opencv做人脸识别

怎样用opencv做人脸识别

这里直接贴代码,可直接运行

import urllib
import ssl
from urllib import request
import json
import cv2
import threading

# client_id 为官网获取的AK， client_secret 为官网获取的SK
def get_token():
    context = ssl._create_unverified_context()
    host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=oxWSUmCiaxLARzcavNHsh4Sq&client_secret=feMOxxWatn53Gxp2IG8rpv5bR2fIKGry'
    request = urllib.request.Request(host)
    request.add_header('Content-Type', 'application/json; charset=UTF-8')
    response = urllib.request.urlopen(request, context=context)
    # 获取请求结果
    content = response.read()
    # 转换为字符
    content = bytes.decode(content)
    # 转换为字典
    content = eval(content[:-1])
    return 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(file1path, file2path):
    import base64
    f = open(r'%s' % file1path, 'rb')
    pic1 = base64.b64encode(f.read())
    f.close()
    f = open(r'%s' % file2path, 'rb')
    pic2 = base64.b64encode(f.read())
    f.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"},
         {"image": str(pic2, 'utf-8'), "image_type": "BASE64", "face_type": "IDCARD", "quality_control": "LOW"}]
    )
    return params.encode(encoding='UTF8')

# 进行对比获得结果
def result(file1path, file2path):
    token = get_token()
    context = ssl._create_unverified_context()
    params = imgdata(file1path, file2path)

    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/match"
    request_url = request_url + "?access_token=" + token
    request = urllib.request.Request(url=request_url, data=params)
    request.add_header('Content-Type', 'application/json')
    response = urllib.request.urlopen(request, context=context)
    content = response.read()
    content = eval(content)
    # # 获得分数
    score = content['result']['score']
    if score > 80:
        return '照片相似度：' + str(score) + ',同一个人'
    else:
        return '照片相似度：' + str(score) + ',不是同一个人'


if __name__ == '__main__':
    # 拍照,捕捉人脸
    def getimg():
        # 获取摄像头
        ret, frame = cap.read()
        # 保存图片，地址自定，要和result里传递的地址一样
        cv2.imwrite("new.jpg", frame)

    # 开启摄像头
    cap = cv2.VideoCapture(0)
    # 开启捕捉摄像头进程
    threading.Thread(target=getimg).start()
    #对比两张照片的相似度, exit.jpg是本来就有的照片(与py文件放在同一目录),new.jpg是现拍的照片
    res = result('exit.jpg', 'new.jpg')
    print(res)