Sagemaker Labelling Jobs

Getting Started with Sagemaker Labelling Jobs

1. Create a private team under AmazonSagemaker/Labellingworkforces from Sagemaker UI.
2. Go to Workers Section and send invites to new workers.
3. Select the private team which you created in step 1, click on workers and add workers to the team.
4. Once done, follow the steps below to execute a labelling job script

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Fill the config with appropriate params value Sample Config Link

Parameters Description :

• iam_role : Sagemaker Execution Role ARN
• region_name : Region in which resources needs to be created. For eg. ap-southeast-1, ap-northeast-1 etc
• private_work_team_arn : Arn of the private work team created in Step 1 above.
• pre_human_arn : Human Labeling ARN for a particular region and particular task. We have to use Object Detection ones. Link. For eg : For ap-northeast-1 and object detection task, pre_human_arn = arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
• acs_arn : For ACS ARN for Bounding Box Task, follow Link
• bucket_name : name of the s3 bucket where the datasets are stored
• dataset_path : relative path of the dataset to be labelled wrt the bucket
• manifest_upload_dir : s3 directory to upload the manifest file of the input dataset
• manifest_file_name : name of the input dataset manifest file
• label_list : list of labels which are to be annotated
• label_file_name : name of the json file containing label info
• label_file_upload_dir : s3 directory to upload label file