8ca6e89d
 Tuo Wenbo
20211021
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using OpenCvSharp;
using OS.Spin.BusinessLayer.SubBusiness;
using OS.Spin.Common;
using OS.Spin.Common.Files;
using OS.Spin.Common.MultiThread;
using OS.Spin.Modle.BusinessLayer;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.InteropServices;
using System.Threading;
using static OS.Spin.Modle.Sdk.StructInfos;
namespace OS.Spin.BusinessLayer.MainBusiness
{
public sealed class FlawDetectionBl
{
#region 变量
private int _cameraCount = 0;
private List<CameraBl> _cameras = new List<CameraBl>();
private List<DetectionBl> _detections = new List<DetectionBl>();
private Thread _runThread;
private SemaphorePool _semaphorePool;
private string _classId = string.Empty;
private int _imageId = 0;
private int _reallyImageId = 0;
private int _finishedCameraCount = 0;
private IntPtr _initHandle = new IntPtr(0);
private IntPtr _handle = new IntPtr(1);
private const int RS_FACTOR = 1;
private const int ROI_WIDTH = 500;
private const int ROI_HEIGHT = 250;
public delegate void WindowsControl(int cmd);
public WindowsControl TlWorker;
private IntPtr _handle_5 = new IntPtr(5);
private IntPtr _handle_37 = new IntPtr(37);
private IntPtr _handle_h = new IntPtr(12);
private IntPtr _handle_v = new IntPtr(22);
private IntPtr _handle_proc = new IntPtr(32);
private Modle.Sdk.StructInfos.FinalResults[] label_poolarray = new Modle.Sdk.StructInfos.FinalResults[100];
private Modle.Sdk.StructInfos.FinalResults[] final_labelout = new Modle.Sdk.StructInfos.FinalResults[16];
//private int pool_size = 0;
private int _gainValue = 0;
private bool _isSetGain = false;
private int current_meter = 0;
//private MachineStopBl _stopBl = null;
//private MaxSmallTransferBl _transferBl = null;
private bool _canRecived = true;
//private string[] _lableNames = new[] { "背景", "停车痕(紧)", "停车痕(松)", "断经", "错花", "并纬", "缩纬", "缺纬", "糙纬", "折返", "断纬",
// "油污", "浆斑", "污经","经条", "擦白", "擦伤","空织","破洞","紧经","污纬","皱印","上首破边","下首破边", "刮伤", "纬密变化","蛛网","挡车工标记","毛纱、线头","起皱","水印","水波纹", "其他" };
private string[] _lableNames = new[] { "背景","棉花","大棉团","横向折痕","经向折痕","小竹节","杂物","棉球","结头","破洞","拖纱","断疵","跳花","云织","经竹节","经缩","粗经","经向异纤","起圈纬缩","纬竹节","纬缩",
"松纬缩","纬向异纤","断经_黑","断经_亮","松经","稀纬","稀弄","双纬","空织","百脚","密路","花毛密路","错支类","豁边","紧边","烂边毛边","深色油污","透明油污","交班印","条干不匀","其他瑕疵","人为干扰" };
public delegate void AddFlawShot(MFlawInfo flaw);
public AddFlawShot DoAddFlawShot;
public delegate void RunningEvent();
public RunningEvent Running;
private int _lostTime = 0;
private TimerBl _tbl = null;
private Modle.Sdk.StructInfos.CLAS_PARAM _findWall;
#endregion
#region 程序入口
public FlawDetectionBl(int cameraCount)
{
try
{
_cameraCount = cameraCount;
_finishedCameraCount = cameraCount;
LogisTrac.WriteInfoLog(String.Format("[开始] =====[{0}]======", "FlawDetectionBl"));
_findWall = new Modle.Sdk.StructInfos.CLAS_PARAM
{
prob_cls = ConfigHelper.GetInstance().GetConfig().Prob_cls,//通用瑕疵
prob_sma = ConfigHelper.GetInstance().GetConfig().Prob_sma,//小瑕疵
prob_color = ConfigHelper.GetInstance().GetConfig().Prob_color,//色纤
prob_thin = ConfigHelper.GetInstance().GetConfig().Prob_thin,//淡痕
len_sma = ConfigHelper.GetInstance().GetConfig().Len_sma,//小瑕疵长度限制阈值
cloths_kind = 0, //布种 0:正常布种; 1:薄布 2:厚布
m_gain = 0, //增益返回值
m_base = ConfigHelper.GetInstance().GetConfig().M_base, //增益基准值
m_meters = (int)OS.Spin.Running.Cache.GetInstance().CMeter, //当前米数计数值
thre_are = ConfigHelper.GetInstance().GetConfig().Thre_Area,//点状瑕疵面积
thre_location = ConfigHelper.GetInstance().GetConfig().Thre_Location//布尾米数位置阈值
};
#region TWB20210902
//// 初始化分类
var count = SdkLayer.SdkMyCode.Flaw_ClassifyInit(ref _handle_h, ref _handle_v, ref _handle_proc);
#endregion
// 初始化后处理
//count = OS.Spin.SdkLayer.SdkImport.Detc_Post_Init(ref _handle, _cameraCount);
_classId = Guid.NewGuid().ToString();
// 获取信号量
_semaphorePool = OS.Spin.Common.MultiThread.SemaphorePool.GetInstance();
// 创建检查信号量
_semaphorePool.MakeSemaphore(string.Format("{0}{1}", OS.Spin.Running.Infos.Names.S_DETECTION_OK, _classId));
// 初始化相机
for (var cId = 0; cId < _cameraCount; cId++)
{
var camera = new CameraBl(cId)
{
SendRecivedImg = RecivedImg
};
_cameras.Add(camera);
DetectionBl detection = new DetectionBl(_classId, cId)
{
DoGetThreeChannelMat = DoGetThreeChannelsMat
};
_detections.Add(detection);
}
// 启动分类线程
if (null == _runThread)
{
_runThread = new Thread(Classifying);
_runThread.Priority = ThreadPriority.AboveNormal;
_runThread.Start();
}
//// 创建码表通讯模块
//_tbl = new TimerBl
//{
// DoRecived = TimerRecived
//};
//_tbl.OnStart();
}
catch (Exception ex)
{
LogisTrac.WriteLog(string.Format("FlawDetectionBl:{0}", ex.Message));
}
}
public bool CanTrigger
{
get { return _canRecived; }
}
private FlawDetectionBl()
{
}
#endregion
#region public
#region 相机触发拍照
/// <summary>
/// 相机触发拍照
/// </summary>
/// <returns></returns>
public bool CameraTrigger(double meter)
{
try
{
LogisTrac.WriteLog("触发");
if (meter < 3)
{
foreach (var camera in _cameras)
{
camera.SetCameraCainValue(ConfigHelper.GetInstance().GetConfig().M_base / 10.0);
LogisTrac.WriteLog(string.Format("5米前设置相机增益===[{0}]=====", ConfigHelper.GetInstance().GetConfig().M_base / 10.0));
}
_isSetGain = true;
//pool_size = 0;
}
OS.Spin.Running.Cache.GetInstance().CMeter = meter;
Running?.Invoke();
if (!_canRecived)
{
_lostTime++;
if (_lostTime > 10)
{
_canRecived = true;
}
return false;
}
_lostTime = 0;
_canRecived = false;
OS.Spin.Running.Cache.GetInstance().CMeter = meter;
//if (_finishedCameraCount >= _cameraCount)
{
//_finishedCameraCount = 0;
// 重置相机接收完成标志
//OS.Spin.Running.Cache.GetInstance().CamerasOk = false;
if (meter > 3 && _isSetGain)
{
foreach (var camera in _cameras)
{
camera.SetCameraCainValue((_gainValue / 10.0));
}
_isSetGain = false;
//_gainValue = 0;
LogisTrac.WriteLog(string.Format("设置相机增益值===[{0}]==============", _gainValue));
}
foreach (var camera in _cameras)
{
camera.Trigger();
}
return true;
}
}
catch (Exception ex)
{
LogisTrac.WriteLog(string.Format("CameraTrigger:{0}", ex.Message));
return false;
}
//return false;
}
#endregion
#region 重置清零后处理参数
/// <summary>
/// 重置清零后处理参数
/// </summary>
public void ReSetDp()
{
//OS.Spin.SdkLayer.SdkImport.DP_Clear(_handle);
}
#endregion
#region 码表清零
/// <summary>
/// 码表清零
/// </summary>
public void Zeroing()
{
if (null == _tbl)
{
return;
}
_tbl.Zero();
}
#endregion
#region 释放资源
/// <summary>
/// 释放资源
/// </summary>
public void Dispose()
{
try
{
foreach (var d in _detections)
{
if (null == d)
{
continue;
}
d.Dispose();
}
foreach (var camera in _cameras)
{
camera.Dispose();
}
if (null != _tbl)
{
_tbl.Dispose();
}
_runThread.Abort();
#region TWB20210902
OS.Spin.SdkLayer.SdkMyCode.Flaw_ClassifyRelease(ref _handle_h, ref _handle_v, ref _handle_proc);
#endregion
OS.Spin.Common.Camera.JaiCamera.GetInstance().Close();
}
catch (Exception ex)
{
LogisTrac.WriteInfoLog(string.Format("FlawDetectionBl Dispose:{0}", ex.Message));
}
}
#endregion
#endregion
#region private
#region 接收相机数据
/// <summary>
/// 接收相机数据
/// </summary>
/// <param name="cameraId">相机编号</param>
/// <param name="img">拍照数据</param>
private void RecivedImg(int cameraId, Modle.Sdk.StructInfos.DATA_IMAGE1 img)
{
_imageId = OS.Spin.Running.Cache.GetInstance().CacheImgId;
// 开始执行
_detections[cameraId].StartDetection(img);
//_finishedCameraCount++;
}
#endregion
private double _cMeter = -1;
public void TimerRecived(int type, double meter)
{
if (type == 1)
{
CameraTrigger(meter);
}
if (type == 0 && !_cMeter.Equals(meter))
{
// ImageSavingBl.Getinstance().PutCopy(new MFileCopy(2, OS.Spin.Running.Cache.GetInstance().CacheImgId, _cameraCount));
_cMeter = meter;
}
}
#region 执行分类处理
/// <summary>
/// 执行分类处理
/// </summary>
private void Classifying()
{
if (_cameraCount <= 0)
{
return;
}
var id = OS.Spin.Common.Machine.CpuTool.SetCpuID(_cameraCount);
//将当前线程绑定到指定的cpu核心上
OS.Spin.Common.Machine.CpuTool.SetThreadAffinityMask(OS.Spin.Common.Machine.CpuTool.GetCurrentThread(), new UIntPtr(id));
while (true)
{
var time = 0;
while (time < _cameraCount)
{
_semaphorePool.Wait(string.Format("{0}{1}", OS.Spin.Running.Infos.Names.S_DETECTION_OK, _classId));
time++;
}
try
{
//// 手动验布时不做算法处理
//if (!OS.Spin.Running.Cache.GetInstance().AutoFlaw)
//{
// //_canRecived = true;
// continue;
//}
// 获取图像原图
var flaw = new MFlawInfo();
for (var i = 0; i < _cameraCount; i++)
{
flaw.AddMat(OS.Spin.Running.Cache.GetInstance().Mats[i].Clone());
}
current_meter = (int)OS.Spin.Running.Cache.GetInstance().CMeter;
// 记录当前处理的图片编号
_reallyImageId = _imageId;
// 释放拍照触发
// 统计需要分类处理的瑕疵快照个数
var classify_num = 0;
var cache = OS.Spin.Running.Cache.GetInstance();
for (var i = 0; i < _cameraCount; i++)
{
var rois = cache.GetFore_Result(i);
//var rts = rois;
if (null == rois)
{
continue;
}
classify_num += rois.Count();
}
//TWB20210902
var result = Marshal.AllocHGlobal(Marshal.SizeOf(typeof(Modle.Sdk.StructInfos.Fore_Result)) * classify_num);
var fIn = Marshal.AllocHGlobal(Marshal.SizeOf(typeof(Modle.Sdk.StructInfos.Fore_Result)) * classify_num);
long ptr = fIn.ToInt64();
var fores = new Modle.Sdk.StructInfos.Fore_Result[classify_num];
//IntPtr RPtr = new IntPtr(ptr);
var classify_cnt = 0;
for (int m = 0; m < _cameraCount; m++)
{
var rois = cache.GetFore_Result(m);
if (null == rois)
{
continue;
}
foreach (var roi in rois)
{
fores[classify_cnt] = roi;
//Marshal.StructureToPtr(fores[classify_cnt], RPtr, false);
ptr += Marshal.SizeOf(typeof(Modle.Sdk.StructInfos.Fore_Result));
//LogisTrac.WriteLog(String.Format("[检测] 结果 image id:{0} label:{1} prob:{2} prob_sum:{3} width:{4} height:{5} x:{6} y:{7}", fores[classify_cnt].img_id, fores[classify_cnt].label, fores[classify_cnt].prob, fores[classify_cnt].prob_sum, fores[classify_cnt].width, fores[classify_cnt].height, fores[classify_cnt].xCenter_cam, fores[classify_cnt].yCenter_cam));
classify_cnt++;
}
}
// 组装分类数据
//var resultSize = Marshal.SizeOf(typeof(Modle.Sdk.StructInfos.CTOOLS_Result)) * classify_num;
//var results = Marshal.AllocHGlobal(resultSize);
LogisTrac.WriteInfoLog(String.Format("[分类] 开始 ={0}======", _reallyImageId));
//int final_labelsize = 0;
#region TWB20210902
_findWall.m_meters = current_meter;
//_findWall.th_prob0 = OS.Spin.Running.Cache.GetInstance().FindWall;
//_findWall.th_prob1 = OS.Spin.Running.Cache.GetInstance().JdWall;
//_findWall.th_prob2 = OS.Spin.Running.Cache.GetInstance().MhWall;
_findWall.cloths_kind = OS.Spin.Running.Cache.GetInstance().Cloths_kind;
#endregion
//int gain = 0;
#region TWB20210902
int finalNum = 0;
var a = OS.Spin.SdkLayer.SdkMyCode.Flaw_Classification(flaw.Mats[0].Data, flaw.Mats[1].Data, flaw.Mats[2].Data, fores, classify_num, result, ref finalNum, ref _findWall, _handle_h, _handle_v, _handle_proc);
//Marshal.FreeHGlobal(ptrIn);
#endregion
_gainValue = _findWall.m_gain;
LogisTrac.WriteInfoLog(String.Format("[相机增益] ===[{0}] ={1}======", _reallyImageId, _gainValue));
List<Fore_Result> rts = new List<Fore_Result>();
// 解析返回结果
for (var i = 0; i < finalNum; i++)
{
var ptr1 = (result + i * Marshal.SizeOf(typeof(Modle.Sdk.StructInfos.Fore_Result)));
rts.Add((Modle.Sdk.StructInfos.Fore_Result)Marshal.PtrToStructure(ptr1, typeof(Modle.Sdk.StructInfos.Fore_Result)));
LogisTrac.WriteInfoLog(String.Format("[分类] 结果 image id:{0} label:{1} prob:{2} prob_sum:{3} width:{4} height:{5} x:{6} y:{7}", rts[i].img_id, rts[i].label, rts[i].prob, rts[i].prob_sum, rts[i].width, rts[i].height, rts[i].xCenter_cam, rts[i].yCenter_cam));
}
//for (var i = 0; i < finalNum; i++)
//{
// LogisTrac.WriteLog(String.Format("[分类] 结果 ={0}===[{1}]===[{2}]==[{3}]==[{4}]==[{5}==[{7}]==[{8}]", fores[i].img_id, fores[i].label, fores[i].prob, fores[i].is_valid, fores[i].xCenter_cam, fores[i].yCenter_cam, fores[i].yCenter_cam, fores[i].width, fores[i].height));
//}
//for (var i = 0; i < final_labelout.Count(); i++)
//{
// final_labelout[i].is_valid = 1;
// final_labelout[i].deduction = 4;
//}
#region TWB20210902 方法删除
// OS.Spin.SdkLayer.SdkMyCode.Detc_Postprocess(fores, classify_num, label_poolarray, ref pool_size, final_labelout, ref final_labelsize, current_meter);
#endregion
//LogisTrac.WriteInfoLog(String.Format("[分类] 结束 ={0}===[{1}]===", _reallyImageId, final_labelsize));
//_canRecived = true;
if (finalNum == 0)
{
continue;
}
var index = cache.FlawId;
var subIndex = 0;
//先抠图后画框 本次只抠图
for (var i = 0; i < finalNum; i++)
{
var fl = rts[i];
//if (fl.is_repeat == 1)
//{
// continue;
//}
MFinalFlawCell fr = new MFinalFlawCell();
fr.FlawName = _lableNames[fl.label];
fr.Meter = OS.Spin.Running.Cache.GetInstance().CMeter;
//MFinalFlawCell fr = new MFinalFlawCell()
//{
// FlawName = _lableNames[fl.label],
// Meter = OS.Spin.Running.Cache.GetInstance().CMeter
//};
flaw.AddFinalFlaw(fr);
var xMeter = 0.5;
if (fl.img_id > 1)
{
xMeter += 1;
}
if (fl.img_id > 2)
{
xMeter += 1;
}
var s = new MFlawSnap
{
No = string.Format("{0}_{1}", index, subIndex),
FlawName = _lableNames[fl.label],
#region TWB20210902
CenterX = xMeter,
CenterY = fl.yCenter_cam / 1200 * 0.3 + OS.Spin.Running.Cache.GetInstance().CMeter
#endregion
};
subIndex++;
var fMat = (flaw.Mats[fl.img_id]);
var newFMat = (flaw.Mats[fl.img_id]).Clone();
int start_x = fl.xCenter_cam * RS_FACTOR - ROI_WIDTH / 2;
int start_y = fl.yCenter_cam * RS_FACTOR - ROI_HEIGHT / 2;
if (start_x < 0)
start_x = 0;
if (start_x + ROI_WIDTH > fMat.Width)
start_x = fMat.Width - ROI_WIDTH;
if (start_y < 0)
start_y = 0;
if (start_y + ROI_HEIGHT > fMat.Height)
start_y = fMat.Height - ROI_HEIGHT;
s.SnapMat = (new Mat(fMat.Clone(), new OpenCvSharp.Rect(start_x, start_y, ROI_WIDTH, ROI_HEIGHT)));
//Cv2.Rectangle(fMat, new Point(start_x, start_y), new Point(start_x + ROI_WIDTH, start_y + ROI_HEIGHT), new Scalar(5, 5, 5), 2);
//Cv2.Circle(fMat, new Point(fore.xCenter_cam * RS_FACTOR, fore.yCenter_cam * RS_FACTOR), 150, new Scalar(255, 255, 255), 5);
flaw.AddSnapFlaws(s);
// LogisTrac.WriteLog(String.Format("[最终] 结果 ={0}===[{1}]===[{2}]==[{3}]", fores[i].img_id, fl.label, fl.prob, fl.is_valid));
//foreach (var fore in fores)
}
//本次循环只画框
for (var i = 0; i < finalNum; i++)
{
var fl = rts[i];
var xMeter = 0.5;
if (fl.img_id > 1)
{
xMeter += 1;
}
if (fl.img_id > 2)
{
xMeter += 1;
}
subIndex++;
var fMat = (flaw.Mats[fl.img_id]);
var newFMat = (flaw.Mats[fl.img_id]).Clone();
int start_x = fl.xCenter_cam * RS_FACTOR - ROI_WIDTH / 2;
int start_y = fl.yCenter_cam * RS_FACTOR - ROI_HEIGHT / 2;
if (start_x < 0)
start_x = 0;
if (start_x + ROI_WIDTH > fMat.Width)
start_x = fMat.Width - ROI_WIDTH;
if (start_y < 0)
start_y = 0;
if (start_y + ROI_HEIGHT > fMat.Height)
start_y = fMat.Height - ROI_HEIGHT;
//s.SnapMat = (new Mat(fMat, new OpenCvSharp.Rect(start_x, start_y, ROI_WIDTH, ROI_HEIGHT)));
Cv2.Rectangle(fMat, new Point(start_x, start_y), new Point(start_x + ROI_WIDTH, start_y + ROI_HEIGHT), new Scalar(5, 5, 5), 2);
//Cv2.Circle(fMat, new Point(fore.xCenter_cam * RS_FACTOR, fore.yCenter_cam * RS_FACTOR), 150, new Scalar(255, 255, 255), 5);
// LogisTrac.WriteLog(String.Format("[最终] 结果 ={0}===[{1}]===[{2}]==[{3}]", fores[i].img_id, fl.label, fl.prob, fl.is_valid));
//foreach (var fore in fores)
}
// 有用瑕疵存在时
if (flaw.FinalFlaws.Count > 0)
{
if (OS.Spin.Running.Cache.GetInstance().AutoFlaw)
{
TlWorker?.Invoke(11);
}
// 保存带瑕疵图片
ImageSavingBl.Getinstance().PutCopy(new MFileCopy(0, _reallyImageId, _cameraCount));
LogisTrac.WriteInfoLog(String.Format("PutCopy ={0}======", _reallyImageId));
DoAddFlawShot?.Invoke(flaw);
LogisTrac.WriteInfoLog(String.Format("DoAddFlawShot ={0}======", _reallyImageId));
}
}
catch (Exception ex)
{
LogisTrac.WriteInfoLog("Classifying");
LogisTrac.WriteLog(ex);
}
finally
{
_canRecived = true;
LogisTrac.WriteInfoLog(String.Format("正常结束 ={0}======", _reallyImageId));
}
}
}
#endregion
/// <summary>
/// 改变布匹参数
/// </summary>
/// <param name="kind"></param>
public void UploadClothsKind(int kind)
{
try
{
foreach (var dl in _detections)
{
dl.DoUploadClothsKind(kind);
}
_findWall.cloths_kind = kind;
OS.Spin.Running.Cache.GetInstance().Cloths_kind = kind;
}
catch (Exception ex)
{
LogisTrac.WriteInfoLog(String.Format("UploadClothsKind: {0}", ex.Message));
}
}
#region 获取三通道照片信息
/// <summary>
/// 获取三通道照片信息
/// </summary>
/// <param name="cammeraId"></param>
/// <returns></returns>
private Mat DoGetThreeChannelsMat(int cammeraId)
{
return _cameras[cammeraId].ThreeChannelMat;
}
#endregion
#endregion
#region ===== WARNING FINISHED ON 2019/06/06 BY Ding Shujie VERSION: V1.0.0 ======
#endregion
}
}
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