OpenCV+face++实现实时人脸识别解锁功能

#从摄像头读取图片并保存
def getpicture():
  cap = cv2.VideoCapture(0)#打开摄像头
  cascade = cv2.CascadeClassifier("E:\OpenCV\sources\data\haarcascades\haarcascade_frontalface_default.xml")#这里是是自己的人脸识别xml路径
  while True:
    # get a frame
    ret, frame = cap.read()#捕获图片
    # show a frame
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)#转为灰度图
    rect = cascade.detectMultiScale(gray, scaleFactor=1.15, minNeighbors=5, minSize=(5, 5),flags=cv2.cv.CV_HAAR_SCALE_IMAGE) # 使用模板匹配图形
    for x, y, z, w in rect:
      cv2.rectangle(frame, (x, y), (x + z, y + w), (0, 0, 255), 2)# 函数的参数分别为：图像，左上角坐标，右下角坐标，颜色，宽度
    cv2.imshow("capture", frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):#按下q拍照
      cv2.imwrite("images\client.jpg", frame)#相对路径，储存图片
      break
  cap.release()
  cv2.destroyAllWindows()

def upload_img(fileDir, oneface=True):
  url = '%s/detect?api_key=%s&api_secret=%s' % (
    BASE_URL, API_KEY, API_SECRET)
  #注意参数名与api文档一致
  files = {'image_file': (os.path.basename(fileDir), open(fileDir, 'rb'),
           mimetypes.guess_type(fileDir)[0]), }
  r = requests.post(url, files=files)
  faces = r.json().get('faces')
  #print faces
  if faces is None:
    print('There is no face found in %s' % fileDir)
  else:
    return faces[0]['face_token']#返回face_token

def compare(face_token1,face_token2):
  url = '%s/compare' % BASE_URL
  params = BASE_PARAMS
  params['face_token1'] = face_token1
  params['face_token2'] = face_token2
  r = requests.post(url, params)
  #print r.status_code
  #print r.json()
  return r.json().get('confidence')#返回两张照片的相似度

#! usr/bin/env python
#-*- coding:utf-8 -*-

import requests
import os
import mimetypes  #判断文件类型
import cv2
import time
import win32api
import win32con

BASE_URL = "https://api-cn.faceplusplus.com/facepp/v3"
API_KEY = "g_vhMthXCQEzF0gZG5-o0ICNDhr3-80b"
API_SECRET = "2HD5ysubTeZTwo20JJTudY0cvZN1BPLt"
BASE_PARAMS = {
  'api_key':'g_vhMthXCQEzF0gZG5-o0ICNDhr3-80b',
  'api_secret':'2HD5ysubTeZTwo20JJTudY0cvZN1BPLt'
}
def upload_img(fileDir, oneface=True):
  url = '%s/detect?api_key=%s&api_secret=%s' % (
    BASE_URL, API_KEY, API_SECRET)
  #注意参数名与api文档一致
  files = {'image_file': (os.path.basename(fileDir), open(fileDir, 'rb'),
           mimetypes.guess_type(fileDir)[0]), }
  r = requests.post(url, files=files)
  faces = r.json().get('faces')
  #print faces
  if faces is None:
    print('There is no face found in %s' % fileDir)
  else:
    return faces[0]['face_token']



def compare(face_token1,face_token2):
  url = '%s/compare' % BASE_URL
  params = BASE_PARAMS
  params['face_token1'] = face_token1
  params['face_token2'] = face_token2
  r = requests.post(url, params)
  #print r.status_code
  #print r.json()
  return r.json().get('confidence')


def getpicture():
  cap = cv2.VideoCapture(0)
  cascade = cv2.CascadeClassifier("E:\OpenCV\sources\data\haarcascades\haarcascade_frontalface_default.xml")#这里是是自己的人脸识别xml路径
  while True:
    # get a frame
    ret, frame = cap.read()
    # show a frame
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    rect = cascade.detectMultiScale(gray, scaleFactor=1.15, minNeighbors=5, minSize=(5, 5),flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
    for x, y, z, w in rect:
      cv2.rectangle(frame, (x, y), (x + z, y + w), (0, 0, 255), 2)
    cv2.imshow("capture", frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
      cv2.imwrite("images\client.jpg", frame)#相对路径
      break
  cap.release()
  cv2.destroyAllWindows()


getpicture()
print u"                   数据读取中。。。。\n"
face1 = upload_img(u"images\demo4.jpg")
print u"                        正在校对人脸。。。。。\n"
time.sleep(5)#防止出现qps
print u"                               再等一下。。。。。\n"
face2 = upload_img(u"images\client.jpg")
confidence = compare(face1,face2)
if confidence>=70:
  #print u"同一个人"
  #win32api.ShellExecute(0,'op','genealogy.exe','','',1)
  win32api.MessageBox(0, u"刷脸成功", u"家谱管理系统", win32con.MB_OK)
  #这里写你想要继续执行的代码
else:
  win32api.MessageBox(0, u"刷脸失败", u"家谱管理系统", win32con.MB_OK)
  #print u"不是同一个人"