Rekognition Indexer

gistfile1.txt

'''
A trigger function for AWS Lambda that listens for object creation in an S3 bucket, 
takes images, finds faces, and tags with metadata into a DDB table.
'''

import boto3
from decimal import Decimal
import json
import urllib

print('Loading function')

dynamodb = boto3.client('dynamodb')
s3 = boto3.client('s3')
rekognition = boto3.client('rekognition')

# --------------- Helper Functions ------------------

def index_faces(bucket, key):

    response = rekognition.index_faces(
        Image={"S3Object":
            {"Bucket": bucket,
            "Name": key}},
            CollectionId="family_and_friends")
    return response
    
def update_index(tableName,faceId, fullName):
    response = dynamodb.put_item(
        TableName=tableName,
        Item={
            'RekognitionId': {'S': faceId},
            'FullName': {'S': fullName}
            }
        ) 
    
# --------------- Main handler ------------------

def lambda_handler(event, context):

    # Get the object from the event
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = urllib.parse.unquote_plus(
        event['Records'][0]['s3']['object']['key']
    )

    try:

        # Calls Amazon Rekognition IndexFaces API to detect faces in S3 object 
        # to index faces into specified collection
        
        response = index_faces(bucket, key)
        
        # Commit faceId and full name object metadata to DynamoDB
        
        if response['ResponseMetadata']['HTTPStatusCode'] == 200:
            faceId = response['FaceRecords'][0]['Face']['FaceId']

            ret = s3.head_object(Bucket=bucket,Key=key)
            personFullName = ret['Metadata']['fullname']

            update_index('rekognition_family_and_friends',faceId,personFullName)

        # Print response to console
        print(response)
        return response
        
    except Exception as e:
        print(e)
        print("Error processing object {} from bucket {}. ".format(key, bucket))
        raise e