百度 AI 开放平台接口调用

百度 AI 开放平台地址 http://ai.baidu.com/tech/face
1，注册登录百度账号
2，创建应用

3，看接口文档，参考接口请求代码示例
接口文档地址http://ai.baidu.com/docs#/Face-Detect-V3/top

Face++ 人工智能开放平台接口调用

方法参考以上

代码示例

# -*- coding: utf-8 -*-
"""
测试图像中人物年龄，调用百度和face++的结果做对比
代码中key ,secret等内容保密，已删减，代码运行时请填写自己申请的key，secret等值
"""

import urllib.error
import time
import json
import requests
import base64
import glob
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)


def face_api(file_path):
    try:
        http_url = 'https://api-cn.faceplusplus.com/facepp/v3/detect'
        key = ""                  
        secret = ""
        boundary = '----------%s' % hex(int(time.time() * 1000))
        data = []
        data.append('--%s' % boundary)
        data.append('Content-Disposition: form-data; name="%s"\r\n' % 'api_key')
        data.append(key)
        data.append('--%s' % boundary)
        data.append('Content-Disposition: form-data; name="%s"\r\n' % 'api_secret')
        data.append(secret)
        data.append('--%s' % boundary)
        ff = requests.get(file_path).content
        data.append('Content-Disposition: form-data; name="%s"; filename=" "' % 'image_file')
        data.append('Content-Type: %s\r\n' % 'application/octet-stream')
        data.append(ff)
        data.append('--%s' % boundary)
        data.append('Content-Disposition: form-data; name="%s"\r\n' % 'return_landmark')
        data.append('1')
        data.append('--%s' % boundary)
        data.append('Content-Disposition: form-data; name="%s"\r\n' % 'return_attributes')
        data.append(
            "gender,age,smiling,headpose,facequality,blur,eyestatus,emotion,ethnicity,beauty,mouthstatus,eyegaze,skinstatus")
        data.append('--%s--\r\n' % boundary)
        for i, d in enumerate(data):
            if isinstance(d, str):
                data[i] = d.encode('utf-8')
        http_body = b'\r\n'.join(data)
        # build http request
        req = urllib.request.Request(url=http_url, data=http_body)
        # header
        req.add_header('Content-Type', 'multipart/form-data; boundary=%s' % boundary)
        # post data to server
        resp = urllib.request.urlopen(req, timeout=20)
        # get response
        qrcont = resp.read()
        result = json.loads(qrcont.decode('utf-8'))
        if result["faces"]:
            age = result["faces"][0]["attributes"]["age"]["value"]
            return age
        else:
            pass
    except urllib.error.HTTPError as e:
        pass


def baidu_api(file_path):
    # client_id 为官网获取的AK， client_secret 为官网获取的SK
    host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=kKA8eAY&client_secret=l6bfP'
    headers = {'Content-Type': 'application/json', 'charset': 'UTF-8'}
    r = requests.get(host, headers=headers, verify=False)
    access_token = r.json()["access_token"]
    # 二进制方式打开图片文件
    # img = base64.b64encode(file_path.read())
    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
    params = {"image": file_path, "image_type": "URL", "face_field": "age"}
    request_url = request_url + "?access_token=" + access_token
    header = {'Content-Type': 'application/json'}
    res = requests.post(request_url, headers=header, data=params, verify=False)
    if res:
        if res.json()["error_code"] == 0:
            age = res.json()["result"]["face_list"][0]["age"]
            return age
        else:
            pass


if __name__ == '__main__':
    import pandas as pd
    with open("/home/ling/skin_age/skin_Age.txt", 'r') as f:
        file = f.readlines()
    num = 1
    result_list = []
    try:
        for url in file:
            url = url.strip()
            try:
                age_1 = baidu_api(url)
                age_2 = face_api(url)
            except Exception as e:
                print(e)
                result_list.append([url, None, None])
            else:
                print("{} {} {}    -- {}".format(url, age_1, age_2, num))
                num += 1
                result_list.append([url, age_1, age_2])
    finally:
        dt = pd.DataFrame(result_list, columns=["image", "baidu_age", "face_age"])
        dt.to_excel("age_result.xlsx")                   # 安装好openpyxl包

部分数据结果查看

有部分调用失败情况，可能图片大小超过出接口限制，可能网络超时。商用付费的应该会比较稳定点。
从数据上看两者年龄相差还是有点大。相差超过 10 岁的数据也有一些。