SageMaker Labelling job: Create_labelling_job() fails - amazon-web-services

Question

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>
<crowd-form>
<crowd-bounding-box
name="annotatedResult"
src="{{ task.input.taskObject | grant_read_access }}"
header="Draw bounding boxes around all the cats and dogs in this image"
labels="['Animal', 'No-animal']"
>
<full-instructions header="Bounding Box Instructions" >
<p>Use the bounding box tool to draw boxes around the requested target of interest:</p>
<ol>
<li>Draw a rectangle using your mouse over each instance of the target.</li>
<li>Make sure the box does not cut into the target, leave a 2 - 3 pixel margin</li>
<li>
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.
</li>
<li>
Do not include parts of the target that cannot be seen,
even though you think you can interpolate the whole shape of the target.
</li>
<li>Avoid shadows, they're not considered as a part of the target.</li>
<li>If the target goes off the screen, label up to the edge of the image.</li>
</ol>
</full-instructions>
<short-instructions>
Draw boxes around the requested target of interest.
</short-instructions>
</crowd-bounding-box>
</crowd-form>
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!