Pyqt搭建YOLOV5目标检测界面_使用pyqt5在搭建一个yolov5检测界面

本项目1.0版本github地址：https://github.com/chenanga/qt5_yolov5_1.0
本项目2.0版本github地址：https://github.com/chenanga/qt5_yolov5_2.0
（2.0版本是优化后的，视频检测和图片检测都比较快）

大家觉得有用的话，帮忙点点star，感谢大家！

2022.5.25更新

大家有问题的话尽量在评论区问，问之前可以看一下评论区有没有类似错误的解决方法。

2022.4.9更新

必读： 本篇文章给出了基于yolov5的实现，具体思路以及如何从零开始搭建界面可以参考上一篇博客：Pyqt搭建YOLOV3目标检测界面（超详细+源代码）

2021.11.19 更新

下面的代码片段大家可以参考着实现，如果直接拖拽到最新版的yolov5文件夹中运行可能会出错，应该我当时那个代码片段写的比较早，后续yolov5更新了，有些函数名有变动，所以直接运行会出错。我这里有当时和这个代码片段对应的yolov5的代码，但是不太知道这是哪个版本的yolov5。
所以有需要的朋友直接在公众号：万能的小陈 后台回复 qtv5，获取整个文件夹以及模型，配置环境后可以直接运行，配置环境教程可以参考这里

注：压缩包名字为qt5_yolov5_1.0的对应原始版本，也就是下面代码片段可以直接用的，qt5_yolov5_2.0对应的是优化后的。这两个压缩包中的yolov5也不是同一个版本的，一个是2021年上半年的，一个是2021年下半年的

---

以下是正文

实现效果如下所示，可以检测图片、视频以及摄像头实时检测。

测试平台：显卡1080ti。视频检测是优化后的版本，之前版本也可以视频检测，但是没这么流畅，优化后的版本在公众号： 万能的小陈 后台回复 qtv5。

具体细节实现可以参考上一篇博客：Pyqt搭建YOLOV3目标检测界面（超详细+源代码）
使用的yolov5版本为https://github.com/ultralytics/yolov5
这里直接贴出具体代码。

方法1：共两个文件，ui_yolov5.py 、detect_qt5.py，然后把yolov5的代码下载下来，直接把这两个文件拷贝到yolov5根目录，下载yolov5官方的yolov5s.pt权重，放置根目录，然后运行ui_yolov5.py 即可。

方法2：整个yolov5以及两个文件都已上传在github，点这里 。无法访问github的关注公众号：万能的小陈,回复qtv5即可获取下载链接。（包含所有代码以及权重文件），只需要配置一下环境，配置环境可以参考这里，如果环境配置困难的或者失败的，在公众号后台回复pyqt5即可获取完整环境。

文件1：ui_yolov5.py

#!/usr/bin/env python                                
# -*- coding:utf-8 -*-                           
# @author   : ChenAng                                    
# @file     : ui_yolov5.py
# @Time     : 2021/8/27 10:13

import time
import os
from PyQt5 import QtWidgets, QtCore, QtGui
from PyQt5.QtGui import *
import cv2
import sys
from PyQt5.QtWidgets import *
from detect_qt5 import main_detect,my_lodelmodel


'''摄像头和视频实时检测界面'''
class Ui_MainWindow(QWidget):
    def __init__(self, parent=None):
        super(Ui_MainWindow, self).__init__(parent)

        # self.face_recong = face.Recognition()
        self.timer_camera1 = QtCore.QTimer()
        self.timer_camera2 = QtCore.QTimer()
        self.timer_camera3 = QtCore.QTimer()
        self.timer_camera4 = QtCore.QTimer()
        self.cap = cv2.VideoCapture()

        self.CAM_NUM = 0

        # self.slot_init()
        self.__flag_work = 0
        self.x = 0
        self.count = 0
        self.setWindowTitle("yolov5检测")
        self.setWindowIcon(QIcon(os.getcwd() + '\\data\\source_image\\Detective.ico'))
        # self.resize(300, 150)  # 宽×高
        window_pale = QtGui.QPalette()
        window_pale.setBrush(self.backgroundRole(), QtGui.QBrush(
            QtGui.QPixmap(os.getcwd() + '\\data\\source_image\\backgroud.jpg')))
        self.setPalette(window_pale)
        self.setFixedSize(1600, 900)
        self.my_model = my_lodelmodel()

        self.button_open_camera = QPushButton(self)
        self.button_open_camera.setText(u'打开摄像头')
        self.button_open_camera.setStyleSheet(''' 
                                     QPushButton
                                     {text-align : center;
                                     background-color : white;
                                     font: bold;
                                     border-color: gray;
                                     border-width: 2px;
                                     border-radius: 10px;
                                     padding: 6px;
                                     height : 14px;
                                     border-style: outset;
                                     font : 14px;}
                                     QPushButton:pressed
                                     {text-align : center;
                                     background-color : light gray;
                                     font: bold;
                                     border-color: gray;
                                     border-width: 2px;
                                     border-radius: 10px;
                                     padding: 6px;
                                     height : 14px;
                                     border-style: outset;
                                     font : 14px;}
                                     ''')
        self.button_open_camera.move(10, 40)
        self.button_open_camera.clicked.connect(self.button_open_camera_click)
        #self.button_open_camera.clicked.connect(self.button_open_camera_click1)
        # btn.clicked.connect(self.openimage)

        self.btn1 = QPushButton(self)
        self.btn1.setText("检测摄像头")
        self.btn1.setStyleSheet(''' 
                                             QPushButton
                                             {text-align : center;
                                             background-color : white;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             QPushButton:pressed
                                             {text-align : center;
                                             background-color : light gray;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             ''')
        self.btn1.move(10, 80)
        self.btn1.clicked.connect(self.button_open_camera_click1)
        # print("QPushButton构建")



        self.open_video = QPushButton(self)
        self.open_video.setText("打开视频")
        self.open_video.setStyleSheet(''' 
                                             QPushButton
                                             {text-align : center;
                                             background-color : white;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             QPushButton:pressed
                                             {text-align : center;
                                             background-color : light gray;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             ''')
        self.open_video.move(10, 160)
        self.open_video.clicked.connect(self.open_video_button)
        print("QPushButton构建")

        self.btn1 = QPushButton(self)
        self.btn1.setText("检测视频文件")
        self.btn1.setStyleSheet(''' 
                                             QPushButton
                                             {text-align : center;
                                             background-color : white;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             QPushButton:pressed
                                             {text-align : center;
                                             background-color : light gray;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             ''')
        self.btn1.move(10, 200)
        self.btn1.clicked.connect(self.detect_video)
        print("QPushButton构建")

        # btn1.clicked.connect(self.detect())
        # btn1.clicked.connect(self.button1_test)


        #btn1.clicked.connect(self.detect())
        # btn1.clicked.connect(self.button1_test)

        btn2 = QPushButton(self)
        btn2.setText("返回上一界面")
        btn2.setStyleSheet(''' 
                                             QPushButton
                                             {text-align : center;
                                             background-color : white;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             QPushButton:pressed
                                             {text-align : center;
                                             background-color : light gray;
                                             font: bold;
                                             border-color: gray;
                                             border-width: 2px;
                                             border-radius: 10px;
                                             padding: 6px;
                                             height : 14px;
                                             border-style: outset;
                                             font : 14px;}
                                             ''')
        btn2.move(10, 240)
        btn2.clicked.connect(self.back_lastui)


        # 信息显示
        self.label_show_camera = QLabel(self)
        self.label_move = QLabel()
        self.label_move.setFixedSize(100, 100)
        # self.label_move.setText(" 11  待检测图片")
        self.label_show_camera.setFixedSize(700, 500)
        self.label_show_camera.setAutoFillBackground(True)
        self.label_show_camera.move(110,80)
        self.label_show_camera.setStyleSheet("QLabel{background:#F5F5DC;}"
                                  "QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
                                  )
        self.label_show_camera1 = QLabel(self)
        self.label_show_camera1.setFixedSize(700, 500)
        self.label_show_camera1.setAutoFillBackground(True)
        self.label_show_camera1.move(850, 80)
        self.label_show_camera1.setStyleSheet("QLabel{background:#F5F5DC;}"
                                             "QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
                                             )

        self.timer_camera1.timeout.connect(self.show_camera)
        self.timer_camera2.timeout.connect(self.show_camera1)
        # self.timer_camera3.timeout.connect(self.show_camera2)
        self.timer_camera4.timeout.connect(self.show_camera2)
        self.timer_camera4.timeout.connect(self.show_camera3)
        self.clicked = False

        # self.setWindowTitle(u'摄像头')
        self.frame_s=3
        '''
        # 设置背景图片
        palette1 = QPalette()
        palette1.setBrush(self.backgroundRole(), QBrush(QPixmap('background.jpg')))
        self.setPalette(palette1)
        '''






    def back_lastui(self):
        self.timer_camera1.stop()
        self.cap.release()
        self.label_show_camera.clear()
        self.timer_camera2.stop()

        self.label_show_camera1.clear()
        cam_t.close()
        ui_p.show()

    '''摄像头'''
    def button_open_camera_click(self):
        if self.timer_camera1.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)

            else:
                self.timer_camera1.start(30)

                self.button_open_camera.setText(u'关闭摄像头')
        else:
            self.timer_camera1.stop()
            self.cap.release()
            self.label_show_camera.clear()
            self.timer_camera2.stop()

            self.label_show_camera1.clear()
            self.button_open_camera.setText(u'打开摄像头')


    def show_camera(self):  #摄像头左边
        flag, self.image = self.cap.read()

        dir_path=os.getcwd()
        camera_source =dir_path+ "\\data\\test\\2.jpg"
        cv2.imwrite(camera_source, self.image)


        width = self.image.shape[1]
        height = self.image.shape[0]

        # 设置新的图片分辨率框架
        width_new = 700
        height_new = 500

        # 判断图片的长宽比率
        if width / height >= width_new / height_new:

            show = cv2.resize(self.image, (width_new, int(height * width_new / width)))
        else:

            show = cv2.resize(self.image, (int(width * height_new / height), height_new))

        show = cv2.cvtColor(show, cv2.COLOR_BGR2RGB)


        showImage = QtGui.QImage(show.data, show.shape[1], show.shape[0],3 * show.shape[1], QtGui.QImage.Format_RGB888)


        self.label_show_camera.setPixmap(QtGui.QPixmap.fromImage(showImage))

    def button_open_camera_click1(self):
        if self.timer_camera2.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)

            else:
                self.timer_camera2.start(30)
                self.button_open_camera.setText(u'关闭摄像头')
        else:
            self.timer_camera2.stop()
            self.cap.release()
            self.label_show_camera1.clear()
            self.button_open_camera.setText(u'打开摄像头')

    def show_camera1(self):
        flag, self.image = self.cap.read()


        dir_path = os.getcwd()
        camera_source = dir_path + "\\data\\test\\2.jpg"

        cv2.imwrite(camera_source, self.image)

        im0, label = main_detect(self.my_model, camera_source)


        if label=='debug':
            print("labelkong")

        width = im0.shape[1]
        height = im0.shape[0]

        # 设置新的图片分辨率框架
        width_new = 700
        height_new = 500

        # 判断图片的长宽比率
        if width / height >= width_new / height_new:

            show = cv2.resize(im0, (width_new, int(height * width_new / width)))
        else:

            show = cv2.resize(im0, (int(width * height_new / height), height_new))
        im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
        # print("debug2")

        showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)

        self.label_show_camera1.setPixmap(QtGui.QPixmap.fromImage(showImage))


    '''视频检测'''
    def open_video_button(self):


        if self.timer_camera4.isActive() == False:

            imgName, imgType = QFileDialog.getOpenFileName(self, "打开视频", "", "*.mp4;;*.AVI;;*.rmvb;;All Files(*)")

            self.cap_video = cv2.VideoCapture(imgName)

            flag = self.cap_video.isOpened()

            if flag == False:
                msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
                                                    buttons=QtWidgets.QMessageBox.Ok,
                                                    defaultButton=QtWidgets.QMessageBox.Ok)
       
            else:

                # self.timer_camera3.start(30)
                self.show_camera2()
                self.open_video.setText(u'关闭视频')
        else:
            # self.timer_camera3.stop()
            self.cap_video.release()
            self.label_show_camera.clear()
            self.timer_camera4.stop()
            self.frame_s=3
            self.label_show_camera1.clear()
            self.open_video.setText(u'打开视频')


    def detect_video(self):

        if self.timer_camera4.isActive() == False:
            flag = self.cap_video.isOpened()
            if flag == False:
                msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
                                                    buttons=QtWidgets.QMessageBox.Ok,
                                                    defaultButton=QtWidgets.QMessageBox.Ok)

            else:
                self.timer_camera4.start(30)

        else:
            self.timer_camera4.stop()
            self.cap_video.release()
            self.label_show_camera1.clear()




    def show_camera2(self):     #显示视频的左边

                  #抽帧
        length = int(self.cap_video.get(cv2.CAP_PROP_FRAME_COUNT))   #抽帧
        print(self.frame_s,length) #抽帧
        flag, self.image1 = self.cap_video.read()   #image1是视频的
        if flag == True:
            if self.frame_s%3==0:  #抽帧


                dir_path=os.getcwd()
                # print("dir_path",dir_path)
                camera_source =dir_path+ "\\data\\test\\video.jpg"

                cv2.imwrite(camera_source, self.image1)


                width=self.image1.shape[1]
                height=self.image1.shape[0]

                # 设置新的图片分辨率框架
                width_new = 700
                height_new = 500

                # 判断图片的长宽比率
                if width / height >= width_new / height_new:

                    show = cv2.resize(self.image1, (width_new, int(height * width_new / width)))
                else:

                    show = cv2.resize(self.image1, (int(width * height_new / height), height_new))


                show = cv2.cvtColor(show, cv2.COLOR_BGR2RGB)


                showImage = QtGui.QImage(show.data, show.shape[1], show.shape[0],3 * show.shape[1], QtGui.QImage.Format_RGB888)


                self.label_show_camera.setPixmap(QtGui.QPixmap.fromImage(showImage))
        else:
            self.cap_video.release()
            self.label_show_camera.clear()
            self.timer_camera4.stop()

            self.label_show_camera1.clear()
            self.open_video.setText(u'打开视频')

    def show_camera3(self):

        flag, self.image1 = self.cap_video.read()
        self.frame_s += 1
        if flag==True:
            if self.frame_s % 3 == 0:   #抽帧
                # face = self.face_detect.align(self.image)
                # if face:
                #     pass

                dir_path = os.getcwd()
                camera_source = dir_path + "\\data\\test\\video.jpg"

                cv2.imwrite(camera_source, self.image1)
                # print("im01")
                im0, label = main_detect(self.my_model, camera_source)
                # print("imo",im0)
                # print(label)
                if label=='debug':
                    print("labelkong")
                # print("debug")

                # im0, label = slef.detect()
                # print("debug1")
                width = im0.shape[1]
                height = im0.shape[0]

                # 设置新的图片分辨率框架
                width_new = 700
                height_new = 500

                # 判断图片的长宽比率
                if width / height >= width_new / height_new:

                    show = cv2.resize(im0, (width_new, int(height * width_new / width)))
                else:

                    show = cv2.resize(im0, (int(width * height_new / height), height_new))

                im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
                # print("debug2")

                showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)

                self.label_show_camera1.setPixmap(QtGui.QPixmap.fromImage(showImage))

'''单张图片检测'''
class picture(QWidget):

    def __init__(self):
        super(picture, self).__init__()

        self.str_name = '0'



        self.my_model=my_lodelmodel()
        self.resize(1600, 900)
        self.setWindowIcon(QIcon(os.getcwd() + '\\data\\source_image\\Detective.ico'))
        self.setWindowTitle("yolov5目标检测平台")



        window_pale = QtGui.QPalette()
        window_pale.setBrush(self.backgroundRole(), QtGui.QBrush(
            QtGui.QPixmap(os.getcwd() + '\\data\\source_image\\backgroud.jpg')))
        self.setPalette(window_pale)


        camera_or_video_save_path = 'data\\test'
        if not os.path.exists(camera_or_video_save_path):
            os.makedirs(camera_or_video_save_path)

        self.label1 = QLabel(self)
        self.label1.setText("   待检测图片")
        self.label1.setFixedSize(700, 500)
        self.label1.move(110, 80)

        self.label1.setStyleSheet("QLabel{background:#7A6969;}"
                                  "QLabel{color:rgb(300,300,300,120);font-size:20px;font-weight:bold;font-family:宋体;}"
                                  )
        self.label2 = QLabel(self)
        self.label2.setText("   检测结果")
        self.label2.setFixedSize(700, 500)
        self.label2.move(850, 80)

        self.label2.setStyleSheet("QLabel{background:#7A6969;}"
                                  "QLabel{color:rgb(300,300,300,120);font-size:20px;font-weight:bold;font-family:宋体;}"
                                  )

        self.label3 = QLabel(self)
        self.label3.setText("")
        self.label3.move(1200, 620)
        self.label3.setStyleSheet("font-size:20px;")
        self.label3.adjustSize()



        btn = QPushButton(self)
        btn.setText("打开图片")
        btn.setStyleSheet(''' 
                                                     QPushButton
                                                     {text-align : center;
                                                     background-color : white;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     QPushButton:pressed
                                                     {text-align : center;
                                                     background-color : light gray;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     ''')
        btn.move(10, 30)
        btn.clicked.connect(self.openimage)

        btn1 = QPushButton(self)
        btn1.setText("检测图片")
        btn1.setStyleSheet(''' 
                                                     QPushButton
                                                     {text-align : center;
                                                     background-color : white;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     QPushButton:pressed
                                                     {text-align : center;
                                                     background-color : light gray;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     ''')
        btn1.move(10, 80)
        # print("QPushButton构建")
        btn1.clicked.connect(self.button1_test)




        btn3 = QPushButton(self)
        btn3.setText("")
        btn3.setStyleSheet(''' 
                                                     QPushButton
                                                     {text-align : center;
                                                     background-color : white;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     QPushButton:pressed
                                                     {text-align : center;
                                                     background-color : light gray;
                                                     font: bold;
                                                     border-color: gray;
                                                     border-width: 2px;
                                                     border-radius: 10px;
                                                     padding: 6px;
                                                     height : 14px;
                                                     border-style: outset;
                                                     font : 14px;}
                                                     ''')
        btn3.move(10, 160)
        btn3.clicked.connect(self.camera_find)

        self.imgname1='0'


    def camera_find(self):
        ui_p.close()
        cam_t.show()


    def openimage(self):

        imgName, imgType = QFileDialog.getOpenFileName(self, "打开图片", "", "*.jpg;;*.png;;All Files(*)")

        if imgName!='':
            self.imgname1=imgName
            # print("imgName",imgName,type(imgName))
            im0=cv2.imread(imgName)

            width = im0.shape[1]
            height = im0.shape[0]

            # 设置新的图片分辨率框架
            width_new = 700
            height_new = 500

            # 判断图片的长宽比率
            if width / height >= width_new / height_new:

                show = cv2.resize(im0, (width_new, int(height * width_new / width)))
            else:

                show = cv2.resize(im0, (int(width * height_new / height), height_new))

            im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
            showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
            self.label1.setPixmap(QtGui.QPixmap.fromImage(showImage))

            # jpg = QtGui.QPixmap(imgName).scaled(self.label1.width(), self.label1.height())
            # self.label1.setPixmap(jpg)


    def button1_test(self):



        if self.imgname1!='0':
            QApplication.processEvents()
            im0,label=main_detect(self.my_model,self.imgname1)

            QApplication.processEvents()

            width = im0.shape[1]
            height = im0.shape[0]

            # 设置新的图片分辨率框架
            width_new = 700
            height_new = 500

            # 判断图片的长宽比率
            if width / height >= width_new / height_new:

                show = cv2.resize(im0, (width_new, int(height * width_new / width)))
            else:

                show = cv2.resize(im0, (int(width * height_new / height), height_new))
            im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
            image_name = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
            # label=label.split(' ')[0]    #label 59 0.96   分割字符串  取前一个
            self.label2.setPixmap(QtGui.QPixmap.fromImage(image_name))
            # jpg = QtGui.QPixmap(image_name).scaled(self.label1.width(), self.label1.height())
            # self.label2.setPixmap(jpg)
        else:
            QMessageBox.information(self, '错误', '请先选择一个图片文件', QMessageBox.Yes, QMessageBox.Yes)



if __name__ == '__main__':
    app = QApplication(sys.argv)
    splash = QSplashScreen(QPixmap(".\\data\\source_image\\logo.png"))
    # 设置画面中的文字的字体
    splash.setFont(QFont('Microsoft YaHei UI', 12))
    # 显示画面
    splash.show()
    # 显示信息
    splash.showMessage("程序初始化中... 0%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)
    time.sleep(0.3)


    splash.showMessage("正在加载模型配置文件...60%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)
    cam_t=Ui_MainWindow()
    splash.showMessage("正在加载模型配置文件...100%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)


    ui_p = picture()
    ui_p.show()
    splash.close()


    sys.exit(app.exec_())

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文件2：detect_qt5.py

import argparse
import time
from pathlib import Path

import cv2
import torch
import torch.backends.cudnn as cudnn

from models.experimental import attempt_load
from utils.datasets import LoadStreams, LoadImages
from utils.general import check_img_size, check_requirements, check_imshow, non_max_suppression, apply_classifier, \
    scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path, save_one_box
from utils.plots import colors, plot_one_box
from utils.torch_utils import select_device, load_classifier, time_synchronized


def my_lodelmodel():
    parser = argparse.ArgumentParser()
    parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
    parser.add_argument('--weights', nargs='+', type=str, default='yolov5s.pt',
                        help='model.pt path(s)')
    opt = parser.parse_args()
    device = select_device(opt.device)

    '''
    打包为exe 时候  这个select——device可能会出错，所以替换为 # device ='cuda:0'
    '''
    # device ='cuda:0'
    print("device", device)

    weights = opt.weights
    # Load model
    model = attempt_load(weights, map_location=device)  # load FP32 model
    return model

@torch.no_grad()
def detect(opt, my_model, source_open):
    source, weights, view_img, save_txt, imgsz = opt.source, opt.weights, opt.view_img, opt.save_txt, opt.img_size
    save_img = not opt.nosave and not source.endswith('.txt')  # save inference images
    webcam = source.isnumeric() or source.endswith('.txt') or source.lower().startswith(
        ('rtsp://', 'rtmp://', 'http://', 'https://'))
    label = 'debug'  #
    # Directories
    save_dir = increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok)  # increment run
    (save_dir / 'labels' if save_txt else save_dir).mkdir(parents=True, exist_ok=True)  # make dir

    # Initialize
    set_logging()
    device = select_device(opt.device)
    half = opt.half and device.type != 'cpu'  # half precision only supported on CUDA

    # Load model
    # model = attempt_load(weights, map_location=device)  # load FP32 model
    model = my_model
    stride = int(model.stride.max())  # model stride
    imgsz = check_img_size(imgsz, s=stride)  # check img_size
    names = model.module.names if hasattr(model, 'module') else model.names  # get class names
    if half:
        model.half()  # to FP16

    # Second-stage classifier
    classify = False
    if classify:
        modelc = load_classifier(name='resnet101', n=2)  # initialize
        modelc.load_state_dict(torch.load('weights/resnet101.pt', map_location=device)['model']).to(device).eval()

    # Set Dataloader
    vid_path, vid_writer = None, None
    source = source_open
    if webcam:
        view_img = check_imshow()
        cudnn.benchmark = True  # set True to speed up constant image size inference
        dataset = LoadStreams(source, img_size=imgsz, stride=stride)
    else:
        dataset = LoadImages(source, img_size=imgsz, stride=stride)

    # Run inference
    if device.type != 'cpu':
        model(torch.zeros(1, 3, imgsz, imgsz).to(device).type_as(next(model.parameters())))  # run once
    t0 = time.time()
    for path, img, im0s, vid_cap in dataset:
        img = torch.from_numpy(img).to(device)
        img = img.half() if half else img.float()  # uint8 to fp16/32
        img /= 255.0  # 0 - 255 to 0.0 - 1.0
        if img.ndimension() == 3:
            img = img.unsqueeze(0)

        # Inference
        t1 = time_synchronized()
        pred = model(img, augment=opt.augment)[0]

        # Apply NMS
        pred = non_max_suppression(pred, opt.conf_thres, opt.iou_thres, opt.classes, opt.agnostic_nms,
                                   max_det=opt.max_det)
        t2 = time_synchronized()

        # Apply Classifier
        if classify:
            pred = apply_classifier(pred, modelc, img, im0s)

        # Process detections
        for i, det in enumerate(pred):  # detections per image
            if webcam:  # batch_size >= 1
                p, s, im0, frame = path[i], f'{i}: ', im0s[i].copy(), dataset.count
            else:
                p, s, im0, frame = path, '', im0s.copy(), getattr(dataset, 'frame', 0)

            p = Path(p)  # to Path
            save_path = str(save_dir / p.name)  # img.jpg
            txt_path = str(save_dir / 'labels' / p.stem) + ('' if dataset.mode == 'image' else f'_{frame}')  # img.txt
            s += '%gx%g ' % img.shape[2:]  # print string
            gn = torch.tensor(im0.shape)[[1, 0, 1, 0]]  # normalization gain whwh
            imc = im0.copy() if opt.save_crop else im0  # for opt.save_crop
            if len(det):
                # Rescale boxes from img_size to im0 size
                det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round()

                # Print results
                for c in det[:, -1].unique():
                    n = (det[:, -1] == c).sum()  # detections per class
                    s += f"{n} {names[int(c)]}{'s' * (n > 1)}, "  # add to string

                # Write results
                for *xyxy, conf, cls in reversed(det):
                    if save_txt:  # Write to file
                        xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh
                        line = (cls, *xywh, conf) if opt.save_conf else (cls, *xywh)  # label format
                        with open(txt_path + '.txt', 'a') as f:
                            f.write(('%g ' * len(line)).rstrip() % line + '\n')

                    if save_img or opt.save_crop or view_img:  # Add bbox to image
                        c = int(cls)  # integer class
                        label = None if opt.hide_labels else (names[c] if opt.hide_conf else f'{names[c]} {conf:.2f}')
                        plot_one_box(xyxy, im0, label=label, color=colors(c, True), line_thickness=opt.line_thickness)
            #             if opt.save_crop:
            #                 save_one_box(xyxy, imc, file=save_dir / 'crops' / names[c] / f'{p.stem}.jpg', BGR=True)
            #
            # # Print time (inference + NMS)
            # print(f'{s}Done. ({t2 - t1:.3f}s)')

            # Stream results
            # if view_img:
            #     cv2.imshow(str(p), im0)
            #     cv2.waitKey(1)  # 1 millisecond

            # Save results (image with detections)
            # if save_img:
            #     if dataset.mode == 'image':
            #         cv2.imwrite(save_path, im0)
            #     else:  # 'video' or 'stream'
            #         if vid_path != save_path:  # new video
            #             vid_path = save_path
            #             if isinstance(vid_writer, cv2.VideoWriter):
            #                 vid_writer.release()  # release previous video writer
            #             if vid_cap:  # video
            #                 fps = vid_cap.get(cv2.CAP_PROP_FPS)
            #                 w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
            #                 h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
            #             else:  # stream
            #                 fps, w, h = 30, im0.shape[1], im0.shape[0]
            #                 save_path += '.mp4'
            #             vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
            #         vid_writer.write(im0)

    # if save_txt or save_img:
    #     s = f"\n{len(list(save_dir.glob('labels/*.txt')))} labels saved to {save_dir / 'labels'}" if save_txt else ''
    #     print(f"Results saved to {save_dir}{s}")

    print(f'Done. ({time.time() - t0:.3f}s)')
    return im0,label
def main_detect(my_model,source_open):
# if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--weights', nargs='+', type=str, default='yolov5s.pt', help='model.pt path(s)')
    parser.add_argument('--source', type=str, default='data/images', help='source')  # file/folder, 0 for webcam
    parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
    parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold')
    parser.add_argument('--iou-thres', type=float, default=0.45, help='IOU threshold for NMS')
    parser.add_argument('--max-det', type=int, default=1000, help='maximum number of detections per image')
    parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
    parser.add_argument('--view-img', action='store_true', help='display results')
    parser.add_argument('--save-txt', action='store_true', help='save results to *.txt')
    parser.add_argument('--save-conf', action='store_true', help='save confidences in --save-txt labels')
    parser.add_argument('--save-crop', action='store_true', help='save cropped prediction boxes')
    parser.add_argument('--nosave', action='store_true', help='do not save images/videos')
    parser.add_argument('--classes', nargs='+', type=int, help='filter by class: --class 0, or --class 0 2 3')
    parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS')
    parser.add_argument('--augment', action='store_true', help='augmented inference')
    parser.add_argument('--update', action='store_true', help='update all models')
    parser.add_argument('--project', default='runs/detect', help='save results to project/name')
    parser.add_argument('--name', default='exp', help='save results to project/name')
    parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
    parser.add_argument('--line-thickness', default=3, type=int, help='bounding box thickness (pixels)')
    parser.add_argument('--hide-labels', default=False, action='store_true', help='hide labels')
    parser.add_argument('--hide-conf', default=False, action='store_true', help='hide confidences')
    parser.add_argument('--half', action='store_true', help='use FP16 half-precision inference')
    opt = parser.parse_args()
    print(opt)


    im0, label = detect(opt, my_model, source_open)
    print("detect")
    return im0, label

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