Rekognition Filter Low Quality Image Sample

import boto3

from io import BytesIO
from PIL import Image

if __name__== "__main__":
    session = boto3.Session(region_name="ap-southeast-1")

    rekognition = session.client('rekognition')
    s3 = session.client('s3')

    # Detect faces to filter image
    response = rekognition.detect_faces(
        Image={
            'S3Object': {
                'Bucket': 'julo-test-bucket',
                'Name': '2.jpeg',
            },
        },
    )

    # Sample simple heuristic rule
    if response['FaceDetails'][0]['Quality']['Brightness'] > 30 and \
        response['FaceDetails'][0]['Quality']['Sharpness'] > 30 and \
        response['FaceDetails'][0]['Quality']['Brightness'] < 70 and \
        response['FaceDetails'][0]['Quality']['Sharpness'] < 70:
        # Index filtered face

        print("Test")

        file_byte_string = s3.get_object(Bucket='ulo-test-bucket', Key='2.jpeg')['Body'].read()

        img = Image.open(BytesIO(file_byte_string))
        img_width, img_height = img.size
        left = response['FaceDetails'][0]['BoundingBox']['Left'] * img_width
        top = response['FaceDetails'][0]['BoundingBox']['Top'] * img_height
        width = response['FaceDetails'][0]['BoundingBox']['Width'] * img_width
        height = response['FaceDetails'][0]['BoundingBox']['Height'] * img_height
        cropped = img.crop((left , top , (left + width), (top + height)))
        imgByteArr = BytesIO()
        cropped.save(imgByteArr, format=img.format)
        imgByteArr = imgByteArr.getvalue()
        response = rekognition.index_faces(
            CollectionId='julo',
            Image={
                'Bytes': imgByteArr,
            }
        )