基于Python的百度AI人脸识别API接口（可用于OpenCV-Python人脸识别）
基于Python的百度AI人脸识别API接口（可用于OpenCV-Python人脸识别）
资源：
https://download.csdn.net/download/weixin_53403301/43644312
之前的项目：
【最新】基于OpenCV的Python人脸识别、检测、框选（遍历目录下所有照片依次识别 视频随时标注）
https://blog.csdn.net/weixin_53403301/article/details/119422635
基于OpenCV-Python的树莓派人脸识别及89C52单片机控制系统设计（指定照片进行识别、遍历目录下所有照片依次识别）
https://blog.csdn.net/weixin_53403301/article/details/118575731
直接上代码：
# -*- coding: utf-8 -*-
"""
Created on Mon May 31 23:40:16 2021
@author: ZHOU
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import requests # 调用 requests的HTTP协议库
import os # 调用os多操作系统接口库
import base64 # 调用base64编码库
import json # 调用JavaScript Object Notation数据交换格式
ACCESS_TOKEN = ''
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) #去掉文件名,返回目录
# ID,KEY的配置信息
INFO_CONFIG = {
'ID': '15050553',
'API_KEY': 'rlRrtRL5oRdXGh71jgg1OmyN',
'SECRET_KEY': 'dK5TpuTAZn2nw5eVpspZLmF5Qs1Uu8A1'
}
"""
若API出错 则改为：
INFO_CONFIG = {
'ID': '15050553',
'API_KEY': 'rlRrtRL5oRdXGh71jgg1OmyN',
'SECRET_KEY': 'dK5TpuTAZn2nw5eVpspZLmF5Qs1Uu8A1'
}
或：
INFO_CONFIG = {
'ID': '15788358',
'API_KEY': 'ohtGa5yYoQEZ8Try8lnL99UK',
'SECRET_KEY': 'qaDjyuXkf5MZ28g5C8pwFngDZenhswC3'
}
"""
# URL配置
URL_LIST_URL = {
# ACCESS_TOKEN_URL用于获取ACCESS_TOKEN, POST请求,
# grant_type必须参数,固定为client_credentials,client_id必须参数,应用的API Key,client_secre 必须参数,应用的Secret Key.
'ACCESS_TOKEN_URL': 'https://aip.baidubce.com/oauth/2.0/token?' + 'grant_type=client_credentials&client_id={API_KEYS}&client_secret={SECRET_KEYS}&'.format(
API_KEYS=INFO_CONFIG['API_KEY'], SECRET_KEYS=INFO_CONFIG['SECRET_KEY']),
# 登入人脸识别机器学习库
'FACE_PLATE': 'https://aip.baidubce.com/rest/2.0/face/v3/match',
}
class AccessTokenSuper(object):
pass
class AccessToken(AccessTokenSuper): # 定义登陆API大类
def getToken(self):
accessToken = requests.post(url=URL_LIST_URL['ACCESS_TOKEN_URL']) #登入网址
accessTokenJson = accessToken.json()
if dict(accessTokenJson).get('error') == 'invalid_client':
return '获取accesstoken错误，请检查API_KEY，SECRET_KEY是否正确！'
return accessTokenJson
ACCESS_TOKEN = AccessToken().getToken()['access_token']
LICENSE_PLATE_URL = URL_LIST_URL['FACE_PLATE'] + '?access_token={}'.format(ACCESS_TOKEN)
class faceSuper(object):
pass
class face(faceSuper): # 定义图像输入大类
def __init__(self, image=None, image2=None): # 定义初始化函数
self.HEADER = {
'Content-Type': 'application/json; charset=UTF-8',
}
if image is not None: # 没有图像1
imagepath = os.path.exists(image)
if imagepath == True:
images = image
with open(images, 'rb') as images:
img1 = base64.b64encode(images.read())
else:
print("图像1不存在")
return
if image2 is not None: # 没有图像2
imagepath2 = os.path.exists(image2)
if imagepath2 == True:
images2 = image2
with open(images2, 'rb') as images2:
img2 = base64.b64encode(images2.read())
else:
print("图像2不存在")
return
self.img = img1
self.imgs = img2
self.IMAGE_CONFIG1 = {"image": str(img1, 'utf-8'), "image_type": "BASE64"}
self.IMAGE_CONFIG2 = {"image": str(img2, 'utf-8'), "image_type": "BASE64"}
self.IMAGE_CONFIG = json.dumps([self.IMAGE_CONFIG1, self.IMAGE_CONFIG2])
def postface(self): # 定义从服务器进行数据获取函数
if (self.img==None and self.imgs==None):
return '图像不存在'
face = requests.post(url=LICENSE_PLATE_URL, headers=self.HEADER, data=self.IMAGE_CONFIG)
# 登陆服务器获取数据
return face.json() # 输出结果
def facef(FA1, FA2): # 人脸识别逻辑函数
testAccessToken = AccessToken() # 获取API配置
testface = face(image=FA1, image2=FA2) # 赋值给图像输入大类
result_json = testface.postface() # 从服务器获取数据
result = result_json['result']['score'] #输出结果
print('人脸相似度：', result)
if result > 80: # 识别结果大于80则成功
print("人脸匹配成功！")
# if result < 20:
# print("未检测到人脸！")
else:
print("人脸匹配失败！")
return '人脸相似度：' + str(result), result # 输出字符串结果
快速版：
# -*- coding: utf-8 -*-
"""
Created on Mon May 31 23:40:16 2021
@author: ZHOU
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import requests # 调用 requests的HTTP协议库
import os # 调用os多操作系统接口库
import base64 # 调用base64编码库
import json # 调用JavaScript Object Notation数据交换格式
ACCESS_TOKEN = ''
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) #去掉文件名,返回目录
# ID,KEY的配置信息
INFO_CONFIG = {
'ID': '15050553',
'API_KEY': 'rlRrtRL5oRdXGh71jgg1OmyN',
'SECRET_KEY': 'dK5TpuTAZn2nw5eVpspZLmF5Qs1Uu8A1'
}
"""
若API出错 则改为：
INFO_CONFIG = {
'ID': '15050553',
'API_KEY': 'rlRrtRL5oRdXGh71jgg1OmyN',
'SECRET_KEY': 'dK5TpuTAZn2nw5eVpspZLmF5Qs1Uu8A1'
}
或：
INFO_CONFIG = {
'ID': '15788358',
'API_KEY': 'ohtGa5yYoQEZ8Try8lnL99UK',
'SECRET_KEY': 'qaDjyuXkf5MZ28g5C8pwFngDZenhswC3'
}
"""
# URL配置
URL_LIST_URL = {
# ACCESS_TOKEN_URL用于获取ACCESS_TOKEN, POST请求,
# grant_type必须参数,固定为client_credentials,client_id必须参数,应用的API Key,client_secre 必须参数,应用的Secret Key.
'ACCESS_TOKEN_URL': 'https://aip.baidubce.com/oauth/2.0/token?' + 'grant_type=client_credentials&client_id={API_KEYS}&client_secret={SECRET_KEYS}&'.format(
API_KEYS=INFO_CONFIG['API_KEY'], SECRET_KEYS=INFO_CONFIG['SECRET_KEY']),
# 登入人脸识别机器学习库
'FACE_PLATE': 'https://aip.baidubce.com/rest/2.0/face/v3/match',
}
class AccessTokenSuper(object):
pass
class AccessToken(AccessTokenSuper): # 定义登陆API大类
def getToken(self):
accessToken = requests.post(url=URL_LIST_URL['ACCESS_TOKEN_URL']) #登入网址
accessTokenJson = accessToken.json()
if dict(accessTokenJson).get('error') == 'invalid_client':
return '获取accesstoken错误，请检查API_KEY，SECRET_KEY是否正确！'
return accessTokenJson
ACCESS_TOKEN = AccessToken().getToken()['access_token']
LICENSE_PLATE_URL = URL_LIST_URL['FACE_PLATE'] + '?access_token={}'.format(ACCESS_TOKEN)
class faceSuper(object):
pass
class face(faceSuper): # 定义图像输入大类
def __init__(self, image=None, image2=None): # 定义初始化函数
self.HEADER = {
'Content-Type': 'application/json; charset=UTF-8',
}
if image is not None: # 没有图像1
imagepath = os.path.exists(image)
if imagepath == True:
images = image
with open(images, 'rb') as images:
img1 = base64.b64encode(images.read())
else:
print("图像1不存在")
return
if image2 is not None: # 没有图像2
imagepath2 = os.path.exists(image2)
if imagepath2 == True:
images2 = image2
with open(images2, 'rb') as images2:
img2 = base64.b64encode(images2.read())
else:
print("图像2不存在")
return
self.img = img1
self.imgs = img2
self.IMAGE_CONFIG1 = {"image": str(img1, 'utf-8'), "image_type": "BASE64"}
self.IMAGE_CONFIG2 = {"image": str(img2, 'utf-8'), "image_type": "BASE64"}
self.IMAGE_CONFIG = json.dumps([self.IMAGE_CONFIG1, self.IMAGE_CONFIG2])
def postface(self): # 定义从服务器进行数据获取函数
if (self.img==None and self.imgs==None):
return '图像不存在'
face = requests.post(url=LICENSE_PLATE_URL, headers=self.HEADER, data=self.IMAGE_CONFIG)
# 登陆服务器获取数据
return face.json() # 输出结果
def facef(FA1, FA2): # 人脸识别逻辑函数
testAccessToken = AccessToken() # 获取API配置
testface = face(image=FA1, image2=FA2) # 赋值给图像输入大类
result_json = testface.postface() # 从服务器获取数据
result = result_json['result']['score'] #输出结果
print('人脸相似度：', result)
# if result > 80: # 识别结果大于80则成功
# print("人脸匹配成功！")
# if result < 20:
# print("未检测到人脸！")
# else:
# print("人脸匹配失败！")
return '人脸相似度：' + str(result), result # 输出字符串结果