글쓰는 감자

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": [
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            "Resource": "arn:aws:logs:*:*:*",
            "Effect": "Allow"
        },
        {
            "Action": [
                "s3:GetObject"
            ],
            "Resource": [
                "arn:aws:s3:::training-bucket-221004/*"
            ],
            "Effect": "Allow"
        },
        {
            "Action": [
                "rekognition:IndexFaces"
            ],
            "Resource": "*",
            "Effect": "Allow"
        },
        {
            "Action": [
                "dynamodb:PutItem"
            ],
            "Resource": "arn:aws:dynamodb:<Region>:<ACCOUNT-ID>:table/family-collection",
            "Effect": "Allow"
        }
    ]
}

import os
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):
    CollectionId = os.getenv("CollectionName")

    response = rekognition.index_faces(
        Image={"S3Object": {"Bucket": bucket, "Name": key}},
        CollectionId=CollectionId,
    )
    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'], encoding='utf-8')
              

    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(os.getenv("DynamoDBTableName"), faceId, personFullName)

        # Print response to console.
        print(response)

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

import boto3
import io
from PIL import Image

rekognition = boto3.client('rekognition', region_name='eu-west-1')
dynamodb = boto3.client('dynamodb', region_name='eu-west-1')
    
image = Image.open("group1.jpeg")
stream = io.BytesIO()
image.save(stream,format="JPEG")
image_binary = stream.getvalue()


response = rekognition.search_faces_by_image(
        CollectionId='family_collection',
        Image={'Bytes':image_binary}                                       
        )
    
for match in response['FaceMatches']:
    print (match['Face']['FaceId'],match['Face']['Confidence'])
        
    face = dynamodb.get_item(
        TableName='family_collection',  
        Key={'RekognitionId': {'S': match['Face']['FaceId']}}
        )
    
    if 'Item' in face:
        print (face['Item']['FullName']['S'])
    else:
        print ('no match found in person lookup')