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_hour6:
# 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()
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