class EmailUI(QtWidgets.QMainWindow, Ui_Form):
def __init__(self):
super(EmailUI, self).__init__()
self.setupUi(self)
self.logger = Logging()
self.read_email_conf()
# 保存邮箱配置
def save_email_conf(self):
receiver_email = self.lineEdit.text()
sender = self.lineEdit_2.text()
receiver = self.lineEdit_3.text()
if not (receiver_email and sender and receiver):
QMessageBox.warning(self, '警告', '有字段为空')
self.logger.log_error('email info save filed')
return
conf = {
'receiver_email': receiver_email,
'sender': sender,
'receiver': receiver
}
with open('email_conf/conf.yaml', 'w', encoding='utf-8') as f:
f.write(str(conf))
QMessageBox.about(self, 'info', '保存成功')
self.logger.log_info('email info save success')
# 读取邮箱配置
def read_email_conf(self):
if os.path.exists('email_conf/conf.yaml'):
with open('email_conf/conf.yaml', 'r', encoding='utf-8') as f:
conf = eval(f.read())
if conf:
self.lineEdit.setText(conf['receiver_email'])
self.lineEdit_2.setText(conf['sender'])
self.lineEdit_3.setText(conf['receiver'])
else:
return
else:
return
class Mail:
def __init__(self):
self.mail_host = 'smtp.qq.com'
self.mail_pass = '' # 授权码
self.sender = '' # 发送人
self.receiver, self.sender_name, self.receiver_name = self.read_conf()
self.logger = Logging()
# 读取配置
def read_conf(self):
with open('E:/Opencv/FaceRecognition_demo/email_conf/conf.yaml',
'r',
encoding='utf-8') as f:
conf = eval(f.read())
return [conf['receiver_email']], conf['sender'], conf['receiver']
# 发邮件
def send(self, text):
# 邮件内容
content = text
message = MIMEText(content, 'plain', 'utf-8')
# 寄件人和收件人
message['From'] = Header(self.sender_name, 'utf-8')
message['To'] = Header(self.receiver_name, 'utf-8')
subject = 'python_test' # 发送的主题，可自由填写
message['Subject'] = Header(subject, 'utf-8')
try:
smtpObj = smtplib.SMTP_SSL(self.mail_host, 465)
smtpObj.login(self.sender, self.mail_pass)
smtpObj.sendmail(self.sender, self.receiver, message.as_string())
smtpObj.quit()
self.logger.log_info('send mail success')
except smtplib.SMTPException as e:
self.logger.log_error('send mail failed')
class DataCollectUI(QtWidgets.QMainWindow, Ui_Form):
def __init__(self):
super(DataCollectUI, self).__init__()
self.setupUi(self)
# sqlite
self.sqlite = SqlLiteManage()
# 日志
self.logger = Logging()
# 摄像头
self.capture = cv2.VideoCapture()
# 定时器
self.timer = QtCore.QTimer(self)
self.timer.timeout.connect(self.update_frame)
# 当前人脸ID
self.faceID = 0
# 是否进行人脸采集
self.isCollect = False
self.isContinueCollect = False
# 是否打开摄像头
self.isOpenCapture = False
# 自定义参数
self.count = 0 # 人脸采集计数
self.MaxCount = 50 # 采集人脸数量
self.scale_factor = 1.1 # 数值越大计算越快，太快会丢失人脸
self.minNeighbors = 3 # 控制着误检测
# 预处理选择
self.isGaussianBlur = False # 高斯
self.isBlur = False # 均值
self.isMedianBlur = False # 中值
self.isEqualizeHist = False # 直方图均衡
# 级联分类器
self.face_detector = cv2.CascadeClassifier(
"E:\Opencv\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml"
)
# 人脸数量
self.max_face_count = 1
# 初始化
def root(self):
isSelected = QMessageBox.question(self, '确认', '初始化会清空表中所有数据，确定要这么做吗？',
QMessageBox.Ok | QMessageBox.Cancel,
QMessageBox.Ok)
if isSelected == QMessageBox.Ok:
self.sqlite.create_table()
self.sqlite.root_db()
for file in os.listdir('./dataset'):
os.remove('./dataset/' + file)
for file in os.listdir('./trainer'):
os.remove('./trainer/' + file)
self.logger.log_info('root database success')
elif isSelected == QMessageBox.Cancel:
self.logger.log_info('usr not select "root database"')
else:
return
# 打开摄像头
# 管理外接摄像头
def open_capture(self):
self.logger.log_info('open capture')
self.isOpenCapture = True
capture_dev_id = 0
if self.checkBox.isChecked():
capture_dev_id = 1
self.capture.open(capture_dev_id)
self.capture.set(cv2.CAP_PROP_FRAME_WIDTH, 721)
self.capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 511)
ret, frame = self.capture.read()
self.timer.start(5)
# 关闭摄像头
def close_capture(self):
self.logger.log_info('close capture')
self.capture.release()
self.timer.stop()
self.label_3.setText("摄像头识别区")
self.isOpenCapture = False
# 人脸检测
def face_detection(self, frame):
min_width = 0.1 * self.capture.get(3)
min_height = 0.1 * self.capture.get(4)
# 灰度图
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = self.face_detector.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=3,
minSize=(int(min_width), int(min_height)),
)
# 有多张人脸时暂停采集，一张人脸继续采集
if len(faces) > self.max_face_count:
self.isContinueCollect = False
else:
self.isContinueCollect = True
# 用矩形画出脸的位置
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
return frame
# 人脸采集
# 录入后，只给最后一条ID录人脸
def face_collect(self):
if not self.isOpenCapture:
QMessageBox.warning(self, '警告', '未打开摄像头')
self.logger.log_warning('capture not open')
return
if self.sqlite.count_data() == 0:
QMessageBox.warning(self, '警告', '数据库为空')
self.logger.log_warning('database is null')
return
isSelected = QMessageBox.question(self, '确认', '人脸采集只会给最新录入的数据采集，是否继续？',
QMessageBox.Ok | QMessageBox.Cancel,
QMessageBox.Ok)
if isSelected == QMessageBox.Ok:
self.logger.log_info('start collect face...')
# 自定义初始化
self.MaxCount = int(self.label_8.text())
self.scale_factor = float(self.doubleSpinBox.value())
self.minNeighbors = int(self.label_10.text())
self.isGaussianBlur = self.radioButton.isChecked()
self.isBlur = self.radioButton_2.isChecked()
self.isMedianBlur = self.radioButton_3.isChecked()
self.isEqualizeHist = self.checkBox_5.isChecked()
self.count = 0
self.faceID = self.sqlite.iter_search()[-1][0]
self.isCollect = True
elif isSelected == QMessageBox.Cancel:
self.logger.log_info('usr not select "face_collect"')
else:
return
# 定时刷新界面
def update_frame(self):
start = time.time()
ret, frame = self.capture.read()
img = self.face_detection(frame)
if ret and self.isCollect and self.isContinueCollect:
end = time.time()
img = cv2.putText(img, 'FPS: %.1f' % (1 / (end - start)), (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1)
img = cv2.putText(
img,
time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime(time.time())), (210, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1)
self.frame_dispose(img)
self.collect_face_data(frame)
else:
end = time.time()
img = cv2.putText(img, 'FPS: %.1f' % (1 / (end - start)), (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1)
img = cv2.putText(
img,
time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime(time.time())), (210, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 1)
self.frame_dispose(img)
if self.count >= self.MaxCount:
self.isCollect = False
self.logger.log_info('face data collect finish')
self.close_capture()
# 人脸采集
def collect_face_data(self, frame):
# 灰度图
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 三种滤波只能选择一种
if self.isGaussianBlur:
gray = cv2.GaussianBlur(gray, (5, 5), 1)
if self.isMedianBlur:
gray = cv2.medianBlur(gray, 5)
if self.isBlur:
gray = cv2.blur(gray, (3, 3))
# 直方图均衡
if self.isEqualizeHist:
gray = cv2.equalizeHist(gray)
# 第一个参数img
# 第二个参数scale_factor，数值越大计算越快，太快会丢失人脸
# 第三个参数minNeighbors，控制着误检测，默认值为3。表明至少有3次重叠检测，我们才认为人脸确实存在
faces = self.face_detector.detectMultiScale(gray, self.scale_factor,
self.minNeighbors)
# 图像中人脸大于1就跳过
if len(faces) > self.max_face_count:
pass
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
self.count += 1
self.lcdNumber.display(self.count)
# 将照片存入指定文件夹./dataset
cv2.imwrite(
"./dataset/User." + str(self.faceID) + '.' + str(self.count) +
".jpg", gray[y:y + h, x:x + w])
# 对每一帧进行处理
def frame_dispose(self, frame):
img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
qformat = QImage.Format_Indexed8
if len(img.shape) == 3: # rows[0], cols[1], channels[2]
if img.shape[2] == 4:
# The image is stored using a 32-bit byte-ordered RGBA format (8-8-8-8)
# A: alpha channel，不透明度参数。如果一个像素的alpha通道数值为0%，那它就是完全透明的
qformat = QImage.Format_RGBA8888
else:
qformat = QImage.Format_RGB888
output_img = QImage(img, img.shape[1], img.shape[0], img.strides[0],
qformat)
self.label_3.setPixmap(QPixmap.fromImage((output_img)))
self.label_3.setScaledContents(True)
# 添加新数据
def add_item(self):
if not (self.lineEdit.text() and self.lineEdit_2.text()
and self.lineEdit_3.text()):
QMessageBox.warning(self, '警告', '部分字段为空，请填写合适数据，否则这段数据不会被插入')
self.logger.log_warning('some fields are null')
self.logger.log_error('insert data failed')
else:
values = (int(self.lineEdit_2.text()), self.lineEdit.text(),
self.lineEdit_3.text(), 0)
try:
self.sqlite.insert(values)
self.log(1, 'insert data success')
except:
QMessageBox.warning(self, '警告', '数据库中已经有ID相同字段，请重试')
self.logger.log_warning('already have the same data')
self.logger.log_error('insert data failed')