AWS SAMでAWS Lambdaを構築し、Amazon Rekognitionを使った写真解析AIのLINE Botを作成してみた！【サーバーレスアプリケーション】

aws configure

├─ src
│  ├─ mylinebot.py
│  └─ requirements.txt
└─ template.json

"""
Line Bot
"""

import os

from linebot import (
    LineBotApi, WebhookHandler
)
from linebot.models import (
    MessageEvent, TextMessage, TextSendMessage, ImageMessage,
)

import boto3

handler = WebhookHandler(os.getenv('LINE_CHANNEL_SECRET'))
line_bot_api = LineBotApi(os.getenv('LINE_CHANNEL_ACCESS_TOKEN'))

client = boto3.client('rekognition')


def lambda_handler(event, context):
    headers = event["headers"]
    body = event["body"]

    # get X-Line-Signature header value
    signature = headers['x-line-signature']

    # handle webhook body
    handler.handle(body, signature)

    return {"statusCode": 200, "body": "OK"}


def all_happy(result):
    # 検出した顔がすべてHappyならTrueを返却
    for detail in result["FaceDetails"]:
        if most_confident_emotion(detail["Emotions"]) != "HAPPY":
            return False
    return True


def most_confident_emotion(emotions):
    """
    複数ある感情のうち、もっとも確度が高い感情を返却する
    :param emotions:
    :return:
    """
    max_conf = 0
    result = ""
    for e in emotions:
        if max_conf < e["Confidence"]:
            max_conf = e["Confidence"]
            result = e["Type"]
    return result


@handler.add(MessageEvent, message=TextMessage)
def handle_text_message(event):
    """ TextMessage handler """
    input_text = event.message.text

    line_bot_api.reply_message(
        event.reply_token,
        TextSendMessage(text=input_text))


@handler.add(MessageEvent, message=ImageMessage)
def handle_image_message(event):
    # ユーザから送られてきた画像を一時ファイルとして保存
    message_content = line_bot_api.get_message_content(event.message.id)
    # lambdaで保存できるディレクトリは「/tmp」配下のみ
    file_path = "/tmp/sent-image.jpg"
    with open(file_path, 'wb') as fd:
        for chunk in message_content.iter_content():
            fd.write(chunk)

    # Rekognition で感情分析
    with open(file_path, 'rb') as fd:
        sent_image_binary = fd.read()
        response = client.detect_faces(Image={"Bytes": sent_image_binary}, Attributes=["ALL"])

    print(response)

    # 応答するメッセージを決める
    if all_happy(response):
        message = "みんな楽しそうですね！！"
    else:
        message = "もう一度写真を取り直してみてはいかがでしょうか。"

    # 応答を返す
    line_bot_api.reply_message(
        event.reply_token,
        TextSendMessage(text=message)
    )

    # file_pathの画像を削除
    os.remove(file_path)

line-bot-sdk
boto3

{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Transform": "AWS::Serverless-2016-10-31",
  "Parameters": {
    "LineChannelAccessToken": {"Type": "String", "Description": "LINEのチャネルアクセストークン"},
    "LineChannelSecret": {"Type": "String", "Description": "LINEのチャネルシークレット"}
  },
  "Resources": {
    "EndPointFunction": {
      "Type": "AWS::Serverless::Function",
      "Properties": {
        "Runtime": "python3.9",
        "CodeUri": "src",
        "Handler": "mylinebot.lambda_handler",
        "Environment": {"Variables": {
            "LINE_CHANNEL_ACCESS_TOKEN": {"Ref": "LineChannelAccessToken"},
            "LINE_CHANNEL_SECRET": {"Ref": "LineChannelSecret"}
        }},
        "Policies": [{"RekognitionDetectOnlyPolicy": {}}],
        "Events": {
          "API": {
            "Type": "Api",
            "Properties": {"Path": "/api_endpoint", "Method": "post"}
          }
        }
      }
    }
  },
  "Outputs": {
    "ApiEndpointURL": {
      "Description": "API Endpoint URL",
      "Value": {"Fn::Sub": "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/${ServerlessRestApi.Stage}/api_endpoint"}
    }
  }
}

sam build -t template.json

sam deploy --guided