<>前言

本项目为IOT实验室人员签到考勤设计,系统实现功能:

◦人员人脸识别并完成签到/签退

◦考勤时间计算

◦保存考勤数据为CSV格式(Excel表格)

PS:本系统2D人脸识别,节约了繁琐的人脸识别训练部分,简洁快捷

该项目为测试版,正式版会加入更多的功能,持续更新中… 测试版项目地址我会放到结尾

<>项目效果图

<>登陆界面

<>主界面展示图:

<>签到功能展示

<>签退功能展示

<>后台签到数据记录

<>是否签到/退判断

<>项目环境

<>核心环境:
◦OpenCV-Python 4.5.5.64 ◦face_recognition 1.30 ◦face_recognition_model 0.3.0
◦dlib19.23.1
<>UI窗体界面:
◦PyQt5 5.15.4 ◦pyqt5-plugins 5.15.4.2.2 ◦PyQt5-Qt5 5.15.2 ◦PyQt5-sip 12.10.1
◦pyqt5-tools 5.15.4.3.2
<>编译器
Pycham 2021.1.3 **Python版本 3.9.12**

<>Anaconda

<>辅助开发QT-designer

<>项目配置

<>代码部分

<>核心代码
python学习交流Q群:906715085#### 「MainWindow.py」UI文件加载: class Ui_Dialog(QDialog): def
__init__(self): super(Ui_Dialog, self).__init__() loadUi("mainwindow.ui", self)
##加载QTUI文件 self.runButton.clicked.connect(self.runSlot) self._new_window = None
self.Videocapture_ = None
<>摄像头调用:
def refreshAll(self): print("当前调用人俩检测摄像头编号(0为笔记本内置摄像头,1为USB外置摄像头):") self.
Videocapture_= "0" 「OutWindow.py」获取当前系统时间 class Ui_OutputDialog(QDialog): def
__init__(self): super(Ui_OutputDialog, self).__init__() loadUi(
"./outputwindow.ui", self) ##加载输出窗体UI ##datetime 时间模块 now = QDate.currentDate()
current_date= now.toString('ddd dd MMMM yyyy') ##时间格式 current_time = datetime.
datetime.now().strftime("%I:%M %p") self.Date_Label.setText(current_date) self.
Time_Label.setText(current_time) self.image = None 签到时间计算 def ElapseList(self,
name): with open('Attendance.csv', "r") as csv_file: csv_reader = csv.reader(
csv_file, delimiter=',') line_count = 2 Time1 = datetime.datetime.now() Time2 =
datetime.datetime.now() for row in csv_reader: for field in row: if field in row
: if field == 'Clock In': if row[0] == name: Time1 = (datetime.datetime.strptime
(row[1], '%y/%m/%d %H:%M:%S')) self.TimeList1.append(Time1) if field == 'Clock
Out': if row[0] == name: Time2 = (datetime.datetime.strptime(row[1], '%y/%m/%d
%H:%M:%S')) self.TimeList2.append(Time2)
<>人脸识别部分
python学习交流Q群:906715085#### ## 人脸识别部分 faces_cur_frame = face_recognition.
face_locations(frame) encodes_cur_frame = face_recognition.face_encodings(frame,
faces_cur_frame) for encodeFace, faceLoc in zip(encodes_cur_frame,
faces_cur_frame): match = face_recognition.compare_faces(encode_list_known,
encodeFace, tolerance=0.50) face_dis = face_recognition.face_distance(
encode_list_known, encodeFace) name = "unknown" ##未知人脸识别为unknown
best_match_index= np.argmin(face_dis) if match[best_match_index]: name =
class_names[best_match_index].upper() y1, x2, y2, x1 = faceLoc cv2.rectangle(
frame, (x1, y1), (x2, y2), (0, 255, 0), 2) cv2.rectangle(frame, (x1, y2 - 20), (
x2, y2), (0, 255, 0), cv2.FILLED) cv2.putText(frame, name, (x1 + 6, y2 - 6), cv2
.FONT_HERSHEY_COMPLEX, 0.5, (255, 255, 255), 1) mark_attendance(name) return
frame

<>签到数据保存与判断
csv表格保存数据 def mark_attendance(name): """ :param name: 人脸识别部分 :return: """ if
self.ClockInButton.isChecked(): self.ClockInButton.setEnabled(False) with open(
'Attendance.csv', 'a') as f: if (name != 'unknown'): ##签到判断:是否为已经识别人脸
buttonReply= QMessageBox.question(self, '欢迎 ' + name, '开始签到' , QMessageBox.Yes |
QMessageBox.No, QMessageBox.No) if buttonReply == QMessageBox.Yes:
date_time_string= datetime.datetime.now().strftime("%y/%m/%d %H:%M:%S") f.
writelines(f'\n{name},{date_time_string},Clock In') self.ClockInButton.
setChecked(False) self.NameLabel.setText(name) self.StatusLabel.setText('签到')
self.HoursLabel.setText('开始签到计时中') self.MinLabel.setText('') self.Time1 =
datetime.datetime.now() self.ClockInButton.setEnabled(True) else: print('签到操作失败'
) self.ClockInButton.setEnabled(True) elif self.ClockOutButton.isChecked(): self
.ClockOutButton.setEnabled(False) with open('Attendance.csv', 'a') as f: if (
name!= 'unknown'): buttonReply = QMessageBox.question(self, '嗨呀 ' + name,
'确认签退?', QMessageBox.Yes | QMessageBox.No, QMessageBox.No) if buttonReply ==
QMessageBox.Yes: date_time_string = datetime.datetime.now().strftime("%y/%m/%d
%H:%M:%S") f.writelines(f'\n{name},{date_time_string},Clock Out') self.
ClockOutButton.setChecked(False) self.NameLabel.setText(name) self.StatusLabel.
setText('签退') self.Time2 = datetime.datetime.now() self.ElapseList(name) self.
TimeList2.append(datetime.datetime.now()) CheckInTime = self.TimeList1[-1]
CheckOutTime= self.TimeList2[-1] self.ElapseHours = (CheckOutTime - CheckInTime)
self.MinLabel.setText("{:.0f}".format(abs(self.ElapseHours.total_seconds() / 60
)%60) + 'm') self.HoursLabel.setText("{:.0f}".format(abs(self.ElapseHours.
total_seconds() / 60**2)) + 'h') self.ClockOutButton.setEnabled(True) else:
print('签退操作失败') self.ClockOutButton.setEnabled(True)
<>项目目录结构

<>后记

◦因为本系统没有进行人脸训练建立模型,系统误识别率较高,安全性较低

◦系统优化较差,摄像头捕捉帧数较低(8-9),后台占有高,CPU利用率较高

◦数据保存CSV格式,安全性较低

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