pyqt5界面的设计：

PYQT5工具设计：

这是使用PYQT5的设计工具设计的，主要部件就一个QDialog一个Qlabel标签和两个QPushButton，当然要设置一些属性。这些属性我就不一一描述了，直接上界面的代码吧。界面除了可以直接使用设计工具完成，也可直接使用代码设计。

PYQT5代码设计：

上述界面对应的代码如下：

from PyQt5 import QtCore, QtGui, QtWidgetsclass Ui_Dialog(object):def setupUi(self, Dialog):Dialog.setObjectName("Dialog")Dialog.resize(1200, 750)self.start_But = QtWidgets.QPushButton(Dialog)self.start_But.setGeometry(QtCore.QRect(990, 150, 140, 80))self.start_But.setObjectName("start_But")self.stop_But = QtWidgets.QPushButton(Dialog)self.stop_But.setGeometry(QtCore.QRect(990, 390, 140, 80))self.stop_But.setObjectName("stop_But")self.label = QtWidgets.QLabel(Dialog)self.label.setGeometry(QtCore.QRect(10, 10, 900, 720))self.label.setObjectName("label")self.retranslateUi(Dialog)QtCore.QMetaObject.connectSlotsByName(Dialog)def retranslateUi(self, Dialog):_translate = QtCore.QCoreApplication.translateDialog.setWindowTitle(_translate("Dialog", "Dialog"))self.start_But.setText(_translate("Dialog", "开始"))self.stop_But.setText(_translate("Dialog", "停止"))self.label.setText(_translate("Dialog", "label_video"))

眨眼检测：

由于要进行眨眼检测，所以我们需要用到人脸识别技术，这里采用68点人脸检测技术。使用该技术一定要确保安装了dlib库。只是基础的眨眼检测，所以采用眼睛纵横比（EAR）来判断是否眨眼。

人脸检测，确定需要取的特征点：

#人脸识别，加载需要用到的模块
detector = dlib.get_frontal_face_detector()
sp68 = dlib.shape_predictor("./models/shape_predictor_68_face_landmarks.dat")
EYE_AR_THRESH = 0.3  # EAR阈值
EYE_AR_CONSEC_FRAMES = 3  # 当EAR小于阈值时，接连多少帧一定发生眨眼动作
# 对应特征点的序号
RIGHT_EYE_START = 37 - 1
RIGHT_EYE_END = 42 - 1
LEFT_EYE_START = 43 - 1
LEFT_EYE_END = 48 - 1

眨眼数的计算：

points = face_utils.shape_to_np(shape)
leftEye = points[LEFT_EYE_START:LEFT_EYE_END + 1]
rightEye = points[RIGHT_EYE_START:RIGHT_EYE_END + 1]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
if ear < EYE_AR_THRESH:self.frame_counter += 1
else:if self.frame_counter >= EYE_AR_CONSEC_FRAMES:self.blink_counter += 1

EAR阈值的计算：

A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
C = dist.euclidean(eye[0], eye[3])
ear = (A + B) / (2.0 * C)

眨眼检测完整代码：

import sys
import _thread
import numpy as np
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
from PyQt5.QtCore import QTimer,QThread,pyqtSignal
import cv2
import dlib
import threading,time
from imutils import face_utils
from scipy.spatial import distance as dist
import os
curPath = os.path.abspath(os.path.dirname(__file__))
rootPath = os.path.split(curPath)[0]
sys.path.append(rootPath)
from ui import video_show_uidef eye_aspect_ratio(eye):# print(eye)A = dist.euclidean(eye[1], eye[5])B = dist.euclidean(eye[2], eye[4])C = dist.euclidean(eye[0], eye[3])ear = (A + B) / (2.0 * C)return earclass Frm_blinking(QDialog):def __init__(self):super().__init__()self.ui = video_show_ui.Ui_Dialog()self.ui.setupUi(self)self.working = Falseself.frame_counter = 0self.blink_counter = 0self.init_ui()def init_ui(self):self.ui.start_But.clicked.connect(self.start_video_show)self.ui.stop_But.clicked.connect(self.stop_video_show)self.ui.start_But.setEnabled(True)self.ui.stop_But.setEnabled(False)def start_video_show(self):self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)self.working = True_thread.start_new_thread(self.showing, ())  #开启线程self.ui.start_But.setEnabled(False)self.ui.stop_But.setEnabled(True)def stop_video_show(self):if self.working:self.working = Falseself.cap.release()_thread.exit()      #关闭线程self.ui.start_But.setEnabled(True)self.ui.stop_But.setEnabled(False)def showing(self):self.ui.start_But.setEnabled(False)self.ui.stop_But.setEnabled(True)while self.working:QApplication.processEvents()detector = dlib.get_frontal_face_detector()sp68 = dlib.shape_predictor("./models/shape_predictor_68_face_landmarks.dat")EYE_AR_THRESH = 0.3  # EAR阈值EYE_AR_CONSEC_FRAMES = 3  # 当EAR小于阈值时，接连多少帧一定发生眨眼动作# 对应特征点的序号RIGHT_EYE_START = 37 - 1RIGHT_EYE_END = 42 - 1LEFT_EYE_START = 43 - 1LEFT_EYE_END = 48 - 1while (self.cap.isOpened()):ret, frame = self.cap.read()gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)rects = detector(gray, 0)for rect in rects:shape = sp68(gray, rect)points = face_utils.shape_to_np(shape)leftEye = points[LEFT_EYE_START:LEFT_EYE_END + 1]rightEye = points[RIGHT_EYE_START:RIGHT_EYE_END + 1]leftEAR = eye_aspect_ratio(leftEye)rightEAR = eye_aspect_ratio(rightEye)ear = (leftEAR + rightEAR) / 2.0if ear < EYE_AR_THRESH:self.frame_counter += 1else:if self.frame_counter >= EYE_AR_CONSEC_FRAMES:self.blink_counter += 1self.frame_counter = 0cv2.putText(frame, "Blinks:{0}".format(self.blink_counter), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7,(0, 0, 255), 2)cv2.putText(frame, "EAR:{:.2f}".format(ear), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255),2)img = frameimg_rgb = cv2.cvtColor(src=img, code=cv2.COLOR_BGR2RGB)height, width, channel = img_rgb.shapebytesPerLine = channel * widthimg = QImage(img_rgb, width, height, bytesPerLine, QImage.Format_RGB888)res = QPixmap.fromImage(img).scaled(self.ui.label.width(), self.ui.label.height())self.ui.label.setPixmap(res)

使用的68位人脸检测模块：

整个程序结构如下：

整个程序通过如下代码进行启动：

import sys
import os
curPath = os.path.abspath(os.path.dirname(__file__))
rootPath = os.path.split(curPath)[0]
sys.path.append(rootPath)
from PyQt5.QtWidgets import QApplication, QMainWindow
from dlib_blink.Frm_blinking import Frm_blinkingdef main():app = QApplication(sys.argv)  # 应用程序实例对象w = Frm_blinking()  # 窗体对象w.show()  # 显示窗体sys.exit(app.exec_())  # 启动应用程序消息循环if __name__ == '__main__':main()

不足之处：

该程序只是简单的眨眼检测，所以受外界的影响较大，影响因素例如光线、角度等。主要难点在于线程，如果没有使用线程，整个界面是比较卡顿的，眨眼检测计数就比较不真实（虽然本身计数就不是很准确）。还有很多写的不好的地方，请多多理解，接受批评指正！

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pyqt5之眨眼检测

PYQT5 GUI界面之眨眼检测