基于深度学习SSD算法实现驾驶员危险驾驶行为检测系统源码+模型+项目说明.zip

import datetime from PyQt5 import QtWidgets from qimage2ndarray.dynqt import QtGui from mtcnn.detector import detect_faces, show_bboxes, get_face_expression, get_head_pose, get_emotion, get_face_state from MainWindow import Ui_MainWindow import sys from PyQt5.QtWidgets import QApplication, QMainWindow, QFileDialog from PyQt5.QtCore import QTimer, QCoreApplication, QDateTime from PyQt5.QtGui import QPixmap, QImage, QTextCursor import qimage2ndarray from torch.autograd import * from detection import * import os # os.environ["CUDA_VISIBLE_DEVICES"] = "-1" from ssd_net_vgg import * from voc0712 import * import torch import torch.nn as nn import numpy as np import cv2 import utils import torch.backends.cudnn as cudnn import time class CameraShow(QMainWindow, Ui_MainWindow): def __del__(self): try: self.camera.release() # 释放资源 except: return def __init__(self, parent=None): super(CameraShow, self).__init__(parent) self.setupUi(self) self.Timer = QTimer() self.timer = QTimer() self.time_first = time.time() self.time_ing = time.time() self.Timer.timeout.connect(self.show_img) self.timer.timeout.connect(self.showTime) self.PrepCamera() self.PrepareTorch() self.CallBackFunctions() self.showTime() self.case = 0 self.frag_cap = True # self.Timer.timeout.connect(self.TimerOutFun) self.video_flg = True self.colors_tableau = [(214, 39, 40), (23, 190, 207), (188, 189, 34), (188, 34, 188), (205, 108, 8), (150, 34, 188), (105, 108, 8)] # 初始化网络 self.net = SSD() self.net = torch.nn.DataParallel(self.net) self.net.train(mode=False) # net.load_state_dict(torch.load('./weights/ssd300_VOC_100000.pth',map_location=lambda storage,loc: storage)) # self.net.load_state_dict( # torch.load('./weights/final_20200226_VOC_100000.pth', map_location=lambda storage, loc: storage)) self.net.load_state_dict(torch.load('./weights/final_20200226_VOC_100000.pth',map_location=lambda storage, loc: storage.cuda(0))) device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") self.net.to(device) if torch.cuda.is_available(): self.net = self.net.cuda() cudnn.benchmark = True self.net = self.net.cuda() self.img_mean = (104.0, 117.0, 123.0) self.max_fps = 0 filename = ('E:\PythonEye\Dataset\\3-FemaleGlasses.mp4') # 保存检测结果的List # 眼睛和嘴巴都是，张开为‘1’，闭合为‘0’ self.Image_num = 0 self.RecordPath = 'E:/PythonEye/DachuangProject/test/3-FemaleGlasses.mp4' self.VideoPath.setText(self.RecordPath) self.isRecordImg = False self.EMOTIONS = ["生气", "厌恶", "害怕", "喜悦", "悲伤", "惊讶", "普通"] # prepare def PrepCamera(self): try: self.camera = cv2.VideoCapture(0) self.Image_num = 0 self.Msg.clear() self.Msg.append('Oboard camera connected.') self.Msg.setPlainText() self.showTime() except Exception as e: self.Msg.clear() self.Msg.append(str(e)) def CallBackFunctions(self): self.BtnRecord.clicked.connect(self.setRecordImg) self.btntestcamera.clicked.connect(self.testCamera) # self.StopBt.clicked.connect(self.StopCamera) self.btn_start.clicked.connect(self.StartDection) self.btnexit.clicked.connect(self.ExitApp) self.btn_testvideo.clicked.connect(self.testVideo) self.BtnReadvideo.clicked.connect(self.setFilePath) # 显示时间 def showTime(self): # time = QDateTime.currentDateTime() now_time = datetime.datetime.now() self.timer.start() # timeDisplay = time.toString("yyyy-MM-dd hh:mm:ss dddd") hour = now_time.strftime('%H') minute = now_time.strftime('%M') second = now_time.strftime('%S') self.TimeHourLCD.display(hour) self.TimeMinuteLCD.display(minute) self.TimeSecondLCD.display(second) def ColorAdjust(self, img): try: B = img[:, :, 0] G = img[:, :, 1] R = img[:, :, 2] img1 = img img1[:, :, 0] = B img1[:, :, 1] = G img1[:, :, 2] = R return img1 except Exception as e: self.Msg.setPlainText(str(e)) # 打开相机 def testCamera(self): # self.camera = cv2.VideoCapture(0) if self.Timer.isActive() == False: flag = self.camera.open(0) if flag == False: msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确", buttons=QtWidgets.QMessageBox.Ok, defaultButton=QtWidgets.QMessageBox.Ok) else: self.case = 1 self.timelb = time.clock() self.btntestcamera.setText(u'关闭相机') self.btn_start.setEnabled(False) self.btn_testvideo.setEnabled(False) self.Image_num = 0 self.Timer.start(30) else: self.Timer.stop() self.camera.release() # self.Camera.clear() self.Camera_2.clear() self.btntestcamera.setText(u'打开相机') self.btn_start.setEnabled(True) self.btn_testvideo.setEnabled(True) def PrepareTorch(self): if torch.cuda.is_available(): print('-----gpu mode-----') torch.set_default_tensor_type('torch.cuda.FloatTensor') else: print('-----cpu mode-----') def TimerOutFun(self): success, img = self.camera.read() if success: self.Image = self.ColorAdjust(img) self.showTime() self.Image_num += 1 if self.Image_num % 10 == 9: frame_rate = 10 / (time.clock() - self.timelb) self.FmRateLCD.display(frame_rate) self.timelb = time.clock() else: self.Msg.clear() self.Msg.setPlainText('Image obtaining failed.') def StartDection(self): if self.Timer.isActive() == False: flag = self.camera.open(0) if flag == False: msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确", buttons=QtWidgets.QMessageBox.Ok, defaultButton=QtWidgets.QMessageBox.Ok) else: self.list_B = np.ones(10) # 眼睛状态List,建议根据fps修改 self.list_Y = np.zeros(50) # 嘴巴状态list，建议根据fps修改 self.list_Y1 = np.ones(8) # 如果在list_Y中存在list_Y1，则判定一次打哈欠，同上，长度建议修改 self.blink_count = 0 # 眨眼计数 self.list_blink=np.ones(60) #判断60帧的睁眼闭眼 self.danger_count=0#危险行为帧 self.yawn_count = 0#哈欠帧 self.blink_freq = 0.5 self.yawn_freq = 0 self.timelb = time.clock() self.btn_start.setText(u'停止运行') self.btntestcamera.setEnabled(False) self.btn_testvideo.setEnabled(False) self.open_t = 0 # 用于刷新眼部状态label self.danger_t=0 #用于刷新危险行为状态 self.blink_start = time.time() # 眨眼时间 self.yawn_start = time.time() # 打哈欠时间