Real-Time Face Detection with Raspberry Pi, Kinesis Video Streams, and AWS Rekognition

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AWSTemplateFormatVersion: 2010-09-09
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Transform: AWS::Serverless-2016-10-31
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Description: face-detector-using-kinesis-video-streams
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Resources:
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  Function:
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    Type: AWS::Serverless::Function
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    Properties:
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      FunctionName: face-detector-function
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      CodeUri: src/
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      Handler: app.lambda_handler
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      Runtime: python3.11
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      Architectures:
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        - arm64
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      Timeout: 3
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      MemorySize: 128
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      Role: !GetAtt FunctionIAMRole.Arn
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      Events:
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        KinesisEvent:
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          Type: Kinesis
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          Properties:
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            Stream: !GetAtt KinesisStream.Arn
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            MaximumBatchingWindowInSeconds: 10
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            MaximumRetryAttempts: 3
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            StartingPosition: LATEST
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  FunctionIAMRole:
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    Type: AWS::IAM::Role
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    Properties:
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      RoleName: face-detector-function-role
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      AssumeRolePolicyDocument:
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        Version: 2012-10-17
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        Statement:
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          - Effect: Allow
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            Principal:
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              Service: lambda.amazonaws.com
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            Action: sts:AssumeRole
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      ManagedPolicyArns:
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        - arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole
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        - arn:aws:iam::aws:policy/service-role/AWSLambdaKinesisExecutionRole
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      Policies:
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        - PolicyName: policy
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          PolicyDocument:
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            Version: 2012-10-17
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            Statement:
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              - Effect: Allow
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                Action:
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                  - kinesisvideo:GetHLSStreamingSessionURL
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                  - kinesisvideo:GetDataEndpoint
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                Resource: !GetAtt KinesisVideoStream.Arn
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  KinesisVideoStream:
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    Type: AWS::KinesisVideo::Stream
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    Properties:
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      Name: face-detector-kinesis-video-stream
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      DataRetentionInHours: 24
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  RekognitionCollection:
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    Type: AWS::Rekognition::Collection
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    Properties:
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      CollectionId: FaceCollection
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  RekognitionStreamProcessor:
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    Type: AWS::Rekognition::StreamProcessor
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    Properties:
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      Name: face-detector-rekognition-stream-processor
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      KinesisVideoStream:
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        Arn: !GetAtt KinesisVideoStream.Arn
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      KinesisDataStream:
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        Arn: !GetAtt KinesisStream.Arn
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      RoleArn: !GetAtt RekognitionStreamProcessorIAMRole.Arn
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      FaceSearchSettings:
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        CollectionId: !Ref RekognitionCollection
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        FaceMatchThreshold: 80
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      DataSharingPreference:
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        OptIn: false
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  KinesisStream:
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    Type: AWS::Kinesis::Stream
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    Properties:
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      Name: face-detector-kinesis-stream
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      StreamModeDetails:
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        StreamMode: ON_DEMAND
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  RekognitionStreamProcessorIAMRole:
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    Type: AWS::IAM::Role
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    Properties:
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      RoleName: face-detector-rekognition-stream-processor-role
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      AssumeRolePolicyDocument:
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        Version: 2012-10-17
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        Statement:
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          - Effect: Allow
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            Principal:
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              Service: rekognition.amazonaws.com
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            Action: sts:AssumeRole
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      ManagedPolicyArns:
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        - arn:aws:iam::aws:policy/service-role/AmazonRekognitionServiceRole
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      Policies:
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        - PolicyName: policy
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          PolicyDocument:
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            Version: 2012-10-17
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            Statement:
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              - Effect: Allow
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                Action:
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                  - kinesis:PutRecord
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                  - kinesis:PutRecords
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                Resource:
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                  - !GetAtt KinesisStream.Arn

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import base64
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import json
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import logging
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from datetime import datetime, timedelta, timezone
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from functools import cache
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import boto3
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JST = timezone(timedelta(hours=9))
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kvs_client = boto3.client('kinesisvideo')
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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def lambda_handler(event: dict, context: dict) -> dict:
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  for record in event['Records']:
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    base64_data = record['kinesis']['data']
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    stream_processor_event = json.loads(base64.b64decode(base64_data).decode())
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    # Refer to https://docs.aws.amazon.com/rekognition/latest/dg/streaming-video-kinesis-output.html for details on the structure.
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    if not stream_processor_event['FaceSearchResponse']:
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      continue
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    logger.info(stream_processor_event)
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    url = get_hls_streaming_session_url(stream_processor_event)
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    logger.info(url)
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  return {
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    'statusCode': 200,
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  }
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@cache
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def get_kvs_am_client(api_name: str, stream_arn: str):
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  # Retrieves the data endpoint for the stream.
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  # See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/kinesisvideo/client/get_data_endpoint.html
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  endpoint = kvs_client.get_data_endpoint(
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    APIName=api_name.upper(),
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    StreamARN=stream_arn
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  )['DataEndpoint']
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  return boto3.client('kinesis-video-archived-media', endpoint_url=endpoint)
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def get_hls_streaming_session_url(stream_processor_event: dict) -> str:
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  # Generates an HLS streaming URL for the video stream.
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  # See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/kinesis-video-archived-media/client/get_hls_streaming_session_url.html
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  kinesis_video = stream_processor_event['InputInformation']['KinesisVideo']
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  stream_arn = kinesis_video['StreamArn']
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  kvs_am_client = get_kvs_am_client('get_hls_streaming_session_url', stream_arn)
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  start_timestamp = datetime.fromtimestamp(kinesis_video['ServerTimestamp'], JST)
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  end_timestamp = datetime.fromtimestamp(kinesis_video['ServerTimestamp'], JST) + timedelta(minutes=1)
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  return kvs_am_client.get_hls_streaming_session_url(
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    StreamARN=stream_arn,
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    PlaybackMode='ON_DEMAND',
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    HLSFragmentSelector={
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      'FragmentSelectorType': 'SERVER_TIMESTAMP',
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      'TimestampRange': {
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        'StartTimestamp': start_timestamp,
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        'EndTimestamp': end_timestamp,
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      },
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    },
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    ContainerFormat='FRAGMENTED_MP4',
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    Expires=300,
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  )['HLSStreamingSessionURL']