#!/usr/bin/python3
# 百度人脸对比 & 人脸检测api-v3
import sys, tkinter.messagebox, ast
import ssl, json,requests
import pdb
import base64
from urllib import request, parse
from aip import AipFace
ssl._create_default_https_context = ssl._create_unverified_context
class BaiDuAipFaceAndFaceIdentify(object):
def __init__(self):
# client_id 为官网获取的AK， client_secret 为官网获取的SK
self.__client_id = "mH7LbbbnfolCy55Tp6xIXA5N"
self.__client_secret = "8vokD7ug44e2LzZHvfb0zPTUTTUTfc79"
self.get_token_url = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s' % (
self.__client_id, self.__client_secret)
self.match_url = 'https://aip.baidubce.com/rest/2.0/face/v3/match?access_token='
self.token = 0
# 获取token
def get_token(self):
req = request.Request(self.get_token_url)
req.add_header('Content-Type', 'application/json; charset=UTF-8')
response = request.urlopen(req)
# 获得请求结果
content = response.read()
# print(content)
# 结果转化为字符
content = bytes.decode(content)
# 转化为字典
content = eval(content[:-1])
self.__token = content['access_token']
# 转换图片
# 读取文件内容，转换为base64编码
# 二进制方式打开图文件
def imgdata(self, file1path, file2path):
f1 = open(r'%s' % file1path, 'rb')
pic1 = base64.b64encode(f1.read())
f1.close()
f2 = open(r'%s' % file2path, 'rb')
pic2 = base64.b64encode(f2.read())
f2.close()
# 将图片信息格式化为可提交信息，这里需要注意str参数设置
params = json.dumps([{"image": str(pic1, 'utf-8'),
"image_type": "BASE64"
# "face_type":"LIVE",
# "quality_control":"LOW"
# "liveness_control":"NONE"
},
{"image": str(pic2, 'utf-8'),
"image_type": "BASE64"
# "face_type": "LIVE",
# "quality_control": "LOW"
# "liveness_control": "NONE"
},
])
return params
# 提交进行对比获得结果
def FaceMath(self):
token = self.__token
pics = self.base64_img(2)
# 将图片信息格式化为可提交信息，这里需要注意str参数设置
params = []
for pic in pics:
params.append({"image": str(pic, 'utf-8'),
"image_type": "BASE64"
# "face_type":"LIVE",
# "quality_control":"LOW"
# "liveness_control":"NONE"
})
# pdb.set_trace()
params = json.dumps(params)
url = self.match_url + token
# urlencode处理需提交的数据
content = self.post(url,params)
# 获得分数
score = content['result']['score']
tkinter.messagebox.showinfo('图片相似度','两个人的相似度为：%d'%score)
if score > 80:
print('照片相似度：' + str(score) + ',为同一个人')
else:
print('照片相似度：' + str(score) + ',不是同一个人')
# 此函数进行人脸识别，返回识别到的人脸列表
# 此函数被parse_face_pic调用,没用到
"""
def identify_faces(self, pic, url_fi):
headers = {
'Content-Type': 'application/json; charset=UTF-8'
}
post_data = {
'image': pic,
'image_type': 'BASE64',
'face_field': 'facetype,gender,age,beauty', # expression,faceshape,landmark,race,quality,glasses
'max_face_num': 2
}
response_fi = requests.post(url_fi, headers=headers, data=post_data)
json_fi_result = json.loads(response_fi.text)
return json_fi_result['result']['face_list']
# 下边的print也许是最直观，你最想要的
# print(json_fi_result['result']['face_list'][0]['age'])
# print(json_fi_result['result']['face_list'][0]['beauty'])
"""
# 此函数用于解析进行人脸图片，输出图片上的人脸的性别、年龄、颜值
# 此函数调用identify_faces
def parse_face_pic(self):
url_pic = input("请输入图片地址？\n请您输入：")
f1 = open(r'%s' % url_pic, 'rb')
pic = base64.b64encode(f1.read())
f1.close()
# 调用get_access_token获取access_token
access_token = self.__token
url = 'https://aip.baidubce.com/rest/2.0/face/v3/detect?access_token=' + access_token
# 调用identify_faces，获取人脸列表
#json_faces = self.identify_faces(pic, url_fi)
params = json.dumps({
'image':str(pic, 'utf-8'),
'image_type': 'BASE64',
'face_field': 'facetype,gender,age,beauty', # expression,faceshape,landmark,race,quality,glasses
'max_face_num': 2
})
json_faces = self.post(url, params)
pdb.set_trace()
if len(json_faces) == 0:
print('未识别到人脸')
else:
for json_face in json_faces['result']['face_list']:
#pdb.set_trace() # 调试
print('种类：' + json_face['face_type']['type'])
if str(json_face['gender']['type']) == 'female':
print('性别： 女' )
else:
print('性别： 男')
print('年龄：' + str(json_face['age']))
print('颜值：' + str(json_face['beauty']))
#face_merge 暂时没有v3 api ,所以暂时没用
def face_merge(self):
file1path, file2path = map(str, input("请输入需要融合图片地址a(模版),b（目标图片）空格隔开？\n请您输入：").split())
f1 = open(r'%s' % file1path, 'rb')
pic1 = base64.b64encode(f1.read())
f1.close()
f2 = open(r'%s' % file2path, 'rb')
pic2 = base64.b64encode(f2.read())
f2.close()
headers = {
'Content-Type': 'application/json; charset=UTF-8'
}
post_data = {"image_template":
{'image': pic1,
'image_type': 'BASE64',
'quality_control': "NONE"
},
"image_target":
{'image': pic2,
'image_type': 'BASE64',
'quality_control': "NONE"
}
}
access_token = self.__token
url_fi = 'https://aip.baidubce.com/rest/2.0/face/v1/merge?access_token=' + access_token
response_fi = requests.post(url_fi, headers=headers, data=post_data)
json_fi_result = json.loads(response_fi.text)
print(json_fi_result)
pdb.set_trace()
#face_faceverify
def face_faceverify(self):
pics = self.base64_img(2)
# 将图片信息格式化为可提交信息，这里需要注意str参数设置
params=[]
for pic in pics:
params.append({"image": str(pic, 'utf-8'),
"image_type": "BASE64",
'face_field': "age,beauty,expression"
})
#pdb.set_trace()
params = json.dumps(params)
access_token = self.__token
url = 'https://aip.baidubce.com/rest/2.0/face/v3/faceverify?access_token=' + access_token
content = self.post(url,params)
#pdb.set_trace()
for json_face in content['result']['face_list']:
# pdb.set_trace() # 调试
print('表情：' + json_face['expression']['type'])
print('年龄：' + str(json_face['age']))
print('颜值：' + str(json_face['beauty']))
#post 请求工具方法
def post(self,url,params):
req = request.Request(url=url, data=params.encode('utf-8'))
req.add_header('Content-Type', 'application/json; charset=UTF-8')
response = request.urlopen(req)
content = response.read()
content = content.decode('utf-8')
#print(content)
content = ast.literal_eval(content)
return content
#本地图片上传base64
#type 1 /单张图片 2 /两张图片
def base64_img(self,type):
imgs = []
if type==1:
url_pic = input("请输入图片地址？\n请您输入：")
f1 = open(r'%s' % url_pic, 'rb')
pic = base64.b64encode(f1.read())
f1.close()
return pic
else:
file1path, file2path = map(str, input("请输入图片地址a,b空格隔开？\n请您输入：").split())
f1 = open(r'%s' % file1path, 'rb')
imgs.append(base64.b64encode(f1.read()))
f1.close()
f2 = open(r'%s' % file2path, 'rb')
imgs.append(base64.b64encode(f2.read()))
f2.close()
return imgs
if __name__ == '__main__':
# file1path = './1.png'
# file2path = './2.png'
b = BaiDuAipFaceAndFaceIdentify()
b.get_token()
#调用人脸对比方法
b.FaceMath()
#调用人脸检测方法
b.parse_face_pic()
#调用在线活体检测
b.face_faceverify()
python3 百度AI-v3之 人脸对比 & 人脸检测 & 在线活体检测 接口的相关教程结束。
