using AI.Common;
using AI.Common.Log;
using AI.Common.Tools;
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Runtime.InteropServices;
using System.Text;
using System.Threading;
using System.Timers;

namespace AutoEFInferenceCalcLib
{


    /// <summary>
    /// AutoEF 的计算
    /// </summary>
    public class AutoEFCalculation
    {
        #region field

        private int _numCpu = 0;
        private int _layerCount = 20;
        private int _edControlLayersCount = 12;
        private int _esControlLayersCount = 10;

        private static InferenceCore _inferenceCore = new InferenceCore();
        private List<IInferenceNetwork> _inferNets = new List<IInferenceNetwork>();
        private bool _initialized = false;
        private ConcurrentDictionary<string, CardiacCycleRecognition> _calculations = new ConcurrentDictionary<string, CardiacCycleRecognition>();
        //超过一定时间阈值没有再塞图，则删除该计算，以便减少内存占用和避免内存溢出的风险
        private double _noNewImagePushedTimeThreshold = 1200;

        private bool _closing = false;
        private ConcurrentQueue<ImageInfo> _imageInfoQueue = new ConcurrentQueue<ImageInfo>();

        //将处理线程唤醒的一个时间，设置初始值为true，表示有信号，
        //有信号的时候，_threadAwakeEvent.WaitOne不会阻塞，没有信号的时候则会阻塞
        //调用_threadAwakeEvent.Set,将对象设置为有信号状态
        //调用_threadAwakeEvent.Reset,将对象重置为无信号状态
        private readonly ManualResetEvent _threadAwakeEvent = new ManualResetEvent(true);
        private readonly object _processThreadLocker = new object();
        private List<Thread> _threads = new List<Thread>();

        #endregion

        #region properties

        public int NumCpu { get => _numCpu; }

        public int LayerCount { get => _layerCount; }

        public int EDControlLayersCount { get => _edControlLayersCount; }

        public int ESControlLayersCount { get => _esControlLayersCount; }

        #endregion

        #region cpp dll中的数据结构

        /// <summary>
        /// cpp中点的结构
        /// </summary>
        [StructLayout(LayoutKind.Sequential)]
        internal struct StructPointCpp
        {
            public int x;
            public int y;
        }

        /// <summary>
        /// cpp中的轮廓外接框结构
        /// </summary>
        [StructLayout(LayoutKind.Sequential)]
        internal struct StructRect
        {
            public int left;
            public int top;
            public int width;
            public int height;
        }

        [StructLayout(LayoutKind.Sequential)]
        internal struct StructEndPoints
        {
            public StructPointCpp leftPoint;
            public StructPointCpp rightPoint;
        }

        /// <summary>
        /// 单帧图像计算的左心室相关
        /// </summary>
        [StructLayout(LayoutKind.Sequential)]
        internal struct StructCppLVVolume
        {
            public double volume;
            public int innerContLen;
            public StructPointCpp apexPoint;
            public StructEndPoints endPoints;
        }

        #endregion

        #region import dll

        [DllImport(@"AutoEFPostProcess.dll", CallingConvention = CallingConvention.Cdecl)]
        [return: MarshalAs(UnmanagedType.I1)]
        internal static extern bool LVVolumeCalculate(int oriWidth, int oriHeight, float cmPerPixel, int layerCount,
            int edControlLayersCount, int esControlLayerCount, int[] controlLayers, IntPtr pDetectedObject,
            int contoureLen, IntPtr pRect, IntPtr slicePoints, IntPtr innerContour, IntPtr controlPoints, ref StructCppLVVolume pLvVolume);

        #endregion

        #region event

        /// <summary>
        /// 通知订阅者，推理过程中发现了错误
        /// </summary>
        public event EventHandler<ErrorEventArgs> NotifyError;

        /// <summary>
        /// 通知订阅者，推理过程中产生了log要记录
        /// </summary>
        public event EventHandler<LogEventArgs> NotifyLog;

        #endregion


        #region public func

        /// <summary>
        /// 构造函数
        /// </summary>
        /// <param name="numCpu"></param>
        /// <param name="netDir"></param>
        /// <param name="layerCount"></param>
        /// <param name="edControlLayersCount"></param>
        /// <param name="esControlLayerCount"></param>
        /// <exception cref="Exception"></exception>
        public AutoEFCalculation(int numCpu = 1, string netDir = "", int layerCount = 20, int edControlLayersCount = 12,
            int esControlLayerCount = 10)
        {
            try
            {
                if (numCpu <= 0)
                {
                    throw new ArgumentOutOfRangeException("numCpu", "numCpu should be greater than 0.");
                }
                _numCpu = Math.Max(1, numCpu);
                _layerCount = layerCount;
                _edControlLayersCount = EDControlLayersCount;
                _esControlLayersCount = ESControlLayersCount;

                //加载网络
                var inferNet = new InferNetOnnxAutoEFCalculation();
                if (!inferNet.ModelLoaded)
                {
                    byte[] trainedNetwork = InferenceNetworkUtils.ReadNetworkDataFromFile(netDir,
                        inferNet.NetworkName, inferNet.HashCode);
                    //设置inferenceCore的参数
                    inferNet.LoadNetwork(_inferenceCore, EnumDeviceType.CPU, trainedNetwork);
                }
                _inferNets.Add(inferNet);

                for (int i = 0; i < _numCpu; i++)
                {
                    var netClone = _inferNets[0].Clone(EnumCloneMethod.Clone);
                    _inferNets.Add(netClone);
                }
                _initialized = true;
            }
            catch (Exception excep)
            {
#if ENABLE_AUTOEF_DEBUG
                LogHelper.EnableLogWrite = true;
                LogHelper.ErrorLog("AutoEF.AutoEFCalculation.Error:", excep.Message);
#endif
                throw new Exception("Failed at Loading AutoEFCalculation:" + excep);
            }
        }

        /// <summary>
        /// 开始一次新的计算
        /// 在整个计算过程中的图像，cmPerPixel不应该发生变化
        /// </summary>
        /// <param name="totalTime"></param>
        /// <param name="cmPerPixel"></param>
        /// <param name="intervalTime"></param>
        /// <returns></returns>
        /// <exception cref="Exception"></exception>
        public string StartCalculation(double totalTime, float cmPerPixel, double intervalTime = 0)
        {
            try
            {
                if (!_initialized)
                {
                    throw new Exception("Uninitialized before call StartCalculation!");
                }
                if (!(totalTime > 0))
                {
                    throw new ArgumentOutOfRangeException("The value of totalTime must be greater than 0!");
                }
                if (!(cmPerPixel > 0))
                {
                    throw new ArgumentOutOfRangeException("The value of cmPerPixel must be greater than 0!");
                }
                if (intervalTime > 500)
                {
                    throw new ArgumentOutOfRangeException("The value of intervalTime must be less than 0.5s!");
                }

                //判断之前的计算是否已经过了一定的时间，过了就清理掉，防止占用内存
                if (_calculations.Count != 0)
                {
                    var keys = _calculations.Keys.ToList();
                    foreach (var key in keys)
                    {
                        TimeSpan timeDiff = DateTime.Now - _calculations[key].LastPushedImageSucceedTime;
                        if (timeDiff.TotalSeconds > _noNewImagePushedTimeThreshold)
                        {
                            _calculations.TryRemove(key, out _);
                        }
                    }
                }
                //生成随机码，作为calculationId
                string calculationId = Guid.NewGuid().ToString();
                //创建一个calculation并添加到_calculations里
                CardiacCycleRecognition calculation = new CardiacCycleRecognition(calculationId, totalTime, cmPerPixel, intervalTime);
                //注：创建时立即订阅事件，以便从calculation中能将事件传出
                calculation.NotifyLog += OnLogWrite;
                calculation.NotifyError += OnErrorOccur;
                _calculations.TryAdd(calculationId, calculation);

                //如果预设的时间间隔大于0.2s时，由于实际预测帧数较少， 导致预测的曲线相较于实际的相差较大，记一下WarnLog，提醒使用者
                if (intervalTime >= 200)
                {
#if ENABLE_AUTOEF_DEBUG
                    LogHelper.EnableLogWrite = true;
                    LogHelper.WarnLog("AutoEF.StartCalculation.Warn:", "calculationId:" + calculationId,
                        "intervalTime,should be less than or equal to 0.2s.");
#endif
                }
                return calculationId;
            }
            catch (Exception excep)
            {
#if ENABLE_AUTOEF_DEBUG
                LogHelper.EnableLogWrite = true;
                LogHelper.ErrorLog("Failed at loading StartCalculation：" + excep.Message);
#endif
                throw new Exception("Failed at loading StartCalculation：" + excep);
            }
        }

        /// <summary>
        /// 塞入一幅图，计算完成后返回结果，实时计算使用 
        /// </summary>
        /// <param name="calculationId"></param>
        /// <param name="rawImage"></param>
        /// <param name="realFrameTime"></param>
        /// <returns></returns>
        /// <exception cref="ArgumentOutOfRangeException"></exception>
        /// <exception cref="Exception"></exception>
        public CardiacCurveInfos PushOneImageSync(string calculationId, RawImage rawImage, double realFrameTime)
        {
            //判断输入图像的类型，并统一转成BGR
            if (rawImage.ColorType == EnumColorType.GrayF32 || rawImage.ColorType == EnumColorType.Gray16)
            {
                throw new ArgumentOutOfRangeException("The ColorType of GrayF32 or Gray16 are not supported for PushOneImageSync by now!");
            }
            RawImage imgRGB = rawImage.Clone(EnumColorType.Bgr);
            //判断此次calculation是否开启
            if (!_calculations.ContainsKey(calculationId))
            {
                throw new Exception("calculation:" + calculationId + "shuould be started first.");
            }

            //判断当前计算类型有没有改变
            //初始化时type类型是None，第一次推图后才会变成真实代表的类型， 所以要排除为None的情况
            var type = _calculations[calculationId].Type;
            if (type != CalcType.None && type != CalcType.OnLine)
            {
                throw new Exception("calculation：" + calculationId + "cannot call PushOneImageSync and PushOneImageAsync at the same time");
            }
            try
            {
                //塞图到队列里计算
                PushOneImage(calculationId, imgRGB, realFrameTime, CalcType.OnLine);
                //判断结果是否计算完
                if (_calculations[calculationId].StartTime == realFrameTime)
                {
                    //等待该图的计算结果
                    while (!_calculations[calculationId].ProcessFinished(realFrameTime))
                    {
                        Thread.Sleep(5);
                    }
                }
                else
                {
                    //等待该图的计算结果
                    while (!_calculations[calculationId].ProcessFinished(realFrameTime))
                    {
                        Thread.Sleep(1);
                    }
                }
                return _calculations[calculationId].GetResult();
            }
            catch (Exception excep)
            {
                NotifyError?.Invoke(this, new ErrorEventArgs(excep));
                return _calculations[calculationId].GetResult();
            }
        }

        /// <summary>
        /// 塞入一副图像，不需要等待计算结果，冻结时使用
        /// </summary>
        /// <param name="caculationId"></param>
        /// <param name="rawImage"></param>
        /// <param name="realFrameTime"></param>
        public void PushOneImageAsync(string caculationId, RawImage rawImage, double realFrameTime)
        {
            try
            {
                if (rawImage.ColorType == EnumColorType.GrayF32 || rawImage.ColorType == EnumColorType.Gray16)
                {
                    throw new Exception("The colorType of GrayF16 and GrayF32 are not supported for PushOneImageAsync by now.");
                }
                RawImage imgBGR = rawImage.Clone(EnumColorType.Bgr);
                //先判断此次calculation是否开启
                if (!_calculations.ContainsKey(caculationId))
                {
                    throw new Exception("calculation_" + caculationId + "should be started first.");
                }
                //判断type是否改变
                //初始化时type设为None，第一次推图后才会变成真实所代表的类型，所以要排除type类型为None的情况
                var type = _calculations[caculationId].Type;
                if (type != CalcType.None && type != CalcType.OffLine)
                {
                    throw new Exception("calculation_" + caculationId + "cannot call PushOneImageAsync and PushOneImageSync at the same time.");
                }
                //塞图到队列中计算
                PushOneImage(caculationId, imgBGR, realFrameTime, CalcType.OffLine);
            }
            catch (Exception excep)
            {
                NotifyError?.Invoke(this, new ErrorEventArgs(excep));
#if ENABLE_AUTOEF_DEBUG
                LogHelper.EnableLogWrite = true;
                LogHelper.ErrorLog("AutoEF.PushOneImageAsync.Error:", excep.Message);
#endif
            }
        }

        /// <summary>
        /// 获取结果（单次要处理的视频全部使用PushOneImageAsync塞图）
        /// </summary>
        /// <param name="calculationId"></param>
        /// <returns></returns>
        public CardiacCurveInfos GetResult(string calculationId)
        {
            try
            {
                //等待最后一帧结果计算完毕
                var frameTime = _calculations[calculationId].LastPushedFrameTime;
                while (!_calculations[calculationId].ProcessFinished(frameTime))
                {
                    Thread.Sleep(1);
                }
                //获取计算结果
                return _calculations[calculationId].GetResult();
            }
            catch (Exception excep)
            {
                NotifyError?.Invoke(this, new ErrorEventArgs(excep));
#if ENABLE_AUTOEF_DEBUG
                LogHelper.EnableLogWrite = true;
                LogHelper.ErrorLog("GetResult.Error:", excep.Message);
#endif
                return _calculations[calculationId].GetResult();
            }
        }

        /// <summary>
        /// 销毁
        /// </summary>
        public void Dispose()
        {
            DoDispose();
            GC.SuppressFinalize(this);
        }

        /// <summary>
        /// 析构函数
        /// </summary>
        ~AutoEFCalculation()
        {
            DoDispose();
        }

        #endregion



        #region private

        private void PushOneImage(string calculationId, RawImage rawImage, double realFrameTime, CalcType calcType)
        {
            //推图，如果成功则塞入队列开始计算，如果没有成功，则不做计算直接返回（返回的时候需要给当前时间赋一个空的检测结果），
            //注意：_closing的时候不能继续塞图了， 要把所有未处理的数据都清空，如果这时候输入另外的数据，则会导致又重新开始计算了
            if (!_closing && _calculations[calculationId].PushOneImage(realFrameTime, calcType))
            {
                //塞入的图像的信息
                ImageInfo imageInfo = new ImageInfo
                {
                    CalculationId = _calculations[calculationId].Id,
                    Time = realFrameTime,
                    RawImage = rawImage,
                    CmPerPixel = _calculations[calculationId].CmPerPixel,
                };
                _imageInfoQueue.Enqueue(imageInfo);
                //设置_threadAwakeEvent状态为有信号，代表有新的输入，线程可以继续跑了
                _threadAwakeEvent.Set();
                int threadCount = Math.Min(_numCpu, _imageInfoQueue.Count);
                for (int i = 0; i < threadCount; i++)
                {
                    lock (_processThreadLocker)
                    {
                        if (_threads.Count < i + 1)
                        {
                            var thread = new Thread(DoImageProcessing);
                            thread.IsBackground = true;
                            thread.Name = "AutoEF_ImgProcessing_" + i.ToString();
                            _threads.Add(thread);
                            thread.Start(i);
                        }
                        else
                        {
                            var thread = _threads[i];
                            if (thread == null || !thread.IsAlive)
                            {
                                thread = new Thread(DoImageProcessing);
                                thread.IsBackground = true;
                                thread.Name = "AutoEF_ImgProcessing_" + i.ToString();
                                thread.Start(i);
                                _threads[i] = thread;
                            }
                        }
                    }
                }
            }
            else
            {
                _calculations[calculationId].UpdateImageResult(realFrameTime, new LVVolumeCalcResult(), ResultType.None);
            }
        }

        /// <summary>
        /// 单帧图像推理
        /// </summary>
        /// <param name="threadIndex"></param>
        private void DoImageProcessing(object threadIndex)
        {
            if (threadIndex == null)
            {
                return;
            }
            while (!_closing)
            {
                if (_imageInfoQueue.Count > 0)
                {
                    if (_imageInfoQueue.TryDequeue(out var sigleImageInfo))
                    {
                        try
                        {
                            var frameTime = sigleImageInfo.Time;
                            var rawImage = sigleImageInfo.RawImage;
                            var cmPerPixel = sigleImageInfo.CmPerPixel;
                            var calculationId = sigleImageInfo.CalculationId;

                            //1.满足预设的时间间隔才实际推理，否则基于时间序列给出结果
                            //当前帧时间与上一次计算的时间间隔小于预设的时间间隔
                            if (frameTime - _calculations[calculationId].LastRealCalcFrameTimeStamp < _calculations[calculationId].IntervalTime &&
                                frameTime != _calculations[calculationId].StartTime)
                            {
                                _calculations[calculationId].UpdateImageResult(frameTime, new LVVolumeCalcResult(), ResultType.FrameSequenceBasedPredict);
                                continue;
                            }
                            //2.当本次计算最新Push的图像的时间戳与将要计算的时间戳大于一定的时间阈值（即计算滞后于Push一定的时间）
                            //则不计算，否则计算的结果将越来越滞后，导致计算失败
                            //一般输入帧率是20-30帧每秒，所以暂取0.15s,即如果滞后3帧，则不计算
                            if (frameTime - _calculations[calculationId].LastPushedFrameTime > Math.Max(_calculations[calculationId].IntervalTime, 150))
                            {
                                _calculations[calculationId].UpdateImageResult(frameTime, new LVVolumeCalcResult(), ResultType.FrameSequenceBasedPredict);
                                continue;
                            }
                            //3.正常情况下
                            _calculations[calculationId].LastRealCalcFrameTimeStamp = frameTime;
                            LVVolumeCalcResult resultPerImage = ProcessOneImage(rawImage, cmPerPixel, (int)threadIndex);
                            _calculations[calculationId].UpdateImageResult(frameTime, resultPerImage, ResultType.SingleFrameBasedPredict);
                        }
                        catch (Exception excep)
                        {
                            NotifyError.Invoke(this, new ErrorEventArgs(excep));
                        }
                    }
                }
                else
                {
                    //将_threadAwakeEvent设为无信号，表示现在没有新的数据了，但又不想让线程结束（避免频繁创建和销毁线程带来的开销）
                    //所以让Waitone一直等卡在这里，直到又新的数据输入，waitOne才继续
                    _threadAwakeEvent.Reset();
                    _threadAwakeEvent.WaitOne();
                }
            }
        }

        /// <summary>
        /// 推理单帧图像结果
        /// </summary>
        /// <param name="rawImage"></param>
        /// <param name="cmPerPixel"></param>
        /// <param name="threadIndex"></param>
        /// <returns></returns>
        private LVVolumeCalcResult ProcessOneImage(RawImage rawImage, float cmPerPixel, int threadIndex = 0)
        {
            //对一张图像进行推理
            InferenceNetworkInputImage inferInput = new InferenceNetworkInputImage(rawImage, new Rect(0, 0, rawImage.Width, rawImage.Height));
            IDetectedObject[] segResult = _inferNets[threadIndex].Process(inferInput);
            LVVolumeCalcResult resultPerImage = new LVVolumeCalcResult();
            if (segResult.Length != 1)
            {
                return LVVolumeCalcResult.Empty;
            }
            resultPerImage = LVVolumeProcess(rawImage, cmPerPixel, segResult);
            return resultPerImage;
        }

        /// <summary>
        /// 左心室容积推理
        /// </summary>
        /// <param name="rawImage"></param>
        /// <param name="cmPerPixel"></param>
        /// <param name="segResult"></param>
        /// <returns></returns>
        private LVVolumeCalcResult LVVolumeProcess(RawImage rawImage, float cmPerPixel, IDetectedObject[] segResult)
        {
            int apexPointSize = 1;
            int endPointSize = 2;
            int slicePointSize = _layerCount * 2; ;
            int controlNum = _edControlLayersCount > _esControlLayersCount ? _edControlLayersCount : _esControlLayersCount;

            //转换分割结果
            int pointCount = segResult[0].Contours[0].Length;
            StructPointCpp[] structPoints = new StructPointCpp[pointCount];
            for (int i = 0; i < pointCount; i++)
            {
                structPoints[i].x = segResult[0].Contours[0][i].X;
                structPoints[i].y = segResult[0].Contours[0][i].Y;
            }
            StructRect cppRect = new StructRect();
            cppRect.left = segResult[0].BoundingBox.Left;
            cppRect.top = segResult[0].BoundingBox.Top;
            cppRect.width = segResult[0].BoundingBox.Width;
            cppRect.height = segResult[0].BoundingBox.Height;

            //初始化需要返回的结果
            StructCppLVVolume structCppLVVolume = new StructCppLVVolume();
            structCppLVVolume.volume = 0;
            structCppLVVolume.innerContLen = 0;
            structCppLVVolume.apexPoint = new StructPointCpp();
            structCppLVVolume.endPoints = new StructEndPoints();
            StructPointCpp[] slicePoints = new StructPointCpp[slicePointSize];
            StructPointCpp[] innerContour = new StructPointCpp[rawImage.Width * rawImage.Height];
            StructPointCpp[] controlPoints = new StructPointCpp[controlNum * 2];
            int[] controlCount = new int[1];
            controlCount[0] = 0;


            //获取轮廓指针
            GCHandle hDetectedObjectArray = GCHandle.Alloc(structPoints, GCHandleType.Pinned);
            IntPtr pDetectedObject = hDetectedObjectArray.AddrOfPinnedObject();
            //获取外接矩形的指针
            GCHandle hObjectRect = GCHandle.Alloc(cppRect, GCHandleType.Pinned);
            IntPtr pObjectRect = hObjectRect.AddrOfPinnedObject();

            GCHandle hSlicePoint = GCHandle.Alloc(slicePoints, GCHandleType.Pinned);
            IntPtr pSlicePoints = hSlicePoint.AddrOfPinnedObject();
            GCHandle hInnerPoints = GCHandle.Alloc(innerContour, GCHandleType.Pinned);
            IntPtr pInnerPoints = hInnerPoints.AddrOfPinnedObject();
            GCHandle hControlPoints = GCHandle.Alloc(controlPoints, GCHandleType.Pinned);
            IntPtr pConrolPoints = hControlPoints.AddrOfPinnedObject();

            bool ret = false;
            ret = LVVolumeCalculate(rawImage.Width, rawImage.Height, cmPerPixel, _layerCount, _edControlLayersCount,
                _esControlLayersCount, controlCount, pDetectedObject, pointCount, pObjectRect,
            pSlicePoints, pInnerPoints, pConrolPoints, ref structCppLVVolume);

            //释放
            if (hDetectedObjectArray.IsAllocated)
            {
                hDetectedObjectArray.Free();
            }
            if (hObjectRect.IsAllocated)
            {
                hObjectRect.Free();
            }
            if (hSlicePoint.IsAllocated)
            {
                hSlicePoint.Free();
            }
            if (hInnerPoints.IsAllocated)
            {
                hInnerPoints.Free();
            }
            if (hControlPoints.IsAllocated)
            {
                hControlPoints.Free();
            }

            //当返回false或计算的内轮廓的长度为0时，返回空值
            if (!ret)
            {
                NotifyLog?.Invoke(this, new LogEventArgs(EnumLogType.WarnLog, "Failed at Loading LVVolumeCalculate."));
                return LVVolumeCalcResult.Empty;
            }
            if (structCppLVVolume.innerContLen == 0 || controlCount[0] == 0)
            {
                return LVVolumeCalcResult.Empty;
            }

            //转换cpp计算的结果
            Point2D[] endPoints = new Point2D[endPointSize];
            for (int i = 0; i < endPointSize; i++)
            {
                endPoints[0] = new Point2D(structCppLVVolume.endPoints.leftPoint.x, structCppLVVolume.endPoints.leftPoint.y);
                endPoints[1] = new Point2D(structCppLVVolume.endPoints.rightPoint.x, structCppLVVolume.endPoints.rightPoint.y);
            }
            Point2D[] slicePointsTran = new Point2D[slicePointSize];
            for (int i = 0; i < slicePointSize; i++)
            {
                slicePointsTran[i] = new Point2D(slicePoints[i].x, slicePoints[i].y);
            }
            Point2D[] innerContourPoint = new Point2D[structCppLVVolume.innerContLen];
            for (int i = 0; i < structCppLVVolume.innerContLen; i++)
            {
                innerContourPoint[i] = new Point2D(innerContour[i].x, innerContour[i].y);
            }
            Point2D[] controlPoint = new Point2D[controlCount[0]];
            for (int i = 0; i < controlCount[0]; i++)
            {
                controlPoint[i] = new Point2D(controlPoints[i].x, controlPoints[i].y);
            }

            LVVolumeMeasureMarks lVVolumeMeasure = new LVVolumeMeasureMarks(new Point2D(structCppLVVolume.apexPoint.x,
                structCppLVVolume.apexPoint.y), endPoints, slicePointsTran, controlPoint);
            LVVolumeCalcResult lVVolumeCalcResult = new LVVolumeCalcResult(innerContourPoint, structCppLVVolume.volume,
                segResult[0].Confidence, lVVolumeMeasure);
            return lVVolumeCalcResult;
        }

        /// <summary>
        /// 主动销毁
        /// </summary>
        private void DoDispose()
        {
            _closing = true;
            //因为_threadAwakeEvent一直在waitone,所以需要先Set一下，使其不阻塞
            _threadAwakeEvent.Set();
            //等待所有线程结束
            while (true)
            {
                bool runing = false;
                lock (_processThreadLocker)
                {
                    for (int i = 0; i < _threads.Count; i++)
                    {
                        var thread = _threads[i];
                        if (thread != null && thread.IsAlive)
                        {
                            runing = true;
                            break;
                        }
                    }
                }
                if (runing)
                {
                    Thread.Sleep(10);
                }
                else
                {
                    break;
                }
            }
            //所有的calculation停止
            foreach (var calculation in _calculations.Values)
            {
                calculation.NotifyLog -= OnLogWrite;
                calculation.NotifyError -= OnErrorOccur;
                calculation.Dispose();
            }
            //所有待处理数据清空
            while (_imageInfoQueue.Count > 0)
            {
                _imageInfoQueue.TryDequeue(out var _);
            }
            //逐个释放inferNet
            for (int i = 0; i < _inferNets.Count; i++)
            {
                _inferNets[i]?.Dispose();
                _inferNets[i] = null;
            }
            _initialized = false;
            _closing = false;
        }

        /// <summary>
        /// 有log要记
        /// </summary>
        /// <param name="sender"></param>
        /// <param name="e"></param>
        private void OnLogWrite(object sender, LogEventArgs e)
        {
            NotifyLog?.Invoke(this, e);
        }

        /// <summary>
        /// 推理过程中发生了错误
        /// </summary>
        /// <param name="sender"></param>
        /// <param name="e"></param>
        private void OnErrorOccur(object sender, ErrorEventArgs e)
        {
            NotifyError?.Invoke(this, e);
        }

        #endregion


    }
}