SageMaker / Client / describe_labeling_job

describe_labeling_job

SageMaker.Client.describe_labeling_job(**kwargs)

Gets information about a labeling job.

See also: AWS API Documentation

Request Syntax

response = client.describe_labeling_job(
    LabelingJobName='string'
)

Parameters:

LabelingJobName (string) –

[REQUIRED]

The name of the labeling job to return information for.

Return type:

dict

Returns:

Response Syntax

{
    'LabelingJobStatus': 'Initializing'|'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
    'LabelCounters': {
        'TotalLabeled': 123,
        'HumanLabeled': 123,
        'MachineLabeled': 123,
        'FailedNonRetryableError': 123,
        'Unlabeled': 123
    },
    'FailureReason': 'string',
    'CreationTime': datetime(2015, 1, 1),
    'LastModifiedTime': datetime(2015, 1, 1),
    'JobReferenceCode': 'string',
    'LabelingJobName': 'string',
    'LabelingJobArn': 'string',
    'LabelAttributeName': 'string',
    'InputConfig': {
        'DataSource': {
            'S3DataSource': {
                'ManifestS3Uri': 'string'
            },
            'SnsDataSource': {
                'SnsTopicArn': 'string'
            }
        },
        'DataAttributes': {
            'ContentClassifiers': [
                'FreeOfPersonallyIdentifiableInformation'|'FreeOfAdultContent',
            ]
        }
    },
    'OutputConfig': {
        'S3OutputPath': 'string',
        'KmsKeyId': 'string',
        'SnsTopicArn': 'string'
    },
    'RoleArn': 'string',
    'LabelCategoryConfigS3Uri': 'string',
    'StoppingConditions': {
        'MaxHumanLabeledObjectCount': 123,
        'MaxPercentageOfInputDatasetLabeled': 123
    },
    'LabelingJobAlgorithmsConfig': {
        'LabelingJobAlgorithmSpecificationArn': 'string',
        'InitialActiveLearningModelArn': 'string',
        'LabelingJobResourceConfig': {
            'VolumeKmsKeyId': 'string',
            'VpcConfig': {
                'SecurityGroupIds': [
                    'string',
                ],
                'Subnets': [
                    'string',
                ]
            }
        }
    },
    'HumanTaskConfig': {
        'WorkteamArn': 'string',
        'UiConfig': {
            'UiTemplateS3Uri': 'string',
            'HumanTaskUiArn': 'string'
        },
        'PreHumanTaskLambdaArn': 'string',
        'TaskKeywords': [
            'string',
        ],
        'TaskTitle': 'string',
        'TaskDescription': 'string',
        'NumberOfHumanWorkersPerDataObject': 123,
        'TaskTimeLimitInSeconds': 123,
        'TaskAvailabilityLifetimeInSeconds': 123,
        'MaxConcurrentTaskCount': 123,
        'AnnotationConsolidationConfig': {
            'AnnotationConsolidationLambdaArn': 'string'
        },
        'PublicWorkforceTaskPrice': {
            'AmountInUsd': {
                'Dollars': 123,
                'Cents': 123,
                'TenthFractionsOfACent': 123
            }
        }
    },
    'Tags': [
        {
            'Key': 'string',
            'Value': 'string'
        },
    ],
    'LabelingJobOutput': {
        'OutputDatasetS3Uri': 'string',
        'FinalActiveLearningModelArn': 'string'
    }
}

Response Structure

• (dict) –

  • LabelingJobStatus (string) –

    The processing status of the labeling job.

  • LabelCounters (dict) –

    Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn’t be labeled, and the total number of objects labeled.

    • TotalLabeled (integer) –

      The total number of objects labeled.

    • HumanLabeled (integer) –

      The total number of objects labeled by a human worker.

    • MachineLabeled (integer) –

      The total number of objects labeled by automated data labeling.

    • FailedNonRetryableError (integer) –

      The total number of objects that could not be labeled due to an error.

    • Unlabeled (integer) –

      The total number of objects not yet labeled.

  • FailureReason (string) –

    If the job failed, the reason that it failed.

  • CreationTime (datetime) –

    The date and time that the labeling job was created.

  • LastModifiedTime (datetime) –

    The date and time that the labeling job was last updated.

  • JobReferenceCode (string) –

    A unique identifier for work done as part of a labeling job.

  • LabelingJobName (string) –

    The name assigned to the labeling job when it was created.

  • LabelingJobArn (string) –

    The Amazon Resource Name (ARN) of the labeling job.

  • LabelAttributeName (string) –

    The attribute used as the label in the output manifest file.

  • InputConfig (dict) –

    Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.

    • DataSource (dict) –

      The location of the input data.

      • S3DataSource (dict) –

        The Amazon S3 location of the input data objects.

        • 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.

      • SnsDataSource (dict) –

        An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.

        • 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.

    • DataAttributes (dict) –

      Attributes of the data specified by the customer.

      • ContentClassifiers (list) –

        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.

        • (string) –

  • OutputConfig (dict) –

    The location of the job’s output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.

    • S3OutputPath (string) –

      The Amazon S3 location to write output data.

    • 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.

    • 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.

  • RoleArn (string) –

    The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.

  • LabelCategoryConfigS3Uri (string) –

    The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:

    • Semantic segmentation labeling jobs using automated labeling: 20 labels

    • Box bounding labeling jobs (all): 10 labels

    The file is a JSON structure in the following format:

    {

    "document-version": "2018-11-28"

    "labels": [

    {

    "label": "label 1"

    },

    {

    "label": "label 2"

    },

    ...

    {

    "label": "label n"

    }

    ]

    }

  • StoppingConditions (dict) –

    A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.

    • MaxHumanLabeledObjectCount (integer) –

      The maximum number of objects that can be labeled by human workers.

    • MaxPercentageOfInputDatasetLabeled (integer) –

      The maximum number of input data objects that should be labeled.

  • LabelingJobAlgorithmsConfig (dict) –

    Configuration information for automated data labeling.

    • LabelingJobAlgorithmSpecificationArn (string) –

      Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:

      • Image classification arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification

      • Text classification arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification

      • Object detection arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection

      • Semantic Segmentation arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation

    • 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.

    • LabelingJobResourceConfig (dict) –

      Provides configuration information for a labeling job.

      • 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"

      • VpcConfig (dict) –

        Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud.

        • SecurityGroupIds (list) –

          The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.

          • (string) –

        • Subnets (list) –

          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.

          • (string) –

  • HumanTaskConfig (dict) –

    Configuration information required for human workers to complete a labeling task.

    • WorkteamArn (string) –

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

    • UiConfig (dict) –

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

      • 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.

      • 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 Recognition

        Use the following HumanTaskUiArn for named entity recognition labeling jobs:

        arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition

        3D Point Cloud HumanTaskUiArns

        Use 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 HumanTaskUiArns

        Use 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

    • 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 Modalities

      Use 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 Jobs

      Use 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

    • TaskKeywords (list) –

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

      • (string) –

    • TaskTitle (string) –

      A title for the task for your human workers.

    • TaskDescription (string) –

      A description of the task for your human workers.

    • NumberOfHumanWorkersPerDataObject (integer) –

      The number of human workers that will label an object.

    • TaskTimeLimitInSeconds (integer) –

      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.

    • TaskAvailabilityLifetimeInSeconds (integer) –

      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.

    • MaxConcurrentTaskCount (integer) –

      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. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.

    • AnnotationConsolidationConfig (dict) –

      Configures how labels are consolidated across human workers.

      • 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 Jobs

        Use 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

    • PublicWorkforceTaskPrice (dict) –

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

      • AmountInUsd (dict) –

        Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.

        • Dollars (integer) –

          The whole number of dollars in the amount.

        • Cents (integer) –

          The fractional portion, in cents, of the amount.

        • TenthFractionsOfACent (integer) –

          Fractions of a cent, in tenths.

  • Tags (list) –

    An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

    • (dict) –

      A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

      You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.

      For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.

      • Key (string) –

        The tag key. Tag keys must be unique per resource.

      • Value (string) –

        The tag value.

  • LabelingJobOutput (dict) –

    The location of the output produced by the labeling job.

    • OutputDatasetS3Uri (string) –

      The Amazon S3 bucket location of the manifest file for labeled data.

    • FinalActiveLearningModelArn (string) –

      The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.

Exceptions

• SageMaker.Client.exceptions.ResourceNotFound