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Man Pages
Paws::SageMaker::HumanTaskConfig(3) User Contributed Perl Documentation Paws::SageMaker::HumanTaskConfig(3)

Paws::SageMaker::HumanTaskConfig

This class represents one of two things:

Arguments in a call to a service

Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object.

As an example, if Att1 is expected to be a Paws::SageMaker::HumanTaskConfig object:

  $service_obj->Method(Att1 => { AnnotationConsolidationConfig => $value, ..., WorkteamArn => $value  });

Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::SageMaker::HumanTaskConfig object:

  $result = $service_obj->Method(...);
  $result->Att1->AnnotationConsolidationConfig

Information required for human workers to complete a labeling task.

REQUIRED AnnotationConsolidationConfig => Paws::SageMaker::AnnotationConsolidationConfig

Configures how labels are consolidated across human workers.

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 NumberOfHumanWorkersPerDataObject => Int

The number of human workers that will label an object.

REQUIRED PreHumanTaskLambdaArn => Str

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 (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html), use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for "PreHumanTaskLambdaArn". For custom labeling workflows, see Pre-annotation Lambda (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-prelambda).

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 Modalities

Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html) 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 Jobs

Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html).

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"

The price that you pay for each task performed by an Amazon Mechanical Turk worker.

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 10 days (864,000 seconds). For most users, the maximum is also 10 days. If you want to change this limit, contact Amazon Web Services Support.

REQUIRED TaskDescription => Str

A description of the task for your human workers.

Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.

REQUIRED TaskTimeLimitInSeconds => Int

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 (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html) the maximum for this parameter depends on the task type you use:

  • For image (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.html) and text (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.html) labeling jobs, the maximum is 8 hours (28,800 seconds).
  • For 3D point cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html) and video frame (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html) labeling jobs, the maximum is 7 days (604,800 seconds). If you want to change these limits, contact Amazon Web Services Support.

REQUIRED TaskTitle => Str

A title for the task for your human workers.

REQUIRED UiConfig => Paws::SageMaker::UiConfig

Information about the user interface that workers use to complete the labeling task.

REQUIRED WorkteamArn => Str

The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.

This class forms part of Paws, describing an object used in Paws::SageMaker

The source code is located here: <https://github.com/pplu/aws-sdk-perl>

Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>

2022-06-01 perl v5.40.2
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