Python连接阿里云接口，实现实时人脸识别与统计

import requestsimport base64import json

access_key_id = "your-access-key-id"access_key_secret = "your-access-key-secret"api_url = "https://api-url"

def face_recognition(image_file):    # 将图片文件转换为Base64编码的字符串    with open(image_file, "rb") as f:        image_data = base64.b64encode(f.read()).decode("ascii")        # 构造请求头部    headers = {        "Content-Type": "application/json",        "Authorization": "APPCODE " + access_key_id + ":" + access_key_secret    }        # 构造请求体    body = {        "image": image_data    }        # 发送请求    response = requests.post(api_url, headers=headers, data=json.dumps(body))        # 解析响应    result = response.json()        # 返回人脸检测和识别的结果    return result

import osimages_dir = "images"result = {}# 遍历images文件夹中的所有图片for filename in os.listdir(images_dir):    if filename.endswith(".jpg") or filename.endswith(".png"):        # 拼接图片文件的完整路径        image_file = os.path.join(images_dir, filename)                # 调用人脸识别函数获取结果        face_result = face_recognition(image_file)                # 根据识别结果统计        for face in face_result["faces"]:            # 获取人脸关键点坐标            landmark = face["landmark"]                        # 统计人脸关键点之和            key_sum = sum(landmark.values())                        # 将结果存放在字典中            if key_sum in result:                result[key_sum] += 1            else:                result[key_sum] = 1# 打印统计结果for key_sum, count in result.items():    print("人脸关键点之和为{}的数量为{}".format(key_sum, count))