def lambda_handler()

in sagemaker/ground_truth/post-label/lambda_function.py [0:0]

• 38 lines of code
• 4 McCabe index (conditional complexity)

def lambda_handler(event, context):
    print("Received event: " + json.dumps(event, indent=2))

    labeling_job_arn = event["labelingJobArn"]
    label_attribute_name = event["labelAttributeName"]

    consolidated_labels = []

    s3_uri = event['payload']['s3Uri']
    bucket, key = split_s3_path(s3_uri)
    
    s3 = boto3.client('s3')
    textFile = s3.get_object(Bucket=bucket, Key=key)
    filecont = textFile['Body'].read()
    annotations = json.loads(filecont)
    
    for dataset in annotations:
        for annotation in dataset['annotations']:
            new_annotation = json.loads(annotation['annotationData']['content'])
            
            texts = []
            for label in new_annotation['transcription']['polygons']:
                text, line_num, word_type = parse_label(label["label"])
                vertices = label["vertices"]
                texts.append({
                    "text": text,
                    "line_num": line_num,
                    "type": word_type,
                    "bb": vertices
                })

            label = {
                'datasetObjectId': dataset['datasetObjectId'],
                'consolidatedAnnotation' : {
                    'content': {
                        label_attribute_name: {
                            'texts': texts,
                            'imageSource': dataset['dataObject']
                            }
                        }
                    }
                }
            consolidated_labels.append(label)
    print("Consolidated labels \n {}".format(consolidated_labels))
    return consolidated_labels