SageMaker Labelling Job: Creating a labelling job for annotating images with a bounding box fails

[kd-jukanti]

Hi,

I am trying to create a labelling job on SageMaker for labelling the images by drawing a bounding box around it. I have successfully created one from the AWS console but I am unable to make it successful using the boto3 function create_labeling_job() .

Here is the code and the function parameters I used. They are similar to the example from the GitHub amazon-sagemaker-examples but unfortunately it did not work as expected. I can create the job, label the images and the status of the job gets completed. But the output manifest file does not store the annotations numbers.

`
task_description = "Draw bounding box around the images"
task_keywords = ['Images', 'bounding boxes', 'object detection']
task_title = "Bounding Box task"
job_name = "test-labeling-job"
acs_arn = "arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox"
prehuman_arn = "arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox"

human_task_config = {
"AnnotationConsolidationConfig": {
"AnnotationConsolidationLambdaArn": acs_arn,
},
"PreHumanTaskLambdaArn": prehuman_arn,
"MaxConcurrentTaskCount": 1000, # 200 images will be sent at a time to the workteam.
"NumberOfHumanWorkersPerDataObject": 1, # 3 separate workers will be required to label each image.
"TaskAvailabilityLifetimeInSeconds": 864000, # Your workteam has 6 hours to complete all pending tasks.
"TaskDescription": task_description,
"TaskKeywords": task_keywords,
"TaskTimeLimitInSeconds": 3600, # Each image must be labeled within 5 minutes.
"TaskTitle": task_title,
"UiConfig": {
"UiTemplateS3Uri": "s3://bucket-name/bounding-box.liquid.html",
},
"WorkteamArn": "arn:aws:sagemaker:eu-west-1:xxxxxxxxx:workteam/private-crowd/Labellers"
}

ground_truth_request = {
"InputConfig": {
"DataSource": {
"S3DataSource": {
"ManifestS3Uri": "s3://bucket-name/manifest-vic-2.manifest",
}
},
"DataAttributes": {
"ContentClassifiers": []
},
},
"OutputConfig": {
"S3OutputPath": "s3://sagemaker-bucket-name/folder-name-07-12-2022/",
},
"StoppingConditions":{
'MaxPercentageOfInputDatasetLabeled': 100
},
"HumanTaskConfig": human_task_config,
"LabelingJobName": job_name,
"RoleArn": "arn:aws:iam::xxxxxxxxx:role/service-role/AmazonSageMaker-ExecutionRole-xxxxxxxxxx",
"LabelAttributeName": job_name,
"LabelCategoryConfigS3Uri": "s3://bucket-name/label-config.json",
}

sagemaker_client = boto3.client("sagemaker")
sagemaker_client.create_labeling_job(**ground_truth_request)`

My label config file looks like the following:
{ "document-version": "2018-11-28", "labels": [{"label": "animal"}, {"label": "no-animal"}] }

The manifest file looks like:

{'source-ref': 's3://sagemaker-inout-folder/2022-10-10-12:50:59/A.jpg'} {'source-ref': 's3://sagemaker-inout-folder/2022-10-10-12:50:59/B.jpg'} {'source-ref': 's3://sagemaker-inout-folder/2022-10-10-12:50:59/C.jpg'}

And the HTML file is a standard crowd liquid files taken from the github sagemaker examples:

<script src="https://assets.crowd.aws/crowd-html-elements.js"></script>

Use the bounding box tool to draw boxes around the requested target of interest:

1. Draw a rectangle using your mouse over each instance of the target.
2. Make sure the box does not cut into the target, leave a 2 - 3 pixel margin
3. When targets are overlapping, draw a box around each object, include all contiguous parts of the target in the box. Do not include parts that are completely overlapped by another object.
4. Do not include parts of the target that cannot be seen, even though you think you can interpolate the whole shape of the target.
5. Avoid shadows, they're not considered as a part of the target.
6. If the target goes off the screen, label up to the edge of the image.

<short-instructions>
  Draw boxes around the requested target of interest.
</short-instructions>

Once this function is executd, I am able to label the images and the labelling job status changes to 'COMPLETE'. But the output manifest files looks like the following:

{ "source-ref": "s3://sagemaker-inout-folder/2022-10-10-12:50:59/A.jpg", "test-labeling-job": { "image_size": [ { "width": 0, "height": 0, "depth": 3 } ], "annotations": [] }, "test-labeling-job-metadata": { "objects": [], "class-map": {}, "type": "groundtruth/object-detection", "human-annotated": "yes", "creation-date": "2022-12-01T08:09:07.933647", "job-name": "labeling-job/test-labeling-job" } }

The image size is weird and the annotations are empty.

Can someone help me if I am doing anything wrong and how do I make this work?

Thank you in advance!

[kd-jukanti]

The problem is resolved. It seems that in the label config file, the "document-version": "2018-11-28" is incorrect although this was what was mentioned in the boto3 documentation. The correct document version is "2021-05-13". By changing this, the labelling job was able to record the annotations in the output manifest file.

I hope this would help others who are trying to the same since the official boto3 documentation has a different version given which does not work.