ラベル付けジョブを作成 (API)

以下は、米国東部 (バージニア北部) リージョンで、プライベートワークフォースを使用して組み込みタスクタイプのラベル付けジョブを作成する AWS Python SDK (Boto3) リクエストの例です。赤色の斜体テキストを、ラベル付けジョブのリソースと仕様に置き換えます。

response = client.create_labeling_job(
    LabelingJobName="example-labeling-job",
    LabelAttributeName="label",
    InputConfig={
        'DataSource': {
            'S3DataSource': {
                'ManifestS3Uri': "s3://bucket/path/manifest-with-input-data.json"
            }
        },
        'DataAttributes': {
            'ContentClassifiers': [
                "FreeOfPersonallyIdentifiableInformation"|"FreeOfAdultContent",
            ]
        }
    },
    OutputConfig={
        'S3OutputPath': "s3://bucket/path/file-to-store-output-data",
        'KmsKeyId': "string"
    },
    RoleArn="arn:aws:iam::*:role/*",
    LabelCategoryConfigS3Uri="s3://bucket/path/label-categories.json",
    StoppingConditions={
        'MaxHumanLabeledObjectCount': 123,
        'MaxPercentageOfInputDatasetLabeled': 123
    },
    HumanTaskConfig={
        'WorkteamArn': "arn:aws:sagemaker:region:*:workteam/private-crowd/*",
        'UiConfig': {
            'UiTemplateS3Uri': "s3://bucket/path/custom-worker-task-template.html"
        },
        'PreHumanTaskLambdaArn': "arn:aws:lambda:us-east-1:432418664414:function:PRE-tasktype",
        'TaskKeywords': [
            "Images",
            "Classification",
            "Multi-label"
        ],
        'TaskTitle': "Multi-label image classification task",
        'TaskDescription': "Select all labels that apply to the images shown",
        'NumberOfHumanWorkersPerDataObject': 1,
        'TaskTimeLimitInSeconds': 3600,
        'TaskAvailabilityLifetimeInSeconds': 21600,
        'MaxConcurrentTaskCount': 1000,
        'AnnotationConsolidationConfig': {
            'AnnotationConsolidationLambdaArn': "arn:aws:lambda:us-east-1:432418664414:function:ACS-"
        },
    Tags=[
        {
            'Key': "string",
            'Value': "string"
        },
    ]
)

以下は、Amazon Mechanical Turk ワークフォース を使用して、米国東部 (バージニア北部) リージョンに組み込みタスクタイプのラベル付けジョブを作成する AWS CLI リクエストの例です。 https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management-public.html詳細については、AWS CLI コマンドリファレンスの start-human-loop を参照してください。赤色の斜体テキストを、ラベル付けジョブのリソースと仕様に置き換えます。

$ aws --region us-east-1 sagemaker create-labeling-job \
--labeling-job-name "example-labeling-job" \
--label-attribute-name "label" \
--role-arn "arn:aws:iam::account-id:role/role-name" \
--input-config '{
        "DataAttributes": {
            "ContentClassifiers": [
                "FreeOfPersonallyIdentifiableInformation",
                "FreeOfAdultContent"
            ]
        },
        "DataSource": {
            "S3DataSource": {
                "ManifestS3Uri": "s3://bucket/path/manifest-with-input-data.json"
            }
        }
    }' \
--output-config '{
        "KmsKeyId": "",
        "S3OutputPath": "s3://bucket/path/file-to-store-output-data"
    }' \
--human-task-config '{
        "AnnotationConsolidationConfig": {
            "AnnotationConsolidationLambdaArn": "arn:aws:lambda:us-east-1:432418664414:function:ACS-"
        },
        "TaskAvailabilityLifetimeInSeconds": 21600,
        "TaskTimeLimitInSeconds": 3600,
        "NumberOfHumanWorkersPerDataObject": 1,
        "PreHumanTaskLambdaArn":  "arn:aws:lambda:us-east-1:432418664414:function:PRE-tasktype",
        "WorkteamArn": "arn:aws:sagemaker:us-east-1:394669845002:workteam/public-crowd/default",
        "PublicWorkforceTaskPrice": {
            "AmountInUsd": {
                "Dollars": 0,
                "TenthFractionsOfACent": 6,
                "Cents": 3
            }
        },
        "TaskDescription": "Select all labels that apply to the images shown",
        "MaxConcurrentTaskCount": 1000,
        "TaskTitle": "Multi-label image classification task",,
        "TaskKeywords": [
            "Images",
            "Classification",
            "Multi-label"
        ],
        "UiConfig": {
            "UiTemplateS3Uri": "s3://bucket/path/custom-worker-task-template.html"
        }
    }'