Step 2: Create a Labeling Job
In this step you use the console to create a labeling job. You tell Amazon SageMaker Ground Truth the Amazon S3 bucket where the manifest file is stored and configure the parameters for the job. For more information about storing data in an Amazon S3 bucket, see Use Input and Output Data.
To create a labeling job
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Open the SageMaker console at https://console.aws.amazon.com/sagemaker/
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From the left navigation, choose Labeling jobs.
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Choose Create labeling job to start the job creation process.
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In the Job overview section, provide the following information:
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Job name – Give the labeling job a name that describes the job. This name is shown in your job list. The name must be unique in your account in an AWS Region.
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Label attribute name – Leave this unchecked as the default value is the best option for this introductory job.
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Input data setup – Select Automated data setup. This option allows you to automatically connect to your input data in S3.
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S3 location for input datasets – Enter the S3 location where you added the images in step 1.
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S3 location for output datasets – The location where your output data is written in S3.
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Data type – Use the drop down menu to select Image. Ground Truth will use all images found in the S3 location for input datasets as input for your labeling job.
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IAM role – Create or choose an IAM role with the AmazonSageMakerFullAccess IAM policy attached.
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In the Task type section, for the Task category field, choose Image.
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In the Task selection choose Bounding box.
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Choose Next to move on to configuring your labeling job.
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