基于Python+OpenCVdlib的疲劳驾驶检测系统源码+数据集+文档说明（高分优秀毕设）

# -*- coding: utf-8 -*- import dlib # 人脸识别的库dlib import cv2 # 图像处理的库OpenCv import wx # 构造显示界面的GUI import wx.xrc import wx.adv from scipy.spatial import distance as dist from imutils import face_utils import numpy as np # 数据处理的库 numpy import time import math import pyttsx3 import pythoncom from win32com import client import sats2 COVER = 'E:/Fatigue_detect/images/ui8.png' class Fatigue_detecting(wx.Frame): def __init__(self, parent, title): wx.Frame.__init__(self, parent, id=wx.ID_ANY, title=title, pos=wx.DefaultPosition, size=wx.Size(925, 535), style=wx.DEFAULT_FRAME_STYLE | wx.TAB_TRAVERSAL) self.SetSizeHints(wx.DefaultSize, wx.DefaultSize) self.SetBackgroundColour(wx.SystemSettings.GetColour(wx.SYS_COLOUR_MENU)) bSizer1 = wx.BoxSizer(wx.VERTICAL) bSizer2 = wx.BoxSizer(wx.HORIZONTAL) bSizer3 = wx.BoxSizer(wx.VERTICAL) self.m_animCtrl1 = wx.adv.AnimationCtrl(self, wx.ID_ANY, wx.adv.NullAnimation, wx.DefaultPosition, wx.DefaultSize, wx.adv.AC_DEFAULT_STYLE) bSizer3.Add(self.m_animCtrl1, 1, wx.ALL | wx.EXPAND, 5) bSizer2.Add(bSizer3, 9, wx.EXPAND, 5) bSizer4 = wx.BoxSizer(wx.VERTICAL) sbSizer1 = wx.StaticBoxSizer(wx.StaticBox(self, wx.ID_ANY, u"参数设置"), wx.VERTICAL) sbSizer2 = wx.StaticBoxSizer(wx.StaticBox(sbSizer1.GetStaticBox(), wx.ID_ANY, u"基础操作"), wx.VERTICAL) gSizer1 = wx.GridSizer(0, 2, 0, 8) self.m_choice1 = wx.Button(sbSizer2.GetStaticBox(), wx.ID_ANY, u"加载车载摄像头", wx.DefaultPosition, wx.Size(120, 60), 0) gSizer1.Add(self.m_choice1, 0, wx.ALL, 5) self.camera_button1 = wx.Button(sbSizer2.GetStaticBox(), wx.ID_ANY, u"开始检测", wx.DefaultPosition, wx.Size(120, 60), 0) gSizer1.Add(self.camera_button1, 0, wx.ALL, 5) self.off_button3 = wx.Button(sbSizer2.GetStaticBox(), wx.ID_ANY, u"暂停", wx.DefaultPosition, wx.Size(120, 60), 0) gSizer1.Add(self.off_button3, 0, wx.ALL, 5) self.off_button4 = wx.Button(sbSizer2.GetStaticBox(), wx.ID_ANY, u"退出检测", wx.DefaultPosition, wx.Size(120, 60), 0) gSizer1.Add(self.off_button4, 0, wx.ALL, 5) sbSizer2.Add(gSizer1, 1, wx.EXPAND, 5) sbSizer1.Add(sbSizer2, 2, wx.EXPAND, 5) sbSizer6 = wx.StaticBoxSizer(wx.StaticBox(sbSizer1.GetStaticBox(), wx.ID_ANY, u"状态输出"), wx.VERTICAL) self.m_textCtrl3 = wx.TextCtrl(sbSizer6.GetStaticBox(), wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, wx.TE_MULTILINE | wx.TE_READONLY) sbSizer6.Add(self.m_textCtrl3, 1, wx.ALL | wx.EXPAND, 5) sbSizer1.Add(sbSizer6, 5, wx.EXPAND, 5) bSizer4.Add(sbSizer1, 1, wx.EXPAND, 5) bSizer2.Add(bSizer4, 3, wx.EXPAND, 5) bSizer1.Add(bSizer2, 1, wx.EXPAND, 5) self.SetSizer(bSizer1) self.Layout() self.Centre(wx.BOTH) # Connect Events self.m_choice1.Bind(wx.EVT_BUTTON, self.prepare) self.camera_button1.Bind(wx.EVT_BUTTON, self.camera_on) # 开 self.off_button3.Bind(wx.EVT_BUTTON, self.off) # 关 self.off_button4.Bind(wx.EVT_BUTTON, self.exit) # 封面图片 self.image_cover = wx.Image(COVER, wx.BITMAP_TYPE_ANY) # 显示图片在m_animCtrl1上 self.bmp = wx.StaticBitmap(self.m_animCtrl1, -1, wx.Bitmap(self.image_cover)) # 设置窗口标题的图标 self.icon = wx.Icon('E:/Fatigue_detect/images/555.ico', wx.BITMAP_TYPE_ICO) self.SetIcon(self.icon) # 系统事件 self.Bind(wx.EVT_CLOSE, self.OnClose) """参数""" # 默认为摄像头0 self.VIDEO_STREAM = 0 self.CAMERA_STYLE = False # False未打开摄像头，True摄像头已打开 self.AR_CONSEC_FRAMES_check = 3 self.OUT_AR_CONSEC_FRAMES_check = 5 # 闪烁阈值（秒） # 眼睛长宽比 self.EYE_AR_THRESH = 0.2 self.EYE_AR_CONSEC_FRAMES = 3 # 打哈欠长宽比 self.MAR_THRESH = 0.5 self.MOUTH_AR_CONSEC_FRAMES = 3 # 瞌睡点头 self.HAR_THRESH = 0.3 self.NOD_AR_CONSEC_FRAMES = 5 """计数""" # 初始化帧计数器和眨眼总数 self.COUNTER = 0 self.TOTAL = 0 # 初始化帧计数器和打哈欠总数 self.mCOUNTER = 0 self.mTOTAL = 0 # 初始化帧计数器和点头总数 self.hCOUNTER = 0 self.hTOTAL = 0 # 离职时间长度 self.oCOUNTER = 0 # 初始化眨眼频率,点头频率，打哈欠频率 self.frequency = 0 self.hfrequency = 0 self.yfrequency = 0 # 初始化疲劳程度 self.score = 0 """姿态""" # 世界坐标系(UVW)：填写3D参考点，该模型参考http://aifi.isr.uc.pt/Downloads/OpenGL/glAnthropometric3DModel.cpp self.object_pts = np.float32([[6.825897, 6.760612, 4.402142], # 33左眉左上角 [1.330353, 7.122144, 6.903745], # 29左眉右角 [-1.330353, 7.122144, 6.903745], # 34右眉左角 [-6.825897, 6.760612, 4.402142], # 38右眉右上角 [5.311432, 5.485328, 3.987654], # 13左眼左上角 [1.789930, 5.393625, 4.413414], # 17左眼右上角 [-1.789930, 5.393625, 4.413414], # 25右眼左上角 [-5.311432, 5.485328, 3.987654], # 21右眼右上角 [2.005628, 1.409845, 6.165652], # 55鼻子左上角 [-2.005628, 1.409845, 6.165652], # 49鼻子右上角 [2.774015, -2.080775, 5.048531], # 43嘴左上角 [-2.774015, -2.080775, 5.048531], # 39嘴右上角 [0.000000, -3.116408, 6.097667], # 45嘴中央下角 [0.000000, -7.415691, 4.070434]]) # 6下巴角 # 相机坐标系(XYZ)：添加相机内参 self.K = [6.5308391993466671e+002, 0.0, 3.1950000000000000e+002, 0.0, 6.5308391993466671e+002, 2.3950000000000000e+002, 0.0, 0.0, 1.0] # 等价于矩阵[fx, 0, cx; 0, fy, cy; 0, 0, 1] # 图像中心坐标系(uv)：相机畸变参数[k1, k2, p1, p2, k3] self.D = [7.0834633684407095e-002, 6.9140193737175351e-002, 0.0, 0.0, -1.3073460323689292e+000] # 像素坐标系(xy)：填写凸轮的本征和畸变系数 self.cam_matrix = np.array(self.K).reshape(3, 3).astype(np.float32) self.dist_coeffs = np.array(self.D).reshape(5, 1).astype(np.float32) # 重新投影3D点的世界坐标轴以验证结果姿势 self.reprojectsrc = np.float32([[10.0, 10.0, 10.0], [10.0, 10.0, -10.0], [10.0, -10.0, -10.0], [10.0, -10.0, 10.0], [-10.0, 10.0, 10.0], [-10.0, 10.0, -10.0], [-10.0, -10.0, -10.0], [-10.0, -10.0, 10.0]]) # 绘制正方体12轴 self.line_pairs = [[0, 1], [1, 2], [2, 3], [3, 0], [4, 5], [5, 6], [6, 7], [7, 4], [0, 4], [1, 5], [2, 6], [3, 7]] def __del__(self): pass def get_head_pose(self, shape): # 头部姿态估计