找红色绿色四边形物体——带qt界面

深碍√TFBOYSˉ_ 2022-11-16 05:44 145阅读 0赞

# 2021.4.6版本程序备份 #

## 效果图 ##

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70]

## 代码 ##

import cv2
    import numpy as np
    from imutils import contours
    
    # 获取一个视频并打开
    cap = cv2.VideoCapture('test.mp4')
    
    # 绿色阈值
    green_lower = np.array([35, 43, 35])
    green_upper = np.array([90, 255, 255])
    
    # 红色阈值
    red_lower = np.array([160, 20, 70])
    red_upper = np.array([190, 255, 255])
    # 内核
    kernel = np.ones((5, 5), np.uint8)
    
    # VideoCapture对象是否成功打开
    if cap.isOpened():
        print('已经打开了视频')
        fps = cap.get(cv2.CAP_PROP_FPS)
        print('视频的帧率为：', fps)
        while 1:
            # 读取一帧视频
            ret, frame = cap.read()
            if not ret:
                print('视频已结束')
                break
            draw_frame = frame.copy()
            # 转变为HSV颜色空间
            img_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
            # 颜色识别
            #img = cv2.inRange(img_hsv, green_lower, green_upper)
            img = cv2.inRange(img_hsv, red_lower, red_upper)
            # 膨胀操作
            dilation = cv2.dilate(img, kernel, iterations=1)
            # 闭操作
            closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)
            # 高斯滤波
            closing = cv2.GaussianBlur(closing, (5, 5), 0)
            # 边缘检测
            edges = cv2.Canny(closing, 10, 20)
    
            # 寻找轮廓
            contour, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    
            if len(contour) > 0:
                # 存放轮廓面积的列表
                s = []
                # 存放最大轮廓的索引
                max_index = 0
                # 获得排序后的轮廓列表以及每个轮廓对应的外接矩形
                (contour, boundingBoxes) = contours.sort_contours(contour)
                # 寻找面积最大的轮廓的索引
                for cnt in contour:
                    s.append(cv2.contourArea(cnt))
                max_index = s.index(max(s))
                # 根据面积最大轮廓的索引找到它的外接矩形的信息
                (x, y, w, h) = boundingBoxes[max_index]
                # 画矩形
                frame_out = cv2.rectangle(draw_frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    
            cv2.namedWindow('draw_frame', 0)
            cv2.imshow("draw_frame", draw_frame)
            cv2.waitKey(int(fps))
    else:
        print('视频打开失败')

# 2021.4.6第二版本程序备份 #

## 效果图 ##

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70 1]

## 代码 ##

import cv2
    import numpy as np
    from imutils import contours
    
    Picture_display_flag=0
    
    # 获取一个视频并打开
    cap = cv2.VideoCapture('test.mp4')
    
    # 绿色阈值
    green_lower = np.array([35, 43, 35])
    green_upper = np.array([90, 255, 255])
    
    # 红色阈值
    red_lower = np.array([160, 20, 70])
    red_upper = np.array([190, 255, 255])
    # 内核
    kernel = np.ones((5, 5), np.uint8)
    kernel_1 = np.ones((7, 7), np.uint8)
    # VideoCapture对象是否成功打开
    if cap.isOpened():
        print('已经打开了视频')
        fps = cap.get(cv2.CAP_PROP_FPS)
        print('视频的帧率为：', fps)
        while 1:
            # 1、 读取一帧视频
            ret, frame = cap.read()
            if not ret:
                print('视频已结束')
                break
            draw_frame = frame.copy()
            # 2、转变为HSV颜色空间
            img_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
            # 3、颜色识别
            #img = cv2.inRange(img_hsv, green_lower, green_upper)
            img = cv2.inRange(img_hsv, red_lower, red_upper)#红色
            if Picture_display_flag==1:
                cv2.namedWindow('img', 0)
                cv2.imshow("img", img)
            # 4、膨胀操作
            dilation = cv2.dilate(img, kernel_1, iterations=1)
            # 5、闭操作
            closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel_1)
            # 6、高斯滤波
            closing = cv2.GaussianBlur(closing, (5, 5), 0)
            if Picture_display_flag==1:
                cv2.namedWindow('closing', 0)
                cv2.imshow("closing", img)
    
            # 7、寻找轮廓
            contour, hierarchy = cv2.findContours(closing, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
            new_contour = []#新轮廓
    
            if len(contour) > 0:
                if Picture_display_flag == 1:
                    drawlk = cv2.drawContours(draw_frame, contour, -1, (0, 255, 255),2)  # 画出所有轮廓，-1 ；最大的轮廓 1是cants【1】，-1是所有轮廓
                # 存放轮廓面积的列表
                s = []
                # 存放最大轮廓的索引
                max_index = 0
                # 获得排序后的轮廓列表以及每个轮廓对应的外接矩形
                (contour, boundingBoxes) = contours.sort_contours(contour)
    
                # 8、寻找面积最大的轮廓的索引,通过面积滤除小轮廓
                for cnt in contour:
                    s.append(cv2.contourArea(cnt))
                max_index = s.index(max(s))
    
                # 9、拟合多边形
                epsilon = 0.01 * cv2.arcLength(contour[max_index], True)        #精度为最大轮廓长*0.01,参数越小越表示逼近的多边形精密
                #epsilon = 0.1 * cv2.arcLength(contour[1], True) # 精度为最大轮廓长*0.01
                approx=cv2.approxPolyDP(contour[max_index],epsilon,True)        #以最大轮廓为准，构造逼近多边形
                cv2.polylines(draw_frame, [approx], True, (255, 255, 0), 4)#画出多边形
    
    
            cv2.namedWindow('draw_frame', 0)
            cv2.imshow("draw_frame", draw_frame)
            cv2.waitKey(int(fps))
    else:
        print('视频打开失败')

# 2021.4.7第一版本程序备份——gui界面 #

## 效果图 ##

![在这里插入图片描述][watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBA57-f57695ZqE_size_20_color_FFFFFF_t_70_g_se_x_16]

## 代码 ##

# -*- coding: utf-8 -*-
    '''************************************************************************** 这是通用的图像识别的qt界面，具有读入图片，读入视频，显示图片显示视频的功能。 版本：1.0 内容：创建pyqt界面，用于图像识别，有基本打开图像，显示图像功能 时间：2020.3.20 作者：狄云 版本：2.0 内容：新增视频可以实时显示并检测，修改图片检测缓存路径，改为相对路劲 时间：2020.7.20 作者：狄云 版本：3.0 内容：新增空间间距设置，新增打开视频功能，（与之前打开图片功能相同） 时间：2020.8.16 作者：狄云 版本：4.0 内容：新增表格显示，使用方法参考：https://www.cnblogs.com/linyfeng/p/11832237.html 时间：2020.8.30 作者：狄云 版本：5.0 内容：新增登录界面，新增保存excel文件，使用方法参考：https://www.cnblogs.com/jyroy/p/9465034.html 时间：2020.9.04 作者：狄云 ***************************************************************************'''
    
    from PIL import Image
    
    
    import datetime
    
    
    import sys
    import argparse
    
    from PIL import Image
    import numpy as np
    import sys
    from PyQt5 import QtCore, QtGui, QtWidgets
    from PyQt5.QtWidgets import *
    from PyQt5.QtCore import *
    from PyQt5.QtGui import *
    
    import os
    import datetime
    from timeit import time
    import warnings
    import cv2 as cv
    import numpy as np
    import argparse
    from PIL import Image
    
    
    import sys
    from PyQt5.QtCore import QSize
    from PyQt5.QtWidgets import QApplication
    from PyQt5.QtCore import Qt
    from PyQt5.QtWidgets import QComboBox
    from PyQt5.QtWidgets import QGridLayout
    from PyQt5.QtWidgets import QLineEdit
    from PyQt5.QtWidgets import QLabel
    from PyQt5.QtGui import QIcon
    from PyQt5.QtWidgets import QWidget, QVBoxLayout, QPushButton, QTextEdit
    
    from PyQt5 import QtWidgets
    from PyQt5.QtWidgets import *
    from PyQt5.QtGui import *
    
    
    from PyQt5.QtCore import *
    from PyQt5.QtWidgets import *
    from PyQt5.QtGui import *
    
    
    
    from imutils import contours
    
    
    
    
    from qtpy import QtGui
    from PyQt5.QtGui import QFont
    
    ###========全局变量 定义开始=======###
    # 打开的是摄像头还是本地视频
    camera_or_local_flag = 0
    # 识别进行中还是暂停识别中，1为摄像头，2位本地摄像头
    Start_or_pause_flag = 0
    
    #是否显示调试图像
    Picture_display_flag=0
    
    result_image = ...
    
    fps = 0.0
    len_last = 0
    #查找系统有几个摄像头
    class Camera:
        def __init__(self, cam_preset_num=10):
            self.cam_preset_num = cam_preset_num
    
        def get_cam_num(self):
            cnt = 0
            for device in range(0, self.cam_preset_num):
                stream = cv.VideoCapture(device)
    
                grabbed = stream.grab()
                stream.release()
                if not grabbed:
                    break
                cnt = cnt + 1
    
            return cnt
    class Ui_MainWindow(object):
    
        def setupUi(self, MainWindow):
            MainWindow.setObjectName("MainWindow")
            # 1、总界面框大小 MainWindow
            MainWindow.resize(1650, 820)  # 总界面框
            # 左边界面区域：verticalLayoutWidget QWidget类
            self.verticalLayoutWidget = QtWidgets.QWidget(MainWindow)
            self.verticalLayoutWidget.setGeometry(QtCore.QRect(30, 25, 1280, 720))  # 左边图片框。左上角坐标及宽度高度
            self.verticalLayoutWidget.setStyleSheet('background-color:rgb(55,55,55)')  # 设置做左边框的颜色
            self.verticalLayoutWidget.setObjectName("verticalLayoutWidget")
            self.verticalLayout = QtWidgets.QVBoxLayout(self.verticalLayoutWidget)  # QVBoxLayout类 垂直地摆放小部件
            self.verticalLayout.setContentsMargins(0, 0, 0, 0)  # 设置左侧、顶部、右侧和底部边距，以便在布局周围使用。
            self.verticalLayout.setObjectName("verticalLayout")
            self.label_ShowPicture = QtWidgets.QLabel(self.verticalLayoutWidget)
            self.label_ShowPicture.setObjectName("label_ShowPicture")
            self.verticalLayout.addWidget(self.label_ShowPicture)
    
            # 右边按钮及显示结果字符的一块区域：verticalLayoutWidget_2 QWidget类
            self.verticalLayoutWidget_2 = QtWidgets.QWidget(MainWindow)
            self.verticalLayoutWidget_2.setGeometry(QtCore.QRect(1350, 50, 250, 700))  # 右边按钮及显示结果字符的大小
            # self.verticalLayoutWidget_2.setStyleSheet('background-color:rgb(155,155,155)') # 设置做左边框的颜色
            self.verticalLayoutWidget_2.setObjectName("verticalLayoutWidget_2")
            self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.verticalLayoutWidget_2)  # QVBoxLayout类 垂直地摆放小部件
            self.verticalLayout_2.setContentsMargins(0, 0, 0, 0)
            self.verticalLayout_2.setObjectName("verticalLayout_2")
    
            # 设置控件间的间距
            self.verticalLayout_2.setSpacing(30)
    
            # 按钮0 查看系统有几个摄像头：pushButton_select_pcture
            self.pushButton_find_camera = QtWidgets.QPushButton(self.verticalLayoutWidget_2)
            self.pushButton_find_camera.setObjectName("pushButton_find_camera")
            self.verticalLayout_2.addWidget(self.pushButton_find_camera)  # 将按钮1增加到
    
    
    
    
            # 按钮1 选择图片按钮：pushButton_select_pcture
            self.pushButton_open_camera = QtWidgets.QPushButton(self.verticalLayoutWidget_2)
            self.pushButton_open_camera.setObjectName("pushButton_open_camera")
            self.verticalLayout_2.addWidget(self.pushButton_open_camera)  # 将按钮1增加到
    
            # 按钮2 选择视频按钮：pushButton_select_pcture
            self.pushButton_open_Local_video = QtWidgets.QPushButton(self.verticalLayoutWidget_2)
            self.pushButton_open_Local_video.setObjectName("pushButton_open_Local_video")
            self.verticalLayout_2.addWidget(self.pushButton_open_Local_video)  # 将按钮1增加到
    
            # 2：下拉菜单：颜色选择
            self.comboBox_1 = QtWidgets.QComboBox(self.verticalLayoutWidget_2)
            self.comboBox_1.setObjectName("comboBox_1")
            self.verticalLayout_2.addWidget(self.comboBox_1)
            self.comboBox_1.addItems([' 颜色选择', ' 红色', ' 绿色'])
    
            # 2：下拉菜单：形状选择
            self.comboBox_2 = QtWidgets.QComboBox(self.verticalLayoutWidget_2)
            self.comboBox_2.setObjectName("comboBox_2")
            self.verticalLayout_2.addWidget(self.comboBox_2)
            self.comboBox_2.addItems([' 形状选择', ' 矩形', ' 圆形'])
    
    
            # 按钮3 开始识别按钮：pushButton_shibie
            self.pushButton_Start_or_pause = QtWidgets.QPushButton(self.verticalLayoutWidget_2)
            self.pushButton_Start_or_pause.setObjectName("pushButton_Start_or_pause")
            self.verticalLayout_2.addWidget(self.pushButton_Start_or_pause)
            # 按钮4 选择模型：pushButton_shibie
            self.pushButton_save = QtWidgets.QPushButton(self.verticalLayoutWidget_2)
            self.pushButton_save.setObjectName("pushButton_save")
            self.verticalLayout_2.addWidget(self.pushButton_save)
    
            # 放“图像识别结果为”这一句话
            self.label = QtWidgets.QLabel(self.verticalLayoutWidget_2)
            font = QtGui.QFont()
            font.setPointSize(15)
            self.label.setFont(font)
            self.label.setObjectName("label")
            self.verticalLayout_2.addWidget(self.label)
    
            #lable_2放显示结果1
            self.label_2 = QtWidgets.QLabel(self.verticalLayoutWidget_2)
            font = QtGui.QFont()
            font.setPointSize(15)
            self.label_2.setFont(font)
            self.label_2.setText("")
            self.label_2.setObjectName("label_2")
            self.verticalLayout_2.addWidget(self.label_2)
            #
    
    
            # 表格
            self.tableWidget = QtWidgets.QTableWidget(self.verticalLayoutWidget_2)
            self.tableWidget.setObjectName("tableWidget")
            self.tableWidget.setColumnCount(3)  # 列数
            self.tableWidget.setRowCount(100000)  # 行数
            # 设置表格的行、列标题，如下：
            self.tableWidget.setHorizontalHeaderLabels(['帧号', '时刻', '状态'])
            # self.tableWidget.setVerticalHeaderLabels(['1', '2'])
            self.verticalLayout_2.addWidget(self.tableWidget)  # 将表格加入到verticalLayout_2空间中，依次罗列
            self.msg_box = QtWidgets.QMessageBox
            # 指定列宽
            self.tableWidget.horizontalHeader().resizeSection(0, 55)
            self.tableWidget.horizontalHeader().resizeSection(1, 265)
            self.tableWidget.horizontalHeader().resizeSection(2, 140)
    
            # self.tableWidget.setEditTriggers(QAbstractItemView.NoEditTriggers)#禁止用户编辑，即只读
            # 行、列标题的显示与隐藏。
            # self.tableWidget.horizontalHeader().setVisible(False)#列标题不显示
            self.tableWidget.verticalHeader().setVisible(False)  # 行标题不显示
    
            self.timer_camera = QtCore.QTimer()  # 初始化定时器
            self.cap = cv.VideoCapture()  # 初始化摄像头
            self.CAM_NUM = 0
            self.__flag_work = 0
            self.x = 0
            self.count = 0
            # 视频显示与计时器，以及关闭识别
            # 建立通信连接
            self.pushButton_find_camera.clicked.connect(self.button_find_camera_click)
            self.pushButton_open_camera.clicked.connect(self.button_open_camera_click)
            self.timer_camera.timeout.connect(self.deep_sort)
            self.pushButton_open_Local_video.clicked.connect(self.pushButton_open_Local_video_click)  #
            self.pushButton_Start_or_pause.clicked.connect(self.pushButton_Start_or_pause_click)
            self.pushButton_save.clicked.connect(self.pushButton_save_click)
    
            # 下拉菜单信号事件
            self.comboBox_1.currentIndexChanged[str].connect(self.print_value_1)  # 条目发生改变，发射信号，传递条目内容
            self.comboBox_1.currentIndexChanged[int].connect(self.print_value_1)  # 条目发生改变，发射信号，传递条目索引
            # 下拉菜单信号事件
            self.comboBox_2.currentIndexChanged[str].connect(self.print_value_2)  # 条目发生改变，发射信号，传递条目内容
            self.comboBox_2.currentIndexChanged[int].connect(self.print_value_2)  # 条目发生改变，发射信号，传递条目索引
            self.retranslateUi(MainWindow)
            QtCore.QMetaObject.connectSlotsByName(MainWindow)
            name_picture = 0
    
        def retranslateUi(self, MainWindow):
            _translate = QtCore.QCoreApplication.translate
            MainWindow.setWindowTitle(_translate("MainWindow", "pyqt通用界面"))
            # self.label_ShowPicture.setText(_translate("MainWindow", "图片展示区"))
            self.pushButton_find_camera.setText(_translate("MainWindow", "检查设备"))
            self.pushButton_open_camera.setText(_translate("MainWindow", "打开摄像头识别"))
            self.pushButton_open_Local_video.setText(_translate("MainWindow", "选择本地视频识别"))
            self.pushButton_Start_or_pause.setText(_translate("MainWindow", "开始识别"))
            self.pushButton_save.setText(_translate("MainWindow", "保存结果"))
            #self.label.setText(_translate("MainWindow", "图像识别结果为："))
    
    
        image = None
    
    
        # 查看系统有几个摄像头
        def button_find_camera_click(self):
            cam = Camera()
            cam_num = cam.get_cam_num()
            print(cam_num)
            new_num=str(cam_num)
            #self.label_2.setText(cam_num)
            self.label.setText( "当前设备摄像头个数为：")
            self.label_2.setText(new_num)
    
        # 打开摄像头
        def button_open_camera_click(self):
            global camera_or_local_flag
            if self.timer_camera.isActive() == False:
                flag = self.cap.open(self.CAM_NUM)
                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)
                # if msg==QtGui.QMessageBox.Cancel:
                # pass
                else:
                    self.timer_camera.start(30)
                    camera_or_local_flag = 1  # 打开了摄像头
                    self.pushButton_open_camera.setText(u'关闭相机')
            else:
                self.timer_camera.stop()
                self.cap.release()
                camera_or_local_flag = 0  # 关闭了摄像头
                self.label_ShowPicture.clear()
                self.pushButton_open_camera.setText(u'打开相机')
    
        # 选择图片
        def pushButton_select_pcture_click(self):
            filename = QFileDialog.getOpenFileName(None, 'Open file', 'C:/Users/Desktop/testpicture/')
            # 设置标签的图片
            src0 = cv.imread(filename[0])
            resized0 = cv.resize(src0, (1280, 720), interpolation=cv.INTER_AREA)
            cv.imwrite("./temp/temp0.jpg", resized0)
            self.label_ShowPicture.setPixmap(QPixmap("./temp/temp0.jpg"))
            print("filename[0]=", filename[0])
            self.image = Image.open(filename[0])
    
        # img1 = yolo.detect_image(image)
        # img1.show()
    
        # 选择视频
        def pushButton_open_Local_video_click(self):
            global camera_or_local_flag
            # 打开本地视频，则关闭摄像头的视频
            self.timer_camera.stop()
            self.cap.release()
            camera_or_local_flag = 0  # 关闭了摄像头
            self.label_ShowPicture.clear()
            self.pushButton_open_camera.setText(u'打开相机')
    
            if self.timer_camera.isActive() == False:
                print("打开本地视频")
                self.fileName, self.fileType = QFileDialog.getOpenFileName(None, 'Choose file', '', '*.mp4')
                self.cap_Local_video = cv.VideoCapture(self.fileName)
    
                # self.timer_camera.start(30)
                camera_or_local_flag = 2  # 打开了本地视频
                #self.pushButton_open_Local_video.setText(u'关闭本地视频')
    
                # 打开录像后，不进行播放，等点击开始识别后开始播放
                ret, self.frame = self.cap_Local_video.read()
                img = cv.resize(self.frame, (1280, 720), interpolation=cv.INTER_AREA)
                height, width, bytesPerComponent = img.shape  # 取彩色图片的长、宽、通道
                bytesPerLine = 3 * width
                cv.cvtColor(img, cv.COLOR_BGR2RGB, img)
                QImg = QImage(img.data, width, height, bytesPerLine, QImage.Format_RGB888)
                pixmap = QPixmap.fromImage(QImg)
                self.label_ShowPicture.setPixmap(QPixmap(pixmap))
            else:
                self.timer_camera.stop()
                self.cap_Local_video.release()
                camera_or_local_flag = 0  # 关闭了摄像头
                self.label_ShowPicture.clear()
                self.pushButton_open_Local_video.setText(u'打开本地视频')
    
        # 开启按钮
        def pushButton_Start_or_pause_click(self):
            global camera_or_local_flag
            global Start_or_pause_flag
            print(camera_or_local_flag, Start_or_pause_flag)
            print(254)
            if camera_or_local_flag == 1: # 摄像头视频
                if Start_or_pause_flag == 0:
                    Start_or_pause_flag = 1  # 代表开始识别
                    print(258)
                    self.timer_camera.start(30)
                    self.pushButton_Start_or_pause.setText(u'识别中')
                # self.deep_sort() # 调用函数
    
                else:
                    Start_or_pause_flag = 0  # 3代表开始识别
                    self.timer_camera.stop(30)
                    self.pushButton_Start_or_pause.setText(u'开始识别')
            elif camera_or_local_flag == 2: # 本地视频
                if Start_or_pause_flag == 0:
                    Start_or_pause_flag = 1  # 代表开始识别
                    self.timer_camera.start(30)
                    print(269)
                    print(camera_or_local_flag, Start_or_pause_flag)
                    self.pushButton_Start_or_pause.setText(u'识别中')
                # self.deep_sort() # 调用函数
    
                else:
                    Start_or_pause_flag = 0  # 3代表开始识别
                    self.timer_camera.stop(30)
                    self.pushButton_Start_or_pause.setText(u'开始识别')
    
            print(" 2 camera_or_local_flag =%d Start_or_pause_flag =%d", camera_or_local_flag, Start_or_pause_flag)
    
        def pushButton_save_click(self):
            print("保存成功")
        #下拉框
        def print_value_1(self, i):
            global type_seting_yanse
            if i==0:
                print("请选择等级")
                type_seting_yanse = -1
            if i == 1:
                print("等级为红色")
                type_seting_yanse=0
            if i == 2:
                print("等级为绿色")
                #global type_seting
                type_seting_yanse = 1
        #下拉框
        def print_value_2(self, i):
            global type_seting_xingzhuang
            if i==0:
                print("请选择等级")
                type_seting_xingzhuang = -1
            if i == 1:
                print("等级为矩形")
                type_seting_xingzhuang=0
            if i == 2:
                print("等级为圆形")
                #global type_seting
                type_seting_xingzhuang = 1
    
        # 事件函数
        def select_shipin(self):
            global camera_or_local_flag
            global Start_or_pause_flag
            global result_image
            print("选择视频中")
    
    
        def deep_sort(self):
            global camera_or_local_flag
            global Start_or_pause_flag
            global result_image
            global counter_zhenhao
            global counter_jueduizhenhao
            global fps
            global len_last
            i = int(0)
            ret = False
            if camera_or_local_flag == 1 and Start_or_pause_flag == 0:
                ret, self.frame = self.cap.read()
            elif camera_or_local_flag == 2 and Start_or_pause_flag == 0:  # 打开本地文件，且只显示首帧
                ret, self.frame = self.cap_Local_video.read()
    
            if camera_or_local_flag == 1 and Start_or_pause_flag == 1:
                ret, self.frame = self.cap.read()
            elif camera_or_local_flag == 2 and Start_or_pause_flag == 1:  # 打开本地文件，且只显示首帧
                ret, self.frame = self.cap_Local_video.read()
    
            # print(ret, camera_or_local_flag, Start_or_pause_flag)
    
            if ret != True:
                print("打开图像失败 or 识别结束")
                return
            if Start_or_pause_flag == 1:
    
                t1 = time.time()
                frame0 = cv.resize(self.frame, (1280, 720), interpolation=cv.INTER_AREA)
                frame = frame0.copy()
                draw_frame = frame0.copy()
                # 2、转变为HSV颜色空间
                img_hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
                # 3、颜色识别
                # img = cv2.inRange(img_hsv, green_lower, green_upper)
                img = cv.inRange(img_hsv, red_lower, red_upper)  # 红色
                if Picture_display_flag == 1:
                    cv.namedWindow('img', 0)
                    cv.imshow("img", img)
                # 4、膨胀操作
                dilation = cv.dilate(img, kernel_1, iterations=1)
                # 5、闭操作
                closing = cv.morphologyEx(dilation, cv.MORPH_CLOSE, kernel_1)
                # 6、高斯滤波
                closing = cv.GaussianBlur(closing, (5, 5), 0)
                if Picture_display_flag == 1:
                    cv.namedWindow('closing', 0)
                    cv.imshow("closing", img)
    
                # 7、寻找轮廓
                contour, hierarchy = cv.findContours(closing, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
                new_contour = []  # 新轮廓
    
                if len(contour) > 0:
                    if Picture_display_flag == 1:
                        drawlk = cv.drawContours(draw_frame, contour, -1, (0, 255, 255),
                                                  2)  # 画出所有轮廓，-1 ；最大的轮廓 1是cants【1】，-1是所有轮廓
                    # 存放轮廓面积的列表
                    s = []
                    # 存放最大轮廓的索引
                    max_index = 0
                    # 获得排序后的轮廓列表以及每个轮廓对应的外接矩形
                    (contour, boundingBoxes) = contours.sort_contours(contour)
    
                    # 8、寻找面积最大的轮廓的索引,通过面积滤除小轮廓
                    for cnt in contour:
                        s.append(cv.contourArea(cnt))
                    max_index = s.index(max(s))
    
                    # 9、拟合多边形
                    epsilon = 0.01 * cv.arcLength(contour[max_index], True)  # 精度为最大轮廓长*0.01,参数越小越表示逼近的多边形精密
                    # epsilon = 0.1 * cv2.arcLength(contour[1], True) # 精度为最大轮廓长*0.01
                    approx = cv.approxPolyDP(contour[max_index], epsilon, True)  # 以最大轮廓为准，构造逼近多边形
                    cv.polylines(draw_frame, [approx], True, (255, 255, 0), 4)  # 画出多边形
    
    
                fps = (fps + (1. / (time.time() - t1))) / 2
                #print("fps= %.2f" % (fps))
                draw_frame = cv.putText(draw_frame, "fps= %.2f" % (fps), (0, 40), cv.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
                frame0 = draw_frame.copy()
    
            else:
                frame0 = self.frame.copy()
            # 在界面实时显示结果
            img = cv.resize(frame0, (1280, 720), interpolation=cv.INTER_AREA)
            height, width, bytesPerComponent = img.shape  # 取彩色图片的长、宽、通道
            bytesPerLine = 3 * width
            cv.cvtColor(img, cv.COLOR_BGR2RGB, img)
            QImg = QImage(img.data, width, height, bytesPerLine, QImage.Format_RGB888)
            pixmap = QPixmap.fromImage(QImg)
            self.label_ShowPicture.setPixmap(QPixmap(pixmap))
    
    
    if __name__ == "__main__":
    
        counter_zhenhao = 3
        counter_jueduizhenhao = 0
        #os.system('python login_main.py') # 执行login_main.py文件，即登录界面，账号和密码为 diyun 12345
        # 绿色阈值
        green_lower = np.array([35, 43, 35])
        green_upper = np.array([90, 255, 255])
    
        # 红色阈值
        red_lower = np.array([160, 20, 70])
        red_upper = np.array([190, 255, 255])
        # 内核
        kernel = np.ones((5, 5), np.uint8)
        kernel_1 = np.ones((7, 7), np.uint8)
    
    
    
        app = QtWidgets.QApplication(sys.argv)
    
        MainWindow = QtWidgets.QMainWindow()
        ui = Ui_MainWindow()
        ui.setupUi(MainWindow)
        MainWindow.show()
        sys.exit(app.exec_())

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70]: /images/20221022/e517fda53eb246d48831e6b5da89d7c7.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70 1]: /images/20221022/b2cd0a54a85843459f3d86ee4f0101bb.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBA57-f57695ZqE_size_20_color_FFFFFF_t_70_g_se_x_16]: /images/20221022/3767c6ed764442f79f05938c91f2351a.png