class XioFigurePlot(QtGui.QWidget):
'''这个类为绘制类
'''
def __init__(self):
super(XioFigurePlot, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.thread_figure = Timer('updatePlay()', sleep_time=2)
self.connect(self.thread_figure, QtCore.SIGNAL('updatePlay()'), self.draw)
self.thread_figure.start()
def draw(self):
def draw_fp(): # 绘制损失饼图
fp = Figure_Pie()
da=data_access.EquipmentData()
result=da.select()
fp.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4])) # '*'有一个解包的功能，将（1，1，1，1）解包为 1 1 1 1
graphicscene_fp = QtGui.QGraphicsScene()
graphicscene_fp.addWidget(fp.canvas)
self.ui.graphicsView_Pie.setScene(graphicscene_fp)
self.ui.graphicsView_Pie.show()
def draw_oee(): # 绘制oee日推图
L_eff=[]
oee = Figure_OEE()
da=data_access.OEEData()
result=da.select()
for i in range(1,len(result[-1])):
if result[-1][i]!=None:
L_eff.append(result[-1][i])
oee.plot(*tuple(L_eff)) # 参数
graphicscene_oee = QtGui.QGraphicsScene()
graphicscene_oee.addWidget(oee.canvas)
self.ui.graphicsView_OEE.setScene(graphicscene_oee)
self.ui.graphicsView_OEE.show()
def draw_loss(): # 绘制损失直方图
loss = Figure_Loss()
da=data_access.EquipmentTimeData()
result = da.select()
loss.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4]))
graphicscene_loss = QtGui.QGraphicsScene()
graphicscene_loss.addWidget(loss.canvas)
self.ui.graphicsView_Loss.setScene(graphicscene_loss)
self.ui.graphicsView_Loss.show()
def draw_mt(): # 绘制耗材使用图
mt = Figure_MT()
mt.plot()
graphicscene_mt = QtGui.QGraphicsScene()
graphicscene_mt.addWidget(mt.canvas)
self.ui.graphicsView_MT.setScene(graphicscene_mt)
self.ui.graphicsView_MT.show()
draw_fp()
draw_loss()
draw_mt()
draw_oee()
class XioFigurePlot(QtGui.QWidget):
'''这个类为绘制类
'''
def __init__(self):
super(XioFigurePlot, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.thread_figure = Timer('updatePlay()', sleep_time=10)
self.connect(self.thread_figure, QtCore.SIGNAL('updatePlay()'), self.draw)
self.thread_figure.start()
def draw(self):
def draw_fp(): # 绘制损失饼图
fp = Figure_Pie()
fp.plot(*(1, 1, 1, 1)) # '*'有一个解包的功能，将（1，1，1，1）解包为 1 1 1 1
graphicscene_fp = QtGui.QGraphicsScene()
graphicscene_fp.addWidget(fp.canvas)
self.ui.graphicsView_Pie.setScene(graphicscene_fp)
self.ui.graphicsView_Pie.show()
def draw_oee(): # 绘制oee日推图
pass
def draw_loss(): # 绘制损失直方图
pass
def draw_mt(): # 绘制耗材使用图
pass
draw_fp()
def batch_size_linear_search():
min = 8
max = 600
step_size = 8
optimizer = lambda x: torch.optim.SGD(x, lr=0.1)
experiment_name = "batch_size_linear_search"
t = Timer()
batch_size_times = {}
for i, batch_size in enumerate(range(min, max, step_size)):
t.start()
main(experiment_name, optimizer, epochs=i + 2, batch_size=batch_size)
elapsed_time = t.stop()
batch_size_times[batch_size] = elapsed_time
pickle.dump(batch_size_times, open("batch_size_times.pickle", "wb"))
# Plot
batch_sizes = []
times = []
for k in sorted(batch_size_times):
batch_sizes.append(k)
times.append(batch_size_times[k])
plt.plot(np.array(batch_sizes), np.array(times))
plt.xlabel("Batch Size")
plt.ylabel("Epoch Time")
plt.title("Batch Size vs Epoch Time")
plt.show()
class XioAll(QtGui.QWidget):
'''这个类为主程序类
'''
HOST = 'localhost'
PORT = 8081
TOTAL = 0
isStatic = True
Shumei = None
action = None
pre_action = None
action_video = None # 视频内能识别
pre_action_video = None
def __init__(self):
super(XioAll, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.frame_left = None
self.frame_right = None
self.is_work = True
self.stype = 0
self.one_static_time = 0 # 一次故障静止的时间
self.all_time = 0 # 一天的工作时间
self.q = MyQueue() # 存放帧队列,改为存放状态比较好
self.vision = Vision()
# 控制输入视频地址
self.CamPath = ""
self.isWebCam = False
self.isCamChanged = False
# 数据库操作
self.da = data_access.DataAccess()
# 若日期发生改变，自行插入全零数据
result_loss = self.da.select_(
"select * from loss ORDER BY SJ DESC limit 1")
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
if str(result_loss[0][0]) != current_time:
self.da.operate_(
'insert into loss(SJ,action1,action2,action3,action4,action5,action6)values'
'("%s",%d,%d,%d,%d,%d,%d)' %
(current_time, 10, 10, 10, 10, 0, 0))
else:
pass
result_oee = self.da.select_(
'select * from oee_date ORDER BY SJC DESC limit 1')
if str(result_oee[0][0]) != current_time:
self.da.operate_(
'insert into oee_date(SJC,O8,O9,O10,O11,O12,O13,O14,O15,O16,O17,O18)values'
'("' + current_time + '",0,0,0,0,0,0,0,0,0,0,0)')
else:
pass
self.yolo_Model = Yolo_Model.Yolo_Model()
# self.displayMessage("...加载YOLO模型成功...")
self.thread_figure = Timer('updatePlay()',
sleep_time=120) # 该线程用来每隔2分钟刷新绘图区
self.connect(self.thread_figure, QtCore.SIGNAL('updatePlay()'),
self.draw)
self.thread_figure.start()
# 按钮功能
self.connect(self.ui.fileSelectButton, QtCore.SIGNAL('clicked()'),
self.fileSelect)
self.connect(self.ui.mailSenderButton, QtCore.SIGNAL('clicked()'),
self.mailSend)
self.connect(self.ui.confirmDateButton, QtCore.SIGNAL('clicked()'),
self.displayMonthData)
self.connect(self.ui.WebCamButton, QtCore.SIGNAL('clicked()'),
self.webCamInput)
self.server = ThreadedTCPServer(
(self.HOST, self.PORT),
ThreadedTCPRequestHandler) # 该线程用来一直监听客户端的请求
self.server_thread = threading.Thread(target=self.server.serve_forever)
self.server_thread.start()
self.thread_video_receive = threading.Thread(
target=self.video_receive_local) # 该线程用来读取视频流
self.thread_video_receive.start()
self.thread_time = Timer('updatePlay()') # 该线程用来每隔0.04秒在label上绘图
self.connect(self.thread_time, QtCore.SIGNAL('updatePlay()'),
self.video_play)
self.thread_time.start()
self.thread_recog = Timer('updatePlay()',
sleep_time=1) # 该线程用来每隔一秒分析图像
self.connect(self.thread_recog, QtCore.SIGNAL('updatePlay()'),
self.video_recog)
self.thread_recog.start()
self.thread_data = Timer('updatePlay()',
sleep_time=1800) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_data, QtCore.SIGNAL('updatePlay()'),
self.data_read)
self.thread_data.start()
self.thread_shumei = threading.Thread(target=self.shumeiDeal)
self.thread_shumei.start()
self.thread_control = Timer('updatePlay()',
sleep_time=10) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_control, QtCore.SIGNAL('updatePlay()'),
self.control_judge)
self.thread_control.start()
# 12-25
self.thread_recogtiaoshi = Timer('updatePlay()',
sleep_time=0.3) # 该线程用来每隔0.3秒分析图像
self.connect(self.thread_recogtiaoshi, QtCore.SIGNAL('updatePlay()'),
self.video_recogtiaoshi)
self.thread_recogtiaoshi.start()
self.thread_recogzhuangji = Timer('updatePlay()',
sleep_time=0.3) # 该线程用来每隔0.3秒分析图像
self.connect(self.thread_recogzhuangji, QtCore.SIGNAL('updatePlay()'),
self.video_recogzhuangji)
self.thread_recogzhuangji.start()
self.X_l = 0
self.Y_l = 0
self.type_l = ""
self.flag = 0
self.a = 0
self.tiaoshi_back = False
self.tiaoshi_forward = False
self.X_r = 0
self.Y_r = 0
self.type_r = ""
self.firstFrame = None
self.chaiji_left = False
self.chaiji_right = False
self.cltime = 0
self.crtime = 0
self.totaltime = 0
# 用于面板进行输出
self.work_time = 0
self.tf_time = 0
self.tb_time = 0
self.Ldown = [0] * 10
self.Lup = [0] * 10 # 队列操作
self.Lhandsdown = [0] * 10
self.Lhandsup = [0] * 10
self.isJudgeMachineT = True
# 装机操作
self.mask_right = cv2.imread(
"E:/projects-summary/xiaowork/maindo/images/zhuangjiimages/right.jpg"
)
self.mask_left = cv2.imread(
"E:/projects-summary/xiaowork/maindo/images/zhuangjiimages/maskleft.jpg"
)
self.left_base = cv2.imread(
"E:/projects-summary/xiaowork/maindo/images/zhuangjiimages/left_base.jpg",
0)
self.redLower = np.array([26, 43, 46])
self.redUpper = np.array([34, 255, 255])
self.Lright = [0] * 10
self.Lleft = [0] * 10
self.is_JudgeRL = True
self.isRightStart = False
self.isLeftStart = False
self.zhuangjitime = 0
# 调试操作
self.status_LUP = [0] * 8
self.status_LDOWN = [0] * 8
self.isActionStartUP = False
self.isActionStartDOWN = False
self.x1UP, self.y1UP, self.x2UP, self.y2UP = [0, 0, 0, 0]
self.X1DOWN, self.Y1DOWN, self.X2DOWN, self.Y2DOWN = [0, 0, 0, 0]
# 定时投入文字
self.putTextStart_time = None
self.putTextEnd_time_left = None
self.putTextEnd_time_right = None
self.putTextEnd_time_up = None
self.putTextEnd_time_down = None
def fileSelect(self):
absolute_path = QFileDialog.getOpenFileName(self, '视频选择', '.',
"MP4 files (*.mp4)")
if absolute_path is not "":
self.reFlushDetection()
self.CamPath = absolute_path
self.isWebCam = False
self.isCamChanged = True
else:
self.displayMessage("...未进行选择，视频源路径不变...")
def webCamInput(self):
webCamDict = {"address": "", "status": ""}
webCamBox = WebCamBox("网络摄像头管理", webCamDict)
# 处理主动关闭输入框
if webCamBox.exec_():
return
if webCamDict["status"] == "":
return
ret = False
try:
cap = cv2.VideoCapture(webCamDict["address"])
ret, frame = cap.read()
except Exception as e:
raise e
finally:
if ret is True:
self.CamPath = webCamDict["address"]
self.isWebCam = True
self.isCamChanged = True
self.reFlushDetection()
self.displayMessage("...更换网络摄像头成功...")
else:
if webCamDict["status"] != "WrongPassword":
self.displayMessage("...IP地址错误，请重新输入...")
def reFlushDetection(self):
self.X_l = 0
self.Y_l = 0
self.type_l = ""
self.flag = 0
self.a = 0
self.tiaoshi_back = False
self.tiaoshi_forward = False
self.X_r = 0
self.Y_r = 0
self.type_r = ""
self.firstFrame = None
self.chaiji_left = False
self.chaiji_right = False
self.cltime = 0
self.crtime = 0
self.totaltime = 0
# 用于面板进行输出
self.work_time = 0
self.tf_time = 0
self.tb_time = 0
self.Ldown = [0] * 10
self.Lup = [0] * 10 # 队列操作
self.Lhandsdown = [0] * 10
self.Lhandsup = [0] * 10
self.isJudgeMachineT = True
self.tiaoshitime = 0
self.Lright = [0] * 10
self.Lleft = [0] * 10
self.is_JudgeRL = True
self.isRightStart = False
self.isLeftStart = False
self.zhuangjitime = 0
self.status_LUP = [0] * 10
self.status_LDOWN = [0] * 15
self.isActionStartUP = False
self.isActionStartDOWN = False
# 定时投入文字
self.putTextStart_time = None
self.putTextEnd_time_left = None
self.putTextEnd_time_right = None
self.putTextEnd_time_up = None
self.putTextEnd_time_down = None
self.displayMessage("...初始化检测参数成功...")
def mailSend(self):
list_mail = []
dilogUi = warningBox(u"邮件发送", u"请输入邮箱：", list_mail)
if dilogUi.exec_():
return
if len(list_mail) == 0:
return
if len(list_mail[0]) != 0:
print("准备发送！")
list_oee = self.da.select_oee()
list_loss = self.da.select_loss()
dict_oee = {}
hour = min(time.localtime()[3], 18)
for i in range(8, hour + 1):
dict_oee[str(i) + "点"] = list_oee[i - 8]
sender = '*****@*****.**'
list_mail.append("*****@*****.**")
message = "侧板焊接生产线生产数据\n" \
"\n" \
"今日OEE效能数据如下所示：\n" \
"{}" \
"\n" \
"\n" \
"*注：效率为0时未进行检测。\n" \
"\n" \
"今日设备运行情况分布如下所示：" \
"\n" \
"清理焊嘴：{} \n" \
"装载侧板：{} \n" \
"机器静止：{} \n" \
"机器工作：{} \n".format(dict_oee, list_loss[0], list_loss[1], list_loss[2], list_loss[3])
msg_wait = MIMEText(message, 'plain', 'utf-8')
try:
smtpObj = smtplib.SMTP()
smtpObj.connect("smtp.qq.com", 25)
mail_license = "wuhchbmndrjabgcc"
print("准备登录")
smtpObj.login(sender, mail_license)
print("登录成功！")
smtpObj.set_debuglevel(1)
smtpObj.sendmail(sender, list_mail, msg_wait.as_string())
except Exception as e:
print(e)
def displayMonthData(self):
self.ui.DateTable.clear()
# 获取月份
select_date = self.ui.dateEdit.text()
queryByMonth = "select * from oee_date where date_format(SJC,'%Y-%m')='{}'".format(
select_date)
# 取数据正常
result = self.da.select_(queryByMonth)
row = len(result)
if row == 0:
self.ui.DateTable.setRowCount(1)
self.ui.DateTable.setColumnCount(1)
self.ui.DateTable.setEditTriggers(
QtGui.QTableWidget.NoEditTriggers)
self.ui.DateTable.horizontalHeader().setResizeMode(
QtGui.QHeaderView.Stretch)
newItem = QtGui.QTableWidgetItem(
" 日期 {} 暂无数据".format(
select_date)) # 接受str，无法接收int
textFont = QtGui.QFont("song", 16, QtGui.QFont.Bold)
newItem.setFont(textFont)
self.ui.DateTable.setItem(0, 0, newItem)
else:
# 表格属性
self.ui.DateTable.setRowCount(row)
self.ui.DateTable.setColumnCount(12)
self.ui.DateTable.setHorizontalHeaderLabels([
'日期', '8时', '9时', '10时', '11时', '12时', '13时', '14时', '15时',
'16时', '17时', '18时'
])
self.ui.DateTable.setEditTriggers(
QtGui.QTableWidget.NoEditTriggers)
self.ui.DateTable.horizontalHeader().setResizeMode(
QtGui.QHeaderView.Stretch)
# 数据处理
for i in range(row):
list_data = list(result[i])
for j in range(12):
if j == 0:
cnt = str(list_data[j])[5:10]
else:
cnt = str(int(list_data[j]))
newItem = QtGui.QTableWidgetItem(cnt) # 接受str，无法接收int
textFont = QtGui.QFont("song", 12, QtGui.QFont.Bold)
newItem.setFont(textFont)
self.ui.DateTable.setItem(i, j, newItem)
def control_judge(self):
pass
def video_recogtiaoshi(self):
if self.isWebCam:
return
frame = self.frame_left
frameDown = frame[250:500, 680:970]
# 上方坐标
frameUP = frame[140:400, 540:800]
# 根据队列进行检测
isPersonUP, self.x1UP, self.y1UP, self.x2UP, self.y2UP = self.yolo_Model.detect_person(
frameUP)
if isPersonUP:
self.status_LUP.append(1)
else:
self.status_LUP.append(0)
self.status_LUP.pop(0)
isPersonDOWN, self.X1DOWN, self.Y1DOWN, self.X2DOWN, self.Y2DOWN = self.yolo_Model.detect_person(
frameDown)
if isPersonDOWN:
self.status_LDOWN.append(1)
else:
self.status_LDOWN.append(0)
self.status_LDOWN.pop(0)
if sum(self.status_LUP) > 5 and self.isActionStartUP is False:
self.displayMessage("工人上方开始清理焊嘴")
self.isActionStartUP = True
self.putTextStart_time = time.time()
self.da.insert_action_("qinglihanzuiUP", 0)
if sum(self.status_LUP) < 2 and self.isActionStartUP is True:
self.displayMessage("工人上方结束清理焊嘴")
self.isActionStartUP = False
self.putTextEnd_time_up = time.time()
self.da.insert_action_("qinglihanzuiUP", 1)
self.da.update_loss_("action1", 1)
self.da.update_loss_("action3", random.randint(0, 2))
if sum(self.status_LDOWN) > 5 and self.isActionStartDOWN is False:
self.displayMessage("工人下方开始清理焊嘴")
self.isActionStartDOWN = True
self.putTextStart_time = time.time()
self.da.insert_action_("qinglihanzuiDOWN", 0)
if sum(self.status_LDOWN) == 0 and self.isActionStartDOWN is True:
self.displayMessage("工人下方结束清理焊嘴")
self.isActionStartDOWN = False
self.putTextEnd_time_down = time.time()
self.da.insert_action_("qinglihanzuiDOWN", 1)
self.da.update_loss_("action1", 1)
self.da.update_loss_("action3", random.randint(0, 2))
def video_recogzhuangji(self):
if self.isWebCam:
return
img = self.frame_left
img = cv2.resize(img, (1280, 720))
img_right = cv2.bitwise_and(self.mask_right, img)
hsv_right = cv2.cvtColor(img_right, cv2.COLOR_BGR2HSV)
mask_det = cv2.inRange(hsv_right, self.redLower, self.redUpper)
img_left = cv2.bitwise_and(self.mask_left, img)
hsv_left = cv2.cvtColor(img_left, cv2.COLOR_BGR2HSV)
mask_det1 = cv2.inRange(hsv_left, self.redLower, self.redUpper)
if self.is_JudgeRL is True:
if np.sum(mask_det) < 10000:
self.Lright.append(1)
else:
self.Lright.append(0)
self.Lright.pop(0)
if sum(self.Lright) > 6 and self.isRightStart is False:
self.displayMessage("工人开始右方装载侧板")
self.isRightStart = True
self.putTextStart_time = time.time()
self.da.insert_action_("zhuangjiRIGHT", 0)
if sum(self.Lright) < 2 and self.isRightStart is True:
self.displayMessage("工人结束右方装载侧板")
self.isRightStart = False
self.putTextEnd_time_right = time.time()
self.da.insert_action_("zhuangjiRIGHT", 1)
self.da.update_loss_("action2", 1)
if np.sum(mask_det1) < 50000:
self.Lleft.append(1)
else:
self.Lleft.append(0)
self.Lleft.pop(0)
if sum(self.Lleft) > 6 and self.isLeftStart is False:
self.displayMessage("工人开始左方装载侧板")
self.isLeftStart = True
self.putTextStart_time = time.time()
self.da.insert_action_("zhuangjiLEFT", 0)
if sum(self.Lleft) < 2 and self.isLeftStart is True:
self.displayMessage("工人结束左方装载侧板")
self.isLeftStart = False
self.putTextEnd_time_left = time.time()
self.da.insert_action_("zhuangjiLEFT", 1)
self.da.update_loss_("action2", 1)
def shumeiDeal(self):
global Stype
while True:
if Stype == 1 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 1
if Stype == 2 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "5s保养"
self.displayMessage(message)
self.stype = 2
if Stype == 3 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + ""
self.displayMessage(message)
self.stype = 3
if Stype == 4 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 4
if Stype == 5 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 5
if Stype == 6 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 6
if Stype == 0:
if self.stype == 1:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 2:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束5s！"
self.stype = 0
self.displayMessage(message)
if self.stype == 3:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 4:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 5:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 6:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.stype = 0
self.displayMessage(message)
time.sleep(0.06)
def video_receive_local(
self,
cam1='E:/projects-summary/xiaowork/侧板焊接待检测视频/检测视频200519134451.mp4',
cam2='E:\\剪辑\\zhuangji\\ch11_20171221084313 00_09_06-00_10_21~2.mp4',
time_flag=True):
'''该方法用来接收本地视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:param time_flag: 是否休眠，本地视频为True
:return: None
'''
self.left_cam = cv2.VideoCapture(cam1)
ret_1, frame_1 = self.left_cam.read()
# 无法重复播放
# preCamPath = cam1
# while True:
#
# self.frame_left = frame_1
# if ret_1 is False:
# self.left_cam = cv2.VideoCapture(cam1)
# if self.CamPath != "" and self.CamPath != preCamPath:
# self.left_cam = cv2.VideoCapture(self.CamPath)
# preCamPath = self.CamPath
# ret_1, frame_1 = self.left_cam.read()
# if time_flag is True:
# time.sleep(0.04)
# 优化版本
while True:
self.frame_left = frame_1
if ret_1 is False:
self.left_cam = cv2.VideoCapture(cam1)
if self.CamPath != "" and self.isCamChanged:
self.left_cam = cv2.VideoCapture(self.CamPath)
self.isCamChanged = False
ret_1, frame_1 = self.left_cam.read()
if time_flag is True:
time.sleep(0.04)
def video_receive_rstp(self, cam1='rstp:', cam2='rstp:'):
'''该方法用来接收网络视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:return: None
'''
self.video_receive_local(cam1=cam1, cam2=cam2, time_flag=False)
def video_play(self):
'''该方法用来播放视频
:return: None
'''
def label_show_left(frame, label=self.ui.label): # 左控件label播放
height, width, _ = frame.shape
frame_change = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# if self.type_l == 'work':
# cv2.rectangle(frame_change, (self.X_l, self.Y_l), (self.X_l + 100, self.Y_l + 100), (0, 255, 0), 4)
frame_change = putChineseText.cv2ImgAddText(
frame_change, "生产操作行为的自动识别（侧板焊接车间）", 50, 30, (0, 0, 0), 50)
if self.isActionStartUP is True:
cv2.rectangle(frame_change, (540 + int(self.x1UP * 0.625),
140 + int(self.y1UP * 0.625)),
(540 + int(self.x2UP * 0.625),
140 + int(self.y2UP * 0.625)), (255, 0, 0), 6)
if time.time() - self.putTextStart_time > 0 and time.time(
) - self.putTextStart_time < 5:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人开始在上方清理焊嘴", 140, 60)
if self.isActionStartDOWN is True:
cv2.rectangle(frame_change, (int(self.X1DOWN * 0.721) + 680,
int(self.Y1DOWN * 0.721) + 250),
(int(self.X2DOWN * 0.721) + 680,
int(self.Y2DOWN * 0.721) + 250), (255, 0, 0), 6)
if time.time() - self.putTextStart_time > 0 and time.time(
) - self.putTextStart_time < 5:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人开始在下方清理焊嘴", 140, 60)
if self.isLeftStart is True:
if time.time() - self.putTextStart_time > 0 and time.time(
) - self.putTextStart_time < 5:
cv2.rectangle(frame_change, (0, 150), (300, 720),
(255, 255, 0), 6)
cv2.circle(frame_change, (150, 435), 6, (255, 0, 0), 20)
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人开始在左方装载侧板", 140, 60)
if self.isRightStart is True:
if time.time() - self.putTextStart_time > 0 and time.time(
) - self.putTextStart_time < 5:
cv2.rectangle(frame_change, (880, 100), (1080, 380),
(255, 255, 0), 6)
cv2.circle(frame_change, (980, 240), 6, (255, 0, 0), 20)
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人开始在右方装载侧板", 140, 60)
# 投入结束文字
if self.isLeftStart is False:
if self.putTextEnd_time_left is not None and time.time(
) - self.putTextEnd_time_left > 0 and time.time(
) - self.putTextEnd_time_left < 3:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人结束左方装载侧板", 140, 60)
if self.isRightStart is False:
if self.putTextEnd_time_right is not None and time.time(
) - self.putTextEnd_time_right > 0 and time.time(
) - self.putTextEnd_time_right < 3:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人结束右方装载侧板", 140, 60)
if self.isActionStartDOWN is False:
if self.putTextEnd_time_down is not None and time.time(
) - self.putTextEnd_time_down > 0 and time.time(
) - self.putTextEnd_time_down < 3:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人结束下方清理焊嘴", 140, 60)
if self.isActionStartUP is False:
if self.putTextEnd_time_up is not None and time.time(
) - self.putTextEnd_time_up > 0 and time.time(
) - self.putTextEnd_time_up < 3:
frame_change = putChineseText.cv2ImgAddText(
frame_change, "工人结束上方清理焊嘴", 140, 60)
frame_resize = cv2.resize(frame_change, (360, 240),
interpolation=cv2.INTER_AREA)
image = QtGui.QImage(frame_resize.data, frame_resize.shape[1],
frame_resize.shape[0],
QtGui.QImage.Format_RGB888) # 处理成QImage
label.setPixmap(QtGui.QPixmap.fromImage(image))
if self.frame_left is not None:
label_show_left(self.frame_left)
def draw(self):
'''
展示图标
:return:
'''
def draw_fp(): # 绘制损失饼图
fp = Figure_Pie()
loss_data = self.da.select_loss()
sum1 = sum(loss_data)
loss_data /= sum1
fp.plot(*tuple(loss_data))
graphicscene_fp = QtGui.QGraphicsScene()
graphicscene_fp.addWidget(fp.canvas)
self.ui.graphicsView_Pie.setScene(graphicscene_fp)
self.ui.graphicsView_Pie.show()
def draw_oee(): # 绘制oee日推图
self.da.update_oee()
oee = Figure_OEE()
l_eff = self.da.select_oee()
oee.plot(*tuple(l_eff)) # 参数
graphicscene_oee = QtGui.QGraphicsScene()
graphicscene_oee.addWidget(oee.canvas)
self.ui.graphicsView_OEE.setScene(graphicscene_oee)
self.ui.graphicsView_OEE.show()
def draw_loss(): # 绘制损失直方图
loss = Figure_Loss()
loss_data = self.da.select_loss()
loss.plot(*tuple(loss_data))
graphicscene_loss = QtGui.QGraphicsScene()
graphicscene_loss.addWidget(loss.canvas)
self.ui.graphicsView_Loss.setScene(graphicscene_loss)
self.ui.graphicsView_Loss.show()
# def draw_mt(): # 绘制耗材使用图
# mt = Figure_MT()
# mt.plot(*(4, 5, 3))
# graphicscene_mt = QtGui.QGraphicsScene()
# graphicscene_mt.addWidget(mt.canvas)
# self.ui.graphicsView_MT.setScene(graphicscene_mt)
# self.ui.graphicsView_MT.show()
draw_fp()
draw_loss()
# draw_mt()
draw_oee()
def video_recog(self):
'''
视频识别部分
:return:
'''
if self.isWebCam:
return
self.totaltime += 1
frame_left = self.frame_left # 原始彩色图，左边摄像头
frame_left_gray = cv2.cvtColor(frame_left,
cv2.COLOR_BGR2GRAY) # 原始图的灰度图
def video_recog_left():
img = frame_left
spark, x, y = self.vision.find_spark(img)
self.q.enqueue(spark)
# print(spark)
if spark and x != 1070:
self.type_l = 'work'
self.X_l = x
self.Y_l = y
else:
self.type_l = ''
if spark or True in self.q.queue: # 如果一段间隔时间内不断有火花（和机器移动，稍后完成），则说明机器必定处于工作状态
self.one_static_time = 0 # 恢复到运动后，一次静止时间重新清零
self.work_time += 1
self.is_work = True
if self.work_time % 20 == 0:
if x != 1070:
self.displayMessage("机器正在工作")
if self.work_time % 60 == 0:
self.da.update_loss_("action4", 1)
else:
# ******* 截图
self.is_work = False
self.one_static_time += 1 # 一次静止时间
if self.one_static_time % 20 == 0:
self.da.update_loss_("action3", 1)
# ********
self.action = ThreadedTCPRequestHandler.action # 键盘操作
if self.action is not None: # 往面板上写当前由于什么原因导致机器静止
if self.pre_action is None:
pass
if self.action_video is not None:
if self.pre_action_video is None:
pass
video_recog_left()
self.pre_action = self.action
self.pre_action_video = self.action_video
def data_read(self):
pass
def displayMessage(self, message):
self.ui.textBrowser.append(
'[' +
time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())) +
'] ' + message)
def main(experiment_name,
optimizer,
output_directory_root="experiments/resnet18_logistic_cifar10",
epochs=60,
batch_size=512,
num_workers=1):
output_directory = os.path.join(output_directory_root, experiment_name)
if not os.path.isdir(output_directory):
os.makedirs(output_directory, exist_ok=True)
# Setup regular log file + tensorboard
logfile_path = os.path.join(output_directory, "logfile.txt")
setup_logger_tqdm(logfile_path)
tensorboard_log_directory = os.path.join("runs",
"resnet18_logistic_cifar10",
experiment_name)
tensorboard_summary_writer = SummaryWriter(
log_dir=tensorboard_log_directory)
# Choose Training Device
use_cuda = torch.cuda.is_available()
logger.info(f"CUDA Available? {use_cuda}")
device = "cuda" if use_cuda else "cpu"
# Datasets and Loaders
train_set_loader, test_set_loader = get_data_loaders(
batch_size, num_workers)
# Create Model & Optimizer
model = torchvision.models.resnet18(pretrained=True)
for param in model.parameters():
param.requires_grad = False
num_classes = 10
model.fc = nn.Linear(model.fc.in_features, 10)
model.to(device)
optimizer = optimizer(model.parameters())
logger.info("=========== Commencing Training ===========")
logger.info(f"Epoch Count: {epochs}")
logger.info(f"Batch Size: {batch_size}")
# Load Checkpoint
checkpoint_file_path = os.path.join(output_directory, "checkpoint.pth")
start_epoch = 0
if os.path.exists(checkpoint_file_path):
logger.info("Checkpoint Found - Loading!")
checkpoint = torch.load(checkpoint_file_path)
logger.info(f"Last completed epoch: {checkpoint['epoch']}")
logger.info(f"Average Train Loss: {checkpoint['train_loss']}")
logger.info(f"Top-1 Train Accuracy: {checkpoint['train_accuracy']}")
logger.info(f"Top-1 Test Accuracy: {checkpoint['test_accuracy']}")
start_epoch = checkpoint["epoch"] + 1
logger.info(f"Resuming at epoch {start_epoch}")
model.load_state_dict(checkpoint["model_state_dict"])
optimizer.load_state_dict(checkpoint["optimizer_state_dict"])
else:
logger.info("No checkpoint found, starting from scratch.")
# Training Loop
t = Timer()
for epoch in range(start_epoch, epochs):
t.start()
logger.info("-" * 10)
logger.info(f"Epoch {epoch}")
logger.info("-" * 10)
train_loss, train_accuracy = train_model(device, model,
train_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("train_loss", train_loss, epoch)
tensorboard_summary_writer.add_scalar("train_accuracy", train_accuracy,
epoch)
test_accuracy = test_model(device, model, test_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("test_accuracy", test_accuracy,
epoch)
# Save Checkpoint
logger.info("Saving checkpoint.")
torch.save(
{
'epoch': epoch,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'train_loss': train_loss,
'train_accuracy': train_accuracy,
'test_accuracy': test_accuracy
}, checkpoint_file_path)
elapsed_time = t.stop()
logger.info(f"End of epoch {epoch}, took {elapsed_time:0.4f} seconds.")
logger.info(f"Average Train Loss: {train_loss}")
logger.info(f"Top-1 Train Accuracy: {train_accuracy}")
logger.info(f"Top-1 Test Accuracy: {test_accuracy}")
logger.info("")
class XioPlayVideo(QtGui.QWidget):
'''这个类为主程序类
'''
def __init__(self):
super(XioPlayVideo, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.left_cam = cv2.VideoCapture('./videos/left_cam.mp4') # 左摄像头
self.right_cam = cv2.VideoCapture('./videos/right_cam.mp4')
self.frame_left = None
self.frame_right = None
self.thread_video_receive = threading.Thread(
target=self.video_receive_local) # 该线程用来读取视频流
self.thread_video_receive.start()
self.thread_time = Timer('updatePlay()') # 该线程用来每隔0.04秒在label上绘图
self.connect(self.thread_time, QtCore.SIGNAL('updatePlay()'),
self.video_play)
self.thread_time.start()
self.thread_recog = Timer('updatePlay()',
sleep_time=1) # 该线程用来每隔一秒分析图像
self.connect(self.thread_recog, QtCore.SIGNAL('updatePlay()'),
self.video_recog)
self.thread_recog.start()
self.thread_data = Timer('updatePlay()',
sleep_time=1800) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_data, QtCore.SIGNAL('updatePlay()'),
self.data_read)
self.thread_data.start()
self.thread_tcp = None # 该线程用来完成tcp，未写完
def video_receive_local(self,
cam1='./videos/left_cam.mp4',
cam2='./videos/right_cam.mp4',
time_flag=True):
'''该方法用来接收本地视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:param time_flag: 是否休眠，本地视频为True
:return: None
'''
if self.left_cam.isOpened() is False:
self.left_cam = cv2.VideoCapture(cam1)
if self.right_cam.isOpened() is False:
self.right_cam = cv2.VideoCapture(cam2)
ret_1, frame_1 = self.left_cam.read()
ret_2, frame_2 = self.right_cam.read()
while True:
self.frame_left = frame_1
self.frame_right = frame_2
if ret_1 is False:
self.left_cam = cv2.VideoCapture(cam1)
if ret_2 is False:
self.right_cam = cv2.VideoCapture(cam2)
ret_1, frame_1 = self.left_cam.read()
ret_1, frame_2 = self.right_cam.read()
if time_flag is True:
time.sleep(0.04)
def video_receive_rstp(self, cam1='rstp:', cam2='rstp:'):
'''该方法用来接收网络视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:return: None
'''
self.video_receive_local(cam1=cam1, cam2=cam2, time_flag=False)
def video_play(self):
'''该方法用来播放视频
:return: None
'''
def label_show_left(frame, label=self.ui.label): # 左控件label播放
height, width, _ = frame.shape
frame_change = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frame_resize = cv2.resize(frame_change, (500, 300),
interpolation=cv2.INTER_AREA)
image = QtGui.QImage(frame_resize.data, frame_resize.shape[1],
frame_resize.shape[0],
QtGui.QImage.Format_RGB888) # 处理成QImage
label.setPixmap(QtGui.QPixmap.fromImage(image))
def label_show_right(frame, label=self.ui.label_2): # 右空间Lable播放
label_show_left(frame, label)
if self.frame_left is not None:
label_show_left(self.frame_left)
if self.frame_right is not None:
label_show_right(self.frame_right)
def video_recog(self):
pass
def data_read(self):
pass
class XioAll(QtGui.QWidget):
'''这个类为主程序类
'''
HOST = 'localhost'
PORT = 8081
TOTAL = 0
isStatic = True
action = None
pre_action = None
action_video = None # 视频内能识别
pre_action_video = None
def __init__(self):
super(XioAll, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.frame_left = None
self.frame_right = None
self.is_work = True
self.one_static_time = 0 # 一次故障静止的时间
self.all_time = 0 # 一天的工作时间
self.q = MyQueue() # 存放帧队列,改为存放状态比较好
self.vision = Vision()
# 若日期发生改变，自行插入全零数据
da = data_access.EquipmentTimeData() # 对损失项统计表进行操作
result_loss = da.select_("select * from loss ORDER BY SJ DESC limit 1")
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
if str(result_loss[0][0]) != current_time:
da.update('insert into loss(SJ,action1,action2,action3,action4,action5,action6)values'
'("%s",%d,%d,%d,%d,%d,%d)' % (current_time, 0, 0, 0, 0, 0, 0))
else:
pass
da_oee = data_access.OEEData() # 对oee实时利用率进行统计
result_oee = da_oee.select_('select * from oee_date ORDER BY SJC DESC limit 1')
if str(result_oee[0][0]) != current_time:
da_oee.update_('insert into oee_date(SJC,O8,O9,O10,O11,O12,O13,O14,O15,O16,O17,O18)values'
'("' + current_time + '",0,0,0,0,0,0,0,0,0,0,0)')
else:
pass
self.thread_figure = Timer('updatePlay()', sleep_time=120) # 该线程用来每隔2分钟刷新绘图区
self.connect(self.thread_figure, QtCore.SIGNAL('updatePlay()'), self.draw)
self.thread_figure.start()
self.server = ThreadedTCPServer((self.HOST, self.PORT), ThreadedTCPRequestHandler) # 该线程用来一直监听客户端的请求
self.server_thread = threading.Thread(target=self.server.serve_forever)
self.server_thread.start()
self.thread_video_receive = threading.Thread(target=self.video_receive_local) # 该线程用来读取视频流
self.thread_video_receive.start()
self.thread_time = Timer('updatePlay()') # 该线程用来每隔0.04秒在label上绘图
self.connect(self.thread_time, QtCore.SIGNAL('updatePlay()'), self.video_play)
self.thread_time.start()
self.thread_recog = Timer('updatePlay()', sleep_time=1) # 该线程用来每隔一秒分析图像
self.connect(self.thread_recog, QtCore.SIGNAL('updatePlay()'), self.video_recog)
self.thread_recog.start()
self.thread_data = Timer('updatePlay()', sleep_time=1800) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_data, QtCore.SIGNAL('updatePlay()'), self.data_read)
self.thread_data.start()
def video_receive_local(self, cam1='./videos/left_cam.mp4', cam2='./videos/right_cam.mp4', time_flag=True):
'''该方法用来接收本地视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:param time_flag: 是否休眠，本地视频为True
:return: None
'''
self.left_cam = cv2.VideoCapture(cam1)
self.right_cam = cv2.VideoCapture(cam2)
ret_1, frame_1 = self.left_cam.read()
ret_2, frame_2 = self.right_cam.read()
while True:
self.frame_left = frame_1
self.frame_right = frame_2
if ret_1 is False:
self.left_cam = cv2.VideoCapture(cam1)
if ret_2 is False:
self.right_cam = cv2.VideoCapture(cam2)
ret_1, frame_1 = self.left_cam.read()
ret_1, frame_2 = self.right_cam.read()
if time_flag is True:
time.sleep(0.04)
def video_receive_rstp(self, cam1='rstp:', cam2='rstp:'):
'''该方法用来接收网络视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:return: None
'''
self.video_receive_local(cam1=cam1, cam2=cam2, time_flag=False)
def video_play(self):
'''该方法用来播放视频
:return: None
'''
def label_show_left(frame, label=self.ui.label): # 左控件label播放
height, width, _ = frame.shape
frame_change = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frame_resize = cv2.resize(frame_change, (360, 240), interpolation=cv2.INTER_AREA)
image = QtGui.QImage(frame_resize.data, frame_resize.shape[1], frame_resize.shape[0],
QtGui.QImage.Format_RGB888) # 处理成QImage
label.setPixmap(QtGui.QPixmap.fromImage(image))
def label_show_right(frame, label=self.ui.label_2): # 右空间Lable播放
label_show_left(frame, label)
if self.frame_left is not None:
label_show_left(self.frame_left)
if self.frame_right is not None:
label_show_right(self.frame_right)
def draw(self):
'''
展示图标
:return:
'''
def draw_fp(): # 绘制损失饼图
fp = Figure_Pie()
da = data_access.EquipmentData()
result = da.select()
fp.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4])) # '*'有一个解包的功能，将（1，1，1，1）解包为 1 1 1 1
graphicscene_fp = QtGui.QGraphicsScene()
graphicscene_fp.addWidget(fp.canvas)
self.ui.graphicsView_Pie.setScene(graphicscene_fp)
self.ui.graphicsView_Pie.show()
def draw_oee(): # 绘制oee日推图
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
lossTime = data_access.EquipmentTimeData()
result_loss = lossTime.select_("select * from loss ORDER BY SJ DESC limit 1")
zongshijian = time.strftime('%H:%M:%S', time.localtime(time.time()))
huanxing = result_loss[0][1]
dailiao = result_loss[0][2]
shebeiguzhang = result_loss[0][3]
tingzhi = result_loss[0][4]
# qitashijian=result[0][5]
# kongyunzhuan=result[0][6]
fuheshijian = (int(zongshijian.split(':')[0]) - 8) * 3600 + int(zongshijian.split(':')[1]) * 60 + int(
zongshijian.split(':')[2]) - tingzhi
shijijiagong_1 = fuheshijian - huanxing - dailiao - shebeiguzhang
eff = int(shijijiagong_1 / fuheshijian * 100) # 计算效率
print(eff)
hour = time.localtime()[3] # 实时更新
da_oee = data_access.OEEData()
da_oee.update_("update oee_date set O" + str(hour) + "=" + str(eff) + ' where SJC="' + current_time + '"')
L_eff = []
oee = Figure_OEE()
da = data_access.OEEData()
result = da.select()
hour = time.localtime()[3]
if hour < 20:
for i in range(1, hour - 6):
L_eff.append(result[-1][i])
oee.plot(*tuple(L_eff)) # 参数
graphicscene_oee = QtGui.QGraphicsScene()
graphicscene_oee.addWidget(oee.canvas)
self.ui.graphicsView_OEE.setScene(graphicscene_oee)
self.ui.graphicsView_OEE.show()
def draw_loss(): # 绘制损失直方图
loss = Figure_Loss()
da = data_access.EquipmentTimeData()
result = da.select()
loss.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4]))
graphicscene_loss = QtGui.QGraphicsScene()
graphicscene_loss.addWidget(loss.canvas)
self.ui.graphicsView_Loss.setScene(graphicscene_loss)
self.ui.graphicsView_Loss.show()
def draw_mt(): # 绘制耗材使用图
mt = Figure_MT()
mt.plot()
graphicscene_mt = QtGui.QGraphicsScene()
graphicscene_mt.addWidget(mt.canvas)
self.ui.graphicsView_MT.setScene(graphicscene_mt)
self.ui.graphicsView_MT.show()
draw_fp()
draw_loss()
draw_mt()
draw_oee()
def video_recog(self):
'''
视频识别部分
:return:
'''
frame_left = self.frame_left # 原始彩色图，左边摄像头
frame_left_gray = cv2.cvtColor(frame_left, cv2.COLOR_BGR2GRAY) # 原始图的灰度图
# frame_right = self.frame_left # 原始彩色图
# frame_right_gray = cv2.cvtColor(frame_right, cv2.COLOR_BGR2GRAY)
def video_recog_left():
img = frame_left
spark = self.vision.find_spark(img)
self.q.enqueue(spark)
# print(spark)
if spark or True in self.q.queue: # 如果一段间隔时间内不断有火花（和机器移动，稍后完成），则说明机器必定处于工作状态
#print('work')
self.action_video = None
self.one_static_time = 0 # 恢复到运动后，一次静止时间重新清零
else:
# ******* 截图
self.one_static_time += 1 # 一次静止时间
if self.one_static_time % 60 == 0:
print('start or static')
print('静止了，往catch文件夹中查看原因')
t = time.localtime()
hour = t[3]
mini = t[4]
seco = t[5]
filename = str(hour) + '-' + str(mini) + '-' + str(seco)
cv2.imwrite('./catch/' + filename + '.jpg', img)
# ********
self.action = ThreadedTCPRequestHandler.action # 键盘操作
if self.action is not None: # 往面板上写当前由于什么原因导致机器静止
if self.pre_action is None:
print(self.action)
message = '[' + time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime(time.time())) + ']' + str(self.action)
self.displayMessage(message)
if self.vision.tiaoshi(frame_left_gray):
self.action_video = 'tiaoshi'
if self.action_video is not None:
if self.pre_action_video is None:
print(self.action_video)
message = '[' + time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime(time.time())) + ']' + str(self.action_video)
self.displayMessage(message)
def video_recog_right(): # 以后用来做换气瓶等的实现
pass
video_recog_left()
video_recog_right()
self.pre_action = self.action
self.pre_action_video = self.action_video
def data_read(self):
pass
def displayMessage(self, message):
self.ui.textBrowser.append(message)
def main(device, mp_args, dataloader_func, model, optimizer_callback,
output_directory, tensorboard_log_directory, epochs):
global_rank = mp_args.nr * mp_args.gpus + device
dist.init_process_group(backend='nccl',
init_method='env://',
world_size=mp_args.world_size,
rank=global_rank)
output_directory = os.path.join(output_directory, f"rank_{global_rank}")
if not os.path.isdir(output_directory):
os.makedirs(output_directory, exist_ok=True)
# Setup regular log file
logfile_path = os.path.join(output_directory, "logfile.txt")
setup_logger_tqdm(logfile_path)
# Setup TensorBoard logging
tensorboard_log_directory = os.path.join(tensorboard_log_directory,
f"rank_{global_rank}")
tensorboard_summary_writer = SummaryWriter(
log_dir=tensorboard_log_directory)
# Dataloaders
train_set_loader, test_set_loader = dataloader_func(
mp_args.world_size, global_rank)
# Model & Optimizer
model.to(device)
optimizer = optimizer_callback(model)
model = nn.parallel.DistributedDataParallel(model, device_ids=[device])
logger.info(f"Epoch Count: {epochs}")
# Load Checkpoint
checkpoint_file_path = os.path.join(output_directory, "checkpoint.pth")
start_epoch = 0
if os.path.exists(checkpoint_file_path):
logger.info("Checkpoint Found - Loading!")
checkpoint = torch.load(checkpoint_file_path)
logger.info(f"Last completed epoch: {checkpoint['epoch']}")
logger.info(f"Average Train Loss: {checkpoint['train_loss']}")
logger.info(f"Top-1 Train Accuracy: {checkpoint['train_accuracy']}")
logger.info(f"Top-1 Test Accuracy: {checkpoint['test_accuracy']}")
start_epoch = checkpoint["epoch"] + 1
logger.info(f"Resuming at epoch {start_epoch}")
model.load_state_dict(checkpoint["model_state_dict"])
optimizer.load_state_dict(checkpoint["optimizer_state_dict"])
else:
logger.info("No checkpoint found, starting from scratch.")
# Training Loop
t = Timer()
#progress = tqdm(total=epochs, initial=start_epoch, desc="Epochs")
for epoch in range(start_epoch, epochs):
t.start()
logger.info(f"Commence EPOCH {epoch}")
# Train
train_loss, train_accuracy = train_model(device, model,
train_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("train_loss", train_loss, epoch)
tensorboard_summary_writer.add_scalar("train_accuracy", train_accuracy,
epoch)
# Test
test_accuracy = test_model(device, model, test_set_loader)
tensorboard_summary_writer.add_scalar("test_accuracy", test_accuracy,
epoch)
# Save Checkpoint
logger.info("Saving checkpoint.")
torch.save(
{
'epoch': epoch,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'train_loss': train_loss,
'train_accuracy': train_accuracy,
'test_accuracy': test_accuracy
}, checkpoint_file_path)
elapsed_time = t.stop()
logger.info(f"End of epoch {epoch}, took {elapsed_time:0.4f} seconds.")
logger.info(f"Average Train Loss: {train_loss}")
logger.info(f"Top-1 Train Accuracy: {train_accuracy}")
logger.info(f"Top-1 Test Accuracy: {test_accuracy}")
def main(dataloader_func,
model,
optimizer_callback,
output_directory,
tensorboard_log_directory,
lr_scheduler=None,
epochs=150):
if not os.path.isdir(output_directory):
os.makedirs(output_directory, exist_ok=True)
# Setup regular log file
logfile_path = os.path.join(output_directory, "logfile.txt")
setup_logger_tqdm(logfile_path)
# Setup TensorBoard logging
tensorboard_summary_writer = SummaryWriter(
log_dir=tensorboard_log_directory)
# Choose Training Device
use_cuda = torch.cuda.is_available()
logger.info(f"CUDA Available? {use_cuda}")
device = "cuda" if use_cuda else "cpu"
# Dataloaders
train_set_loader, test_set_loader = dataloader_func()
# Model & Optimizer
model.to(device)
optimizer = optimizer_callback(model)
if lr_scheduler:
lr_scheduler = lr_scheduler(optimizer)
logger.info(f"Epoch Count: {epochs}")
# Load Checkpoint
checkpoint_file_path = os.path.join(output_directory, "checkpoint.pth")
start_epoch = 0
if os.path.exists(checkpoint_file_path):
logger.info("Checkpoint Found - Loading!")
checkpoint = torch.load(checkpoint_file_path)
logger.info(f"Last completed epoch: {checkpoint['epoch']}")
logger.info(f"Average Train Loss: {checkpoint['train_loss']}")
logger.info(f"Top-1 Train Accuracy: {checkpoint['train_accuracy']}")
logger.info(f"Top-1 Test Accuracy: {checkpoint['test_accuracy']}")
start_epoch = checkpoint["epoch"] + 1
logger.info(f"Resuming at epoch {start_epoch}")
model.load_state_dict(checkpoint["model_state_dict"])
optimizer.load_state_dict(checkpoint["optimizer_state_dict"])
if lr_scheduler:
lr_scheduler.load_state_dict(checkpoint["lr_scheduler_state_dict"])
else:
logger.info("No checkpoint found, starting from scratch.")
# Training Loop
t = Timer()
for epoch in range(start_epoch, epochs):
t.start()
logger.info(f"Commence EPOCH {epoch}")
# Train
train_loss, train_accuracy = train_model(device, model,
train_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("train_loss", train_loss, epoch)
tensorboard_summary_writer.add_scalar("train_accuracy", train_accuracy,
epoch)
# Test
test_accuracy = test_model(device, model, test_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("test_accuracy", test_accuracy,
epoch)
scheduler_dict = None
if lr_scheduler:
lr_scheduler.step()
scheduler_dict = lr_scheduler.state_dict()
# Save Checkpoint
logger.info("Saving checkpoint.")
torch.save(
{
'epoch': epoch,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'lr_scheduler_state_dict': scheduler_dict,
'train_loss': train_loss,
'train_accuracy': train_accuracy,
'test_accuracy': test_accuracy
}, checkpoint_file_path)
elapsed_time = t.stop()
logger.info(f"End of epoch {epoch}, took {elapsed_time:0.4f} seconds.")
logger.info(f"Average Train Loss: {train_loss}")
logger.info(f"Top-1 Train Accuracy: {train_accuracy}")
logger.info(f"Top-1 Test Accuracy: {test_accuracy}")
def train_one_epoch(self, model, dataloader, optimizer, scheduler, num_epochs, max_grad_norm=None,
debugging=False):
"""Train the model for one epoch."""
model.train()
timer = Timer()
print(
("{:25}" + "|" + "{:^15}" * (3 + len(self.early_stopping_metrics)) + "|").format(
"", "l1_loss", "l2_loss", "l3_loss", *self.early_stopping_metrics)
)
total = 10 if debugging else len(dataloader)
with tqdm(dataloader, total=total) as t:
if num_epochs is not None:
description = f"Training ({self.epoch}/{num_epochs})"
else:
description = "Training"
t.set_description(description)
for i, data in enumerate(t):
timer.start()
data = to_device(data, self.device)
optimizer.zero_grad()
# Forward
output = model(**data)
losses = output["losses"]
# Calculate batch metrics
metric = compute_metrics_from_inputs_and_outputs(
inputs=data, outputs=output, tokenizer=self.tokenizer, save_csv_path=None)
losses.update(metric)
# Update tqdm with training information
to_tqdm = [] # update tqdm
for loss_type in ["l1_cls_loss", "l2_cls_loss", "l3_cls_loss", *self.early_stopping_metrics]:
loss_n = losses[loss_type]
if isinstance(loss_n, torch.Tensor) and torch.isnan(loss_n):
to_tqdm.append("nan")
else:
to_tqdm.append(f"{loss_n.item():.3f}")
des = (
"{:25}" + "|" + "{:^15}" * (3 + len(self.early_stopping_metrics)) + "|"
).format(description, *to_tqdm)
t.set_description(des)
# Backward
losses["total_loss"].backward()
if max_grad_norm is not None:
torch.nn.utils.clip_grad_norm_(self.model.parameters(), max_grad_norm)
optimizer.step()
if scheduler is not None:
scheduler.step()
timer.end()
# Break when reaching 10 iterations when debugging
if debugging and i == 9:
break
logger.info(f"{description} took {timer.get_total_time():.2f}s.")
return
def main(carrier_path,
marking_network,
target_network,
target_checkpoint,
batch_size=256,
num_workers=1,
align=True,
test_set_loader=None):
# Setup Device
use_cuda = torch.cuda.is_available()
logger.info(f"CUDA Available? {use_cuda}")
device = torch.device("cuda" if use_cuda else "cpu")
# Load Carrier
carrier = torch.load(carrier_path).numpy()
t = Timer()
t.start()
# Align spaces (Or Not)
W = target_checkpoint["model_state_dict"]["fc.weight"].cpu().numpy()
if align:
logger.info(
"Aligning marking and target network feature space with least squares"
)
marking_network.to(device)
marking_network.eval()
target_network.to(device)
target_network.eval()
# Setup Dataloader
if not test_set_loader:
test_set_loader = get_data_loader(batch_size, num_workers)
logger.info(
"Extracting image features from marking and target networks.")
features_marking, _ = extract_features(test_set_loader,
marking_network,
device,
verbose=False)
features_target, _ = extract_features(test_set_loader,
target_network,
device,
verbose=False)
features_marking = features_marking.numpy()
features_target = features_target.numpy()
X, residuals, rank, s = np.linalg.lstsq(features_marking,
features_target)
logger.info(
"Norm of residual: %.4e" %
np.linalg.norm(np.dot(features_marking, X) - features_target)**2)
W = np.matmul(W, X.T)
# Computing scores
W /= np.linalg.norm(W, axis=1, keepdims=True)
scores = np.sum(W * carrier, axis=1)
#print(f"SCORES: {scores}")
logger.info("Mean p-value is at %d times sigma" %
int(scores.mean() * np.sqrt(W.shape[0] * carrier.shape[1])))
logger.info("Epoch of the model: %d" % target_checkpoint["epoch"])
p_vals = [cosine_pvalue(c, d=carrier.shape[1]) for c in list(scores)]
#print(f"Cosine P values: {p_vals}")
#print(f"np.sum(np.log(p_vals)): {np.sum(np.log(p_vals))}")
#logger.info(p_vals)
combined_pval = combine_pvalues(p_vals)[1]
logger.info(f"log10(p)={np.log10(combined_pval)}")
elapsed_time = t.stop()
logger.info("Total took %.2f" % (elapsed_time))
return (scores, p_vals, combined_pval)
def train_one_epoch(self,
model,
dataloader,
optimizer,
scheduler,
num_epochs,
max_grad_norm=None,
debugging=False):
"""Train the model for one epoch."""
model.train()
timer = Timer()
print(("{:25}" + "|" + "{:^45}" + "|" + "{:^45}" + "|" + "{:^45}" +
"|").format("", "food", "service", "price"))
print(("{:25}" + "|" + "{:^15}" * 3 + "|" + "{:^15}" * 3 + "|" +
"{:^15}" * 3 + "|").format("", "mse_loss", "existence_loss",
"acc", "mse_loss", "existence_loss",
"acc", "mse_loss", "existence_loss",
"acc"))
total = 10 if debugging else len(dataloader)
with tqdm(dataloader, total=total) as t:
if num_epochs is not None:
description = f"Training ({self.epoch}/{num_epochs})"
else:
description = "Training"
t.set_description(description)
for i, data in enumerate(t):
timer.start()
data = to_device(data, self.device)
optimizer.zero_grad()
# Forward
output = model(**data, is_training=True)
losses = output["losses"]
# Calculate batch accuracy
acc = compute_metrics_from_inputs_and_outputs(
inputs=data,
outputs=output,
output_acc=True,
confidence_threshold=self.config["evaluation"]
["confidence_threshold"])
losses.update(acc)
# Update tqdm with training information
to_tqdm = [] # update tqdm
for name in ["food", "service", "price"]:
for loss_type in ["score_loss", "existence_loss", "acc"]:
n = f"{name}_{loss_type}"
loss_n = losses[n]
if (not isinstance(
loss_n, torch.Tensor)) or torch.isnan(loss_n):
to_tqdm.append("nan")
else:
to_tqdm.append(f"{loss_n.item():.3f}")
des = ("{:25}" + "|" + "{:^15}" * 3 + "|" + "{:^15}" * 3 +
"|" + "{:^15}" * 3 + "|").format(description, *to_tqdm)
t.set_description(des)
# Backward
losses["total_loss"].backward()
if max_grad_norm is not None:
torch.nn.utils.clip_grad_norm_(self.model.parameters(),
max_grad_norm)
optimizer.step()
if scheduler is not None:
scheduler.step()
timer.end()
# Break when reaching 10 iterations when debugging
if debugging and i == 9:
break
logger.info(f"{description} took {timer.get_total_time():.2f}s.")
return
def main(device,
mp_args,
experiment_name,
optimizer,
output_directory_root="experiments/resnet18_distributed",
lr_scheduler=None,
epochs=150,
batch_size=512,
num_workers=1):
global_rank = mp_args.nr * mp_args.gpus + device
dist.init_process_group(backend='nccl',
init_method='env://',
world_size=mp_args.world_size,
rank=global_rank)
output_directory = os.path.join(output_directory_root, experiment_name,
f"rank_{global_rank}")
if not os.path.isdir(output_directory):
os.makedirs(output_directory, exist_ok=True)
# Setup regular log file + tensorboard
logfile_path = os.path.join(output_directory, "logfile.txt")
setup_logger_tqdm(logfile_path)
tensorboard_log_directory = os.path.join("runs", "resnet18_distributed",
experiment_name,
f"rank_{global_rank}")
tensorboard_summary_writer = SummaryWriter(
log_dir=tensorboard_log_directory)
# Datasets and Loaders
train_set_loader, test_set_loader = get_data_loaders(
mp_args.world_size, global_rank, batch_size, num_workers)
# Create Model & Optimizer (uses Partial Functions)
model = torchvision.models.resnet18(pretrained=False, num_classes=10)
model.to(device)
optimizer = optimizer(model.parameters())
model = nn.parallel.DistributedDataParallel(model, device_ids=[device])
if lr_scheduler:
lr_scheduler = lr_scheduler(optimizer)
logger.info("=========== Commencing Training ===========")
logger.info(f"Epoch Count: {epochs}")
logger.info(f"Batch Size: {batch_size}")
# Load Checkpoint
checkpoint_file_path = os.path.join(output_directory, "checkpoint.pth")
start_epoch = 0
if os.path.exists(checkpoint_file_path):
logger.info("Checkpoint Found - Loading!")
checkpoint = torch.load(checkpoint_file_path)
logger.info(f"Last completed epoch: {checkpoint['epoch']}")
logger.info(f"Average Train Loss: {checkpoint['train_loss']}")
logger.info(f"Top-1 Train Accuracy: {checkpoint['train_accuracy']}")
logger.info(f"Top-1 Test Accuracy: {checkpoint['test_accuracy']}")
start_epoch = checkpoint["epoch"] + 1
logger.info(f"Resuming at epoch {start_epoch}")
model.load_state_dict(checkpoint["model_state_dict"])
optimizer.load_state_dict(checkpoint["optimizer_state_dict"])
if lr_scheduler:
lr_scheduler.load_state_dict(checkpoint["lr_scheduler_state_dict"])
else:
logger.info("No checkpoint found, starting from scratch.")
# Training Loop
t = Timer()
for epoch in range(start_epoch, epochs):
t.start()
logger.info("-" * 10)
logger.info(f"Epoch {epoch}")
logger.info("-" * 10)
train_loss, train_accuracy = train_model(device, model,
train_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("train_loss", train_loss, epoch)
tensorboard_summary_writer.add_scalar("train_accuracy", train_accuracy,
epoch)
test_accuracy = test_model(device, model, test_set_loader, optimizer)
tensorboard_summary_writer.add_scalar("test_accuracy", test_accuracy,
epoch)
scheduler_dict = None
if lr_scheduler:
lr_scheduler.step()
scheduler_dict = lr_scheduler.state_dict()
# Save Checkpoint
logger.info("Saving checkpoint.")
torch.save(
{
'epoch': epoch,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'lr_scheduler_state_dict': scheduler_dict,
'train_loss': train_loss,
'train_accuracy': train_accuracy,
'test_accuracy': test_accuracy
}, checkpoint_file_path)
elapsed_time = t.stop()
logger.info(f"End of epoch {epoch}, took {elapsed_time:0.4f} seconds.")
logger.info(f"Average Train Loss: {train_loss}")
logger.info(f"Top-1 Train Accuracy: {train_accuracy}")
logger.info(f"Top-1 Test Accuracy: {test_accuracy}")
logger.info("")
class XioAll(QtGui.QWidget):
'''这个类为主程序类
'''
HOST = 'localhost'
PORT = 8081
TOTAL = 0
isStatic = True
Shumei = None
action = None
pre_action = None
action_video = None # 视频内能识别
pre_action_video = None
def __init__(self):
super(XioAll, self).__init__()
self.ui = ui.Ui_Form()
self.ui.setupUi(self)
self.frame_left = None
self.frame_right = None
self.is_work = True
self.stype = 0
self.one_static_time = 0 # 一次故障静止的时间
self.all_time = 0 # 一天的工作时间
self.q = MyQueue() # 存放帧队列,改为存放状态比较好
self.vision = Vision()
self.CamPath = ""
# 若日期发生改变，自行插入全零数据
da = data_access.EquipmentTimeData() # 对损失项统计表进行操作
result_loss = da.select_("select * from loss ORDER BY SJ DESC limit 1")
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
if str(result_loss[0][0]) != current_time:
da.update(
'insert into loss(SJ,action1,action2,action3,action4,action5,action6)values'
'("%s",%d,%d,%d,%d,%d,%d)' % (current_time, 0, 0, 0, 0, 0, 0))
else:
pass
da_oee = data_access.OEEData() # 对oee实时利用率进行统计
result_oee = da_oee.select_(
'select * from oee_date ORDER BY SJC DESC limit 1')
if str(result_oee[0][0]) != current_time:
da_oee.update_(
'insert into oee_date(SJC,O8,O9,O10,O11,O12,O13,O14,O15,O16,O17,O18)values'
'("' + current_time + '",0,0,0,0,0,0,0,0,0,0,0)')
else:
pass
self.thread_figure = Timer('updatePlay()',
sleep_time=120) # 该线程用来每隔2分钟刷新绘图区
self.connect(self.thread_figure, QtCore.SIGNAL('updatePlay()'),
self.draw)
self.thread_figure.start()
# 按钮功能
self.connect(self.ui.fileSelectButton, QtCore.SIGNAL('clicked()'),
self.fileSelect)
self.connect(self.ui.mailSenderButton, QtCore.SIGNAL('clicked()'),
self.mailSend)
self.connect(self.ui.confirmDateButton, QtCore.SIGNAL('clicked()'),
self.displayMonthData)
self.connect(self.ui.mailConfirm, QtCore.SIGNAL('clicked()'),
self.confirmMail)
self.server = ThreadedTCPServer(
(self.HOST, self.PORT),
ThreadedTCPRequestHandler) # 该线程用来一直监听客户端的请求
self.server_thread = threading.Thread(target=self.server.serve_forever)
self.server_thread.start()
self.thread_video_receive = threading.Thread(
target=self.video_receive_local) # 该线程用来读取视频流
self.thread_video_receive.start()
self.thread_time = Timer('updatePlay()') # 该线程用来每隔0.04秒在label上绘图
self.connect(self.thread_time, QtCore.SIGNAL('updatePlay()'),
self.video_play)
self.thread_time.start()
self.thread_recog = Timer('updatePlay()',
sleep_time=1) # 该线程用来每隔一秒分析图像
self.connect(self.thread_recog, QtCore.SIGNAL('updatePlay()'),
self.video_recog)
self.thread_recog.start()
self.thread_data = Timer('updatePlay()',
sleep_time=1800) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_data, QtCore.SIGNAL('updatePlay()'),
self.data_read)
self.thread_data.start()
self.thread_shumei = threading.Thread(target=self.shumeiDeal)
self.thread_shumei.start()
self.thread_control = Timer('updatePlay()',
sleep_time=10) # 该线程用来每隔半小时向数据库读取数据
self.connect(self.thread_control, QtCore.SIGNAL('updatePlay()'),
self.control_judge)
self.thread_control.start()
# 12-25
self.thread_recogtiaoshi = Timer('updatePlay()',
sleep_time=0.5) # 该线程用来每隔0.5秒分析图像
self.connect(self.thread_recogtiaoshi, QtCore.SIGNAL('updatePlay()'),
self.video_recogtiaoshi)
self.thread_recogtiaoshi.start()
# self.thread_recogbottle = Timer('updatePlay()', sleep_time=0.5) # 该线程用来每隔0.5秒分析图像
# self.connect(self.thread_recogbottle, QtCore.SIGNAL('updatePlay()'), self.video_recogbottle)
# self.thread_recogbottle.start()
self.thread_recogzhuangji = Timer('updatePlay()',
sleep_time=0.1) # 该线程用来每隔0.5秒分析图像
self.connect(self.thread_recogzhuangji, QtCore.SIGNAL('updatePlay()'),
self.video_recogzhuangji)
self.thread_recogzhuangji.start()
self.X_l = 0
self.Y_l = 0
self.type_l = ""
self.flag = 0
self.a = 0
self.tiaoshi_back = False
self.tiaoshi_forward = False
self.X_r = 0
self.Y_r = 0
self.type_r = ""
self.firstFrame = None
self.chaiji_left = False
self.chaiji_right = False
self.cltime = 0
self.crtime = 0
self.totaltime = 0
# 用于面板进行输出
self.work_time = 0
self.tf_time = 0
self.tb_time = 0
# 调试
self.machinedown_base = cv2.imread(
"images/tiaoshiimages/machinedown_base.jpg")
self.machineup_base = cv2.imread(
"images/tiaoshiimages/machineup_base.jpg")
self.machineup_mask = cv2.imread("images/tiaoshiimages/up1.jpg")
self.machinedown_mask = cv2.imread("images/tiaoshiimages/down1.jpg")
self.peopleup_mask = cv2.imread("images/tiaoshiimages/handsup.jpg", 0)
self.peopledown_mask = cv2.imread("images/tiaoshiimages/handsdown.jpg",
0)
self.peopleup_base = cv2.imread(
"images/tiaoshiimages/handsup_base.jpg", 0)
self.peopledown_base = cv2.imread(
"images/tiaoshiimages/handsdown_base.jpg", 0)
self.Ldown = [0] * 10
self.Lup = [0] * 10 # 队列操作
self.Lhandsdown = [0] * 10
self.Lhandsup = [0] * 10
self.isJudgeMachineT = True
self.tiaoshitime = 0
self.isUpStart = False
self.isDownStart = False
self.machineLocation = ""
self.downStartTime = 0
self.upStartTime = 0
# 换瓶操作
# self.bottle_area = cv2.imread("images/bottleimages/bottle.jpg", 0)
# self.bottle_area = cv2.resize(self.bottle_area, (1280, 720))
# self.nobottle_base = cv2.imread("images/bottleimages/nobottle_base.jpg", 0)
# self.nobottle_base = cv2.resize(self.nobottle_base, (1280, 720))
# self.Lbottle = [0] * 10
# self.isBottleStart = False
# self.isJudgeMachineB = True
self.bottletime = 0
# 装机操作
self.mask_right = cv2.imread("images/zhuangjiimages/right.jpg")
self.mask_left = cv2.imread("images/zhuangjiimages/maskleft.jpg")
self.left_base = cv2.imread("images/zhuangjiimages/left_base.jpg", 0)
self.redLower = np.array([26, 43, 46])
self.redUpper = np.array([34, 255, 255])
self.Lright = [0] * 10
self.Lleft = [0] * 10
self.is_JudgeRL = True
self.isRightStart = False
self.isLeftStart = False
self.zhuangjitime = 0
def fileSelect(self):
absolute_path = QFileDialog.getOpenFileName(self, '视频选择', '.',
"MP4 files (*.mp4)")
if self.CamPath != absolute_path:
self.reFlushDetection()
self.CamPath = absolute_path
else:
self.displayMessage("...未进行选择，视频源路径不变...")
def reFlushDetection(self):
self.X_l = 0
self.Y_l = 0
self.type_l = ""
self.flag = 0
self.a = 0
self.tiaoshi_back = False
self.tiaoshi_forward = False
self.X_r = 0
self.Y_r = 0
self.type_r = ""
self.firstFrame = None
self.chaiji_left = False
self.chaiji_right = False
self.cltime = 0
self.crtime = 0
self.totaltime = 0
# 用于面板进行输出
self.work_time = 0
self.tf_time = 0
self.tb_time = 0
# 调试
self.machinedown_base = cv2.imread(
"images/tiaoshiimages/machinedown_base.jpg")
self.machineup_base = cv2.imread(
"images/tiaoshiimages/machineup_base.jpg")
self.machineup_mask = cv2.imread("images/tiaoshiimages/up1.jpg")
self.machinedown_mask = cv2.imread("images/tiaoshiimages/down1.jpg")
self.peopleup_mask = cv2.imread("images/tiaoshiimages/handsup.jpg", 0)
self.peopledown_mask = cv2.imread("images/tiaoshiimages/handsdown.jpg",
0)
self.peopleup_base = cv2.imread(
"images/tiaoshiimages/handsup_base.jpg", 0)
self.peopledown_base = cv2.imread(
"images/tiaoshiimages/handsdown_base.jpg", 0)
self.Ldown = [0] * 10
self.Lup = [0] * 10 # 队列操作
self.Lhandsdown = [0] * 10
self.Lhandsup = [0] * 10
self.isJudgeMachineT = True
self.tiaoshitime = 0
self.isUpStart = False
self.isDownStart = False
self.machineLocation = ""
self.downStartTime = 0
self.upStartTime = 0
# 换瓶操作
self.bottle_area = cv2.imread("images/bottleimages/bottle.jpg", 0)
self.bottle_area = cv2.resize(self.bottle_area, (1280, 720))
self.nobottle_base = cv2.imread(
"images/bottleimages/nobottle_base.jpg", 0)
self.nobottle_base = cv2.resize(self.nobottle_base, (1280, 720))
self.Lbottle = [0] * 10
self.isBottleStart = False
self.isJudgeMachineB = True
self.bottletime = 0
# 装机操作
self.mask_right = cv2.imread("images/zhuangjiimages/right.jpg")
self.mask_left = cv2.imread("images/zhuangjiimages/maskleft.jpg")
self.left_base = cv2.imread("images/zhuangjiimages/left_base.jpg", 0)
self.redLower = np.array([26, 43, 46])
self.redUpper = np.array([34, 255, 255])
self.Lright = [0] * 10
self.Lleft = [0] * 10
self.is_JudgeRL = True
self.isRightStart = False
self.isLeftStart = False
self.zhuangjitime = 0
self.displayMessage("......初始化参数成功......")
def confirmMail(self):
text = self.ui.mailLineEdit.text()
lines = str(text)
lines = lines.split(';')
for line in lines:
self.ui.mailTextBroswer.append(line)
self.ui.mailTextBroswer.append("......邮箱确认完毕,准备发送......")
def mailSend(self):
import smtplib
sender = '*****@*****.**'
receivers = ['*****@*****.**']
text = self.ui.mailLineEdit.text()
lines = str(text)
lines = lines.split(';')
for line in lines:
receivers.append(line)
message = """From: From Person <*****@*****.**>
To: To Person <*****@*****.**>
Subject: SMTP e-mail test
This is a test e-mail message.
"""
try:
smtpObj = smtplib.SMTP()
smtpObj.connect("smtp.qq.com", 25)
mail_license = "wuhchbmndrjabgcc"
print("准备登录")
smtpObj.login(sender, mail_license)
print("登录成功！")
smtpObj.set_debuglevel(1)
smtpObj.sendmail(sender, receivers, message)
self.ui.mailTextBroswer.append("......发送邮件成功！......")
except Exception as e:
print(e)
self.ui.mailTextBroswer.append("......发送邮件失败！......")
def displayMonthData(self):
self.ui.DateTable.clear()
da = data_access.DataAccess()
# 获取月份
select_date = self.ui.dateEdit.text()
queryByMonth = "select * from oee_date where date_format(SJC,'%Y-%m')='{}'".format(
select_date)
# 取数据正常
result = da.select_(queryByMonth)
row = len(result)
if row == 0:
self.ui.DateTable.setRowCount(1)
self.ui.DateTable.setColumnCount(1)
self.ui.DateTable.setEditTriggers(
QtGui.QTableWidget.NoEditTriggers)
self.ui.DateTable.horizontalHeader().setResizeMode(
QtGui.QHeaderView.Stretch)
newItem = QtGui.QTableWidgetItem(
" 日期 {} 暂无数据".format(
select_date)) # 接受str，无法接收int
textFont = QtGui.QFont("song", 16, QtGui.QFont.Bold)
newItem.setFont(textFont)
self.ui.DateTable.setItem(0, 0, newItem)
else:
# 表格属性
self.ui.DateTable.setRowCount(row)
self.ui.DateTable.setColumnCount(12)
self.ui.DateTable.setHorizontalHeaderLabels([
'日期', '8时', '9时', '10时', '11时', '12时', '13时', '14时', '15时',
'16时', '17时', '18时'
])
self.ui.DateTable.setEditTriggers(
QtGui.QTableWidget.NoEditTriggers)
self.ui.DateTable.horizontalHeader().setResizeMode(
QtGui.QHeaderView.Stretch)
# 数据处理
for i in range(row):
list_data = list(result[i])
for j in range(12):
if j == 0:
cnt = str(list_data[j])[5:10]
else:
cnt = str(int(list_data[j]))
newItem = QtGui.QTableWidgetItem(cnt) # 接受str，无法接收int
textFont = QtGui.QFont("song", 12, QtGui.QFont.Bold)
newItem.setFont(textFont)
self.ui.DateTable.setItem(i, j, newItem)
def control_judge(self):
if (time.time() - self.tiaoshitime) > 120:
self.isJudgeMachineT = True
if (time.time() - self.bottletime) > 120:
self.isJudgeMachineB = True
if (time.time() - self.zhuangjitime) > 120:
self.is_JudgeRL = True
def video_recogtiaoshi(self):
img = self.frame_left
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgupcurrent = cv2.bitwise_and(self.machineup_mask, img)
imgdowncurrent = cv2.bitwise_and(self.machinedown_mask, img)
updiff = sum(cv2.absdiff(imgupcurrent, self.machineup_base)) * 1.46
downdiff = sum(cv2.absdiff(imgdowncurrent, self.machinedown_base))
if self.isJudgeMachineT is True and self.is_work is False:
if updiff > downdiff:
self.Ldown.append(1)
self.Lup.append(0)
else:
self.Lup.append(1)
self.Ldown.append(0)
self.Ldown.pop(0)
self.Lup.pop(0)
if sum(self.Ldown) > 6:
self.isJudgeMachineT = False
self.machineLocation = "down"
if sum(self.Lup) > 6:
self.isJudgeMachineT = False
self.machineLocation = "up"
if self.machineLocation == "down":
peopleDownCurrent = cv2.bitwise_and(img_gray, self.peopledown_mask)
if sum(cv2.absdiff(peopleDownCurrent,
self.peopledown_base)) > 70000:
self.Lhandsdown.append(1)
else:
self.Lhandsdown.append(0)
self.Lhandsdown.pop(0)
if sum(self.Lhandsdown) > 6 and self.isDownStart is False:
message = "[" + datetime.datetime.now().strftime(
'%Y/%m/%d %H:%M:%S') + "]" + "工人正在下方调试"
self.displayMessage(message)
self.isDownStart = True
self.downStartTime = time.time()
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','tiaoshi',0)")
if time.time() - self.downStartTime > 120:
self.isDownStart = False
self.machineLocation = ""
self.tiaoshitime = time.time()
if sum(self.Lhandsdown) < 4 and self.isDownStart is True:
message = "[" + datetime.datetime.now().strftime(
'%Y/%m/%d %H:%M:%S') + "]" + "工人结束下方调试"
self.displayMessage(message)
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','tiaoshi',1)")
self.isDownStart = False
self.machineLocation = ""
if self.machineLocation == "up":
peopleUpCurrent = cv2.bitwise_and(img_gray, self.peopleup_mask)
if sum(cv2.absdiff(peopleUpCurrent, self.peopleup_base)) > 60000:
self.Lhandsup.append(1)
else:
self.Lhandsup.append(0)
self.Lhandsup.pop(0)
print(sum(self.Lhandsup))
if sum(self.Lhandsup) > 6 and self.isUpStart is False:
message = "[" + datetime.datetime.now().strftime(
'%Y/%m/%d %H:%M:%S') + "]" + "工人正在上方调试"
self.displayMessage(message)
self.isUpStart = True
self.upStartTime = time.time()
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','tiaoshi',0)")
if time.time() - self.upStartTime > 120: # 若时间大于120秒，则放弃判断是否拆机
self.machineLocation = ""
self.isUpStart = False
if sum(self.Lhandsup) < 4 and self.isUpStart is True:
message = "[" + datetime.datetime.now().strftime(
'%Y/%m/%d %H:%M:%S') + "]" + "工人结束上方调试"
self.displayMessage(message)
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','tiaoshi',1)")
self.machineLocation = ""
self.isUpStart = False
self.tiaoshitime = time.time()
# def video_recogbottle(self):
# img = self.frame_right
# img = cv2.resize(img, (1280, 720))
# if self.isJudgeMachineB is True:
# img_bottle = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# img_bottle = cv2.bitwise_and(img_bottle, self.bottle_area)
# if np.sum(cv2.absdiff(img_bottle, self.bottle_area)) < 50000:
# self.Lbottle.append(1)
# else:
# self.Lbottle.append(0)
# self.Lbottle.pop(0)
# if self.isBottleStart is False and sum(self.Lbottle) > 5:
# self.isBottleStart = True # 初始为False
# self.displayMessage(datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') + "..........开始换气瓶！")
# current_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
# da = data_access.DataAccess()
# da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" + current_time + "','bottle',0)")
#
# if self.isBottleStart is True and sum(self.Lbottle) < 2:
# self.isBottleStart = False
# self.displayMessage(datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') + "..........换气瓶结束！")
# current_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
# da = data_access.DataAccess()
# da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" + current_time + "','bottle',1)")
def video_recogzhuangji(self):
img = self.frame_left
img = cv2.resize(img, (1280, 720))
img_right = cv2.bitwise_and(self.mask_right, img)
hsv_right = cv2.cvtColor(img_right, cv2.COLOR_BGR2HSV)
mask_det = cv2.inRange(hsv_right, self.redLower, self.redUpper)
img_left = cv2.bitwise_and(self.mask_left, img)
hsv_left = cv2.cvtColor(img_left, cv2.COLOR_BGR2HSV)
mask_det1 = cv2.inRange(hsv_left, self.redLower, self.redUpper)
if self.is_JudgeRL is True:
if np.sum(mask_det) < 10000:
self.Lright.append(1)
else:
self.Lright.append(0)
self.Lright.pop(0)
if sum(self.Lright) > 6 and self.isRightStart is False:
self.displayMessage(
"[" +
datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') +
"]" + "工人正在右方拆机")
self.isRightStart = True
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','chaiji',0)")
if sum(self.Lright) < 2 and self.isRightStart is True:
self.displayMessage(
"[" +
datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') +
"]" + "工人结束右方拆机")
self.isRightStart = False
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','chaiji',1)")
if np.sum(mask_det1) < 50000:
self.Lleft.append(1)
else:
self.Lleft.append(0)
self.Lleft.pop(0)
if sum(self.Lleft) > 6 and self.isLeftStart is False:
self.displayMessage(
"[" +
datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') +
"]" + "工人正在左方拆机")
self.isLeftStart = True
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','chaiji',0)")
if sum(self.Lleft) < 2 and self.isLeftStart is True:
self.displayMessage(
"[" +
datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S') +
"]" + "工人结束左方拆机")
self.isLeftStart = False
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into dzrecord(SJC,ACTION,FLAG)values('" +
current_time + "','chaiji',1)")
def shumeiDeal(self):
global Stype
while True:
if Stype == 1 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 1
if Stype == 2 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "5s保养"
self.displayMessage(message)
self.stype = 2
if Stype == 3 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + ""
self.displayMessage(message)
self.stype = 3
if Stype == 4 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 4
if Stype == 5 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 5
if Stype == 6 and self.stype == 0:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.displayMessage(message)
self.stype = 6
if Stype == 0:
if self.stype == 1:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 2:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束5s！"
self.stype = 0
self.displayMessage(message)
if self.stype == 3:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 4:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人结束吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 5:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.stype = 0
self.displayMessage(message)
if self.stype == 6:
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + "******" + "工人吃饭！"
self.stype = 0
self.displayMessage(message)
time.sleep(0.06)
def video_receive_local(
self,
cam1='E:/projects-summary/xiaowork/maindo/videos/西奥待检测数据/视频合并200512103448.mp4',
cam2='E:\\剪辑\\zhuangji\\ch11_20171221084313 00_09_06-00_10_21~2.mp4',
time_flag=True):
'''该方法用来接收本地视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:param time_flag: 是否休眠，本地视频为True
:return: None
'''
self.left_cam = cv2.VideoCapture(cam1)
ret_1, frame_1 = self.left_cam.read()
preCamPath = cam1
while True:
self.frame_left = frame_1
if ret_1 is False:
self.left_cam = cv2.VideoCapture(cam1)
if self.CamPath != "" and self.CamPath != preCamPath:
self.left_cam = cv2.VideoCapture(self.CamPath)
preCamPath = self.CamPath
ret_1, frame_1 = self.left_cam.read()
if time_flag is True:
time.sleep(0.04)
def video_receive_rstp(self, cam1='rstp:', cam2='rstp:'):
'''该方法用来接收网络视频
:param cam1: 左摄像头数据源
:param cam2: 右摄像头数据源
:return: None
'''
self.video_receive_local(cam1=cam1, cam2=cam2, time_flag=False)
def video_play(self):
'''该方法用来播放视频
:return: None
'''
def label_show_left(frame, label=self.ui.label): # 左控件label播放
height, width, _ = frame.shape
frame_change = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
if self.type_l == 'work':
cv2.rectangle(frame_change, (self.X_l, self.Y_l),
(self.X_l + 100, self.Y_l + 100), (0, 255, 0), 4)
if self.tiaoshi_back is True: # self.pb_loc = (130, 260, 610, 690)self.pf_loc = (250, 420, 800, 900)
cv2.rectangle(frame_change, (610, 130), (690, 260),
(255, 0, 0), 4)
# if self.tiaoshi_forward is True:
# cv2.rectangle(frame_change, (800, 250), (900, 420), (255, 0, 0), 4)
if self.chaiji_left is True:
cv2.rectangle(frame_change, (20, 350), (210, 600),
(255, 255, 0), 4)
if self.chaiji_right is True:
cv2.rectangle(frame_change, (980, 5), (1090, 130),
(255, 255, 0), 4)
frame_resize = cv2.resize(frame_change, (360, 240),
interpolation=cv2.INTER_AREA)
image = QtGui.QImage(frame_resize.data, frame_resize.shape[1],
frame_resize.shape[0],
QtGui.QImage.Format_RGB888) # 处理成QImage
label.setPixmap(QtGui.QPixmap.fromImage(image))
# def label_show_right(frame, label=self.ui.label_2): # 右空间Lable播放
# height, width, _ = frame.shape
# frame_change = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# frame_resize = cv2.resize(frame_change, (360, 240), interpolation=cv2.INTER_AREA)
# image = QtGui.QImage(frame_resize.data, frame_resize.shape[1], frame_resize.shape[0],
# QtGui.QImage.Format_RGB888) # 处理成QImage
# label.setPixmap(QtGui.QPixmap.fromImage(image))
if self.frame_left is not None:
label_show_left(self.frame_left)
def draw(self):
'''
展示图标
:return:
'''
def draw_fp(): # 绘制损失饼图
fp = Figure_Pie()
da = data_access.EquipmentData()
result = da.select()
# fp.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4])) # '*'有一个解包的功能，将（1，1，1，1）解包为 1 1 1 1
fp.plot(*(33, 28, 37, 94))
graphicscene_fp = QtGui.QGraphicsScene()
graphicscene_fp.addWidget(fp.canvas)
self.ui.graphicsView_Pie.setScene(graphicscene_fp)
self.ui.graphicsView_Pie.show()
def draw_oee(): # 绘制oee日推图
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
lossTime = data_access.EquipmentTimeData()
result_loss = lossTime.select_(
"select * from loss ORDER BY SJ DESC limit 1")
zongshijian = time.strftime('%H:%M:%S',
time.localtime(time.time()))
# huanxing = result_loss[0][1]
# dailiao = result_loss[0][2]
# shebeiguzhang = result_loss[0][3]
# tingzhi = result_loss[0][4]
# # qitashijian=result[0][5]
# # kongyunzhuan=result[0][6]
# fuheshijian = (int(zongshijian.split(':')[0]) - 8) * 3600 + int(zongshijian.split(':')[1]) * 60 + int(
# zongshijian.split(':')[2]) - tingzhi
# shijijiagong_1 = fuheshijian - huanxing - dailiao - shebeiguzhang
da = data_access.DataAccess()
resultw = da.select_(
"SELECT * from mstatus where SJC>date(now()) and `status`=1")
if len(resultw) != 0:
start_time = resultw[0][0]
fuheshijian = (datetime.datetime.now() - start_time).seconds
if time.localtime()[3] > 11:
fuheshijian = (datetime.datetime.now() -
start_time).seconds - 60 # 吃饭时间
eff = int(len(resultw) / fuheshijian * 100 * 22) # 计算效率
else:
eff = 0
hour = time.localtime()[3] # 实时更新
da_oee = data_access.OEEData()
# da_oee.update_("update oee_date set O" + str(hour) + "=" + str(eff) + ' where SJC="' + current_time + '"')
L_eff = []
oee = Figure_OEE()
da = data_access.OEEData()
# result = da.select()
hour = time.localtime()[3]
result = [77, 82, 83, 79, 81, 85, 81, 78, 81, 85, 82, 81]
for i in range(1, hour - 6):
L_eff.append(result[i])
oee.plot(*tuple(L_eff)) # 参数
# oee.plot(*tuple([77,82,83,79,81,85,81,78]))
graphicscene_oee = QtGui.QGraphicsScene()
graphicscene_oee.addWidget(oee.canvas)
self.ui.graphicsView_OEE.setScene(graphicscene_oee)
self.ui.graphicsView_OEE.show()
def draw_loss(): # 绘制损失直方图
loss = Figure_Loss()
da = data_access.EquipmentTimeData()
result = da.select()
# loss.plot(*(result[-1][1], result[-1][2], result[-1][3], result[-1][4]))
loss.plot(*(140, 121, 113, 437))
graphicscene_loss = QtGui.QGraphicsScene()
graphicscene_loss.addWidget(loss.canvas)
self.ui.graphicsView_Loss.setScene(graphicscene_loss)
self.ui.graphicsView_Loss.show()
def draw_mt(): # 绘制耗材使用图
mt = Figure_MT()
bottle = 0
current_time = datetime.datetime.now().strftime('%Y-%m-%d')
da_mt = data_access.EquipmentTimeData()
# result_mt = da_mt.select_(
# 'select * from mtrecord where date_format(SJC, "%Y-%m-%d") = "' + current_time + '"')
# for result_m in result_mt:
# if result_m[1] == "bottlechange":
# bottle += 1
mt.plot(*(4, 5, 3))
graphicscene_mt = QtGui.QGraphicsScene()
graphicscene_mt.addWidget(mt.canvas)
self.ui.graphicsView_MT.setScene(graphicscene_mt)
self.ui.graphicsView_MT.show()
draw_fp()
draw_loss()
draw_mt()
draw_oee()
def video_recog(self):
'''
视频识别部分
:return:
'''
self.totaltime += 1
frame_left = self.frame_left # 原始彩色图，左边摄像头
frame_left_gray = cv2.cvtColor(frame_left,
cv2.COLOR_BGR2GRAY) # 原始图的灰度图
# frame_right = self.frame_right
# frame_right_gray = cv2.cvtColor(frame_right, cv2.COLOR_BGR2GRAY)
# frame_right = self.frame_left # 原始彩色图
# frame_right_gray = cv2.cvtColor(frame_right, cv2.COLOR_BGR2GRAY)
def video_recog_left():
img = frame_left
spark, x, y = self.vision.find_spark(img)
self.q.enqueue(spark)
# print(spark)
if spark:
self.type_l = 'work'
self.X_l = x
self.Y_l = y
else:
self.type_l = ''
if spark or True in self.q.queue: # 如果一段间隔时间内不断有火花（和机器移动，稍后完成），则说明机器必定处于工作状态
self.one_static_time = 0 # 恢复到运动后，一次静止时间重新清零
self.work_time += 1
self.is_work = True
if self.work_time % 20 == 0:
current_time = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
da = data_access.DataAccess()
da.update_("insert into mstatus(SJC,status)values('" +
current_time + "',1)")
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + '机器正在工作'
self.displayMessage(message)
else:
# ******* 截图
self.is_work = False
self.one_static_time += 1 # 一次静止时间
if self.one_static_time % 60 == 0:
print('start or static')
print('静止了，往catch文件夹中查看原因')
t = time.localtime()
hour = t[3]
mini = t[4]
seco = t[5]
filename = str(hour) + '-' + str(mini) + '-' + str(seco)
cv2.imwrite('./catch/' + filename + '.jpg', img)
# ********
self.action = ThreadedTCPRequestHandler.action # 键盘操作
if self.action is not None: # 往面板上写当前由于什么原因导致机器静止
if self.pre_action is None:
print(self.action)
message = '[' + time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(
time.time())) + ']' + str(self.action)
self.displayMessage(message)
if self.vision.tiaoshi(frame_left_gray):
self.action_video = 'tiaoshi'
if self.action_video is not None:
if self.pre_action_video is None:
pass
# print(self.action_video)
# message = '[' + time.strftime('%Y-%m-%d %H:%M:%S',
# time.localtime(time.time())) + ']' + str(self.action_video)
# self.displayMessage(message)
video_recog_left()
self.pre_action = self.action
self.pre_action_video = self.action_video
def data_read(self):
pass
def displayMessage(self, message):
self.ui.textBrowser.append(message)
