DATE: 2018.12.9

1、前言

這個介面是之前讀研時候學習QT時寫的一個簡單的介面，主要實現了人臉檢測部分的功能，比較簡單。

從今年3月份就開始寫這個視訊監控的功能，一直拖到了11月份。找工作結束後，可以好好研究一下Python和Qt以及兩者的混合程式設計了。
不過，在實現視訊監控介面的過程中，甚是糾結，看來混合程式設計是不好弄的。

2、簡單的視訊監控介面實現

平臺：Python + Qt
初步程式碼如下：

	
# -*- coding:utf-8 -*-
#Created by SoaringLee at 2016/3/26
#Updated by SoaringLee at 2016/11/9
 


from PyQt4 import QtCore, QtGui
import sys
import cv2
import cv2.cv as cv
import numpy as np
cascade_fn = 'data/haarcascades/haarcascade_frontalface_alt2.xml' #訓練好的xml資料
save_video = False
snap_flag = False
open_face = True
preprocessing = True

def Face_detect(img, cascade):  #人臉檢測函式
    rects = cascade.
 
detectMultiScale(img, scaleFactor=1.3,minNeighbors=5, minSize=(20, 20),
                                         flags = cv.CV_HAAR_SCALE_IMAGE)
    if len(rects) == 0:
            return []
    #print rects
    rects[:,2:] += rects[:,:2]  #這是什麼意思,設定矩形框的大小
    print rects
    return rects

def draw_rects
 
(img, rects, color): #在img上繪製矩形
    for x1, y1, x2, y2 in rects:
        cv2.rectangle(img, (x1, y1), (x2, y2), color, 2)

def laplaceTransform(img):    #Laplace濾波
    gray_laplace = cv2.Laplacian(img,cv2.CV_16S,ksize = 3)
    dst = cv2.convertScaleAbs(gray_laplace)
    return dst

def SobelFilter(img):        #Sobel濾波
    x = cv2.Sobel(img,cv2.CV_16S,1,0)
    y = cv2.Sobel(img,cv2.CV_16S,0,1)
    absX = cv2.convertScaleAbs(x)
    absY = cv2.convertScaleAbs(y)
    gray_sobel = cv2.addWeighted(absX,0.5,absY,0.5,0)
    return gray_sobel
#########################################################################
##視訊監控介面原型 功能說明：
##（1）按下ESC或者q鍵，退出視訊監控介面【已實現】
##（2）按下空格鍵，儲存當前視訊影象到本地（攝像頭拍照功能）【已實現】
##（3）選擇是否人臉檢測和將視訊儲存到本地（本地錄影功能）【已實現】
##（4）增加功能：多路實時監控，調節亮度和對比度功能，調節畫質功能，網路視訊監控，迴圈錄影功能
##（5）GUI介面封裝：將視訊監控功能封裝成介面，實現監控產品的基本功能。進一步考慮網路功能
#########################################################################

try:
    _fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
    def _fromUtf8(s):
        return s

try:
    _encoding = QtGui.QApplication.UnicodeUTF8
    def _translate(context, text, disambig):
        return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
    def _translate(context, text, disambig):
        return QtGui.QApplication.translate(context, text, disambig)

class Ui_MainWindow(object):
    def setupUi(self, MainWindow):
        MainWindow.setObjectName(_fromUtf8("Video Surveilliance Interface"))
        MainWindow.resize(688, 427)
        self.centralWidget = QtGui.QWidget(MainWindow)
        self.centralWidget.setObjectName(_fromUtf8("centralWidget"))
        self.Btn_VideoWriter = QtGui.QPushButton(self.centralWidget)
        self.Btn_VideoWriter.setGeometry(QtCore.QRect(20, 40, 91, 41))
        self.Btn_VideoWriter.setObjectName(_fromUtf8("Btn_VideoWriter"))
        self.Btn_VideoWriter.clicked.connect(self.Btn_VideoWriter_Clicked)

        self.Btn_VideoWarning = QtGui.QPushButton(self.centralWidget)
        self.Btn_VideoWarning.setGeometry(QtCore.QRect(20, 110, 91, 41))
        self.Btn_VideoWarning.setObjectName(_fromUtf8("Btn_VideoWarning"))

        self.Btn_VideoSnap = QtGui.QPushButton(self.centralWidget)
        self.Btn_VideoSnap.setGeometry(QtCore.QRect(20, 180, 91, 41))
        self.Btn_VideoSnap.setObjectName(_fromUtf8("Btn_VideoSnap"))
        self.Btn_VideoSnap.clicked.connect(self.Btn_VideoSnap_Clicked)

        self.Btn_FaceDetection = QtGui.QPushButton(self.centralWidget)
        self.Btn_FaceDetection.setGeometry(QtCore.QRect(20, 250, 91, 41))
        self.Btn_FaceDetection.setObjectName(_fromUtf8("Btn_FaceDetection"))
        self.Btn_FaceDetection.clicked.connect(self.Btn_FaceDetection_Clicked)

        self.Btn_Preprocessing = QtGui.QPushButton(self.centralWidget)
        self.Btn_Preprocessing.setGeometry(QtCore.QRect(20, 320, 91, 41))
        self.Btn_Preprocessing.setObjectName(_fromUtf8("Btn_Preprocessing"))
        self.Btn_Preprocessing.clicked.connect(self.Btn_Preprocessing_Clicked)

        self.label = QtGui.QLabel(self.centralWidget)
        self.label.setObjectName(_fromUtf8("label"))
        #self.label.setGeometry(QtCore.QRect(20, 320, 91, 41))

        MainWindow.setCentralWidget(self.centralWidget)
        self.menuBar = QtGui.QMenuBar(MainWindow)
        self.menuBar.setGeometry(QtCore.QRect(0, 0, 688, 23))
        self.menuBar.setObjectName(_fromUtf8("menuBar"))
        MainWindow.setMenuBar(self.menuBar)
        self.mainToolBar = QtGui.QToolBar(MainWindow)
        self.mainToolBar.setObjectName(_fromUtf8("mainToolBar"))
        MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.mainToolBar)
        self.statusBar = QtGui.QStatusBar(MainWindow)
        self.statusBar.setObjectName(_fromUtf8("statusBar"))
        MainWindow.setStatusBar(self.statusBar)

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

    def Btn_VideoWriter_Clicked(self):
        save_video =True
    def Btn_VideoSnap_Clicked(self):
        snap_flag = True
    def Btn_FaceDetection_Clicked(self):
        open_face = True
    def Btn_Preprocessing_Clicked(self):
        preprocessing = True
    def retranslateUi(self, MainWindow):
        MainWindow.setWindowTitle( "MainWindow")

        self.Btn_VideoWriter.setText(_fromUtf8("Recoding"))
        self.Btn_VideoWarning.setText(_translate("MainWindow","Video Warning",None))
        self.Btn_VideoSnap.setText(_translate("MainWindow","Snap",None))
        self.Btn_FaceDetection.setText(_translate("MainWindow","Face Detection",None))
        self.Btn_Preprocessing.setText(_translate("MainWindow","Preprocessing",None))
        self.label.setText("Image")
    def camera_cap(self,MainWindow):
        capture1=cv2.VideoCapture(0) #獲取攝像頭資料
      #將capture儲存為motion-jpeg,cv_fourcc為儲存格式
        size = (int(capture1.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)),
            int(capture1.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)))

      #isopened可以檢視攝像頭是否開啟
        print capture1.isOpened(),r"攝像頭1已開啟！"
        num=0
        if save_video:
            flag = True
            video=cv2.VideoWriter("VideoTest.avi", cv2.cv.CV_FOURCC('I','4','2','0'),30, size)
        else:
            flag = None
          #要不斷讀取image需要設定一個迴圈
        while True:
            if capture1.isOpened():
                ret1,img1=capture1.read()
           #視訊中的圖片一張張寫入
            if flag:
                video.write(img1)
            cv2.imshow(r'【視訊監控畫面1】',img1);
            cv2.waitKey(1)
            #cv2.imwrite('%s.jpg'%(str(num)),img)
            gray = cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)
            cascade = cv2.CascadeClassifier(cascade_fn) #載入分類器
            if not cascade:
                print stderr,"ERROR:Could not load classifier cascade!"
            else:
                pass
            rects1 = Face_detect(gray, cascade) #進行人臉檢測
            vis1= img1.copy()
            if open_face:
                draw_rects(vis1, rects1, (0, 255, 0))
                cv2.imshow(r'人臉檢測', vis1)
            if preprocessing:
                laplace=laplaceTransform(vis1)
                cv2.imshow(r'laplace【拉普拉斯銳化】',laplace)

                sobel =SobelFilter(vis1)
                cv2.imshow(r'Sobel【邊緣提取】',sobel)

                equalize = cv2.equalizeHist(gray)
                cv2.imshow(r'【直方圖均衡化】',equalize)

            key=cv2.waitKey(2)#裡面數字為delay時間，如果大於0為重新整理時間，
                #超過指定時間則返回-1，等於0沒有返回值，但也可以讀取鍵盤數值。此處設定重新整理時間為2ms
            num = num+1
            if key == ord('q'):
                break
            if key == 27: #27表示ESC的ASCII碼值
                break
            if snap_flag:
                cv2.imwrite(r'通道1_儲存的圖片'+str(num)+'.jpg',img1)
        capture1.release()#關閉攝像頭
        cv2.destroyAllWindows()#關閉所有視窗


if __name__ == "__main__":
    app = QtGui.QApplication(sys.argv)
    MainWindow = QtGui.QMainWindow()
    ui = Ui_MainWindow()
    ui.setupUi(MainWindow)
    MainWindow.show()
    ui.camera_cap(MainWindow)
    sys.exit(app.exec_())

執行結果：

相關功能有待進一步完善！

THE END!