• 利用opencv 做一个疲劳检测系统（2）

    文章目录

    杂谈

    最近发现视力下降严重， 可能跟我的过度用眼有关，于是想着能不能做一个检测用眼疲劳的，灵感来自特斯拉的疲劳检测系统。
    效果如下：
    在这里插入图片描述

    实现步骤

    1. 实现核心算法
    2. 制作交互界面
    3. 设计交互逻辑

    核心算法

    疲劳检测算法讲解：
    利用dlib 人脸检测算法来捕获人脸的关键点数（68个关键点）
    参考文章：https://blog.csdn.net/monk96/article/details/127751414?spm=1001.2014.3001.5502

    获取眼睛和嘴巴的点位置
    在这里插入图片描述
    在这里插入图片描述

    眼睛疲劳计算公式
    利用欧拉距离计算
    dist = (||P2 - P6|| + ||P3 - P5||)/ 2 * ||P1 - P4||

    对应就是上下距离 与左右的比值， 然后我们设定一个阈值，比如说0.3， 另外设置帧数，如3帧，超过3帧则 检测为闭眼， 在闭眼总数上加1，如果闭眼次数超过设定的阈值（6次），判断为疲劳状态。
    哈欠疲劳计算公式

    哈欠用于眼睛相同的计算方式来计算打哈欠， 同样设置阈值和帧数， 不同点是在于哈欠是设定为0.8。
    tips： 这里需要设置多少时间内没闭眼，这去除计数器，不然长时间的检测，肯定会超过阈值

    这里需要拿到眼睛的位置进行计算，引入欧拉距离工具

    from scipy.spatial import distance as dist 
from collections import OrderedDict

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    设定点位（固定的）

    self.LANDMARKS = OrderedDict([
            ("mouth", (48, 68)),
            ("right_eyebrow", (17, 22)),
            ("left_eyebrow", (22, 27)),
            ("right_eye", (36, 42)),
            ("left_eye", (42, 48)),
            ("nose", (27, 36)),
            ("jaw", (0, 17))
        ])
self.EYE_THRESH = 0.3
        self.EYE_FRAMES = 3
        self.COUNTER_FRAMES = 0
        self.TOTAL = 0
        self.MOUSE_UP_FRAMES = 5
        self.MOUSE_COUNTER_FRAMES = 0
        self.MOUSE_RATE = 0.8
        (self.lStart, self.lEnd) = self.LANDMARKS['left_eye']
        (self.rStart, self.rEnd) = self.LANDMARKS['right_eye']
        (self.mStart, self.mEnd) = self.LANDMARKS['mouth']

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    计算大小 这里计算欧拉距离，然后再把距离进行平均，减少误差

    def eye_aspect_ratio(self, eye):
        A = dist.euclidean(eye[1], eye[5])
        B = dist.euclidean(eye[2], eye[4])
        C = dist.euclidean(eye[0], eye[3])
        return (A + B) / (2 * C)
def cal_height(self, points):
        leftEye = points[self.lStart: self.lEnd]
        rightEye = points[self.rStart: self.rEnd]
        leftEAR = self.eye_aspect_ratio(leftEye)
        rightEAR = self.eye_aspect_ratio(rightEye)
        return (leftEAR + rightEAR)/2

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    设定检测的方法：这里用来每一帧检测图片，并返回信息给到交互界面

    def skim_video(self, img, ha, eye, warn):
            img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
            # 人脸数rects
            rects = self.detector(img_gray, 0)
            close_eye = False
            for i in range(len(rects)):
                faces = self.predictor(img, rects[i]).parts()
                points = np.matrix([[p.x, p.y] for p in faces])
                rate = self.cal_height(points)  # 闭眼
                rate_mouse = self.cal_mouse_height(points) # 哈欠
                if rate_mouse > self.MOUSE_RATE and ha:
                    self.MOUSE_COUNTER_FRAMES += 1
                    if self.MOUSE_COUNTER_FRAMES >= self.MOUSE_UP_FRAMES:
                        print('打哈欠')
                        cv2.putText(img, "haha", (rects[i].left(), rects[i].top() - 60), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255))   
                        
                if rate < self.EYE_THRESH and eye:
                    self.COUNTER_FRAMES += 1
                    # print('闭眼检测到了，第%s次'%COUNTER_FRAMES)
                    if self.COUNTER_FRAMES >= 5:
                        self.TOTAL += 1
                        self.COUNTER_FRAMES = 0
                        close_eye = True
                else:
                    self.COUNTER_FRAMES = 0
                # for idx, point in enumerate(points):
                #     pos = (point[0, 0], point[0, 1])
                #     cv2.circle(img, pos, 2, (0, 0, 255), 1)
                #     cv2.putText(img, str(idx + 1), pos, cv2.FONT_HERSHEY_SIMPLEX, 0.3, (0, 255, 255))  
                if self.TOTAL >= 10 and warn:
                        cv2.rectangle(img, (rects[i].left(), rects[i].top()), (rects[i].right(), rects[i].bottom()), color= (255, 0, 255))
                        cv2.putText(img, "tired", (rects[i].left(), rects[i].top() - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255))   
                        print('warning， 您已疲劳，请尽快休息')    
            return "%s闭眼"%time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) if close_eye else "", img


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    完整的数据处理类

    import numpy as np
import dlib 
import cv2 
import sys
import time
sys.path.append("..")
from scipy.spatial import distance as dist 
from collections import OrderedDict

class Recognize():
    
    def __init__(self):
        self.init_data()
        self.init_model()
    def init_data(self):
        self.LANDMARKS = OrderedDict([
            ("mouth", (48, 68)),
            ("right_eyebrow", (17, 22)),
            ("left_eyebrow", (22, 27)),
            ("right_eye", (36, 42)),
            ("left_eye", (42, 48)),
            ("nose", (27, 36)),
            ("jaw", (0, 17))
        ])
        self.EYE_THRESH = 0.3
        self.EYE_FRAMES = 3
        self.COUNTER_FRAMES = 0
        self.TOTAL = 0
        self.MOUSE_UP_FRAMES = 5
        self.MOUSE_COUNTER_FRAMES = 0
        self.MOUSE_RATE = 0.8
        (self.lStart, self.lEnd) = self.LANDMARKS['left_eye']
        (self.rStart, self.rEnd) = self.LANDMARKS['right_eye']
        (self.mStart, self.mEnd) = self.LANDMARKS['mouth']

    def cal_height(self, points):
        leftEye = points[self.lStart: self.lEnd]
        rightEye = points[self.rStart: self.rEnd]
        leftEAR = self.eye_aspect_ratio(leftEye)
        rightEAR = self.eye_aspect_ratio(rightEye)
        return (leftEAR + rightEAR)/2
    
    def cal_mouse_height(self, points):
        mouse = points[self.mStart: self.mEnd]
        mouse_rate = self.mouse_aspect_ratio(mouse)
        return mouse_rate
    
    def mouse_aspect_ratio(self, mouse):
        A = dist.euclidean(mouse[2],mouse[9])
        B = dist.euclidean(mouse[4],mouse[7])
        C = dist.euclidean(mouse[0],mouse[6])
        return (A+ B) / (2 * C)
    def eye_aspect_ratio(self, eye):
        A = dist.euclidean(eye[1], eye[5])
        B = dist.euclidean(eye[2], eye[4])
        C = dist.euclidean(eye[0], eye[3])
        return (A + B) / (2 * C)

    def init_model(self):
        self.detector = dlib.get_frontal_face_detector()
        self.predictor = dlib.shape_predictor('F:/python/ML/11-learn/tired/model_data/shape_predictor_68_face_landmarks.dat')

    def init_video_capture(self, method):
        if method == 0:
            self.capture = cv2.VideoCapture(0)
        else:
            self.capture = cv2.VideoCapture(method)
    
    def skim_video(self, img, ha, eye, warn):
            img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
            # 人脸数rects
            rects = self.detector(img_gray, 0)
            close_eye = False
            for i in range(len(rects)):
                faces = self.predictor(img, rects[i]).parts()
                points = np.matrix([[p.x, p.y] for p in faces])
                rate = self.cal_height(points)  # 闭眼
                rate_mouse = self.cal_mouse_height(points) # 哈欠
                if rate_mouse > self.MOUSE_RATE and ha:
                    self.MOUSE_COUNTER_FRAMES += 1
                    if self.MOUSE_COUNTER_FRAMES >= self.MOUSE_UP_FRAMES:
                        print('打哈欠')
                        cv2.putText(img, "haha", (rects[i].left(), rects[i].top() - 60), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255))   
                        
                if rate < self.EYE_THRESH and eye:
                    self.COUNTER_FRAMES += 1
                    # print('闭眼检测到了，第%s次'%COUNTER_FRAMES)
                    if self.COUNTER_FRAMES >= 5:
                        self.TOTAL += 1
                        self.COUNTER_FRAMES = 0
                        close_eye = True
                else:
                    self.COUNTER_FRAMES = 0
                # for idx, point in enumerate(points):
                #     pos = (point[0, 0], point[0, 1])
                #     cv2.circle(img, pos, 2, (0, 0, 255), 1)
                #     cv2.putText(img, str(idx + 1), pos, cv2.FONT_HERSHEY_SIMPLEX, 0.3, (0, 255, 255))  
                if self.TOTAL >= 10 and warn:
                        cv2.rectangle(img, (rects[i].left(), rects[i].top()), (rects[i].right(), rects[i].bottom()), color= (255, 0, 255))
                        cv2.putText(img, "tired", (rects[i].left(), rects[i].top() - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255))   
                        print('warning， 您已疲劳，请尽快休息')    
            return "%s闭眼"%time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) if close_eye else "", img
# print('结束检测，检测到了%s次疲劳闭眼'%TOTAL)


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    交互界面

    交互界面利用qtdesigner， 可视化的设计， 再转化成python语言进行操作。

    在这里插入图片描述

    交互代码

    # 控件绑定相关操作
        def init_slots(self):
                self.ui.tired_time.setValue(3)
                self.ui.tired_count.setValue(6)
                self.ui.eye.setChecked(True)
                self.ui.video.setChecked(True)
                
                self.ui.select_video.clicked.connect(self.button_video_open)
                self.ui.start_skim.clicked.connect(self.toggleState)
                self.ui.camera.clicked.connect(partial(self.change_method, METHOD.CAMERA))
                self.ui.video.clicked.connect(partial(self.change_method, METHOD.VIDEO))

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    暂停和开始： 这里利用了QtCore.QTimer() 的方法，里面有开始和暂停的api可以调用

    



import argparse
import random
import sys
import time


sys.path.append("..")
from ui import detect
from logic.recognize import Recognize
import torch
from PyQt5.QtWidgets import *
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtWidgets import QApplication,QMainWindow
from functools import partial
import torch.backends.cudnn as cudnn
import cv2 as cv
import numpy as np
class METHOD():
        CAMERA = 0
        VIDEO = 1
# pyuic5 -o name.py test.ui
class UI_Logic_Window(QtWidgets.QMainWindow):
        def __init__(self, parent = None):
                super(UI_Logic_Window, self).__init__(parent)
                self.timer_video = QtCore.QTimer() # 创建定时器
                #创建一个窗口
                self.w = QMainWindow()
                self.ui = detect.Ui_DREAM_EYE()
                self.ui.setupUi(self)
                self.init_slots()
                self.output_folder = 'output/'
                self.cap = cv.VideoCapture()
                # 日志
                self.logging = ''
                self.recognize = Recognize()    
       # 控件绑定相关操作
        def init_slots(self):
                self.ui.tired_time.setValue(3)
                self.ui.tired_count.setValue(6)
                self.ui.eye.setChecked(True)
                self.ui.video.setChecked(True)
                
                self.ui.select_video.clicked.connect(self.button_video_open)
                self.ui.start_skim.clicked.connect(self.toggleState)
                self.ui.camera.clicked.connect(partial(self.change_method, METHOD.CAMERA))
                self.ui.video.clicked.connect(partial(self.change_method, METHOD.VIDEO))
                
                # self.ui.capScan.clicked.connect(self.button_camera_open)
                # self.ui.loadWeight.clicked.connect(self.open_model)
                # self.ui.initModel.clicked.connect(self.model_init)
                # self.ui.start_skim.clicked.connect(self.toggleState)
                # self.ui.end.clicked.connect(self.endVideo)
                #         # self.ui.pushButton_stop.clicked.connect(self.button_video_stop)
                #         # self.ui.pushButton_finish.clicked.connect(self.finish_detect)
                self.timer_video.timeout.connect(self.show_video_frame) # 定时器超时，将槽绑定至show_video_frame
                
        def change_method(self, type):
                if type == METHOD.CAMERA:
                   self.ui.select_video.setDisabled(True)
                else:
                   self.ui.select_video.setDisabled(False)
                        
        def button_image_open(self):
            print('button_image_open')
            name_list = []
            try:
                img_name, _ = QtWidgets.QFileDialog.getOpenFileName(self, "选择文件")
            except OSError as reason:
                print('文件出错啦')
                QtWidgets.QMessageBox.warning(self, 'Warning', '文件出错', buttons=QtWidgets.QMessageBox.Ok)
            else:
                if not img_name:
                   QtWidgets.QMessageBox.warning(self,"Warning", '文件出错', buttons=QtWidgets.QMessageBox.Ok)
                   self.log('文件出错')
                else:
                    img = cv.imread(img_name)
                    info_show = self.recognize.skim_video(img)
                    date = time.strftime('%Y-%m-%d-%H-%M-%S', time.localtime(time.time())) # 当前时间
                    file_extaction = img_name.split('.')[-1]
                    new_fileName = date + '.' + file_extaction
                    file_path = self.output_folder + 'img_output/' + new_fileName
                    cv.imwrite(file_path, img)
                    self.show_img(info_show, img)
                    
                #     self.log(info_show) #检测信息
                    
                #     self.result = cv.cvtColor(img, cv.COLOR_BGR2BGRA)
                    
                #     self.result =  letterbox(self.result, new_shape=self.opt.img_size)[0] #cv.resize(self.result, (640, 480), interpolation=cv.INTER_AREA)
                #     self.QtImg = QtGui.QImage(self.result.data, self.result.shape[1], self.result.shape[0], QtGui.QImage.Format_RGB32)
                #     print(type(self.ui.show))
                #     self.ui.show.setPixmap(QtGui.QPixmap.fromImage(self.QtImg))
                #     self.ui.show.setScaledContents(True) # 设置图像自适应界面大小
        def show_img(self, info_show, img):
                if info_show:
                    self.log(info_show)
                show = cv.resize(img, (640, 480)) # 直接将原始img上的检测结果进行显示
                self.result = cv.cvtColor(show, cv.COLOR_BGR2RGB)
                showImage = QtGui.QImage(self.result.data, self.result.shape[1], self.result.shape[0],
                                     QtGui.QImage.Format_RGB888)
                self.ui.capture.setPixmap(QtGui.QPixmap.fromImage(showImage))
                self.ui.capture.setScaledContents(True)  # 设置图像自适应界面大小
        def toggleState(self):
                print('toggle')
                state = self.timer_video.signalsBlocked()
                self.timer_video.blockSignals(not state)
                text = '继续' if not state else '暂停'
                self.ui.start_skim.setText(text)
        def endVideo(self):
                print('end')
                self.timer_video.blockSignals(True)
                self.releaseRes()
              
        def button_video_open(self):
                video_path, _ = QtWidgets.QFileDialog.getOpenFileName(self, '选择检测视频', './', filter="*.mp4;;*.avi;;All Files(*)")
                self.ui.video_path.setText(video_path)
                flag = self.cap.open(video_path)
                if not flag:
                        QtWidgets.QMessageBox.warning(self,"Warning", '打开视频失败', buttons=QtWidgets.QMessageBox.Ok)
                else: 
                        self.timer_video.start(1000/self.cap.get(cv.CAP_PROP_FPS)) # 以30ms为间隔，启动或重启定时器
                        # if self.opt.save:
                        #         fps, w, h, path = self.set_video_name_and_path()
                        #         self.vid_writer = cv.VideoWriter(path, cv.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
        def set_video_name_and_path(self):
                # 获取当前系统时间，作为img和video的文件名
                now = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime(time.time()))
                # if vid_cap:  # video
                fps = self.cap.get(cv.CAP_PROP_FPS)
                w = int(self.cap.get(cv.CAP_PROP_FRAME_WIDTH))
                h = int(self.cap.get(cv.CAP_PROP_FRAME_HEIGHT))
                # 视频检测结果存储位置
                save_path = self.output_folder + 'video/' + now + '.mp4'
                return fps, w, h, save_path

        def button_camera_open(self):
                camera_num = 0
                self.cap = cv.VideoCapture(camera_num)
                if not self.cap.isOpened():
                        QtWidgets.QMessageBox.warning(self, u"Warning", u'摄像头打开失败', buttons=QtWidgets.QMessageBox.Ok)
                else:
                        self.timer_video.start(1000/60)
                        if self.opt.save:
                                fps, w, h, path = self.set_video_name_and_path()
                                self.vid_writer = cv.VideoWriter(path, cv.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
                        
        def open_model(self):
                self.openfile_name_model, _ = QFileDialog.getOpenFileName(self, '选择权重文件', directory='./yolov5\yolo\YoloV5_PyQt5-main\weights')
                print(self.openfile_name_model)
                if not self.openfile_name_model:
                #    QtWidgets.QMessageBox.warning(self, u"Warning" u'未选择权重文件，请重试', buttons=QtWidgets.QMessageBox.Ok)
                   self.log("warining 未选择权重文件，请重试")
                else :
                   print(self.openfile_name_model)
                   self.log("权重文件路径为：%s"%self.openfile_name_model)
                pass
        
        def show_video_frame(self):
                name_list = []
                flag, img = self.cap.read()
                if img is None:
                       self.releaseRes() 
                else:
                        close_eye, img = self.recognize.skim_video(img, self.ui.ha.checkState(), self.ui.eye.checkState(), self.ui.tired.checkState())
                        # if self.opt.save:
                        #         self.vid_writer.write(img) # 检测结果写入视频
                        self.show_img(close_eye, img)
        def releaseRes(self):
                        print('读取结束')
                        self.log('检测结束')
                        self.timer_video.stop()
                        self.cap.release() # 释放video_capture资源
                        self.ui.show.clear()
                        if self.opt.save:
                                self.vid_writer.release()               
        def log(self, msg):
                self.logging += '%s\n'%msg
                self.ui.log.setText(self.logging)
                self.ui.log.moveCursor(QtGui.QTextCursor.End)
if __name__=='__main__':
    # 创建QApplication实例
    app=QApplication(sys.argv)#获取命令行参数
    current_ui = UI_Logic_Window()
    current_ui.show()
    sys.exit(app.exec_())
    

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    界面代码

    # -*- coding: utf-8 -*-

# Form implementation generated from reading ui file 'detect_ui.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!

from PyQt5 import QtCore, QtGui, QtWidgets

class Ui_DREAM_EYE(object):
    def setupUi(self, DREAM_EYE):
        DREAM_EYE.setObjectName("DREAM_EYE")
        DREAM_EYE.resize(936, 636)
        icon = QtGui.QIcon()
        icon.addPixmap(QtGui.QPixmap("../../ui_img/icon.jpg"), QtGui.QIcon.Normal, QtGui.QIcon.Off)
        DREAM_EYE.setWindowIcon(icon)
        self.centralwidget = QtWidgets.QWidget(DREAM_EYE)
        self.centralwidget.setEnabled(True)
        sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed)
        sizePolicy.setHorizontalStretch(0)
        sizePolicy.setVerticalStretch(0)
        sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().hasHeightForWidth())
        self.centralwidget.setSizePolicy(sizePolicy)
        self.centralwidget.setObjectName("centralwidget")
        self.groupBox = QtWidgets.QGroupBox(self.centralwidget)
        self.groupBox.setGeometry(QtCore.QRect(640, 10, 311, 621))
        font = QtGui.QFont()
        font.setFamily("Microsoft YaHei")
        font.setPointSize(11)
        self.groupBox.setFont(font)
        self.groupBox.setObjectName("groupBox")
        self.groupBox_2 = QtWidgets.QGroupBox(self.groupBox)
        self.groupBox_2.setGeometry(QtCore.QRect(10, 270, 271, 151))
        self.groupBox_2.setObjectName("groupBox_2")
        self.camera = QtWidgets.QRadioButton(self.groupBox_2)
        self.camera.setGeometry(QtCore.QRect(20, 30, 89, 16))
        self.camera.setObjectName("camera")
        self.video = QtWidgets.QRadioButton(self.groupBox_2)
        self.video.setGeometry(QtCore.QRect(140, 30, 89, 16))
        self.video.setObjectName("video")
        self.label = QtWidgets.QLabel(self.groupBox_2)
        self.label.setGeometry(QtCore.QRect(20, 60, 81, 31))
        self.label.setObjectName("label")
        self.select_video = QtWidgets.QPushButton(self.groupBox_2)
        self.select_video.setGeometry(QtCore.QRect(30, 110, 81, 31))
        self.select_video.setObjectName("select_video")
        self.start_skim = QtWidgets.QPushButton(self.groupBox_2)
        self.start_skim.setGeometry(QtCore.QRect(150, 110, 81, 31))
        self.start_skim.setObjectName("start_skim")
        self.video_path = QtWidgets.QTextEdit(self.groupBox_2)
        self.video_path.setGeometry(QtCore.QRect(110, 60, 151, 31))
        self.video_path.setObjectName("video_path")
        self.groupBox_3 = QtWidgets.QGroupBox(self.groupBox)
        self.groupBox_3.setGeometry(QtCore.QRect(10, 30, 271, 111))
        self.groupBox_3.setObjectName("groupBox_3")
        self.eye = QtWidgets.QCheckBox(self.groupBox_3)
        self.eye.setGeometry(QtCore.QRect(20, 30, 91, 21))
        self.eye.setObjectName("eye")
        self.ha = QtWidgets.QCheckBox(self.groupBox_3)
        self.ha.setGeometry(QtCore.QRect(150, 30, 91, 21))
        self.ha.setObjectName("ha")
        self.head = QtWidgets.QCheckBox(self.groupBox_3)
        self.head.setGeometry(QtCore.QRect(20, 70, 91, 21))
        self.head.setObjectName("head")
        self.tired = QtWidgets.QCheckBox(self.groupBox_3)
        self.tired.setGeometry(QtCore.QRect(150, 70, 91, 21))
        self.tired.setObjectName("tired")
        self.groupBox_5 = QtWidgets.QGroupBox(self.groupBox)
        self.groupBox_5.setGeometry(QtCore.QRect(10, 430, 271, 181))
        self.groupBox_5.setObjectName("groupBox_5")
        self.log = QtWidgets.QTextBrowser(self.groupBox_5)
        self.log.setGeometry(QtCore.QRect(10, 30, 251, 141))
        self.log.setObjectName("log")
        self.groupBox_4 = QtWidgets.QGroupBox(self.groupBox)
        self.groupBox_4.setGeometry(QtCore.QRect(10, 150, 271, 111))
        self.groupBox_4.setObjectName("groupBox_4")
        self.label_3 = QtWidgets.QLabel(self.groupBox_4)
        self.label_3.setGeometry(QtCore.QRect(20, 30, 81, 21))
        self.label_3.setObjectName("label_3")
        self.tired_time = QtWidgets.QSpinBox(self.groupBox_4)
        self.tired_time.setGeometry(QtCore.QRect(100, 30, 42, 22))
        self.tired_time.setObjectName("tired_time")
        self.label_4 = QtWidgets.QLabel(self.groupBox_4)
        self.label_4.setGeometry(QtCore.QRect(20, 70, 81, 21))
        self.label_4.setObjectName("label_4")
        self.tired_count = QtWidgets.QSpinBox(self.groupBox_4)
        self.tired_count.setGeometry(QtCore.QRect(100, 70, 42, 22))
        self.tired_count.setObjectName("tired_count")
        self.capture = QtWidgets.QLabel(self.centralwidget)
        self.capture.setGeometry(QtCore.QRect(10, 10, 611, 611))
        self.capture.setText("")
        self.capture.setObjectName("capture")
        DREAM_EYE.setCentralWidget(self.centralwidget)

        self.retranslateUi(DREAM_EYE)
        QtCore.QMetaObject.connectSlotsByName(DREAM_EYE)

    def retranslateUi(self, DREAM_EYE):
        _translate = QtCore.QCoreApplication.translate
        DREAM_EYE.setWindowTitle(_translate("DREAM_EYE", "疲劳检测系统"))
        self.groupBox.setTitle(_translate("DREAM_EYE", "参数设置"))
        self.groupBox_2.setTitle(_translate("DREAM_EYE", "视频源"))
        self.camera.setText(_translate("DREAM_EYE", "摄像头"))
        self.video.setText(_translate("DREAM_EYE", "视频文件"))
        self.label.setText(_translate("DREAM_EYE", "视频地址："))
        self.select_video.setText(_translate("DREAM_EYE", "选择文件"))
        self.start_skim.setText(_translate("DREAM_EYE", "确定"))
        self.groupBox_3.setTitle(_translate("DREAM_EYE", "疲劳检测"))
        self.eye.setText(_translate("DREAM_EYE", "闭眼检测"))
        self.ha.setText(_translate("DREAM_EYE", "哈欠检测"))
        self.head.setText(_translate("DREAM_EYE", "瞌睡检测"))
        self.tired.setText(_translate("DREAM_EYE", "疲劳预警"))
        self.groupBox_5.setTitle(_translate("DREAM_EYE", "输出"))
        self.groupBox_4.setTitle(_translate("DREAM_EYE", "检测设置"))
        self.label_3.setText(_translate("DREAM_EYE", "疲劳时间："))
        self.label_4.setText(_translate("DREAM_EYE", "疲劳次数："))


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    检测效果

    效果还不错，不过对于不是那么明显的情况可能就不是很好了，如光线不好，人脸不全的情况。
    接下来可以放到你笔记本上，让他定时提醒你休息。

    源代码

    https://github.com/cdmstrong/tried

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  • 原文地址：https://blog.csdn.net/monk96/article/details/127774115