Interface CreateLabelingJobRequest.Builder
- All Superinterfaces:
AwsRequest.Builder
,Buildable
,CopyableBuilder<CreateLabelingJobRequest.Builder,
,CreateLabelingJobRequest> SageMakerRequest.Builder
,SdkBuilder<CreateLabelingJobRequest.Builder,
,CreateLabelingJobRequest> SdkPojo
,SdkRequest.Builder
- Enclosing class:
CreateLabelingJobRequest
-
Method Summary
Modifier and TypeMethodDescriptiondefault CreateLabelingJobRequest.Builder
humanTaskConfig
(Consumer<HumanTaskConfig.Builder> humanTaskConfig) Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).humanTaskConfig
(HumanTaskConfig humanTaskConfig) Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).default CreateLabelingJobRequest.Builder
inputConfig
(Consumer<LabelingJobInputConfig.Builder> inputConfig) Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.inputConfig
(LabelingJobInputConfig inputConfig) Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.labelAttributeName
(String labelAttributeName) The attribute name to use for the label in the output manifest file.labelCategoryConfigS3Uri
(String labelCategoryConfigS3Uri) The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.default CreateLabelingJobRequest.Builder
labelingJobAlgorithmsConfig
(Consumer<LabelingJobAlgorithmsConfig.Builder> labelingJobAlgorithmsConfig) Configures the information required to perform automated data labeling.labelingJobAlgorithmsConfig
(LabelingJobAlgorithmsConfig labelingJobAlgorithmsConfig) Configures the information required to perform automated data labeling.labelingJobName
(String labelingJobName) The name of the labeling job.default CreateLabelingJobRequest.Builder
outputConfig
(Consumer<LabelingJobOutputConfig.Builder> outputConfig) The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.outputConfig
(LabelingJobOutputConfig outputConfig) The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.overrideConfiguration
(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Add an optional request override configuration.overrideConfiguration
(AwsRequestOverrideConfiguration overrideConfiguration) Add an optional request override configuration.The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling.default CreateLabelingJobRequest.Builder
stoppingConditions
(Consumer<LabelingJobStoppingConditions.Builder> stoppingConditions) A set of conditions for stopping the labeling job.stoppingConditions
(LabelingJobStoppingConditions stoppingConditions) A set of conditions for stopping the labeling job.tags
(Collection<Tag> tags) An array of key/value pairs.tags
(Consumer<Tag.Builder>... tags) An array of key/value pairs.An array of key/value pairs.Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder
overrideConfiguration
Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder
build
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
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Method Details
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labelingJobName
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region.
LabelingJobName
is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.- Parameters:
labelingJobName
- The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region.LabelingJobName
is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelAttributeName
The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The
LabelAttributeName
must meet the following requirements.-
The name can't end with "-metadata".
-
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
-
Image semantic segmentation (
SemanticSegmentation)
, and adjustment (AdjustmentSemanticSegmentation
) and verification (VerificationSemanticSegmentation
) labeling jobs for this task type. -
Video frame object detection (
VideoObjectDetection
), and adjustment and verification (AdjustmentVideoObjectDetection
) labeling jobs for this task type. -
Video frame object tracking (
VideoObjectTracking
), and adjustment and verification (AdjustmentVideoObjectTracking
) labeling jobs for this task type. -
3D point cloud semantic segmentation (
3DPointCloudSemanticSegmentation
), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation
) labeling jobs for this task type. -
3D point cloud object tracking (
3DPointCloudObjectTracking
), and adjustment and verification (Adjustment3DPointCloudObjectTracking
) labeling jobs for this task type.
-
If you are creating an adjustment or verification labeling job, you must use a different
LabelAttributeName
than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.- Parameters:
labelAttributeName
- The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. TheLabelAttributeName
must meet the following requirements.-
The name can't end with "-metadata".
-
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
-
Image semantic segmentation (
SemanticSegmentation)
, and adjustment (AdjustmentSemanticSegmentation
) and verification (VerificationSemanticSegmentation
) labeling jobs for this task type. -
Video frame object detection (
VideoObjectDetection
), and adjustment and verification (AdjustmentVideoObjectDetection
) labeling jobs for this task type. -
Video frame object tracking (
VideoObjectTracking
), and adjustment and verification (AdjustmentVideoObjectTracking
) labeling jobs for this task type. -
3D point cloud semantic segmentation (
3DPointCloudSemanticSegmentation
), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation
) labeling jobs for this task type. -
3D point cloud object tracking (
3DPointCloudObjectTracking
), and adjustment and verification (Adjustment3DPointCloudObjectTracking
) labeling jobs for this task type.
-
If you are creating an adjustment or verification labeling job, you must use a different
LabelAttributeName
than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
inputConfig
Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following:
S3DataSource
orSnsDataSource
.-
Use
SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled. -
Use
S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSource
is optional if you useSnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use
ContentClassifiers
to specify that your data is free of personally identifiable information and adult content.- Parameters:
inputConfig
- Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.You must specify at least one of the following:
S3DataSource
orSnsDataSource
.-
Use
SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled. -
Use
S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSource
is optional if you useSnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use
ContentClassifiers
to specify that your data is free of personally identifiable information and adult content.-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-
inputConfig
default CreateLabelingJobRequest.Builder inputConfig(Consumer<LabelingJobInputConfig.Builder> inputConfig) Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following:
S3DataSource
orSnsDataSource
.-
Use
SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled. -
Use
S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSource
is optional if you useSnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use
This is a convenience method that creates an instance of theContentClassifiers
to specify that your data is free of personally identifiable information and adult content.LabelingJobInputConfig.Builder
avoiding the need to create one manually viaLabelingJobInputConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toinputConfig(LabelingJobInputConfig)
.- Parameters:
inputConfig
- a consumer that will call methods onLabelingJobInputConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
-
outputConfig
The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
- Parameters:
outputConfig
- The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
outputConfig
default CreateLabelingJobRequest.Builder outputConfig(Consumer<LabelingJobOutputConfig.Builder> outputConfig) The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
This is a convenience method that creates an instance of theLabelingJobOutputConfig.Builder
avoiding the need to create one manually viaLabelingJobOutputConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tooutputConfig(LabelingJobOutputConfig)
.- Parameters:
outputConfig
- a consumer that will call methods onLabelingJobOutputConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
roleArn
The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
- Parameters:
roleArn
- The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelCategoryConfigS3Uri
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to
"labels"
, you must provide worker instructions in the label category configuration file using the"instructions"
parameter:"instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing
label_1
,label_2
,...
,label_n
with your label categories.{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
-
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
-
Each label category must be unique, you cannot specify duplicate label categories.
-
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include
auditLabelAttributeName
in the label category configuration. Use this parameter to enter theLabelAttributeName
of the labeling job you want to adjust or verify annotations of.
- Parameters:
labelCategoryConfigS3Uri
- The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to
"labels"
, you must provide worker instructions in the label category configuration file using the"instructions"
parameter:"instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing
label_1
,label_2
,...
,label_n
with your label categories.{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
-
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
-
Each label category must be unique, you cannot specify duplicate label categories.
-
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include
auditLabelAttributeName
in the label category configuration. Use this parameter to enter theLabelAttributeName
of the labeling job you want to adjust or verify annotations of.
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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stoppingConditions
CreateLabelingJobRequest.Builder stoppingConditions(LabelingJobStoppingConditions stoppingConditions) A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
- Parameters:
stoppingConditions
- A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
stoppingConditions
default CreateLabelingJobRequest.Builder stoppingConditions(Consumer<LabelingJobStoppingConditions.Builder> stoppingConditions) A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
This is a convenience method that creates an instance of theLabelingJobStoppingConditions.Builder
avoiding the need to create one manually viaLabelingJobStoppingConditions.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tostoppingConditions(LabelingJobStoppingConditions)
.- Parameters:
stoppingConditions
- a consumer that will call methods onLabelingJobStoppingConditions.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
labelingJobAlgorithmsConfig
CreateLabelingJobRequest.Builder labelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig labelingJobAlgorithmsConfig) Configures the information required to perform automated data labeling.
- Parameters:
labelingJobAlgorithmsConfig
- Configures the information required to perform automated data labeling.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelingJobAlgorithmsConfig
default CreateLabelingJobRequest.Builder labelingJobAlgorithmsConfig(Consumer<LabelingJobAlgorithmsConfig.Builder> labelingJobAlgorithmsConfig) Configures the information required to perform automated data labeling.
This is a convenience method that creates an instance of theLabelingJobAlgorithmsConfig.Builder
avoiding the need to create one manually viaLabelingJobAlgorithmsConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tolabelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig)
.- Parameters:
labelingJobAlgorithmsConfig
- a consumer that will call methods onLabelingJobAlgorithmsConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
humanTaskConfig
Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
- Parameters:
humanTaskConfig
- Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
humanTaskConfig
default CreateLabelingJobRequest.Builder humanTaskConfig(Consumer<HumanTaskConfig.Builder> humanTaskConfig) Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
This is a convenience method that creates an instance of theHumanTaskConfig.Builder
avoiding the need to create one manually viaHumanTaskConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tohumanTaskConfig(HumanTaskConfig)
.- Parameters:
humanTaskConfig
- a consumer that will call methods onHumanTaskConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
tags
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
- Parameters:
tags
- An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tags
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
- Parameters:
tags
- An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tags
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
This is a convenience method that creates an instance of theTag.Builder
avoiding the need to create one manually viaTag.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed totags(List<Tag>)
.- Parameters:
tags
- a consumer that will call methods onTag.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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overrideConfiguration
CreateLabelingJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
overrideConfiguration
- The override configuration.- Returns:
- This object for method chaining.
-
overrideConfiguration
CreateLabelingJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
builderConsumer
- AConsumer
to which an emptyAwsRequestOverrideConfiguration.Builder
will be given.- Returns:
- This object for method chaining.
-