public static interface CreateLabelingJobRequest.Builder extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder<CreateLabelingJobRequest.Builder,CreateLabelingJobRequest>
| Modifier and Type | Method and Description |
|---|---|
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).
|
CreateLabelingJobRequest.Builder |
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.
|
CreateLabelingJobRequest.Builder |
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.
|
CreateLabelingJobRequest.Builder |
labelAttributeName(String labelAttributeName)
The attribute name to use for the label in the output manifest file.
|
CreateLabelingJobRequest.Builder |
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.
|
CreateLabelingJobRequest.Builder |
labelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig labelingJobAlgorithmsConfig)
Configures the information required to perform automated data labeling.
|
CreateLabelingJobRequest.Builder |
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.
|
CreateLabelingJobRequest.Builder |
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.
|
CreateLabelingJobRequest.Builder |
overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) |
CreateLabelingJobRequest.Builder |
overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) |
CreateLabelingJobRequest.Builder |
roleArn(String roleArn)
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.
|
CreateLabelingJobRequest.Builder |
stoppingConditions(LabelingJobStoppingConditions stoppingConditions)
A set of conditions for stopping the labeling job.
|
CreateLabelingJobRequest.Builder |
tags(Collection<Tag> tags)
An array of key/value pairs.
|
CreateLabelingJobRequest.Builder |
tags(Consumer<Tag.Builder>... tags)
An array of key/value pairs.
|
CreateLabelingJobRequest.Builder |
tags(Tag... tags)
An array of key/value pairs.
|
buildoverrideConfigurationequalsBySdkFields, sdkFieldscopyapplyMutation, buildCreateLabelingJobRequest.Builder labelingJobName(String 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.
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.CreateLabelingJobRequest.Builder labelAttributeName(String 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.
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.
CreateLabelingJobRequest.Builder 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.
You must specify at least one of the following: S3DataSource or SnsDataSource.
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 an S3DataSource is optional if you use SnsDataSource 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.
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 or
SnsDataSource.
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 an S3DataSource is optional if you use SnsDataSource
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.
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 or SnsDataSource.
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 an S3DataSource is optional if you use SnsDataSource 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.
LabelingJobInputConfig.Builder avoiding the
need to create one manually via LabelingJobInputConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to inputConfig(LabelingJobInputConfig).inputConfig - a consumer that will call methods on LabelingJobInputConfig.BuilderinputConfig(LabelingJobInputConfig)CreateLabelingJobRequest.Builder 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.
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.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 that creates an instance of theLabelingJobOutputConfig.Builder avoiding the
need to create one manually via LabelingJobOutputConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately
and its result is passed to outputConfig(LabelingJobOutputConfig).outputConfig - a consumer that will call methods on LabelingJobOutputConfig.BuilderoutputConfig(LabelingJobOutputConfig)CreateLabelingJobRequest.Builder roleArn(String 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.
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.CreateLabelingJobRequest.Builder 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.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels", you must provide worker instructions
in the label category configuration file using the "instructions" parameter:
"instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create
a Named Entity Recognition Labeling Job (API) .
For all other built-in task
types and custom
tasks, your label category configuration file must be a JSON file in the following format. Identify the
labels you want to use by replacing label_1, label_2,...,
label_n with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include
auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
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 the LabelAttributeName of the labeling job you want to adjust or verify annotations
of.
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.
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.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 that creates an instance of theLabelingJobStoppingConditions.Builder avoiding
the need to create one manually via LabelingJobStoppingConditions.builder().
When the Consumer completes, SdkBuilder.build() is called
immediately and its result is passed to stoppingConditions(LabelingJobStoppingConditions).stoppingConditions - a consumer that will call methods on LabelingJobStoppingConditions.BuilderstoppingConditions(LabelingJobStoppingConditions)CreateLabelingJobRequest.Builder labelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig labelingJobAlgorithmsConfig)
Configures the information required to perform automated data labeling.
labelingJobAlgorithmsConfig - Configures the information required to perform automated data labeling.default CreateLabelingJobRequest.Builder labelingJobAlgorithmsConfig(Consumer<LabelingJobAlgorithmsConfig.Builder> labelingJobAlgorithmsConfig)
Configures the information required to perform automated data labeling.
This is a convenience that creates an instance of theLabelingJobAlgorithmsConfig.Builder avoiding
the need to create one manually via LabelingJobAlgorithmsConfig.builder().
When the Consumer completes, SdkBuilder.build() is called
immediately and its result is passed to labelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig).labelingJobAlgorithmsConfig - a consumer that will call methods on LabelingJobAlgorithmsConfig.BuilderlabelingJobAlgorithmsConfig(LabelingJobAlgorithmsConfig)CreateLabelingJobRequest.Builder 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).
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 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 that creates an instance of theHumanTaskConfig.Builder avoiding the need to
create one manually via HumanTaskConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to humanTaskConfig(HumanTaskConfig).humanTaskConfig - a consumer that will call methods on HumanTaskConfig.BuilderhumanTaskConfig(HumanTaskConfig)CreateLabelingJobRequest.Builder tags(Collection<Tag> 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.
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.CreateLabelingJobRequest.Builder tags(Tag... 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.
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.CreateLabelingJobRequest.Builder tags(Consumer<Tag.Builder>... 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 that creates an instance of theList.Builder avoiding the need to create
one manually via List#builder() .
When the Consumer completes, List.Builder#build() is called immediately and its result
is passed to #tags(List) .tags - a consumer that will call methods on List.Builder #tags(List) CreateLabelingJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
overrideConfiguration in interface AwsRequest.BuilderCreateLabelingJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
overrideConfiguration in interface AwsRequest.BuilderCopyright © 2022. All rights reserved.