Merge branch 'master' of https://gitea.star-rising.cn/vcrmn/CheckDevice

Check.Main/Camera/CameraManager.cs

@@ -22,42 +22,29 @@ namespace Check.Main.Camera
     /// <summary>
     /// 静态全局相机管理器，负责所有相机的生命周期、配置应用和多相机同步
     /// </summary>
+    /// 222222
     public static class CameraManager
     {
         //1、相机与UI管理----管理每台相机对象和对应的图像显示窗口。
-        // 活动的相机实例字典（键值对），键 (string)：使用相机的名称，值 (HikvisionCamera)：存储实际的相机实例，{ get; } 创建了一个只读的公共属性
+
         public static Dictionary<string, HikvisionCamera> ActiveCameras { get; } = new Dictionary<string, HikvisionCamera>();
-
-        // 相机对应的图像显示窗口字典
-        //public static Dictionary<string, FormImageDisplay> CameraDisplays { get; } = new Dictionary<string, FormImageDisplay>();
-
         public static Dictionary<string, FormImageDisplay> OriginalImageDisplays { get; } = new Dictionary<string, FormImageDisplay>();//原始图像窗口
         public static Dictionary<string, FormImageDisplay> ResultImageDisplays { get; } = new Dictionary<string, FormImageDisplay>();//结果图像窗口
 
         //2、多相机同步逻辑
-        // 【队列】一个产品需要多台相机拍完，才算完整。
         private static readonly Queue<ProductResult> ProductQueue = new Queue<ProductResult>();
-        // 【（队列）锁】保证队列在多线程下安全
         private static readonly object QueueLock = new object();
-        // 当前启用的相机数量，用于判断产品是否检测完毕
         private static int EnabledCameraCount = 0;
-        //public static event EventHandler<DetectionResultEventArgs> OnDetectionCompleted;
-        // public static bool IsDetectionRunning { get; private set; } = false;
-        // 产品ID【计数器】
         private static long _productCounter = 0;
-        // 用于同步计数器访问的锁，虽然long的自增是原子操作，但为清晰和未来扩展，使用锁是好习惯
         private static readonly object _counterLock = new object();
 
         // 3、--- 新增：硬触发模拟器 ---
         private static readonly System.Timers.Timer _hardwareTriggerSimulator;
-        /// <summary>
+             
-        /// 获取或设置模拟硬触发的间隔时间（毫秒）。
+        // 获取或设置模拟硬触发的间隔时间（毫秒）。
-        /// </summary>
         public static double TriggerInterval { get; set; } = 1000; // 默认1秒触发一次
 
-        /// <summary>
+        // 获取一个值，该值指示硬件触发模拟器当前是否正在运行。
-        /// 获取一个值，该值指示硬件触发模拟器当前是否正在运行。
-        /// </summary>
         public static bool IsHardwareTriggerSimulating { get; private set; } = false;
 
         /// <summary>
@@ -73,93 +60,26 @@ namespace Check.Main.Camera
         }
 
 
-        //// 事件：用于向UI发送日志消息
-        //public static event Action<string> OnLogMessage;
-        //// 用于写入日志文件的 StreamWriter
-        //private static StreamWriter _logFileWriter;
         
-        ////私有的、静态的、只读的对象，专门用作线程同步的“锁”。
-        //private static readonly object _logLock = new object();
-
-        /// <summary>
-        /// 初始化文件日志记录器。应在程序启动时调用一次。
-        /// </summary>
-        //public static void InitializeLogger()
-        //{
-        //    try
-        //    {
-        //        string logDirectory = Path.Combine(Application.StartupPath, "Logs");
-        //        Directory.CreateDirectory(logDirectory); // 确保Logs文件夹存在
-
-        //        string logFileName = $"Log_{DateTime.Now:yyyy-MM-dd_HH-mm-ss}.txt";
-        //        string logFilePath = Path.Combine(logDirectory, logFileName);
-
-        //        // 创建StreamWriter，设置为追加模式和自动刷新
-        //        _logFileWriter = new StreamWriter(logFilePath, append: true, encoding: System.Text.Encoding.UTF8)
-        //        {
-        //            AutoFlush = true
-        //        };
-
-        //        Log("文件日志记录器已初始化。");
-        //    }
-        //    catch (Exception ex)
-        //    {
-        //        // 如果文件日志初始化失败，在UI上报告错误
-        //        OnLogMessage?.Invoke($"[CRITICAL] 文件日志初始化失败: {ex.Message}");
-        //    }
-        //}
-
-        /// <summary>
-        /// 【新增】一个完整的业务流程方法：
-        /// 1. 根据配置初始化所有相机并显示它们的窗口。
-        /// 2. 在所有窗口都显示后，命令所有相机开始采集。
-        /// 这个方法是响应“开启设备”或“应用配置并启动”按钮的理想入口点。
-        /// </summary>
-        /// <param name="settingsList">要应用的相机配置列表。</param>
-        /// <param name="mainForm">主窗体，用于停靠显示窗口。</param>
-        //public static void ApplyConfigurationAndStartGrabbing(List<CameraSettings> settingsList, FrmMain mainForm)
-        //{
-        //    ThreadSafeLogger.Log("开始执行“开启设备”流程...");
-
-        //    // 步骤 1: 初始化所有相机和UI窗口
-        //    // Initialize 方法会负责 Shutdown 旧实例、创建新实例、打开硬件、显示窗口等。
-        //    // 因为 Initialize 方法中的 displayForm.Show() 是非阻塞的，它会立即返回，
-        //    // 窗体的创建和显示过程会被调度到UI线程的消息队列中。
-        //    Initialize(settingsList, mainForm);
-
-        //    // 检查是否有任何相机成功初始化
-        //    if (ActiveCameras.Count == 0)
-        //    {
-        //        ThreadSafeLogger.Log("“开启设备”流程中止，因为没有相机被成功初始化。");
-        //        return;
-        //    }
-
-        //    // 步骤 2: 在 Initialize 完成后（意味着所有窗口都已创建并 Show），开始采集
-        //    // 这个调用会紧接着 Initialize 执行，此时窗体可能还在绘制过程中，但这没关系。
-        //    // StartAll() 会启动后台线程开始拉取图像，一旦图像到达，就会通过事件推送到已经存在的窗体上。
-        //    ThreadSafeLogger.Log("所有相机窗口已创建，现在开始采集图像...");
-        //    StartAll();
-
-        //    ThreadSafeLogger.Log("“开启设备”流程已完成。相机正在采集中。");
-        //}
 
+        ////********************初始化和启动流程*******************
         ///// <summary>
-        ///// 根据配置列表初始化或更新所有相机
+        ///// 准备所有相机硬件、UI窗口和后台处理器，但不开始采集。
+        ///// 这是“启动设备”的第一阶段。
         ///// </summary>
-        //public static void Initialize(List<CameraSettings> settingsList, FrmMain mainForm)
+        //public static void PrepareAll(ProcessConfig config, FrmMain mainForm)//①准备所有相机和模型
         //{
-
+        //    // 1. 清理旧资源和UI
-        //    // 先停止并释放所有旧的相机
+        //    mainForm.ClearStatusStrip();
         //    Shutdown();
-        //    ThreadSafeLogger.Log("开始应用新的相机配置...");
+        //    ThreadSafeLogger.Log("开始准备设备和模型...");
 
-        //    EnabledCameraCount = settingsList.Count(s => s.IsEnabled);
+        //    // 2. 初始化检测协调器和AI模型
-        //    if (EnabledCameraCount == 0)
+        //    // 注意：YoloModelManager 的 Initialize 现在也应在这里被调用，以确保逻辑集中
-        //    {
+        //    YoloModelManager.Initialize(config.ModelSettings);
-        //        ThreadSafeLogger.Log("没有启用的相机。");
+        //    DetectionCoordinator.Initialize(config.CameraSettings, config.ModelSettings);
-        //        return;
-        //    }
 
+        //    // 3. 创建相机硬件实例和UI窗口------
         //    var deviceList = new HikvisionCamera().FindDevices();
         //    if (deviceList.Count == 0)
         //    {
@@ -167,19 +87,9 @@ namespace Check.Main.Camera
         //        return;
         //    }
 
-        //    int deviceIndex = 0;
+        //    foreach (var setting in config.CameraSettings.Where(s => s.IsEnabled))//打开相机 → 设置触发模式 → 绑定事件（图像采集、检测完成）。
-        //    foreach (var setting in settingsList)
         //    {
-        //        if (!setting.IsEnabled) continue;
+        //        var cam = new HikvisionCamera { Name = setting.Name, CameraIndex = setting.CameraIndex };
-
-        //        if (deviceIndex >= deviceList.Count)
-        //        {
-        //            ThreadSafeLogger.Log($"警告：相机配置'{setting.Name}'无法分配物理设备，因为设备数量不足。");
-        //            continue;
-        //        }
-
-        //        // --- 创建相机实例 ---
-        //        var cam = new HikvisionCamera { Name = setting.Name };
         //        cam.TriggerMode = setting.TriggerMode;
         //        if (!cam.Open(setting))
         //        {
@@ -203,40 +113,38 @@ namespace Check.Main.Camera
 
         //        // --- 订阅事件 ---
         //        cam.ImageAcquired += OnCameraImageAcquired;
-        //        cam.CameraMessage += (sender, msg, err) => ThreadSafeLogger.Log($"{(sender as HikvisionCamera).Name}: {msg}");
+        //        var processor = DetectionCoordinator.GetProcessor(cam.CameraIndex);
-
+        //        if (processor != null) { processor.OnProcessingCompleted += Processor_OnProcessingCompleted; }
-        //        // --- 创建显示窗口 ---
-        //        var displayForm = new FormImageDisplay { Text = setting.Name, CameraName = setting.Name };
-        //        displayForm.OnDisplayEvent += ThreadSafeLogger.Log;
-        //        displayForm.Show(mainForm.MainDockPanel, WeifenLuo.WinFormsUI.Docking.DockState.Document);
 
+        //        // --- 创建【但不显示】图像的UI窗口 ---
+        //        var originalDisplay = new FormImageDisplay { Text = $"{setting.Name} - 原图", CameraName = setting.Name };
+        //        var resultDisplay = new FormImageDisplay { Text = $"{setting.Name} - 结果", CameraName = setting.Name };
+        //        originalDisplay.Show(mainForm.MainDockPanel, WeifenLuo.WinFormsUI.Docking.DockState.Document);
+        //        resultDisplay.Show(mainForm.MainDockPanel, WeifenLuo.WinFormsUI.Docking.DockState.Document);
 
+        //        // --- 保存引用 ---
         //        ActiveCameras.Add(setting.Name, cam);
-        //        CameraDisplays.Add(setting.Name, displayForm);
+        //        OriginalImageDisplays.Add(setting.Name, originalDisplay);
+        //        ResultImageDisplays.Add(setting.Name, resultDisplay);
         //        mainForm.AddCameraToStatusStrip(setting.Name);
-        //        ThreadSafeLogger.Log($"相机'{setting.Name}'初始化成功，分配到物理设备 {deviceIndex}。");
-        //        deviceIndex++;
         //    }
+        //    ThreadSafeLogger.Log("所有设备和模型已准备就绪。");
         //}
 
-        //********************初始化和启动流程*******************
         /// <summary>
         /// 准备所有相机硬件、UI窗口和后台处理器，但不开始采集。
         /// 这是“启动设备”的第一阶段。
         /// </summary>
-        public static void PrepareAll(ProcessConfig config, FrmMain mainForm)//①准备所有相机和模型
+        public static void PrepareAll(ProcessConfig config, FrmMain mainForm)
         {
-            // 1. 清理旧资源和UI
+            mainForm.ClearStatusStrip(); // 清理旧的状态条
-            mainForm.ClearStatusStrip();
+            Shutdown(); // 清理旧的相机和协调器资源
-            Shutdown();
             ThreadSafeLogger.Log("开始准备设备和模型...");
 
-            // 2. 初始化检测协调器和AI模型
+            // 1. 初始化检测协调器和AI模型（此步骤会加载YOLO模型并创建CameraProcessor）
-            // 注意：YoloModelManager 的 Initialize 现在也应在这里被调用，以确保逻辑集中
-            YoloModelManager.Initialize(config.ModelSettings);
             DetectionCoordinator.Initialize(config.CameraSettings, config.ModelSettings);
 
-            // 3. 创建相机硬件实例和UI窗口------
+            // 2. 创建相机硬件实例和UI窗口
             var deviceList = new HikvisionCamera().FindDevices();
             if (deviceList.Count == 0)
             {
@@ -244,8 +152,15 @@ namespace Check.Main.Camera
                 return;
             }
 
-            foreach (var setting in config.CameraSettings.Where(s => s.IsEnabled))//打开相机 → 设置触发模式 → 绑定事件（图像采集、检测完成）。
+            int deviceIndex = 0;
+            foreach (var setting in config.CameraSettings.Where(s => s.IsEnabled))
             {
+                if (deviceIndex >= deviceList.Count)
+                {
+                    ThreadSafeLogger.Log($"警告：相机配置'{setting.Name}'无法分配物理设备，因为设备数量不足。");
+                    continue;
+                }
+
                 var cam = new HikvisionCamera { Name = setting.Name, CameraIndex = setting.CameraIndex };
                 cam.TriggerMode = setting.TriggerMode;
                 if (!cam.Open(setting))
@@ -270,12 +185,26 @@ namespace Check.Main.Camera
 
                 // --- 订阅事件 ---
                 cam.ImageAcquired += OnCameraImageAcquired;
-                var processor = DetectionCoordinator.GetProcessor(cam.CameraIndex);
+                cam.CameraMessage += (sender, msg, err) => ThreadSafeLogger.Log($"{(sender as HikvisionCamera).Name}: {msg}");
-                if (processor != null) { processor.OnProcessingCompleted += Processor_OnProcessingCompleted; }
 
-                // --- 创建【但不显示】图像的UI窗口 ---
+                // 获取 CameraProcessor 并订阅其完成事件
+                var processor = DetectionCoordinator.GetProcessor(cam.CameraIndex);
+                if (processor != null)
+                {
+                    processor.OnProcessingCompleted += Processor_OnProcessingCompleted;
+                }
+                else
+                {
+                    ThreadSafeLogger.Log($"[警告] 未能为相机 '{setting.Name}' (Index: {setting.CameraIndex}) 获取处理器，检测结果将不会显示。");
+                }
+
+
+                // --- 创建【并显示】图像的UI窗口 ---
                 var originalDisplay = new FormImageDisplay { Text = $"{setting.Name} - 原图", CameraName = setting.Name };
                 var resultDisplay = new FormImageDisplay { Text = $"{setting.Name} - 结果", CameraName = setting.Name };
+                originalDisplay.OnDisplayEvent += ThreadSafeLogger.Log;
+                resultDisplay.OnDisplayEvent += ThreadSafeLogger.Log;
+
                 originalDisplay.Show(mainForm.MainDockPanel, WeifenLuo.WinFormsUI.Docking.DockState.Document);
                 resultDisplay.Show(mainForm.MainDockPanel, WeifenLuo.WinFormsUI.Docking.DockState.Document);
 
@@ -284,6 +213,8 @@ namespace Check.Main.Camera
                 OriginalImageDisplays.Add(setting.Name, originalDisplay);
                 ResultImageDisplays.Add(setting.Name, resultDisplay);
                 mainForm.AddCameraToStatusStrip(setting.Name);
+                ThreadSafeLogger.Log($"相机'{setting.Name}'初始化成功，分配到物理设备 {deviceIndex}。");
+                deviceIndex++;
             }
             ThreadSafeLogger.Log("所有设备和模型已准备就绪。");
         }
@@ -507,8 +438,6 @@ namespace Check.Main.Camera
             // 3. 关闭检测协调器，它会负责清理所有后台线程和队列
             DetectionCoordinator.Shutdown();
 
-            YoloModelManager.Shutdown();
-
             ThreadSafeLogger.Log("所有相机及协调器资源已释放。");
         }
 
@@ -517,10 +446,11 @@ namespace Check.Main.Camera
         /// </summary>
         public static void ResetProductCounter()
         {
-            lock (_counterLock)
+            //lock (_counterLock)
-            {
+            //{
-                _productCounter = 0;
+            //    _productCounter = 0;
-            }
+            //}
+            DetectionCoordinator.ResetAllCounters(); // 调用协调器的重置方法            
             ThreadSafeLogger.Log("产品计数器已重置。");
         }
 
@@ -620,6 +550,7 @@ namespace Check.Main.Camera
         //}
 
         //【相机回调】
+        // 【相机回调】现在只负责图像分发
         private static void OnCameraImageAcquired(HikvisionCamera sender, Bitmap bmp)
         {
             Bitmap bmpForDisplay = null;
@@ -627,66 +558,51 @@ namespace Check.Main.Camera
 
             try
             {
-                // 1. 深度克隆 Bitmap → 分成 显示副本 和 处理副本。
                 bmpForDisplay = DeepCloneBitmap(bmp, "Display");
                 bmpForProcessing = DeepCloneBitmap(bmp, "Processing");
             }
             finally
             {
-                // 2.无论克隆成功与否，都必须立即释放事件传递过来的原始bmp，防止泄漏。
+                bmp?.Dispose();
-                bmp?.Dispose();//空条件运算符 ?.-----在访问对象成员前检查对象是否为 null，如果 bmp 不是 null，则正常调用 Dispose() 方法，替代传统的 if (bmp != null) 检查
             }
-            // 分支 A: 显示副本 → 交给 FormImageDisplay.UpdateImage()。
+
             if (bmpForDisplay != null && OriginalImageDisplays.TryGetValue(sender.Name, out var displayWindow))
             {
-                // displayWindow.UpdateImage 会处理线程安全问题
                 displayWindow.UpdateImage(bmpForDisplay);
             }
             else
             {
-                // 如果没有对应的显示窗口，或克隆失败，必须释放为显示创建的副本
                 bmpForDisplay?.Dispose();
             }
-            // 分支 B: 处理副本 → 交给 DetectionCoordinator.EnqueueImage() 进行检测。
+
+            // 直接将处理副本和相机编号交给 DetectionCoordinator
             if (bmpForProcessing != null)
             {
-                // bmpForProcessing 的所有权在这里被转移给了协调器
                 DetectionCoordinator.EnqueueImage(sender.CameraIndex, bmpForProcessing);
             }
-            //// 深度克隆图像以确保线程安全
-            //Bitmap bmpForProcessing = DeepCloneBitmap(bmp, "Processing");
-            //bmp?.Dispose(); // 立即释放原始图
-
-            //// 直接将图像和相机编号交给协调器，无需任何本地处理
-            //DetectionCoordinator.EnqueueImage(sender.CameraIndex, bmpForProcessing);
         }
-        // 事件处理器
+
+        // 事件处理器：从 CameraProcessor 接收带有结果的图像
         private static void Processor_OnProcessingCompleted(object sender, ProcessingCompletedEventArgs e)
         {
-
-            // 1. 找到与此相机匹配的相机名称
             var cameraEntry = ActiveCameras.FirstOrDefault(kvp => kvp.Value.CameraIndex == e.CameraIndex);
             if (cameraEntry.Key == null)
             {
-                e.Dispose(); // 如果找不到接收者，必须释放事件参数中的图像
+                e.Dispose();
                 return;
             }
-            // 2. 找到此相机的结果显示窗口
+
             if (ResultImageDisplays.TryGetValue(cameraEntry.Key, out var resultDisplay))
             {
-                //var bmp = ConvertSKImageToBitmap(e.ResultImage);
                 if (e.ResultImage != null)
                 {
-                    // UpdateImage 会负责克隆并显示，所以这里传递 bmp 即可
                     resultDisplay.UpdateImage(e.ResultImage);
                 }
             }
             else
             {
-                // 如果找到了相机但没有对应的结果窗口，也要释放图像
                 e.Dispose();
             }
-
         }
 
         /// <summary>
@@ -808,32 +724,6 @@ namespace Check.Main.Camera
 
             return clone;
         }
-
-        // 触发日志事件的辅助方法
-        //public static void Log(string message)
-        //{
-        //    string formattedMessage = $"[{DateTime.Now:HH:mm:ss.fff}] {message}";
-
-        //    // 1. 触发事件，更新UI
-        //    OnLogMessage?.Invoke(formattedMessage);
-
-        //    // 2. 【关键修改】在写入文件前，先获取锁。
-        //    // lock 语句块确保了花括号内的代码在同一时间只能被一个线程执行。
-        //    // 如果另一个线程也想执行这段代码，它必须等待前一个线程执行完毕并释放锁。
-        //    lock (_logLock)
-        //    {
-        //        try
-        //        {
-        //            _logFileWriter?.WriteLine(formattedMessage);
-        //        }
-        //        catch (Exception)
-        //        {
-        //            // 即使有锁，也保留try-catch以防万一（如磁盘满了等IO问题）。
-        //            // 可以在这里决定是否要在UI上显示警告。
-        //        }
-        //    }
-        //}
-
     }
 
 }

Check.Main/Camera/CameraProcessor.cs

@@ -12,13 +12,15 @@ using System.Text;
 using System.Threading.Tasks;
 using YoloDotNet.Extensions;
 using OpenCvSharp;
+using Check.Main.Infer; // 引入 IDetector, DetectionResult
+
 namespace Check.Main.Camera
 {
     public class CameraProcessor : IDisposable
     {
         private readonly int _cameraIndex;
-        private readonly int _modeId;
+        private readonly IDetector _detector; // 替换为接口
-        // private readonly ModelSettings _model;
+        private readonly ModelSettings _modelSettings; // 保留模型设置以获取更多参数
         private readonly BlockingCollection<ImageData> _imageQueue = new BlockingCollection<ImageData>();
         private readonly Thread _workerThread;
         private volatile bool _isRunning = false;
@@ -28,11 +30,12 @@ namespace Check.Main.Camera
         public event EventHandler<ProcessingCompletedEventArgs> OnProcessingCompleted;
 
 
-        public CameraProcessor(int cameraIndex, int modelId)//, ModelSettings model
+        // 构造函数现在接受 IDetector 实例和 ModelSettings
+        public CameraProcessor(int cameraIndex, IDetector detector, ModelSettings modelSettings)
         {
             _cameraIndex = cameraIndex;
-            _modeId = modelId;
+            _detector = detector ?? throw new ArgumentNullException(nameof(detector));
-            //_model = model;
+            _modelSettings = modelSettings ?? throw new ArgumentNullException(nameof(modelSettings));
             _workerThread = new Thread(ProcessQueue) { IsBackground = true, Name = $"Cam_{_cameraIndex}_Processor" };
         }
 
@@ -42,15 +45,16 @@ namespace Check.Main.Camera
             _workerThread.Start();
         }
 
-        public void EnqueueImage(Bitmap bmp)
+        public void EnqueueImage(Bitmap bmp, long productId) // 接收产品ID
         {
             if (!_isRunning)
             {
                 bmp?.Dispose();
                 return;
             }
-            _imageCounter++;
+            // _imageCounter 在此用于内部跟踪，不是产品ID
-            _imageQueue.Add(new ImageData(_imageCounter, _cameraIndex, bmp));
+            // 产品ID现在由 DetectionCoordinator 生成并传递
+            _imageQueue.Add(new ImageData(productId, _cameraIndex, bmp));
         }
 
         /// <summary>
@@ -58,42 +62,38 @@ namespace Check.Main.Camera
         /// </summary>
         private void ProcessQueue()
         {
-            //// 从模型管理器获取此线程专属的YOLO模型
+
-            //var yoloModel = YoloModelManager.GetModel(_modeId);
+            ThreadSafeLogger.Log($"相机#{_cameraIndex} 启动处理线程，算法类型：{_modelSettings.M_AType}");
-            //if (yoloModel == null)
+
+            ////训练HALCON模型
+            ////训练阶段（相机2）
+            //var trainer = new LogoTemplateTrainer();
+
+            //trainer.TrainAndSaveTemplates(
+            //    new List<string>
             //    {
-            //    ThreadSafeLogger.Log($"[错误] 相机 #{_modeId} 无法获取对应的YOLO模型，处理线程已中止。");
+            //    @"D:\HalconTemplateMatch\train2\logo1.bmp",
-            //    return; // 如果没有模型，此线程无法工作
+            //    @"D:\HalconTemplateMatch\train2\logo2.bmp",
+            //    @"D:\HalconTemplateMatch\train2\logo3.bmp"
+            //    },
+            //    @"D:\HalconTemplateMatch\model_2");
+
+            ////训练阶段（相机3）9.25修改！！
+            //trainer.TrainAndSaveTemplates(
+            //   new List<string>
+            //   {
+            //    @"D:\HalconTemplateMatch\train3\3C_1.bmp",
+            //    @"D:\HalconTemplateMatch\train3\3C_2.bmp",
+            //    @"D:\HalconTemplateMatch\train3\3C_3.bmp"
+            //   },
+            //   @"D:\HalconTemplateMatch\model_3");
+
+            //if (trainer == null)
+            //{
+            //    ThreadSafeLogger.Log($"[错误] 相机 #{_modeId} 未加载模板，处理线程已中止。");
+            //    return;
             //}
 
-            //训练阶段（相机2）
-            var trainer = new LogoTemplateTrainer();
-
-            trainer.TrainAndSaveTemplates(
-                new List<string>
-                {
-                @"D:\HalconTemplateMatch\train2\logo1.bmp",
-                @"D:\HalconTemplateMatch\train2\logo2.bmp",
-                @"D:\HalconTemplateMatch\train2\logo3.bmp"
-                },
-                @"D:\HalconTemplateMatch\model_2");
-
-            //训练阶段（相机3）9.25修改！！
-            trainer.TrainAndSaveTemplates(
-               new List<string>
-               {
-                @"D:\HalconTemplateMatch\train3\3C_1.bmp",
-                @"D:\HalconTemplateMatch\train3\3C_2.bmp",
-                @"D:\HalconTemplateMatch\train3\3C_3.bmp"
-               },
-               @"D:\HalconTemplateMatch\model_3");
-
-            if (trainer == null)
-            {
-                ThreadSafeLogger.Log($"[错误] 相机 #{_modeId} 未加载模板，处理线程已中止。");
-                return;
-            }
-
 
             while (_isRunning)
             {
@@ -103,116 +103,23 @@ namespace Check.Main.Camera
                     ImageData data = _imageQueue.Take();
                     using (data)
                     {
-
-                        //using (var skImage = ConvertBitmapToSKImage(data.Image)) // 转换图像格式并管理其生命周期
-                        //{
-                        //    if (skImage == null) continue;
-                        //    var predictions = yoloModel.RunObjectDetection(skImage);
-                        //    string result = predictions.Any() ? "NG" : "OK";
-
-                        //    ThreadSafeLogger.Log($"相机 #{_cameraIndex} 处理产品 #{data.ProductId}，检测到 {predictions.Count} 个目标，结果: {result}");
-
-                        //    // 将处理结果交给协调器进行组装
-                        //    DetectionCoordinator.AssembleProduct(data, result);
-
-                        //    if (OnProcessingCompleted != null)
-                        //    {
-                        //        using (var resultSkImage = skImage.Draw(predictions))
-                        //        {
-                        //            // 4. 触发事件，将绘制好的 resultSkImage 传递出去
-                        //            // 所有权在这里被转移
-                        //            OnProcessingCompleted?.Invoke(this, new ProcessingCompletedEventArgs(
-                        //                _cameraIndex,
-                        //                data.ProductId,
-                        //                resultSkImage
-                        //            ));
-                        //        }
-                        //    }
-                        //}
-
-                        //***********************************使用Halcon模板匹配进行检测****************************************************
                         if (data.Image == null) continue;
-                        // 统一定义预测结果
-                        var matcher = new LogoMatcher();
 
-                        //9.25（增加一根据不同的相机编号调用不同的模型！）
+                        DetectionResult detectionResult = _detector.Detect(data.Image);
-                        string filepath = "";
+                        ThreadSafeLogger.Log($"相机 #{_cameraIndex} 处理产品 #{data.ProductId}，结果: {(detectionResult.IsOk ? "OK" : "NG")}, 信息: {detectionResult.Message}, 得分: {detectionResult.Score:F2}");
-                        if (_cameraIndex == 2)
-                        {
-                            matcher.LoadTemplates(@"D:\HalconTemplateMatch\model_2");
-                            filepath = "D:\\HalconTemplateMatch\\train2";
-                        }
-                        else if (_cameraIndex == 3)
-                        {
-                            matcher.LoadTemplates(@"D:\HalconTemplateMatch\model_3");
-                            filepath = "D:\\HalconTemplateMatch\\train3";
-                        }
-
-                        ////原bool返回的处理
-                        //bool found = matcher.FindLogo(data.Image);
-                        //string result = found ? "OK":"NG";
-
-                        //double返回的处理
-                        double score = matcher.FindLogo(data.Image);
-                         
-
-                        //Mat cam = ProcessImg.BitmapToMat(data.Image);
-                        
-                        //score= ProcessImg.ProcessImagesInFolder(filepath,cam);
-
-                        string result = (score > 0.5) ? "OK" : "NG";
-
-                        ThreadSafeLogger.Log($"相机 #{_cameraIndex} 处理产品 #{data.ProductId}，结果: {result},得分: {score}");
 
                         // 将处理结果交给协调器进行组装
-                        DetectionCoordinator.AssembleProduct(data, result);
+                        DetectionCoordinator.AssembleProduct(data.ProductId, data.CameraIndex, detectionResult.IsOk, detectionResult.ResultImage);
               
 
-                        //给PLC的M90、M91写值（10.10）
+                        // 外部订阅事件，传递结果图像
-                        if (FrmMain.PlcClient != null)
-                        {
-                            if (result == "OK")
-                            {
-                                //吹气到合格框
-                                FrmMain.PlcClient.WriteBool("90", true); // 写入M90为1
-                                // 延时复位
-                                Task.Run(async () =>
-                                {
-                                    //await Task.Delay(300); // 延时300毫秒，可根据实际气动时间调整
-                                    //await FrmMain.PlcClient.WriteAsync("M90", 0);
-                                });
-                            }
-                            else
-                            {
-                                //吹气到不合格框
-                                FrmMain.PlcClient.WriteBool("91", true);// 写入M91为1
-                                // 延时复位
-                                Task.Run(async () =>
-                                {
-                                    //await Task.Delay(300);
-                                    //await FrmMain.PlcClient.WriteAsync("M91", 0);
-                                });
-                            }
-                            //完成一次检测进行刷新
-                            Thread.Sleep(2000);
-                            FrmMain.PlcClient.WriteBool("90", false); // 
-                            FrmMain.PlcClient.WriteBool("91", false); // 写入M90为1
-
-                        }
-                        else
-                        {
-                            ThreadSafeLogger.Log("6，跳过写入。");
-                        }
-
-
-                        // ③ 外部订阅事件
                         OnProcessingCompleted?.Invoke(
                             this,
                             new ProcessingCompletedEventArgs
                             (
                                 _cameraIndex,
                                 data.ProductId,
-                                data.Image // 原图传出去
+                                detectionResult.ResultImage // 传递带有绘制结果的图像
                             )
                         );
                     }
@@ -252,6 +159,7 @@ namespace Check.Main.Camera
         }
         public static SKBitmap ToSKBitmapFast(Bitmap bitmap)
         {
+            if (bitmap == null) return null;
             // 确保是 32bppArgb（BGRA 内存布局）
             Bitmap src = bitmap;
             if (bitmap.PixelFormat != PixelFormat.Format32bppArgb)
@@ -298,13 +206,15 @@ namespace Check.Main.Camera
                 }
             }
         }
+
         public void Stop()
         {
             _isRunning = false;
             // 解除阻塞，让线程可以检查 _isRunning 标志并退出
             _imageQueue.CompleteAdding();
-            _workerThread.Join(500); // 等待线程结束
+            _workerThread.Join(5000); // 等待线程结束。10.22修改，原来是500
         }
+
         /// <summary>
         /// 线程安全地重置该相机的图像计数器。
         /// </summary>
@@ -322,6 +232,27 @@ namespace Check.Main.Camera
         {
             Stop();
             _imageQueue.Dispose();
+            _detector?.Dispose(); // 释放检测器资源
+        }
+
+    }
+
+    public class ProcessingCompletedEventArgs : EventArgs, IDisposable
+    {
+        public int CameraIndex { get; }
+        public long ProductId { get; }
+        public Bitmap ResultImage { get; } // 新增：带有检测结果的图像
+
+        public ProcessingCompletedEventArgs(int cameraIndex, long productId, Bitmap resultImage)
+        {
+            CameraIndex = cameraIndex;
+            ProductId = productId;
+            ResultImage = resultImage;
+        }
+
+        public void Dispose()
+        {
+            ResultImage?.Dispose();
         }
     }
 

Check.Main/Check.Main.csproj

@@ -39,7 +39,7 @@
       <HintPath>..\..\..\HslCommunication-master\HslCommunication.dll</HintPath>
     </Reference>
     <Reference Include="MvCameraControl.Net">
-      <HintPath>..\..\XKRS2025\CheckDevice\Check.Main\bin\Debug\MvCameraControl.Net.dll</HintPath>
+      <HintPath>C:\Program Files (x86)\MVS\Development\DotNet\win64\MvCameraControl.Net.dll</HintPath>
     </Reference>
   </ItemGroup>
 

Check.Main/Common/LogoMatcher.cs

@@ -158,6 +158,9 @@ namespace HalconTemplateMatch
     {
         private readonly List<HTuple> modelHandles = new List<HTuple>();
 
+        // 构造函数用于初始化
+        public LogoMatcher() { }
+
         /// <summary>
         /// 从指定目录加载所有 .shm 模板文件
         /// </summary>
@@ -207,33 +210,80 @@ namespace HalconTemplateMatch
             }
         }
 
-        /// <summary>
+        //        /// <summary>
-        /// 匹配并返回最高得分（double返回）
+        //        /// 匹配并返回最高得分（double返回）
-        /// </summary>
+        //        /// </summary>
-        public double FindLogo(Bitmap bmp)
+        //        public double FindLogo(Bitmap bmp)
+        //        {
+        //            if (modelHandles.Count == 0)
+        //            {
+        //                Console.WriteLine("[警告] 尚未加载任何模板。");
+        //                return -1;
+        //            }
+
+        //            // Bitmap 转 Halcon 对象
+        //            HObject ho_TestImage;
+        //            Bitmap2HObject(bmp, out ho_TestImage);
+        //            HOperatorSet.Rgb1ToGray(ho_TestImage, out ho_TestImage);
+
+        //            double bestScore = -1;
+
+        //            foreach (var modelID in modelHandles)
+        //            {
+        //                try
+        //                {
+        //                    HOperatorSet.FindScaledShapeModel(
+        //    ho_TestImage,
+        //    modelID,
+        //    new HTuple(0).TupleRad(),
+        //    new HTuple(360).TupleRad(),
+        //    0.8, 1.2,
+        //    0.5, 1, 0.5,
+        //    "least_squares_high",
+        //    0, 0.9,
+        //    out HTuple row, out HTuple col, out HTuple angle, out HTuple scale, out HTuple score
+        //);
+
+
+        //                    if (score.Length > 0 && score[0].D > bestScore)
+        //                        bestScore = score[0].D;
+        //                }
+        //                catch (HOperatorException ex)
+        //                {
+        //                    Console.WriteLine($"[错误] 模板匹配失败: {ex.Message}");
+        //                }
+        //            }
+
+        //            ho_TestImage.Dispose();
+        //            return bestScore;
+        //        }
+
+        public double FindLogo(Bitmap bmp, out Bitmap resultImage) // 返回结果图像
         {
             if (modelHandles.Count == 0)
             {
                 Console.WriteLine("[警告] 尚未加载任何模板。");
+                resultImage = (Bitmap)bmp.Clone();
                 return -1;
             }
 
-            // Bitmap 转 Halcon 对象
             HObject ho_TestImage;
             Bitmap2HObject(bmp, out ho_TestImage);
             HOperatorSet.Rgb1ToGray(ho_TestImage, out ho_TestImage);
 
             double bestScore = -1;
+            HTuple bestRow = new HTuple(), bestCol = new HTuple(), bestAngle = new HTuple(), bestScale = new HTuple();
+            int bestModelIndex = -1;
 
-            foreach (var modelID in modelHandles)
+            for (int i = 0; i < modelHandles.Count; i++)
             {
+                var modelID = modelHandles[i];
                 try
                 {
                     HOperatorSet.FindScaledShapeModel(
                         ho_TestImage,
                         modelID,
-    new HTuple(0).TupleRad(),
+                        new HTuple(0).TupleRad(), new HTuple(360).TupleRad(),
-    new HTuple(360).TupleRad(),
                         0.8, 1.2,
                         0.5, 1, 0.5,
                         "least_squares_high",
@@ -241,20 +291,150 @@ namespace HalconTemplateMatch
                         out HTuple row, out HTuple col, out HTuple angle, out HTuple scale, out HTuple score
                     );
 
-
                     if (score.Length > 0 && score[0].D > bestScore)
+                    {
                         bestScore = score[0].D;
+                        bestRow = row;
+                        bestCol = col;
+                        bestAngle = angle;
+                        bestScale = scale;
+                        bestModelIndex = i;
+                    }
                 }
                 catch (HOperatorException ex)
                 {
-                    Console.WriteLine($"[错误] 模板匹配失败: {ex.Message}");
+                    //Console.WriteLine($"[错误] 模板匹配失败: {ex.Message}"); // 避免过多日志
                 }
             }
 
+            resultImage = DrawHalconResults(bmp, bestModelIndex >= 0 ? modelHandles[bestModelIndex] : new HTuple(), bestRow, bestCol, bestAngle, bestScale, bestScore);
+
             ho_TestImage.Dispose();
             return bestScore;
         }
 
+        //private Bitmap DrawHalconResults(Bitmap originalBmp, HTuple modelID, HTuple row, HTuple col, HTuple angle, HTuple scale, double score)
+        //{
+        //    Bitmap drawnBmp = (Bitmap)originalBmp.Clone();
+        //    if (score <= 0 || modelID.Length == 0) return drawnBmp; // 未找到或分数过低不绘制
+
+        //    using (Graphics g = Graphics.FromImage(drawnBmp))
+        //    {
+        //        Pen pen = (score > 0.7) ? new Pen(Color.Green, 3) : new Pen(Color.Orange, 3); // 可以根据分数改变颜色
+        //        Font font = new Font("Arial", 12, FontStyle.Bold);
+        //        Brush brush = (score > 0.7) ? new SolidBrush(Color.Green) : new SolidBrush(Color.Orange);
+
+        //        // 获取匹配模板的轮廓
+        //        HOperatorSet.GetShapeModelContours(out HObject modelContours, modelID, 1);
+
+        //        // 转换到图像坐标
+        //        HOperatorSet.AffineTransContourXld(modelContours, out HObject transformedContours,
+        //            new HTuple(angle), new HTuple(scale), new HTuple(row), new HTuple(col),
+        //            "fit_origin"); // 假设 FindScaledShapeModel 的 row/col 是中心
+
+        //        // 绘制 XLD 轮廓
+        //        HTuple numContours;
+        //        HOperatorSet.CountObj(transformedContours, out numContours);
+
+        //        for (int i = 1; i <= numContours; i++)
+        //        {
+        //            HOperatorSet.SelectObj(transformedContours, out HObject currentContour, i);
+        //            HOperatorSet.GetContourXld(currentContour, out HTuple contourRow, out HTuple contourCol);
+
+        //            if (contourRow.Length > 1)
+        //            {
+        //                Point[] points = new Point[contourRow.Length];
+        //                for (int j = 0; j < contourRow.Length; j++)
+        //                {
+        //                    points[j] = new Point((int)contourCol.DArr[j], (int)contourRow.DArr[j]);
+        //                }
+        //                g.DrawPolygon(pen, points);
+        //            }
+        //            currentContour.Dispose();
+        //        }
+
+        //        // 绘制得分
+        //        if (row.Length > 0 && col.Length > 0)
+        //        {
+        //            g.DrawString($"Score: {score:F2}", font, brush, (float)col.D - 50, (float)row.D - 50);
+        //        }
+
+        //        modelContours.Dispose();
+        //        transformedContours.Dispose();
+        //    }
+        //    return drawnBmp;
+        //}
+
+        private Bitmap DrawHalconResults(Bitmap originalBmp, HTuple modelID, HTuple row, HTuple col, HTuple angle, HTuple scale, double score)
+        {
+            // 克隆输入图像用于绘制
+            Bitmap drawnBmp = (Bitmap)originalBmp.Clone();
+
+            // 如果未找到匹配，不绘制任何内容
+            if (score <= 0 || modelID.Length == 0)
+                return drawnBmp;
+
+            using (Graphics g = Graphics.FromImage(drawnBmp))
+            {
+                // 绘制样式：高分绿色、低分橙色
+                Pen pen = (score > 0.7) ? new Pen(Color.Green, 3) : new Pen(Color.Orange, 3);
+                Font font = new Font("Arial", 12, FontStyle.Bold);
+                Brush brush = (score > 0.7) ? new SolidBrush(Color.Green) : new SolidBrush(Color.Orange);
+
+                // 1️⃣ 获取模板的轮廓
+                HOperatorSet.GetShapeModelContours(out HObject modelContours, modelID, 1);
+
+                // 2️⃣ 构建仿射变换矩阵
+                HTuple homMat2D;
+                HOperatorSet.HomMat2dIdentity(out homMat2D);                                     // 初始化单位矩阵
+                HOperatorSet.HomMat2dScale(homMat2D, scale, scale, 0, 0, out homMat2D);          // 缩放
+                HOperatorSet.HomMat2dRotate(homMat2D, angle, 0, 0, out homMat2D);                // 旋转
+                HOperatorSet.HomMat2dTranslate(homMat2D, col, row, out homMat2D);                // 平移
+
+                // 3️⃣ 将轮廓按仿射矩阵变换
+                HOperatorSet.AffineTransContourXld(modelContours, out HObject transformedContours, homMat2D);
+
+                // 4️⃣ 统计轮廓数量并逐一绘制
+                HOperatorSet.CountObj(transformedContours, out HTuple numContours);
+
+                for (int i = 1; i <= numContours; i++)
+                {
+                    HOperatorSet.SelectObj(transformedContours, out HObject currentContour, i);
+                    HOperatorSet.GetContourXld(currentContour, out HTuple contourRow, out HTuple contourCol);
+
+                    if (contourRow.Length > 1)
+                    {
+                        Point[] points = new Point[contourRow.Length];
+                        for (int j = 0; j < contourRow.Length; j++)
+                        {
+                            points[j] = new Point((int)contourCol[j].D, (int)contourRow[j].D);
+                        }
+                        g.DrawPolygon(pen, points);
+                    }
+                    currentContour.Dispose();
+                }
+
+                // 5️⃣ 绘制得分文字
+                if (row.Length > 0 && col.Length > 0)
+                {
+                    g.DrawString($"Score: {score:F2}", font, brush, (float)col.D - 50, (float)row.D - 50);
+                }
+
+                // 6️⃣ 清理资源
+                modelContours.Dispose();
+                transformedContours.Dispose();
+
+                // 释放 GDI+ 对象
+                pen.Dispose();
+                font.Dispose();
+                brush.Dispose();
+            }
+
+            return drawnBmp;
+        }
+
+
+
         /// <summary>
         /// Bitmap 转 Halcon HObject
         /// </summary>

Check.Main/Common/PLC_Control_Base.cs

@@ -2,13 +2,13 @@
 using HslCommunication.ModBus;
 using System;
 using System.Net.Sockets;
-//
+
 // ModbusTcp读写服务类，线程安全，互斥锁
 namespace Check.Main.Common
 {
     public class ModbusTcpService
     {
-        private readonly TcpClient _tcpClient = new();//
+        private readonly TcpClient _tcpClient = new();
         private readonly ModbusTcpNet _plc;
         private readonly object _lock = new();
         public bool IsConnected => _tcpClient != null && _tcpClient.Connected;//

Check.Main/Infer/DetectionCoordinator.cs

@@ -25,6 +25,8 @@ namespace Check.Main.Infer
         /// </summary>
         private static int _enabledCameraCount = 0;
 
+        private static long _productCounter = 0; // 新增产品计数器10.22
+
         public static event EventHandler<DetectionResultEventArgs> OnDetectionCompleted;
         public static bool IsDetectionRunning { get; private set; } = false;
 
@@ -51,72 +53,220 @@ namespace Check.Main.Infer
         public static void Initialize(List<CameraSettings> cameraSettings, List<ModelSettings> modelSettings)
         {
             Shutdown(); // 先关闭旧的
+            YoloModelManager.Initialize(modelSettings); // 确保 YOLO 模型在初始化协调器时加载。10.22新增
+
             var enabledCameras = cameraSettings.Where(c => c.IsEnabled).ToList();
             _enabledCameraCount = enabledCameras.Count;
-            if (_enabledCameraCount == 0) return;
+            //if (_enabledCameraCount == 0) return;
+            if (_enabledCameraCount == 0)
+            {
+                ThreadSafeLogger.Log("没有启用的相机，检测协调器未初始化。");
+                return;
+            }
 
             foreach (var camSetting in enabledCameras)
             {
                 // 找到与相机编号匹配的模型
-                var model = modelSettings.FirstOrDefault(m => m.Id == camSetting.ModelID);
+                ModelSettings model = modelSettings.FirstOrDefault(m => m.Id == camSetting.ModelID);
                 if (model == null)
                 {
-                    ThreadSafeLogger.Log($"[警告] 找不到与相机 #{camSetting.CameraIndex} 匹配的模型，该相机将无法处理图像。");
+                    //ThreadSafeLogger.Log($"[警告] 找不到与相机 #{camSetting.CameraIndex} 匹配的模型，该相机将无法处理图像");
+                    ThreadSafeLogger.Log($"[警告] 找不到与相机 #{camSetting.CameraIndex} (Name: {camSetting.Name}) 匹配的模型 (ID: {camSetting.ModelID})。该相机将无法处理图像。");
                     continue;
                 }
 
-                var processor = new CameraProcessor(camSetting.CameraIndex,camSetting.ModelID);
+                IDetector detector = null;
+                object detectorSettings = null; // 用于传递特定检测器的设置
+
+                // 根据相机的 CheckType 和模型的 AlgorithmType 决定使用哪个检测器
+                if (camSetting.CheckType == CheckType.Traditional && model.M_AType == AlgorithmType.Tradition)
+                {
+                    detector = new HalconTemplateDetector();
+                    detectorSettings = new HalconDetectionSettings { ScoreThreshold = model.HalconScoreThreshold };
+                    ThreadSafeLogger.Log($"为相机 #{camSetting.CameraIndex} (Name: {camSetting.Name}) 绑定 HALCON 传统算法。");
+                }
+                else if (camSetting.CheckType == CheckType.DeepLearning && model.M_AType == AlgorithmType.DeepLearning)
+                {
+                    detector = new YoloDetector();
+                    detectorSettings = new YoloDetectionSettings
+                    {
+                        ConfidenceThreshold = model.YoloConfidenceThreshold,
+                        NmsThreshold = model.YoloNmsThreshold
+                    };
+                    ThreadSafeLogger.Log($"为相机 #{camSetting.CameraIndex} (Name: {camSetting.Name}) 绑定 YOLO 深度学习算法。");
+                }
+                else
+                {
+                    ThreadSafeLogger.Log($"[警告] 相机 #{camSetting.CameraIndex} (Name: {camSetting.Name}) 的 CheckType ({camSetting.CheckType}) 与模型 (ID: {model.Id}, AlgorithmType: {model.M_AType}) 不匹配或不支持。跳过此相机。");
+                    continue;
+                }
+
+                // 初始化检测器
+                try
+                {
+                    // 对于YOLO，modelPath实际上传递的是ModelID
+                    // 对于HALCON，modelPath是实际的模板目录
+                    string initPath = (detector is YoloDetector) ? model.Id.ToString() : model.Path;
+                    detector.Initialize(initPath, detectorSettings);
+                }
+                catch (Exception ex)
+                {
+                    ThreadSafeLogger.Log($"[错误] 初始化相机 #{camSetting.CameraIndex} 的检测器失败: {ex.Message}");
+                    detector?.Dispose();
+                    continue;
+                }
+
+                var processor = new CameraProcessor(camSetting.CameraIndex, detector, model);
                 _processors.TryAdd(camSetting.CameraIndex, processor);
                 processor.Start();
             }
             ThreadSafeLogger.Log($"检测协调器已初始化，启动了 {_processors.Count} 个相机处理线程。");
         }
 
+        //public static void EnqueueImage(int cameraIndex, Bitmap bmp)
+        //{
+        //    if (_processors.TryGetValue(cameraIndex, out var processor))
+        //    {
+        //        processor.EnqueueImage(bmp);
+        //    }
+        //    else
+        //    {
+        //        // 如果找不到处理器，必须释放Bitmap防止泄漏
+        //        bmp?.Dispose();
+        //    }
+        //}
+
         public static void EnqueueImage(int cameraIndex, Bitmap bmp)
         {
+            // 在图像进入队列之前生成一个新的产品ID
+            long currentProductId;
+            lock (_productAssemblies) // 同步访问产品计数器
+            {
+                _productCounter++;
+                currentProductId = _productCounter;
+            }
+
             if (_processors.TryGetValue(cameraIndex, out var processor))
             {
-                processor.EnqueueImage(bmp);
+                processor.EnqueueImage(bmp, currentProductId); // 传递产品ID
             }
             else
             {
-                // 如果找不到处理器，必须释放Bitmap防止泄漏
+                bmp?.Dispose(); // 如果找不到处理器，必须释放Bitmap防止泄漏
-                bmp?.Dispose();
+                ThreadSafeLogger.Log($"[警告] 未能为相机 {cameraIndex} 找到处理器，产品 {currentProductId} 的图像被丢弃。");
+                // 如果没有处理器，不需要在 _productAssemblies 中添加，因为不会有结果返回
             }
         }
 
-        // 供 CameraProcessor 回调，用以组装产品
+        //// 供 CameraProcessor 回调，用以组装产品
-        public static void AssembleProduct(ImageData data, string result)
+        //public static void AssembleProduct(ImageData data, string result)
-        {
+        //{
-            var assembly = _productAssemblies.GetOrAdd(data.ProductId, (id) => new ProductAssembly(id, _enabledCameraCount));
+        //    var assembly = _productAssemblies.GetOrAdd(data.ProductId, (id) => new ProductAssembly(id, _enabledCameraCount));
 
-            if (assembly.AddResult(data.CameraIndex, result))
+        //    if (assembly.AddResult(data.CameraIndex, result))
+        //    {
+        //        string finalResult = assembly.GetFinalResult();
+        //        ThreadSafeLogger.Log($"产品 #{assembly.ProductId} 已检测完毕，最终结果: {finalResult}");
+
+        //        // 只有在检测运行时，才触发事件
+        //        if (IsDetectionRunning)
+        //        {
+        //            OnDetectionCompleted?.Invoke(null, new DetectionResultEventArgs(finalResult == "OK"));
+        //        }
+
+        //        if (_productAssemblies.TryRemove(assembly.ProductId, out var finishedAssembly))
+        //        {
+        //            finishedAssembly.Dispose();
+        //        }
+        //    }
+        //}
+
+        // CameraProcessor 回调，用以组装产品
+        public static void AssembleProduct(long productId, int cameraIndex, bool isOk, Bitmap resultImage)
         {
-                string finalResult = assembly.GetFinalResult();
+            // GetOrAdd 确保 ProductAssembly 只被创建一次
+            var assembly = _productAssemblies.GetOrAdd(productId, (id) => new ProductAssembly(id, _enabledCameraCount));
+
+            assembly.AddResult(cameraIndex, isOk, resultImage);
+
+            // 检查产品是否已完成所有相机的检测
+            if (assembly.IsComplete())
+            {
+                string finalResult = assembly.GetFinalResult() ? "OK" : "NG";
                 ThreadSafeLogger.Log($"产品 #{assembly.ProductId} 已检测完毕，最终结果: {finalResult}");
 
-                // 只有在检测运行时，才触发事件
+                // 触发事件 (例如更新主UI上的总OK/NG计数)
                 if (IsDetectionRunning)
                 {
-                    OnDetectionCompleted?.Invoke(null, new DetectionResultEventArgs(finalResult == "OK"));
+                    OnDetectionCompleted?.Invoke(null, new DetectionResultEventArgs(assembly.GetFinalResult()));
                 }
 
-                if (_productAssemblies.TryRemove(assembly.ProductId, out var finishedAssembly))
+                // PLC 写入逻辑
+                if (FrmMain.PlcClient != null) // 假设 FrmMain.PlcClient 可访问
                 {
-                    finishedAssembly.Dispose();
+                    try
+                    {
+                        if (assembly.GetFinalResult()) // 最终结果 OK
+                        {
+                            FrmMain.PlcClient.WriteBool("M90", true); // 写入M90为1
+                            Thread.Sleep(50); // 短暂延时
+                            FrmMain.PlcClient.WriteBool("M90", false);
+                        }
+                        else // 最终结果 NG
+                        {
+                            FrmMain.PlcClient.WriteBool("M91", true); // 写入M91为1
+                            Thread.Sleep(50); // 短暂延时
+                            FrmMain.PlcClient.WriteBool("M91", false);
+                        }
+                        ThreadSafeLogger.Log($"产品 #{assembly.ProductId} 最终结果 {finalResult} 已写入PLC。");
+                    }
+                    catch (Exception ex)
+                    {
+                        ThreadSafeLogger.Log($"[错误] 写入PLC失败：{ex.Message}");
+                    }
+                }
+                else
+                {
+                    ThreadSafeLogger.Log($"[警告] 产品 #{assembly.ProductId} 检测结果未能写入PLC：PLC客户端未连接。");
+                }
+
+                // 移除并释放 ProductAssembly
+                if (_productAssemblies.TryRemove(productId, out var finishedAssembly))
+                {
+                    finishedAssembly.Dispose(); // 释放所有存储的 Bitmap
                 }
             }
         }
-        /// <summary>
+
-        /// 命令所有活动的相机处理器重置它们的内部计数器。
+        ///// <summary>
-        /// </summary>
+        ///// 命令所有活动的相机处理器重置它们的内部计数器。
+        ///// </summary>
+        //public static void ResetAllCounters()
+        //{
+        //    foreach (var processor in _processors.Values)
+        //    {
+        //        processor.ResetCounter();
+        //    }
+        //    ThreadSafeLogger.Log("所有相机处理器的产品计数器已重置。");
+        //}
+
         public static void ResetAllCounters()
         {
+            lock (_productAssemblies)
+            {
+                _productCounter = 0;
+                // 清空所有未完成的产品，并释放其资源
+                foreach (var assembly in _productAssemblies.Values)
+                {
+                    assembly.Dispose();
+                }
+                _productAssemblies.Clear();
+            }
             foreach (var processor in _processors.Values)
             {
                 processor.ResetCounter();
             }
-            ThreadSafeLogger.Log("所有相机处理器的产品计数器已重置。");
+            ThreadSafeLogger.Log("所有相机处理器和产品计数器已重置。");
         }
 
         public static CameraProcessor GetProcessor(int cameraIndex)
@@ -142,8 +292,88 @@ namespace Check.Main.Infer
             {
                 assembly.Dispose();
             }
-            _productAssemblies.Clear();
+            YoloModelManager.Shutdown(); // 确保YOLO模型也关闭
             ThreadSafeLogger.Log("检测协调器已关闭。");
         }
     }
+
+    // 新增 ProductAssembly 类，用于集中管理一个产品的检测结果和图像
+    public class ProductAssembly : IDisposable
+    {
+        public long ProductId { get; }
+        private readonly int _expectedCameraCount;
+        private readonly ConcurrentDictionary<int, bool> _cameraResults = new ConcurrentDictionary<int, bool>();
+        private readonly ConcurrentDictionary<int, Bitmap> _resultImages = new ConcurrentDictionary<int, Bitmap>(); // 存储每个相机的结果图像
+        private readonly object _lock = new object();
+
+        public ProductAssembly(long productId, int expectedCameraCount)
+        {
+            ProductId = productId;
+            _expectedCameraCount = expectedCameraCount;
+        }
+
+        /// <summary>
+        /// 添加单个相机的检测结果。
+        /// </summary>
+        /// <param name="cameraIndex">相机编号。</param>
+        /// <param name="isOk">检测结果是否为OK。</param>
+        /// <param name="resultImage">带有检测结果的图像。</param>
+        public void AddResult(int cameraIndex, bool isOk, Bitmap resultImage)
+        {
+            lock (_lock)
+            {
+                _cameraResults.TryAdd(cameraIndex, isOk);
+                if (resultImage != null)
+                {
+                    // 克隆图像，确保 ProductAssembly 拥有其所有权
+                    _resultImages.TryAdd(cameraIndex, (Bitmap)resultImage.Clone());
+                    resultImage.Dispose(); // 释放传入的原始图像副本
+                }
+            }
+        }
+
+        /// <summary>
+        /// 检查是否所有相机都已提交结果。
+        /// </summary>
+        public bool IsComplete()
+        {
+            lock (_lock)
+            {
+                return _cameraResults.Count == _expectedCameraCount;
+            }
+        }
+
+        /// <summary>
+        /// 获取最终产品检测结果（所有相机都OK才为OK）。
+        /// </summary>
+        public bool GetFinalResult()
+        {
+            lock (_lock)
+            {
+                return _cameraResults.Values.All(r => r);
+            }
+        }
+
+        /// <summary>
+        /// 获取某个相机的结果图像。
+        /// </summary>
+        public Bitmap GetResultImage(int cameraIndex)
+        {
+            _resultImages.TryGetValue(cameraIndex, out var bmp);
+            return bmp;
+        }
+
+        public void Dispose()
+        {
+            lock (_lock)
+            {
+                foreach (var bmp in _resultImages.Values)
+                {
+                    bmp?.Dispose();
+                }
+                _resultImages.Clear();
+                _cameraResults.Clear();
+            }
+        }
+    }
 }

Check.Main/Infer/HalconTemplateDetector.cs

@@ -0,0 +1,57 @@
+using HalconTemplateMatch;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+using System.Drawing;
+
+namespace Check.Main.Infer
+{
+    public class HalconTemplateDetector : IDetector
+    {
+        private LogoMatcher _matcher; // 使用您现有的 LogoMatcher
+        private double _scoreThreshold = 0.5; // 可以从 ModelSettings 中配置
+
+        public void Initialize(string modelPath, object detectionSettings = null)
+        {
+            _matcher = new LogoMatcher();
+            _matcher.LoadTemplates(modelPath); // modelPath 现在是 Halcon 模板目录
+
+            // 如果 detectionSettings 包含阈值，可以在这里解析
+            if (detectionSettings is HalconDetectionSettings halconSettings)
+            {
+                _scoreThreshold = halconSettings.ScoreThreshold;
+            }
+        }
+
+        public DetectionResult Detect(Bitmap image)
+        {
+            if (_matcher == null)
+                throw new InvalidOperationException("HalconTemplateDetector 未初始化。");
+
+            Bitmap resultImage;
+            double score = _matcher.FindLogo(image, out resultImage);
+            bool isOk = score >= _scoreThreshold;
+            string message = isOk ? "OK" : "NG";
+
+            // 如果需要绘制结果图像，可以在 LogoMatcher 中添加绘制逻辑并返回
+            // 假设 LogoMatcher 也可以返回一个带有匹配标记的 Bitmap
+            // Bitmap resultImage = _matcher.DrawResults(image, score);
+
+            return new DetectionResult(isOk, message, score); //, resultImage
+        }
+
+        public void Dispose()
+        {
+            // LogoMatcher 如果有需要释放的资源，可以在这里处理
+        }
+    }
+
+    // 辅助设置类，用于传递给 HalconTemplateDetector
+    public class HalconDetectionSettings
+    {
+        public double ScoreThreshold { get; set; } = 0.5;
+        // 可以添加其他 Halcon 匹配参数
+    }
+}

Check.Main/Infer/IDetector.cs

@@ -0,0 +1,62 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using System.Threading.Tasks;
+
+namespace Check.Main.Infer
+{
+    public interface IDetector : IDisposable
+    {
+        /// <summary>
+        /// 初始化检测器。
+        /// </summary>
+        /// <param name="modelPath">模型文件路径（对于传统算法可能是模板目录）</param>
+        /// <param name="detectionSettings">特定于检测器的设置对象（可选，可以用于传递阈值等）</param>
+        void Initialize(string modelPath, object detectionSettings = null);
+
+        /// <summary>
+        /// 执行图像检测。
+        /// </summary>
+        /// <param name="image">待检测的图像。</param>
+        /// <returns>包含检测结果（如OK/NG，得分，边界框等）的统一对象。</returns>
+        DetectionResult Detect(Bitmap image);
+    }
+
+    /// <summary>
+    /// 统一的检测结果类。
+    /// </summary>
+    public class DetectionResult
+    {
+        public bool IsOk { get; set; }
+        public string Message { get; set; }
+        public double Score { get; set; }
+        public List<RectangleF> BoundingBoxes { get; set; } // 深度学习可能返回多个目标框
+
+        // 如果需要，可以添加带有绘制结果的图像
+        public Bitmap ResultImage { get; set; }
+
+        public DetectionResult(bool isOk, string message = "Unknown", double score = 0.0, List<RectangleF> boundingBoxes = null, Bitmap resultImage = null)
+        {
+            IsOk = isOk;
+            Message = message;
+            Score = score;
+            BoundingBoxes = boundingBoxes ?? new List<RectangleF>();
+            ResultImage = resultImage;
+        }
+    }
+
+    //// 辅助设置类，用于传递给 HalconTemplateDetector
+    //public class HalconDetectionSettings
+    //{
+    //    public double ScoreThreshold { get; set; } = 0.5;
+    //}
+
+    // 辅助设置类，用于传递给 YoloDetector
+    public class YoloDetectionSettings
+    {
+        public float ConfidenceThreshold { get; set; } = 0.25f;
+        public float NmsThreshold { get; set; } = 0.45f;
+    }
+
+}

Check.Main/Infer/ModelSettings.cs

@@ -1,4 +1,14 @@
-using Check.Main.Common;
+//using Check.Main.Common;
+//using System;
+//using System.Collections.Generic;
+//using System.ComponentModel;// 需要引入此命名空间以使用 INotifyPropertyChanged
+//using System.Linq;
+//using System.Runtime.CompilerServices;
+//using System.Runtime.Serialization;
+//using System.Text;
+//using System.Threading.Tasks;
+
+using Check.Main.Common;
 using System;
 using System.Collections.Generic;
 using System.ComponentModel;
@@ -7,28 +17,12 @@ using System.Runtime.CompilerServices;
 using System.Runtime.Serialization;
 using System.Text;
 using System.Threading.Tasks;
+using System.Windows.Forms.Design;
+using System.Drawing.Design;
 
 namespace Check.Main.Infer
 {
-    public enum DetectDevice
-    {
-        [Description("CPU")]
-        CPU = 0,
 
-        [Description("GPU")]
-        GPU,
-
-        //[Description("VPU")]
-        //VPU,
-    }
-    public enum AlgorithmType
-    {
-        [Description("传统算法")]
-        Tradition = 0,
-
-        [Description("深度学习")]
-        DeepLearning,
-    }
     public enum CheckModelType
     {
         [Description("分类")]
@@ -47,9 +41,32 @@ namespace Check.Main.Infer
         PoseEstimation
     }
 
-    [Serializable] // 确保可被XML序列化
+    public enum AlgorithmType
-    public class ModelSettings : INotifyPropertyChanged, ICloneable
     {
+        [Description("传统算法")]
+        Tradition = 0,
+
+        [Description("深度学习")]
+        DeepLearning,
+    }
+
+    public enum DetectDevice
+    {
+        [Description("CPU")]
+        CPU = 0,
+
+        [Description("GPU")]
+        GPU,
+
+        //[Description("VPU")]
+        //VPU,
+    }
+   
+
+    [Serializable] // 确保可被XML序列化
+    public class ModelSettings : INotifyPropertyChanged, ICloneable//类ModelSettings继承或实现两个接口：①提供一个事件，用于在属性值更改时发出通知；②提供一个方法，用于创建对象的独立副本
+    {
+        //1. 实现 INotifyPropertyChanged 接口
         public event PropertyChangedEventHandler PropertyChanged;
 
         private int _id;
@@ -57,9 +74,14 @@ namespace Check.Main.Infer
         private string _path = "";
         private DetectDevice _checkDevice=DetectDevice.CPU;
         private AlgorithmType _mAType = AlgorithmType.Tradition;
-        private CheckModelType _mType = CheckModelType.Classification;
+        private CheckModelType _mType = CheckModelType.ObjectDetection;
         private bool _isEnabled = true;
 
+        // 新增 HALCON 和 YOLO 的参数。10.22
+        private double _halconScoreThreshold = 0.5;
+        private float _yoloConfidenceThreshold = 0.25f;
+        private float _yoloNmsThreshold = 0.45f;
+
         [Category("基本信息"), DisplayName("模型编号"), Description("模型的唯一标识符，用于与相机编号对应。")]
         public int Id
         {
@@ -73,13 +95,6 @@ namespace Check.Main.Infer
             get => _name;
             set { if (_name != value) { _name = value; OnPropertyChanged(); } }
         }
-        [Category("基本信息"), DisplayName("推理设备"), Description("推理模型的设备。")]
-        [TypeConverter(typeof(EnumDescriptionTypeConverter))]
-        public DetectDevice CheckDevice
-        {
-            get => _checkDevice;
-            set { if (_checkDevice != value) { _checkDevice = value; OnPropertyChanged(); } }
-        }
 
         [Category("基本信息"), DisplayName("算法类型"), Description("所使用的算法的类型。")]
         [TypeConverter(typeof(EnumDescriptionTypeConverter))]
@@ -88,6 +103,16 @@ namespace Check.Main.Infer
             get => _mAType;
             set { if (_mAType != value) { _mAType = value; OnPropertyChanged(); } }
         }
+
+        [Category("基本信息"), DisplayName("推理设备"), Description("推理模型的设备。")]
+        [TypeConverter(typeof(EnumDescriptionTypeConverter))]
+        public DetectDevice CheckDevice
+        {
+            get => _checkDevice;
+            set { if (_checkDevice != value) { _checkDevice = value; OnPropertyChanged(); } }
+        }
+
+
         [Category("基本信息"), DisplayName("模型类型"), Description("推理模型的类型。")]
         [TypeConverter(typeof(EnumDescriptionTypeConverter))]
         public CheckModelType MType
@@ -96,12 +121,12 @@ namespace Check.Main.Infer
             set { if (_mType != value) { _mType = value; OnPropertyChanged(); } }
         }
 
+
         [Category("基本信息"), DisplayName("是否启用"), Description("是否在程序启动时是否启用模型")]
         public bool IsEnabled
         {
             get => _isEnabled;
-            set
+            set  { 
-            {
                         if (_isEnabled != value)
                         {
                             _isEnabled = value;
@@ -118,6 +143,27 @@ namespace Check.Main.Infer
             set { if (_path != value) { _path = value; OnPropertyChanged(); } }
         }
 
+        [Category("模型参数"), DisplayName("HALCON得分阈值"), Description("HALCON模板匹配的得分阈值（0-1）。")]
+        public double HalconScoreThreshold
+        {
+            get => _halconScoreThreshold;
+            set { if (_halconScoreThreshold != value) { _halconScoreThreshold = value; OnPropertyChanged(); } }
+        }
+
+        [Category("模型参数"), DisplayName("YOLO置信度阈值"), Description("YOLO检测的置信度阈值（0-1）。")]
+        public float YoloConfidenceThreshold
+        {
+            get => _yoloConfidenceThreshold;
+            set { if (_yoloConfidenceThreshold != value) { _yoloConfidenceThreshold = value; OnPropertyChanged(); } }
+        }
+
+        [Category("模型参数"), DisplayName("YOLO NMS阈值"), Description("YOLO检测的非极大值抑制（NMS）阈值（0-1）。")]
+        public float YoloNmsThreshold
+        {
+            get => _yoloNmsThreshold;
+            set { if (_yoloNmsThreshold != value) { _yoloNmsThreshold = value; OnPropertyChanged(); } }
+        }
+
         protected void OnPropertyChanged([CallerMemberName] string propertyName = null)
         {
             PropertyChanged?.Invoke(this, new PropertyChangedEventArgs(propertyName));

Check.Main/Infer/YoloDetector.cs

@@ -0,0 +1,409 @@
+using Check.Main.Camera;
+using Check.Main.Common;
+using OpenCvSharp;
+using SkiaSharp;
+using System;
+using System.Collections.Generic;
+using System.Drawing;
+using System.Linq;
+using YoloDotNet;
+using YoloDotNet.Models;
+
+namespace Check.Main.Infer
+{
+    /// <summary>
+    /// YOLO 检测结果对象，包含标签、置信度与检测框
+    /// </summary>
+    public class YoloPrediction
+    {
+        public YoloLabel Label { get; set; }
+        public float Score { get; set; }
+        public BoundingBox BoundingBox { get; set; }
+    }
+
+    /// <summary>
+    /// YOLO 类别标签
+    /// </summary>
+    public class YoloLabel
+    {
+        public string Name { get; set; }
+    }
+
+    /// <summary>
+    /// 检测框坐标结构体
+    /// </summary>
+    public struct BoundingBox
+    {
+        public float Left { get; set; }
+        public float Top { get; set; }
+        public float Width { get; set; }
+        public float Height { get; set; }
+
+        public BoundingBox(float left, float top, float width, float height)
+        {
+            Left = left;
+            Top = top;
+            Width = width;
+            Height = height;
+        }
+    }
+
+    /// <summary>
+    /// YOLO 目标检测器实现类
+    /// </summary>
+    public class YoloDetector : IDetector, IDisposable
+    {
+        private Yolo _yoloModel;
+        private int _modelID;
+        private float _confidenceThreshold = 0.25f;
+        private float _nmsThreshold = 0.45f;
+
+        /// <summary>
+        /// 初始化 YOLO 检测器并加载模型
+        /// </summary>
+        /// <param name="modelIdStr">模型 ID 字符串</param>
+        /// <param name="detectionSettings">可选检测参数</param>
+        /// <exception cref="ArgumentException">ID 无效</exception>
+        /// <exception cref="InvalidOperationException">模型未加载</exception>
+        public void Initialize(string modelIdStr, object detectionSettings = null)
+        {
+            if (string.IsNullOrWhiteSpace(modelIdStr))
+                throw new ArgumentException("模型ID字符串不能为空。", nameof(modelIdStr));
+
+            if (!int.TryParse(modelIdStr, out _modelID))
+                throw new ArgumentException("模型ID必须为有效整数。", nameof(modelIdStr));
+
+            _yoloModel = YoloModelManager.GetModel(_modelID)
+                ?? throw new InvalidOperationException($"YOLO 模型 (ID: {_modelID}) 未加载或找不到。");
+
+            if (detectionSettings is YoloDetectionSettings yoloSettings)
+            {
+                _confidenceThreshold = Math.Clamp(yoloSettings.ConfidenceThreshold, 0f, 1f);
+                _nmsThreshold = Math.Clamp(yoloSettings.NmsThreshold, 0f, 1f);
+            }
+        }
+
+        /// <summary>
+        /// 执行检测，判断是否含有 logo 类对象
+        /// </summary>
+        public DetectionResult Detect(Bitmap image)
+        {
+            if (_yoloModel == null)
+                throw new InvalidOperationException("YoloDetector 未初始化或模型未加载。");
+
+            if (image == null)
+                return new DetectionResult(false, "输入图像为空。");
+
+            try
+            {
+                using var skBitmap = CameraProcessor.ToSKBitmapFast(image);
+                if (skBitmap == null)
+                    return new DetectionResult(false, "图像转换失败。");
+
+                using var skImage = SKImage.FromBitmap(skBitmap);
+                if (skImage == null)
+                    return new DetectionResult(false, "无法生成 SKImage。");
+
+                var predictions = _yoloModel.RunObjectDetection(
+                    skImage,
+                    confidence: _confidenceThreshold,
+                    iou: _nmsThreshold
+                );
+
+                // 检查是否检测到 logo
+                bool foundLogo = predictions.Any(p =>
+                    p.Label.Name.Equals("logo", StringComparison.OrdinalIgnoreCase));
+
+                return foundLogo
+                    ? new DetectionResult(false, "NG")
+                    : new DetectionResult(true, "OK");
+            }
+            catch (Exception ex)
+            {
+                return new DetectionResult(false, $"检测失败: {ex.Message}");
+            }
+        }
+
+        /// <summary>
+        /// 在图像上绘制检测框与标签
+        /// </summary>
+        public Bitmap DrawYoloPredictions(Bitmap source, IEnumerable<YoloPrediction> predictions)
+        {
+            if (source == null)
+                throw new ArgumentNullException(nameof(source));
+
+            if (predictions == null || !predictions.Any())
+                return (Bitmap)source.Clone();
+
+            Bitmap output = (Bitmap)source.Clone();
+
+            using var graphics = Graphics.FromImage(output);
+            using var pen = new Pen(Color.Yellow, 2);
+            using var font = new Font("Arial", 10, FontStyle.Bold);
+            using var brush = new SolidBrush(Color.Yellow);
+
+            foreach (var pred in predictions)
+            {
+                var box = pred.BoundingBox;
+                var rect = new RectangleF(box.Left, box.Top, box.Width, box.Height);
+
+                // 绘制检测框
+                graphics.DrawRectangle(pen, rect.X, rect.Y, rect.Width, rect.Height);
+
+                // 绘制标签
+                string label = $"{pred.Label?.Name ?? "unknown"} ({pred.Score:P1})";
+                graphics.DrawString(label, font, brush, rect.X, rect.Y - 15);
+            }
+
+            return output;
+        }
+
+        /// <summary>
+        /// 无需显式释放模型，资源由 YoloModelManager 管理
+        /// </summary>
+        public void Dispose()
+        {
+            //_yoloModel = null;
+        }
+    }
+}
+//总结，区分好YoloModelManager.cs和YoloDetector.cs各自的职能，谁负责模型管理，谁负责yolo算法的执行，现在这两个文件是交织在一起比较乱的，有时间去处理一下
+//看上面的定义的一些结构体胡总和类，就可以调用啦
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
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+
+
+
+
+
+
+
+
+
+
+
+
+
+
+//using Check.Main.Camera;
+//using Check.Main.Common;
+//using SkiaSharp;
+//using System;
+//using System.Collections.Generic;
+//using System.Drawing;
+//using System.Linq;
+//using System.Text;
+//using System.Threading.Tasks;
+//using YoloDotNet;
+//using YoloDotNet.Models;
+
+
+
+//namespace Check.Main.Infer
+//{
+//    public class YoloDetector : IDetector
+//    {
+//        private Yolo _yoloModel;
+//        private int _modelID; // 需要知道模型ID来从 YoloModelManager 获取
+//        private float _confidenceThreshold = 0.25f;
+//        private float _nmsThreshold = 0.45f;
+
+//        public void Initialize(string modelIdStr, object detectionSettings = null)
+//        {
+//            if (!int.TryParse(modelIdStr, out _modelID))
+//            {
+//                throw new ArgumentException("YoloDetector 初始化需要有效的模型ID字符串。", nameof(modelIdStr));
+//            }
+//            _yoloModel = YoloModelManager.GetModel(_modelID);
+//            if (_yoloModel == null)
+//            {
+//                throw new InvalidOperationException($"YOLO 模型 (ID: {_modelID}) 未加载或找不到。");
+//            }
+
+//            if (detectionSettings is YoloDetectionSettings yoloSettings)
+//            {
+//                _confidenceThreshold = yoloSettings.ConfidenceThreshold;
+//                _nmsThreshold = yoloSettings.NmsThreshold;
+//                // 注意：YOLO模型的置信度和NMS阈值最好在YoloModelManager加载时设置
+//                // 这里如果需要运行时调整，可能需要Yolo.SetThresholds方法
+//            }
+//        }
+
+//        public DetectionResult Detect(Bitmap image)
+//        {
+//            if (_yoloModel == null)
+//                throw new InvalidOperationException("YoloDetector 未初始化或模型未加载。");
+
+//            using (var skImage = CameraProcessor.ToSKBitmapFast(image)) // 使用 CameraProcessor 的静态方法
+//            {
+//                if (skImage == null)
+//                {
+//                    return new DetectionResult(false, "图像转换失败");
+//                }
+
+//                // 在这里可以应用运行时阈值，如果Yolo模型支持
+//                // _yoloModel.Confidence = _confidenceThreshold;
+//                // _yoloModel.Nms = _nmsThreshold;
+
+//                var predictions = _yoloModel.RunObjectDetection(skImage);
+
+//                bool isOk = !predictions.Any(); // 假设没有检测到任何目标为 OK
+//                string message = isOk ? "OK" : "NG";
+
+//                List<RectangleF> boundingBoxes = predictions.Select(p => new RectangleF(p.Rectangle.X, p.Rectangle.Y, p.Rectangle.Width, p.Rectangle.Height)).ToList();
+//                Bitmap resultImage = DrawYoloPredictions(image, predictions);
+
+//                return new DetectionResult(isOk, message, 0, boundingBoxes, resultImage);
+//            }
+//        }
+
+//        private Bitmap DrawYoloPredictions(Bitmap originalImage, IEnumerable<YoloPrediction> predictions)
+//        {
+//            Bitmap resultBmp = (Bitmap)originalImage.Clone();
+//            using (Graphics g = Graphics.FromImage(resultBmp))
+//            {
+//                Pen ngPen = new Pen(Color.Red, 3);
+//                Font font = new Font("Arial", 12, FontStyle.Bold);
+//                Brush brush = new SolidBrush(Color.Red);
+
+//                foreach (var p in predictions)
+//                {
+//                    Rectangle rect = new Rectangle((int)p.Rectangle.X, (int)p.Rectangle.Y, (int)p.Rectangle.Width, (int)p.Rectangle.Height);
+//                    g.DrawRectangle(ngPen, rect);
+//                    g.DrawString($"{p.Label} ({p.Confidence:P})", font, brush, rect.X, rect.Y - 20);
+//                }
+//            }
+//            return resultBmp;
+//        }
+
+//        public void Dispose()
+//        {
+//            // YOLO 模型生命周期由 YoloModelManager 管理，这里不需要额外释放
+//        }
+//    }
+//}
+
+
+//public DetectionResult Detect(Bitmap image)
+//{
+//    if (_yoloModel == null)
+//        throw new InvalidOperationException("YoloDetector 未初始化或模型未加载。");
+
+//    using (var skBitmap = CameraProcessor.ToSKBitmapFast(image))
+//    using (var skImage = SKImage.FromBitmap(skBitmap))
+//    {
+//        //注意深拷贝浅拷贝的概念，复制的图片别忘了释放
+//        var output = image.Clone();
+
+//        if (skImage == null)
+//            return new DetectionResult(false, "图像转换失败");
+
+//        //var results = _yoloModel.RunObjectDetection(skImage, confidence: 0.4f, iou: 0.5f);
+
+//        var predictions = _yoloModel.RunObjectDetection(
+//            skImage,
+//            confidence: _confidenceThreshold,
+//            iou: _nmsThreshold
+//        );
+//        var ExistBool = predictions.FirstOrDefault(res => res.Label.Name.Equals("logo", StringComparison.OrdinalIgnoreCase));
+//        if (ExistBool != null)
+//        {
+//            var box = ExistBool.BoundingBox;
+//            var rect = new Rect(box.Left, box.Top, box.Width, box.Height);
+
+//            //Cv2.Rectangle(output, rect, Scalar.Yellow, 2);
+//            //Cv2.PutText(output, $"{logoResult.Label.Name}: {logoResult.Confidence:P2}", new CvPoint(rect.X, rect.Y - 10), HersheyFonts.HersheySimplex, 0.6, Scalar.Yellow, 2);
+//        }
+//        bool isOk = !predictions.Any(); // 没有检测结果为OK
+//        string message = isOk ? "OK" : "NG";
+
+//        //var boundingBoxes = predictions
+//        //    .Select(p => new RectangleF(p.Rectangle.X, p.Rectangle.Y, p.Rectangle.Width, p.Rectangle.Height))
+//        //    .ToList();
+
+//        //Bitmap resultImage = DrawYoloPredictions(image, predictions);
+
+//        //return new DetectionResult(isOk, message, 0, boundingBoxes, resultImage);
+//    }
+//}
+
+//// 注意：如果你使用的是 YoloResult，请改为 IEnumerable<YoloResult>     IEnumerable<YoloPrediction> 
+//private Bitmap DrawYoloPredictions(Bitmap originalImage, IEnumerable<YoloPrediction> predictions)
+//{
+//    Bitmap resultBmp = (Bitmap)originalImage.Clone();
+//    using (Graphics g = Graphics.FromImage(resultBmp))
+//    {
+//        Pen boxPen = new Pen(Color.Red, 3);
+//        Font font = new Font("Arial", 12, FontStyle.Bold);
+//        Brush brush = new SolidBrush(Color.Red);
+
+//        foreach (var p in predictions)
+//        {
+//            Rectangle rect = new Rectangle(
+//                (int)p.Rectangle.X,
+//                (int)p.Rectangle.Y,
+//                (int)p.Rectangle.Width,
+//                (int)p.Rectangle.Height
+//            );
+//            g.DrawRectangle(boxPen, rect);
+//            g.DrawString($"{p.Label} ({p.Confidence:P0})", font, brush, rect.X, rect.Y - 20);
+//        }
+
+//        boxPen.Dispose();
+//        font.Dispose();
+//        brush.Dispose();
+//    }
+//    return resultBmp;
+//}
+// 错误②：CS0246 解决方法：确保 YoloPrediction 的完整命名空间正确引用。
+// 由于你的文件开头已经有了 `using YoloDotNet.Models;`
+// 所以这里直接使用 `YoloPrediction` 应该是正确的，除非 `YoloPrediction` 不在该命名空间下。
+// 如果问题依然存在，检查 YoloDotNet.Models 命名空间中 YoloPrediction 的具体定义。
+//private Bitmap DrawYoloPredictions(Bitmap originalImage, IEnumerable<YoloPrediction> predictions)
+//{
+//    Bitmap resultBmp = (Bitmap)originalImage.Clone();
+//    using (Graphics g = Graphics.FromImage(resultBmp))
+//    {
+//        Pen boxPen = new Pen(Color.Red, 3);
+//        Font font = new Font("Arial", 12, FontStyle.Bold);
+//        Brush brush = new SolidBrush(Color.Red);
+
+//        foreach (var p in predictions)
+//        {
+//            Rectangle rect = new Rectangle(
+//                (int)p.Rectangle.X,
+//                (int)p.Rectangle.Y,
+//                (int)p.Rectangle.Width,
+//                (int)p.Rectangle.Height
+//            );
+//            g.DrawRectangle(boxPen, rect);
+//            g.DrawString($"{p.Label} ({p.Confidence:P0})", font, brush, rect.X, rect.Y - 20);
+//        }
+
+//        boxPen.Dispose();
+//        font.Dispose();
+//        brush.Dispose();
+//    }
+//    return resultBmp;
+//}
+
+
+
+
+

Check.Main/Infer/YoloModelManager.cs

@@ -31,40 +31,41 @@ namespace Check.Main.Infer
             if (modelSettings == null) return;
 
             ThreadSafeLogger.Log("开始加载YOLO模型...");
-            foreach (var setting in modelSettings)
+            // 筛选出启用的深度学习模型进行加载
+            foreach (var setting in modelSettings.Where(s => s.IsEnabled && s.M_AType == AlgorithmType.DeepLearning))
             {
-                bool gpuUse = false;
+                bool gpuUse = setting.CheckDevice == DetectDevice.GPU;
-                if (setting.CheckDevice == DetectDevice.GPU)
-                {
-                    gpuUse = true;
-                }
 
                 if (string.IsNullOrEmpty(setting.Path) || !File.Exists(setting.Path))
                 {
-                    ThreadSafeLogger.Log($"[警告] 模型 '{setting.Name}' (ID: {setting.Id}) 路径无效或文件不存在，已跳过加载。");
+                    ThreadSafeLogger.Log($"[警告] YOLO模型 '{setting.Name}' (ID: {setting.Id}) 路径无效或文件不存在，已跳过加载。");
                     continue;
                 }
 
                 try
                 {
-                    // 创建YOLO实例
                     var yolo = new Yolo(new YoloOptions
                     {
                         OnnxModel = setting.Path,
-                        // 您可以根据需要从配置中读取这些值
                         ModelType = (YoloDotNet.Enums.ModelType)setting.MType,
-                        Cuda = gpuUse, // 推荐使用GPU
+                        Cuda = gpuUse,
-                        PrimeGpu = false
+                        //Confidence = setting.YoloConfidenceThreshold, // 从 ModelSettings 读取
+                        //Nms = setting.YoloNmsThreshold,           // 从 ModelSettings 读取
+                        PrimeGpu = false // 根据需求设置
                     });
 
+                    // 保存阈值配置
+                    var conf = setting.YoloConfidenceThreshold;
+                    var nms = setting.YoloNmsThreshold;
+
                     if (_loadedModels.TryAdd(setting.Id, yolo))
                     {
-                        ThreadSafeLogger.Log($"成功加载模型 '{setting.Name}' (ID: {setting.Id})。");
+                        ThreadSafeLogger.Log($"成功加载YOLO模型 '{setting.Name}' (ID: {setting.Id})。");
                     }
                 }
                 catch (Exception ex)
                 {
-                    ThreadSafeLogger.Log($"[错误] 加载模型 '{setting.Name}' (ID: {setting.Id}) 失败: {ex.Message}");
+                    ThreadSafeLogger.Log($"[错误] 加载YOLO模型 '{setting.Name}' (ID: {setting.Id}) 失败: {ex.Message}");
                 }
             }
             ThreadSafeLogger.Log($"YOLO模型加载完成，共成功加载 {_loadedModels.Count} 个模型。");

Check.Main/UI/FrmConfig.cs

@@ -17,8 +17,7 @@ namespace Check.Main.UI
 {
     public partial class FrmConfig : DockContent
     {
-        //private ProcessConfig _mainSettings=new ProcessConfig();
+
-        //private readonly string _configFilePath = Path.Combine(Application.StartupPath, "main_config.xml");
         public FrmConfig()
         {
             InitializeComponent();