CCDCount/TestWork.DLL/ShuLiClass.cs

using CCDCount.DLL.AlarmTools;
using CCDCount.MODEL.ConfigModel;
using CCDCount.MODEL.ResultModel;
using CCDCount.MODEL.ShuLiModel;
using LogClass;
using MvCameraControl;
using Org.BouncyCastle.Utilities;
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Data.Entity.Core.Common.CommandTrees.ExpressionBuilder;
using System.Diagnostics;
using System.Drawing;
using System.IO;
using System.Linq;
using System.Runtime.InteropServices.WindowsRuntime;
using System.Threading;
using System.Threading.Tasks;
using System.Windows.Media.Media3D;
using static iTextSharp.text.pdf.AcroFields;

namespace CCDCount.DLL
{
    public class ShuLiClass
    {
        #region 变量
        /// <summary>
        /// 当活跃物体转变为历史物体时的回调事件
        /// </summary>
        public event EventHandler<ActiveObjectEventArgsClass> WorkCompleted;
        private List<ActiveObjectClass> activeObjects = new List<ActiveObjectClass>(); // 当前跟踪中的物体
        private List<ActiveObjectClass> historyActiveObjects = new List<ActiveObjectClass>(); // 历史物体
        private ConcurrentQueue<IFrameOut> IFrameDatas = new ConcurrentQueue<IFrameOut>(); //图像数据队列
        private Thread IdentifyImageProcessThread = null; // 识别线程
        private bool IsIdentify = false; //线程是否开始识别的标志
        private long currentLine = 0; //行数记录
        private ShuLiConfigClass shuLiConfig = null;// 数粒参数配置文件
        public List<int> ChannelsRoi { get { return _ChannelsRoi; } }
        private List<int> _ChannelsRoi = new List<int>();
        private int ChannelWidth = 0;//每个区域的宽度
        private int IdentifyImageWidth = -1;
        private int ObjectNum = 0;
        public int ImageNum { get { return IFrameDatas.Count; } }
        private ReaderWriterLockSlim _rwLock = new ReaderWriterLockSlim();
        private double XCoefficient = 1;
        private double YCoefficient = 2;
        private DateTime[] ChannelIntervalTime = new DateTime[8];
        #endregion

        #region 公共方法
        /// <summary>
        /// 初始化构造方法
        /// </summary>
        public ShuLiClass()
        {
            // 加载默认参数
            shuLiConfig = new ShuLiConfigClass()
            {
                Channel = 8,
                PandingCode = 2
            };
            for(int i = 0; i < ChannelIntervalTime.Length; i++)
            {
                ChannelIntervalTime[i] = DateTime.Now;
            }

        }

        /// <summary>
        /// 带参数的构造方法
        /// </summary>
        public ShuLiClass(ShuLiConfigClass config)
        {
            if (config.IsLoadCanfig)
            {
                // 加载传出的参数
                shuLiConfig = config;
                XCoefficient = shuLiConfig.ScaleX;
                YCoefficient = shuLiConfig.ScaleY;
            }
            else
            {
                // 加载默认参数
                shuLiConfig = new ShuLiConfigClass()
                {
                    Channel = 8,
                    PandingCode = 2
                };
            }
            InitChannel();
        }

        public long InitCurrentLine(int line)
        {
            currentLine = line;
            return currentLine;
        }

        public int InitNum(int num)
        {
            ObjectNum = num;
            return ObjectNum;
        }

        List<ActiveObjectClass> lostObjects = new List<ActiveObjectClass>();
        /// <summary>
        /// 处理图像序列的主入口
        /// </summary>
        /// <param name="image">图像像素数据</param>
        /// <param name="ImageWidth">图像宽</param>
        /// <param name="currentLine">当前行数</param>
        /// <returns>检测到的物体总数</returns>
        public bool ProcessImageSequence(IFrameOut image)
        {
            bool result = false;
            ReadOnlySpan<byte> spanFromArr = image.Image.PixelData.AsSpan();
            for (int i = 0; i < image.Image.Height; i++)
            {
                result = ProcessLine2(spanFromArr,image.HostTimeStamp,image.Image.Width, i);
                currentLine += 1;
            }

            //识别到结果并输出

            _rwLock.EnterReadLock();
            // 清理超时未更新的物体
            lostObjects = activeObjects
                .Where(o => (currentLine - o.LastSeenLine) > shuLiConfig.MAX_GAP || (o.LastSeenLine - o.StartLine) > shuLiConfig.MAX_Idetify_Height)
                .ToList();
            _rwLock.ExitReadLock();


            List<ActiveObjectClass> OneActive = new List<ActiveObjectClass>();

            // 有物体转变为活跃物体，返回值转为true
            if (lostObjects.Count > 0)
            {
                Stopwatch stopwatch = Stopwatch.StartNew();
                result = true;
                //stopwatch.Restart();
                foreach (var item in lostObjects)
                {

                    item.PictureEndReadTime = FromUnixTimestamp((long)image.HostTimeStamp);
                    DateTime NowTime = DateTime.Now;
                    var AllPictureUseTime = (item.PictureEndReadTime - item.PictureStartReadTime).TotalMilliseconds;
                    var PictureUsetime = (NowTime - item.PictureStartReadTime).TotalMilliseconds;
                    if (PictureUsetime - AllPictureUseTime > 20)
                        LOG.error($"算法耗时超过了20ms,相机取图总耗时：{AllPictureUseTime},从取第一张图到现在的耗时{PictureUsetime}");
                    //噪点判定
                    if (item.Area < shuLiConfig.NoiseFilter_Threshold)
                    {
                        item.StateCode = 9;
                        //LOG.log(string.Format("噪点过滤，噪点面积：{0}", item.Area), 6);
                        continue;
                    }
                    if(item.StartLine == item.LastSeenLine)
                    {
                        item.MaxLength = item.MaxEndCol - item.MinStartCol;
                        item.StateCode = 10;
                        LOG.log(string.Format("颗粒{0}的有效高度仅一行", item.Num));
                    }
                    else
                    {
                        if((item.LastSeenLine - item.StartLine) < shuLiConfig.MAX_Idetify_Height)
                        {
                            var CalculationResult = SizeCalculation(item.RowsData);
                            if(CalculationResult!=null)
                            {
                                item.MaxLength = CalculationResult.Height;
                            }
                            //item.hasSignificantConcavity = CalculationResult.hasSignificantConcavity;
                            //item.concavityRatio = CalculationResult.concavityRatio;
                            //if(CalculationResult.hasSignificantConcavity)
                            //{
                            //    if(CalculationResult.concavityRatio>0.3)
                            //    {
                            //        item.StateCode= 11;
                            //    }
                            //}
                        }
                        else
                        {
                            item.StateCode = 7;
                        }
                    }
                    if (shuLiConfig.PandingCode != -1)
                    {
                        if (item.StateCode != -1)
                        {
                            if (item.StateCode == 8)
                            {
                                //LOG.log(string.Format("颗粒编号{0}：疑似叠片或缺损", item.Num));
                            }
                            else if (item.StateCode == 7)
                            {
                                //LOG.log(string.Format("颗粒编号{0}：视野被遮挡", item.Num));
                            }
                        }
                        else if (item.Area < shuLiConfig.MinArea
                            && (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 1))
                        {
                            item.StateCode = 6;
                            //LOG.log(string.Format("颗粒编号{0}：面积过小", item.Num));
                            //Console.WriteLine("颗粒编号{0}：面积过小", item.Num);
                        }
                        else if (item.Area > shuLiConfig.MaxArea
                            && (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 1))
                        {
                            item.StateCode = 5;
                            //LOG.log(string.Format("颗粒编号{0}：面积过大", item.Num));
                            //Console.WriteLine("颗粒编号{0}：面积过大", item.Num);
                        }
                        else if (item.MaxLength < shuLiConfig.MIN_Object_LENGTH
                            && (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 0))
                        {
                            item.StateCode = 2;
                            //LOG.log(string.Format("颗粒编号{0}：超短粒", item.Num));
                            //Console.WriteLine("颗粒编号{0}：超短粒", item.Num);
                        }
                        else if (item.MaxLength > shuLiConfig.MAX_Object_LENGTH
                            && (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 0))
                        {
                            item.StateCode = 1;
                            //LOG.log(string.Format("颗粒编号{0}：超长粒", item.Num));
                            //Console.WriteLine("颗粒编号{0}：超长粒", item.Num);
                        }
                        else
                        {
                            item.StateCode = 0;
                            //LOG.log(string.Format("颗粒编号{0}：正常粒", item.Num));
                            //Console.WriteLine("颗粒编号{0}：正常粒", item.Num);
                        }
                    }
                    if(item.StateCode != 7&&item.StateCode!=9)
                    {
                        //转为历史物体，添加缺少的参数
                        item.Num = Interlocked.Increment(ref ObjectNum);
                        item.ChannelNO = ActiveChannel(item);
                    }
                    item.EndCheckTime = DateTime.Now;
                    if(item.StateCode != 9)
                        OneActive.Add(item);
                }
                stopwatch.Stop();
                if (stopwatch.ElapsedMilliseconds > 1)
                {
                    Console.WriteLine($"ShuLiClass-ProcessImageSequence:图像结果分析-结果参数补全，此次识别耗时：{stopwatch.Elapsed}");
                    //FaultLog.RecordErrorMessage($"ShuLiClass-ProcessImageSequence:图像结果分析-结果参数补全，此次识别耗时：{stopwatch.Elapsed}");
                }
                //stopwatch.Restart();
                if (OneActive.Count > 0)
                {
                    //触发回调事件
                    OnWorkCompleted(OneActive);
                }
               // stopwatch.Stop();
                //if (stopwatch.ElapsedMilliseconds > 1)
                //{
                //    FaultLog.RecordErrorMessage($"ShuLiClass-ProcessImageSequence:图像结果分析-结果完成回调函数，此次识别耗时：{stopwatch.Elapsed}");
                //}
            }
            else
            {
                OneActive.Clear();
            }
            _rwLock.EnterWriteLock();
            // 累加到总数并从活跃物体转移到历史物体
            foreach (var item in OneActive)
            {
               TryAdd(historyActiveObjects, item, 2500);
            }
            lostObjects.ForEach(o => activeObjects.Remove(o));
            _rwLock.ExitWriteLock();
            return result;
        }

        /// <summary>
        /// 处理图像序列的主入口
        /// </summary>
        /// <param name="image">图像像素数据</param>
        /// <returns>检测到的物体总数</returns>
        public bool ProcessImageSequence2(IFrameOut image)
        {
            bool result = false;
            ReadOnlySpan<byte> spanFromArr = image.Image.PixelData.AsSpan();
            for (int i = 0; i < image.Image.Height; i++)
            {
                result = ProcessLine2(spanFromArr, image.HostTimeStamp, image.Image.Width, i);
                currentLine += 1;
            }

            // 优化: 减少锁的使用频率，批量处理逻辑
            List<ActiveObjectClass> objectsToProcess = null;
            _rwLock.EnterReadLock();
            try
            {
                // 使用ToList()避免在锁内进行复杂查询
                objectsToProcess = activeObjects
                    .Where(o => (currentLine - o.LastSeenLine) > shuLiConfig.MAX_GAP ||
                               (o.LastSeenLine - o.StartLine) > shuLiConfig.MAX_Idetify_Height)
                    .ToList();
            }
            finally
            {
                _rwLock.ExitReadLock();
            }

            // 优化: 提前返回，避免不必要的处理
            if (objectsToProcess.Count == 0)
            {
                return result;
            }

            // 优化: 预分配容量，减少内存重新分配
            var processedObjects = new List<ActiveObjectClass>(objectsToProcess.Count);

            // 优化: 将耗时的计算移到循环外
            var endTime = DateTime.Now;
            var pictureEndTime = FromUnixTimestamp((long)image.HostTimeStamp);

            foreach (var item in objectsToProcess)
            {
                // 优化: 将耗时的计算移到循环外
                ProcessSingleObject(item, pictureEndTime, endTime, processedObjects);
            }

            result = true;

            // 优化: 批量操作减少锁的持有时间
            if (processedObjects.Count > 0)
            {
                _rwLock.EnterWriteLock();
                try
                {
                    // 批量转移对象
                    foreach (var item in processedObjects)
                    {
                        TryAdd(historyActiveObjects, item, 2500);
                    }

                    // 批量移除
                    foreach (var item in objectsToProcess)
                    {
                        activeObjects.Remove(item);
                    }
                }
                finally
                {
                    _rwLock.ExitWriteLock();
                }

                // 优化: 异步触发事件，避免阻塞主线程
                ThreadPool.QueueUserWorkItem(_ =>
                {
                    OnWorkCompleted(processedObjects);
                });
            }

            return result;
        }

        // 抽取的单个对象处理方法
        private void ProcessSingleObject(ActiveObjectClass item, DateTime pictureEndTime,
                                       DateTime endTime,  List<ActiveObjectClass> processedObjects)
        {
            item.PictureEndReadTime = pictureEndTime;
            var nowTime = DateTime.Now;
            var ShiBieLuoHouTime = (nowTime - item.PictureEndReadTime).TotalMilliseconds;
            // 优化: 将日志记录改为条件执行
            if (ShiBieLuoHouTime > 30)
            {
                LOG.error($"算法落后了超过30ms,相机取图总耗时：{ShiBieLuoHouTime}");
            }

            // 快速滤除噪点
            if (item.Area < shuLiConfig.NoiseFilter_Threshold)
            {
                item.StateCode = 9;
                return;
            }

            // 计算长度
            if (item.StartLine == item.LastSeenLine)
            {
                item.MaxLength = item.MaxEndCol - item.MinStartCol;
                item.StateCode = 10;
                LOG.log(string.Format("颗粒{0}的有效高度仅一行", item.Num));
            }
            else
            {
                if ((item.LastSeenLine - item.StartLine) < shuLiConfig.MAX_Idetify_Height)
                {
                    var calculationResult = SizeCalculation(item.RowsData);
                    if(calculationResult!=null)
                    {
                        item.MaxLength = calculationResult.Height;
                    }
                }
                else
                {
                    item.StateCode = 7;
                }
            }

            // 分类处理
            ApplyClassificationRules(item);

            // 添加到历史记录
            if (item.StateCode != 7 && item.StateCode != 9)
            {
                item.Num = Interlocked.Increment(ref ObjectNum);
                item.ChannelNO = ActiveChannel(item);
            }

            item.EndCheckTime = endTime;

            if (item.StateCode != 9)
            {
                processedObjects.Add(item);
            }
        }

        // 抽取分类规则，便于维护
        private void ApplyClassificationRules(ActiveObjectClass item)
        {
            if (shuLiConfig.PandingCode == -1) return;

            if (item.StateCode != -1)
            {
                if (item.StateCode == 8)
                {
                    LOG.log(string.Format("颗粒编号{0}：疑似叠片或缺损", item.Num));
                }
                else if (item.StateCode == 7)
                {
                    LOG.log(string.Format("颗粒编号{0}：视野被遮挡", item.Num));
                }
            }
            else if (item.Area < shuLiConfig.MinArea &&
                     (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 1))
            {
                item.StateCode = 6;
                LOG.log(string.Format("颗粒编号{0}：面积过小", item.Num));
            }
            else if (item.Area > shuLiConfig.MaxArea &&
                     (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 1))
            {
                item.StateCode = 5;
                LOG.log(string.Format("颗粒编号{0}：面积过大", item.Num));
            }
            else if (item.MaxLength < shuLiConfig.MIN_Object_LENGTH &&
                     (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 0))
            {
                item.StateCode = 2;
                LOG.log(string.Format("颗粒编号{0}：超短粒", item.Num));
            }
            else if (item.MaxLength > shuLiConfig.MAX_Object_LENGTH &&
                     (shuLiConfig.PandingCode == 2 || shuLiConfig.PandingCode == 0))
            {
                item.StateCode = 1;
                LOG.log(string.Format("颗粒编号{0}：超长粒", item.Num));
            }
            else
            {
                item.StateCode = 0;
                LOG.log(string.Format("颗粒编号{0}：正常粒", item.Num));
            }
        }

        /// <summary>
        /// 返回最后一个历史物品
        /// </summary>
        /// <returns></returns>
        public ActiveObjectClass GetLastActive()
        {
            if (historyActiveObjects.Count() == 0)
                return null;
            return historyActiveObjects.Last();
        }

        /// <summary>
        /// 返回历史物品
        /// </summary>
        /// <returns></returns>
        public List<ActiveObjectClass> GetHistoryActive()
        {
            //lock (_lockObj) // 加锁
            //{
            _rwLock.EnterReadLock();
            var result = historyActiveObjects.ToList();
            _rwLock.ExitReadLock();
            return result;
            //}
        }

        /// <summary>
        /// 返回缓存在内存的历史物品的总数量
        /// </summary>
        /// <returns></returns>
        public int GetHistoryActiveNum()
        {
            //lock (_lockObj) // 加锁
            _rwLock.EnterReadLock();
            var result = historyActiveObjects.Where(o=>o.StateCode!=7&&o.StateCode!=9).ToList().Count;
            _rwLock.ExitReadLock();
            return result;
        }

        /// <summary>
        /// 获取历史数据中，正常数据数量
        /// </summary>
        /// <returns></returns>
        public int GetOkHistoryNum()
        {
            //lock (_lockObj)
            _rwLock.EnterReadLock();
            var result = historyActiveObjects.Where(o => o.StateCode != 7 && o.StateCode != 9&& o.StateCode == 0).ToList().Count;
            _rwLock.ExitReadLock();
            return result;
        }

        /// <summary>
        /// 获取历史数据中，异常数据数量
        /// </summary>
        /// <returns></returns>
        public int GetNgHistoryNum()
        {
            //lock (_lockObj)
            _rwLock.EnterReadLock();
            var result = historyActiveObjects.Where(o => o.StateCode != 7 && o.StateCode != 9 && o.StateCode != 0).ToList().Count;
            _rwLock.ExitReadLock();
            return result;
        }

        /// <summary>
        /// 清除历史数据
        /// </summary>
        /// <returns></returns>
        public bool ClearHistoryActive()
        {
            //lock (_lockObj)
            //{
            _rwLock.EnterWriteLock();
            historyActiveObjects.Clear();
            _rwLock.ExitWriteLock();
            return true;
            //}
        }

        /// <summary>
        /// 开启识别
        /// </summary>
        public void StartIdentifyFuntion(int ImaageWidth)
        {
            UpdateIdentifyImageWidth(ImaageWidth);
            InitChannel();
            try
            {
                // 标志位置位true
                IsIdentify = true;
                // 打开识别线程
                IdentifyImageProcessThread = new Thread(IdentifyImageProcess)
                {
                    Priority = ThreadPriority.AboveNormal
                };
                IdentifyImageProcessThread.Start();
                SystemAlarm.AlarmCancel(AlarmMessageList.识别线程启动失败);
            }
            catch (Exception ex)
            {
                SystemAlarm.AlarmAlert(AlarmMessageList.识别线程启动失败,
                    "Start thread failed!, " + ex.Message,
                    "识别线程启动失败, " + ex.Message,
                    "DLL:ShuLiClass-StartIdentifyFuntion");
                //FaultLog.RecordErrorMessage("Start thread failed!, " + ex.Message);
                throw;
            }
        }

        public void StartIdentifyFuntion2(int ImaageWidth)
        {
            UpdateIdentifyImageWidth(ImaageWidth);
            InitChannel();
            try
            {
                CancellationTokenSource = new CancellationTokenSource();
                var token = CancellationTokenSource.Token;

                // 启动图像处理线程
                ProcessingTask = Task.Factory.StartNew(() => IdentifyImageProcessTask(token),
                    token, TaskCreationOptions.LongRunning, TaskScheduler.Default);
                SystemAlarm.AlarmCancel(AlarmMessageList.识别线程启动失败);
            }
            catch (Exception ex)
            {
                SystemAlarm.AlarmAlert(AlarmMessageList.识别线程启动失败,
                    "Start thread failed!, " + ex.Message,
                    "识别线程启动失败, " + ex.Message,
                    "DLL:ShuLiClass-StartIdentifyFuntion");
                //FaultLog.RecordErrorMessage("Start thread failed!, " + ex.Message);
                throw;
            }
        }

        /// <summary>
        /// 关闭识别
        /// </summary>
        public void StopIdentifyFuntion()
        {
            try
            {
                // 标志位设为false
                IsIdentify = false;
                if (IdentifyImageProcessThread != null && IdentifyImageProcessThread.IsAlive)
                    IdentifyImageProcessThread.Join();
                SystemAlarm.AlarmCancel(AlarmMessageList.识别线程停止失败);
            }
            catch (Exception ex)
            {
                //FaultLog.RecordErrorMessage("Stop thread failed!, " + ex.Message);
                SystemAlarm.AlarmAlert(AlarmMessageList.识别线程停止失败,
                    "Stop thread failed!, " + ex.Message,
                    "识别线程停止失败, " + ex.Message,
                    "DLL:ShuLiClass-StopIdentifyFuntion");
                throw;
            }
        }
        public async void StopIdentifyFuntion2()
        {
            try
            {
                // 发送取消信号
                CancellationTokenSource.Cancel();

                // 等待线程完成
                try
                {
                    if (ProcessingTask != null)
                        await ProcessingTask;
                }
                catch (OperationCanceledException)
                {
                    // 正常取消，忽略异常
                }
                SystemAlarm.AlarmCancel(AlarmMessageList.识别线程停止失败);
            }
            catch (Exception ex)
            {
                //FaultLog.RecordErrorMessage("Stop thread failed!, " + ex.Message);
                SystemAlarm.AlarmAlert(AlarmMessageList.识别线程停止失败,
                    "Stop thread failed!, " + ex.Message,
                    "识别线程停止失败, " + ex.Message,
                    "DLL:ShuLiClass-StopIdentifyFuntion");
                throw;
            }
        }

        /// <summary>
        /// 向识别队列添加一个数据
        /// </summary>
        /// <param name="items"></param>
        public void SetOnceIdentifyImageData(IFrameOut items)
        {
            IFrameDatas.Enqueue(items.Clone() as IFrameOut);
            //IFrameDatas.Enqueue(items );
        }

        /// <summary>
        /// 保存参数
        /// </summary>
        public void SaveConfig()
        {
            if (!Directory.Exists(".\\Config\\")) Directory.CreateDirectory(".\\Config\\");
            XmlStorage.SerializeToXml(shuLiConfig, ".\\Config\\ShuLiConfig.xml");
        }

        /// <summary>
        /// 更新检测宽度信息
        /// </summary>
        /// <param name="Width"></param>
        public void UpdateIdentifyImageWidth(int Width)
        {
            IdentifyImageWidth = Width;
        }

        /// <summary>
        /// 初始化通道划分
        /// </summary>
        /// <param name="ImageWidth"></param>
        public void InitChannel()
        {
            _ChannelsRoi.Clear();
            shuLiConfig.ImageWidth = IdentifyImageWidth == -1 ? shuLiConfig.ImageWidth : IdentifyImageWidth;
            if (shuLiConfig.Channel > 0)
            {
                if (shuLiConfig.IsIdentifyRoiOpen)
                {
                    ChannelWidth = (shuLiConfig.IdentifyStopX - shuLiConfig.IdentifyStartX) / shuLiConfig.Channel;
                }
                else
                {
                    ChannelWidth = shuLiConfig.ImageWidth / shuLiConfig.Channel;
                }
                for (int i = 0; i < shuLiConfig.Channel; i++)
                {
                    _ChannelsRoi.Add(ChannelWidth + i * ChannelWidth);
                }
            }
        }

        /// <summary>
        /// 获取配置信息
        /// </summary>
        /// <returns></returns>
        public ShuLiConfigClass GetConfigValue()
        {
            ShuLiConfigClass result = shuLiConfig;

            return result;
        }

        public int GetConfigImageWidth()
        {
            int result = -1;
            if (shuLiConfig != null)
                result = shuLiConfig.ImageWidth;
            return result;
        }

        /// <summary>
        /// 获取坐标转换系数
        /// </summary>
        /// <param name="XCoefficient"></param>
        /// <param name="YCoefficient"></param>
        public void GetXYCoefficient(out double XCoefficient, out double YCoefficient)
        {
            XCoefficient = this.XCoefficient;
            YCoefficient = this.YCoefficient;
        }

        /// <summary>
        /// 设置坐标转换X系数
        /// </summary>
        /// <param name="XCoefficient"></param>
        public void SetXCoefficient(double XCoefficient)
        {
            this.XCoefficient = XCoefficient;
        }

        /// <summary>
        /// 设置坐标转换Y系数
        /// </summary>
        public void SetYCoefficient(double YCoefficient)
        {
            this.YCoefficient = YCoefficient;
        }

        /// <summary>
        /// 获取结果最长长边
        /// </summary>
        /// <param name="Rows"></param>
        /// <returns></returns>
        public BoundingRectangleMdoel SizeCalculation(List<RowStartEndCol> Rows)
        {
            //Stopwatch stopwatch = Stopwatch.StartNew();
            var points = ConvexHull(Rows);
            //stopwatch.Stop();
            //Console.WriteLine($"凸包计算耗时：{stopwatch.Elapsed}");
            //var test = CalculateMinimumBoundingRectangle(points); 
            var result = CoefficientCalculateMinimumBoundingRectangle(points);
            return result;
        }
        public MaxLengthModel SizeCalculation2(List<RowStartEndCol> Rows)
        {
            var points = ConvexHull(Rows);
            var result = CoefficientRotatingCalipers(points);
            return result;
        }

        /// <summary>
        /// 凸包点集合获取
        /// </summary>
        /// <param name="Rows"></param>
        /// <returns></returns>
        public List<Point> ConvexHull(List<RowStartEndCol> Rows)
        {
            List<Point> points = Rows.Select(o => new Point(o.StartCol, (int)o.RowsCol)).ToList();
            points.AddRange(Rows.Select(o => new Point(o.EndCol, (int)o.RowsCol)).ToList());
            points = points.OrderBy(o => o.X).ThenBy(o => o.Y).ToList();
            var lower = new List<Point>();
            foreach (var p in points)
            {
                while (lower.Count >= 2 && Cross(lower[lower.Count - 2], lower[lower.Count - 1], p) <= 0)
                    lower.RemoveAt(lower.Count - 1);
                lower.Add(p);
            }

            var upper = new List<Point>();
            for (int i = points.Count - 1; i >= 0; i--)
            {
                var p = points[i];
                while (upper.Count >= 2 && Cross(upper[upper.Count - 2], upper[upper.Count - 1], p) <= 0)
                    upper.RemoveAt(upper.Count - 1);
                upper.Add(p);
            }

            lower.RemoveAt(lower.Count - 1);
            upper.RemoveAt(upper.Count - 1);
            lower.AddRange(upper);
            return lower;
        }

        /// <summary>
        /// 凸包点集合获取,输出原点集
        /// </summary>
        /// <param name="Rows"></param>
        /// <returns></returns>
        public List<Point> ConvexHull(List<RowStartEndCol> Rows, out List<Point> points)
        {
            points = Rows.Select(o => new Point(o.StartCol, (int)o.RowsCol)).ToList();
            points.AddRange(Rows.Select(o => new Point(o.EndCol, (int)o.RowsCol)).ToList());
            points = points.OrderBy(o => o.X).ThenBy(o => o.Y).ToList();
            var lower = new List<Point>();
            foreach (var p in points)
            {
                while (lower.Count >= 2 && Cross(lower[lower.Count - 2], lower[lower.Count - 1], p) <= 0)
                    lower.RemoveAt(lower.Count - 1);
                lower.Add(p);
            }

            var upper = new List<Point>();
            for (int i = points.Count - 1; i >= 0; i--)
            {
                var p = points[i];
                while (upper.Count >= 2 && Cross(upper[upper.Count - 2], upper[upper.Count - 1], p) <= 0)
                    upper.RemoveAt(upper.Count - 1);
                upper.Add(p);
            }

            lower.RemoveAt(lower.Count - 1);
            upper.RemoveAt(upper.Count - 1);
            lower.AddRange(upper);
            return lower;
        }

        /// <summary>
        /// 凸包点集合获取，同时检测较大的内凹
        /// </summary>
        /// <param name="Rows"></param>
        /// <returns>返回凸包点集</returns>
        public ConvexResultClass ConvexHullWithConcavityDetection(List<RowStartEndCol> Rows)
        {
            ConvexResultClass result = null;
            // 构建原始点集
            var lower = ConvexHull(Rows, out List<Point> originalPoints);

            // 检测内凹
            ConvexResultClass ConvexResult = DetectConcavity(originalPoints, lower);

            return result = new ConvexResultClass()
            {
                convexHull = lower,
                hasSignificantConcavity = ConvexResult.hasSignificantConcavity,
                concavityRatio = ConvexResult.concavityRatio,
            };
        }
        #endregion

        #region 私有方法

        public DateTime FromUnixTimestamp(long timestamp, bool isMilliseconds = false)
        {
            try
            {
                // 如果未指定单位，尝试自动检测
                if (!isMilliseconds)
                {
                    // 如果时间戳看起来像毫秒级（13位数字）
                    if (timestamp.ToString().Length > 10)
                    {
                        isMilliseconds = true;
                    }
                }

                if (isMilliseconds)
                {
                    // 验证毫秒级时间戳范围
                    const long minMilliTimestamp = -62135596800000; // 0001-01-01 00:00:00 UTC
                    const long maxMilliTimestamp = 253402300799999; // 9999-12-31 23:59:59 UTC

                    if (timestamp < minMilliTimestamp || timestamp > maxMilliTimestamp)
                    {
                        throw new ArgumentOutOfRangeException(nameof(timestamp),
                            "毫秒级时间戳超出有效范围");
                    }

                    DateTime origin = new DateTime(1970, 1, 1, 0, 0, 0, 0, DateTimeKind.Utc).AddMilliseconds(timestamp);
                    return TimeZoneInfo.ConvertTimeFromUtc(origin, TimeZoneInfo.Local);
                }
                else
                {
                    // 验证秒级时间戳范围
                    const long minTimestamp = -62135596800;
                    const long maxTimestamp = 253402300799;

                    if (timestamp < minTimestamp || timestamp > maxTimestamp)
                    {
                        throw new ArgumentOutOfRangeException(nameof(timestamp),
                            "秒级时间戳超出有效范围");
                    }

                    DateTime origin = new DateTime(1970, 1, 1, 0, 0, 0, 0, DateTimeKind.Utc).AddSeconds(timestamp);
                    return TimeZoneInfo.ConvertTimeFromUtc(origin, TimeZoneInfo.Local);
                }
            }
            catch (ArgumentOutOfRangeException)
            {
                throw;
            }
            catch (Exception ex)
            {
                throw new ArgumentException($"无法转换时间戳 {timestamp}: {ex.Message}", ex);
            }
        }

        /// <summary>
        /// 对外通知事件
        /// </summary>
        private void OnWorkCompleted(List<ActiveObjectClass> activeObject)
        {
            if(activeObject == null) return;
            ActiveObjectEventArgsClass activeObjectEventArgs = new ActiveObjectEventArgsClass(activeObject);
            // 触发事件
            WorkCompleted?.Invoke(this, activeObjectEventArgs);
        }

        private bool IsPrintLightOnError = false;
        List<ValidRegionModelClass> currentRegions = null;
        /// <summary>
        /// 处理单行像素数据
        /// 返回值为false的时候无活跃物体转变为历史物体
        /// 返回值为true的时候有活跃物体转变为历史物体
        /// </summary>
        /// <param name="image">当前行像素数组</param>
        private bool ProcessLine(IFrameOut imagedata, int RowNo)
        {
            //Stopwatch stopwatch = Stopwatch.StartNew();
            bool result = false;
            // 步骤1：检测当前行的有效区域
            var currentRegions = FindValidRegions(imagedata.Image, RowNo);
            if (currentRegions.Count == 0) return result;
            if (currentRegions.Count == 1)
            {
                if (currentRegions[0].End - (currentRegions[0]).Start + 1 == imagedata.Image.Width)
                {
                    if (!IsPrintLightOnError)
                    {
                        FaultLog.RecordLogMessage("The current effective area is the entire row. Check the field of view and light source", 6);
                        IsPrintLightOnError = true;
                    }
                    return false;
                }
            }
            IsPrintLightOnError = false;
            //stopwatch.Stop();
            //if (stopwatch.ElapsedMilliseconds > 1)
            //{
            //    FaultLog.RecordErrorMessage($"ShuLiClass-ProcessLine:图像连通域检测超时，此次识别耗时：{stopwatch.Elapsed}");
            //}
            //stopwatch.Restart();
            foreach (var region in currentRegions)
            {

                // 查找全部可合并的活跃物体（有重叠+在允许间隔内）
                _rwLock.EnterReadLock();
                var matcheds = activeObjects.Where(o =>
                    IsOverlapping(o, region) &&
                    (currentLine - o.LastSeenLine - 1) <= shuLiConfig.MAX_GAP).ToList();
                _rwLock.ExitReadLock();
                //当有多个可合并的活跃物体时，将多个物体合并
                if (matcheds.Count >= 2)
                {
                    // 合并有效区域队列
                    var CopeRowsData = new List<RowStartEndCol>();
                    matcheds.ForEach(o => CopeRowsData = CopeRowsData.Concat(o.RowsData).ToList());
                    // 合并有效区域并保存在新的区域中
                    var MergeMatched = new ActiveObjectClass
                    {
                        MinStartCol = matcheds.Min(o => o.MinStartCol),
                        MaxEndCol = matcheds.Max(o => o.MaxEndCol),
                        StartLine = matcheds.Min(o => o.StartLine),
                        LastSeenLine = matcheds.Max(o => o.LastSeenLine),
                        LastSeenLineStartCol = matcheds.Min(o => o.LastSeenLineStartCol),
                        LastSeenLineEndCol = matcheds.Max(o => o.LastSeenLineEndCol),
                        StartCheckTime = matcheds.Min(o => o.StartCheckTime),
                        EndCheckTime = matcheds.Max(o => o.EndCheckTime),
                        Area = matcheds.Sum(o => o.Area),
                        RowsData = CopeRowsData,
                        ImageWidth = matcheds.FirstOrDefault().ImageWidth,
                        StateCode = 8
                    };
                    _rwLock.EnterWriteLock();
                    // 从活跃区域中删除被合并的区域
                    matcheds.ForEach(o => activeObjects.Remove(o));
                    // 保存新的区域到活跃区域中
                    activeObjects.Add(MergeMatched);
                    _rwLock.ExitWriteLock();
                }
                _rwLock.EnterReadLock();
                // 搜获可用且可合并的活跃区域
                var matched = activeObjects.FirstOrDefault(o =>
                    IsOverlapping(o, region) &&
                    (currentLine - o.LastSeenLine - 1) <= shuLiConfig.MAX_GAP);
                _rwLock.ExitReadLock();
                if (matched != null)
                {
                    // 合并区域：扩展物体边界并更新状态
                    matched.MinStartCol = Math.Min(matched.MinStartCol, region.Start);
                    matched.MaxEndCol = Math.Max(matched.MaxEndCol, region.End);
                    matched.Area += region.End - region.Start + 1;
                    matched.LastSeenLine = currentLine;
                    matched.RowsData.Add(new RowStartEndCol
                    {
                        StartCol = region.Start,
                        EndCol = region.End,
                        RowsCol = currentLine,
                    });
                    matched.LastSeenLineStartCol = region.Start;
                    matched.LastSeenLineEndCol = region.End;
                }
                else
                {
                    _rwLock.EnterWriteLock();
                    // 创建新物体（首次出现的区域）
                    activeObjects.Add(new ActiveObjectClass
                    {
                        MinStartCol = region.Start,
                        MaxEndCol = region.End,
                        StartLine = currentLine,
                        LastSeenLine = currentLine,
                        LastSeenLineStartCol = region.Start,
                        LastSeenLineEndCol = region.End,
                        StartCheckTime = DateTime.Now,
                        PictureStartReadTime = FromUnixTimestamp((long)imagedata.HostTimeStamp),
                        Area = region.End - region.Start + 1,
                        ImageWidth = IdentifyImageWidth,
                        RowsData = new List<RowStartEndCol> {
                            new RowStartEndCol {
                                StartCol = region.Start,
                                EndCol = region.End,
                                RowsCol = currentLine,
                            }
                        }
                    });
                    _rwLock.ExitWriteLock();
                }
            }

            //stopwatch.Stop();
            //if (stopwatch.ElapsedMilliseconds > 1)
            //{
            //    FaultLog.RecordErrorMessage($"ShuLiClass-ProcessLine:图像区域合并超时，此次识别耗时：{stopwatch.Elapsed}");
            //}
            return result;
        }
        private bool ProcessLine2(ReadOnlySpan<byte> image, ulong ImageHostTime, uint imageWidth, int RowNo)
        {
            // 缓存配置值
            int maxGap = shuLiConfig.MAX_GAP;
            long currentTimeLine = currentLine;

            // 步骤1：检测当前行的有效区域
            currentRegions = FindValidRegions(image, (int)imageWidth, RowNo);

            if (currentRegions.Count == 0|| currentRegions == null) return false;

            if (currentRegions.Count == 1)
            {
                if (currentRegions[0].End - (currentRegions[0]).Start + 1 == imageWidth)
                {
                    if (!IsPrintLightOnError)
                    {
                        FaultLog.RecordLogMessage("The current effective area is the entire row. Check the field of view and light source", 6);
                        IsPrintLightOnError = true;
                    }
                    return false;
                }
            }
            IsPrintLightOnError = false;

            // 批量处理操作列表
            var operations = new List<OperationItem>();
            var currentActiveObjects = new List<ActiveObjectClass>();

            // 一次性获取当前活跃物体快照
            _rwLock.EnterReadLock();
            try
            {
                currentActiveObjects = new List<ActiveObjectClass>(activeObjects);
            }
            finally
            {
                _rwLock.ExitReadLock();
            }

            foreach (var region in currentRegions)
            {
                // 查找所有可合并的活跃物体（重叠+在允许间隔内）
                var matcheds = currentActiveObjects.Where(o =>
                    IsOverlapping(o, region) &&
                    (currentTimeLine - o.LastSeenLine - 1) <= maxGap).ToList();

                // 当有多个可合并的活跃物体时，将多个物体合并
                if (matcheds.Count >= 2)
                {
                    // 计算聚合值（单次遍历）
                    var aggregateResult = CalculateAggregates(matcheds);

                    var mergedObject = new ActiveObjectClass
                    {
                        MinStartCol = aggregateResult.minStartCol,
                        MaxEndCol = aggregateResult.maxEndCol,
                        StartLine = aggregateResult.minStartLine,
                        LastSeenLine = aggregateResult.maxLastSeenLine,
                        LastSeenLineStartCol = aggregateResult.minLastSeenStartCol,
                        LastSeenLineEndCol = aggregateResult.maxLastSeenEndCol,
                        StartCheckTime = aggregateResult.minStartTime,
                        EndCheckTime = aggregateResult.maxEndTime,
                        PictureStartReadTime = aggregateResult.pictureMinReadTime,
                        Area = aggregateResult.totalArea,
                        RowsData = aggregateResult.mergedRowsData,
                        ImageWidth = aggregateResult.imageWidth,
                        StateCode = 8
                    };

                    operations.Add(new OperationItem
                    {
                        Type = OperationType.MergeMultiple,
                        ObjectsToRemove = matcheds,
                        ObjectToAdd = mergedObject
                    });

                    // 从currentActiveObjects中移除已处理的物体，避免重复处理
                    foreach (var obj in matcheds)
                    {
                        currentActiveObjects.Remove(obj);
                    }
                }
                else
                {
                    // 查找单一匹配物体
                    var matched = matcheds.FirstOrDefault();
                    if (matched != null)
                    {
                        operations.Add(new OperationItem
                        {
                            Type = OperationType.Update,
                            ObjectToUpdate = matched,
                            Region = region
                        });
                    }
                    else
                    {
                        // 创建新物体
                        var newObject = new ActiveObjectClass
                        {
                            MinStartCol = region.Start,
                            MaxEndCol = region.End,
                            StartLine = currentTimeLine,
                            LastSeenLine = currentTimeLine,
                            LastSeenLineStartCol = region.Start,
                            LastSeenLineEndCol = region.End,
                            StartCheckTime = DateTime.Now,
                            PictureStartReadTime = FromUnixTimestamp((long)ImageHostTime),
                            Area = region.End - region.Start + 1,
                            ImageWidth = IdentifyImageWidth,
                            RowsData = new List<RowStartEndCol> {
                                new RowStartEndCol {
                                    StartCol = region.Start,
                                    EndCol = region.End,
                                    RowsCol = currentTimeLine,
                                }
                            }
                        };
                        operations.Add(new OperationItem
                        {
                            Type = OperationType.Add,
                            ObjectToAdd = newObject
                        });
                    }
                }
            }

            currentRegions.Clear();
            // 执行所有操作（最小化锁持有时间）
            bool hasChanges = false;
            if (operations.Count > 0)
            {
                _rwLock.EnterWriteLock();
                try
                {
                    foreach (var op in operations)
                    {
                        switch (op.Type)
                        {
                            case OperationType.MergeMultiple:
                                // 移除被合并的物体
                                foreach (var objItem in op.ObjectsToRemove)
                                {
                                    activeObjects.Remove(objItem);
                                }
                                // 添加合并后的物体
                                activeObjects.Add(op.ObjectToAdd);
                                break;

                            case OperationType.Update:
                                // 更新现有物体
                                var obj = op.ObjectToUpdate;
                                obj.MinStartCol = Math.Min(obj.MinStartCol, op.Region.Start);
                                obj.MaxEndCol = Math.Max(obj.MaxEndCol, op.Region.End);
                                obj.Area += op.Region.End - op.Region.Start + 1;
                                obj.LastSeenLine = currentTimeLine;
                                obj.RowsData.Add(new RowStartEndCol
                                {
                                    StartCol = op.Region.Start,
                                    EndCol = op.Region.End,
                                    RowsCol = currentTimeLine,
                                });
                                obj.LastSeenLineStartCol = op.Region.Start;
                                obj.LastSeenLineEndCol = op.Region.End;
                                break;

                            case OperationType.Add:
                                activeObjects.Add(op.ObjectToAdd);
                                break;
                        }
                    }

                    hasChanges = true;
                }
                finally
                {
                    _rwLock.ExitWriteLock();
                }
            }

            return hasChanges;
        }

        // 辅助类定义
        private enum OperationType
        {
            MergeMultiple,
            Update,
            Add
        }

        private class OperationItem
        {
            public OperationType Type { get; set; }
            public List<ActiveObjectClass> ObjectsToRemove { get; set; }
            public ActiveObjectClass ObjectToAdd { get; set; }
            public ActiveObjectClass ObjectToUpdate { get; set; }
            public ValidRegionModelClass Region { get; set; }
        }

        // 计算聚合值的方法
        private (int minStartCol, int maxEndCol, long minStartLine, long maxLastSeenLine,
                 int minLastSeenStartCol, int maxLastSeenEndCol, DateTime minStartTime,
                 DateTime maxEndTime,DateTime pictureMinReadTime,int totalArea, List<RowStartEndCol> mergedRowsData, int imageWidth)
        CalculateAggregates(List<ActiveObjectClass> objects)
        {
            int minStartCol = int.MaxValue;
            int maxEndCol = int.MinValue;
            long minStartLine = int.MaxValue;
            long maxLastSeenLine = int.MinValue;
            int minLastSeenStartCol = int.MaxValue;
            int maxLastSeenEndCol = int.MinValue;
            DateTime minStartTime = DateTime.MaxValue;
            DateTime maxEndTime = DateTime.MinValue;
            DateTime pictureMinReadTime = DateTime.MaxValue;
            int totalArea = 0;
            int imageWidth = objects.FirstOrDefault()?.ImageWidth ?? IdentifyImageWidth;

            var mergedRowsData = new List<RowStartEndCol>();

            foreach (var obj in objects)
            {
                minStartCol = Math.Min(minStartCol, obj.MinStartCol);
                maxEndCol = Math.Max(maxEndCol, obj.MaxEndCol);
                minStartLine = Math.Min(minStartLine, obj.StartLine);
                maxLastSeenLine = Math.Max(maxLastSeenLine, obj.LastSeenLine);
                minLastSeenStartCol = Math.Min(minLastSeenStartCol, obj.LastSeenLineStartCol);
                maxLastSeenEndCol = Math.Max(maxLastSeenEndCol, obj.LastSeenLineEndCol);

                if (obj.StartCheckTime < minStartTime) minStartTime = obj.StartCheckTime;
                if (obj.EndCheckTime > maxEndTime) maxEndTime = obj.EndCheckTime;
                if (obj.PictureStartReadTime<pictureMinReadTime) pictureMinReadTime = obj.PictureStartReadTime;

                totalArea += obj.Area;
                mergedRowsData.AddRange(obj.RowsData);
            }

            return (minStartCol, maxEndCol, minStartLine, maxLastSeenLine,
                    minLastSeenStartCol, maxLastSeenEndCol, minStartTime,
                    maxEndTime,pictureMinReadTime,totalArea, mergedRowsData, imageWidth);
        }

        List<ValidRegionModelClass> regions = new List<ValidRegionModelClass>();
        /// <summary>
        /// 检测有效物体区域（横向连续黑色像素段）
        /// </summary>
        /// <param name="line">当前行像素数组</param>
        /// <returns>有效区域列表（起始/结束位置）</returns>
        private List<ValidRegionModelClass> FindValidRegions(IImage image, int RowNo)
        {
            regions.Clear();
            int start = -1; // 当前区域起始标记
            int end = -1;
            int imageWidth = (int)image.Width;
            var pixelSpan = image.PixelData.AsSpan();
            // 遍历所有像素列
            if (shuLiConfig.IsIdentifyRoiOpen)
            {
                for (int i = imageWidth * RowNo + shuLiConfig.IdentifyStartX; i < imageWidth * RowNo + shuLiConfig.IdentifyStopX; i++)
                {
                    if (pixelSpan[i] < shuLiConfig.RegionThreshold&& start == -1) // 发现黑色像素
                    {
                        start = i % imageWidth; // 开始新区域
                    }
                    else if (start != -1) // 遇到白色像素且存在进行中的区域
                    {
                        end = (i - 1) % imageWidth;
                        // 检查区域宽度是否达标
                        regions.Add(new ValidRegionModelClass()
                        {
                            Start = start,
                            End = end
                        }); // 记录有效区域
                        start = -1; // 重置区域标记
                        end = -1;
                    }
                }
            }
            else
            {
                for (int i = imageWidth * RowNo; i < imageWidth * (RowNo + 1); i++)
                {
                    if (pixelSpan[i] < shuLiConfig.RegionThreshold) // 发现黑色像素
                    {
                        if (start == -1) start = i % imageWidth; // 开始新区域
                    }
                    else if (start != -1) // 遇到白色像素且存在进行中的区域
                    {
                        end = (i - 1) % imageWidth;
                        regions.Add(new ValidRegionModelClass()
                        {
                            Start = start,
                            End = end
                        }); // 记录有效区域
                        start = -1; // 重置区域标记
                        end = -1;
                    }
                }
            }


            // 处理行尾未闭合的区域
            if (start != -1 && image.Width - start >= shuLiConfig.NoiseFilter_Threshold)
            {
                regions.Add(new ValidRegionModelClass()
                {
                    Start = start,
                    End = (int)image.Width - 1
                });
            }
            return new List<ValidRegionModelClass>(regions);
        }

        private List<ValidRegionModelClass> FindValidRegions(ReadOnlySpan<byte> image,int imageWidth, int RowNo)
        {
            regions.Clear();
            regions.Capacity = 10;

            ReadOnlySpan<byte> rowSpan;
            if (shuLiConfig.IsIdentifyRoiOpen)
            {
                int offset = RowNo * imageWidth + shuLiConfig.IdentifyStartX;
                int length = Math.Min(shuLiConfig.IdentifyStopX - shuLiConfig.IdentifyStartX,
                                     imageWidth - shuLiConfig.IdentifyStartX);
                rowSpan = image.Slice(offset, length);
            }
            else
            {
                rowSpan = image.Slice(RowNo * imageWidth, imageWidth);
            }

            int start = -1;
            byte threshold = (byte)shuLiConfig.RegionThreshold;

            for (int i = 0; i < rowSpan.Length; i++)
            {
                if (rowSpan[i] < threshold)
                {
                    if (start == -1) start = i;
                }
                else if (start != -1)
                {
                    regions.Add(new ValidRegionModelClass { Start = start, End = i - 1 });
                    start = -1;
                }
            }

            if (start != -1)
            {
                regions.Add(new ValidRegionModelClass { Start = start, End = rowSpan.Length - 1 });
            }

            return new List<ValidRegionModelClass>(regions);
        }

        /// <summary>
        /// 判断区域重叠（与活跃物体的横向坐标重叠检测）
        /// </summary>
        /// <param name="obj">活跃物体</param>
        /// <param name="region">当前区域</param>
        /// <returns>是否发生重叠</returns>
        private bool IsOverlapping(ActiveObjectClass obj, ValidRegionModelClass region)
        {
            // 判断区域是否不相交的逆条件
            return !(region.End < obj.LastSeenLineStartCol || region.Start > obj.LastSeenLineEndCol);
        }

        /// <summary>
        /// 通道区域判定
        /// </summary>
        /// <param name="activeObject"></param>
        /// <returns></returns>
        private int ActiveChannel(ActiveObjectClass activeObject)
        {
            int result = -1;
            int StartChannel = activeObject.MinStartCol / ChannelWidth;
            int EndChannel = activeObject.MaxEndCol / ChannelWidth;
            if (StartChannel == EndChannel)
            {
                result = StartChannel;
            }
            else if (EndChannel - StartChannel > 1)
            {
                Console.WriteLine("ActiveChannel-Error");
                //error
            }
            else
            {
                result = _ChannelsRoi[StartChannel] - activeObject.MinStartCol > activeObject.MaxEndCol - _ChannelsRoi[StartChannel] ? StartChannel : EndChannel;
            }
            return result;
        }

        /// <summary>
        /// 检测是否存在显著的内凹
        /// </summary>
        /// <param name="originalPoints">原始点集</param>
        /// <param name="convexHull">凸包点集</param>
        /// <returns>是否存在显著内凹和程度比值</returns>
        private ConvexResultClass DetectConcavity(List<Point> originalPoints, List<Point> convexHull)
        {
            if (convexHull.Count < 3) return new ConvexResultClass()
            {
                hasSignificantConcavity = false,
                concavityRatio = 0,
            };

            // 检查原始点集中有多少点在凸包内部（即非凸包顶点）
            HashSet<Point> hullPoints = new HashSet<Point>(convexHull);
            var internalPoints = originalPoints.Where(p => !hullPoints.Contains(p)).ToList();

            if (internalPoints.Count == 0)
            {
                // 所有点都在凸包上，没有内凹
                return new ConvexResultClass()
                {
                    hasSignificantConcavity = false,
                    concavityRatio = 0,
                };
            }

            // 计算凸包面积
            double convexHullArea = CalculatePolygonArea(SortPointsByNearestNeighbor(convexHull));

            double PointsArea = CalculatePolygonArea(SortPointsByNearestNeighbor(originalPoints));

            var concavityMeasure = (convexHullArea - PointsArea) / convexHullArea;


            // 判断是否存在显著内凹（可以根据实际需求调整阈值）
            bool hasSignificantConcavity = concavityMeasure > 0.3;

            return new ConvexResultClass()
            {
                hasSignificantConcavity = hasSignificantConcavity,
                concavityRatio = concavityMeasure,
            }; 
        }

        /// <summary>
        /// 计算封闭多边形的面积（鞋带公式）
        /// </summary>
        /// <param name="polygon">多边形顶点（必须是封闭的）</param>
        /// <returns>面积</returns>
        private double CalculatePolygonArea(List<Point> polygon)
        {
            if (polygon.Count < 3) return 0;

            // 确保多边形是封闭的
            var closedPolygon = new List<Point>(polygon);
            if (closedPolygon.First() != closedPolygon.Last())
            {
                closedPolygon.Add(closedPolygon[0]);
            }

            double area = 0;
            for (int i = 0; i < closedPolygon.Count - 1; i++)
            {
                area += (double)closedPolygon[i].X * closedPolygon[i + 1].Y;
                area -= (double)closedPolygon[i].Y * closedPolygon[i + 1].X;
            }

            return Math.Abs(area) / 2.0;
        }


        /// <summary>
        /// 凸包最长边,结果通过系数计算
        /// </summary>
        /// <param name="hull"></param>
        /// <returns></returns>
        public MaxLengthModel CoefficientRotatingCalipers(List<Point> hull)
        {
            //老方法
            MaxLengthModel result = new MaxLengthModel();
            int n = hull.Count;
            if (n == 1)
            {
                result = null;
                return result;
            }
            if (n == 2)
            {
                result.MaxLength = Distance(hull[0], hull[1]);
                result.Point1Index = 0;
                result.Point1 = hull[0];
                result.Point2Index = 1;
                result.Point2 = hull[1];
                return result;
            }

            double maxDist = 0;
            int pointIndex1 = 0;
            int pointIndex2 = 0;

            for (int i = 0; i < n; i++)
            {
                for (int j = i + 1; j < n; j++)
                {
                    if (CoefficientDistance(hull[i], hull[j]) > maxDist)
                    {
                        maxDist = CoefficientDistance(hull[i], hull[j]);
                        pointIndex1 = i;
                        pointIndex2 = j;
                    }

                }
            }

            result.Point1 = hull[pointIndex1];
            result.Point1Index = pointIndex1;
            result.Point2 = hull[pointIndex2];
            result.Point2Index = pointIndex2;
            result.MaxLength = maxDist;

            return result;
        }

        /// <summary>
        /// 凸包最长边
        /// </summary>
        /// <param name="hull"></param>
        /// <returns></returns>
        public MaxLengthModel RotatingCalipers(List<Point> hull)
        {
            //老方法
            MaxLengthModel result = new MaxLengthModel();
            int n = hull.Count;
            if (n == 1)
            {
                result = null;
                return result;
            }
            if (n == 2)
            {
                result.MaxLength = Distance(hull[0], hull[1]);
                result.Point1Index = 0;
                result.Point1 = hull[0];
                result.Point2Index = 1;
                result.Point2 = hull[1];
                return result;
            }

            double maxDist = 0;
            int pointIndex1 = 0;
            int pointIndex2 = 0;

            for (int i = 0; i < n; i++)
            {
                for (int j = i + 1; j < n; j++)
                {
                    if (Distance(hull[i], hull[j]) > maxDist)
                    {
                        maxDist = Distance(hull[i], hull[j]);
                        pointIndex1 = i;
                        pointIndex2 = j;
                    }

                }
            }

            result.Point1 = hull[pointIndex1];
            result.Point1Index = pointIndex1;
            result.Point2 = hull[pointIndex2];
            result.Point2Index = pointIndex2;
            result.MaxLength = Distance(result.Point1, result.Point2);

            return result;
        }

        /// <summary>
        /// 计算凸包的最小外接矩形
        /// </summary>
        /// <param name="convexHull">凸包顶点列表（按逆时针顺序排列）</param>
        /// <returns>最小外接矩形的四个顶点</returns>
        public BoundingRectangleMdoel CalculateMinimumBoundingRectangle(List<Point> convexHull)
        {
            BoundingRectangleMdoel result = new BoundingRectangleMdoel();
            if (convexHull == null || convexHull.Count < 3)
                return null;

            double minArea = double.MaxValue;

            int n = convexHull.Count;

            // 遍历每一条边作为基准边
            for (int i = 0; i < n; i++)
            {
                Point edgeStart = convexHull[i];
                Point edgeEnd = convexHull[(i + 1) % n];

                // 计算当前边的角度
                double angle = Math.Atan2(edgeEnd.Y - edgeStart.Y, edgeEnd.X - edgeStart.X);

                // 将所有点绕原点旋转-angle角度，使当前边与x轴平行
                var rotatedPoints = convexHull.Select(p => RotatePoint(p, -angle)).ToList();

                // 找到包围盒
                int minX = rotatedPoints.Min(p => p.X);
                int maxX = rotatedPoints.Max(p => p.X);
                int minY = rotatedPoints.Min(p => p.Y);
                int maxY = rotatedPoints.Max(p => p.Y);

                // 计算面积
                double area = (maxX - minX) * (maxY - minY);

                // 如果面积更小，则更新最小矩形
                if (area < minArea)
                {
                    minArea = area;

                    // 构造矩形的四个顶点并旋转回原来的角度
                    var rectangle = new List<Point>
                    {
                         RotatePoint(new Point(minX, minY), angle),
                         RotatePoint(new Point(maxX, minY), angle),
                         RotatePoint(new Point(maxX, maxY), angle),
                         RotatePoint(new Point(minX, maxY), angle)
                    };

                    result.points = rectangle;
                    result.Angle = angle;
                    result.CenterPoint = RotatePoint(new Point((maxX + minX) / 2, (maxY + minY) / 2), angle);
                }
            }

            double l1 = Distance(result.points[0], result.points[1]);
            double l2 = Distance(result.points[1], result.points[2]);

            if (l1 < l2)
            {
                result.WidthPoints = new List<Point>
                {
                    result.points[0],
                    result.points[1],
                };
                result.HeightPoints = new List<Point>
                {
                    result.points[1],
                    result.points[2],
                };
            }
            else
            {
                result.WidthPoints = new List<Point>
                {
                    result.points[2],
                    result.points[1],
                };
                result.HeightPoints = new List<Point>
                {
                    result.points[1],
                    result.points[0],
                };
            }

            result.Height = Math.Max(l1, l2);
            result.Width = Math.Min(l1, l2);

            return result;
        }

        /// <summary>
        /// 计算凸包的最小外接矩形
        /// </summary>
        /// <param name="convexHull">凸包顶点列表（按逆时针顺序排列）</param>
        /// <returns>最小外接矩形的四个顶点</returns>
        public BoundingRectangleMdoel CoefficientCalculateMinimumBoundingRectangle(List<Point> convexHull)
        {
            BoundingRectangleMdoel result = new BoundingRectangleMdoel();
            if (convexHull == null || convexHull.Count < 3)
                return null;

            double minArea = double.MaxValue;

            int n = convexHull.Count;

            // 遍历每一条边作为基准边
            for (int i = 0; i < n; i++)
            {
                Point edgeStart = convexHull[i];
                Point edgeEnd = convexHull[(i + 1) % n];

                // 计算当前边的角度
                double angle = Math.Atan2(edgeEnd.Y - edgeStart.Y, edgeEnd.X - edgeStart.X);

                // 将所有点绕原点旋转-angle角度，使当前边与x轴平行
                var rotatedPoints = convexHull.Select(p => RotatePoint(p, -angle)).ToList();

                // 找到包围盒
                int minX = rotatedPoints.Min(p => p.X);
                int maxX = rotatedPoints.Max(p => p.X);
                int minY = rotatedPoints.Min(p => p.Y);
                int maxY = rotatedPoints.Max(p => p.Y);

                // 计算面积
                double area = (maxX - minX) * (maxY - minY);

                // 如果面积更小，则更新最小矩形
                if (area < minArea)
                {
                    minArea = area;

                    // 构造矩形的四个顶点并旋转回原来的角度
                    var rectangle = new List<Point>
                    {
                         RotatePoint(new Point(minX, minY), angle),
                         RotatePoint(new Point(maxX, minY), angle),
                         RotatePoint(new Point(maxX, maxY), angle),
                         RotatePoint(new Point(minX, maxY), angle)
                    };

                    result.points = rectangle;
                    result.Angle = angle;
                    result.CenterPoint = RotatePoint(new Point((maxX + minX) / 2, (maxY + minY) / 2), angle);
                }
            }

            double l1 = CoefficientDistance(result.points[0], result.points[1]);
            double l2 = CoefficientDistance(result.points[1], result.points[2]);

            if (l1 < l2)
            {
                result.WidthPoints = new List<Point>
                {
                    result.points[0],
                    result.points[1],
                };
                result.HeightPoints = new List<Point>
                {
                    result.points[1],
                    result.points[2],
                };
            }
            else
            {
                result.WidthPoints = new List<Point>
                {
                    result.points[2],
                    result.points[1],
                };
                result.HeightPoints = new List<Point>
                {
                    result.points[1],
                    result.points[0],
                };
            }

            result.Height = Math.Max(l1, l2);
            result.Width = Math.Min(l1, l2);

            return result;
        }

        public List<Point> SortPointsByNearestNeighbor(List<Point> points)
        {
            if (points.Count <= 1) return points;

            var sorted = new List<Point>();
            var remaining = new HashSet<Point>(points);

            // 选择起始点（例如最左边的点）
            var current = remaining.OrderBy(p => p.X).First();
            sorted.Add(current);
            remaining.Remove(current);

            while (remaining.Any())
            {
                // 找到最近的点
                var nearest = remaining.OrderBy(p => Distance(current, p)).First();
                sorted.Add(nearest);
                remaining.Remove(nearest);
                current = nearest;
            }

            return sorted;
        }

        /// <summary>
        /// 绕原点旋转点
        /// </summary>
        /// <param name="point">待旋转的点</param>
        /// <param name="angle">旋转角度（弧度）</param>
        /// <returns>旋转后的点</returns>
        private static Point RotatePoint(Point point, double angle)
        {
            double cos = Math.Cos(angle);
            double sin = Math.Sin(angle);

            return new Point(
                (int)(point.X * cos - point.Y * sin),
                (int)(point.X * sin + point.Y * cos)
            );
        }

        /// <summary>
        /// 计算点到线段的距离
        /// </summary>
        /// <param name="a">线段点1</param>
        /// <param name="b">线段点2</param>
        /// <param name="c">点三</param>
        /// <returns></returns>
        private double DistanceToLine(Point a, Point b, Point c)
        {
            double area = Math.Abs(Area2(a, b, c));
            double baseLength = Distance(a, b);
            return area / baseLength;
        }

        // 计算向量叉积
        private int Cross(Point o, Point a, Point b) =>
            (a.X - o.X) * (b.Y - o.Y) - (a.Y - o.Y) * (b.X - o.X);

        // 计算三角形面积的两倍
        private int Area2(Point a, Point b, Point c) =>
            (b.X - a.X) * (c.Y - a.Y) - (b.Y - a.Y) * (c.X - a.X);

        // 计算两点间距离
        private double Distance(Point a, Point b)
        {
            int dx = a.X - b.X;
            int dy = a.Y - b.Y;
            return Math.Sqrt((dx * dx) + (dy * dy));
        }

        private double CoefficientDistance(Point a,Point b)
        {
            double dx = (a.X - b.X) * XCoefficient;
            double dy = (a.Y - b.Y) * YCoefficient;
            return Math.Sqrt((dx * dx) + (dy * dy));
        }

        private bool TryAdd(List<ActiveObjectClass> list, ActiveObjectClass item, int maxSize)
        {
            list.Add(item);
            if (list.Count > maxSize)
            {
                list[list.Count - maxSize].RowsData.Clear();
            }
            return true;
        }
        #endregion

        #region 线程方法
        //信号量
        public SemaphoreSlim QueueSemaphore { get; set; }
        //取消令牌
        public CancellationTokenSource CancellationTokenSource { get; set; }
        //图像处理线程
        public Task ProcessingTask { get; set; }
        /// <summary>
        /// 识别图像线程
        /// </summary>
        private void IdentifyImageProcess()
        {
            Stopwatch stopwatch = Stopwatch.StartNew();
            while (IsIdentify)
            {
                //判断队列中是否有数据
                if (IFrameDatas.Count() > 0)
                {
                    stopwatch.Restart();
                    if (IFrameDatas.Count() > 5)
                    {
                        //FaultLog.RecordErrorMessage($"图像数据队列中数据过多，请及时处理！当前数据数量为：{IFrameDatas.Count()}");
                        FaultLog.RecordErrorMessage($"There is too much data in the image data queue. Please handle it in a timely manner! The current data quantity is：{IFrameDatas.Count()}");
                        if (IFrameDatas.Count() > 100)
                        {
                            SystemAlarm.AlarmAlert(AlarmMessageList.待识别队列数据堆积,
                                $"The image data queue is blocked. Please check the configuration and images",
                                "待识别队列数据堆积，请检查设置和图像",
                                "DLL:ShuLIClass-IdentifyImageProcess");
                        }
                        else
                        {
                            SystemAlarm.AlarmCancel(AlarmMessageList.待识别队列数据堆积);
                        }
                    }
                    IFrameDatas.TryDequeue(out IFrameOut IframeData);
                    stopwatch.Stop();
                    var ShiBieLuoHouTime = (DateTime.Now - FromUnixTimestamp((long)IframeData.HostTimeStamp)).TotalMilliseconds;
                    // 优化: 将日志记录改为条件执行
                    if (ShiBieLuoHouTime > 30)
                    {
                        LOG.error($"算法落后了超过30ms,相机取图总耗时：{ShiBieLuoHouTime}");
                    }
                    if (stopwatch.ElapsedMilliseconds > 5)
                    {
                        FaultLog.RecordErrorMessage($"ShuLiClass-IdentifyImageProcess:Image reading timed out, this recognition took time：{stopwatch.Elapsed}");
                    }
                    if (IframeData != null)
                    {
                        //识别
                        ProcessImageSequence2(IframeData);
                        IframeData.Dispose();
                    }
                    else
                    {
                        continue;
                    }
                }
                else
                {
                    Thread.Sleep(1);
                }
            }
        }

        private async void IdentifyImageProcessTask(CancellationToken token)
        {
            Stopwatch stopwatch = Stopwatch.StartNew();
            const int batchSize = 5; // 每批处理的最大图像数量
            var batch = new List<IFrameOut>(batchSize); // 存储当前批次的图像
            while (!token.IsCancellationRequested)
            {
                // 等待图像数据
                await QueueSemaphore.WaitAsync(token);
                //判断队列中是否有数据
                if (IFrameDatas.Count() > 5)
                {
                    //FaultLog.RecordErrorMessage($"图像数据队列中数据过多，请及时处理！当前数据数量为：{IFrameDatas.Count()}");
                    FaultLog.RecordErrorMessage($"There is too much data in the image data queue. Please handle it in a timely manner! The current data quantity is：{IFrameDatas.Count()}");
                    if (IFrameDatas.Count() > 100)
                    {
                        SystemAlarm.AlarmAlert(AlarmMessageList.待识别队列数据堆积,
                            $"The image data queue is blocked. Please check the configuration and images",
                            "待识别队列数据堆积，请检查设置和图像",
                            "DLL:ShuLIClass-IdentifyImageProcess");
                    }
                    else
                    {
                        SystemAlarm.AlarmCancel(AlarmMessageList.待识别队列数据堆积);
                    }
                }
                // 收集一批图像（严格按队列顺序）
                while (batch.Count < batchSize && IFrameDatas.TryDequeue(out IFrameOut imageData))
                {
                    batch.Add(imageData);
                    if (IFrameDatas.Count > 0)
                    {
                        QueueSemaphore.Release(); // 提前释放信号量，唤醒其他等待线程
                    }
                }
                // 顺序处理当前批次的所有图像
                foreach (var image in batch)
                {
                    if (image != null)
                    {
                        //识别
                        ProcessImageSequence2(image);
                        image.Dispose();
                    }
                    else
                    {
                        continue;
                    }
                }
                batch.Clear();
            }
        }
        #endregion
    }
}