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Command Reference

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Synopsis

Calls the Amazon SageMaker Service CreateLabelingJob API operation.

Syntax

New-SMLabelingJob
-LabelingJobName <String>
-AnnotationConsolidationConfig_AnnotationConsolidationLambdaArn <String>
-AmountInUsd_Cent <Int32>
-DataAttributes_ContentClassifier <String[]>
-AmountInUsd_Dollar <Int32>
-UiConfig_HumanTaskUiArn <String>
-LabelingJobAlgorithmsConfig_InitialActiveLearningModelArn <String>
-OutputConfig_KmsKeyId <String>
-LabelAttributeName <String>
-LabelCategoryConfigS3Uri <String>
-LabelingJobAlgorithmsConfig_LabelingJobAlgorithmSpecificationArn <String>
-S3DataSource_ManifestS3Uri <String>
-HumanTaskConfig_MaxConcurrentTaskCount <Int32>
-StoppingConditions_MaxHumanLabeledObjectCount <Int32>
-StoppingConditions_MaxPercentageOfInputDatasetLabeled <Int32>
-HumanTaskConfig_NumberOfHumanWorkersPerDataObject <Int32>
-HumanTaskConfig_PreHumanTaskLambdaArn <String>
-RoleArn <String>
-OutputConfig_S3OutputPath <String>
-VpcConfig_SecurityGroupId <String[]>
-SnsDataSource_SnsTopicArn <String>
-OutputConfig_SnsTopicArn <String>
-VpcConfig_Subnet <String[]>
-Tag <Tag[]>
-HumanTaskConfig_TaskAvailabilityLifetimeInSecond <Int32>
-HumanTaskConfig_TaskDescription <String>
-HumanTaskConfig_TaskKeyword <String[]>
-HumanTaskConfig_TaskTimeLimitInSecond <Int32>
-HumanTaskConfig_TaskTitle <String>
-AmountInUsd_TenthFractionsOfACent <Int32>
-UiConfig_UiTemplateS3Uri <String>
-LabelingJobResourceConfig_VolumeKmsKeyId <String>
-HumanTaskConfig_WorkteamArn <String>
-Select <String>
-PassThru <SwitchParameter>
-Force <SwitchParameter>

Description

Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models. You can select your workforce from one of three providers:
  • A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
  • One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
  • The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling. The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data. The output can be used as the manifest file for another labeling job or as training data for your machine learning models. You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.

Parameters

-AmountInUsd_Cent <Int32>
The fractional portion, in cents, of the amount.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_PublicWorkforceTaskPrice_AmountInUsd_Cents
-AmountInUsd_Dollar <Int32>
The whole number of dollars in the amount.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_PublicWorkforceTaskPrice_AmountInUsd_Dollars
-AmountInUsd_TenthFractionsOfACent <Int32>
Fractions of a cent, in tenths.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_PublicWorkforceTaskPrice_AmountInUsd_TenthFractionsOfACent
-AnnotationConsolidationConfig_AnnotationConsolidationLambdaArn <String>
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_AnnotationConsolidationConfig_AnnotationConsolidationLambdaArn
-DataAttributes_ContentClassifier <String[]>
Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesInputConfig_DataAttributes_ContentClassifiers
-Force <SwitchParameter>
This parameter overrides confirmation prompts to force the cmdlet to continue its operation. This parameter should always be used with caution.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_MaxConcurrentTaskCount <Int32>
Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_NumberOfHumanWorkersPerDataObject <Int32>
The number of human workers that will label an object.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_PreHumanTaskLambdaArn <String>
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud ModalitiesUse the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more. 3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
  • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
  • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_TaskAvailabilityLifetimeInSecond <Int32>
The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
  • If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
  • If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_TaskAvailabilityLifetimeInSeconds
-HumanTaskConfig_TaskDescription <String>
A description of the task for your human workers.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_TaskKeyword <String[]>
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_TaskKeywords
-HumanTaskConfig_TaskTimeLimitInSecond <Int32>
The amount of time that a worker has to complete a task. If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
  • For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
  • For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_TaskTimeLimitInSeconds
-HumanTaskConfig_TaskTitle <String>
A title for the task for your human workers.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-HumanTaskConfig_WorkteamArn <String>
The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-LabelAttributeName <String>
The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
  • The name can't end with "-metadata".
  • If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
    • Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.
    • Video frame object detection (VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.
    • Video frame object tracking (VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.
    • 3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.
    • 3D point cloud object tracking (3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a differentLabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-LabelCategoryConfigS3Uri <String>
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs. For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.{ "document-version": "2018-11-28","labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]}Note the following about the label category configuration file:
  • For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
  • Each label category must be unique, you cannot specify duplicate label categories.
  • If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-LabelingJobAlgorithmsConfig_InitialActiveLearningModelArn <String>
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-LabelingJobAlgorithmsConfig_LabelingJobAlgorithmSpecificationArn <String>
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
  • Image classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
  • Text classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
  • Object detectionarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
  • Semantic Segmentationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-LabelingJobName <String>
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
Required?True
Position?1
Accept pipeline input?True (ByValue, ByPropertyName)
-LabelingJobResourceConfig_VolumeKmsKeyId <String>
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.The VolumeKmsKeyId can be any of the following formats:
  • KMS Key ID"1234abcd-12ab-34cd-56ef-1234567890ab"
  • Amazon Resource Name (ARN) of a KMS Key"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesLabelingJobAlgorithmsConfig_LabelingJobResourceConfig_VolumeKmsKeyId
-OutputConfig_KmsKeyId <String>
The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-OutputConfig_S3OutputPath <String>
The Amazon S3 location to write output data.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-OutputConfig_SnsTopicArn <String>
An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.If you provide an SnsTopicArn in OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here. To learn more, see Receive Output Data from a Streaming Labeling Job.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-PassThru <SwitchParameter>
Changes the cmdlet behavior to return the value passed to the LabelingJobName parameter. The -PassThru parameter is deprecated, use -Select '^LabelingJobName' instead. This parameter will be removed in a future version.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-RoleArn <String>
The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-S3DataSource_ManifestS3Uri <String>
The Amazon S3 location of the manifest file that describes the input data objects.The input manifest file referenced in ManifestS3Uri must contain one of the following keys: source-ref or source. The value of the keys are interpreted as follows:
  • source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
  • source: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesInputConfig_DataSource_S3DataSource_ManifestS3Uri
-Select <String>
Use the -Select parameter to control the cmdlet output. The default value is 'LabelingJobArn'. Specifying -Select '*' will result in the cmdlet returning the whole service response (Amazon.SageMaker.Model.CreateLabelingJobResponse). Specifying the name of a property of type Amazon.SageMaker.Model.CreateLabelingJobResponse will result in that property being returned. Specifying -Select '^ParameterName' will result in the cmdlet returning the selected cmdlet parameter value.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-SnsDataSource_SnsTopicArn <String>
The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesInputConfig_DataSource_SnsDataSource_SnsTopicArn
-StoppingConditions_MaxHumanLabeledObjectCount <Int32>
The maximum number of objects that can be labeled by human workers.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-StoppingConditions_MaxPercentageOfInputDatasetLabeled <Int32>
The maximum number of input data objects that should be labeled.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Tag <Tag[]>
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesTags
-UiConfig_HumanTaskUiArn <String>
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region with us-west-1 if you create a labeling job in US West (N. California).Named Entity RecognitionUse the following HumanTaskUiArn for named entity recognition labeling jobs:arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition3D Point Cloud HumanTaskUiArnsUse this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
  • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
  • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
  • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArnsUse this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
  • arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
  • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_UiConfig_HumanTaskUiArn
-UiConfig_UiTemplateS3Uri <String>
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesHumanTaskConfig_UiConfig_UiTemplateS3Uri
-VpcConfig_SecurityGroupId <String[]>
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesLabelingJobAlgorithmsConfig_LabelingJobResourceConfig_VpcConfig_SecurityGroupIds
-VpcConfig_Subnet <String[]>
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesLabelingJobAlgorithmsConfig_LabelingJobResourceConfig_VpcConfig_Subnets

Common Credential and Region Parameters

-AccessKey <String>
The AWS access key for the user account. This can be a temporary access key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAK
-Credential <AWSCredentials>
An AWSCredentials object instance containing access and secret key information, and optionally a token for session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-EndpointUrl <String>
The endpoint to make the call against.Note: This parameter is primarily for internal AWS use and is not required/should not be specified for normal usage. The cmdlets normally determine which endpoint to call based on the region specified to the -Region parameter or set as default in the shell (via Set-DefaultAWSRegion). Only specify this parameter if you must direct the call to a specific custom endpoint.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-NetworkCredential <PSCredential>
Used with SAML-based authentication when ProfileName references a SAML role profile. Contains the network credentials to be supplied during authentication with the configured identity provider's endpoint. This parameter is not required if the user's default network identity can or should be used during authentication.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-ProfileLocation <String>
Used to specify the name and location of the ini-format credential file (shared with the AWS CLI and other AWS SDKs)If this optional parameter is omitted this cmdlet will search the encrypted credential file used by the AWS SDK for .NET and AWS Toolkit for Visual Studio first. If the profile is not found then the cmdlet will search in the ini-format credential file at the default location: (user's home directory)\.aws\credentials.If this parameter is specified then this cmdlet will only search the ini-format credential file at the location given.As the current folder can vary in a shell or during script execution it is advised that you use specify a fully qualified path instead of a relative path.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAWSProfilesLocation, ProfilesLocation
-ProfileName <String>
The user-defined name of an AWS credentials or SAML-based role profile containing credential information. The profile is expected to be found in the secure credential file shared with the AWS SDK for .NET and AWS Toolkit for Visual Studio. You can also specify the name of a profile stored in the .ini-format credential file used with the AWS CLI and other AWS SDKs.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesStoredCredentials, AWSProfileName
-Region <Object>
The system name of an AWS region or an AWSRegion instance. This governs the endpoint that will be used when calling service operations. Note that the AWS resources referenced in a call are usually region-specific.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesRegionToCall
-SecretKey <String>
The AWS secret key for the user account. This can be a temporary secret key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSK, SecretAccessKey
-SessionToken <String>
The session token if the access and secret keys are temporary session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesST

Outputs

System.String or Amazon.SageMaker.Model.CreateLabelingJobResponse
This cmdlet returns a System.String object. The service call response (type Amazon.SageMaker.Model.CreateLabelingJobResponse) can also be referenced from properties attached to the cmdlet entry in the $AWSHistory stack.
Developer Guide
Service API Reference
AWS Tools for PowerShell User Guide

Supported Version

AWS Tools for PowerShell: 2.x.y.z