666

src/src/YOLOv8/.idea/.gitignore

@@ -0,0 +1,8 @@
+# 默认忽略的文件
+/shelf/
+/workspace.xml
+# 基于编辑器的 HTTP 客户端请求
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

src/src/YOLOv8/.idea/YOLOv8face.iml

@@ -0,0 +1,12 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="py39" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PyDocumentationSettings">
+    <option name="format" value="GOOGLE" />
+    <option name="myDocStringFormat" value="Google" />
+  </component>
+</module>

src/src/YOLOv8/.idea/inspectionProfiles/Project_Default.xml

@@ -0,0 +1,20 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="7">
+            <item index="0" class="java.lang.String" itemvalue="torch" />
+            <item index="1" class="java.lang.String" itemvalue="torchvision" />
+            <item index="2" class="java.lang.String" itemvalue="seaborn" />
+            <item index="3" class="java.lang.String" itemvalue="thop" />
+            <item index="4" class="java.lang.String" itemvalue="matplotlib" />
+            <item index="5" class="java.lang.String" itemvalue="pyqt5-tools" />
+            <item index="6" class="java.lang.String" itemvalue="ultralytics" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

src/src/YOLOv8/.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

src/src/YOLOv8/.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="py39" project-jdk-type="Python SDK" />
+</project>

src/src/YOLOv8/.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/YOLOv8face.iml" filepath="$PROJECT_DIR$/.idea/YOLOv8face.iml" />
+    </modules>
+  </component>
+</project>

src/src/YOLOv8/AppLauncher.py

@@ -0,0 +1,110 @@
+# -*- coding: utf-8 -*-
+"""
+室内多传感器寻敌系统应用启动器
+整合启动画面、欢迎界面和主程序
+从根目录启动版本
+"""
+
+import sys
+import os
+from PyQt5.QtWidgets import QApplication
+from PyQt5.QtCore import QTimer, Qt
+from PyQt5.QtGui import QIcon
+
+# 添加UIProgram目录到系统路径
+current_dir = os.path.dirname(os.path.abspath(__file__))
+ui_dir = os.path.join(current_dir, 'UIProgram')
+sys.path.append(ui_dir)
+sys.path.append(current_dir)
+
+# 导入自定义模块
+from UIProgram.SplashScreen import SplashScreen
+from UIProgram.InitialWindow import InitialWindow
+from UIProgram.ModernMainWindow import ModernMainWindow
+
+class AppLauncher:
+    """应用程序启动器"""
+    
+    def __init__(self):
+        self.app = None
+        self.splash = None
+        self.initial_window = None
+        self.main_window = None
+        
+    def run(self):
+        """运行应用程序"""
+        # 设置高DPI支持（必须在创建QApplication之前）
+        QApplication.setAttribute(Qt.AA_EnableHighDpiScaling, True)
+        QApplication.setAttribute(Qt.AA_UseHighDpiPixmaps, True)
+        
+        # 创建QApplication
+        self.app = QApplication(sys.argv)
+        self.app.setApplicationName("室内多传感器寻敌系统")
+        self.app.setApplicationVersion("2.0.0")
+        
+        # 设置应用图标
+        icon_path = "UIProgram/ui_imgs/icons/face.png"
+        if os.path.exists(icon_path):
+            self.app.setWindowIcon(QIcon(icon_path))
+        
+        # 显示启动画面
+        self.showSplashScreen()
+        
+        # 运行应用
+        sys.exit(self.app.exec_())
+        
+    def showSplashScreen(self):
+        """显示启动画面"""
+        self.splash = SplashScreen()
+        self.splash.splashFinished.connect(self.showInitialWindow)
+        self.splash.show()
+        
+    def showInitialWindow(self):
+        """显示欢迎界面"""
+        # 确保启动画面已关闭
+        if self.splash:
+            self.splash.close()
+            self.splash = None
+            
+        # 创建并显示欢迎界面
+        self.initial_window = InitialWindow()
+        self.initial_window.enterSystem.connect(self.showMainWindow)
+        self.initial_window.show()
+        
+    def showMainWindow(self):
+        """显示主程序界面"""
+        # 关闭欢迎界面
+        if self.initial_window:
+            self.initial_window.close()
+            self.initial_window = None
+            
+        # 创建并显示主程序
+        try:
+            self.main_window = ModernMainWindow()
+            self.main_window.show()
+            
+            # 确保主窗口在最前面
+            self.main_window.raise_()
+            self.main_window.activateWindow()
+            
+        except Exception as e:
+            print(f"启动主程序时出现错误: {e}")
+            # 如果主程序启动失败，提供备用方案
+            from PyQt5.QtWidgets import QMessageBox
+            msg = QMessageBox()
+            msg.setIcon(QMessageBox.Critical)
+            msg.setWindowTitle("启动错误")
+            msg.setText(f"无法启动主程序：\n{str(e)}")
+            msg.setInformativeText("请检查依赖库是否正确安装。")
+            msg.exec_()
+            
+            # 重新显示欢迎界面
+            self.showInitialWindow()
+
+def main():
+    """主函数"""
+    launcher = AppLauncher()
+    launcher.run()
+
+if __name__ == "__main__":
+    main() 

src/src/YOLOv8/CITATION.cff

@@ -0,0 +1,20 @@
+cff-version: 1.2.0
+preferred-citation:
+  type: software
+  message: If you use this software, please cite it as below.
+  authors:
+  - family-names: Jocher
+    given-names: Glenn
+    orcid: "https://orcid.org/0000-0001-5950-6979"
+  - family-names: Chaurasia
+    given-names: Ayush
+    orcid: "https://orcid.org/0000-0002-7603-6750"
+  - family-names: Qiu
+    given-names: Jing
+    orcid: "https://orcid.org/0000-0003-3783-7069"
+  title: "YOLO by Ultralytics"
+  version: 8.0.0
+  # doi: 10.5281/zenodo.3908559  # TODO
+  date-released: 2023-1-10
+  license: AGPL-3.0
+  url: "https://github.com/ultralytics/ultralytics"

src/src/YOLOv8/CameraTest.py

@@ -0,0 +1,46 @@
+#coding:utf-8
+import cv2
+from ultralytics import YOLO
+
+# 所需加载的模型目录
+path = 'models/best.pt'
+
+# Load the YOLOv8 model
+model = YOLO(path)
+
+ID = 0
+while(ID<10):
+    cap = cv2.VideoCapture(ID)
+    # get a frame
+    ret, frame = cap.read()
+    if ret == False:
+        ID += 1
+    else:
+        print('摄像头ID:',ID)
+        break
+
+# Loop through the video frames
+while cap.isOpened():
+    # Read a frame from the video
+    success, frame = cap.read()
+
+    if success:
+        # Run YOLOv8 inference on the frame
+        results = model(frame)
+
+        # Visualize the results on the frame
+        annotated_frame = results[0].plot()
+
+        # Display the annotated frame
+        cv2.imshow("YOLOv8 Inference", annotated_frame)
+
+        # Break the loop if 'q' is pressed
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    else:
+        # Break the loop if the end of the video is reached
+        break
+
+# Release the video capture object and close the display window
+cap.release()
+cv2.destroyAllWindows()

src/src/YOLOv8/Config.py

@@ -0,0 +1,9 @@
+#coding:utf-8
+
+# 图片及视频检测结果保存路径
+save_path = 'save_data'
+
+# 使用的模型路径
+model_path = 'models/best.pt'
+names = {0: 'face'}
+CH_names = ['人脸']

src/src/YOLOv8/MainProgram.py

@@ -0,0 +1,616 @@
+# -*- coding: utf-8 -*-
+import time
+from PyQt5.QtWidgets import QApplication , QMainWindow, QFileDialog, \
+    QMessageBox,QWidget,QHeaderView,QTableWidgetItem, QAbstractItemView
+import sys
+import os
+from PIL import ImageFont
+from ultralytics import YOLO
+sys.path.append('UIProgram')
+from UIProgram.UiMain import Ui_MainWindow
+import sys
+from PyQt5.QtCore import QTimer, Qt, QThread, pyqtSignal,QCoreApplication
+import detect_tools as tools
+import cv2
+import Config
+from UIProgram.QssLoader import QSSLoader
+from UIProgram.precess_bar import ProgressBar
+import numpy as np
+# import torch
+
+class MainWindow(QMainWindow):
+    def __init__(self, parent=None):
+        super(QMainWindow, self).__init__(parent)
+        self.ui = Ui_MainWindow()
+        self.ui.setupUi(self)
+        self.initMain()
+        self.signalconnect()
+
+        # 加载css渲染效果
+        style_file = 'UIProgram/style.css'
+        qssStyleSheet = QSSLoader.read_qss_file(style_file)
+        self.setStyleSheet(qssStyleSheet)
+
+    def signalconnect(self):
+        self.ui.PicBtn.clicked.connect(self.open_img)
+        self.ui.comboBox.activated.connect(self.combox_change)
+        self.ui.VideoBtn.clicked.connect(self.vedio_show)
+        self.ui.CapBtn.clicked.connect(self.camera_show)
+        self.ui.SaveBtn.clicked.connect(self.save_detect_video)
+        self.ui.ExitBtn.clicked.connect(QCoreApplication.quit)
+        self.ui.FilesBtn.clicked.connect(self.detact_batch_imgs)
+
+    def initMain(self):
+        # 更新显示区域尺寸以适配新UI
+        self.show_width = 880
+        self.show_height = 580
+
+        self.org_path = None
+
+        self.is_camera_open = False
+        self.cap = None
+
+        # self.device = 0 if torch.cuda.is_available() else 'cpu'
+
+        # 加载检测模型
+        self.model = YOLO(Config.model_path, task='detect')
+        self.model(np.zeros((48, 48, 3)))  #预先加载推理模型
+        self.fontC = ImageFont.truetype("Font/platech.ttf", 25, 0)
+
+        # 用于绘制不同颜色矩形框
+        self.colors = tools.Colors()
+
+        # 更新视频图像
+        self.timer_camera = QTimer()
+
+        # 更新检测信息表格
+        # self.timer_info = QTimer()
+        # 保存视频
+        self.timer_save_video = QTimer()
+
+        # 表格 - 更新列宽以适配新的宽屏布局
+        self.ui.tableWidget.verticalHeader().setSectionResizeMode(QHeaderView.Fixed)
+        self.ui.tableWidget.verticalHeader().setDefaultSectionSize(40)
+        self.ui.tableWidget.setColumnWidth(0, 80)  # 序号
+        self.ui.tableWidget.setColumnWidth(1, 400)  # 文件路径 - 增加宽度
+        self.ui.tableWidget.setColumnWidth(2, 150)  # 类别
+        self.ui.tableWidget.setColumnWidth(3, 120)  # 置信度
+        self.ui.tableWidget.setColumnWidth(4, 300)  # 坐标位置 - 增加宽度
+        self.ui.tableWidget.setSelectionBehavior(QAbstractItemView.SelectRows)  # 设置表格整行选中
+        self.ui.tableWidget.verticalHeader().setVisible(False)  # 隐藏列标题
+        self.ui.tableWidget.setAlternatingRowColors(True)  # 表格背景交替
+
+
+    def open_img(self):
+        if self.cap:
+            # 打开图片前关闭摄像头
+            self.video_stop()
+            self.is_camera_open = False
+            self.ui.CaplineEdit.setText('摄像头未开启')
+            self.cap = None
+
+        # 弹出的窗口名称：'打开图片'
+        # 默认打开的目录：'./'
+        # 只能打开.jpg与.gif结尾的图片文件
+        # file_path, _ = QFileDialog.getOpenFileName(self.ui.centralwidget, '打开图片', './', "Image files (*.jpg *.gif)")
+        file_path, _ = QFileDialog.getOpenFileName(None, '打开图片', './', "Image files (*.jpg *.jepg *.png)")
+        if not file_path:
+            return
+
+        self.ui.comboBox.setDisabled(False)
+        self.org_path = file_path
+        self.org_img = tools.img_cvread(self.org_path)
+
+        # 目标检测
+        t1 = time.time()
+        self.results = self.model(self.org_path)[0]
+        t2 = time.time()
+        take_time_str = '{:.3f} s'.format(t2 - t1)
+        self.ui.time_lb.setText(take_time_str)
+
+        location_list = self.results.boxes.xyxy.tolist()
+        self.location_list = [list(map(int, e)) for e in location_list]
+        cls_list = self.results.boxes.cls.tolist()
+        self.cls_list = [int(i) for i in cls_list]
+        self.conf_list = self.results.boxes.conf.tolist()
+        self.conf_list = ['%.2f %%' % (each*100) for each in self.conf_list]
+
+        # now_img = self.cv_img.copy()
+        # for loacation, type_id, conf in zip(self.location_list, self.cls_list, self.conf_list):
+        #     type_id = int(type_id)
+        #     color = self.colors(int(type_id), True)
+        #     # cv2.rectangle(now_img, (int(x1), int(y1)), (int(x2), int(y2)), colors(int(type_id), True), 3)
+        #     now_img = tools.drawRectBox(now_img, loacation, Config.CH_names[type_id], self.fontC, color)
+        now_img = self.results.plot()
+        self.draw_img = now_img
+        # 获取缩放后的图片尺寸
+        self.img_width, self.img_height = self.get_resize_size(now_img)
+        resize_cvimg = cv2.resize(now_img,(self.img_width, self.img_height))
+        pix_img = tools.cvimg_to_qpiximg(resize_cvimg)
+        self.ui.label_show.setPixmap(pix_img)
+        self.ui.label_show.setAlignment(Qt.AlignCenter)
+        # 设置路径显示
+        self.ui.PiclineEdit.setText(self.org_path)
+
+        # 目标数目
+        target_nums = len(self.cls_list)
+        self.ui.label_nums.setText(str(target_nums))
+
+        # 设置目标选择下拉框
+        choose_list = ['全部']
+        target_names = [Config.names[id]+ '_'+ str(index) for index,id in enumerate(self.cls_list)]
+        # object_list = sorted(set(self.cls_list))
+        # for each in object_list:
+        #     choose_list.append(Config.CH_names[each])
+        choose_list = choose_list + target_names
+
+        self.ui.comboBox.clear()
+        self.ui.comboBox.addItems(choose_list)
+
+        if target_nums >= 1:
+            self.ui.type_lb.setText(Config.CH_names[self.cls_list[0]])
+            self.ui.label_conf.setText(str(self.conf_list[0]))
+        #   默认显示第一个目标框坐标
+        #   设置坐标位置值
+            self.ui.label_xmin.setText(str(self.location_list[0][0]))
+            self.ui.label_ymin.setText(str(self.location_list[0][1]))
+            self.ui.label_xmax.setText(str(self.location_list[0][2]))
+            self.ui.label_ymax.setText(str(self.location_list[0][3]))
+        else:
+            self.ui.type_lb.setText('')
+            self.ui.label_conf.setText('')
+            self.ui.label_xmin.setText('')
+            self.ui.label_ymin.setText('')
+            self.ui.label_xmax.setText('')
+            self.ui.label_ymax.setText('')
+
+        # # 删除表格所有行
+        self.ui.tableWidget.setRowCount(0)
+        self.ui.tableWidget.clearContents()
+        self.tabel_info_show(self.location_list, self.cls_list, self.conf_list,path=self.org_path)
+
+
+    def detact_batch_imgs(self):
+        if self.cap:
+            # 打开图片前关闭摄像头
+            self.video_stop()
+            self.is_camera_open = False
+            self.ui.CaplineEdit.setText('摄像头未开启')
+            self.cap = None
+        directory = QFileDialog.getExistingDirectory(self,
+                                                      "选取文件夹",
+                                                      "./")  # 起始路径
+        if not  directory:
+            return
+        self.org_path = directory
+        img_suffix = ['jpg','png','jpeg','bmp']
+        for file_name in os.listdir(directory):
+            full_path = os.path.join(directory,file_name)
+            if os.path.isfile(full_path) and file_name.split('.')[-1].lower() in img_suffix:
+                # self.ui.comboBox.setDisabled(False)
+                img_path = full_path
+                self.org_img = tools.img_cvread(img_path)
+                # 目标检测
+                t1 = time.time()
+                self.results = self.model(img_path)[0]
+                t2 = time.time()
+                take_time_str = '{:.3f} s'.format(t2 - t1)
+                self.ui.time_lb.setText(take_time_str)
+
+                location_list = self.results.boxes.xyxy.tolist()
+                self.location_list = [list(map(int, e)) for e in location_list]
+                cls_list = self.results.boxes.cls.tolist()
+                self.cls_list = [int(i) for i in cls_list]
+                self.conf_list = self.results.boxes.conf.tolist()
+                self.conf_list = ['%.2f %%' % (each * 100) for each in self.conf_list]
+
+                now_img = self.results.plot()
+
+                self.draw_img = now_img
+                # 获取缩放后的图片尺寸
+                self.img_width, self.img_height = self.get_resize_size(now_img)
+                resize_cvimg = cv2.resize(now_img, (self.img_width, self.img_height))
+                pix_img = tools.cvimg_to_qpiximg(resize_cvimg)
+                self.ui.label_show.setPixmap(pix_img)
+                self.ui.label_show.setAlignment(Qt.AlignCenter)
+                # 设置路径显示
+                self.ui.PiclineEdit.setText(img_path)
+
+                # 目标数目
+                target_nums = len(self.cls_list)
+                self.ui.label_nums.setText(str(target_nums))
+
+                # 设置目标选择下拉框
+                choose_list = ['全部']
+                target_names = [Config.names[id] + '_' + str(index) for index, id in enumerate(self.cls_list)]
+                choose_list = choose_list + target_names
+
+                self.ui.comboBox.clear()
+                self.ui.comboBox.addItems(choose_list)
+
+                if target_nums >= 1:
+                    self.ui.type_lb.setText(Config.CH_names[self.cls_list[0]])
+                    self.ui.label_conf.setText(str(self.conf_list[0]))
+                    #   默认显示第一个目标框坐标
+                    #   设置坐标位置值
+                    self.ui.label_xmin.setText(str(self.location_list[0][0]))
+                    self.ui.label_ymin.setText(str(self.location_list[0][1]))
+                    self.ui.label_xmax.setText(str(self.location_list[0][2]))
+                    self.ui.label_ymax.setText(str(self.location_list[0][3]))
+                else:
+                    self.ui.type_lb.setText('')
+                    self.ui.label_conf.setText('')
+                    self.ui.label_xmin.setText('')
+                    self.ui.label_ymin.setText('')
+                    self.ui.label_xmax.setText('')
+                    self.ui.label_ymax.setText('')
+
+                # # 删除表格所有行
+                # self.ui.tableWidget.setRowCount(0)
+                # self.ui.tableWidget.clearContents()
+                self.tabel_info_show(self.location_list, self.cls_list, self.conf_list, path=img_path)
+                self.ui.tableWidget.scrollToBottom()
+                QApplication.processEvents()  #刷新页面
+
+    def draw_rect_and_tabel(self, results, img):
+        now_img = img.copy()
+        location_list = results.boxes.xyxy.tolist()
+        self.location_list = [list(map(int, e)) for e in location_list]
+        cls_list = results.boxes.cls.tolist()
+        self.cls_list = [int(i) for i in cls_list]
+        self.conf_list = results.boxes.conf.tolist()
+        self.conf_list = ['%.2f %%' % (each * 100) for each in self.conf_list]
+
+        for loacation, type_id, conf in zip(self.location_list, self.cls_list, self.conf_list):
+            type_id = int(type_id)
+            color = self.colors(int(type_id), True)
+            # cv2.rectangle(now_img, (int(x1), int(y1)), (int(x2), int(y2)), colors(int(type_id), True), 3)
+            now_img = tools.drawRectBox(now_img, loacation, Config.CH_names[type_id], self.fontC, color)
+
+        # 获取缩放后的图片尺寸
+        self.img_width, self.img_height = self.get_resize_size(now_img)
+        resize_cvimg = cv2.resize(now_img, (self.img_width, self.img_height))
+        pix_img = tools.cvimg_to_qpiximg(resize_cvimg)
+        self.ui.label_show.setPixmap(pix_img)
+        self.ui.label_show.setAlignment(Qt.AlignCenter)
+        # 设置路径显示
+        self.ui.PiclineEdit.setText(self.org_path)
+
+        # 目标数目
+        target_nums = len(self.cls_list)
+        self.ui.label_nums.setText(str(target_nums))
+        if target_nums >= 1:
+            self.ui.type_lb.setText(Config.CH_names[self.cls_list[0]])
+            self.ui.label_conf.setText(str(self.conf_list[0]))
+            self.ui.label_xmin.setText(str(self.location_list[0][0]))
+            self.ui.label_ymin.setText(str(self.location_list[0][1]))
+            self.ui.label_xmax.setText(str(self.location_list[0][2]))
+            self.ui.label_ymax.setText(str(self.location_list[0][3]))
+        else:
+            self.ui.type_lb.setText('')
+            self.ui.label_conf.setText('')
+            self.ui.label_xmin.setText('')
+            self.ui.label_ymin.setText('')
+            self.ui.label_xmax.setText('')
+            self.ui.label_ymax.setText('')
+
+        # 删除表格所有行
+        self.ui.tableWidget.setRowCount(0)
+        self.ui.tableWidget.clearContents()
+        self.tabel_info_show(self.location_list, self.cls_list, self.conf_list, path=self.org_path)
+        return now_img
+
+    def combox_change(self):
+        com_text = self.ui.comboBox.currentText()
+        if com_text == '全部':
+            cur_box = self.location_list
+            cur_img = self.results.plot()
+            self.ui.type_lb.setText(Config.CH_names[self.cls_list[0]])
+            self.ui.label_conf.setText(str(self.conf_list[0]))
+        else:
+            index = int(com_text.split('_')[-1])
+            cur_box = [self.location_list[index]]
+            cur_img = self.results[index].plot()
+            self.ui.type_lb.setText(Config.CH_names[self.cls_list[index]])
+            self.ui.label_conf.setText(str(self.conf_list[index]))
+
+        # 设置坐标位置值
+        self.ui.label_xmin.setText(str(cur_box[0][0]))
+        self.ui.label_ymin.setText(str(cur_box[0][1]))
+        self.ui.label_xmax.setText(str(cur_box[0][2]))
+        self.ui.label_ymax.setText(str(cur_box[0][3]))
+
+        resize_cvimg = cv2.resize(cur_img, (self.img_width, self.img_height))
+        pix_img = tools.cvimg_to_qpiximg(resize_cvimg)
+        self.ui.label_show.clear()
+        self.ui.label_show.setPixmap(pix_img)
+        self.ui.label_show.setAlignment(Qt.AlignCenter)
+
+
+    def get_video_path(self):
+        file_path, _ = QFileDialog.getOpenFileName(None, '打开视频', './', "Image files (*.avi *.mp4 *.jepg *.png)")
+        if not file_path:
+            return None
+        self.org_path = file_path
+        self.ui.VideolineEdit.setText(file_path)
+        return file_path
+
+    def video_start(self):
+        # 删除表格所有行
+        self.ui.tableWidget.setRowCount(0)
+        self.ui.tableWidget.clearContents()
+
+        # 清空下拉框
+        self.ui.comboBox.clear()
+
+        # 定时器开启，每隔一段时间，读取一帧
+        self.timer_camera.start(1)
+        self.timer_camera.timeout.connect(self.open_frame)
+
+    def tabel_info_show(self, locations, clses, confs, path=None):
+        path = path
+        for location, cls, conf in zip(locations, clses, confs):
+            row_count = self.ui.tableWidget.rowCount()  # 返回当前行数(尾部)
+            self.ui.tableWidget.insertRow(row_count)  # 尾部插入一行
+            item_id = QTableWidgetItem(str(row_count+1))  # 序号
+            item_id.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)  # 设置文本居中
+            item_path = QTableWidgetItem(str(path))  # 路径
+            # item_path.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)
+
+            item_cls = QTableWidgetItem(str(Config.CH_names[cls]))
+            item_cls.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)  # 设置文本居中
+
+            item_conf = QTableWidgetItem(str(conf))
+            item_conf.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)  # 设置文本居中
+
+            item_location = QTableWidgetItem(str(location)) # 目标框位置
+            # item_location.setTextAlignment(Qt.AlignHCenter | Qt.AlignVCenter)  # 设置文本居中
+
+            self.ui.tableWidget.setItem(row_count, 0, item_id)
+            self.ui.tableWidget.setItem(row_count, 1, item_path)
+            self.ui.tableWidget.setItem(row_count, 2, item_cls)
+            self.ui.tableWidget.setItem(row_count, 3, item_conf)
+            self.ui.tableWidget.setItem(row_count, 4, item_location)
+        self.ui.tableWidget.scrollToBottom()
+
+    def video_stop(self):
+        self.cap.release()
+        self.timer_camera.stop()
+        # self.timer_info.stop()
+
+    def open_frame(self):
+        ret, now_img = self.cap.read()
+        if ret:
+            # 目标检测
+            t1 = time.time()
+            results = self.model(now_img)[0]
+            t2 = time.time()
+            take_time_str = '{:.3f} s'.format(t2 - t1)
+            self.ui.time_lb.setText(take_time_str)
+
+            location_list = results.boxes.xyxy.tolist()
+            self.location_list = [list(map(int, e)) for e in location_list]
+            cls_list = results.boxes.cls.tolist()
+            self.cls_list = [int(i) for i in cls_list]
+            self.conf_list = results.boxes.conf.tolist()
+            self.conf_list = ['%.2f %%' % (each * 100) for each in self.conf_list]
+
+            now_img = results.plot()
+
+            # 获取缩放后的图片尺寸
+            self.img_width, self.img_height = self.get_resize_size(now_img)
+            resize_cvimg = cv2.resize(now_img, (self.img_width, self.img_height))
+            pix_img = tools.cvimg_to_qpiximg(resize_cvimg)
+            self.ui.label_show.setPixmap(pix_img)
+            self.ui.label_show.setAlignment(Qt.AlignCenter)
+
+            # 目标数目
+            target_nums = len(self.cls_list)
+            self.ui.label_nums.setText(str(target_nums))
+
+            # 设置目标选择下拉框
+            choose_list = ['全部']
+            target_names = [Config.names[id] + '_' + str(index) for index, id in enumerate(self.cls_list)]
+            # object_list = sorted(set(self.cls_list))
+            # for each in object_list:
+            #     choose_list.append(Config.CH_names[each])
+            choose_list = choose_list + target_names
+
+            self.ui.comboBox.clear()
+            self.ui.comboBox.addItems(choose_list)
+
+            if target_nums >= 1:
+                self.ui.type_lb.setText(Config.CH_names[self.cls_list[0]])
+                self.ui.label_conf.setText(str(self.conf_list[0]))
+                #   默认显示第一个目标框坐标
+                #   设置坐标位置值
+                self.ui.label_xmin.setText(str(self.location_list[0][0]))
+                self.ui.label_ymin.setText(str(self.location_list[0][1]))
+                self.ui.label_xmax.setText(str(self.location_list[0][2]))
+                self.ui.label_ymax.setText(str(self.location_list[0][3]))
+            else:
+                self.ui.type_lb.setText('')
+                self.ui.label_conf.setText('')
+                self.ui.label_xmin.setText('')
+                self.ui.label_ymin.setText('')
+                self.ui.label_xmax.setText('')
+                self.ui.label_ymax.setText('')
+
+
+            # 删除表格所有行
+            # self.ui.tableWidget.setRowCount(0)
+            # self.ui.tableWidget.clearContents()
+            self.tabel_info_show(self.location_list, self.cls_list, self.conf_list, path=self.org_path)
+
+        else:
+            self.cap.release()
+            self.timer_camera.stop()
+
+    def vedio_show(self):
+        if self.is_camera_open:
+            self.is_camera_open = False
+            self.ui.CaplineEdit.setText('摄像头未开启')
+
+        video_path = self.get_video_path()
+        if not video_path:
+            return None
+        self.cap = cv2.VideoCapture(video_path)
+        self.video_start()
+        self.ui.comboBox.setDisabled(True)
+
+    def camera_show(self):
+        self.is_camera_open = not self.is_camera_open
+        if self.is_camera_open:
+            self.ui.CaplineEdit.setText('摄像头开启')
+            self.cap = cv2.VideoCapture(0)
+            self.video_start()
+            self.ui.comboBox.setDisabled(True)
+        else:
+            self.ui.CaplineEdit.setText('摄像头未开启')
+            self.ui.label_show.setText('')
+            if self.cap:
+                self.cap.release()
+                cv2.destroyAllWindows()
+            self.ui.label_show.clear()
+
+    def get_resize_size(self, img):
+        _img = img.copy()
+        img_height, img_width , depth= _img.shape
+        ratio = img_width / img_height
+        if ratio >= self.show_width / self.show_height:
+            self.img_width = self.show_width
+            self.img_height = int(self.img_width / ratio)
+        else:
+            self.img_height = self.show_height
+            self.img_width = int(self.img_height * ratio)
+        return self.img_width, self.img_height
+
+    def save_detect_video(self):
+        if self.cap is None and not self.org_path:
+            QMessageBox.about(self, '提示', '当前没有可保存信息，请先打开图片或视频！')
+            return
+
+        if self.is_camera_open:
+            QMessageBox.about(self, '提示', '摄像头视频无法保存!')
+            return
+
+        if self.cap:
+            res = QMessageBox.information(self, '提示', '保存视频检测结果可能需要较长时间，请确认是否继续保存？',QMessageBox.Yes | QMessageBox.No ,  QMessageBox.Yes)
+            if res == QMessageBox.Yes:
+                self.video_stop()
+                com_text = self.ui.comboBox.currentText()
+                self.btn2Thread_object = btn2Thread(self.org_path, self.model, com_text)
+                self.btn2Thread_object.start()
+                self.btn2Thread_object.update_ui_signal.connect(self.update_process_bar)
+            else:
+                return
+        else:
+            if os.path.isfile(self.org_path):
+                fileName = os.path.basename(self.org_path)
+                name , end_name= fileName.rsplit(".",1)
+                save_name = name + '_detect_result.' + end_name
+                save_img_path = os.path.join(Config.save_path, save_name)
+                # 保存图片
+                cv2.imwrite(save_img_path, self.draw_img)
+                QMessageBox.about(self, '提示', '图片保存成功!\n文件路径:{}'.format(save_img_path))
+            else:
+                img_suffix = ['jpg', 'png', 'jpeg', 'bmp']
+                for file_name in os.listdir(self.org_path):
+                    full_path = os.path.join(self.org_path, file_name)
+                    if os.path.isfile(full_path) and file_name.split('.')[-1].lower() in img_suffix:
+                        name, end_name = file_name.rsplit(".",1)
+                        save_name = name + '_detect_result.' + end_name
+                        save_img_path = os.path.join(Config.save_path, save_name)
+                        results = self.model(full_path)[0]
+                        now_img = results.plot()
+                        # 保存图片
+                        cv2.imwrite(save_img_path, now_img)
+
+                QMessageBox.about(self, '提示', '图片保存成功!\n文件路径:{}'.format(Config.save_path))
+
+
+    def update_process_bar(self,cur_num, total):
+        if cur_num == 1:
+            self.progress_bar = ProgressBar(self)
+            self.progress_bar.show()
+        if cur_num >= total:
+            self.progress_bar.close()
+            QMessageBox.about(self, '提示', '视频保存成功!\n文件在{}目录下'.format(Config.save_path))
+            return
+        if self.progress_bar.isVisible() is False:
+            # 点击取消保存时，终止进程
+            self.btn2Thread_object.stop()
+            return
+        value = int(cur_num / total *100)
+        self.progress_bar.setValue(cur_num, total, value)
+        QApplication.processEvents()
+
+
+class btn2Thread(QThread):
+    """
+    进行检测后的视频保存
+    """
+    # 声明一个信号
+    update_ui_signal = pyqtSignal(int,int)
+
+    def __init__(self, path, model, com_text):
+        super(btn2Thread, self).__init__()
+        self.org_path = path
+        self.model = model
+        self.com_text = com_text
+        # 用于绘制不同颜色矩形框
+        self.colors = tools.Colors()
+        self.is_running = True  # 标志位，表示线程是否正在运行
+
+    def run(self):
+        # VideoCapture方法是cv2库提供的读取视频方法
+        cap = cv2.VideoCapture(self.org_path)
+        # 设置需要保存视频的格式“xvid”
+        # 该参数是MPEG-4编码类型，文件名后缀为.avi
+        fourcc = cv2.VideoWriter_fourcc(*'XVID')
+        # 设置视频帧频
+        fps = cap.get(cv2.CAP_PROP_FPS)
+        # 设置视频大小
+        size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
+        # VideoWriter方法是cv2库提供的保存视频方法
+        # 按照设置的格式来out输出
+        fileName = os.path.basename(self.org_path)
+        name, end_name = fileName.split('.')
+        save_name = name + '_detect_result.avi'
+        save_video_path = os.path.join(Config.save_path, save_name)
+        out = cv2.VideoWriter(save_video_path, fourcc, fps, size)
+
+        prop = cv2.CAP_PROP_FRAME_COUNT
+        total = int(cap.get(prop))
+        print("[INFO] 视频总帧数：{}".format(total))
+        cur_num = 0
+
+        # 确定视频打开并循环读取
+        while (cap.isOpened() and self.is_running):
+            cur_num += 1
+            print('当前第{}帧，总帧数{}'.format(cur_num, total))
+            # 逐帧读取，ret返回布尔值
+            # 参数ret为True 或者False,代表有没有读取到图片
+            # frame表示截取到一帧的图片
+            ret, frame = cap.read()
+            if ret == True:
+                # 检测
+                results = self.model(frame)[0]
+                frame = results.plot()
+                out.write(frame)
+                self.update_ui_signal.emit(cur_num, total)
+            else:
+                break
+        # 释放资源
+        cap.release()
+        out.release()
+
+    def stop(self):
+        self.is_running = False
+
+
+if __name__ == "__main__":
+    app = QApplication(sys.argv)
+    win = MainWindow()
+    win.show()
+    sys.exit(app.exec_())

src/src/YOLOv8/UIProgram/BattleMapTools.py

@@ -0,0 +1,851 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+"""
+室内多传感器寻敌系统 - 作战地图工具
+===============================
+
+提供作战地图显示和标绘功能，支持在地图上进行标绘操作
+
+功能特性：
+- 支持导入地图图片（PNG、JPG等格式）
+- 支持自由绘制线条，多种颜色和线宽
+- 支持标记敌人位置（红色圆圈）
+- 支持标记人质位置（蓝色圆圈）
+- 支持清除和撤销操作
+- 支持保存标绘结果
+
+作者: 郭晋鹏团队
+版本: 2.0.0
+"""
+
+from PyQt5.QtWidgets import (QWidget, QPushButton, QColorDialog, QSlider, QLabel, 
+                            QHBoxLayout, QVBoxLayout, QFileDialog, QMessageBox, 
+                            QButtonGroup, QFrame, QSizePolicy)
+from PyQt5.QtCore import Qt, QPoint, QRect, QSize
+from PyQt5.QtGui import QPainter, QPen, QColor, QPixmap, QPainterPath, QImage, QBrush, QIcon, QFont
+
+import cv2
+import numpy as np
+import sys
+import os
+
+# 确保可以从任何位置导入
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+class MapDrawingArea(QWidget):
+    """
+    地图绘图区域类
+    
+    提供一个可以进行地图标绘的区域，支持多种绘制工具和操作
+    
+    主要属性:
+        drawing: 是否正在绘制
+        last_point: 上一个绘制点
+        current_point: 当前绘制点
+        pixmap: 绘制的图像
+        temp_pixmap: 临时绘制的图像
+        history: 历史记录，用于撤销操作
+        scale_factor: 缩放因子
+        
+    主要方法:
+        loadMap: 加载地图图片
+        setDrawingTool: 设置绘图工具
+        setDrawingColor: 设置绘图颜色
+        setLineWidth: 设置线宽
+        undo: 撤销操作
+        clear: 清除所有绘制
+        getImage: 获取绘制后的图像
+        zoomIn: 放大地图
+        zoomOut: 缩小地图
+    """
+    
+    # 绘图工具枚举
+    TOOL_PEN = 0      # 自由绘制
+    TOOL_ENEMY = 1    # 标记敌人
+    TOOL_HOSTAGE = 2  # 标记人质
+    TOOL_ERASER = 3   # 橡皮擦
+    
+    # 符号尺寸
+    SYMBOL_SIZE = 20
+    
+    # 缩放设置
+    MIN_SCALE = 0.1   # 最小缩放比例
+    MAX_SCALE = 5.0   # 最大缩放比例
+    ZOOM_FACTOR = 1.2 # 每次缩放的比例
+    
+    def __init__(self, parent=None):
+        """初始化地图绘图区域"""
+        super().__init__(parent)
+        
+        # 初始化绘图属性
+        self.drawing = False
+        self.last_point = QPoint()
+        self.current_point = QPoint()
+        self.pixmap = QPixmap()
+        self.temp_pixmap = QPixmap()
+        self.original_pixmap = QPixmap()  # 保存原始图像
+        self.history = []
+        self.has_map = False
+        
+        # 缩放和平移属性
+        self.scale_factor = 1.0
+        self.offset = QPoint(0, 0)
+        self.panning = False
+        self.pan_start_pos = QPoint()
+        
+        # 绘图设置
+        self.drawing_tool = self.TOOL_PEN
+        self.pen_color = QColor(0, 255, 0)  # 默认绿色
+        self.pen_width = 3
+        
+        # 敌人和人质标记颜色
+        self.enemy_color = QColor(255, 0, 0)    # 红色
+        self.hostage_color = QColor(0, 0, 255)  # 蓝色
+        
+        # 橡皮擦设置
+        self.eraser_size = 20
+        
+        # 设置鼠标跟踪
+        self.setMouseTracking(True)
+        
+        # 设置焦点策略，使其能接收键盘事件
+        self.setFocusPolicy(Qt.StrongFocus)
+        
+        # 创建空白图像
+        self.createEmptyMap()
+        
+    def createEmptyMap(self):
+        """创建空白地图"""
+        self.pixmap = QPixmap(800, 600)
+        self.pixmap.fill(Qt.white)
+        self.history = [self.pixmap.copy()]
+        self.has_map = False
+        self.update()
+        
+    def loadMap(self, file_path=None):
+        """
+        加载地图图片
+        
+        参数:
+            file_path: 图片文件路径，如果为None则弹出文件选择对话框
+        
+        返回:
+            bool: 是否成功加载地图
+        """
+        if file_path is None:
+            file_path, _ = QFileDialog.getOpenFileName(
+                self, '导入地图', './', 
+                "图像文件 (*.jpg *.jpeg *.png *.bmp)"
+            )
+            
+        if not file_path:
+            return False
+            
+        try:
+            # 加载原始图片
+            original_pixmap = QPixmap(file_path)
+            if original_pixmap.isNull():
+                QMessageBox.warning(self, "错误", "无法加载地图文件")
+                return False
+            
+            # 保存原始图片
+            self.original_pixmap = original_pixmap.copy()
+            
+            # 重置缩放和偏移
+            self.scale_factor = 1.0
+            self.offset = QPoint(0, 0)
+            
+            # 适配图像大小到窗口
+            self.fitToView()
+            
+            # 保存初始状态到历史记录
+            self.history = [self.pixmap.copy()]
+            self.has_map = True
+            
+            # 更新界面
+            self.update()
+            return True
+            
+        except Exception as e:
+            QMessageBox.warning(self, "错误", f"加载地图失败: {str(e)}")
+            return False
+            
+    def fitToView(self):
+        """适配图像大小到当前视图"""
+        if self.original_pixmap.isNull():
+            return
+            
+        # 获取父窗口大小（如果有）
+        parent_size = self.parentWidget().size() if self.parentWidget() else self.size()
+        
+        # 计算适合的缩放比例
+        width_ratio = (parent_size.width() - 40) / self.original_pixmap.width()
+        height_ratio = (parent_size.height() - 40) / self.original_pixmap.height()
+        
+        # 选择较小的比例，确保图像完全可见
+        self.scale_factor = min(width_ratio, height_ratio, 1.0)
+        
+        # 缩放图像
+        self.updateScaledPixmap()
+        
+    def updateScaledPixmap(self):
+        """根据当前缩放因子更新缩放后的图像"""
+        if self.original_pixmap.isNull():
+            return
+            
+        # 计算缩放后的尺寸
+        new_width = int(self.original_pixmap.width() * self.scale_factor)
+        new_height = int(self.original_pixmap.height() * self.scale_factor)
+        
+        # 缩放图像
+        self.pixmap = self.original_pixmap.scaled(
+            new_width, new_height, 
+            Qt.KeepAspectRatio, 
+            Qt.SmoothTransformation
+        )
+        
+        # 设置最小尺寸
+        self.setMinimumSize(new_width, new_height)
+        
+        # 更新界面
+        self.update()
+        
+    def zoomIn(self):
+        """放大地图"""
+        if self.scale_factor < self.MAX_SCALE:
+            self.scale_factor *= self.ZOOM_FACTOR
+            self.updateScaledPixmap()
+            
+    def zoomOut(self):
+        """缩小地图"""
+        if self.scale_factor > self.MIN_SCALE:
+            self.scale_factor /= self.ZOOM_FACTOR
+            self.updateScaledPixmap()
+            
+    def setDrawingTool(self, tool):
+        """设置绘图工具"""
+        self.drawing_tool = tool
+        
+    def setDrawingColor(self, color):
+        """设置绘图颜色"""
+        self.pen_color = color
+        
+    def setLineWidth(self, width):
+        """设置线宽"""
+        self.pen_width = width
+        
+    def undo(self):
+        """撤销上一步操作"""
+        if len(self.history) > 1:
+            self.history.pop()
+            self.pixmap = self.history[-1].copy()
+            self.update()
+            
+    def clear(self):
+        """清除所有绘制，恢复到初始状态"""
+        if self.history:
+            self.pixmap = self.history[0].copy()
+            self.history = [self.pixmap.copy()]
+            self.update()
+            
+    def getImage(self):
+        """获取绘制后的图像（QPixmap格式）"""
+        return self.pixmap.copy()
+    
+    def saveImage(self, filename=None):
+        """
+        保存绘制后的图像到文件
+        
+        参数:
+            filename: 文件路径，如果为None则弹出文件选择对话框
+            
+        返回:
+            bool: 是否成功保存
+        """
+        if filename is None:
+            filename, _ = QFileDialog.getSaveFileName(
+                self, "保存地图标绘", "./", 
+                "PNG图像 (*.png);;JPEG图像 (*.jpg);;所有文件 (*.*)"
+            )
+            
+        if filename:
+            return self.pixmap.save(filename)
+        return False
+        
+    def paintEvent(self, event):
+        """绘制事件处理"""
+        painter = QPainter(self)
+        painter.setRenderHint(QPainter.Antialiasing)
+        painter.setRenderHint(QPainter.SmoothPixmapTransform)
+        
+        # 绘制背景
+        painter.fillRect(self.rect(), QColor(40, 40, 40))
+        
+        # 绘制底图（居中显示）
+        if not self.pixmap.isNull():
+            # 计算居中位置
+            x = (self.width() - self.pixmap.width()) // 2 + self.offset.x()
+            y = (self.height() - self.pixmap.height()) // 2 + self.offset.y()
+            painter.drawPixmap(x, y, self.pixmap)
+            
+        # 绘制临时内容（如拖动中的形状）
+        if self.drawing and not self.temp_pixmap.isNull():
+            x = (self.width() - self.temp_pixmap.width()) // 2 + self.offset.x()
+            y = (self.height() - self.temp_pixmap.height()) // 2 + self.offset.y()
+            painter.drawPixmap(x, y, self.temp_pixmap)
+            
+    def wheelEvent(self, event):
+        """鼠标滚轮事件处理"""
+        if self.has_map:
+            # 获取滚轮方向
+            delta = event.angleDelta().y()
+            
+            # 根据滚轮方向缩放
+            if delta > 0:
+                self.zoomIn()  # 放大
+            else:
+                self.zoomOut()  # 缩小
+                
+            # 阻止事件传播
+            event.accept()
+            
+    def mousePressEvent(self, event):
+        """鼠标按下事件处理"""
+        if event.button() == Qt.LeftButton:
+            # 计算图像坐标系中的点击位置
+            img_pos = self._mapToImagePos(event.pos())
+            
+            # 检查点击是否在图像范围内
+            if self._isPointInImage(img_pos):
+                if event.modifiers() & Qt.ControlModifier:
+                    # 按住Ctrl键进行平移
+                    self.panning = True
+                    self.pan_start_pos = event.pos()
+                else:
+                    # 正常绘制
+                    self.drawing = True
+                    self.last_point = img_pos
+                    
+                    # 对于敌人和人质标记，直接在点击位置绘制符号
+                    if self.drawing_tool == self.TOOL_ENEMY:
+                        self._drawSymbol(img_pos, self.enemy_color)
+                        
+                    elif self.drawing_tool == self.TOOL_HOSTAGE:
+                        self._drawSymbol(img_pos, self.hostage_color)
+                
+    def mouseMoveEvent(self, event):
+        """鼠标移动事件处理"""
+        if self.panning:
+            # 平移地图
+            delta = event.pos() - self.pan_start_pos
+            self.offset += delta
+            self.pan_start_pos = event.pos()
+            self.update()
+        elif self.drawing:
+            # 计算图像坐标系中的当前位置
+            img_pos = self._mapToImagePos(event.pos())
+            
+            # 检查是否在图像范围内
+            if self._isPointInImage(img_pos):
+                self.current_point = img_pos
+                
+                if self.drawing_tool == self.TOOL_PEN:
+                    # 自由绘制，直接在pixmap上绘制
+                    painter = QPainter(self.pixmap)
+                    painter.setPen(QPen(self.pen_color, self.pen_width, Qt.SolidLine, Qt.RoundCap, Qt.RoundJoin))
+                    painter.drawLine(self.last_point, self.current_point)
+                    painter.end()
+                    
+                    # 更新上一个点
+                    self.last_point = self.current_point
+                    
+                elif self.drawing_tool == self.TOOL_ERASER:
+                    # 橡皮擦，绘制白色圆形
+                    painter = QPainter(self.pixmap)
+                    painter.setPen(Qt.NoPen)
+                    painter.setBrush(QBrush(Qt.white))
+                    painter.drawEllipse(self.current_point, self.eraser_size, self.eraser_size)
+                    painter.end()
+                    
+                    # 更新上一个点
+                    self.last_point = self.current_point
+                    
+                # 更新界面
+                self.update()
+            
+    def mouseReleaseEvent(self, event):
+        """鼠标释放事件处理"""
+        if event.button() == Qt.LeftButton:
+            if self.panning:
+                self.panning = False
+            elif self.drawing:
+                self.drawing = False
+                
+                # 保存到历史记录
+                self.history.append(self.pixmap.copy())
+                
+            # 更新界面
+            self.update()
+            
+    def _mapToImagePos(self, pos):
+        """将窗口坐标映射到图像坐标"""
+        # 计算图像左上角在窗口中的位置
+        x_offset = (self.width() - self.pixmap.width()) // 2 + self.offset.x()
+        y_offset = (self.height() - self.pixmap.height()) // 2 + self.offset.y()
+        
+        # 计算相对于图像左上角的坐标
+        return QPoint(pos.x() - x_offset, pos.y() - y_offset)
+        
+    def _isPointInImage(self, pos):
+        """检查点是否在图像范围内"""
+        return (0 <= pos.x() < self.pixmap.width() and 
+                0 <= pos.y() < self.pixmap.height())
+            
+    def _drawSymbol(self, position, color):
+        """
+        绘制符号（敌人或人质标记）
+        
+        参数:
+            position: 符号位置
+            color: 符号颜色
+        """
+        try:
+            painter = QPainter(self.pixmap)
+            painter.setRenderHint(QPainter.Antialiasing)  # 抗锯齿
+            
+            # 设置画笔
+            pen = QPen(color, 3, Qt.SolidLine)
+            painter.setPen(pen)
+            
+            # 设置画刷 - 半透明填充
+            brush = QBrush(QColor(color.red(), color.green(), color.blue(), 80))
+            painter.setBrush(brush)
+            
+            # 符号尺寸
+            size = self.SYMBOL_SIZE
+            
+            # 绘制外圆
+            painter.drawEllipse(position, size, size)
+            
+            # 绘制内圆
+            painter.setBrush(QBrush(QColor(color.red(), color.green(), color.blue(), 150)))
+            painter.drawEllipse(position, int(size/2), int(size/2))
+            
+            # 绘制十字线 - 确保使用整数坐标
+            painter.setPen(QPen(Qt.white, 2, Qt.SolidLine))
+            x1 = int(position.x() - size/2)
+            y1 = int(position.y())
+            x2 = int(position.x() + size/2)
+            y2 = int(position.y())
+            painter.drawLine(x1, y1, x2, y2)
+            
+            x1 = int(position.x())
+            y1 = int(position.y() - size/2)
+            x2 = int(position.x())
+            y2 = int(position.y() + size/2)
+            painter.drawLine(x1, y1, x2, y2)
+            
+            # 添加文字标签
+            if color == self.enemy_color:
+                text = "敌"
+            elif color == self.hostage_color:
+                text = "质"
+            else:
+                text = ""
+                
+            if text:
+                painter.setPen(Qt.white)
+                font = QFont("Arial", 10)
+                font.setBold(True)
+                painter.setFont(font)
+                painter.drawText(int(position.x() - 7), int(position.y() + 5), text)
+            
+            painter.end()
+            
+            # 保存到历史记录
+            self.history.append(self.pixmap.copy())
+            
+            # 更新界面
+            self.update()
+            
+        except Exception as e:
+            print(f"绘制符号错误: {e}")
+            # 如果出错，确保painter被结束
+            if painter.isActive():
+                painter.end()
+
+
+class BattleMapToolbar(QWidget):
+    """
+    作战地图工具栏类
+    
+    提供地图操作、绘图工具选择、颜色选择等功能
+    
+    主要属性:
+        map_area: 关联的地图绘图区域
+        
+    主要方法:
+        setupUI: 设置用户界面
+        connectSignals: 连接信号和槽
+    """
+    
+    def __init__(self, map_area, parent=None):
+        """
+        初始化作战地图工具栏
+        
+        参数:
+            map_area: 关联的地图绘图区域
+            parent: 父窗口
+        """
+        super().__init__(parent)
+        self.map_area = map_area
+        self.setupUI()
+        self.connectSignals()
+        
+    def setupUI(self):
+        """设置用户界面"""
+        # 主布局
+        main_layout = QVBoxLayout(self)
+        main_layout.setContentsMargins(5, 5, 5, 5)
+        main_layout.setSpacing(5)
+        
+        # 地图操作布局
+        map_layout = QHBoxLayout()
+        
+        # 导入地图按钮
+        self.import_map_btn = QPushButton("📷 导入地图")
+        self.import_map_btn.setFixedSize(100, 30)
+        
+        # 清除地图按钮
+        self.clear_map_btn = QPushButton("🗑️ 清除地图")
+        self.clear_map_btn.setFixedSize(100, 30)
+        
+        # 保存地图按钮
+        self.save_map_btn = QPushButton("💾 保存地图")
+        self.save_map_btn.setFixedSize(100, 30)
+        
+        # 撤销按钮
+        self.undo_btn = QPushButton("↩️ 撤销")
+        self.undo_btn.setFixedSize(80, 30)
+        
+        # 将按钮添加到地图操作布局
+        map_layout.addWidget(self.import_map_btn)
+        map_layout.addWidget(self.clear_map_btn)
+        map_layout.addWidget(self.save_map_btn)
+        map_layout.addWidget(self.undo_btn)
+        map_layout.addStretch()
+        
+        # 工具选择布局
+        tools_layout = QHBoxLayout()
+        
+        # 创建工具按钮组
+        self.tools_group = QButtonGroup(self)
+        
+        # 笔刷工具按钮
+        self.pen_btn = QPushButton("✏️ 笔刷")
+        self.pen_btn.setCheckable(True)
+        self.pen_btn.setChecked(True)
+        self.pen_btn.setFixedSize(80, 30)
+        self.tools_group.addButton(self.pen_btn, MapDrawingArea.TOOL_PEN)
+        
+        # 标记敌人按钮
+        self.enemy_btn = QPushButton("🔴 敌人")
+        self.enemy_btn.setCheckable(True)
+        self.enemy_btn.setFixedSize(80, 30)
+        self.tools_group.addButton(self.enemy_btn, MapDrawingArea.TOOL_ENEMY)
+        
+        # 标记人质按钮
+        self.hostage_btn = QPushButton("🔵 人质")
+        self.hostage_btn.setCheckable(True)
+        self.hostage_btn.setFixedSize(80, 30)
+        self.tools_group.addButton(self.hostage_btn, MapDrawingArea.TOOL_HOSTAGE)
+        
+        # 橡皮擦按钮
+        self.eraser_btn = QPushButton("🧽 橡皮擦")
+        self.eraser_btn.setCheckable(True)
+        self.eraser_btn.setFixedSize(80, 30)
+        self.tools_group.addButton(self.eraser_btn, MapDrawingArea.TOOL_ERASER)
+        
+        # 将按钮添加到工具布局
+        tools_layout.addWidget(self.pen_btn)
+        tools_layout.addWidget(self.enemy_btn)
+        tools_layout.addWidget(self.hostage_btn)
+        tools_layout.addWidget(self.eraser_btn)
+        
+        # 添加分隔符
+        separator = QFrame()
+        separator.setFrameShape(QFrame.VLine)
+        separator.setFrameShadow(QFrame.Sunken)
+        separator.setStyleSheet("background-color: rgba(150, 150, 150, 0.5);")
+        separator.setFixedSize(1, 25)
+        tools_layout.addWidget(separator)
+        
+        # 缩放按钮
+        self.zoom_in_btn = QPushButton("🔍+")
+        self.zoom_in_btn.setFixedSize(40, 30)
+        self.zoom_in_btn.setToolTip("放大地图")
+        
+        self.zoom_out_btn = QPushButton("🔍-")
+        self.zoom_out_btn.setFixedSize(40, 30)
+        self.zoom_out_btn.setToolTip("缩小地图")
+        
+        self.fit_view_btn = QPushButton("🔍⟲")
+        self.fit_view_btn.setFixedSize(40, 30)
+        self.fit_view_btn.setToolTip("适应窗口大小")
+        
+        tools_layout.addWidget(self.zoom_in_btn)
+        tools_layout.addWidget(self.zoom_out_btn)
+        tools_layout.addWidget(self.fit_view_btn)
+        tools_layout.addStretch()
+        
+        # 颜色和线宽布局
+        settings_layout = QHBoxLayout()
+        
+        # 颜色选择按钮
+        self.color_btn = QPushButton("🎨 颜色")
+        self.color_btn.setFixedSize(80, 30)
+        
+        # 颜色预览
+        self.color_preview = QLabel()
+        self.color_preview.setFixedSize(30, 30)
+        self.color_preview.setStyleSheet("background-color: #00FF00; border: 1px solid black;")
+        
+        # 线宽标签
+        self.width_label = QLabel("线宽:")
+        self.width_label.setStyleSheet("color: white;")
+        
+        # 线宽滑动条
+        self.width_slider = QSlider(Qt.Horizontal)
+        self.width_slider.setMinimum(1)
+        self.width_slider.setMaximum(20)
+        self.width_slider.setValue(3)
+        self.width_slider.setFixedWidth(100)
+        
+        # 线宽数值显示
+        self.width_value = QLabel("3")
+        self.width_value.setStyleSheet("color: white;")
+        self.width_value.setFixedWidth(20)
+        
+        # 将控件添加到设置布局
+        settings_layout.addWidget(self.color_btn)
+        settings_layout.addWidget(self.color_preview)
+        settings_layout.addWidget(self.width_label)
+        settings_layout.addWidget(self.width_slider)
+        settings_layout.addWidget(self.width_value)
+        settings_layout.addStretch()
+        
+        # 将所有布局添加到主布局
+        main_layout.addLayout(map_layout)
+        main_layout.addLayout(tools_layout)
+        main_layout.addLayout(settings_layout)
+        
+        # 设置样式
+        self.setStyleSheet("""
+            QPushButton {
+                background: rgba(60, 60, 60, 0.8);
+                color: white;
+                font-size: 12px;
+                border: 1px solid rgba(100, 100, 100, 0.8);
+                border-radius: 5px;
+            }
+            QPushButton:hover {
+                background: rgba(80, 80, 80, 1.0);
+                border: 1px solid rgba(150, 150, 150, 1.0);
+            }
+            QPushButton:checked {
+                background: rgba(0, 120, 215, 0.8);
+                border: 1px solid rgba(0, 150, 255, 1.0);
+            }
+            QLabel {
+                color: white;
+                font-size: 12px;
+            }
+            QSlider::groove:horizontal {
+                height: 8px;
+                background: rgba(80, 80, 80, 0.8);
+                border-radius: 4px;
+            }
+            QSlider::handle:horizontal {
+                background: rgba(0, 120, 215, 0.8);
+                border: 1px solid rgba(0, 150, 255, 1.0);
+                width: 18px;
+                margin: -5px 0;
+                border-radius: 9px;
+            }
+        """)
+        
+        # 设置工具提示
+        self.import_map_btn.setToolTip("导入地图图片文件")
+        self.clear_map_btn.setToolTip("清除当前标绘内容")
+        self.save_map_btn.setToolTip("保存标绘结果")
+        self.undo_btn.setToolTip("撤销上一步操作")
+        self.pen_btn.setToolTip("自由绘制工具")
+        self.enemy_btn.setToolTip("标记敌人位置")
+        self.hostage_btn.setToolTip("标记人质位置")
+        self.eraser_btn.setToolTip("橡皮擦工具")
+        self.color_btn.setToolTip("选择绘制颜色")
+        
+    def connectSignals(self):
+        """连接信号和槽"""
+        # 地图操作按钮信号 - 这些信号将由BattleMapWidget处理
+        # self.import_map_btn.clicked.connect(self.map_area.loadMap)
+        # self.clear_map_btn.clicked.connect(self.map_area.clear)
+        # self.save_map_btn.clicked.connect(self.map_area.saveImage)
+        self.undo_btn.clicked.connect(self.map_area.undo)
+        
+        # 工具按钮组信号
+        self.tools_group.buttonClicked.connect(self._onToolButtonClicked)
+        
+        # 颜色按钮信号
+        self.color_btn.clicked.connect(self._onColorButtonClicked)
+        
+        # 线宽滑动条信号
+        self.width_slider.valueChanged.connect(self._onWidthChanged)
+        
+        # 缩放按钮信号
+        self.zoom_in_btn.clicked.connect(self.map_area.zoomIn)
+        self.zoom_out_btn.clicked.connect(self.map_area.zoomOut)
+        self.fit_view_btn.clicked.connect(self.map_area.fitToView)
+        
+    def _onToolButtonClicked(self, button):
+        """工具按钮点击处理"""
+        tool_id = self.tools_group.id(button)
+        self.map_area.setDrawingTool(tool_id)
+        
+    def _onColorButtonClicked(self):
+        """颜色按钮点击处理"""
+        color = QColorDialog.getColor(self.map_area.pen_color, self, "选择颜色")
+        if color.isValid():
+            self.map_area.setDrawingColor(color)
+            self.color_preview.setStyleSheet(f"background-color: {color.name()}; border: 1px solid black;")
+            
+    def _onWidthChanged(self, value):
+        """线宽改变处理"""
+        self.map_area.setLineWidth(value)
+        self.width_value.setText(str(value))
+
+
+class BattleMapWidget(QWidget):
+    """
+    作战地图组件类
+    
+    集成地图显示和工具栏，提供完整的作战地图功能
+    
+    主要属性:
+        map_area: 地图绘图区域
+        toolbar: 工具栏
+        
+    主要方法:
+        setupUI: 设置用户界面
+        loadMap: 加载地图
+        saveMap: 保存地图
+    """
+    
+    def __init__(self, parent=None):
+        """
+        初始化作战地图组件
+        
+        参数:
+            parent: 父窗口
+        """
+        super().__init__(parent)
+        self.setupUI()
+        
+    def setupUI(self):
+        """设置用户界面"""
+        # 主布局
+        main_layout = QVBoxLayout(self)
+        main_layout.setContentsMargins(0, 0, 0, 0)
+        main_layout.setSpacing(0)
+        
+        # 创建标题区域
+        title_frame = QFrame()
+        title_frame.setFixedHeight(50)
+        title_frame.setStyleSheet("background: rgba(30, 30, 30, 0.7);")
+        title_layout = QHBoxLayout(title_frame)
+        title_layout.setContentsMargins(20, 5, 20, 5)
+        
+        # 标题标签
+        title_label = QLabel("作战地图标绘系统")
+        title_label.setStyleSheet("""
+            color: #FFD700;
+            font-size: 18px;
+            font-weight: bold;
+        """)
+        
+        # 状态标签
+        self.status_label = QLabel("准备就绪")
+        self.status_label.setStyleSheet("""
+            color: #00FF00;
+            font-size: 12px;
+        """)
+        
+        title_layout.addWidget(title_label)
+        title_layout.addStretch()
+        title_layout.addWidget(self.status_label)
+        
+        # 创建地图绘图区域
+        self.map_area = MapDrawingArea()
+        
+        # 创建工具栏
+        self.toolbar = BattleMapToolbar(self.map_area)
+        
+        # 创建滚动区域容器
+        map_container = QFrame()
+        map_container.setStyleSheet("background: rgba(40, 40, 40, 0.5);")
+        map_container_layout = QVBoxLayout(map_container)
+        map_container_layout.setContentsMargins(10, 10, 10, 10)
+        map_container_layout.addWidget(self.map_area)
+        
+        # 将工具栏和地图区域添加到主布局
+        main_layout.addWidget(title_frame)
+        main_layout.addWidget(self.toolbar)
+        main_layout.addWidget(map_container, 1)  # 1表示拉伸因子
+        
+        # 连接信号
+        self.toolbar.import_map_btn.clicked.connect(self._onMapLoaded)
+        self.toolbar.save_map_btn.clicked.connect(self._onMapSaved)
+        self.toolbar.clear_map_btn.clicked.connect(self._onMapCleared)
+        
+    def _onMapLoaded(self):
+        """地图加载回调"""
+        if self.map_area.loadMap():
+            self.status_label.setText("地图已加载")
+            self.status_label.setStyleSheet("color: #00FF00; font-size: 12px;")
+        
+    def _onMapSaved(self):
+        """地图保存回调"""
+        if self.map_area.saveImage():
+            self.status_label.setText("地图已保存")
+            self.status_label.setStyleSheet("color: #00FF00; font-size: 12px;")
+            
+    def _onMapCleared(self):
+        """地图清除回调"""
+        self.map_area.clear()
+        self.status_label.setText("地图已清除")
+        self.status_label.setStyleSheet("color: #FFA500; font-size: 12px;")
+        
+    def loadMap(self, file_path=None):
+        """
+        加载地图
+        
+        参数:
+            file_path: 图片文件路径，如果为None则弹出文件选择对话框
+            
+        返回:
+            bool: 是否成功加载地图
+        """
+        return self.map_area.loadMap(file_path)
+        
+    def saveMap(self, file_path=None):
+        """
+        保存地图
+        
+        参数:
+            file_path: 文件路径，如果为None则弹出文件选择对话框
+            
+        返回:
+            bool: 是否成功保存
+        """
+        return self.map_area.saveImage(file_path) 

src/src/YOLOv8/UIProgram/InitialWindow.py

@@ -0,0 +1,287 @@
+# -*- coding: utf-8 -*-
+"""
+室内多传感器寻敌系统欢迎界面
+===============================
+
+欢迎界面模块，启动画面后显示的系统介绍页面
+
+功能特性：
+- 显示系统欢迎信息和介绍
+- 提供"进入系统"按钮
+- 支持窗口拖拽移动
+- 自定义关闭按钮
+- 智能背景图片加载
+- 响应式布局设计
+
+窗口尺寸: 600x400
+背景图片: BA.png (自动缩放适配)
+
+交互功能：
+- 点击"进入系统"按钮进入主程序
+- 支持拖拽移动窗口
+- 点击关闭按钮退出程序
+
+作者: 郭晋鹏团队
+版本: 2.0.0
+"""
+
+from PyQt5.QtWidgets import QWidget, QVBoxLayout, QHBoxLayout, QLabel, QPushButton, QFrame, QApplication
+from PyQt5.QtCore import Qt, pyqtSignal, QPropertyAnimation, QEasingCurve, QTimer
+from PyQt5.QtGui import QPixmap, QPainter, QLinearGradient, QBrush, QPen, QFont, QColor, QMouseEvent
+import os
+
+class InitialWindow(QWidget):
+    """
+    欢迎界面窗口类
+    
+    继承自QWidget，提供系统介绍和进入功能。
+    支持拖拽移动和自定义样式。
+    
+    信号：
+        enterSystem: 进入系统信号，用于通知启动主程序
+        
+    属性：
+        drag_start_position: 拖拽起始位置
+        is_dragging (bool): 是否正在拖拽窗口
+    """
+    
+    # 进入系统信号
+    enterSystem = pyqtSignal()
+    
+    def __init__(self, parent=None):
+        """
+        初始化欢迎界面
+        
+        参数：
+            parent: 父窗口，默认为None
+        """
+        super().__init__(parent)
+        self.drag_start_position = None  # 拖拽起始位置
+        self.is_dragging = False  # 拖拽状态标志
+        self.setupUI()  # 设置用户界面
+        
+    def setupUI(self):
+        """设置用户界面"""
+        # 设置窗口属性 - 缩小到一半
+        self.setFixedSize(600, 400)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        
+        # 主布局
+        main_layout = QVBoxLayout(self)
+        main_layout.setContentsMargins(0, 0, 0, 0)
+        main_layout.setSpacing(0)
+        
+        # 创建背景标签（全屏背景） - 调整为新尺寸
+        self.background_label = QLabel(self)
+        self.background_label.setGeometry(0, 0, 600, 400)
+        
+        # 加载BA.png作为背景并缩放填充
+        # 智能路径查找
+        def find_image_path(image_name):
+            possible_paths = [
+                image_name,
+                os.path.join("UIProgram", image_name),
+                os.path.join("..", "UIProgram", image_name) if os.path.basename(os.getcwd()) == "UIProgram" else os.path.join("UIProgram", image_name)
+            ]
+            for path in possible_paths:
+                if os.path.exists(path):
+                    return path
+            return image_name
+            
+        bg_path = find_image_path("ui_imgs/icons/BA.png")
+        if os.path.exists(bg_path):
+            pixmap = QPixmap(bg_path)
+            if not pixmap.isNull():
+                scaled_pixmap = pixmap.scaled(600, 400, Qt.KeepAspectRatioByExpanding, Qt.SmoothTransformation)
+                self.background_label.setPixmap(scaled_pixmap)
+                self.background_label.setScaledContents(False)
+                self.background_label.setAlignment(Qt.AlignCenter)
+        
+        # 确保背景在最底层
+        self.background_label.lower()
+        
+        # 主框架（透明，用于布局）
+        self.background_frame = QFrame()
+        self.background_frame.setObjectName("backgroundFrame")
+        self.background_frame.setStyleSheet("background: transparent;")
+        main_layout.addWidget(self.background_frame)
+        
+        # 背景框架布局
+        bg_layout = QVBoxLayout(self.background_frame)
+        bg_layout.setContentsMargins(50, 50, 50, 50)
+        bg_layout.setSpacing(30)
+        
+        # 创建自定义关闭按钮 - 调整位置
+        self.close_btn = QPushButton("×", self)
+        self.close_btn.setFixedSize(30, 30)
+        self.close_btn.move(600 - 40, 10)
+        self.close_btn.setObjectName("closeButton")
+        self.close_btn.clicked.connect(self.close)
+        
+        # 移除Logo区域，只保留背景图片
+        
+        # 添加弹性空间
+        bg_layout.addStretch()
+        
+        # 欢迎文字
+        self.welcome_label = QLabel("欢迎指挥官")
+        self.welcome_label.setAlignment(Qt.AlignCenter)
+        self.welcome_label.setObjectName("welcomeLabel")
+        bg_layout.addWidget(self.welcome_label)
+        
+        # 系统描述
+        self.desc_label = QLabel("室内多传感器寻敌系统")
+        self.desc_label.setAlignment(Qt.AlignCenter)
+        self.desc_label.setObjectName("descLabel")
+        bg_layout.addWidget(self.desc_label)
+        
+        # 版本信息
+        self.version_label = QLabel("智能识别 • 精准定位 • 实时检测")
+        self.version_label.setAlignment(Qt.AlignCenter)
+        self.version_label.setObjectName("versionLabel")
+        bg_layout.addWidget(self.version_label)
+        
+        # 按钮区域 - 按照UI文件的样式
+        button_layout = QHBoxLayout()
+        button_layout.addStretch()
+        
+        self.enter_btn = QPushButton("进入系统")
+        self.enter_btn.setFixedSize(150, 40)  # 缩小到一半
+        self.enter_btn.setObjectName("enterSystemButton")
+        self.enter_btn.clicked.connect(self.onEnterSystem)
+        button_layout.addWidget(self.enter_btn)
+        
+        button_layout.addStretch()
+        bg_layout.addLayout(button_layout)
+        
+        # 底部空间
+        bg_layout.addStretch()
+        
+        # 底部信息
+        self.bottom_label = QLabel("© 2025 室内多传感器寻敌系统")
+        self.bottom_label.setAlignment(Qt.AlignCenter)
+        self.bottom_label.setObjectName("bottomLabel")
+        bg_layout.addWidget(self.bottom_label)
+        
+        # 设置样式
+        self.setStyles()
+        
+        # 居中显示
+        self.centerWindow()
+        
+    def setStyles(self):
+        """设置样式"""
+        # 按照UI文件的样式设计
+        self.setStyleSheet("""
+            InitialWindow {
+                background: transparent;
+            }
+            
+            #welcomeLabel {
+                color: #FFD700;
+                font-size: 36px;
+                font-weight: bold;
+                font-family: 'Impact', 'Arial Black', sans-serif;
+
+                background: rgba(0, 0, 0, 0.3);
+                border-radius: 15px;
+                padding: 30px;
+                border: 2px solid rgba(255, 215, 0, 0.6);
+            }
+            
+            QLabel#descLabel {
+                color: rgba(255, 255, 255, 200);
+                font-size: 24px;
+                font-weight: normal;
+                background: transparent;
+                margin: 10px;
+            }
+            
+            QLabel#versionLabel {
+                color: rgba(76, 175, 80, 255);
+                font-size: 16px;
+                font-weight: normal;
+                background: transparent;
+                margin: 10px;
+            }
+            
+            QLabel#bottomLabel {
+                color: rgba(255, 255, 255, 120);
+                font-size: 12px;
+                background: transparent;
+                margin: 10px;
+            }
+            
+            #enterSystemButton {
+                background: qlineargradient(x1:0, y1:0, x2:0, y2:1, 
+                    stop:0 rgba(255, 69, 0, 0.9), stop:1 rgba(220, 20, 60, 0.9));
+                color: #FFFFFF;
+                font-size: 12px;
+                font-weight: bold;
+                font-family: 'Arial Black', sans-serif;
+                border: 3px solid rgba(255, 255, 255, 0.8);
+                border-radius: 15px;
+            }
+            
+            #enterSystemButton:hover {
+                background: qlineargradient(x1:0, y1:0, x2:0, y2:1, 
+                    stop:0 rgba(255, 99, 71, 1.0), stop:1 rgba(255, 69, 0, 1.0));
+                border: 3px solid rgba(255, 215, 0, 1.0);
+            }
+            
+            #enterSystemButton:pressed {
+                background: qlineargradient(x1:0, y1:0, x2:0, y2:1, 
+                    stop:0 rgba(178, 34, 34, 0.9), stop:1 rgba(139, 0, 0, 0.9));
+            }
+            
+            #closeButton {
+                background: rgba(220, 20, 60, 0.8);
+                color: white;
+                font-size: 14px;
+                font-weight: bold;
+                border: 2px solid rgba(255, 255, 255, 0.6);
+                border-radius: 20px;
+            }
+            
+            #closeButton:hover {
+                background: rgba(255, 69, 0, 1.0);
+                border: 2px solid rgba(255, 215, 0, 1.0);
+            }
+            
+            #closeButton:pressed {
+                background: rgba(139, 0, 0, 1.0);
+            }
+        """)
+        
+    def centerWindow(self):
+        """窗口居中显示"""
+        screen = QApplication.desktop().screenGeometry()
+        x = (screen.width() - self.width()) // 2
+        y = (screen.height() - self.height()) // 2
+        self.move(x, y)
+        
+    def onEnterSystem(self):
+        """进入系统按钮点击"""
+        self.enterSystem.emit()
+        self.close()
+        
+    def mousePressEvent(self, event: QMouseEvent):
+        """鼠标按下事件"""
+        if event.button() == Qt.LeftButton and self.isDraggableArea(event.pos()):
+            self.is_dragging = True
+            self.drag_start_position = event.globalPos() - self.pos()
+            
+    def mouseMoveEvent(self, event: QMouseEvent):
+        """鼠标移动事件"""
+        if self.is_dragging and event.buttons() == Qt.LeftButton:
+            self.move(event.globalPos() - self.drag_start_position)
+            
+    def mouseReleaseEvent(self, event: QMouseEvent):
+        """鼠标释放事件"""
+        self.is_dragging = False
+        
+    def isDraggableArea(self, pos):
+        """判断是否在可拖动区域"""
+        # 除了按钮区域外都可以拖动
+        return not (self.enter_btn.geometry().contains(pos) or 
+                   self.close_btn.geometry().contains(pos)) 

src/src/YOLOv8/UIProgram/SplashScreen.py

@@ -0,0 +1,251 @@
+# -*- coding: utf-8 -*-
+"""
+室内多传感器寻敌系统启动画面
+===============================
+
+启动画面模块，提供优雅的应用程序启动体验
+
+功能特性：
+- 显示系统名称和版本信息
+- 模拟加载进度动画
+- 动态状态提示文字
+- 自动进度更新
+- 支持半透明背景效果
+- 智能图片路径查找
+
+窗口尺寸: 250x175 (紧凑型设计)
+显示时长: 约5秒 (100个进度步骤，每步50ms)
+
+作者: 郭晋鹏团队
+版本: 2.0.0
+"""
+
+from PyQt5.QtWidgets import QSplashScreen, QLabel, QProgressBar, QVBoxLayout, QWidget
+from PyQt5.QtCore import QTimer, Qt, pyqtSignal, QPropertyAnimation, QEasingCurve
+from PyQt5.QtGui import QPixmap, QPainter, QLinearGradient, QBrush, QPen, QFont, QColor
+import os
+
+class SplashScreen(QSplashScreen):
+    """
+    启动画面窗口类
+    
+    继承自QSplashScreen，提供应用程序启动时的欢迎界面。
+    包含进度条、状态文字、系统信息等元素。
+    
+    信号：
+        splashFinished: 启动完成信号，用于通知主程序继续执行
+        
+    属性：
+        current_progress (int): 当前加载进度 (0-100)
+        progress_timer (QTimer): 进度更新定时器
+    """
+    
+    # 启动完成信号
+    splashFinished = pyqtSignal()
+    
+    def __init__(self, parent=None):
+        """
+        初始化启动画面
+        
+        参数：
+            parent: 父窗口，默认为None
+        """
+        super().__init__(parent)
+        self.current_progress = 0  # 初始化进度为0
+        self.setupUI()  # 设置用户界面
+        self.startAnimation()  # 启动加载动画
+    
+    def setupUI(self):
+        """
+        设置用户界面
+        
+        创建启动画面的所有UI元素，包括：
+        - 系统标题和版本信息
+        - 状态提示标签
+        - 进度条
+        - 背景图片和视觉效果
+        """
+        # 设置窗口属性 - 缩小到一半
+        self.setFixedSize(250, 175)
+        self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
+        self.setAttribute(Qt.WA_TranslucentBackground)
+        
+        # 创建主widget和布局
+        main_widget = QWidget()
+        layout = QVBoxLayout(main_widget)
+        layout.setContentsMargins(10, 10, 10, 10)
+        layout.setSpacing(5)
+        
+        # 标题标签
+        self.title_label = QLabel("室内多传感器寻敌系统")
+        self.title_label.setAlignment(Qt.AlignCenter)
+        self.title_label.setStyleSheet("""
+            QLabel {
+                color: white;
+                font-size: 14px;
+                font-weight: bold;
+                background: transparent;
+            }
+        """)
+        layout.addWidget(self.title_label)
+        
+        # 版本标签
+        self.version_label = QLabel("版本 2.0.0")
+        self.version_label.setAlignment(Qt.AlignCenter)
+        self.version_label.setStyleSheet("""
+            QLabel {
+                color: rgba(255, 255, 255, 180);
+                font-size: 10px;
+                background: transparent;
+            }
+        """)
+        layout.addWidget(self.version_label)
+        
+        # 添加弹性空间
+        layout.addStretch()
+        
+        # 状态标签
+        self.status_label = QLabel("正在初始化...")
+        self.status_label.setAlignment(Qt.AlignCenter)
+        self.status_label.setStyleSheet("""
+            QLabel {
+                color: rgba(255, 255, 255, 200);
+                font-size: 9px;
+                background: transparent;
+            }
+        """)
+        layout.addWidget(self.status_label)
+        
+        # 进度条
+        self.progress_bar = QProgressBar()
+        self.progress_bar.setRange(0, 100)
+        self.progress_bar.setValue(0)
+        self.progress_bar.setFixedHeight(4)
+        self.progress_bar.setStyleSheet("""
+            QProgressBar {
+                background-color: rgba(255, 255, 255, 30);
+                border: 1px solid rgba(255, 255, 255, 50);
+                border-radius: 2px;
+                text-align: center;
+            }
+            
+            QProgressBar::chunk {
+                background: qlineargradient(x1: 0, y1: 0, x2: 1, y2: 0,
+                           stop: 0 #4CAF50, stop: 1 #2196F3);
+                border-radius: 1px;
+            }
+        """)
+        layout.addWidget(self.progress_bar)
+        
+        # 创建背景图片 - 调整为新尺寸
+        background_pixmap = QPixmap(250, 175)
+        background_pixmap.fill(Qt.transparent)
+        
+        painter = QPainter(background_pixmap)
+        painter.setRenderHint(QPainter.Antialiasing)
+        painter.setRenderHint(QPainter.SmoothPixmapTransform)
+        
+        # 加载loading.png作为背景并缩放填充
+        # 智能路径查找
+        def find_image_path(image_name):
+            possible_paths = [
+                image_name,
+                os.path.join("UIProgram", image_name),
+                os.path.join("..", "UIProgram", image_name) if os.path.basename(os.getcwd()) == "UIProgram" else os.path.join("UIProgram", image_name)
+            ]
+            for path in possible_paths:
+                if os.path.exists(path):
+                    return path
+            return image_name
+            
+        loading_bg_path = find_image_path("ui_imgs/icons/loading.png")
+        if os.path.exists(loading_bg_path):
+            loading_image = QPixmap(loading_bg_path)
+            if not loading_image.isNull():
+                # 按比例缩放并填充整个区域
+                scaled_image = loading_image.scaled(250, 175, Qt.KeepAspectRatioByExpanding, Qt.SmoothTransformation)
+                painter.drawPixmap(0, 0, 250, 175, scaled_image)
+        
+        # 绘制半透明遮罩层，使文字更清晰
+        painter.setBrush(QBrush(QColor(0, 0, 0, 80)))
+        painter.setPen(Qt.NoPen)
+        painter.drawRoundedRect(0, 0, 250, 175, 8, 8)
+        
+        # 绘制边框
+        painter.setPen(QPen(QColor(116, 185, 255), 1))
+        painter.setBrush(Qt.NoBrush)
+        painter.drawRoundedRect(1, 1, 248, 173, 8, 8)
+        
+        painter.end()
+        self.setPixmap(background_pixmap)
+        
+        # 将主widget设置为layout
+        main_widget.setParent(self)
+        main_widget.setGeometry(0, 0, 250, 175)
+        main_widget.setStyleSheet("background: transparent;")
+        
+    def startAnimation(self):
+        """
+        启动动画效果
+        
+        创建并启动进度更新定时器，每50毫秒更新一次进度。
+        整个启动过程约持续5秒钟。
+        """
+        # 进度更新定时器
+        self.progress_timer = QTimer()
+        self.progress_timer.timeout.connect(self.updateProgress)
+        self.progress_timer.start(50)  # 50ms更新一次
+        
+    def updateProgress(self):
+        """
+        更新加载进度
+        
+        定时器回调函数，负责：
+        - 更新进度条数值
+        - 根据进度显示不同的状态文字
+        - 检查是否完成加载并触发结束信号
+        """
+        self.current_progress += 1
+        
+        # 更新进度条
+        self.progress_bar.setValue(self.current_progress)
+        
+        # 更新状态文本
+        if self.current_progress < 20:
+            self.status_label.setText("正在初始化系统...")
+        elif self.current_progress < 40:
+            self.status_label.setText("正在加载检测模型...")
+        elif self.current_progress < 60:
+            self.status_label.setText("正在初始化摄像头...")
+        elif self.current_progress < 80:
+            self.status_label.setText("正在配置用户界面...")
+        elif self.current_progress < 95:
+            self.status_label.setText("正在准备启动...")
+        else:
+            self.status_label.setText("启动完成！")
+        
+        # 完成启动
+        if self.current_progress >= 100:
+            self.progress_timer.stop()
+            QTimer.singleShot(500, self.finishSplash)  # 延迟500ms显示完成状态
+            
+    def finishSplash(self):
+        """
+        完成启动流程
+        
+        发出启动完成信号并关闭启动画面窗口。
+        """
+        self.splashFinished.emit()
+        self.close()
+        
+    def paintEvent(self, event):
+        """
+        重写绘制事件
+        
+        参数：
+            event: 绘制事件对象
+            
+        注意：
+            背景图片已经在setPixmap中设置，这里直接调用父类方法即可。
+        """
+        super().paintEvent(event) 

src/src/YOLOv8/UIProgram/__init__.py

@@ -0,0 +1,45 @@
+# -*- coding: utf-8 -*-
+"""
+UIProgram包
+===========
+
+YOLOv8人脸检测系统的用户界面模块
+
+包含以下模块：
+- SplashScreen: 启动画面，提供应用程序启动时的欢迎界面
+- InitialWindow: 欢迎窗口，用户进入系统前的主界面  
+- ModernMainWindow: 主程序窗口，包含完整的检测功能
+
+模块结构：
+- ui_imgs/: 界面图片资源文件夹
+  - icons/: 图标和背景图片
+    - loading.png: 启动画面背景
+    - BA.png: 欢迎界面背景
+    - R6.png: 主程序背景
+    - face.png: 应用程序图标
+
+功能特性：
+- 现代化UI设计风格
+- 半透明背景效果
+- 支持图片、视频、摄像头、批量检测
+- 批量检测支持图片浏览功能
+- 全屏显示支持
+- 智能路径查找，支持多种启动方式
+
+版本: 1.0.0
+作者: YOLOv8人脸检测系统开发团队
+"""
+
+__version__ = "1.0.0"
+__author__ = "YOLOv8人脸检测系统开发团队"
+
+# 导出主要类
+from .SplashScreen import SplashScreen
+from .InitialWindow import InitialWindow  
+from .ModernMainWindow import ModernMainWindow
+
+__all__ = [
+    'SplashScreen',
+    'InitialWindow', 
+    'ModernMainWindow'
+]

src/src/YOLOv8/VideoTest.py

@@ -0,0 +1,37 @@
+#coding:utf-8
+import cv2
+from ultralytics import YOLO
+
+# 所需加载的模型目录
+path = 'models/best.pt'
+# 需要检测的图片地址
+video_path = "TestFiles/1.mp4"
+
+# Load the YOLOv8 model
+model = YOLO(path)
+cap = cv2.VideoCapture(video_path)
+# Loop through the video frames
+while cap.isOpened():
+    # Read a frame from the video
+    success, frame = cap.read()
+
+    if success:
+        # Run YOLOv8 inference on the frame
+        results = model(frame)
+
+        # Visualize the results on the frame
+        annotated_frame = results[0].plot()
+
+        # Display the annotated frame
+        cv2.imshow("YOLOv8 Inference", annotated_frame)
+
+        # Break the loop if 'q' is pressed
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+    else:
+        # Break the loop if the end of the video is reached
+        break
+
+# Release the video capture object and close the display window
+cap.release()
+cv2.destroyAllWindows()

src/src/YOLOv8/datasets/count_size.py

@@ -0,0 +1,129 @@
+# 1、统计数据集中小、中、大 GT的个数
+# 2、统计某个类别小、中、大 GT的个数
+# 3、统计数据集中ss、sm、sl GT的个数
+import os
+from pathlib import Path
+import matplotlib.pyplot as plt
+
+# 设置中文字体为微软雅黑
+plt.rcParams['font.sans-serif'] = 'SimHei'
+
+
+def getGtAreaAndRatio(label_dir):
+    """
+    得到不同尺度的gt框个数
+    :params label_dir: label文件地址
+    :return data_dict: {dict: 3}  3 x {'类别':{’area':[...]}, {'ratio':[...]}}
+    """
+    data_dict = {}
+    assert Path(label_dir).is_dir(), "label_dir is not exist"
+
+    txts = os.listdir(label_dir)  # 得到label_dir目录下的所有txt GT文件
+
+    for txt in txts:  # 遍历每一个txt文件
+        with open(os.path.join(label_dir, txt), 'r') as f:  # 打开当前txt文件 并读取所有行的数据
+            lines = f.readlines()
+
+        for line in lines:  # 遍历当前txt文件中每一行的数据
+            temp = line.split()  # str to list{5}
+            coor_list = list(map(lambda x: x, temp[1:]))  # [x, y, w, h]
+            area = float(coor_list[2]) * float(coor_list[3])  # 计算出当前txt文件中每一个gt的面积
+            # center = (int(coor_list[0] + 0.5*coor_list[2]),
+            #           int(coor_list[1] + 0.5*coor_list[3]))
+            if float(coor_list[3])!=0:
+                ratio = round(float(coor_list[2]) / float(coor_list[3]), 2)  # 计算出当前txt文件中每一个gt的 w/h
+
+            if temp[0] not in data_dict:
+                data_dict[temp[0]] = {}
+                data_dict[temp[0]]['area'] = []
+                data_dict[temp[0]]['ratio'] = []
+
+            data_dict[temp[0]]['area'].append(area)
+            data_dict[temp[0]]['ratio'].append(ratio)
+
+    return data_dict
+
+
+def getSMLGtNumByClass(data_dict, class_num):
+    """
+    计算某个类别的小物体、中物体、大物体的个数
+    params data_dict: {dict: 3}  3 x {'类别':{’area':[...]}, {'ratio':[...]}}
+    params class_num: 类别  0, 1, 2
+    return s: 该类别小物体的个数  0 < area <= 0.5%
+           m: 该类别中物体的个数  0.5% < area <= 1%
+           l: 该类别大物体的个数  area > 1%
+    """
+    s, m, l = 0, 0, 0
+    # 图片的尺寸大小 注意修改!!!
+    h = 640
+    w = 640
+    for item in data_dict['{}'.format(class_num)]['area']:
+        if item * h * w <= h * w * 0.035:
+            s += 1
+        elif item * h * w <= h * w * 0.165:
+            m += 1
+        else:
+            l += 1
+    return s, m, l
+
+def getAllSMLGtNum(data_dict, isEachClass=False):
+    """
+    数据集所有类别小、中、大GT分布情况
+    isEachClass 控制是否按每个类别输出结构
+    """
+    S, M, L = 0, 0, 0
+    # 需要手动初始化下，有多少个类别就需要写多个
+    classDict = {'0': {'S': 0, 'M': 0, 'L': 0}}
+
+    print(classDict['0']['S'])
+    # range(class_num)类别数 注意修改!!!
+    if isEachClass == False:
+        for i in range(1):
+            s, m, l = getSMLGtNumByClass(data_dict, i)
+            S += s
+            M += m
+            L += l
+        return [S, M, L]
+    else:
+        for i in range(3):
+            S = 0
+            M = 0
+            L = 0
+            s, m, l = getSMLGtNumByClass(data_dict, i)
+            S += s
+            M += m
+            L += l
+            classDict[str(i)]['S'] = S
+            classDict[str(i)]['M'] = M
+            classDict[str(i)]['L'] = L
+        return classDict
+
+
+# 画图函数
+def plotAllSML(SML):
+    x = ['S:[0, 120x120]', 'M:[120x120, 260x260]', 'L:[260*260, 640x640]']
+    fig = plt.figure(figsize=(10, 8))  # 画布大小和像素密度
+    plt.bar(x, SML, width=0.5, align="center", color=['skyblue', 'orange', 'green'])
+    for a, b, i in zip(x, SML, range(len(x))):  # zip 函数
+        plt.text(a, b + 0.01, "%d" % int(SML[i]), ha='center', fontsize=15, color="r")  # plt.text 函数
+    plt.xticks(fontsize=15)
+    plt.yticks(fontsize=15)
+    plt.xlabel('gt大小', fontsize=16)
+    plt.ylabel('数量', fontsize=16)
+    plt.title('人脸检测训练集小、中、大分布情况(640x640)', fontsize=16)
+    plt.show()
+    # 保存到本地
+    # plt.savefig("")
+
+
+if __name__ == '__main__':
+    labeldir = r'C:\Users\pc\Desktop\YOLOv8face\datasets\faceData\train\labels'
+    data_dict = getGtAreaAndRatio(labeldir)
+    # 1、数据集所有类别小、中、大GT分布情况
+    # 控制是否按每个类别输出结构
+    isEachClass = False
+    SML = getAllSMLGtNum(data_dict, isEachClass)
+    # print(SML)
+    if not isEachClass:
+        plotAllSML(SML)
+

src/src/YOLOv8/detect_tools.py

@@ -0,0 +1,222 @@
+# encoding:utf-8
+import cv2
+from PyQt5.QtGui import QPixmap, QImage
+import numpy as np
+from PIL import Image,ImageDraw,ImageFont
+import csv
+import os
+
+# fontC = ImageFont.truetype("Font/platech.ttf", 20, 0)
+
+# 绘图展示
+def cv_show(name,img):
+	cv2.imshow(name, img)
+	cv2.waitKey(0)
+	cv2.destroyAllWindows()
+
+
+def drawRectBox(image, rect, addText, fontC, color):
+    """
+    绘制矩形框与结果
+    :param image: 原始图像
+    :param rect: 矩形框坐标, int类型
+    :param addText: 类别名称
+    :param fontC: 字体
+    :return:
+    """
+    # 绘制位置方框
+    cv2.rectangle(image, (rect[0], rect[1]),
+                 (rect[2], rect[3]),
+                 color, 2)
+
+    # 绘制字体背景框
+    cv2.rectangle(image, (rect[0] - 1, rect[1] - 25), (rect[0] + 60, rect[1]), color, -1, cv2.LINE_AA)
+    # 图片 添加的文字 位置 字体 字体大小 字体颜色 字体粗细
+    # cv2.putText(image, addText, (int(rect[0])+2, int(rect[1])-3), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
+
+    img = Image.fromarray(image)
+    draw = ImageDraw.Draw(img)
+    draw.text((rect[0]+2, rect[1]-27), addText, (255, 255, 255), font=fontC)
+    imagex = np.array(img)
+    return imagex
+
+
+def img_cvread(path):
+    # 读取含中文名的图片文件
+    # img = cv2.imread(path)
+    img = cv2.imdecode(np.fromfile(path, dtype=np.uint8), cv2.IMREAD_COLOR)
+    return img
+
+
+def draw_boxes(img, boxes):
+    for each in boxes:
+        x1 = each[0]
+        y1 = each[1]
+        x2 = each[2]
+        y2 = each[3]
+        cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
+    return img
+
+
+
+def cvimg_to_qpiximg(cvimg):
+    height, width, depth = cvimg.shape
+    cvimg = cv2.cvtColor(cvimg, cv2.COLOR_BGR2RGB)
+    qimg = QImage(cvimg.data, width, height, width * depth, QImage.Format_RGB888)
+    qpix_img = QPixmap(qimg)
+    return qpix_img
+
+
+def save_video():
+    # VideoCapture方法是cv2库提供的读取视频方法
+    cap = cv2.VideoCapture('C:\\Users\\xxx\\Desktop\\sweet.mp4')
+    # 设置需要保存视频的格式“xvid”
+    # 该参数是MPEG-4编码类型，文件名后缀为.avi
+    fourcc = cv2.VideoWriter_fourcc(*'XVID')
+    # 设置视频帧频
+    fps = cap.get(cv2.CAP_PROP_FPS)
+    # 设置视频大小
+    size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
+    # VideoWriter方法是cv2库提供的保存视频方法
+    # 按照设置的格式来out输出
+    out = cv2.VideoWriter('C:\\Users\\xxx\\Desktop\\out.avi', fourcc, fps, size)
+
+    # 确定视频打开并循环读取
+    while (cap.isOpened()):
+        # 逐帧读取，ret返回布尔值
+        # 参数ret为True 或者False,代表有没有读取到图片
+        # frame表示截取到一帧的图片
+        ret, frame = cap.read()
+        if ret == True:
+            # 垂直翻转矩阵
+            frame = cv2.flip(frame, 0)
+
+            out.write(frame)
+
+            cv2.imshow('frame', frame)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+        else:
+            break
+
+    # 释放资源
+    cap.release()
+    out.release()
+    # 关闭窗口
+    cv2.destroyAllWindows()
+
+
+# 封装函数:图片上显示中文
+def cv2AddChineseText(img, text, position, textColor=(0, 255, 0), textSize=50):
+    if (isinstance(img, np.ndarray)):  # 判断是否OpenCV图片类型
+        img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
+    # 创建一个可以在给定图像上绘图的对象
+    draw = ImageDraw.Draw(img)
+    # 字体的格式
+    fontStyle = ImageFont.truetype(
+        "simsun.ttc", textSize, encoding="utf-8")
+    # 绘制文本
+    draw.text(position, text, textColor, font=fontStyle)
+    # 转换回OpenCV格式
+    return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
+
+
+def insert_rows(path, lines ,header):
+    """
+    将n行数据写入csv文件
+    :param path:
+    :param lines:
+    :return:
+    """
+    no_header = False
+    if not os.path.exists(path):
+        no_header = True
+        start_num = 1
+    else:
+        start_num = len(open(path).readlines())
+
+    csv_head = header
+    with open(path, 'a', newline='') as f:
+        csv_write = csv.writer(f)
+        if no_header:
+            csv_write.writerow(csv_head)  # 写入表头
+
+        for each_list in lines:
+            # 添加序号
+            each_list = [start_num] + each_list
+            csv_write.writerow(each_list)
+            # 序号 + 1
+            start_num += 1
+
+class Colors:
+    # 用于绘制不同颜色
+    def __init__(self):
+        """Initialize colors as hex = matplotlib.colors.TABLEAU_COLORS.values()."""
+        hexs = ('FF3838', 'FF9D97', 'FF701F', 'FFB21D', 'CFD231', '48F90A', '92CC17', '3DDB86', '1A9334', '00D4BB',
+                '2C99A8', '00C2FF', '344593', '6473FF', '0018EC', '8438FF', '520085', 'CB38FF', 'FF95C8', 'FF37C7')
+        self.palette = [self.hex2rgb(f'#{c}') for c in hexs]
+        self.n = len(self.palette)
+        self.pose_palette = np.array([[255, 128, 0], [255, 153, 51], [255, 178, 102], [230, 230, 0], [255, 153, 255],
+                                      [153, 204, 255], [255, 102, 255], [255, 51, 255], [102, 178, 255], [51, 153, 255],
+                                      [255, 153, 153], [255, 102, 102], [255, 51, 51], [153, 255, 153], [102, 255, 102],
+                                      [51, 255, 51], [0, 255, 0], [0, 0, 255], [255, 0, 0], [255, 255, 255]],
+                                     dtype=np.uint8)
+
+    def __call__(self, i, bgr=False):
+        """Converts hex color codes to rgb values."""
+        c = self.palette[int(i) % self.n]
+        return (c[2], c[1], c[0]) if bgr else c
+
+    @staticmethod
+    def hex2rgb(h):  # rgb order (PIL)
+        return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))
+
+
+def yolo_to_location(w,h,yolo_data):
+    # yolo文件转两点坐标，注意画图坐标要转换成int格式
+    x_, y_, w_, h_ = yolo_data
+    x1 = int(w * x_ - 0.5 * w * w_)
+    x2 = int(w * x_ + 0.5 * w * w_)
+    y1 = int(h * y_ - 0.5 * h * h_)
+    y2 = int(h * y_ + 0.5 * h * h_)
+    # cv2.rectangle(img, (int(x1), int(y1)), (int(x2), int(y2)), (255, 0, 0))
+    return [x1,y1,x2,y2]
+
+def location_to_yolo(w, h, locations):
+    # x1,y1左上角坐标，x2,y2右上角坐标
+    x1, y1, x2, y2 = locations
+    x_ = (x1 + x2) / 2 / w
+    x_ = float('%.5f' % x_)
+    y_ = (y1 + y2) / 2 / h
+    y_ = float('%.5f' % y_)
+    w_ = (x2 - x1) / w
+    w_ = float('%.5f' % w_)
+    h_ = (y2 - y1) / h
+    h_ = float('%.5f' % h_)
+    return [x_,y_,w_,h_]
+
+def draw_yolo_data(img_path, yolo_file_path):
+    # 读取yolo标注数据并显示
+    img = cv2.imread(img_path)
+    h, w, _ = img.shape
+    print(img.shape)
+    # yolo标注数据文件名为786_rgb_0616.txt
+    with open(yolo_file_path, 'r') as f:
+        data = f.readlines()
+        for each in data:
+            temp = each.split()
+            # ['1', '0.43906', '0.52083', '0.34687', '0.15']
+            # YOLO转换为两点坐标x1, x2, y1, y2
+            x_, y_, w_, h_ = eval(temp[1]), eval(temp[2]), eval(temp[3]), eval(temp[4])
+            x1, y1, x2, y2 = yolo_to_location(w,h,[x_, y_, w_, h_])
+            # 画图验证框是否正确
+            cv2.rectangle(img, (x1, y1), (x2, y2), (0, 0, 255))
+
+    cv2.imshow('windows', img)
+    cv2.waitKey(0)
+
+if __name__ == '__main__':
+    img_path = 'TestFiles/1.jpg'
+    yolo_file_path = 'save_data/yolo_labels/1.txt'
+    draw_yolo_data(img_path, yolo_file_path)
+

src/src/YOLOv8/imgTest.py

@@ -0,0 +1,21 @@
+#coding:utf-8
+from ultralytics import YOLO
+import cv2
+
+# 所需加载的模型目录
+path = 'models/best.pt'
+# 需要检测的图片地址
+img_path = "TestFiles/test4.jpg"
+
+# 加载预训练模型
+# conf	0.25	object confidence threshold for detection
+# iou	0.7	intersection over union (IoU) threshold for NMS
+model = YOLO(path, task='detect')
+# model = YOLO(path, task='detect',conf=0.5)
+
+
+# 检测图片
+results = model(img_path)
+res = results[0].plot()
+cv2.imshow("YOLOv8 Detection", res)
+cv2.waitKey(0)

src/src/YOLOv8/installPackages.py

@@ -0,0 +1,7 @@
+import os
+
+pkgs = ['ultralytics','PyQt5==5.15.2','pyqt5-tools==5.15.2.3.1']
+
+for each in pkgs:
+    cmd_line = f"pip install {each} -i https://pypi.tuna.tsinghua.edu.cn/simple"
+    os.system(cmd_line)

src/src/YOLOv8/main.py

@@ -0,0 +1,5 @@
+import torch
+print(torch.cuda.is_available())
+print(torch.backends.cudnn.is_available())
+print(torch.cuda_version)
+print(torch.backends.cudnn.version())

src/src/YOLOv8/requirements.txt

@@ -0,0 +1,31 @@
+certifi==2023.7.22
+charset-normalizer==3.3.0
+colorama==0.4.6
+contourpy==1.1.1
+cycler==0.12.1
+fonttools==4.43.1
+idna==3.4
+importlib-resources==6.1.0
+kiwisolver==1.4.5
+matplotlib==3.8.0
+numpy==1.26.1
+opencv-python==4.8.1.78
+packaging==23.2
+psutil==5.9.6
+py-cpuinfo==9.0.0
+pyparsing==3.1.1
+python-dateutil==2.8.2
+pyyaml==6.0.1
+requests==2.31.0
+scipy==1.11.3
+seaborn==0.13.0
+six==1.16.0
+thop==0.1.1-2209072238
+# torch==1.9.0
+tqdm==4.66.1
+typing-extensions==4.8.0
+ultralytics==8.0.199
+urllib3==2.0.6
+zipp==3.17.0
+PyQt5==5.15.2
+pyqt5-tools==5.15.2.3.1

src/src/YOLOv8/runs/detect/train/args.yaml

@@ -0,0 +1,98 @@
+task: detect
+mode: train
+model: yolov8n.pt
+data: datasets/faceData/data.yaml
+epochs: 300
+patience: 50
+batch: 4
+imgsz: 640
+save: true
+save_period: -1
+cache: true
+device: 0
+workers: 12
+project: null
+name: train
+exist_ok: false
+pretrained: true
+optimizer: auto
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+save_hybrid: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+show: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+vid_stride: 1
+stream_buffer: false
+line_width: null
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+boxes: true
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: false
+opset: null
+workspace: 4
+nms: false
+lr0: 0.01
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+label_smoothing: 0.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+cfg: null
+tracker: botsort.yaml
+save_dir: runs\detect\train

src/src/YOLOv8/runs/detect/train/results.csv

@@ -0,0 +1,301 @@
+                  epoch,         train/box_loss,         train/cls_loss,         train/dfl_loss,   metrics/precision(B),      metrics/recall(B),       metrics/mAP50(B),    metrics/mAP50-95(B),           val/box_loss,           val/cls_loss,           val/dfl_loss,                 lr/pg0,                 lr/pg1,                 lr/pg2
+                      1,                 1.8366,                 1.6172,                   1.23,                0.73216,                 0.4057,                0.45729,                0.22342,                 1.6173,                 1.0335,                 1.1176,              0.0033324,              0.0033324,              0.0033324
+                      2,                 1.6996,                 1.1415,                 1.1168,                0.74462,                0.42432,                0.48077,                0.23546,                 1.5982,                 0.9299,                 1.0967,              0.0066437,              0.0066437,              0.0066437
+                      3,                 1.6942,                 1.0916,                 1.1144,                0.75214,                0.41787,                0.48389,                0.24459,                 1.5876,                0.91869,                 1.1124,               0.009933,               0.009933,               0.009933
+                      4,                 1.7002,                 1.0721,                 1.1165,                 0.7459,                0.43503,                0.49319,                0.24855,                 1.5479,                0.88047,                 1.0963,               0.009901,               0.009901,               0.009901
+                      5,                 1.6564,                 1.0036,                 1.1029,                0.75251,                0.44131,                0.50205,                0.25468,                  1.526,                0.86462,                 1.0938,               0.009901,               0.009901,               0.009901
+                      6,                 1.6158,                0.96155,                 1.0948,                0.77936,                0.44961,                0.51763,                0.26644,                 1.5144,                0.82764,                  1.092,               0.009868,               0.009868,               0.009868
+                      7,                 1.6037,                0.94048,                 1.0802,                0.77111,                0.46326,                0.52994,                0.27099,                 1.5069,                0.79548,                 1.0745,               0.009835,               0.009835,               0.009835
+                      8,                 1.5843,                0.92476,                 1.0833,                 0.7791,                0.46007,                0.52712,                0.27167,                 1.4899,                0.78321,                  1.079,               0.009802,               0.009802,               0.009802
+                      9,                 1.5674,                0.89715,                 1.0711,                0.77923,                0.46449,                0.53776,                0.28055,                   1.47,                0.76636,                  1.068,               0.009769,               0.009769,               0.009769
+                     10,                 1.5512,                0.87952,                 1.0653,                0.77521,                0.47389,                0.54483,                0.28164,                 1.4713,                 0.7573,                 1.0651,               0.009736,               0.009736,               0.009736
+                     11,                 1.5439,                0.87521,                 1.0637,                0.77805,                0.48045,                0.55307,                0.28919,                 1.4537,                0.74462,                 1.0681,               0.009703,               0.009703,               0.009703
+                     12,                 1.5349,                0.86626,                 1.0638,                0.79144,                0.48473,                0.55704,                 0.2906,                 1.4447,                0.74001,                 1.0585,                0.00967,                0.00967,                0.00967
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+                     17,                 1.5004,                0.82738,                 1.0452,                0.80276,                0.50093,                0.57732,                0.30315,                 1.4102,                0.70162,                   1.04,               0.009505,               0.009505,               0.009505
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+                    287,                 1.2569,                0.59836,                0.94949,                0.83075,                0.55859,                0.64377,                0.35045,                 1.3298,                0.58096,                 1.0038,               0.000595,               0.000595,               0.000595
+                    288,                 1.2467,                0.59551,                0.94928,                0.83142,                 0.5582,                0.64347,                0.35043,                 1.3301,                  0.581,                 1.0039,               0.000562,               0.000562,               0.000562
+                    289,                 1.2488,                0.59376,                0.94848,                0.83046,                 0.5586,                0.64385,                0.35029,                 1.3302,                0.58103,                 1.0039,               0.000529,               0.000529,               0.000529
+                    290,                 1.2512,                0.59594,                0.94861,                0.83122,                 0.5579,                0.64364,                0.35038,                 1.3303,                0.58092,                 1.0039,               0.000496,               0.000496,               0.000496
+                    291,                 1.2183,                0.55915,                0.94806,                0.83069,                0.55834,                0.64381,                0.35052,                 1.3306,                0.58101,                  1.004,               0.000463,               0.000463,               0.000463
+                    292,                 1.2135,                0.55606,                0.94714,                0.83051,                0.55849,                0.64382,                0.35047,                 1.3307,                0.58106,                  1.004,                0.00043,                0.00043,                0.00043
+                    293,                 1.2068,                 0.5524,                0.94658,                0.83093,                  0.558,                0.64399,                0.35041,                 1.3307,                0.58107,                  1.004,               0.000397,               0.000397,               0.000397
+                    294,                 1.2077,                0.55273,                0.94783,                0.83089,                 0.5579,                0.64375,                0.35043,                 1.3308,                0.58095,                 1.0041,               0.000364,               0.000364,               0.000364
+                    295,                 1.2061,                0.55151,                0.94596,                0.83098,                0.55731,                0.64381,                0.35045,                 1.3312,                0.58103,                 1.0042,               0.000331,               0.000331,               0.000331
+                    296,                 1.1994,                0.54712,                0.94586,                0.83113,                0.55809,                0.64418,                0.35057,                 1.3312,                 0.5812,                 1.0044,               0.000298,               0.000298,               0.000298
+                    297,                 1.1969,                0.54597,                0.94278,                0.83107,                0.55785,                0.64399,                0.35048,                 1.3314,                 0.5811,                 1.0044,               0.000265,               0.000265,               0.000265
+                    298,                 1.1968,                0.54484,                0.94344,                0.83156,                0.55785,                0.64394,                0.35043,                 1.3316,                 0.5812,                 1.0045,               0.000232,               0.000232,               0.000232
+                    299,                 1.1948,                0.54383,                 0.9427,                0.83074,                 0.5579,                0.64404,                0.35051,                 1.3318,                 0.5812,                 1.0046,               0.000199,               0.000199,               0.000199
+                    300,                 1.1984,                0.54449,                0.94156,                0.83123,                0.55839,                0.64426,                0.35051,                 1.3321,                 0.5813,                 1.0047,               0.000166,               0.000166,               0.000166

src/src/YOLOv8/setup.py

@@ -0,0 +1,105 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+
+import re
+from pathlib import Path
+
+from setuptools import setup
+
+# Settings
+FILE = Path(__file__).resolve()
+PARENT = FILE.parent  # root directory
+README = (PARENT / 'README.md').read_text(encoding='utf-8')
+
+
+def get_version():
+    """
+    Retrieve the version number from the 'ultralytics/__init__.py' file.
+
+    Returns:
+        (str): The version number extracted from the '__version__' attribute in the 'ultralytics/__init__.py' file.
+    """
+    file = PARENT / 'ultralytics/__init__.py'
+    return re.search(r'^__version__ = [\'"]([^\'"]*)[\'"]', file.read_text(encoding='utf-8'), re.M)[1]
+
+
+def parse_requirements(file_path: Path):
+    """
+    Parse a requirements.txt file, ignoring lines that start with '#' and any text after '#'.
+
+    Args:
+        file_path (str | Path): Path to the requirements.txt file.
+
+    Returns:
+        (List[str]): List of parsed requirements.
+    """
+
+    requirements = []
+    for line in Path(file_path).read_text().splitlines():
+        line = line.strip()
+        if line and not line.startswith('#'):
+            requirements.append(line.split('#')[0].strip())  # ignore inline comments
+
+    return requirements
+
+
+setup(
+    name='ultralytics',  # name of pypi package
+    version=get_version(),  # version of pypi package
+    python_requires='>=3.8',
+    license='AGPL-3.0',
+    description=('Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, '
+                 'pose estimation and image classification.'),
+    long_description=README,
+    long_description_content_type='text/markdown',
+    url='https://github.com/ultralytics/ultralytics',
+    project_urls={
+        'Bug Reports': 'https://github.com/ultralytics/ultralytics/issues',
+        'Funding': 'https://ultralytics.com',
+        'Source': 'https://github.com/ultralytics/ultralytics'},
+    author='Ultralytics',
+    author_email='hello@ultralytics.com',
+    packages=['ultralytics'] + [str(x) for x in Path('ultralytics').rglob('*/') if x.is_dir() and '__' not in str(x)],
+    package_data={
+        '': ['*.yaml'],
+        'ultralytics.assets': ['*.jpg']},
+    include_package_data=True,
+    install_requires=parse_requirements(PARENT / 'requirements.txt'),
+    extras_require={
+        'dev': [
+            'ipython',
+            'check-manifest',
+            'pre-commit',
+            'pytest',
+            'pytest-cov',
+            'coverage',
+            'mkdocs-material',
+            'mkdocstrings[python]',
+            'mkdocs-redirects',  # for 301 redirects
+            'mkdocs-ultralytics-plugin>=0.0.32',  # for meta descriptions and images, dates and authors
+        ],
+        'export': [
+            'coremltools>=7.0',
+            'openvino-dev>=2023.0',
+            'tensorflow<=2.13.1',
+            'tensorflowjs',  # automatically installs tensorflow
+        ], },
+    classifiers=[
+        'Development Status :: 4 - Beta',
+        'Intended Audience :: Developers',
+        'Intended Audience :: Education',
+        'Intended Audience :: Science/Research',
+        'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.8',
+        'Programming Language :: Python :: 3.9',
+        'Programming Language :: Python :: 3.10',
+        'Programming Language :: Python :: 3.11',
+        'Topic :: Software Development',
+        'Topic :: Scientific/Engineering',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Image Recognition',
+        'Operating System :: POSIX :: Linux',
+        'Operating System :: MacOS',
+        'Operating System :: Microsoft :: Windows', ],
+    keywords='machine-learning, deep-learning, vision, ML, DL, AI, YOLO, YOLOv3, YOLOv5, YOLOv8, HUB, Ultralytics',
+    entry_points={'console_scripts': ['yolo = ultralytics.cfg:entrypoint', 'ultralytics = ultralytics.cfg:entrypoint']})

src/src/YOLOv8/train.py

@@ -0,0 +1,15 @@
+#coding:utf-8
+from ultralytics import YOLO
+
+# 加载模型
+model = YOLO("yolov8n.pt")  # 加载预训练模型
+# Use the model
+if __name__ == '__main__':
+    # Use the model
+    results = model.train(data='datasets/faceData/data.yaml', epochs=300,device=0, batch=4,imgsz=640,cache=True,workers=12)  # 训练模型
+    # 将模型转为onnx格式
+    # success = model.export(format='onnx')
+
+
+
+

src/src/YOLOv8/程序运行说明文档.txt

@@ -0,0 +1,35 @@
+软件开发环境:python3.9
+系统界面开发：pyqt5
+
+---------项目文件说明---------
+见目录中的【目录文件说明.png】图片。
+
+环境配置步骤【共两步】：
+【注意：软件存放路径最好不要有中文。】
+
+---------【第一步：安装python3.9】---------
+方法一【推荐】：
+先安装ananconda软件，官网地址：https://www.anaconda.com/download
+安装完成后，在conda命令窗口，使用命令"conda create -n py39 python=3.9"创建3.9的虚拟环境
+然后激活虚拟环境“conda activate py39”,然后再进行第二步依赖库的安装。
+方法二：
+直接在python官网下载pyhon3.9的exe文件，安装即可。
+
+---------【第二步：安装软件所需的依赖库】---------
+（注意：输入命令前，命令行需先进入项目目录的路径下，不然会提示找不到文件）
+方法一：【推荐】
+直接运行installPackages.py一键安装第三方库的脚本。命令为：python installPackages.py
+方法二: 运行下方命令
+pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+
+---------【运行程序】---------
+按照以上两步环境配置完成后，直接运行MainProgram.py文件即可打开程序。
+命令为：python MainProgram.py
+
+
+---------【模型训练】---------
+将文件【datasets/faceData/data.yaml】中train,val数据集的绝对路径改为自己项目数据集的绝对路径
+
+然后运行train.py文件即可开始进行模型训练,训练结果会默认保存在runs目录中。
+
+

src/src/car_code/README.md

@@ -0,0 +1,302 @@
+# UVPTCCS 机器人系统 README 文档
+
+## 项目概述
+UVPTCCS (Unmanned Vehicle Positioning Tracking Control and Communication System) 是一个基于ROS2的无人车定位、追踪、控制和通信系统。该系统提供了完整的机器人功能包集合，包括底盘驱动、视觉追踪、导航建图、SLAM、位姿发布等功能。
+
+## 系统架构
+```
+UVPTCCS/
+├── car_astra/          # 颜色追踪与识别包
+├── car_bringup/        # 机器人底盘驱动包
+├── car_nav/            # 机器人导航包
+├── car_slam/           # SLAM与点云处理包
+├── robot_pose_publisher_ros2/  # 机器人位姿发布包
+└── laserscan_to_point_pulisher/  # 激光雷达点云转换包
+```
+
+## 包功能说明
+
+### 1. car_astra - 颜色追踪与识别包
+**主要功能**:
+- 基于深度摄像头的颜色目标识别
+- HSV颜色空间参数调整
+- 实时颜色目标追踪和跟随
+- PID控制器优化运动控制
+
+**核心节点**:
+- `colorHSV`: 颜色识别和HSV参数调整
+- `colorTracker`: 基于深度信息的目标追踪
+
+**应用场景**: 目标跟随、颜色识别、视觉导航
+
+### 2. car_bringup - 机器人底盘驱动包
+**主要功能**:
+- 支持多种机器人型号(X1、X3、R2)
+- 底层运动控制和传感器数据发布
+- RGB灯光和蜂鸣器控制
+- 自主巡逻和校准功能
+
+**核心节点**:
+- `Mcnamu_driver_X3`: X3型机器人驱动
+- `Mcnamu_driver_x1`: X1型机器人驱动
+- `Ackman_driver_R2`: R2型阿克曼转向机器人驱动
+- `patrol_*`: 各种巡逻功能节点
+
+**应用场景**: 机器人底层控制、传感器集成、自主巡逻
+
+### 3. car_nav - 机器人导航包
+**主要功能**:
+- 多种SLAM建图算法(Gmapping、Cartographer、RTABMap)
+- 路径规划和自主导航(DWA、TEB)
+- 激光雷达数据处理和滤波
+- 地图保存和加载
+
+**核心节点**:
+- `scan_filter`: 激光雷达数据滤波
+
+**应用场景**: 自主导航、环境建图、路径规划
+
+### 4. car_slam - SLAM与点云处理包
+**主要功能**:
+- 基于ORB-SLAM的视觉SLAM
+- RGB-D相机点云建图
+- 八叉树地图构建
+- 实时点云处理和可视化
+
+**核心节点**:
+- `pointcloud_mapping`: 点云建图节点
+
+**应用场景**: 视觉SLAM、3D建图、环境感知
+
+### 5. robot_pose_publisher_ros2 - 机器人位姿发布包
+**主要功能**:
+- 基于TF变换的位姿计算
+- 实时机器人位姿发布
+- 支持多种消息格式
+
+**核心节点**:
+- `robot_pose_publisher`: 位姿发布节点
+
+**应用场景**: 位姿监控、导航状态反馈、数据记录
+
+### 6. laserscan_to_point_pulisher - 激光雷达点云转换包
+**主要功能**:
+- 激光雷达数据转换为点云
+- 坐标系转换和数据处理
+- 实时数据可视化
+
+**核心节点**:
+- `laserscanToPointPublish`: 激光雷达点云转换节点
+
+**应用场景**: 数据转换、可视化、环境感知
+
+## 系统要求
+
+### 硬件要求
+- 支持的机器人平台: X1、X3、R2系列
+- 传感器: 激光雷达、RGB-D相机、IMU
+- 计算平台: 支持ROS2的Linux系统
+
+### 软件依赖
+- **操作系统**: Ubuntu 20.04/22.04
+- **ROS版本**: ROS2 Foxy/Galactic/Humble
+- **核心库**:
+  - OpenCV (计算机视觉)
+  - PCL (点云处理)
+  - Nav2 (导航功能)
+  - tf2_ros (坐标变换)
+  - Cartographer (SLAM)
+  - RTABMap (视觉SLAM)
+
+## 快速开始
+
+### 1. 环境准备
+```bash
+# 安装ROS2
+sudo apt update
+sudo apt install ros-humble-desktop-full
+
+# 安装依赖
+sudo apt install python3-colcon-common-extensions
+sudo apt install ros-humble-nav2-bringup
+sudo apt install ros-humble-cartographer-ros
+sudo apt install ros-humble-rtabmap-ros
+```
+
+### 2. 编译系统
+```bash
+# 创建工作空间
+mkdir -p ~/robot_ws/src
+cd ~/robot_ws/src
+
+# 克隆代码
+git clone <repository_url>
+
+# 编译
+cd ~/robot_ws
+colcon build --symlink-install
+
+# 设置环境
+source install/setup.bash
+```
+
+### 3. 启动系统
+
+#### 启动机器人底盘
+```bash
+# X3机器人
+ros2 launch car_bringup car_bringup_X3_launch.py
+
+# R2机器人
+ros2 launch car_bringup car_bringup_R2_launch.py
+```
+
+#### 启动颜色追踪
+```bash
+ros2 launch car_astra colorTracker_X3.launch.py
+```
+
+#### 启动导航系统
+```bash
+# SLAM建图
+ros2 launch car_nav map_gmapping_launch.py
+
+# 自主导航
+ros2 launch car_nav navigation_dwa_launch.py
+```
+
+#### 启动SLAM系统
+```bash
+# 点云建图
+ros2 launch car_slam orbslam_pcl_map_launch.py
+
+# 八叉树建图
+ros2 launch car_slam orbslam_pcl_octomap_launch.py
+```
+
+## 使用指南
+
+### 1. 机器人控制
+```bash
+# 手动控制
+ros2 run teleop_twist_keyboard teleop_twist_keyboard
+
+# 查看机器人状态
+ros2 topic echo /robot_pose
+ros2 topic echo /voltage
+```
+
+### 2. 建图导航
+```bash
+# 开始建图
+export RPLIDAR_TYPE=a1
+ros2 launch car_nav map_gmapping_launch.py
+
+# 保存地图
+ros2 launch car_nav save_map_launch.py
+
+# 开始导航
+ros2 launch car_nav navigation_dwa_launch.py
+```
+
+### 3. 视觉功能
+```bash
+# 颜色识别
+ros2 run car_astra colorHSV
+
+# 目标追踪
+ros2 run car_astra colorTracker
+```
+
+### 4. 数据可视化
+```bash
+# 启动RViz
+ros2 run rviz2 rviz2
+
+# 查看点云
+ros2 launch car_slam display_pcl_launch.py
+
+# 查看导航
+ros2 launch car_nav display_nav_launch.py
+```
+
+## 配置说明
+
+### 1. 机器人参数配置
+根据实际机器人型号修改对应的参数文件:
+- `car_bringup/param/`: 机器人底盘参数
+- `car_nav/params/`: 导航算法参数
+- `car_slam/params/`: SLAM算法参数
+
+### 2. 传感器校准
+- 激光雷达: 使用`calibrate_*`节点进行校准
+- 相机: 修改`car_slam/params/`中的相机参数
+- IMU: 调整`car_bringup/param/imu_filter_param.yaml`
+
+### 3. 坐标系配置
+确保以下坐标系正确配置:
+- `base_link`: 机器人基座
+- `base_footprint`: 机器人地面投影
+- `laser`: 激光雷达坐标系
+- `camera`: 相机坐标系
+- `map`: 全局地图坐标系
+- `odom`: 里程计坐标系
+
+## 故障排除
+
+### 1. 常见问题
+- **TF变换错误**: 检查坐标系配置和时间同步
+- **激光雷达无数据**: 检查设备连接和驱动
+- **相机图像异常**: 检查相机参数和USB连接
+- **导航失败**: 检查地图质量和参数配置
+
+### 2. 调试工具
+```bash
+# 查看TF树
+ros2 run tf2_tools view_frames
+
+# 检查话题
+ros2 topic list
+ros2 topic echo /topic_name
+
+# 查看节点状态
+ros2 node list
+ros2 node info /node_name
+
+# 参数调试
+ros2 param list /node_name
+ros2 param get /node_name parameter_name
+```
+
+## 开发指南
+
+### 1. 代码结构
+- 遵循ROS2标准包结构
+- 使用Python或C++开发节点
+- 添加适当的错误处理和日志
+
+### 2. 测试验证
+- 单元测试: 使用pytest或gtest
+- 集成测试: 验证节点间通信
+- 性能测试: 监控CPU和内存使用
+
+### 3. 文档维护
+- 更新README文档
+- 添加代码注释
+- 记录参数说明
+
+## 许可证
+本项目遵循开源许可证，具体请查看LICENSE文件。
+
+## 贡献指南
+欢迎提交问题报告和改进建议。请遵循以下步骤:
+1. Fork项目
+2. 创建特性分支
+3. 提交更改
+4. 发起Pull Request
+
+## 联系方式
+如有问题或建议，请通过以下方式联系:
+- 邮箱: [维护者邮箱]
+- 项目地址: [GitHub链接]
+- 文档地址: [文档链接] 

src/src/car_code/car_astra/README.md

@@ -0,0 +1,110 @@
+# ROS2 颜色追踪与识别包 README 文档
+
+## 包名称
+**car_astra**
+
+## 功能描述
+该包主要用于基于深度摄像头的颜色目标追踪和识别功能。包含颜色识别、HSV颜色空间处理、目标追踪等功能，适用于机器人视觉导航和目标跟随应用。
+
+## 节点列表
+
+### 1. colorHSV (颜色识别节点)
+- **节点名称**: `coloridentify`
+- **可执行文件**: `colorHSV`
+- **功能**: 实时颜色识别和HSV参数调整
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/Current_point` | `yahboomcar_msgs/msg/Position` | 发布检测到的颜色目标位置信息 |
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | 发布运动控制命令 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| 摄像头数据 | `sensor_msgs/msg/Image` | 通过OpenCV VideoCapture获取 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `Hmin` | int | 0 | HSV色彩空间H分量最小值 |
+| `Smin` | int | 85 | HSV色彩空间S分量最小值 |
+| `Vmin` | int | 126 | HSV色彩空间V分量最小值 |
+| `Hmax` | int | 9 | HSV色彩空间H分量最大值 |
+| `Smax` | int | 253 | HSV色彩空间S分量最大值 |
+| `Vmax` | int | 253 | HSV色彩空间V分量最大值 |
+| `refresh` | bool | false | 是否刷新HSV参数 |
+
+### 2. colorTracker (颜色追踪节点)
+- **节点名称**: `color_tracker`
+- **可执行文件**: `colorTracker`
+- **功能**: 基于深度信息的颜色目标追踪和跟随
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | 发布机器人运动控制命令 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/camera/depth/image_raw` | `sensor_msgs/msg/Image` | `depth_img_Callback` | 订阅深度图像数据 |
+| `/JoyState` | `std_msgs/msg/Bool` | `JoyStateCallback` | 订阅手柄状态 |
+| `/Current_point` | `yahboomcar_msgs/msg/Position` | `positionCallback` | 订阅目标位置信息 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `linear_Kp` | double | 3.0 | 线性PID控制器比例系数 |
+| `linear_Ki` | double | 0.0 | 线性PID控制器积分系数 |
+| `linear_Kd` | double | 1.0 | 线性PID控制器微分系数 |
+| `angular_Kp` | double | 0.5 | 角度PID控制器比例系数 |
+| `angular_Ki` | double | 0.0 | 角度PID控制器积分系数 |
+| `angular_Kd` | double | 2.0 | 角度PID控制器微分系数 |
+| `scale` | int | 1000 | 距离缩放因子 |
+| `minDistance` | double | 1.0 | 最小跟随距离(米) |
+
+## 启动文件
+
+### colorTracker_X3.launch.py
+启动颜色追踪系统，包含：
+- 机器人底盘驱动节点
+- 颜色识别节点
+
+## 使用说明
+
+### 1. 颜色识别模式
+```bash
+# 启动颜色识别节点
+ros2 run car_astra colorHSV
+```
+
+**操作说明**:
+- 按 `i` 键进入识别模式
+- 按 `r` 键重置参数
+- 按空格键进入追踪模式
+- 按 `q` 键退出程序
+
+### 2. 颜色追踪模式
+```bash
+# 启动完整的颜色追踪系统
+ros2 launch car_astra colorTracker_X3.launch.py
+```
+
+### 3. HSV参数调整
+- 在识别模式下，可以通过鼠标选择区域来自动获取HSV参数
+- 参数会自动保存到 `colorHSV.text` 文件中
+- 可以通过ROS2参数服务器动态调整HSV参数
+
+## 依赖项
+- OpenCV (计算机视觉库)
+- PCL (点云处理库)
+- ROS2 (机器人操作系统)
+- yahboomcar_msgs (自定义消息类型)
+- cv_bridge (OpenCV与ROS图像转换)
+
+## 注意事项
+1. 需要连接深度摄像头(如Astra系列)
+2. 确保光照条件良好，避免颜色识别误差
+3. 根据实际环境调整HSV参数范围
+4. 追踪模式下请确保安全距离，避免碰撞 

src/src/car_code/car_bringup/README.md

@@ -0,0 +1,218 @@
+# ROS2 机器人底盘驱动包 README 文档
+
+## 包名称
+**car_bringup**
+
+## 功能描述
+该包是机器人底盘驱动的核心包，提供不同型号机器人的底层控制接口，包括运动控制、IMU数据发布、RGB灯光控制、蜂鸣器控制等功能。支持多种机器人型号(X1、X3、R2)的驱动程序。
+
+## 节点列表
+
+### 1. Mcnamu_driver_X3 (X3型机器人驱动节点)
+- **节点名称**: `driver_node`
+- **可执行文件**: `Mcnamu_driver_X3`
+- **功能**: X3型机器人底盘驱动控制
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/edition` | `std_msgs/msg/Float32` | 发布版本信息 |
+| `/voltage` | `std_msgs/msg/Float32` | 发布电池电压信息 |
+| `/joint_states` | `sensor_msgs/msg/JointState` | 发布关节状态信息 |
+| `/vel_raw` | `geometry_msgs/msg/Twist` | 发布原始速度信息 |
+| `/imu/data_raw` | `sensor_msgs/msg/Imu` | 发布IMU原始数据 |
+| `/imu/mag` | `sensor_msgs/msg/MagneticField` | 发布磁力计数据 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | `cmd_vel_callback` | 订阅运动控制命令 |
+| `/RGBLight` | `std_msgs/msg/Int32` | `RGBLightcallback` | 订阅RGB灯光控制 |
+| `/Buzzer` | `std_msgs/msg/Bool` | `Buzzercallback` | 订阅蜂鸣器控制 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `car_type` | string | "X3" | 机器人型号 |
+| `imu_link` | string | "imu_link" | IMU坐标系名称 |
+| `Prefix` | string | "" | 话题前缀 |
+| `xlinear_limit` | double | 1.0 | X轴线速度限制 |
+| `ylinear_limit` | double | 1.0 | Y轴线速度限制 |
+| `angular_limit` | double | 5.0 | 角速度限制 |
+
+### 2. Mcnamu_driver_x1 (X1型机器人驱动节点)
+- **节点名称**: `driver_node`
+- **可执行文件**: `Mcnamu_driver_x1`
+- **功能**: X1型机器人底盘驱动控制
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/edition` | `std_msgs/msg/Float32` | 发布版本信息 |
+| `/voltage` | `std_msgs/msg/Float32` | 发布电池电压信息 |
+| `/joint_states` | `sensor_msgs/msg/JointState` | 发布关节状态信息 |
+| `/vel_raw` | `geometry_msgs/msg/Twist` | 发布原始速度信息 |
+| `/imu/data_raw` | `sensor_msgs/msg/Imu` | 发布IMU原始数据 |
+| `/imu/mag` | `sensor_msgs/msg/MagneticField` | 发布磁力计数据 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | `cmd_vel_callback` | 订阅运动控制命令 |
+| `/RGBLight` | `std_msgs/msg/Int32` | `RGBLightcallback` | 订阅RGB灯光控制 |
+| `/Buzzer` | `std_msgs/msg/Bool` | `Buzzercallback` | 订阅蜂鸣器控制 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `car_type` | string | "X1" | 机器人型号 |
+| `imu_link` | string | "imu_link" | IMU坐标系名称 |
+| `nav_use_rotvel` | bool | false | 导航是否使用旋转速度 |
+
+### 3. Ackman_driver_R2 (R2型机器人驱动节点)
+- **节点名称**: `driver_node`
+- **可执行文件**: `Ackman_driver_R2`
+- **功能**: R2型阿克曼转向机器人底盘驱动控制
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/edition` | `std_msgs/msg/Float32` | 发布版本信息 |
+| `/voltage` | `std_msgs/msg/Float32` | 发布电池电压信息 |
+| `/joint_states` | `sensor_msgs/msg/JointState` | 发布关节状态信息 |
+| `/vel_raw` | `geometry_msgs/msg/Twist` | 发布原始速度信息 |
+| `/imu/data_raw` | `sensor_msgs/msg/Imu` | 发布IMU原始数据 |
+| `/imu/mag` | `sensor_msgs/msg/MagneticField` | 发布磁力计数据 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | `cmd_vel_callback` | 订阅运动控制命令 |
+| `/RGBLight` | `std_msgs/msg/Int32` | `RGBLightcallback` | 订阅RGB灯光控制 |
+| `/Buzzer` | `std_msgs/msg/Bool` | `Buzzercallback` | 订阅蜂鸣器控制 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `car_type` | string | "R2" | 机器人型号 |
+| `imu_link` | string | "imu_link" | IMU坐标系名称 |
+| `nav_use_rotvel` | bool | false | 导航是否使用旋转速度 |
+
+## 巡逻功能节点
+
+### 4. patrol_4ROS (四轮机器人巡逻节点)
+- **节点名称**: `patrol_node`
+- **可执行文件**: `patrol_4ROS`
+- **功能**: 基于激光雷达的自主巡逻功能
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/cmd_vel` | `geometry_msgs/msg/Twist` | 发布运动控制命令 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/scan` | `sensor_msgs/msg/LaserScan` | `LaserScanCallback` | 订阅激光雷达数据 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `odom_frame` | string | "odom" | 里程计坐标系名称 |
+| `base_frame` | string | "base_footprint" | 机器人基座坐标系名称 |
+
+### 5. patrol_a1_X3 (A1雷达X3机器人巡逻节点)
+- **节点名称**: `patrol_node`
+- **可执行文件**: `patrol_a1_X3`
+- **功能**: 基于A1激光雷达的X3机器人巡逻
+
+### 6. patrol_a1_R2 (A1雷达R2机器人巡逻节点)
+- **节点名称**: `patrol_node`
+- **可执行文件**: `patrol_a1_R2`
+- **功能**: 基于A1激光雷达的R2机器人巡逻
+
+### 7. patrol_4ROS_R2 (四轮雷达R2机器人巡逻节点)
+- **节点名称**: `patrol_node`
+- **可执行文件**: `patrol_4ROS_R2`
+- **功能**: 基于四轮激光雷达的R2机器人巡逻
+
+## 校准功能节点
+
+### 8. calibrate_linear_X3 (X3线性校准节点)
+- **可执行文件**: `calibrate_linear_X3`
+- **功能**: X3机器人线性运动校准
+
+### 9. calibrate_angular_X3 (X3角度校准节点)
+- **可执行文件**: `calibrate_angular_X3`
+- **功能**: X3机器人角度运动校准
+
+### 10. calibrate_linear_R2 (R2线性校准节点)
+- **可执行文件**: `calibrate_linear_R2`
+- **功能**: R2机器人线性运动校准
+
+### 11. calibrate_angular_R2 (R2角度校准节点)
+- **可执行文件**: `calibrate_angular_R2`
+- **功能**: R2机器人角度运动校准
+
+## 启动文件
+
+### car_bringup_R2_launch.py
+启动R2机器人完整系统，包含：
+- R2机器人驱动节点
+- 机器人状态发布节点
+- IMU滤波节点
+- EKF定位节点
+- 手柄控制节点
+
+## 使用说明
+
+### 1. 启动机器人驱动
+```bash
+# 启动X3机器人
+ros2 run car_bringup Mcnamu_driver_X3
+
+# 启动X1机器人
+ros2 run car_bringup Mcnamu_driver_x1
+
+# 启动R2机器人
+ros2 run car_bringup Ackman_driver_R2
+```
+
+### 2. 启动完整系统
+```bash
+# 启动R2机器人完整系统
+ros2 launch car_bringup car_bringup_R2_launch.py
+```
+
+### 3. 控制机器人运动
+```bash
+# 发布运动控制命令
+ros2 topic pub /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.5, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}"
+```
+
+### 4. 控制RGB灯光
+```bash
+# 控制RGB灯光效果 (0-6不同效果)
+ros2 topic pub /RGBLight std_msgs/msg/Int32 "data: 1"
+```
+
+### 5. 控制蜂鸣器
+```bash
+# 打开蜂鸣器
+ros2 topic pub /Buzzer std_msgs/msg/Bool "data: true"
+```
+
+## 依赖项
+- ROS2 (机器人操作系统)
+- Rosmaster_Lib (机器人底层控制库)
+- tf2_ros (坐标变换库)
+- sensor_msgs (传感器消息类型)
+- geometry_msgs (几何消息类型)
+- PyKDL (运动学和动力学库)
+
+## 注意事项
+1. 确保机器人硬件连接正确
+2. 根据实际机器人型号选择对应的驱动节点
+3. 校准功能需要在开阔平坦的环境中进行
+4. 巡逻功能需要激光雷达正常工作
+5. 注意电池电压监控，低电压时及时充电 

src/src/car_code/car_nav/README.md

@@ -0,0 +1,249 @@
+# ROS2 机器人导航包 README 文档
+
+## 包名称
+**car_nav**
+
+## 功能描述
+该包提供机器人导航和建图的完整解决方案，包括SLAM建图、路径规划、自主导航等功能。支持多种建图算法(Gmapping、Cartographer、RTABMap)和导航算法(DWA、TEB)。
+
+## 节点列表
+
+### 1. scan_filter (激光雷达滤波节点)
+- **节点名称**: `scan_dilute`
+- **可执行文件**: `scan_filter`
+- **功能**: 激光雷达数据降采样和滤波处理
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/downsampled_scan` | `sensor_msgs/msg/LaserScan` | 发布降采样后的激光雷达数据 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/scan` | `sensor_msgs/msg/LaserScan` | `laserCallback` | 订阅原始激光雷达数据 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `multiple` | int | 2 | 降采样倍数 |
+
+## 启动文件
+
+### 建图相关启动文件
+
+#### 1. map_gmapping_launch.py
+- **功能**: 启动Gmapping SLAM建图
+- **支持的雷达类型**: A1、S2、4ROS
+- **环境变量**: `RPLIDAR_TYPE`
+
+#### 2. map_gmapping_a1_launch.py
+- **功能**: 基于A1激光雷达的Gmapping建图
+
+#### 3. map_gmapping_4ros_s2_launch.py
+- **功能**: 基于4ROS/S2激光雷达的Gmapping建图
+
+#### 4. map_cartographer_launch.py
+- **功能**: 启动Cartographer SLAM建图
+- **配置文件**: `lds_2d.lua`
+
+#### 5. map_rtabmap_launch.py
+- **功能**: 启动RTABMap SLAM建图
+- **包含组件**:
+  - 激光雷达启动
+  - RTABMap同步节点
+
+#### 6. save_map_launch.py
+- **功能**: 保存建图结果
+- **默认保存路径**: `maps/yahboomcar`
+
+### 导航相关启动文件
+
+#### 7. navigation_dwa_launch.py
+- **功能**: 基于DWA算法的自主导航
+- **参数文件**: `dwa_nav_params.yaml`
+- **地图文件**: `maps/yahboomcar.yaml`
+
+#### 8. navigation_teb_launch.py
+- **功能**: 基于TEB算法的自主导航
+- **参数文件**: `teb_nav_params.yaml`
+- **地图文件**: `maps/yahboomcar.yaml`
+
+#### 9. navigation_rtabmap_launch.py
+- **功能**: 基于RTABMap的自主导航
+- **包含组件**:
+  - 激光雷达启动
+  - RTABMap定位
+  - RTABMap导航
+
+#### 10. rtabmap_nav_launch.py
+- **功能**: RTABMap导航系统
+- **参数文件**: `rtabmap_nav_params.yaml`
+
+### 定位相关启动文件
+
+#### 11. rtabmap_localization_launch.py
+- **功能**: RTABMap定位系统
+
+#### 12. rtabmap_sync_launch.py
+- **功能**: RTABMap数据同步
+
+### 显示相关启动文件
+
+#### 13. display_map_launch.py
+- **功能**: 显示建图结果
+- **RViz配置**: `rviz/map.rviz`
+
+#### 14. display_nav_launch.py
+- **功能**: 显示导航过程
+- **RViz配置**: `rviz/nav.rviz`
+
+#### 15. display_rtabmap_map_launch.py
+- **功能**: 显示RTABMap建图结果
+- **RViz配置**: `rviz/rtabmap_map.rviz`
+
+#### 16. display_rtabmap_nav_launch.py
+- **功能**: 显示RTABMap导航过程
+- **RViz配置**: `rviz/rtabmap_nav.rviz`
+
+### 其他启动文件
+
+#### 17. laser_bringup_launch.py
+- **功能**: 启动激光雷达驱动
+
+#### 18. occupancy_grid_launch.py
+- **功能**: 启动占用栅格地图
+
+#### 19. rtabmap_viz_launch.py
+- **功能**: RTABMap可视化
+
+## 配置文件
+
+### 导航参数文件
+
+#### 1. dwa_nav_params.yaml
+- **功能**: DWA导航算法参数配置
+- **包含组件**:
+  - bt_navigator (行为树导航器)
+  - controller_server (控制器服务器)
+  - local_costmap (局部代价地图)
+  - global_costmap (全局代价地图)
+  - planner_server (路径规划器)
+  - map_server (地图服务器)
+
+#### 2. teb_nav_params.yaml
+- **功能**: TEB导航算法参数配置
+
+#### 3. rtabmap_nav_params.yaml
+- **功能**: RTABMap导航参数配置
+
+### 建图参数文件
+
+#### 4. lds_2d.lua
+- **功能**: Cartographer 2D建图参数配置
+- **主要参数**:
+  - `map_frame`: "map"
+  - `tracking_frame`: "base_footprint"
+  - `published_frame`: "odom"
+  - `use_odometry`: true
+  - `num_laser_scans`: 1
+
+## 地图文件
+
+### 1. yahboomcar.yaml/yahboomcar.pgm
+- **分辨率**: 0.05m/pixel
+- **原点**: [-2.3, -8.95, 0]
+- **占用阈值**: 0.65
+- **空闲阈值**: 0.25
+
+### 2. yahboomcar2.yaml/yahboomcar2.pgm
+- **分辨率**: 0.05m/pixel
+- **原点**: [-10, -10, 0]
+
+## 使用说明
+
+### 1. SLAM建图
+
+#### Gmapping建图
+```bash
+# 设置激光雷达类型
+export RPLIDAR_TYPE=a1
+
+# 启动建图
+ros2 launch car_nav map_gmapping_launch.py
+
+# 保存地图
+ros2 launch car_nav save_map_launch.py
+```
+
+#### Cartographer建图
+```bash
+# 启动Cartographer建图
+ros2 launch car_nav map_cartographer_launch.py
+
+# 保存地图
+ros2 service call /write_state cartographer_ros_msgs/srv/WriteState "{filename: '/path/to/map.bag'}"
+```
+
+#### RTABMap建图
+```bash
+# 启动RTABMap建图
+ros2 launch car_nav map_rtabmap_launch.py
+```
+
+### 2. 自主导航
+
+#### DWA导航
+```bash
+# 启动DWA导航
+ros2 launch car_nav navigation_dwa_launch.py
+```
+
+#### TEB导航
+```bash
+# 启动TEB导航
+ros2 launch car_nav navigation_teb_launch.py
+```
+
+#### RTABMap导航
+```bash
+# 启动RTABMap导航
+ros2 launch car_nav navigation_rtabmap_launch.py
+```
+
+### 3. 可视化
+
+#### 查看建图过程
+```bash
+# 显示建图结果
+ros2 launch car_nav display_map_launch.py
+```
+
+#### 查看导航过程
+```bash
+# 显示导航过程
+ros2 launch car_nav display_nav_launch.py
+```
+
+### 4. 激光雷达滤波
+```bash
+# 启动激光雷达滤波节点
+ros2 run car_nav scan_filter
+```
+
+## 依赖项
+- ROS2 (机器人操作系统)
+- Nav2 (导航功能包)
+- Cartographer (谷歌SLAM算法)
+- RTABMap (实时外观建图)
+- Gmapping (SLAM建图算法)
+- RViz2 (可视化工具)
+- TF2 (坐标变换库)
+
+## 注意事项
+1. 建图前确保激光雷达正常工作
+2. 建图过程中保持机器人缓慢移动
+3. 导航前确保已有准确的地图
+4. 根据环境特点选择合适的导航算法
+5. 定期校准里程计和IMU数据
+6. 注意机器人安全，避免碰撞障碍物 

src/src/car_code/car_slam/README.md

@@ -0,0 +1,234 @@
+# ROS2 SLAM与点云处理包 README 文档
+
+## 包名称
+**car_slam**
+
+## 功能描述
+该包提供视觉SLAM和点云处理功能，主要基于ORB-SLAM和点云建图技术。包含点云生成、滤波、可视化、八叉树地图构建等功能，适用于机器人三维环境感知和建图。
+
+## 节点列表
+
+### 1. pointcloud_mapping (点云建图节点)
+- **节点名称**: `pointcloud_mapping`
+- **可执行文件**: `point_cloud_main`
+- **功能**: 基于RGB-D相机的实时点云建图
+
+#### 发布接口
+| 话题名称 | 消息类型 | 描述 |
+|:---------|:---------|:-----|
+| `/Global/PointCloudOutput` | `sensor_msgs/msg/PointCloud2` | 发布全局点云地图 |
+| `/Local/PointCloudOutput` | `sensor_msgs/msg/PointCloud2` | 发布局部点云地图 |
+
+#### 订阅接口
+| 话题名称 | 消息类型 | 回调函数 | 描述 |
+|:---------|:---------|:---------|:-----|
+| `/RGBD/RGB/Image` | `sensor_msgs/msg/Image` | `callback` | 订阅RGB图像数据 |
+| `/RGBD/Depth/Image` | `sensor_msgs/msg/Image` | `callback` | 订阅深度图像数据 |
+| `/RGBD/CameraPose` | `geometry_msgs/msg/PoseStamped` | `callback` | 订阅相机位姿数据 |
+
+#### 参数配置
+| 参数名称 | 类型 | 默认值 | 描述 |
+|:---------|:-----|:-------|:-----|
+| `topicColor` | string | "/RGBD/RGB/Image" | RGB图像话题名称 |
+| `topicDepth` | string | "/RGBD/Depth/Image" | 深度图像话题名称 |
+| `topicTcw` | string | "/RGBD/CameraPose" | 相机位姿话题名称 |
+| `local_frame_id` | string | "camera" | 局部坐标系ID |
+| `global_frame_id` | string | "camera" | 全局坐标系ID |
+| `node_path` | string | "/root/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_slam/pcl/" | 点云文件保存路径 |
+| `use_viewer` | bool | false | 是否启用PCL可视化 |
+| `fx` | float | 517.306408 | 相机内参fx |
+| `fy` | float | 516.469215 | 相机内参fy |
+| `cx` | float | 318.643040 | 相机内参cx |
+| `cy` | float | 255.313989 | 相机内参cy |
+| `resolution` | float | 0.05 | 点云分辨率 |
+| `depthfactor` | float | 1000.0 | 深度图缩放因子 |
+| `queueSize` | int | 10 | 消息队列大小 |
+| `buseExact` | bool | false | 是否使用精确时间同步 |
+
+## 启动文件
+
+### 1. orbslam_ros_launch.py
+- **功能**: 启动ORB-SLAM系统
+- **包含组件**:
+  - ORB-SLAM节点
+  - 相机驱动节点
+
+### 2. orbslam_base_launch.py
+- **功能**: 启动ORB-SLAM基础系统
+
+### 3. orbslam_pose_launch.py
+- **功能**: 启动ORB-SLAM位姿估计
+
+### 4. orbslam_pcl_map_launch.py
+- **功能**: 启动ORB-SLAM点云建图
+- **包含组件**:
+  - ORB-SLAM节点
+  - 点云建图节点
+
+### 5. orbslam_pcl_octomap_launch.py
+- **功能**: 启动ORB-SLAM点云八叉树建图
+- **包含组件**:
+  - ORB-SLAM节点
+  - 点云建图节点
+  - 八叉树地图节点
+
+### 6. camera_octomap_launch.py
+- **功能**: 启动相机八叉树建图
+
+### 7. octomap_server_launch.py
+- **功能**: 启动八叉树地图服务器
+
+### 8. display_octomap_launch.py
+- **功能**: 显示八叉树地图
+- **RViz配置**: `rviz/octomap.rviz`
+
+### 9. display_pcl_launch.py
+- **功能**: 显示点云地图
+- **RViz配置**: `rviz/orbslam_pcl.rviz`
+
+## 配置文件
+
+### 相机参数文件
+
+#### 1. mono.yaml
+- **功能**: 单目相机参数配置
+- **包含参数**:
+  - 相机内参矩阵
+  - 畸变系数
+  - 图像尺寸
+
+#### 2. rgbd.yaml
+- **功能**: RGB-D相机参数配置
+- **包含参数**:
+  - RGB相机内参
+  - 深度相机内参
+  - 基线距离
+
+#### 3. usb_cam_param.yaml
+- **功能**: USB相机参数配置
+
+### SLAM参数文件
+
+#### 4. ORBvoc.txt
+- **功能**: ORB特征词汇表
+- **用途**: 用于回环检测和重定位
+
+### 点云处理参数文件
+
+#### 5. pointcloud_map.yaml
+- **功能**: 点云建图参数配置
+- **包含参数**:
+  - 点云分辨率
+  - 滤波参数
+  - 可视化参数
+
+#### 6. pointcloud_octomap.yaml
+- **功能**: 点云八叉树建图参数配置
+- **包含参数**:
+  - 八叉树分辨率
+  - 占用概率阈值
+  - 更新参数
+
+## 点云数据文件
+
+### resultPointCloudFile.pcd
+- **功能**: 保存的点云地图文件
+- **格式**: PCD (Point Cloud Data)
+- **用途**: 离线点云分析和可视化
+
+## 使用说明
+
+### 1. 启动ORB-SLAM系统
+```bash
+# 启动基础ORB-SLAM系统
+ros2 launch car_slam orbslam_base_launch.py
+
+# 启动带位姿估计的ORB-SLAM
+ros2 launch car_slam orbslam_pose_launch.py
+
+# 启动完整的ORB-SLAM系统
+ros2 launch car_slam orbslam_ros_launch.py
+```
+
+### 2. 启动点云建图
+```bash
+# 启动点云建图
+ros2 launch car_slam orbslam_pcl_map_launch.py
+
+# 启动点云八叉树建图
+ros2 launch car_slam orbslam_pcl_octomap_launch.py
+```
+
+### 3. 启动八叉树地图
+```bash
+# 启动八叉树地图服务器
+ros2 launch car_slam octomap_server_launch.py
+
+# 启动相机八叉树建图
+ros2 launch car_slam camera_octomap_launch.py
+```
+
+### 4. 可视化
+```bash
+# 显示点云地图
+ros2 launch car_slam display_pcl_launch.py
+
+# 显示八叉树地图
+ros2 launch car_slam display_octomap_launch.py
+```
+
+### 5. 单独运行点云建图节点
+```bash
+# 运行点云建图节点
+ros2 run car_slam point_cloud_main
+
+# 设置参数
+ros2 param set /pointcloud_mapping use_viewer true
+ros2 param set /pointcloud_mapping resolution 0.05
+```
+
+## 主要功能
+
+### 1. 点云生成
+- 基于RGB-D图像生成彩色点云
+- 支持实时点云生成和处理
+- 自动去除无效点和噪声
+
+### 2. 点云滤波
+- 体素滤波降低点云密度
+- 通过滤波器去除离群点
+- 支持自定义滤波参数
+
+### 3. 点云变换
+- 基于相机位姿变换点云到全局坐标系
+- 支持多帧点云融合
+- 实时更新全局点云地图
+
+### 4. 点云可视化
+- 支持PCL可视化器实时显示
+- 发布ROS点云消息供RViz显示
+- 支持点云保存和加载
+
+### 5. 八叉树建图
+- 将点云转换为八叉树表示
+- 支持占用概率更新
+- 适用于路径规划和碰撞检测
+
+## 依赖项
+- ROS2 (机器人操作系统)
+- PCL (点云处理库)
+- OpenCV (计算机视觉库)
+- Eigen3 (线性代数库)
+- ORB-SLAM2/3 (视觉SLAM算法)
+- OctoMap (八叉树地图库)
+- message_filters (消息同步)
+- cv_bridge (OpenCV与ROS图像转换)
+
+## 注意事项
+1. 确保RGB-D相机正常工作并已校准
+2. 根据实际相机参数修改配置文件
+3. 点云建图需要足够的计算资源
+4. 建图过程中保持相机稳定移动
+5. 定期保存点云地图以防数据丢失
+6. 大规模点云建图时注意内存使用
+7. 八叉树分辨率影响地图精度和存储空间