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利用PYQT5结合YOLOX搭建检测系统_yolov8病虫害识别和pyqt5

作者：笔触狂放9 | 2024-02-27 07:24:26

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yolov8病虫害识别和pyqt5

今天给大家分享用pyqt5桌面小组件搭建一个检测系统，暂定为公共场合猫狗检测系统，检测算法为YOLOX。后续会更新YOLOv8+pyqt5教程

系统界面展示： 

该系统可以进行图片检测，实时检测，视频检测

首先创建一个.py文件复制下面代码：

  1. from PIL import Image
  2. import numpy as np
  3. import time
  4. import os
  5. from PyQt5 import QtWidgets, QtCore, QtGui
  6. from PyQt5.QtGui import *
  7. import cv2
  8. import sys
  9. from PyQt5.QtWidgets import *
  10. # from detect_qt5 import main_detect,my_lodelmodel
  11. from demo import main
  12.  
  13.  
  14. '''摄像头和视频实时检测界面'''
  15.  
  16.  
  17. class Ui_MainWindow(QWidget):
  18.     def __init__(self, parent=None):
  19.         super(Ui_MainWindow, self).__init__(parent)
  20.  
  21.         # self.face_recong = face.Recognition()
  22.         self.timer_camera1 = QtCore.QTimer()
  23.         self.timer_camera2 = QtCore.QTimer()
  24.         self.timer_camera3 = QtCore.QTimer()
  25.         self.timer_camera4 = QtCore.QTimer()
  26.         self.cap = cv2.VideoCapture()
  27.  
  28.         self.CAM_NUM = 0
  29.  
  30.         # self.slot_init()
  31.         self.__flag_work = 0
  32.         self.x = 0
  33.         self.count = 0
  34.         self.setWindowTitle("公共场合猫狗检测系统")
  35.         self.setWindowIcon(QIcon(os.getcwd() + '\\data\\source_image\\Detective.ico'))
  36.         self.setFixedSize(1600, 900)
  37.         self.yolo=main()
  38.         # self.my_model = my_lodelmodel()
  39.         self.button_open_camera = QPushButton(self)
  40.         self.button_open_camera.setText(u'打开摄像头')
  41.         self.button_open_camera.setStyleSheet(''' 
  42.                                      QPushButton
  43.                                      {text-align : center;
  44.                                      background-color : white;
  45.                                      font: bold;
  46.                                      border-color: gray;
  47.                                      border-width: 2px;
  48.                                      border-radius: 10px;
  49.                                      padding: 6px;
  50.                                      height : 14px;
  51.                                      border-style: outset;
  52.                                      font : 14px;}
  53.                                      QPushButton:pressed
  54.                                      {text-align : center;
  55.                                      background-color : light gray;
  56.                                      font: bold;
  57.                                      border-color: gray;
  58.                                      border-width: 2px;
  59.                                      border-radius: 10px;
  60.                                      padding: 6px;
  61.                                      height : 14px;
  62.                                      border-style: outset;
  63.                                      font : 14px;}
  64.                                      ''')
  65.         self.button_open_camera.move(10, 40)
  66.         self.button_open_camera.clicked.connect(self.button_open_camera_click)
  67.         # self.button_open_camera.clicked.connect(self.button_open_camera_click1)
  68.         # btn.clicked.connect(self.openimage)
  69.  
  70.         self.btn1 = QPushButton(self)
  71.         self.btn1.setText("检测摄像头")
  72.         self.btn1.setStyleSheet(''' 
  73.                                              QPushButton
  74.                                              {text-align : center;
  75.                                              background-color : white;
  76.                                              font: bold;
  77.                                              border-color: gray;
  78.                                              border-width: 2px;
  79.                                              border-radius: 10px;
  80.                                              padding: 6px;
  81.                                              height : 14px;
  82.                                              border-style: outset;
  83.                                              font : 14px;}
  84.                                              QPushButton:pressed
  85.                                              {text-align : center;
  86.                                              background-color : light gray;
  87.                                              font: bold;
  88.                                              border-color: gray;
  89.                                              border-width: 2px;
  90.                                              border-radius: 10px;
  91.                                              padding: 6px;
  92.                                              height : 14px;
  93.                                              border-style: outset;
  94.                                              font : 14px;}
  95.                                              ''')
  96.         self.btn1.move(10, 80)
  97.         self.btn1.clicked.connect(self.button_open_camera_click1)
  98.         # print("QPushButton构建")
  99.  
  100.         self.open_video = QPushButton(self)
  101.         self.open_video.setText("打开视频")
  102.         self.open_video.setStyleSheet(''' 
  103.                                              QPushButton
  104.                                              {text-align : center;
  105.                                              background-color : white;
  106.                                              font: bold;
  107.                                              border-color: gray;
  108.                                              border-width: 2px;
  109.                                              border-radius: 10px;
  110.                                              padding: 6px;
  111.                                              height : 14px;
  112.                                              border-style: outset;
  113.                                              font : 14px;}
  114.                                              QPushButton:pressed
  115.                                              {text-align : center;
  116.                                              background-color : light gray;
  117.                                              font: bold;
  118.                                              border-color: gray;
  119.                                              border-width: 2px;
  120.                                              border-radius: 10px;
  121.                                              padding: 6px;
  122.                                              height : 14px;
  123.                                              border-style: outset;
  124.                                              font : 14px;}
  125.                                              ''')
  126.         self.open_video.move(10, 160)
  127.         self.open_video.clicked.connect(self.open_video_button)
  128.         print("QPushButton构建")
  129.  
  130.         self.btn1 = QPushButton(self)
  131.         self.btn1.setText("检测视频文件")
  132.         self.btn1.setStyleSheet(''' 
  133.                                              QPushButton
  134.                                              {text-align : center;
  135.                                              background-color : white;
  136.                                              font: bold;
  137.                                              border-color: gray;
  138.                                              border-width: 2px;
  139.                                              border-radius: 10px;
  140.                                              padding: 6px;
  141.                                              height : 14px;
  142.                                              border-style: outset;
  143.                                              font : 14px;}
  144.                                              QPushButton:pressed
  145.                                              {text-align : center;
  146.                                              background-color : light gray;
  147.                                              font: bold;
  148.                                              border-color: gray;
  149.                                              border-width: 2px;
  150.                                              border-radius: 10px;
  151.                                              padding: 6px;
  152.                                              height : 14px;
  153.                                              border-style: outset;
  154.                                              font : 14px;}
  155.                                              ''')
  156.         self.btn1.move(10, 200)
  157.         self.btn1.clicked.connect(self.detect_video)
  158.         print("QPushButton构建")
  159.  
  160.         # btn1.clicked.connect(self.detect())
  161.         # btn1.clicked.connect(self.button1_test)
  162.  
  163.         # btn1.clicked.connect(self.detect())
  164.         # btn1.clicked.connect(self.button1_test)
  165.  
  166.         btn2 = QPushButton(self)
  167.         btn2.setText("返回上一界面")
  168.         btn2.setStyleSheet(''' 
  169.                                              QPushButton
  170.                                              {text-align : center;
  171.                                              background-color : white;
  172.                                              font: bold;
  173.                                              border-color: gray;
  174.                                              border-width: 2px;
  175.                                              border-radius: 10px;
  176.                                              padding: 6px;
  177.                                              height : 14px;
  178.                                              border-style: outset;
  179.                                              font : 14px;}
  180.                                              QPushButton:pressed
  181.                                              {text-align : center;
  182.                                              background-color : light gray;
  183.                                              font: bold;
  184.                                              border-color: gray;
  185.                                              border-width: 2px;
  186.                                              border-radius: 10px;
  187.                                              padding: 6px;
  188.                                              height : 14px;
  189.                                              border-style: outset;
  190.                                              font : 14px;}
  191.                                              ''')
  192.         btn2.move(10, 240)
  193.         btn2.clicked.connect(self.back_lastui)
  194.  
  195.         # 信息显示
  196.         self.label_show_camera = QLabel(self)
  197.         self.label_move = QLabel()
  198.         self.label_move.setFixedSize(100, 100)
  199.         # self.label_move.setText(" 11  待检测图片")
  200.         self.label_show_camera.setFixedSize(700, 500)
  201.         self.label_show_camera.setAutoFillBackground(True)
  202.         self.label_show_camera.move(110, 80)
  203.         self.label_show_camera.setStyleSheet("QLabel{background:#F5F5DC;}"
  204.                                              "QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
  205.                                              )
  206.         self.label_show_camera1 = QLabel(self)
  207.         self.label_show_camera1.setFixedSize(700, 500)
  208.         self.label_show_camera1.setAutoFillBackground(True)
  209.         self.label_show_camera1.move(850, 80)
  210.         self.label_show_camera1.setStyleSheet("QLabel{background:#F5F5DC;}"
  211.                                               "QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
  212.                                               )
  213.  
  214.         self.timer_camera1.timeout.connect(self.show_camera)
  215.         self.timer_camera2.timeout.connect(self.show_camera1)
  216.         # self.timer_camera3.timeout.connect(self.show_camera2)
  217.         self.timer_camera4.timeout.connect(self.show_camera2)
  218.         self.timer_camera4.timeout.connect(self.show_camera3)
  219.         self.clicked = False
  220.  
  221.         # self.setWindowTitle(u'摄像头')
  222.         self.frame_s = 3
  223.         # 设置背景图片
  224.         palette1 = QPalette()
  225.         palette1.setBrush(self.backgroundRole(), QBrush(QPixmap('R-C.png')))
  226.         self.setPalette(palette1)
  227.  
  228.     def back_lastui(self):
  229.         self.timer_camera1.stop()
  230.         self.cap.release()
  231.         self.label_show_camera.clear()
  232.         self.timer_camera2.stop()
  233.  
  234.         self.label_show_camera1.clear()
  235.         cam_t.close()
  236.         ui_p.show()
  237.  
  238.     '''摄像头'''
  239.  
  240.     def button_open_camera_click(self):
  241.         if self.timer_camera1.isActive() == False:
  242.             flag = self.cap.open(self.CAM_NUM)
  243.             if flag == False:
  244.                 msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
  245.                                                     buttons=QtWidgets.QMessageBox.Ok,
  246.                                                     defaultButton=QtWidgets.QMessageBox.Ok)
  247.  
  248.             else:
  249.                 self.timer_camera1.start(30)
  250.  
  251.                 self.button_open_camera.setText(u'关闭摄像头')
  252.         else:
  253.             self.timer_camera1.stop()
  254.             self.cap.release()
  255.             self.label_show_camera.clear()
  256.             self.timer_camera2.stop()
  257.  
  258.             self.label_show_camera1.clear()
  259.             self.button_open_camera.setText(u'打开摄像头')
  260.  
  261.     def show_camera(self):  # 摄像头左边
  262.         flag, self.image = self.cap.read()
  263.  
  264.         dir_path = os.getcwd()
  265.         camera_source = dir_path + "\\data\\test\\2.jpg"
  266.         cv2.imwrite(camera_source, self.image)
  267.  
  268.         width = self.image.shape[1]
  269.         height = self.image.shape[0]
  270.  
  271.         # 设置新的图片分辨率框架
  272.         width_new = 700
  273.         height_new = 500
  274.  
  275.         # 判断图片的长宽比率
  276.         if width / height >= width_new / height_new:
  277.  
  278.             show = cv2.resize(self.image, (width_new, int(height * width_new / width)))
  279.         else:
  280.  
  281.             show = cv2.resize(self.image, (int(width * height_new / height), height_new))
  282.  
  283.         show = cv2.cvtColor(show, cv2.COLOR_BGR2RGB)
  284.  
  285.         showImage = QtGui.QImage(show.data, show.shape[1], show.shape[0], 3 * show.shape[1], QtGui.QImage.Format_RGB888)
  286.  
  287.         self.label_show_camera.setPixmap(QtGui.QPixmap.fromImage(showImage))
  288.  
  289.     def button_open_camera_click1(self):
  290.         if self.timer_camera2.isActive() == False:
  291.             flag = self.cap.open(self.CAM_NUM)
  292.             if flag == False:
  293.                 msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
  294.                                                     buttons=QtWidgets.QMessageBox.Ok,
  295.                                                     defaultButton=QtWidgets.QMessageBox.Ok)
  296.  
  297.             else:
  298.                 self.timer_camera2.start(30)
  299.                 self.button_open_camera.setText(u'关闭摄像头')
  300.         else:
  301.             self.timer_camera2.stop()
  302.             self.cap.release()
  303.             self.label_show_camera1.clear()
  304.             self.button_open_camera.setText(u'打开摄像头')
  305.  
  306.     def show_camera1(self):
  307.         fps = 0.0
  308.         t1 = time.time()
  309.         flag, self.image = self.cap.read()
  310.         self.image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)
  311.         # self.image = Image.fromarray(np.uint8(self.image))
  312.         im0, nums, ti = self.yolo.demoimg(self.image)
  313.         im0= cv2.cvtColor(im0, cv2.COLOR_BGR2RGB)
  314.         width = im0.shape[1]
  315.         height = im0.shape[0]
  316.  
  317.         # 设置新的图片分辨率框架
  318.         width_new = 640
  319.         height_new = 640
  320.  
  321.         # 判断图片的长宽比率
  322.         if width / height >= width_new / height_new:
  323.  
  324.             show = cv2.resize(im0, (width_new, int(height * width_new / width)))
  325.         else:
  326.  
  327.             show = cv2.resize(im0, (int(width * height_new / height), height_new))
  328.         # im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
  329.         if nums>= 1:
  330.             fps = (fps + (1. / (time.time() - t1))) / 2
  331.             im0 = cv2.putText(im0, "fps= %.2f" % (fps), (0, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
  332.             im0 = cv2.putText(im0, "No pets allowed", (0, 150), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  333.  
  334.         showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
  335.  
  336.         self.label_show_camera1.setPixmap(QtGui.QPixmap.fromImage(showImage))
  337.  
  338.     '''视频检测'''
  339.  
  340.     def open_video_button(self):
  341.  
  342.         if self.timer_camera4.isActive() == False:
  343.  
  344.             imgName, imgType = QFileDialog.getOpenFileName(self, "打开视频", "", "*.mp4;;*.AVI;;*.rmvb;;All Files(*)")
  345.  
  346.             self.cap_video = cv2.VideoCapture(imgName)
  347.  
  348.             flag = self.cap_video.isOpened()
  349.  
  350.             if flag == False:
  351.                 msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
  352.                                                     buttons=QtWidgets.QMessageBox.Ok,
  353.                                                     defaultButton=QtWidgets.QMessageBox.Ok)
  354.  
  355.             else:
  356.  
  357.                 # self.timer_camera3.start(10)
  358.                 self.show_camera2()
  359.                 self.open_video.setText(u'关闭视频')
  360.         else:
  361.             # self.timer_camera3.stop()
  362.             self.cap_video.release()
  363.             self.label_show_camera.clear()
  364.             self.timer_camera4.stop()
  365.             self.frame_s = 3
  366.             self.label_show_camera1.clear()
  367.             self.open_video.setText(u'打开视频')
  368.  
  369.     def detect_video(self):
  370.  
  371.         if self.timer_camera4.isActive() == False:
  372.             flag = self.cap_video.isOpened()
  373.             if flag == False:
  374.                 msg = QtWidgets.QMessageBox.warning(self, u"Warning", u"请检测相机与电脑是否连接正确",
  375.                                                     buttons=QtWidgets.QMessageBox.Ok,
  376.                                                     defaultButton=QtWidgets.QMessageBox.Ok)
  377.  
  378.             else:
  379.                 self.timer_camera4.start(30)
  380.  
  381.         else:
  382.             self.timer_camera4.stop()
  383.             self.cap_video.release()
  384.             self.label_show_camera1.clear()
  385.  
  386.     def show_camera2(self):  # 显示视频的左边
  387.  
  388.         # 抽帧
  389.         length = int(self.cap_video.get(cv2.CAP_PROP_FRAME_COUNT))  # 抽帧
  390.         print(self.frame_s, length)  # 抽帧
  391.         flag, self.image1 = self.cap_video.read()  # image1是视频的
  392.         if flag == True:
  393.  
  394.             width = self.image1.shape[1]
  395.             height = self.image1.shape[0]
  396.  
  397.             # 设置新的图片分辨率框架
  398.             width_new = 700
  399.             height_new = 500
  400.  
  401.             # 判断图片的长宽比率
  402.             if width / height >= width_new / height_new:
  403.  
  404.                 show = cv2.resize(self.image1, (width_new, int(height * width_new / width)))
  405.             else:
  406.  
  407.                 show = cv2.resize(self.image1, (int(width * height_new / height), height_new))
  408.  
  409.             show = cv2.cvtColor(show, cv2.COLOR_BGR2RGB)
  410.  
  411.             showImage = QtGui.QImage(show.data, show.shape[1], show.shape[0], 3 * show.shape[1],
  412.                                      QtGui.QImage.Format_RGB888)
  413.  
  414.             self.label_show_camera.setPixmap(QtGui.QPixmap.fromImage(showImage))
  415.         else:
  416.             self.cap_video.release()
  417.             self.label_show_camera.clear()
  418.             self.timer_camera4.stop()
  419.  
  420.             self.label_show_camera1.clear()
  421.             self.open_video.setText(u'打开视频')
  422.  
  423.     def show_camera3(self):
  424.  
  425.         flag, self.image1 = self.cap_video.read()
  426.         self.frame_s += 1
  427.         if flag == True:
  428.             # if self.frame_s % 3 == 0:   #抽帧
  429.             # face = self.face_detect.align(self.image)
  430.             # if face:
  431.             #     pass
  432.  
  433.             # dir_path = os.getcwd()
  434.             # camera_source = dir_path + "\\data\\test\\video.jpg"
  435.             #
  436.             # cv2.imwrite(camera_source, self.image1)
  437.             # print("im01")
  438.             # im0, label = main_detect(self.my_model, camera_source)
  439.             im0,nums,ti = self.yolo.demoimg(self.image1)
  440.             # print("imo",im0)
  441.             # print(label)
  442.             # if label == 'debug':
  443.             #     print("labelkong")
  444.             # print("debug")
  445.  
  446.             # im0, label = slef.detect()
  447.             # print("debug1")
  448.             width = im0.shape[1]
  449.             height = im0.shape[0]
  450.  
  451.             # 设置新的图片分辨率框架
  452.             width_new = 700
  453.             height_new = 500
  454.  
  455.             # 判断图片的长宽比率
  456.             if width / height >= width_new / height_new:
  457.  
  458.                 show = cv2.resize(im0, (width_new, int(height * width_new / width)))
  459.             else:
  460.  
  461.                 show = cv2.resize(im0, (int(width * height_new / height), height_new))
  462.  
  463.             im0 = show#cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
  464.             # print("debug2")
  465.             if nums >= 1:
  466.                 im0 = cv2.putText(im0, "Warning", (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  467.                 im0 = cv2.putText(im0, f"nums:{nums}", (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  468.             showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
  469.  
  470.             self.label_show_camera1.setPixmap(QtGui.QPixmap.fromImage(showImage))
  471.  
  472.  
  473. '''单张图片检测'''
  474.  
  475.  
  476. class picture(QWidget):
  477.  
  478.     def __init__(self):
  479.         super(picture, self).__init__()
  480.  
  481.         self.str_name = '0'
  482.  
  483.         self.yolo = main()
  484.  
  485.         # self.my_model=my_lodelmodel()
  486.         self.resize(1600, 900)
  487.         self.setWindowIcon(QIcon(os.getcwd() + '\\data\\source_image\\Detective.ico'))
  488.         self.setWindowTitle("公共场合猫狗检测系统")
  489.  
  490.         # window_pale = QtGui.QPalette()
  491.         # window_pale.setBrush(self.backgroundRole(), QtGui.QBrush(
  492.         #     QtGui.QPixmap(os.getcwd() + '\\data\\source_image\\backgroud.jpg')))
  493.         # self.setPalette(window_pale)
  494.         palette2 = QPalette()
  495.         palette2.setBrush(self.backgroundRole(), QBrush(QPixmap('4.jpg')))
  496.         self.setPalette(palette2)
  497.  
  498.         camera_or_video_save_path = 'data\\test'
  499.         if not os.path.exists(camera_or_video_save_path):
  500.             os.makedirs(camera_or_video_save_path)
  501.  
  502.         self.label1 = QLabel(self)
  503.         self.label1.setText("   待检测图片")
  504.         self.label1.setFixedSize(700, 500)
  505.         self.label1.move(110, 80)
  506.  
  507.         self.label1.setStyleSheet("QLabel{background:#7A6969;}"
  508.                                   "QLabel{color:rgb(300,300,300,120);font-size:20px;font-weight:bold;font-family:宋体;}"
  509.                                   )
  510.         self.label2 = QLabel(self)
  511.         self.label2.setText("检测结果")
  512.         self.label2.setFixedSize(700, 500)
  513.         self.label2.move(850, 80)
  514.  
  515.         self.label2.setStyleSheet("QLabel{background:#7A6969;}"
  516.                                   "QLabel{color:rgb(300,300,300,120);font-size:20px;font-weight:bold;font-family:宋体;}"
  517.                                   )
  518.  
  519.         self.label3 = QLabel(self)
  520.         self.label3.setText("")
  521.         self.label3.move(1200, 620)
  522.         self.label3.setStyleSheet("font-size:20px;")
  523.         self.label3.adjustSize()
  524.  
  525.         btn = QPushButton(self)
  526.         btn.setText("打开图片")
  527.         btn.setStyleSheet(''' 
  528.                                                      QPushButton
  529.                                                      {text-align : center;
  530.                                                      background-color : white;
  531.                                                      font: bold;
  532.                                                      border-color: gray;
  533.                                                      border-width: 2px;
  534.                                                      border-radius: 10px;
  535.                                                      padding: 6px;
  536.                                                      height : 14px;
  537.                                                      border-style: outset;
  538.                                                      font : 14px;}
  539.                                                      QPushButton:pressed
  540.                                                      {text-align : center;
  541.                                                      background-color : light gray;
  542.                                                      font: bold;
  543.                                                      border-color: gray;
  544.                                                      border-width: 2px;
  545.                                                      border-radius: 10px;
  546.                                                      padding: 6px;
  547.                                                      height : 14px;
  548.                                                      border-style: outset;
  549.                                                      font : 14px;}
  550.                                                      ''')
  551.         btn.move(10, 30)
  552.         btn.clicked.connect(self.openimage)
  553.  
  554.         btn1 = QPushButton(self)
  555.         btn1.setText("检测图片")
  556.         btn1.setStyleSheet(''' 
  557.                                                      QPushButton
  558.                                                      {text-align : center;
  559.                                                      background-color : white;
  560.                                                      font: bold;
  561.                                                      border-color: gray;
  562.                                                      border-width: 2px;
  563.                                                      border-radius: 10px;
  564.                                                      padding: 6px;
  565.                                                      height : 14px;
  566.                                                      border-style: outset;
  567.                                                      font : 14px;}
  568.                                                      QPushButton:pressed
  569.                                                      {text-align : center;
  570.                                                      background-color : light gray;
  571.                                                      font: bold;
  572.                                                      border-color: gray;
  573.                                                      border-width: 2px;
  574.                                                      border-radius: 10px;
  575.                                                      padding: 6px;
  576.                                                      height : 14px;
  577.                                                      border-style: outset;
  578.                                                      font : 14px;}
  579.                                                      ''')
  580.         btn1.move(10, 80)
  581.         # print("QPushButton构建")
  582.         btn1.clicked.connect(self.button1_test)
  583.  
  584.         btn3 = QPushButton(self)
  585.         btn3.setText("视频和摄像头检测")
  586.         btn3.setStyleSheet(''' 
  587.                                                      QPushButton
  588.                                                      {text-align : center;
  589.                                                      background-color : white;
  590.                                                      font: bold;
  591.                                                      border-color: gray;
  592.                                                      border-width: 2px;
  593.                                                      border-radius: 10px;
  594.                                                      padding: 6px;
  595.                                                      height : 14px;
  596.                                                      border-style: outset;
  597.                                                      font : 14px;}
  598.                                                      QPushButton:pressed
  599.                                                      {text-align : center;
  600.                                                      background-color : light gray;
  601.                                                      font: bold;
  602.                                                      border-color: gray;
  603.                                                      border-width: 2px;
  604.                                                      border-radius: 10px;
  605.                                                      padding: 6px;
  606.                                                      height : 14px;
  607.                                                      border-style: outset;
  608.                                                      font : 14px;}
  609.                                                      ''')
  610.         btn3.move(10, 160)
  611.         btn3.clicked.connect(self.camera_find)
  612.  
  613.         self.imgname1 = '0'
  614.  
  615.     def camera_find(self):
  616.         ui_p.close()
  617.         cam_t.show()
  618.  
  619.     def openimage(self):
  620.  
  621.         imgName, imgType = QFileDialog.getOpenFileName(self, "打开图片", "D://",
  622.                                                        "Image files (*.jpg *.gif *.png *.jpeg)")  # "*.jpg;;*.png;;All Files(*)"
  623.         if imgName != '':
  624.             self.imgname1 = imgName
  625.             # print("imgName",imgName,type(imgName))
  626.             self.im0 = cv2.imread(imgName)
  627.             width = self.im0.shape[1]
  628.             height = self.im0.shape[0]
  629.             # 设置新的图片分辨率框架
  630.             width_new = 700
  631.             height_new = 500
  632.  
  633.             # 判断图片的长宽比率
  634.             if width / height >= width_new / height_new:
  635.  
  636.                 show = cv2.resize(self.im0, (width_new, int(height * width_new / width)))
  637.             else:
  638.  
  639.                 show = cv2.resize(self.im0, (int(width * height_new / height), height_new))
  640.             im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
  641.             showImage = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
  642.             self.label1.setPixmap(QtGui.QPixmap.fromImage(showImage))
  643.  
  644.             # jpg = QtGui.QPixmap(imgName).scaled(self.label1.width(), self.label1.height())
  645.             # self.label1.setPixmap(jpg)
  646.  
  647.     def button1_test(self):
  648.         if self.imgname1 != '0':
  649.             # QApplication.processEvents()
  650.             # image = Image.open(self.imgname1)
  651.             image = cv2.imread(self.imgname1)
  652.             # K, im0 = self.yolo.detect_image(image)
  653.             im0,nums,time=self.yolo.demoimg(image)
  654.             print(nums)
  655.             # im0 = np.array(im0)
  656.             # QApplication.processEvents()
  657.             width = im0.shape[1]
  658.             height = im0.shape[0]
  659.  
  660.             # 设置新的图片分辨率框架
  661.             width_new = 700
  662.             height_new = 700
  663.  
  664.             # 判断图片的长宽比率
  665.             if width / height >= width_new / height_new:
  666.  
  667.                 im0 = cv2.resize(im0, (width_new, int(height * width_new / width)))
  668.             else:
  669.  
  670.                 im0 = cv2.resize(im0, (int(width * height_new / height), height_new))
  671.             im0 = cv2.putText(im0, f"Infertime:{round(time,2)}s", (410, 80), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  672.             # im0 = cv2.cvtColor(show, cv2.COLOR_RGB2BGR)
  673.             if nums >= 1:
  674.                      im0 = cv2.putText(im0, "Warning", (410, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  675.                      im0 = cv2.putText(im0, f"nums:{nums}", (410, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
  676.             image_name = QtGui.QImage(im0, im0.shape[1], im0.shape[0], 3 * im0.shape[1], QtGui.QImage.Format_RGB888)
  677.             # label=label.split(' ')[0]    #label 59 0.96   分割字符串  取前一个
  678.             self.label2.setPixmap(QtGui.QPixmap.fromImage(image_name))
  679.             # jpg = QtGui.QPixmap(image_name).scaled(self.label1.width(), self.label1.height())
  680.             # self.label2.setPixmap(jpg)
  681.         else:
  682.             QMessageBox.information(self, '错误', '请先选择一个图片文件', QMessageBox.Yes, QMessageBox.Yes)
  683.  
  684.  
  685. if __name__ == '__main__':
  686.     app = QApplication(sys.argv)
  687.     splash = QSplashScreen(QPixmap(".\\data\\source_image\\logo.png"))
  688.     # 设置画面中的文字的字体
  689.     splash.setFont(QFont('Microsoft YaHei UI', 12))
  690.     # 显示画面
  691.     splash.show()
  692.     # 显示信息
  693.     splash.showMessage("程序初始化中... 0%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)
  694.     time.sleep(0.3)
  695.  
  696.     splash.showMessage("正在加载模型配置文件...60%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)
  697.     cam_t = Ui_MainWindow()
  698.     splash.showMessage("正在加载模型配置文件...100%", QtCore.Qt.AlignLeft | QtCore.Qt.AlignBottom, QtCore.Qt.black)
  699.  
  700.     ui_p = picture()
  701.     ui_p.show()
  702.     splash.close()
  703.  
  704.     sys.exit(app.exec_())

想给系统起什么名字自己更换以及背景

然后将YOLOX demo.py文件移动至根目录下，并将下面内容复制过去:

  1. import argparse
  2. import os
  3. import time
  4. from loguru import logger
  5.  
  6. import cv2
  7.  
  8. import torch
  9.  
  10. from yolox.data.data_augment import ValTransform
  11. from yolox.data.datasets import COCO_CLASSES
  12. from yolox.exp import get_exp
  13. from yolox.utils import fuse_model, get_model_info, postprocess, vis
  14.  
  15. IMAGE_EXT = [".jpg", ".jpeg", ".webp", ".bmp", ".png"]
  16.  
  17.  
  18. def make_parser():
  19.     parser = argparse.ArgumentParser("YOLOX Demo!")
  20.     parser.add_argument(
  21.         "--demo", default="image", help="demo type, eg. image, video and webcam"
  22.     )
  23.     parser.add_argument("-expn", "--experiment-name", type=str, default=None)
  24.     parser.add_argument("-n", "--name", type=str, default=None, help="model name")
  25.  
  26.     parser.add_argument(
  27.         "--path", default="./assets/dog.jpg", help="path to images or video"
  28.     )
  29.     parser.add_argument("--camid", type=int, default=0, help="webcam demo camera id")
  30.     parser.add_argument(
  31.         "--save_result",
  32.         action="store_true",
  33.         help="whether to save the inference result of image/video",
  34.     )
  35.  
  36.     # exp file
  37.     parser.add_argument(
  38.         "-f",
  39.         "--exp_file",
  40.         default='exps/default/yolox_s.py',
  41.         type=str,
  42.         help="please input your experiment description file",
  43.     )
  44.     parser.add_argument("-c", "--ckpt", default='yolox_s.pth', type=str, help="ckpt for eval")
  45.     parser.add_argument(
  46.         "--device",
  47.         default="cpu",
  48.         type=str,
  49.         help="device to run our model, can either be cpu or gpu",
  50.     )
  51.     parser.add_argument("--conf", default=0.01, type=float, help="test conf")
  52.     parser.add_argument("--nms", default=0.45, type=float, help="test nms threshold")
  53.     parser.add_argument("--tsize", default=640, type=int, help="test img size")
  54.     parser.add_argument(
  55.         "--fp16",
  56.         dest="fp16",
  57.         default=False,
  58.         action="store_true",
  59.         help="Adopting mix precision evaluating.",
  60.     )
  61.     parser.add_argument(
  62.         "--legacy",
  63.         dest="legacy",
  64.         default=False,
  65.         action="store_true",
  66.         help="To be compatible with older versions",
  67.     )
  68.     parser.add_argument(
  69.         "--fuse",
  70.         dest="fuse",
  71.         default=False,
  72.         action="store_true",
  73.         help="Fuse conv and bn for testing.",
  74.     )
  75.     parser.add_argument(
  76.         "--trt",
  77.         dest="trt",
  78.         default=False,
  79.         action="store_true",
  80.         help="Using TensorRT model for testing.",
  81.     )
  82.     return parser
  83.  
  84.  
  85. def get_image_list(path):
  86.     image_names = []
  87.     for maindir, subdir, file_name_list in os.walk(path):
  88.         for filename in file_name_list:
  89.             apath = os.path.join(maindir, filename)
  90.             ext = os.path.splitext(apath)[1]
  91.             if ext in IMAGE_EXT:
  92.                 image_names.append(apath)
  93.     return image_names
  94.  
  95.  
  96. class Predictor(object):
  97.     def __init__(
  98.         self,
  99.         model,
  100.         exp,
  101.         cls_names=COCO_CLASSES,
  102.         trt_file=None,
  103.         decoder=None,
  104.         device="cpu",
  105.         fp16=False,
  106.         legacy=False,
  107.     ):
  108.         self.model = model
  109.         self.cls_names = cls_names
  110.         self.decoder = decoder
  111.         self.num_classes = exp.num_classes
  112.         self.confthre = exp.test_conf
  113.         self.nmsthre = exp.nmsthre
  114.         self.test_size = exp.test_size
  115.         self.device = device
  116.         self.fp16 = fp16
  117.         self.preproc = ValTransform(legacy=legacy)
  118.         if trt_file is not None:
  119.             from torch2trt import TRTModule
  120.  
  121.             model_trt = TRTModule()
  122.             model_trt.load_state_dict(torch.load(trt_file))
  123.  
  124.             x = torch.ones(1, 3, exp.test_size[0], exp.test_size[1]).cuda()
  125.             self.model(x)
  126.             self.model = model_trt
  127.  
  128.     def inference(self, img):
  129.         # img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
  130.         img_info = {"id": 0}
  131.         # if isinstance(img, str):
  132.         #     img_info["file_name"] = os.path.basename(img)
  133.         #     img = cv2.imread(img)
  134.         # else:
  135.         img_info["file_name"] = None
  136.         img= cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
  137.         height, width = img.shape[:2]
  138.         img_info["height"] = height
  139.         img_info["width"] = width
  140.         img_info["raw_img"] = img
  141.  
  142.         ratio = min(self.test_size[0] / img.shape[0], self.test_size[1] / img.shape[1])
  143.         img_info["ratio"] = ratio
  144.  
  145.         img, _ = self.preproc(img, None, self.test_size)
  146.         img = torch.from_numpy(img).unsqueeze(0)
  147.         img = img.float()
  148.         if self.device == "gpu":
  149.             img = img.cuda()
  150.             if self.fp16:
  151.                 img = img.half()  # to FP16
  152.  
  153.         with torch.no_grad():
  154.             t0 = time.time()
  155.             outputs = self.model(img)
  156.             if self.decoder is not None:
  157.                 outputs = self.decoder(outputs, dtype=outputs.type())
  158.             outputs = postprocess(
  159.                 outputs, self.num_classes, self.confthre,
  160.                 self.nmsthre, class_agnostic=True
  161.             )
  162.             logger.info("Infer time: {:.4f}s".format(time.time() - t0))
  163.         return outputs, img_info,time.time() - t0
  164.  
  165.     def visual(self, output, img_info, cls_conf=0.35):
  166.         ratio = img_info["ratio"]
  167.         img = img_info["raw_img"]
  168.         if output is None:
  169.             return img,0
  170.         output = output.cpu()
  171.  
  172.         bboxes = output[:, 0:4]
  173.  
  174.         # preprocessing: resize
  175.         bboxes /= ratio
  176.  
  177.         cls = output[:, 6]
  178.         scores = output[:, 4] * output[:, 5]
  179.  
  180.         vis_res,k = vis(img, bboxes, scores, cls, cls_conf, self.cls_names)
  181.         return vis_res,k
  182.  
  183.  
  184. def image_demo(predictor,current_time,image):
  185.     # if os.path.isdir(path):
  186.     #     files = get_image_list(path)
  187.     # else:
  188.     #     files = [path]
  189.     # files.sort()
  190.     # for image_name in files:
  191.         outputs, img_info,ti = predictor.inference(image)
  192.         result_image,nums = predictor.visual(outputs[0], img_info, predictor.confthre)
  193.         return result_image,nums,ti
  194.         # if save_result:
  195.         #     save_folder = os.path.join(
  196.         #         vis_folder, time.strftime("%Y_%m_%d_%H_%M_%S", current_time)
  197.         #     )
  198.         #     os.makedirs(save_folder, exist_ok=True)
  199.         #     save_file_name = os.path.join(save_folder, os.path.basename(image_name))
  200.         #     logger.info("Saving detection result in {}".format(save_file_name))
  201.         #     cv2.imwrite(save_file_name, result_image)
  202.         # ch = cv2.waitKey(0)
  203.         # if ch == 27 or ch == ord("q") or ch == ord("Q"):
  204.         #     break
  205.  
  206.  
  207. def imageflow_demo(predictor, vis_folder, current_time, args):
  208.     # cap = cv2.VideoCapture(args.path if args.demo == "video" else args.camid)
  209.     # width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)  # float
  210.     # height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)  # float
  211.     # fps = cap.get(cv2.CAP_PROP_FPS)
  212.     # if args.save_result:
  213.     #     save_folder = os.path.join(
  214.     #         vis_folder, time.strftime("%Y_%m_%d_%H_%M_%S", current_time)
  215.     #     )
  216.     #     os.makedirs(save_folder, exist_ok=True)
  217.     #     if args.demo == "video":
  218.     #         save_path = os.path.join(save_folder, os.path.basename(args.path))
  219.     #     else:
  220.     #         save_path = os.path.join(save_folder, "camera.mp4")
  221.     #     logger.info(f"video save_path is {save_path}")
  222.     #     vid_writer = cv2.VideoWriter(
  223.     #         save_path, cv2.VideoWriter_fourcc(*"mp4v"), fps, (int(width), int(height))
  224.     #     )
  225.     while True:
  226.         ret_val, frame = cap.read()
  227.         if ret_val:
  228.             outputs, img_info = predictor.inference(frame)
  229.             result_frame = predictor.visual(outputs[0], img_info, predictor.confthre)
  230.             if args.save_result:
  231.                 vid_writer.write(result_frame)
  232.             else:
  233.                 cv2.namedWindow("yolox", cv2.WINDOW_NORMAL)
  234.                 cv2.imshow("yolox", result_frame)
  235.             ch = cv2.waitKey(1)
  236.             if ch == 27 or ch == ord("q") or ch == ord("Q"):
  237.                 break
  238.         else:
  239.             break
  240.  
  241.  
  242. class main(object):
  243.     def __init__(self):
  244.         args = make_parser().parse_args()
  245.         exp = get_exp(args.exp_file, args.name)
  246.         if not args.experiment_name:
  247.             args.experiment_name = exp.exp_name
  248.  
  249.         file_name = os.path.join(exp.output_dir, args.experiment_name)
  250.         os.makedirs(file_name, exist_ok=True)
  251.  
  252.         # vis_folder = None
  253.         # if args.save_result:
  254.         #     vis_folder = os.path.join(file_name, "vis_res")
  255.         #     os.makedirs(vis_folder, exist_ok=True)
  256.  
  257.         if args.trt:
  258.             args.device = "gpu"
  259.  
  260.         logger.info("Args: {}".format(args))
  261.  
  262.         if args.conf is not None:
  263.             exp.test_conf = args.conf
  264.         if args.nms is not None:
  265.             exp.nmsthre = args.nms
  266.         if args.tsize is not None:
  267.             exp.test_size = (args.tsize, args.tsize)
  268.  
  269.         model = exp.get_model()
  270.         logger.info("Model Summary: {}".format(get_model_info(model, exp.test_size)))
  271.  
  272.         if args.device == "gpu":
  273.             model.cuda()
  274.             if args.fp16:
  275.                 model.half()  # to FP16
  276.         model.eval()
  277.  
  278.         if not args.trt:
  279.             if args.ckpt is None:
  280.                 ckpt_file = os.path.join(file_name, "best_ckpt.pth")
  281.             else:
  282.                 ckpt_file = args.ckpt
  283.             logger.info("loading checkpoint")
  284.             ckpt = torch.load(ckpt_file, map_location="cpu")
  285.             # load the model state dict
  286.             model.load_state_dict(ckpt["model"])
  287.             logger.info("loaded checkpoint done.")
  288.  
  289.         if args.fuse:
  290.             logger.info("\tFusing model...")
  291.             model = fuse_model(model)
  292.  
  293.         if args.trt:
  294.             assert not args.fuse, "TensorRT model is not support model fusing!"
  295.             trt_file = os.path.join(file_name, "model_trt.pth")
  296.             assert os.path.exists(
  297.                 trt_file
  298.             ), "TensorRT model is not found!\n Run python3 tools/trt.py first!"
  299.             model.head.decode_in_inference = False
  300.             decoder = model.head.decode_outputs
  301.             logger.info("Using TensorRT to inference")
  302.         else:
  303.             trt_file = None
  304.             decoder = None
  305.  
  306.         self.predictor = Predictor(
  307.             model, exp, COCO_CLASSES, trt_file, decoder,
  308.             args.device, args.fp16, args.legacy,
  309.         )
  310.     def demoimg(self,img):
  311.         current_time = time.localtime()
  312.  
  313.         im=image_demo(self.predictor,current_time,img)
  314.         return im
  315.     def demovido(self,img):
  316.         imageflow_demo(predictor, img, current_time)
  317.  
  318.  
  319. if __name__ == "__main__":
  320.     args = make_parser().parse_args()
  321.     exp = get_exp(args.exp_file, args.name)
  322.  
  323.     main(exp, args)

需要的参数直接在上面改好，由于这里我没有单独训练猫狗数据集直接利用的YOLOX-s的权重文件，然后需要将索引更改为猫和狗的分类索引，更改visualize.py文件

  1. def vis(img, boxes, scores, cls_ids, conf=0.5, class_names=None):
  2.     k = 0
  3.     for i in range(len(boxes)):
  4.         box = boxes[i]
  5.         cls_id = int(cls_ids[i])
  6.         if cls_id in (15,16):
  7.             score = scores[i]
  8.             if score < conf:
  9.                 continue
  10.             k+=1
  11.             x0 = int(box[0])
  12.             y0 = int(box[1])
  13.             x1 = int(box[2])
  14.             y1 = int(box[3])
  15.  
  16.             color = (_COLORS[cls_id] * 255).astype(np.uint8).tolist()
  17.             text = '{}:{:.1f}%'.format(class_names[cls_id], score * 100)
  18.             txt_color = (0, 0, 0) if np.mean(_COLORS[cls_id]) > 0.5 else (255, 255, 255)
  19.             font = cv2.FONT_HERSHEY_SIMPLEX
  20.  
  21.             txt_size = cv2.getTextSize(text, font, 0.4, 1)[0]
  22.             cv2.rectangle(img, (x0, y0), (x1, y1), color, 2)
  23.  
  24.             txt_bk_color = (_COLORS[cls_id] * 255 * 0.7).astype(np.uint8).tolist()
  25.             cv2.rectangle(
  26.                 img,
  27.                 (x0, y0 + 1),
  28.                 (x0 + txt_size[0] + 1, y0 + int(1.5*txt_size[1])),
  29.                 txt_bk_color,
  30.                 -1
  31.             )
  32.             cv2.putText(img, text, (x0, y0 + txt_size[1]), font, 0.4, txt_color, thickness=1)
  33.  
  34.     return img,k

因为希望知道数量所以这里设置了个参数k并进行return

最后运行一下之前的pyqt5文件就可以进行检测了：

示例如下：

 

 

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