From b2582675dc099af864a0efd69f2d9d786921e48d Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 22 Jul 2025 10:10:07 +0000 Subject: [PATCH] Daily Sync with Botocore v1.39.10 on 2025/07/22 --- sample/sagemaker/2017-07-24/service-2.json | 81 ++++++++++++++++--- .../main/code_injection/shape_dag.py | 16 ++++ src/sagemaker_core/main/resources.py | 10 ++- src/sagemaker_core/main/shapes.py | 42 +++++++++- 4 files changed, 130 insertions(+), 19 deletions(-) diff --git a/sample/sagemaker/2017-07-24/service-2.json b/sample/sagemaker/2017-07-24/service-2.json index fcb840e7..67f510a9 100644 --- a/sample/sagemaker/2017-07-24/service-2.json +++ b/sample/sagemaker/2017-07-24/service-2.json @@ -5014,7 +5014,7 @@ "members":{ "AnnotationConsolidationLambdaArn":{ "shape":"LambdaFunctionArn", - "documentation":"

The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.

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.

Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

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.

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.

Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

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.

Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

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.

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.

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.

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.

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.

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.

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.

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.

Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

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.

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.

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.

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.

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.

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.

" + "documentation":"

The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.

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.

Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

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.

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.

Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

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.

Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

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.

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.

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.

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.

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.

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.

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.

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.

Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

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.

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.

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.

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.

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.

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.

Generative AI/Custom - Direct passthrough of output data without any transformation.

" } }, "documentation":"

Configures how labels are consolidated across human workers and processes output data.

" @@ -6910,7 +6910,7 @@ "type":"integer", "box":true, "max":500, - "min":1 + "min":0 }, "Branch":{ "type":"string", @@ -7971,7 +7971,6 @@ }, "ClusterEbsVolumeConfig":{ "type":"structure", - "required":["VolumeSizeInGB"], "members":{ "VolumeSizeInGB":{ "shape":"ClusterEbsVolumeSizeInGB", @@ -8187,7 +8186,7 @@ "ClusterInstanceStorageConfigs":{ "type":"list", "member":{"shape":"ClusterInstanceStorageConfig"}, - "max":1, + "max":2, "min":0 }, "ClusterInstanceType":{ @@ -9106,10 +9105,7 @@ }, "ComputeQuotaResourceConfig":{ "type":"structure", - "required":[ - "InstanceType", - "Count" - ], + "required":["InstanceType"], "members":{ "InstanceType":{ "shape":"ClusterInstanceType", @@ -10275,11 +10271,11 @@ }, "SubnetIds":{ "shape":"Subnets", - "documentation":"

The VPC subnets that the domain uses for communication.

" + "documentation":"

The VPC subnets that the domain uses for communication.

The field is optional when the AppNetworkAccessType parameter is set to PublicInternetOnly for domains created from Amazon SageMaker Unified Studio.

" }, "VpcId":{ "shape":"VpcId", - "documentation":"

The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.

" + "documentation":"

The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.

The field is optional when the AppNetworkAccessType parameter is set to PublicInternetOnly for domains created from Amazon SageMaker Unified Studio.

" }, "Tags":{ "shape":"TagList", @@ -12702,6 +12698,10 @@ "WorkforceVpcConfig":{ "shape":"WorkforceVpcConfigRequest", "documentation":"

Use this parameter to configure a workforce using VPC.

" + }, + "IpAddressType":{ + "shape":"WorkforceIpAddressType", + "documentation":"

Use this parameter to specify whether you want IPv4 only or dualstack (IPv4 and IPv6) to support your labeling workforce.

" } } }, @@ -12798,6 +12798,10 @@ "FSxLustreFileSystem":{ "shape":"FSxLustreFileSystem", "documentation":"

A custom file system in Amazon FSx for Lustre.

" + }, + "S3FileSystem":{ + "shape":"S3FileSystem", + "documentation":"

A custom file system in Amazon S3. This is only supported in Amazon SageMaker Unified Studio.

" } }, "documentation":"

A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

", @@ -12813,6 +12817,10 @@ "FSxLustreFileSystemConfig":{ "shape":"FSxLustreFileSystemConfig", "documentation":"

The settings for a custom Amazon FSx for Lustre file system.

" + }, + "S3FileSystemConfig":{ + "shape":"S3FileSystemConfig", + "documentation":"

Configuration settings for a custom Amazon S3 file system.

" } }, "documentation":"

The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.

", @@ -22473,7 +22481,7 @@ }, "PreHumanTaskLambdaArn":{ "shape":"LambdaFunctionArn", - "documentation":"

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.

Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

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.

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.

Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

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.

Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

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.

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.

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.

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.

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.

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.

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.

Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

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.

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.

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.

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.

3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.

3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.

3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.

" + "documentation":"

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.

Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

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.

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.

Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

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.

Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

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.

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.

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.

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.

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.

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.

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.

Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

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.

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.

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.

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.

3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.

3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.

3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.

Generative AI/Custom - Direct passthrough of input data without any transformation.

" }, "TaskKeywords":{ "shape":"TaskKeywords", @@ -24384,7 +24392,8 @@ "InstanceCount":{ "type":"integer", "box":true, - "min":1 + "max":10000000, + "min":0 }, "InstanceGroup":{ "type":"structure", @@ -36954,7 +36963,8 @@ "ml.p5en.48xlarge", "ml.trn1.32xlarge", "ml.trn2.48xlarge", - "ml.p6-b200.48xlarge" + "ml.p6-b200.48xlarge", + "ml.p4de.24xlarge" ] }, "ReservedCapacityOffering":{ @@ -37542,6 +37552,30 @@ "Converse" ] }, + "S3FileSystem":{ + "type":"structure", + "members":{ + "S3Uri":{ + "shape":"S3SchemaUri", + "documentation":"

The Amazon S3 URI that specifies the location in S3 where files are stored, which is mounted within the Studio environment. For example: s3://<bucket-name>/<prefix>/.

" + } + }, + "documentation":"

A custom file system in Amazon S3. This is only supported in Amazon SageMaker Unified Studio.

" + }, + "S3FileSystemConfig":{ + "type":"structure", + "members":{ + "MountPath":{ + "shape":"String1024", + "documentation":"

The file system path where the Amazon S3 storage location will be mounted within the Amazon SageMaker Studio environment.

" + }, + "S3Uri":{ + "shape":"S3SchemaUri", + "documentation":"

The Amazon S3 URI of the S3 file system configuration.

" + } + }, + "documentation":"

Configuration for the custom Amazon S3 file system.

" + }, "S3ModelDataSource":{ "type":"structure", "required":[ @@ -37614,6 +37648,12 @@ }, "documentation":"

This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access.

To learn more about how custom templates are created, see Create custom worker task templates.

" }, + "S3SchemaUri":{ + "type":"string", + "max":1024, + "min":0, + "pattern":"(s3)://([^/]+)/?(.*)" + }, "S3StorageConfig":{ "type":"structure", "required":["S3Uri"], @@ -43744,6 +43784,10 @@ "WorkforceVpcConfig":{ "shape":"WorkforceVpcConfigRequest", "documentation":"

Use this parameter to update your VPC configuration for a workforce.

" + }, + "IpAddressType":{ + "shape":"WorkforceIpAddressType", + "documentation":"

Use this parameter to specify whether you want IPv4 only or dualstack (IPv4 and IPv6) to support your labeling workforce.

" } } }, @@ -44278,6 +44322,10 @@ "FailureReason":{ "shape":"WorkforceFailureReason", "documentation":"

The reason your workforce failed.

" + }, + "IpAddressType":{ + "shape":"WorkforceIpAddressType", + "documentation":"

The IP address type you specify - either IPv4 only or dualstack (IPv4 and IPv6) - to support your labeling workforce.

" } }, "documentation":"

A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.

" @@ -44294,6 +44342,13 @@ "min":1, "pattern":".+" }, + "WorkforceIpAddressType":{ + "type":"string", + "enum":[ + "ipv4", + "dualstack" + ] + }, "WorkforceName":{ "type":"string", "max":63, diff --git a/src/sagemaker_core/main/code_injection/shape_dag.py b/src/sagemaker_core/main/code_injection/shape_dag.py index efb1ef9f..4412f5bc 100644 --- a/src/sagemaker_core/main/code_injection/shape_dag.py +++ b/src/sagemaker_core/main/code_injection/shape_dag.py @@ -3377,6 +3377,7 @@ "shape": "WorkforceVpcConfigRequest", "type": "structure", }, + {"name": "IpAddressType", "shape": "WorkforceIpAddressType", "type": "string"}, ], "type": "structure", }, @@ -3413,6 +3414,7 @@ "members": [ {"name": "EFSFileSystem", "shape": "EFSFileSystem", "type": "structure"}, {"name": "FSxLustreFileSystem", "shape": "FSxLustreFileSystem", "type": "structure"}, + {"name": "S3FileSystem", "shape": "S3FileSystem", "type": "structure"}, ], "type": "structure", }, @@ -3424,6 +3426,7 @@ "shape": "FSxLustreFileSystemConfig", "type": "structure", }, + {"name": "S3FileSystemConfig", "shape": "S3FileSystemConfig", "type": "structure"}, ], "type": "structure", }, @@ -13672,6 +13675,17 @@ ], "type": "structure", }, + "S3FileSystem": { + "members": [{"name": "S3Uri", "shape": "S3SchemaUri", "type": "string"}], + "type": "structure", + }, + "S3FileSystemConfig": { + "members": [ + {"name": "MountPath", "shape": "String1024", "type": "string"}, + {"name": "S3Uri", "shape": "S3SchemaUri", "type": "string"}, + ], + "type": "structure", + }, "S3ModelDataSource": { "members": [ {"name": "S3Uri", "shape": "S3ModelUri", "type": "string"}, @@ -16118,6 +16132,7 @@ "shape": "WorkforceVpcConfigRequest", "type": "structure", }, + {"name": "IpAddressType", "shape": "WorkforceIpAddressType", "type": "string"}, ], "type": "structure", }, @@ -16326,6 +16341,7 @@ }, {"name": "Status", "shape": "WorkforceStatus", "type": "string"}, {"name": "FailureReason", "shape": "WorkforceFailureReason", "type": "string"}, + {"name": "IpAddressType", "shape": "WorkforceIpAddressType", "type": "string"}, ], "type": "structure", }, diff --git a/src/sagemaker_core/main/resources.py b/src/sagemaker_core/main/resources.py index 02aeee08..097a0797 100644 --- a/src/sagemaker_core/main/resources.py +++ b/src/sagemaker_core/main/resources.py @@ -7436,8 +7436,8 @@ def create( auth_mode: The mode of authentication that members use to access the domain. default_user_settings: The default settings to use to create a user profile when UserSettings isn't specified in the call to the CreateUserProfile API. SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain. domain_settings: A collection of Domain settings. - subnet_ids: The VPC subnets that the domain uses for communication. - vpc_id: The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication. + subnet_ids: The VPC subnets that the domain uses for communication. The field is optional when the AppNetworkAccessType parameter is set to PublicInternetOnly for domains created from Amazon SageMaker Unified Studio. + vpc_id: The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication. The field is optional when the AppNetworkAccessType parameter is set to PublicInternetOnly for domains created from Amazon SageMaker Unified Studio. tags: Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API. Tags that you specify for the Domain are also added to all Apps that the Domain launches. app_network_access_type: Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly. PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access VpcOnly - All traffic is through the specified VPC and subnets home_efs_file_system_kms_key_id: Use KmsKeyId. @@ -31261,6 +31261,7 @@ def create( source_ip_config: Optional[shapes.SourceIpConfig] = Unassigned(), tags: Optional[List[shapes.Tag]] = Unassigned(), workforce_vpc_config: Optional[shapes.WorkforceVpcConfigRequest] = Unassigned(), + ip_address_type: Optional[str] = Unassigned(), session: Optional[Session] = None, region: Optional[str] = None, ) -> Optional["Workforce"]: @@ -31274,6 +31275,7 @@ def create( source_ip_config: tags: An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define. workforce_vpc_config: Use this parameter to configure a workforce using VPC. + ip_address_type: Use this parameter to specify whether you want IPv4 only or dualstack (IPv4 and IPv6) to support your labeling workforce. session: Boto3 session. region: Region name. @@ -31307,6 +31309,7 @@ def create( "WorkforceName": workforce_name, "Tags": tags, "WorkforceVpcConfig": workforce_vpc_config, + "IpAddressType": ip_address_type, } operation_input_args = Base.populate_chained_attributes( @@ -31417,6 +31420,7 @@ def update( source_ip_config: Optional[shapes.SourceIpConfig] = Unassigned(), oidc_config: Optional[shapes.OidcConfig] = Unassigned(), workforce_vpc_config: Optional[shapes.WorkforceVpcConfigRequest] = Unassigned(), + ip_address_type: Optional[str] = Unassigned(), ) -> Optional["Workforce"]: """ Update a Workforce resource @@ -31425,6 +31429,7 @@ def update( source_ip_config: A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce. Maximum: Ten CIDR values oidc_config: Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP. workforce_vpc_config: Use this parameter to update your VPC configuration for a workforce. + ip_address_type: Use this parameter to specify whether you want IPv4 only or dualstack (IPv4 and IPv6) to support your labeling workforce. Returns: The Workforce resource. @@ -31450,6 +31455,7 @@ def update( "SourceIpConfig": source_ip_config, "OidcConfig": oidc_config, "WorkforceVpcConfig": workforce_vpc_config, + "IpAddressType": ip_address_type, } logger.debug(f"Input request: {operation_input_args}") # serialize the input request diff --git a/src/sagemaker_core/main/shapes.py b/src/sagemaker_core/main/shapes.py index c8b4bfdd..b7937eb0 100644 --- a/src/sagemaker_core/main/shapes.py +++ b/src/sagemaker_core/main/shapes.py @@ -1221,7 +1221,7 @@ class AnnotationConsolidationConfig(Base): Attributes ---------------------- - annotation_consolidation_lambda_arn: The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data. 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 + annotation_consolidation_lambda_arn: The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data. 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 Generative AI/Custom - Direct passthrough of output data without any transformation. arn:aws:lambda:us-east-1:432418664414:function:ACS-PassThrough arn:aws:lambda:us-east-2:266458841044:function:ACS-PassThrough arn:aws:lambda:us-west-2:081040173940:function:ACS-PassThrough arn:aws:lambda:eu-west-1:568282634449:function:ACS-PassThrough arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-PassThrough arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-PassThrough arn:aws:lambda:ap-south-1:565803892007:function:ACS-PassThrough arn:aws:lambda:eu-central-1:203001061592:function:ACS-PassThrough arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-PassThrough arn:aws:lambda:eu-west-2:487402164563:function:ACS-PassThrough arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-PassThrough arn:aws:lambda:ca-central-1:918755190332:function:ACS-PassThrough """ annotation_consolidation_lambda_arn: str @@ -3284,7 +3284,7 @@ class ClusterEbsVolumeConfig(Base): volume_size_in_gb: The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to /opt/sagemaker. """ - volume_size_in_gb: int + volume_size_in_gb: Optional[int] = Unassigned() class ClusterLifeCycleConfig(Base): @@ -3922,7 +3922,7 @@ class ComputeQuotaResourceConfig(Base): """ instance_type: str - count: int + count: Optional[int] = Unassigned() class ResourceSharingConfig(Base): @@ -4884,6 +4884,21 @@ class FSxLustreFileSystemConfig(Base): file_system_path: Optional[str] = Unassigned() +class S3FileSystemConfig(Base): + """ + S3FileSystemConfig + Configuration for the custom Amazon S3 file system. + + Attributes + ---------------------- + mount_path: The file system path where the Amazon S3 storage location will be mounted within the Amazon SageMaker Studio environment. + s3_uri: The Amazon S3 URI of the S3 file system configuration. + """ + + mount_path: Optional[str] = Unassigned() + s3_uri: Optional[str] = Unassigned() + + class CustomFileSystemConfig(Base): """ CustomFileSystemConfig @@ -4893,10 +4908,12 @@ class CustomFileSystemConfig(Base): ---------------------- efs_file_system_config: The settings for a custom Amazon EFS file system. f_sx_lustre_file_system_config: The settings for a custom Amazon FSx for Lustre file system. + s3_file_system_config: Configuration settings for a custom Amazon S3 file system. """ efs_file_system_config: Optional[EFSFileSystemConfig] = Unassigned() f_sx_lustre_file_system_config: Optional[FSxLustreFileSystemConfig] = Unassigned() + s3_file_system_config: Optional[S3FileSystemConfig] = Unassigned() class HiddenSageMakerImage(Base): @@ -6514,7 +6531,7 @@ class HumanTaskConfig(Base): ---------------------- workteam_arn: The Amazon Resource Name (ARN) of the work team assigned to complete the tasks. ui_config: Information about the user interface that workers use to complete the labeling task. - pre_human_task_lambda_arn: 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 + pre_human_task_lambda_arn: 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 Generative AI/Custom - Direct passthrough of input data without any transformation. arn:aws:lambda:us-east-1:432418664414:function:PRE-PassThrough arn:aws:lambda:us-east-2:266458841044:function:PRE-PassThrough arn:aws:lambda:us-west-2:081040173940:function:PRE-PassThrough arn:aws:lambda:ca-central-1:918755190332:function:PRE-PassThrough arn:aws:lambda:eu-west-1:568282634449:function:PRE-PassThrough arn:aws:lambda:eu-west-2:487402164563:function:PRE-PassThrough arn:aws:lambda:eu-central-1:203001061592:function:PRE-PassThrough arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-PassThrough arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-PassThrough arn:aws:lambda:ap-south-1:565803892007:function:PRE-PassThrough arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-PassThrough arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-PassThrough task_keywords: Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task. task_title: A title for the task for your human workers. task_description: A description of the task for your human workers. @@ -7741,6 +7758,19 @@ class FSxLustreFileSystem(Base): file_system_id: str +class S3FileSystem(Base): + """ + S3FileSystem + A custom file system in Amazon S3. This is only supported in Amazon SageMaker Unified Studio. + + Attributes + ---------------------- + s3_uri: The Amazon S3 URI that specifies the location in S3 where files are stored, which is mounted within the Studio environment. For example: s3://<bucket-name>/<prefix>/. + """ + + s3_uri: Optional[str] = Unassigned() + + class CustomFileSystem(Base): """ CustomFileSystem @@ -7750,10 +7780,12 @@ class CustomFileSystem(Base): ---------------------- efs_file_system: A custom file system in Amazon EFS. f_sx_lustre_file_system: A custom file system in Amazon FSx for Lustre. + s3_file_system: A custom file system in Amazon S3. This is only supported in Amazon SageMaker Unified Studio. """ efs_file_system: Optional[EFSFileSystem] = Unassigned() f_sx_lustre_file_system: Optional[FSxLustreFileSystem] = Unassigned() + s3_file_system: Optional[S3FileSystem] = Unassigned() class SpaceSettings(Base): @@ -9573,6 +9605,7 @@ class Workforce(Base): workforce_vpc_config: The configuration of a VPC workforce. status: The status of your workforce. failure_reason: The reason your workforce failed. + ip_address_type: The IP address type you specify - either IPv4 only or dualstack (IPv4 and IPv6) - to support your labeling workforce. """ workforce_name: Union[str, object] @@ -9586,6 +9619,7 @@ class Workforce(Base): workforce_vpc_config: Optional[WorkforceVpcConfigResponse] = Unassigned() status: Optional[str] = Unassigned() failure_reason: Optional[str] = Unassigned() + ip_address_type: Optional[str] = Unassigned() class Workteam(Base):