throws ResourceNotFoundException * @throws ProvisionedThroughputExceededException * @throws ResourceInUseException * @throws AmazonClientException If any internal errors are encountered * inside the client while attempting to make the request or * handle the response. For example if a network connection is * not available. * @throws AmazonServiceException If an error response is returned by Amazon * Rekognition indicating either a problem with the data in the * request, or a server side issue. */ UpdateStreamProcessorResult updateStreamProcessor( UpdateStreamProcessorRequest updateStreamProcessorRequest) throws AmazonClientException, AmazonServiceException; /** * Shuts down this client object, releasing any resources that might be held * open. This is an optional method, and callers are not expected to call * it, but can if they want to explicitly release any open resources. Once a * client has been shutdown, it should not be used to make any more * requests. */ public void shutdown(); /** * Returns additional metadata for a previously executed successful request, * typically used for debugging issues where a service isn't acting as * expected. This data isn't considered part of the result data returned by * an operation, so it's available through this separate, diagnostic * interface. ** Response metadata is only cached for a limited period of time, so if you * need to access this extra diagnostic information for an executed request, * you should use this method to retrieve it as soon as possible after * executing a request. * * @param request The originally executed request. * @return The response metadata for the specified request, or null if none * is available. */ public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request); }