v1.2 新禾欣版本初版

LeatherProject/LeatherApp/Config.cs

@@ -90,6 +90,10 @@ namespace LeatherApp
         public static string cloud_ip, cloud_username, cloud_password, CloudThisName;
         public static int cloud_port, cloud_open;
 
+        //传统算法
+        public static bool OpenHalconDefect;
+        public static string HalconParamPath;
+
         public static void LoadCloudConfig()
         {
             if (string.IsNullOrWhiteSpace(appBasePath))
@@ -212,6 +216,14 @@ namespace LeatherApp
                 SkipLabelGrade = lsTmp.Split(new char[] { ',', ';' });
             else
                 SkipLabelGrade = new string[1] { "" };
+
+            //传统参数
+            OpenHalconDefect = ini.ReadBool("Halcon", "OpenHalconDefect");
+            lsTmp = ini.ReadString("Halcon", "HalconParamPath", "").Trim();
+            if (!string.IsNullOrWhiteSpace(lsTmp))
+                HalconParamPath = lsTmp;
+            else
+                HalconParamPath = appBasePath;
         }
 
         #region defectItemList <=> DefectItemList.json
@@ -245,10 +257,20 @@ namespace LeatherApp
         {
             try
             {
+                if (id == -99)
+                {
+                    JObject obj = new JObject();
+                    obj.Add("id", 0);
+                    obj.Add("code", "ng");
+                    obj.Add("name", "NG");
+                    obj.Add("color", "Red");
+                    return obj;
+                }
+
                 var item = Config.defectItemList.FirstOrDefault(m => m.Value<int>("id") == id);
-            if (item == null)
+                if (item == null)
-                return null;
+                    return null;
-            return (JObject)item;
+                return (JObject)item;
             }
             catch { return null; }
         }

LeatherProject/LeatherApp/Device/DefectLib.cs

@@ -10,11 +10,15 @@ using System.Linq;
 using System.Reflection;
 using System.Runtime.InteropServices;
 using System.Threading;
+using HalconDotNet;
+using System.Windows.Forms.VisualStyles;
 using LeatherApp.Utils;
 using Models;
 using OpenCvSharp;
 using OpenCvSharp.Extensions;
+using PG_Detect;
 using SqlSugar;
+using HZH_Controls;
 
 namespace LeatherApp.Device
 {
@@ -93,22 +97,14 @@ namespace LeatherApp.Device
         private List<DefectTask> taskMakeTagList = new List<DefectTask>();
 
         private string preModelName = "";
+
+        //传统算法核心
+        private PGDetect tPGDetect = new PGDetect();
         public DefectLib()
         {
         } 
         public bool start()
         {
-            //List<DefectLabelInfo> DefectLabelInfoList = new List<DefectLabelInfo>();
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 1953, y = 429, w = 200, h = 200, classId = 1, confidence = 0.8, contrast = 0.9, i = 0, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() {x = 1953,y = 929,w=900,h = 400,classId = 11,confidence = 0.8, contrast = 0.9, i = 0,j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 3169, y = 1029, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 1, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 4721, y = 919, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 2, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 6145, y = 829, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 3, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 8073, y = 929, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 4, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 9407, y = 929, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 5, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 10801, y = 999, w = 900, h = 400, classId = 11, confidence = 0.8, contrast = 0.9, i = 6, j = 0 });
-            //DefectLabelInfoList.Add(new DefectLabelInfo() { x = 12465, y = 629, w = 900, h = 800, classId = 11, confidence = 0.8, contrast = 0.9, i = 7, j = 0 });
-            //DefectLabelInfoList = HeBingDefect(16384, DefectLabelInfoList);
             try
             {
                 //detector = CreateDetector(Config.model_path, Config.labels_path, true, 6); 
@@ -238,6 +234,51 @@ namespace LeatherApp.Device
                 }
             }
         }
+
+
+        public bool LoadModel(string modelPath)
+        {
+            int step = 0;
+            try
+            {
+                if (!Config.OpenHalconDefect)
+                {
+                    if (preModelName != modelPath)
+                    {
+                        step = 3;
+                        //先释放模型
+                        if (detector != IntPtr.Zero)
+                        {
+                            step = 4;
+                            DestroyDetector(detector);
+                            detector = IntPtr.Zero;
+                        }
+                        step = 5;
+                        detector = CreateDetector($"./models/{modelPath}");
+                        if (detector == IntPtr.Zero)
+                            throw new Exception($"模型({modelPath})初始化失败！");
+                        step = 6;
+                        preModelName = modelPath;
+                    } 
+                }
+                else 
+                {
+                    HObject obj = new HObject();
+                    Mat mat = new Mat($"./init.bmp");
+                    OpenCVUtil.MatToHObject(mat, out obj);
+                    //HOperatorSet.GenImageConst(out obj, "byte", 2048 * 8, 2048 * 2);//生成一幅图像，用byte格式，默认是黑色
+                    //Mat initMat = new Mat(2048 * 2, 2048 * 8, MatType.CV_8UC3);
+                    if (!tPGDetect.IniOptimization(obj, Config.HalconParamPath))
+                        throw new Exception($"传统算法({Config.HalconParamPath})初始化失败！");
+                }
+                return true;
+            }
+            catch (Exception e)
+            {
+                WarningEvent?.Invoke(DateTime.Now, WarningEnum.Low, $"Load Model err({step}):" + e.Message);
+                return false;
+            }
+        }
         private void runStep()
         {
             int step = 0;
@@ -258,54 +299,67 @@ namespace LeatherApp.Device
                     {
                         Stopwatch stopwatch = Stopwatch.StartNew();
                         step =2;
-                        if (preModelName != task.modelName)
+                        LoadModel(task.modelName);
-                        {
-                            step = 3;
-                            //先释放模型
-                            if (detector != IntPtr.Zero)
-                            {
-                                step = 4;
-                                DestroyDetector(detector); 
-                                detector = IntPtr.Zero;
-                            }
-                            step = 5;
-                            detector = CreateDetector($"./models/{task.modelName}");
-                            if (detector == IntPtr.Zero)
-                                throw new Exception($"模型({task.modelName})初始化失败！");
-                            step = 6;
-                            preModelName = task.modelName;
-                        }
                         //源图  
                         //Bitmap bmp = yolo1.Read2Bmp(file_path);
                         //切割图像，输入图像格式14208*10640
                         stopwatch.Start();
-                        //task.resizeBmp = OpenCVUtil.resize( task.bmp.Clone(), task.resize.Width, task.resize.Height);//在外面已做了resize
+                        if (!Config.OpenHalconDefect)
-
-                        //Cv2.CvtColor(task.bmp, task.bmpBgr2rgb, ColorConversionCodes.BGR2RGB); 
-                        //task.bmps_cut = OpenCVToCutsMat(task.bmpBgr2rgb, image_width, image_hight); //这里cut时之前加的clone 
-                        step = 7;
-                        task.bmps_cut = OpenCVToCutsMat(task.bmp, image_width, image_hight); //这里cut时之前加的clone 
-                        stopwatch.Stop();
-                        task.stopwatch[0] = stopwatch.ElapsedMilliseconds;
-
-                        //Resize图像
-                        //stopwatch.Restart();
-                        //task.bmps_resize = yolo1.OpenCVToResizesMat(task.bmps_cut, task.resize.Width, task.resize.Height);
-                        //stopwatch.Stop();
-                        //task.stopwatch[1] = stopwatch.ElapsedMilliseconds;
-
-                        //预处理模型
-                        //stopwatch.Restart();
-                        //task.tensors = yolo1.PreprocessImageMat(task.bmps_resize);
-                        //stopwatch.Stop();
-                        //task.stopwatch[2] = stopwatch.ElapsedMilliseconds;
-                        step = 8;
-                        lock (taskOperationList)
                         {
-                            taskOperationList.Add(task);
+                            //task.resizeBmp = OpenCVUtil.resize( task.bmp.Clone(), task.resize.Width, task.resize.Height);//在外面已做了resize
-                            QueueCountEvent?.BeginInvoke(1, taskOperationList.Count, null, null);
+
+                            //Cv2.CvtColor(task.bmp, task.bmpBgr2rgb, ColorConversionCodes.BGR2RGB); 
+                            //task.bmps_cut = OpenCVToCutsMat(task.bmpBgr2rgb, image_width, image_hight); //这里cut时之前加的clone 
+                            step = 7;
+                            task.bmps_cut = OpenCVToCutsMat(task.bmp, image_width, image_hight); //这里cut时之前加的clone 
+                            stopwatch.Stop();
+                            task.stopwatch[0] = stopwatch.ElapsedMilliseconds;
+
+                            //Resize图像
+                            //stopwatch.Restart();
+                            //task.bmps_resize = yolo1.OpenCVToResizesMat(task.bmps_cut, task.resize.Width, task.resize.Height);
+                            //stopwatch.Stop();
+                            //task.stopwatch[1] = stopwatch.ElapsedMilliseconds;
+
+                            //预处理模型
+                            //stopwatch.Restart();
+                            //task.tensors = yolo1.PreprocessImageMat(task.bmps_resize);
+                            //stopwatch.Stop();
+                            //task.stopwatch[2] = stopwatch.ElapsedMilliseconds;
+                            step = 8;
+                            lock (taskOperationList)
+                            {
+                                taskOperationList.Add(task);
+                                QueueCountEvent?.BeginInvoke(1, taskOperationList.Count, null, null);
+                            }
+                            step = 9;
+                        }
+                        else
+                        {
+                            step = 20;
+
+                            int object_num = 0;
+                            //转换
+                            OpenCVUtil.MatToHObject(task.bmp, out task.ho_Img);
+
+                            stopwatch.Stop();
+                            task.stopwatch[0] = stopwatch.ElapsedMilliseconds;
+                            stopwatch.Restart();
+                            step = 21;
+                            //预处理
+                            tPGDetect.Processing(task.ho_Img, out task.ho_imgG, out task.ho_ImageResult3, out task.ho_ImageSub,
+                                Config.HalconParamPath,
+                                out task.hv_RES, out task.hv_gauss_filter1, out task.hv_gauss_filter2,
+                                out task.hv_Energy_value, out task.hv_Region_S_value, out task.hv_class);
+
+                            stopwatch.Stop();
+                            task.stopwatch[1] = stopwatch.ElapsedMilliseconds;
+                            lock (taskOperationList)
+                            {
+                                taskOperationList.Add(task);
+                                QueueCountEvent?.BeginInvoke(1, taskOperationList.Count, null, null);
+                            }
                         }
-                        step = 9;
                     }
                 }
                 catch (Exception ex)
@@ -335,7 +389,7 @@ namespace LeatherApp.Device
                 int cut_count=0,step = 0;
                 try
                 {
-                    if (task != null && task.bmps_cut.Count()>0)
+                    if (task != null && task.bmps_cut.Count()>0 && !Config.OpenHalconDefect)
                     { 
                         //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, "DefectLib tasks 运行推理...");
                         cut_count = task.bmps_cut.Count();
@@ -375,6 +429,24 @@ namespace LeatherApp.Device
                             QueueCountEvent?.BeginInvoke(2, taskMakeTagList.Count, null, null);
                         }
                     }
+                    else
+                    {
+                        Stopwatch stopwatch = Stopwatch.StartNew();
+                        stopwatch.Start();
+                        step = 22;
+                        //算法处理
+                        tPGDetect.Detect(task.ho_Img, task.ho_imgG, task.ho_ImageResult3, task.ho_ImageSub,
+                            task.hv_Energy_value, task.hv_Region_S_value, task.hv_class,
+                            out task.hv_defectinfo, out task.object_num);
+
+                        stopwatch.Stop();
+                        task.stopwatch[2] = stopwatch.ElapsedMilliseconds;
+                        lock (taskMakeTagList)
+                        {
+                            taskMakeTagList.Add(task);
+                            QueueCountEvent?.BeginInvoke(2, taskMakeTagList.Count, null, null);
+                        }
+                    }
                 }
                 catch (Exception ex)
                 {
@@ -663,60 +735,62 @@ namespace LeatherApp.Device
                     int count = 0;
                     liStep = 3;
 
-                    //车用革去除接头处横档误判
+                    if (!Config.OpenHalconDefect)
-                    bool haveJieTou = false;
-                    List<DefectLabelInfo> DefectLabelInfoList = new List<DefectLabelInfo>();
-
-                    for (int i = 0; i < cut_count; i++)
                     {
-                        liStep = i * 100;
+                        //车用革去除接头处横档误判
-                        //task.resultInfo += $"第 {i}/{cut_count} 张小图(大图索引{task.photoIndex}): 缺陷数 = {task.output_num[i]}\n";
+                        bool haveJieTou = false;
-                        //task.resultInfo +=$"大图({task.tag})[{task.bmp.Width}*{task.bmp.Height}],第 {i + 1}/{cut_count} 张小图[{task.bmps_cut[i].Width}*{task.bmps_cut[i].Height}]: 瑕疵output_num = {output_num[i]}\n";
+                        List<DefectLabelInfo> DefectLabelInfoList = new List<DefectLabelInfo>();
-                        #region 检测信息汇总
+
-                        for (int j = 0; j < task.output_num[i]; j++)//缺陷数
+                        for (int i = 0; i < cut_count; i++)
                         {
-                            liStep += j;//0
+                            liStep = i * 100;
-                                        //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"-------");
+                            //task.resultInfo += $"第 {i}/{cut_count} 张小图(大图索引{task.photoIndex}): 缺陷数 = {task.output_num[i]}\n";
-                            int index = count * detect_elem_size;
+                            //task.resultInfo +=$"大图({task.tag})[{task.bmp.Width}*{task.bmp.Height}],第 {i + 1}/{cut_count} 张小图[{task.bmps_cut[i].Width}*{task.bmps_cut[i].Height}]: 瑕疵output_num = {output_num[i]}\n";
-
+                            #region 检测信息汇总
-                            // 打印输出信息（示例代码，根据实际情况进行修改和格式化）
+                            for (int j = 0; j < task.output_num[i]; j++)//缺陷数
-                            // 获取输出信息
-                            int x = (int)task.output[index];
-                            int y = (int)task.output[index + 1];
-                            int w = (int)task.output[index + 2];
-                            int h = (int)task.output[index + 3];
-                            int classId = (int)task.output[index + 4];
-                            double confidence = Math.Round(task.output[index + 5], 2); //置信度
-                            double contrast = Math.Round(task.output[index + 6], 3);//对比度
-                            //y = image_hight-y-h;//转到右下角为原点
-                            count++;
-
-                            //var cmW = Math.Round(w * task.widthRatio / Config.cm2px_x, 2);
-                            //var cmH = Math.Round(h * task.widthRatio / Config.cm2px_y, 2);
-                            var cmW = Math.Round(w * 1.0 / Config.cm2px_x, 2);
-                            var cmH = Math.Round(h * 1.0 / Config.cm2px_y, 2);
-                            // 打印输出信息
-                            //task.resultInfo += $"----{i}----col:{i % colNum}/{colNum} row:{i / colNum}/{colNum}-----------\n目标:{j + 1} 类别ID:{classId} 置信度:{confidence} 对比度:{contrast} 坐标:({x},{y})-({x + w},{y + h}) 宽高:w={w},h={h}; \n";
-
-                            DefectLabelInfoList.Add(new DefectLabelInfo()
                             {
-                                x = (int)task.output[index],
+                                liStep += j;//0
-                                y = (int)task.output[index + 1],
+                                            //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"-------");
-                                w = (int)task.output[index + 2],
+                                int index = count * detect_elem_size;
-                                h = (int)task.output[index + 3],
-                                classId = (int)task.output[index + 4],
-                                confidence = Math.Round(task.output[index + 5], 2), //置信度
-                                contrast = ContrastToPercent( Math.Round(task.output[index + 6], 3)),//对比度
-                                //cmW = Math.Round(w * task.widthRatio / Config.cm2px_x, 2),
-                                //cmH = Math.Round(h * task.widthRatio / Config.cm2px_y, 2),
-                                cmW = Math.Round(w * 1.0 / Config.cm2px_x, 2),
-                                cmH = Math.Round(h * 1.0 / Config.cm2px_y, 2),
-                                i = i,
-                                j = j,
-                            });
-                        }
 
-                        #endregion       
+                                // 打印输出信息（示例代码，根据实际情况进行修改和格式化）
+                                // 获取输出信息
+                                int x = (int)task.output[index];
+                                int y = (int)task.output[index + 1];
+                                int w = (int)task.output[index + 2];
+                                int h = (int)task.output[index + 3];
+                                int classId = (int)task.output[index + 4];
+                                double confidence = Math.Round(task.output[index + 5], 2); //置信度
+                                double contrast = Math.Round(task.output[index + 6], 3);//对比度
+                                                                                        //y = image_hight-y-h;//转到右下角为原点
+                                count++;
+
+                                //var cmW = Math.Round(w * task.widthRatio / Config.cm2px_x, 2);
+                                //var cmH = Math.Round(h * task.widthRatio / Config.cm2px_y, 2);
+                                var cmW = Math.Round(w * 1.0 / Config.cm2px_x, 2);
+                                var cmH = Math.Round(h * 1.0 / Config.cm2px_y, 2);
+                                // 打印输出信息
+                                //task.resultInfo += $"----{i}----col:{i % colNum}/{colNum} row:{i / colNum}/{colNum}-----------\n目标:{j + 1} 类别ID:{classId} 置信度:{confidence} 对比度:{contrast} 坐标:({x},{y})-({x + w},{y + h}) 宽高:w={w},h={h}; \n";
+
+                                DefectLabelInfoList.Add(new DefectLabelInfo()
+                                {
+                                    x = (int)task.output[index],
+                                    y = (int)task.output[index + 1],
+                                    w = (int)task.output[index + 2],
+                                    h = (int)task.output[index + 3],
+                                    classId = (int)task.output[index + 4],
+                                    confidence = Math.Round(task.output[index + 5], 2), //置信度
+                                    contrast = ContrastToPercent(Math.Round(task.output[index + 6], 3)),//对比度
+                                                                                                        //cmW = Math.Round(w * task.widthRatio / Config.cm2px_x, 2),
+                                                                                                        //cmH = Math.Round(h * task.widthRatio / Config.cm2px_y, 2),
+                                    cmW = Math.Round(w * 1.0 / Config.cm2px_x, 2),
+                                    cmH = Math.Round(h * 1.0 / Config.cm2px_y, 2),
+                                    i = i,
+                                    j = j,
+                                });
+                            }
+
+                            #endregion
 #if false
                         for (int j = 0; j < task.output_num[i]; j++)//缺陷数
                         {
@@ -832,132 +906,206 @@ namespace LeatherApp.Device
                                      //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"缺陷小图数量:{task.lstDefectBmp.Count}");
                         }
 #endif
-                    }
+                        }
 
-                    #region 合并接头横档
+                        #region 合并接头横档
-                    liStep = 3000;
+                        liStep = 3000;
-                    if (DefectLabelInfoList.Count >0)
+                        if (DefectLabelInfoList.Count > 0)
-                        DefectLabelInfoList = HeBingDefect(task.bmp.Width, DefectLabelInfoList);
+                            DefectLabelInfoList = HeBingDefect(task.bmp.Width, DefectLabelInfoList);
-                    liStep++;
+                        liStep++;
-                    #endregion
+                        #endregion
 
-                    //结果过滤
+                        //结果过滤
-                    #region 结果过滤
+                        #region 结果过滤
-                    //降序排序，先得到是否有接头检出
+                        //降序排序，先得到是否有接头检出
-                    List<DefectLabelInfo> DefectLabelInfoListByClassID = DefectLabelInfoList.OrderByDescending(t => t.classId).ToList();//降序
+                        List<DefectLabelInfo> DefectLabelInfoListByClassID = DefectLabelInfoList.OrderByDescending(t => t.classId).ToList();//降序
-                    for (int q = 0; q < DefectLabelInfoListByClassID.Count; q++)
+                        for (int q = 0; q < DefectLabelInfoListByClassID.Count; q++)
-                    {
-                        //是否满足此产品标准
-                        if (task.qualifiedLimitList != null && task.qualifiedLimitList.Count > 0)
                         {
-                            qualifiedLimit = task.qualifiedLimitList.FirstOrDefault(m => m.Code == Config.getDefectCode(DefectLabelInfoListByClassID[q].classId));
+                            //是否满足此产品标准
-                            if (qualifiedLimit != null)
+                            if (task.qualifiedLimitList != null && task.qualifiedLimitList.Count > 0)
                             {
-                                // 打印输出信息
+                                qualifiedLimit = task.qualifiedLimitList.FirstOrDefault(m => m.Code == Config.getDefectCode(DefectLabelInfoListByClassID[q].classId));
-                                task.resultInfo += $"----{DefectLabelInfoListByClassID[q].i}----col:{DefectLabelInfoListByClassID[q].i % colNum}/{colNum} row:{DefectLabelInfoListByClassID[q].i / colNum}/{colNum}-----------\n目标:{DefectLabelInfoListByClassID[q].j + 1} 类别ID:{DefectLabelInfoListByClassID[q].classId} 置信度:{DefectLabelInfoListByClassID[q].confidence} 对比度:{DefectLabelInfoListByClassID[q].contrast}\n";
+                                if (qualifiedLimit != null)
+                                {
+                                    // 打印输出信息
+                                    task.resultInfo += $"----{DefectLabelInfoListByClassID[q].i}----col:{DefectLabelInfoListByClassID[q].i % colNum}/{colNum} row:{DefectLabelInfoListByClassID[q].i / colNum}/{colNum}-----------\n目标:{DefectLabelInfoListByClassID[q].j + 1} 类别ID:{DefectLabelInfoListByClassID[q].classId} 置信度:{DefectLabelInfoListByClassID[q].confidence} 对比度:{DefectLabelInfoListByClassID[q].contrast}\n";
 
-                                //if ((qualifiedLimit.ZXD > 0 && qualifiedLimit.ZXD > confidence)
+                                    //if ((qualifiedLimit.ZXD > 0 && qualifiedLimit.ZXD > confidence)
-                                //    || (qualifiedLimit.ContrastTop + qualifiedLimit.ContrastLower > 0 && x> qualifiedLimit.ContrastLower && x < qualifiedLimit.ContrastTop)
+                                    //    || (qualifiedLimit.ContrastTop + qualifiedLimit.ContrastLower > 0 && x> qualifiedLimit.ContrastLower && x < qualifiedLimit.ContrastTop)
-                                //    || (qualifiedLimit.Area > 0 && qualifiedLimit.Area > cmW * cmH))
+                                    //    || (qualifiedLimit.Area > 0 && qualifiedLimit.Area > cmW * cmH))
-                                if (DefectLabelInfoListByClassID[q].confidence <= qualifiedLimit.ZXD)//confidence > qualifiedLimit.ZXD 是瑕疵 才继续判断下面的两个条件
+                                    if (DefectLabelInfoListByClassID[q].confidence <= qualifiedLimit.ZXD)//confidence > qualifiedLimit.ZXD 是瑕疵 才继续判断下面的两个条件
-                                {
-                                    task.resultInfo += $"   置信度不满足此产品瑕疵标准，跳过！ \n";
-                                    continue;
-                                }
-
-                                //下限<对比度<上限：不是瑕疵
-                                var ContrastTotal = qualifiedLimit.ContrastTop + qualifiedLimit.ContrastLower;
-                                if (qualifiedLimit.IsOR)
-                                {
-                                    //if (!(
-                                    //    (ContrastTotal <= 0 || (PercentToContrast(DefectLabelInfoListByClassID[q].contrast) < qualifiedLimit.ContrastLower || PercentToContrast(DefectLabelInfoListByClassID[q].contrast) > qualifiedLimit.ContrastTop))))
-                                    //{
-                                    //    task.resultInfo += $"   不满足此产品瑕疵标准，跳过！ \n";
-                                    //    //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断不是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
-                                    //    continue;
-                                    //}
-                                }
-                                else
-                                {
-                                    if (!(ContrastTotal <= 0 || (PercentToContrast(DefectLabelInfoListByClassID[q].contrast) < qualifiedLimit.ContrastLower || PercentToContrast(DefectLabelInfoListByClassID[q].contrast) > qualifiedLimit.ContrastTop)))
                                     {
-                                        task.resultInfo += $"   不满足此产品瑕疵标准，跳过！ \n";
+                                        task.resultInfo += $"   置信度不满足此产品瑕疵标准，跳过！ \n";
-                                        //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断不是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
                                         continue;
                                     }
+
+                                    //下限<对比度<上限：不是瑕疵
+                                    var ContrastTotal = qualifiedLimit.ContrastTop + qualifiedLimit.ContrastLower;
+                                    if (qualifiedLimit.IsOR)
+                                    {
+                                        //if (!(
+                                        //    (ContrastTotal <= 0 || (PercentToContrast(DefectLabelInfoListByClassID[q].contrast) < qualifiedLimit.ContrastLower || PercentToContrast(DefectLabelInfoListByClassID[q].contrast) > qualifiedLimit.ContrastTop))))
+                                        //{
+                                        //    task.resultInfo += $"   不满足此产品瑕疵标准，跳过！ \n";
+                                        //    //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断不是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
+                                        //    continue;
+                                        //}
+                                    }
+                                    else
+                                    {
+                                        if (!(ContrastTotal <= 0 || (PercentToContrast(DefectLabelInfoListByClassID[q].contrast) < qualifiedLimit.ContrastLower || PercentToContrast(DefectLabelInfoListByClassID[q].contrast) > qualifiedLimit.ContrastTop)))
+                                        {
+                                            task.resultInfo += $"   不满足此产品瑕疵标准，跳过！ \n";
+                                            //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断不是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
+                                            continue;
+                                        }
+                                    }
+                                    if (qualifiedLimit.Area > 0 && DefectLabelInfoListByClassID[q].cmW * DefectLabelInfoListByClassID[q].cmH < qualifiedLimit.Area)
+                                    {
+                                        task.resultInfo += $"   不满足此产品瑕疵标准面积，跳过！ \n";
+                                        continue;
+                                    }
+                                    if (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "jietou")
+                                        haveJieTou = true;
+                                    if (haveJieTou && (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "hengdang"))
+                                    {
+                                        task.resultInfo += $"   判断为接头处横档，跳过！ \n";
+                                        continue;
+                                    }
+                                    if (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "na")
+                                    {
+                                        task.resultInfo += $"   判断为正向标签na，跳过！ \n";
+                                        continue;
+                                    }
+                                    //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
                                 }
-                                if(qualifiedLimit.Area > 0 && DefectLabelInfoListByClassID[q].cmW * DefectLabelInfoListByClassID[q].cmH < qualifiedLimit.Area)
-                                {
-                                    task.resultInfo += $"   不满足此产品瑕疵标准面积，跳过！ \n";     
-                                    continue;
-                                }
-                                if (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "jietou")
-                                    haveJieTou = true;
-                                if(haveJieTou && (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "hengdang"))
-                                {
-                                    task.resultInfo += $"   判断为接头处横档，跳过！ \n";
-                                    continue;
-                                }
-                                if (Config.getDefectCode(DefectLabelInfoListByClassID[q].classId) == "na")
-                                {
-                                    task.resultInfo += $"   判断为正向标签na，跳过！ \n";
-                                    continue;
-                                }
-                                //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"判断是瑕疵：类别ID:{classId}； 置信度({confidence},[{qualifiedLimit.ZXD}]); isOr({qualifiedLimit.IsOR}); 面积({cmW * cmH},[{ qualifiedLimit.Area}]); 对比度({contrast},[{qualifiedLimit.ContrastLower}-{qualifiedLimit.ContrastTop}])");
                             }
+                            liStep++;//1
+                                     //打标
+                            var point1 = new OpenCvSharp.Point((DefectLabelInfoListByClassID[q].i % colNum) * image_width + DefectLabelInfoListByClassID[q].x, (DefectLabelInfoListByClassID[q].i / colNum) * image_hight + DefectLabelInfoListByClassID[q].y);
+                            var point2 = new OpenCvSharp.Point(point1.X + DefectLabelInfoListByClassID[q].w, point1.Y + DefectLabelInfoListByClassID[q].h);
+                            liStep++;//2
+                                     //task.resultInfo += $"   转换到大图坐标(px)：p1={point1.X},{point1.Y}; p2={point2.X},{point2.Y}\n";
+                            Cv2.Rectangle(task.bmpTag, point1, point2, new Scalar(0.0, 0.0, 255.0), 5);//画打标点 
+
+                            //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"保存第 {count} 行缺陷信息；");
+                            int px = (point1.X - task.xw) > 0 ? (point1.X - task.xw) : 0;
+                            //var cmX = Math.Round(px * task.widthRatio / Config.cm2px_x, 2);
+                            var cmX = Math.Round((double)px / Config.cm2px_x, 2);
+                            //var cmY = Math.Round((task.bmp.Height - point1.Y - DefectLabelInfoListByClassID[q].h) * task.widthRatio / Config.cm2px_y, 2);//外面计Y从右下角为原点
+                            var cmY = Math.Round((task.bmp.Height - point1.Y - DefectLabelInfoListByClassID[q].h) * 1.0 / Config.cm2px_y, 2);//外面计Y从右下角为原点
+                            liStep++;//3
+                                     //task.resultInfo += $"   转换到大图坐标(cm)[widthRatio={task.widthRatio}]：x={cmX},y={cmY}; w={DefectLabelInfoList[q].cmW},h={DefectLabelInfoList[q].cmH}\n";
+                            task.excelTable.Rows.Add($"{task.photoIndex}", cmX, cmY, DefectLabelInfoListByClassID[q].cmW, DefectLabelInfoListByClassID[q].cmH, DefectLabelInfoListByClassID[q].j + 1, DefectLabelInfoListByClassID[q].classId, DefectLabelInfoListByClassID[q].confidence, DefectLabelInfoListByClassID[q].contrast);
+
+                            liStep++;//4
+                                     //切缺陷小图 
+                                     //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"保存第 {count} 个缺陷小图；");
+                            int left, top, decX, decY;
+                            decX = (DefectLabelInfoListByClassID[q].w > 236 ? 20 : 256 - DefectLabelInfoListByClassID[q].w) / 2;
+                            decY = (DefectLabelInfoListByClassID[q].h > 236 ? 20 : 256 - DefectLabelInfoListByClassID[q].h) / 2;
+                            left = point1.X - decX;
+                            top = point1.Y - decY;
+                            if (left < 0) left = 0;
+                            if (top < 0) top = 0;
+
+                            int width = DefectLabelInfoListByClassID[q].w + decX * 2;
+                            int height = DefectLabelInfoListByClassID[q].h + decY * 2;
+                            if (left + width > task.bmp.Width - 1) width = task.bmp.Width - left - 1;
+                            if (top + height > task.bmp.Height - 1) height = task.bmp.Height - top - 1;
+                            liStep++;//5 
+                            Rect roi = new Rect(left, top, width, height);
+                            liStep++;//6
+                            if (height < 1 || width < 1)
+                            {
+                                //task.resultInfo += $"   打标到大图坐标Rect(px)：left={left},top={top}; width={width},height={height}\n";
+                                //task.resultInfo += $"   test  point1.Y={point1.Y},h={DefectLabelInfoList[q].h}; top={top},mat.Height={task.bmp.Height}\n================\n";
+                                WarningEvent?.Invoke(DateTime.Now, WarningEnum.Normal, task.resultInfo);
+                            }
+
+                            //保存
+                            //string filename = $"{Config.appBasePath}\\temp\\{task.tag}\\{task.tag}_X{mmX.ToString()}_Y{mmY.ToString()}_W{mmW.ToString()}_H{mmH.ToString()}_目标{j + 1}_类别{classId}_置信度{confidence}.bmp";
+                            //OpenCvSharp.Extensions.BitmapConverter.ToBitmap(new Mat(task.bmp, roi)).Save(filename, ImageFormat.Jpeg);
+
+                            task.lstDefectBmp.Add(new Mat(task.bmpTag, roi).Clone());
+                            liStep++;//7
                         }
-                        liStep++;//1
+                        #endregion
-                                 //打标
-                        var point1 = new OpenCvSharp.Point((DefectLabelInfoListByClassID[q].i % colNum) * image_width + DefectLabelInfoListByClassID[q].x, (DefectLabelInfoListByClassID[q].i / colNum) * image_hight + DefectLabelInfoListByClassID[q].y);
-                        var point2 = new OpenCvSharp.Point(point1.X + DefectLabelInfoListByClassID[q].w, point1.Y + DefectLabelInfoListByClassID[q].h);
-                        liStep++;//2
-                        //task.resultInfo += $"   转换到大图坐标(px)：p1={point1.X},{point1.Y}; p2={point2.X},{point2.Y}\n";
-                        Cv2.Rectangle(task.bmpTag, point1, point2, new Scalar(0.0, 0.0, 255.0), 5);//画打标点 
-
-                        //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"保存第 {count} 行缺陷信息；");
-                        int px = (point1.X - task.xw) > 0 ? (point1.X - task.xw) : 0;
-                        //var cmX = Math.Round(px * task.widthRatio / Config.cm2px_x, 2);
-                        var cmX = Math.Round((double)px / Config.cm2px_x, 2);
-                        //var cmY = Math.Round((task.bmp.Height - point1.Y - DefectLabelInfoListByClassID[q].h) * task.widthRatio / Config.cm2px_y, 2);//外面计Y从右下角为原点
-                        var cmY = Math.Round((task.bmp.Height - point1.Y - DefectLabelInfoListByClassID[q].h) * 1.0 / Config.cm2px_y, 2);//外面计Y从右下角为原点
-                        liStep++;//3
-                        //task.resultInfo += $"   转换到大图坐标(cm)[widthRatio={task.widthRatio}]：x={cmX},y={cmY}; w={DefectLabelInfoList[q].cmW},h={DefectLabelInfoList[q].cmH}\n";
-                        task.excelTable.Rows.Add($"{task.photoIndex}", cmX, cmY, DefectLabelInfoListByClassID[q].cmW, DefectLabelInfoListByClassID[q].cmH, DefectLabelInfoListByClassID[q].j + 1, DefectLabelInfoListByClassID[q].classId, DefectLabelInfoListByClassID[q].confidence, DefectLabelInfoListByClassID[q].contrast);
-
-                        liStep++;//4
-                                 //切缺陷小图 
-                                 //WarningEvent?.Invoke(DateTime.Now,WarningEnum.Low, $"保存第 {count} 个缺陷小图；");
-                        int left, top, decX, decY;
-                        decX = (DefectLabelInfoListByClassID[q].w > 236 ? 20 : 256 - DefectLabelInfoListByClassID[q].w) / 2;
-                        decY = (DefectLabelInfoListByClassID[q].h > 236 ? 20 : 256 - DefectLabelInfoListByClassID[q].h) / 2;
-                        left = point1.X - decX;
-                        top = point1.Y - decY;
-                        if (left < 0) left = 0;
-                        if (top < 0) top = 0;
-
-                        int width = DefectLabelInfoListByClassID[q].w + decX * 2;
-                        int height = DefectLabelInfoListByClassID[q].h + decY * 2;
-                        if (left + width > task.bmp.Width - 1) width = task.bmp.Width - left - 1;
-                        if (top + height > task.bmp.Height - 1) height = task.bmp.Height - top - 1;
-                        liStep++;//5 
-                        Rect roi = new Rect(left, top, width, height);
-                        liStep++;//6
-                        if (height < 1 || width < 1)
-                        {
-                            //task.resultInfo += $"   打标到大图坐标Rect(px)：left={left},top={top}; width={width},height={height}\n";
-                            //task.resultInfo += $"   test  point1.Y={point1.Y},h={DefectLabelInfoList[q].h}; top={top},mat.Height={task.bmp.Height}\n================\n";
-                            WarningEvent?.Invoke(DateTime.Now, WarningEnum.Normal, task.resultInfo);
-                        }
-
-                        //保存
-                        //string filename = $"{Config.appBasePath}\\temp\\{task.tag}\\{task.tag}_X{mmX.ToString()}_Y{mmY.ToString()}_W{mmW.ToString()}_H{mmH.ToString()}_目标{j + 1}_类别{classId}_置信度{confidence}.bmp";
-                        //OpenCvSharp.Extensions.BitmapConverter.ToBitmap(new Mat(task.bmp, roi)).Save(filename, ImageFormat.Jpeg);
-
-                        task.lstDefectBmp.Add(new Mat(task.bmpTag, roi).Clone());
-                        liStep++;//7
                     }
-                    #endregion
+                    else
-                    liStep = 99;
+                    {
+                        stopwatch.Restart();
+                        //打标
+                        var defectinfo = task.hv_defectinfo.ToOArr();
+                        List<DefectLabelInfo> DefectLabelInfoList = new List<DefectLabelInfo>();
+                        for (int i = 0; i < task.object_num; i++)
+                        {
+                            liStep = 23 + i;
+                            #region 检测信息汇总
+                            int index = i * 6;
+
+                            // 打印输出信息（示例代码，根据实际情况进行修改和格式化）
+                            // 获取输出信息
+                            int x = (int)defectinfo[index].ToInt();
+                            int y = (int)defectinfo[index + 1].ToInt();
+                            int w = (int)defectinfo[index + 2].ToInt();
+                            int h = (int)defectinfo[index + 3].ToInt();
+                            int classId = -99;//(int)defectinfo[index + 4].ToInt();
+                            double confidence = Math.Round(defectinfo[index + 5].ToDouble(), 2); //置信度
+
+                            int px = x;
+                            var cmX = Math.Round(px * task.widthRatio / Config.cm2px_x, 2);
+                            var cmY = Math.Round((task.bmp.Height - y - h) * task.widthRatio / Config.cm2px_y, 2);//外面计Y从右下角为原点
+
+                            DefectLabelInfoList.Add(new DefectLabelInfo()
+                            {
+                                x = x,
+                                y = y,
+                                w = w,
+                                h = h,
+                                classId = classId,
+                                confidence = confidence, //置信度
+                                cmW = Math.Round(w * task.widthRatio / Config.cm2px_x, 2),
+                                cmH = Math.Round(h * task.widthRatio / Config.cm2px_y, 2),
+                                i = i,
+                                j = i,
+                            });
+                            //y = image_hight-y-h;//转到右下角为原点
+                            task.excelTable.Rows.Add($"{task.photoIndex}", cmX, cmY,
+                                Math.Round(w * task.widthRatio / Config.cm2px_x, 2), Math.Round(h * task.widthRatio / Config.cm2px_y, 2),
+                                i, classId, confidence, 0);
+
+                            int penLine = 20;
+                            //打标
+                            var point1 = new OpenCvSharp.Point(x, y);
+                            var point2 = new OpenCvSharp.Point(point1.X + w + penLine / 2, point1.Y + h + penLine / 2);
+                            Cv2.Rectangle(task.bmpTag, point1, point2, new Scalar(0.0, 0.0, 255.0), penLine);//画打标点 
+
+                            //切小图
+                            int left, top, decX, decY;
+
+                            int tdecX = (w / 2) / 2;
+                            int tdecY = w / h > 4 ? w / 8 : (h / 1) / 2;
+
+                            decX = (w > 236 ? tdecX : 256 - w) / 2;
+                            decY = (h > 236 ? tdecY : 256 - h) / 2;
+
+                            left = point1.X - decX;
+                            top = point1.Y - decY;
+                            if (left < 0) left = 0;
+                            if (top < 0) top = 0;
+
+                            int width = w + decX * 2;
+                            int height = h + decY * 2;
+                            if (left + width > task.bmp.Width - 1) width = task.bmp.Width - left - 1;
+                            if (top + height > task.bmp.Height - 1) height = task.bmp.Height - top - 1;
+
+                            Rect roi = new Rect(left, top, width, height);
+                            task.lstDefectBmp.Add(new Mat(task.bmpTag, roi).Clone());
+                            #endregion
+                        }
+                    }
+                        liStep = 99;
                     stopwatch.Stop();
                     task.stopwatch[3] = stopwatch.ElapsedMilliseconds;
 
@@ -1081,6 +1229,14 @@ namespace LeatherApp.Device
             public long[] stopwatch = new long[4];
 
             public int xw;
+
+            //传统算法使用
+            public HObject ho_Img = new HObject();
+            public HObject ho_imgG = new HObject();
+            public HObject ho_ImageResult3 = new HObject();
+            public HObject ho_ImageSub = new HObject();
+            public HTuple hv_RES, hv_gauss_filter1, hv_gauss_filter2, hv_Energy_value, hv_Region_S_value, hv_class, hv_defectinfo;
+            public int object_num = 0;
         }
 
         public void add(DefectTask task)

LeatherProject/LeatherApp/LeatherApp.csproj

@@ -59,6 +59,15 @@
     <Reference Include="ExcelNumberFormat, Version=1.1.0.0, Culture=neutral, PublicKeyToken=23c6f5d73be07eca, processorArchitecture=MSIL">
       <HintPath>..\packages\ExcelNumberFormat.1.1.0\lib\net20\ExcelNumberFormat.dll</HintPath>
     </Reference>
+    <Reference Include="halcondotnet">
+      <HintPath>Dll\halcondotnet.dll</HintPath>
+    </Reference>
+    <Reference Include="hdevenginedotnet">
+      <HintPath>Dll\hdevenginedotnet.dll</HintPath>
+    </Reference>
+    <Reference Include="HZH_Controls">
+      <HintPath>..\..\..\..\..\版博士\源码\V2.0\halftoneproject-master\BanBoShi\Dlls\HZH_Controls.dll</HintPath>
+    </Reference>
     <Reference Include="IKapBoardClassLibrary">
       <HintPath>C:\Program Files\I-TEK OptoElectronics\IKapLibrary\Dll\C#\IKapBoardClassLibrary.dll</HintPath>
     </Reference>
@@ -86,6 +95,9 @@
     <Reference Include="OpenCvSharp.Extensions, Version=1.0.0.0, Culture=neutral, PublicKeyToken=6adad1e807fea099, processorArchitecture=MSIL">
       <HintPath>..\packages\OpenCvSharp4.Extensions.4.7.0.20230115\lib\net48\OpenCvSharp.Extensions.dll</HintPath>
     </Reference>
+    <Reference Include="PG_Detect">
+      <HintPath>Dll\PG_Detect.dll</HintPath>
+    </Reference>
     <Reference Include="S7.Net, Version=0.20.0.0, Culture=neutral, PublicKeyToken=d5812d469e84c693, processorArchitecture=MSIL">
       <HintPath>..\packages\S7netplus.0.20.0\lib\net462\S7.Net.dll</HintPath>
     </Reference>

LeatherProject/LeatherApp/Page/FHome.cs

@@ -64,6 +64,9 @@ namespace LeatherApp.Page
         private bool init_Cloud;
         //
         private bool _residueWarnningLenStop;
+
+        //判断是否已经扫码获取erp信息
+        private bool _IsGetErpCode = false;
         public FHome(FProductInfo frm)
         { 
             InitializeComponent();
@@ -804,6 +807,8 @@ namespace LeatherApp.Page
                             //
                             pStopWatch.Restart();
                             errCode = 19;
+                            //扫码成功
+                            _IsGetErpCode = true;
                         }
                         catch (Exception ex)
                         {
@@ -1590,6 +1595,11 @@ namespace LeatherApp.Page
                 //System.GC.Collect();
             }
         }
+        
+        /// <summary>
+        /// 处理完成回调
+        /// </summary>
+        /// <param name="res"></param>
         private void callBackDefectEvent(Device.DefectLib.DefectTask res)
         {
             {
@@ -1791,7 +1801,9 @@ namespace LeatherApp.Page
                 }
             }
         }
-
+        /// <summary>
+        /// 数据保存状态
+        /// </summary>
         private bool _isDefect = false;
         private async void saveCurrRecord(int key, string batchId, string reelId, double erpLen)
         {
@@ -1892,6 +1904,14 @@ namespace LeatherApp.Page
         //启动
         private void btnStart_Click(object sender, EventArgs e)
         {
+            if(!_IsGetErpCode)
+            {
+                AddTextEvent(DateTime.Now, "启动", "还未扫码获取检测信息！", WarningEnum.Low);
+                return;
+            }
+
+            devContainer.devCamer1.resetScanIndex();
+            devContainer.devCamer2.resetScanIndex();
             AddTextEvent(DateTime.Now,"启动", "下发启动指令...");
             if (!Config.StopPLC)
                 this.devContainer.devPlc.runDev();
@@ -2042,11 +2062,13 @@ namespace LeatherApp.Page
                 pStopWatch.Stop();
                 this.btnStart.Enabled = true;
                 this.btnEnd.Enabled = this.btnPause.Enabled = false;//这里有问题，应该是devPlc回调设置
+                _IsGetErpCode = false;
             }
             else
             {
                 AddTextEvent(DateTime.Now, "结束验布", "无数据结束验布！");
                 _isDefect = false;
+                _IsGetErpCode = false;
             }
         }
         private void lstboxLog_DrawItem(object sender, DrawItemEventArgs e)

LeatherProject/LeatherApp/Utils/OpenCVUtil.cs

@@ -1,10 +1,12 @@
 using System;
 using System.Collections.Generic;
 using System.Linq;
+using System.Runtime.InteropServices;
 using System.Text;
 using System.Threading.Tasks;
 using System.Xaml;
 using DocumentFormat.OpenXml.Vml;
+using HalconDotNet;
 using OpenCvSharp;
 using OpenCvSharp.XImgProc;
 namespace LeatherApp.Utils
@@ -1241,5 +1243,155 @@ namespace LeatherApp.Utils
             return result;
         }
 
+        #region MatToHalcon
+        public static void MatToHObject(Mat imgMat, out HObject imgHOject)
+        {
+            int ImageWidth = imgMat.Width;
+            int ImageHeight = imgMat.Height;
+            int channel = imgMat.Channels();
+            long size = ImageWidth * ImageHeight * channel;
+            int col_byte_num = ImageWidth * channel;
+
+
+            byte[] rgbValues = new byte[size];
+            unsafe
+            {
+                for (int i = 0; i < ImageHeight; i++)
+                {
+                    IntPtr c = imgMat.Ptr(i);
+                    // 一行一行将mat 像素复制到byte[]
+                    Marshal.Copy(c, rgbValues, i * col_byte_num, col_byte_num);
+                }
+                void* p;
+                IntPtr ptr;
+                fixed (byte* pc = rgbValues)
+                {
+                    p = (void*)pc;
+                    ptr = new IntPtr(p);
+                }
+
+
+                if (channel == 1)
+                {
+                    HOperatorSet.GenImage1(out imgHOject, "byte", ImageWidth, ImageHeight, ptr);
+                }
+                else
+                {
+                    HOperatorSet.GenImageInterleaved(out imgHOject, ptr, "bgr", ImageWidth, ImageHeight, 0, "byte", 0, 0, 0, 0, -1, 0);
+                }
+            }
+        }
+#if false
+            /// <summary>
+            /// 把OpenCV图像转换到Halcon图像
+            /// </summary>
+            /// <param name="mImage">OpenCV图像_Mat</param>
+            /// <returns>Halcon图像_HObject</returns>
+            public HObject MatToHImage(Mat mImage)
+            {
+                try
+                {
+                    HObject hImage;
+                    int matChannels = 0;   // 通道数
+                    Type matType = null;
+                    int width, height;   // 宽，高
+                    width = height = 0;  // 宽，高初始化
+ 
+                    // 获取通道数
+                    matChannels = mImage.Channels();
+                    if (matChannels == 0)
+                    {
+                        return null;
+                    }
+                    if (matChannels == 1)        // 单通道
+                    {
+                        IntPtr ptr;      // 灰度图通道
+                        Mat[] mats = mImage.Split();
+ 
+                        // 改自：Mat.GetImagePointer1(mImage, out ptr, out matType, out width, out height);     // ptr=2157902018096    cType=byte    width=830    height=822
+                        ptr = mats[0].Data;          // 取灰度图值
+                        matType = mImage.GetType();  // byte
+                        height = mImage.Rows;        // 高
+                        width = mImage.Cols;         // 宽
+ 
+                        // 改自：hImage = new HObject(new OpenCvSharp.Size(width, height), MatType.CV_8UC1, new Scalar(0));
+                        byte[] dataGrayScaleImage = new byte[width * height];      //Mat dataGrayScaleImage = new Mat(new OpenCvSharp.Size(width, height), MatType.CV_8UC1);
+ 
+                        unsafe
+                        {
+                            fixed (byte* ptrdata = dataGrayScaleImage)
+                            {
+
+            #region 按行复制
+                                 //for (int i = 0; i < height; i++)
+                                 //{
+                                 //    CopyMemory((IntPtr)(ptrdata + width * i), new IntPtr((long)ptr + width * i), width);
+                                 //}
+
+            #endregion
+
+                                CopyMemory((IntPtr)ptrdata, new IntPtr((long)ptr), width * height);
+                                HOperatorSet.GenImage1(out hImage, "byte", width, height, (IntPtr) ptrdata);
+ 
+                            }
+                        }
+                        return hImage;
+                    }
+                    else if (matChannels == 3)   // 三通道
+                    {
+                        IntPtr ptrRed;    // R通道图
+                        IntPtr ptrGreen;  // G通道图
+                        IntPtr ptrBlue;   // B通道图
+                        Mat[] mats = mImage.Split();
+  
+                        ptrRed = mats[0].Data;    // 取R通道值
+                        ptrGreen = mats[1].Data;  // 取G通道值
+                        ptrBlue = mats[2].Data;   // 取B通道值
+                        matType = mImage.GetType();  // 类型
+                        height = mImage.Rows;        // 高
+                        width = mImage.Cols;         // 宽
+   
+                        // 改自：hImage = new HObject(new OpenCvSharp.Size(width, height), MatType.CV_8UC1, new Scalar(0));
+                        byte[] dataRed = new byte[width * height];      //Mat dataGrayScaleImage = new Mat(new OpenCvSharp.Size(width, height), MatType.CV_8UC1);
+                        byte[] dataGreen = new byte[width * height];
+                        byte[] dataBlue = new byte[width * height];
+   
+                        unsafe
+                        {
+                            fixed (byte* ptrdataRed = dataRed, ptrdataGreen = dataGreen, ptrdataBlue = dataBlue)
+                            {
+           
+                #region 按行复制
+                            //HImage himg = new HImage("byte", width, height, (IntPtr)ptrdataRed);
+                            //for (int i = 0; i < height; i++)
+                            //{
+                            //     CopyMemory((IntPtr)(ptrdataRed + width * i), new IntPtr((long)ptrRed + width * i), width);
+                            //     CopyMemory((IntPtr)(ptrdataGreen + width * i), new IntPtr((long)ptrGreen + width * i), width);
+                            //     CopyMemory((IntPtr)(ptrdataBlue + width * i), new IntPtr((long)ptrBlue + width * i), width);
+                            //}
+ 
+                #endregion
+
+                                CopyMemory((IntPtr)ptrdataRed, new IntPtr((long)ptrRed), width * height);        // 复制R通道
+                                CopyMemory((IntPtr)ptrdataGreen, new IntPtr((long)ptrGreen), width * height);    // 复制G通道
+                                CopyMemory((IntPtr)ptrdataBlue, new IntPtr((long)ptrBlue), width * height);      // 复制B通道
+                                HOperatorSet.GenImage3(out hImage, "byte", width, height, (IntPtr)ptrdataRed, (IntPtr)ptrdataGreen, (IntPtr)ptrdataBlue);   // 合成
+                            }
+                        }
+                        return hImage;
+                    }
+                    else
+                    {
+                        return null;
+                    }
+                }
+                catch (Exception ex)
+                {
+                    throw ex;
+                }
+
+            }
+#endif
+        #endregion
     }
 }

LeatherProject/LeatherApp/bin/Debug/CMDProcess/10.json

@@ -1 +1 @@
-{"Direction":0,"IN_OP_SHOW":["XXXX XXXL","XXXX XXXX","XXXX XXXX","XXXX XXXX"],"IN_Waiting_Timeout":0,"OUT_OP_SHOW":["XXXX XXXH","XXXX XXXX","XXXX XXXX","XXXX XXXX"],"SleepPre":0,"SleepLater":0,"AsynRun":false,"Disable":false}
+{"Direction":0,"IN_OP_SHOW":["XXXX XXXH","XXXX XXXX","XXXX XXXX","XXXX XXXX"],"IN_Waiting_Timeout":0,"OUT_OP_SHOW":["XXXX XXXH","XXXX XXXX","XXXX XXXX","XXXX XXXX"],"SleepPre":0,"SleepLater":0,"AsynRun":false,"Disable":false}