Serverless computing refers to the concept of building and running applications that do not require server management. It describes a finer-grained deployment model where applications, bundled as one or more functions, are uploaded to a platform and then executed, scaled, and billed in response to the exact demand needed at the moment.

Q

A

• 无需运维 ：用户不需要再关心服务器资源及复杂运行环境；
• 弹性伸缩 ：根据请求并发量实时自动扩缩资源；
• 按需付费 ：为实际消耗资源付费，无占用不收费，运行成本更低；

Step1：创建函数

#coding=utf-8



import json

import base64

import os



from jdcloud_apim_sdk.core.credential import Credential

from jdcloud_apim_sdk.core.config import Config

from jdcloud_apim_sdk.core.const import SCHEME_HTTPS, SCHEME_HTTP



from ai_sdk.apis.ai_face_detect_attr_request import *

from ai_sdk.client.ai_Face_Detect_Attr_client import *



'''

AI

'''



def handler(event,context):

    if not bool(event):

        result = {

            'statusCode': 200,

            'headers': {},

            'body': "",

        }



        return result



    # get request data

    print('AI Request')

    # get request data

    body = event['detail']['body']

    body = json.loads(body)



    if type(body) == unicode:

      body = json.loads(body)



    # request

    access_key = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'

    secret_key = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'

    credential = Credential(access_key, secret_key)

    config = Config('aiapi.jdcloud.com', scheme=SCHEME_HTTPS)

    client = AiFaceDetectAttrClient(credential, config)



    header = dict()

    parameters = {

            'return_landmark':0,

            'return_attr':1,

            'face_detect_num':0

            }

    data = body.get('data', "")

    imageBase64Data = 'imageBase64=' + data.decode("utf-8")

    s = imageBase64Data.encode('utf-8')



    ai_face_detect_attr_request = AiFaceDetectAttrRequest(parameters, s, header)

    AiFaceDetectAttr_response = client.send(ai_face_detect_attr_request)



    respBody = {'code': 0, 'data': AiFaceDetectAttr_response.json()}

    resp = json.dumps(respBody)

    result = {

        'statusCode': 200,

        'headers': {},

        'body': resp,

    }



    # statistics

    resp = AiFaceDetectAttr_response.json()

    if resp['result']['status'] == 0:

      attrs = json.loads(resp['result']['result'])

      if len(attrs['faces']) > 0:

        if attrs['faces'][0]['faceAttribute']['gender'] == 0:

          print("lookup ai attr success, this is a woman")

        else:

          print("lookup ai attr success, this is a man")



    return result

Step2：测试函数

Step3：对接 API 网关

Step4：测试验证上线