python opencv怎么實現人臉識別考勤系統

小編給大家分享一下python opencv怎么實現人臉識別考勤系統，相信大部分人都還不怎么了解，因此分享這篇文章給大家參考一下，希望大家閱讀完這篇文章后大有收獲，下面讓我們一起去了解一下吧！

python可以做什么

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運行結果如下：

代碼如下：

import wx
import wx.grid
from time import localtime,strftime
import os
import io
import zlib
import dlib  # 人臉識別的庫dlib
import numpy as np  # 數據處理的庫numpy
import cv2  # 圖像處理的庫OpenCv
import _thread
import threading
 
ID_NEW_REGISTER = 160
ID_FINISH_REGISTER = 161
 
ID_START_PUNCHCARD = 190
ID_END_PUNCARD = 191
 
ID_OPEN_LOGCAT = 283
ID_CLOSE_LOGCAT = 284
 
ID_WORKER_UNAVIABLE = -1
 
PATH_FACE = "data/face_img_database/"
# face recognition model, the object maps human faces into 128D vectors
facerec = dlib.face_recognition_model_v1("model/dlib_face_recognition_resnet_model_v1.dat")
# Dlib 預測器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('model/shape_predictor_68_face_landmarks.dat')
 
class WAS(wx.Frame):
    def __init__(self):
        wx.Frame.__init__(self,parent=None,title="員工考勤系統",size=(920,560))
 
        self.initMenu()
        self.initInfoText()
        self.initGallery()
        self.initDatabase()
        self.initData()
 
    def initData(self):
        self.name = ""
        self.id =ID_WORKER_UNAVIABLE
        self.face_feature = ""
        self.pic_num = 0
        self.flag_registed = False
        self.puncard_time = "21:00:00"
        self.loadDataBase(1)
 
    def initMenu(self):
 
        menuBar = wx.MenuBar()  #生成菜單欄
        menu_Font = wx.Font()#Font(faceName="consolas",pointsize=20)
        menu_Font.SetPointSize(14)
        menu_Font.SetWeight(wx.BOLD)
 
 
        registerMenu = wx.Menu() #生成菜單
        self.new_register = wx.MenuItem(registerMenu,ID_NEW_REGISTER,"新建錄入")
        self.new_register.SetBitmap(wx.Bitmap("drawable/new_register.png"))
        self.new_register.SetTextColour("SLATE BLUE")
        self.new_register.SetFont(menu_Font)
        registerMenu.Append(self.new_register)
 
        self.finish_register = wx.MenuItem(registerMenu,ID_FINISH_REGISTER,"完成錄入")
        self.finish_register.SetBitmap(wx.Bitmap("drawable/finish_register.png"))
        self.finish_register.SetTextColour("SLATE BLUE")
        self.finish_register.SetFont(menu_Font)
        self.finish_register.Enable(False)
        registerMenu.Append(self.finish_register)
 
 
        puncardMenu = wx.Menu()
        self.start_punchcard = wx.MenuItem(puncardMenu,ID_START_PUNCHCARD,"開始簽到")
        self.start_punchcard.SetBitmap(wx.Bitmap("drawable/start_punchcard.png"))
        self.start_punchcard.SetTextColour("SLATE BLUE")
        self.start_punchcard.SetFont(menu_Font)
        puncardMenu.Append(self.start_punchcard)
 
 
        self.close_logcat = wx.MenuItem(logcatMenu, ID_CLOSE_LOGCAT, "關閉日志")
        self.close_logcat.SetBitmap(wx.Bitmap("drawable/close_logcat.png"))
        self.close_logcat.SetFont(menu_Font)
        self.close_logcat.SetTextColour("SLATE BLUE")
        logcatMenu.Append(self.close_logcat)
 
        menuBar.Append(registerMenu,"&人臉錄入")
        menuBar.Append(puncardMenu,"&刷臉簽到")
        menuBar.Append(logcatMenu,"&考勤日志")
        self.SetMenuBar(menuBar)
 
        self.Bind(wx.EVT_MENU,self.OnNewRegisterClicked,id=ID_NEW_REGISTER)
        self.Bind(wx.EVT_MENU,self.OnFinishRegisterClicked,id=ID_FINISH_REGISTER)
        self.Bind(wx.EVT_MENU,self.OnStartPunchCardClicked,id=ID_START_PUNCHCARD)
        self.Bind(wx.EVT_MENU,self.OnEndPunchCardClicked,id=ID_END_PUNCARD)
        self.Bind(wx.EVT_MENU,self.OnOpenLogcatClicked,id=ID_OPEN_LOGCAT)
        self.Bind(wx.EVT_MENU,self.OnCloseLogcatClicked,id=ID_CLOSE_LOGCAT)
 
 
        pass
 
    def OnCloseLogcatClicked(self,event):
        self.SetSize(920,560)
 
        self.initGallery()
        pass
 
    def register_cap(self,event):
        # 創建 cv2 攝像頭對象
        self.cap = cv2.VideoCapture(0)
        # cap.set(propId, value)
        # 設置視頻參數，propId設置的視頻參數，value設置的參數值
        # self.cap.set(3, 600)
        # self.cap.set(4,600)
        # cap是否初始化成功
        while self.cap.isOpened():
            # cap.read()
            # 返回兩個值：
            #    一個布爾值true/false，用來判斷讀取視頻是否成功/是否到視頻末尾
            #    圖像對象，圖像的三維矩陣
            flag, im_rd = self.cap.read()
 
            # 每幀數據延時1ms，延時為0讀取的是靜態幀
            kk = cv2.waitKey(1)
            # 人臉數 dets
            dets = detector(im_rd, 1)
 
            # 檢測到人臉
            if len(dets) != 0:
                biggest_face = dets[0]
                #取占比最大的臉
                maxArea = 0
                for det in dets:
                    w = det.right() - det.left()
                    h = det.top()-det.bottom()
                    if w*h > maxArea:
                        biggest_face = det
                        maxArea = w*h
                        # 繪制矩形框
 
                cv2.rectangle(im_rd, tuple([biggest_face.left(), biggest_face.top()]),
                                      tuple([biggest_face.right(), biggest_face.bottom()]),
                                      (255, 0, 0), 2)
                img_height, img_width = im_rd.shape[:2]
                image1 = cv2.cvtColor(im_rd, cv2.COLOR_BGR2RGB)
                pic = wx.Bitmap.FromBuffer(img_width, img_height, image1)
                # 顯示圖片在panel上
                self.bmp.SetBitmap(pic)
 
                # 獲取當前捕獲到的圖像的所有人臉的特征，存儲到 features_cap_arr
                shape = predictor(im_rd, biggest_face)
                features_cap = facerec.compute_face_descriptor(im_rd, shape)
 
                # 對于某張人臉，遍歷所有存儲的人臉特征
                for i,knew_face_feature in enumerate(self.knew_face_feature):
                    # 將某張人臉與存儲的所有人臉數據進行比對
                    compare = return_euclidean_distance(features_cap, knew_face_feature)
                    if compare == "same":  # 找到了相似臉
                        self.infoText.AppendText(self.getDateAndTime()+"工號:"+str(self.knew_id[i])
                                                 +" 姓名:"+self.knew_name[i]+" 的人臉數據已存在\r\n")
                        self.flag_registed = True
                        self.OnFinishRegister()
                        _thread.exit()
 
                        # print(features_known_arr[i][-1])
                face_height = biggest_face.bottom()-biggest_face.top()
                face_width = biggest_face.right()- biggest_face.left()
                im_blank = np.zeros((face_height, face_width, 3), np.uint8)
                try:
                    for ii in range(face_height):
                        for jj in range(face_width):
                            im_blank[ii][jj] = im_rd[biggest_face.top() + ii]parent=self.bmp,max=100000000,min=ID_WORKER_UNAVIABLE)
            for knew_id in self.knew_id:
                if knew_id == self.id:
                    self.id = ID_WORKER_UNAVIABLE
                    wx.MessageBox(message="工號已存在，請重新輸入", caption="警告")
 
        while self.name == '':
            self.name = wx.GetTextFromUser(message="請輸入您的的姓名,用于創建姓名文件夾",
                                           caption="溫馨提示",
                                      default_value="", parent=self.bmp)
 
            # 監測是否重名
            for exsit_name in (os.listdir(PATH_FACE)):
                if self.name == exsit_name:
                    wx.MessageBox(message="姓名文件夾已存在，請重新輸入", caption="警告")
                    self.name = ''
                    break
        os.makedirs(PATH_FACE+self.name)
        _thread.start_new_thread(self.register_cap,(event,))
        pass
 
    def OnFinishRegister(self):
 
        self.new_register.Enable(True)
        self.finish_register.Enable(False)
        self.cap.release()
 
        self.bmp.SetBitmap(wx.Bitmap(self.pic_index))
        if self.flag_registed == True:
            dir = PATH_FACE + self.name
            for file in os.listdir(dir):
                os.remove(dir+"/"+file)
                print("已刪除已錄入人臉的圖片", dir+"/"+file)
            os.rmdir(PATH_FACE + self.name)
            print("已刪除已錄入人臉的姓名文件夾", dir)
            self.initData()
            return
        if self.pic_num>0:
            pics = os.listdir(PATH_FACE + self.name)
            feature_list = []
            feature_average = []
            for i in range(len(pics)):
                pic_path = PATH_FACE + self.name + "/" + pics[i]
                print("正在讀的人臉圖像：", pic_path)
                img = iio.imread(pic_path)
                img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
                dets = detector(img_gray, 1)
                if len(dets) != 0:
                    shape = predictor(img_gray, dets[0])
                    face_descriptor = facerec.compute_face_descriptor(img_gray, shape)
                    feature_list.append(face_descriptor)
                else:
                    face_descriptor = 0
                    print("未在照片中識別到人臉")
            if len(feature_list) > 0:
                for j in range(128):
                    #防止越界
                    feature_average.append(0)
                    for i in range(len(feature_list)):
                        feature_average[j] += feature_list[i][j]
                    feature_average[j] = (feature_average[j]) / len(feature_list)
                self.insertARow([self.id,self.name,feature_average],1)
                self.infoText.AppendText(self.getDateAndTime()+"工號:"+str(self.id)
                                     +" 姓名:"+self.name+" 的人臉數據已成功存入\r\n")
            pass
 
        else:
            os.rmdir(PATH_FACE + self.name)
            print("已刪除空文件夾",PATH_FACE + self.name)
        self.initData()
 
    def OnFinishRegisterClicked(self,event):
        self.OnFinishRegister()
        pass
 
 
    def OnStartPunchCardClicked(self,event):
        # cur_hour = datetime.datetime.now().hour
        # print(cur_hour)
        # if cur_hour>=8 or cur_hour<6:
        #     wx.MessageBox(message='''您錯過了今天的簽到時間，請明天再來\n
        #     每天的簽到時間是:6:00~7:59''', caption="警告")
        #     return
        self.start_punchcard.Enable(False)
        self.end_puncard.Enable(True)
        self.loadDataBase(2)
        threading.Thread(target=self.punchcard_cap,args=(event,)).start()
        #_thread.start_new_thread(self.punchcard_cap,(event,))
        pass
 
    def OnEndPunchCardClicked(self,event):
        self.start_punchcard.Enable(True)
        self.end_puncard.Enable(False)
        pass
 
 
    def initGallery(self):
        self.pic_index = wx.Image("drawable/index.png", wx.BITMAP_TYPE_ANY).Scale(600, 500)
        self.bmp = wx.StaticBitmap(parent=self, pos=(320,0), bitmap=wx.Bitmap(self.pic_index))
        pass
 
    def getDateAndTime(self):
        dateandtime = strftime("%Y-%m-%d %H:%M:%S",localtime())
        return "["+dateandtime+"]"
 
    #數據庫部分
    #初始化數據庫
    def initDatabase(self):
        conn = sqlite3.connect("inspurer.db")  #建立數據庫連接
        cur = conn.cursor()             #得到游標對象
        cur.execute('''create table if not exists worker_info
        (name text not null,
        id int not null primary key,
        face_feature array not null)''')
        cur.execute('''create table if not exists logcat
         (datetime text not null,
         id int not null,
         name text not null,
         late text not null)''')
        cur.close()
        conn.commit()
        conn.close()
 
    def adapt_array(self,arr):
        out = io.BytesIO()
        np.save(out, arr)
        out.seek(0)
 
        dataa = out.read()
        # 壓縮數據流
        return sqlite3.Binary(zlib.compress(dataa, zlib.Z_BEST_COMPRESSION))
 
    def convert_array(self,text):
        out = io.BytesIO(text)
        out.seek(0)
 
        dataa = out.read()
        # 解壓縮數據流
        out = io.BytesIO(zlib.decompress(dataa))
        return np.load(out)
 
    def insertARow(self,Row,type):
        conn = sqlite3.connect("inspurer.db")  # 建立數據庫連接
        cur = conn.cursor()  # 得到游標對象
        if type == 1:
            cur.execute("insert into worker_info (id,name,face_feature) values(?,?,?)",
                    (Row[0],Row[1],self.adapt_array(Row[2])))
            print("寫人臉數據成功")
        if type == 2:
            cur.execute("insert into logcat (id,name,datetime,late) values(?,?,?,?)",
                        (Row[0],Row[1],Row[2],Row[3]))
            print("寫日志成功")
            pass
        cur.close()
        conn.commit()
        conn.close()
        pass
 
    def loadDataBase(self,type):
 
        conn = sqlite3.connect("inspurer.db")  # 建立數據庫連接
        cur = conn.cursor()  # 得到游標對象
 
        if type == 1:
            self.knew_id = []
            self.knew_name = []
            self.knew_face_feature = []
            cur.execute('select id,name,face_feature from worker_info')
            origin = cur.fetchall()
            for row in origin:
                print(row[0])
                self.knew_id.append(row[0])
                print(row[1])
                self.knew_name.append(row[1])
                print(self.convert_array(row[2]))
                self.knew_face_feature.append(self.convert_array(row[2]))
        if type == 2:
            self.logcat_id = []
            self.logcat_name = []
            self.logcat_datetime = []
            self.logcat_late = []
            cur.execute('select id,name,datetime,late from logcat')
            origin = cur.fetchall()
            for row in origin:
                print(row[0])
                self.logcat_id.append(row[0])
                print(row[1])
                self.logcat_name.append(row[1])
                print(row[2])
                self.logcat_datetime.append(row[2])
                print(row[3])
                self.logcat_late.append(row[3])
        pass
app = wx.App()
frame = WAS()
frame.Show()
app.MainLoop()

運行結果如下：

以上是“python opencv怎么實現人臉識別考勤系統”這篇文章的所有內容，感謝各位的閱讀！相信大家都有了一定的了解，希望分享的內容對大家有所幫助，如果還想學習更多知識，歡迎關注億速云行業資訊頻道！