rqw5Mx2J

1from __future__ import print_function
2
3import boto3
4from decimal import Decimal
5import json
6import urllib
7
8print('Loading function')
9
10rekognition = boto3.client('rekognition')
11
12def detect_faces(bucket, key):
13    response = rekognition.detect_faces(Image={"S3Object": {"Bucket": bucket, "Name": key}})
14    return response
15
16def lambda_handler(event, context):
17
18    def publish_message_to_queue(message):
19        queue = 'releasethedrone'
20        sqs = boto3.client('sqs')
21        queue_url = (sqs.get_queue_url(QueueName=queue))['QueueUrl']
22        response = sqs.send_message(QueueUrl=queue_url,MessageBody=message)
23
24        if response['ResponseMetadata']['HTTPStatusCode'] != 200:
25            raise Exception('Non200Response: A non-200 http response was received.')
26            
27    bucket = event['Records'][0]['s3']['bucket']['name']
28    key = urllib.unquote_plus(event['Records'][0]['s3']['object']['key'].encode('utf8'))
29    try:
30        # Calls rekognition DetectFaces API to detect faces in S3 object
31        response = detect_faces(bucket, key)
32
33        print(response)
34        if response['Confidence'] > 80:
35	        publish_message_to_queue(face)
36        return response
37    except Exception as e:
38        print(e)
39        print("Error processing object {} from bucket {}. ".format(key, bucket) +
40              "Make sure your object and bucket exist and your bucket is in the same region as this function.")
41        raise e