using HalconDotNet;
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using LB_SmartVisionCommon;
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using LB_VisionControls;
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using Newtonsoft.Json;
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using Newtonsoft.Json.Linq;
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using OpenCvSharp;
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using SmartMore.ViMo;
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using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Drawing.Imaging;
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using System.Linq;
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using System.Reflection;
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using Point = OpenCvSharp.Point;
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namespace LB_VisionProcesses.Alogrithms.BigModel.Segment
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{
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public class SegmentTool : TAlgorithm
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{
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public Dictionary<string, SegmentParam> dicSegmentParam;
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/// <summary>
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/// 模型路径
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/// </summary>
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private string modelPath = string.Empty;
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/// <summary>
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/// 模型ID
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/// </summary>
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private string modelID = "0";
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/// <summary>
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/// 是否使用GPU
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/// </summary>
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private bool isUseGPU = false;
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/// <summary>
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/// GPUID
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/// </summary>
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private int deviceGPUID = 0;
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/// <summary>
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/// BatchSize
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/// </summary>
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private int batchSize = 1;
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/// <summary>
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/// DP解决方案
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/// </summary>
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private Solution solution;
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/// <summary>
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/// 分割模型
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/// </summary>
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private ISegmentationModule module;
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/// <summary>
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/// 分割参数
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/// </summary>
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private SegmentationParams segParams;
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public List<string> SegFeatures = new List<string>();
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public SegmentTool()
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{
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strProcessClass = "LB_VisionProcesses.Alogrithms.BigModel.Segment.SegmentTool";
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strProcessName = "语义分割工具";
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//模型输入
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Params.Inputs.Add("ModelPath", "");
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Params.Inputs.Add("ModuleId", "0");
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Params.Inputs.Add("UseGpu", false);
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Params.Inputs.Add("DeviceId", 0);
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Params.Inputs.Add("BatchSize", 1);
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Params.Inputs.Add("MaxTimeOut", 5000);
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//面积阈值
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Params.Inputs.Add("AreaThresholds", new Dictionary<string, double>());
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//长边过滤阈值
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Params.Inputs.Add("LongSideThresholds", new Dictionary<string, double>());
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//短边过滤阈值
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Params.Inputs.Add("ShortSideThresholds", new Dictionary<string, double>());
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//平均置信度阈值
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//Params.Inputs.Add("MeanScoreThresholds", 0.0f);
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//类别置信度阈值
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Params.Inputs.Add("ClassesScoreThresholds", new Dictionary<string, double>());
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//ROI
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//Params.Inputs.Add("ROIx1", 0);
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//Params.Inputs.Add("ROIy1", 0);
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//Params.Inputs.Add("ROIx2", 0);
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//Params.Inputs.Add("ROIy2", 0);
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Params.Inputs.Add("ROI", new List<double>());
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//筛选后输出输出
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Params.Outputs.Add("Count", 0);
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Params.Outputs.Add("ClassID", new List<int>());
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Params.Outputs.Add("Labels", new List<string>());
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Params.Outputs.Add("Area", new List<double>());
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Params.Outputs.Add("LongSide", new List<double>());
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Params.Outputs.Add("ShortSide", new List<double>());
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Params.Outputs.Add("MeanScore", new List<double>());
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//bbox
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Params.Outputs.Add("X", new List<double>());
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Params.Outputs.Add("Y", new List<double>());
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Params.Outputs.Add("Height", new List<double>());
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Params.Outputs.Add("Width", new List<double>());
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//轮廓线
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Params.Outputs.Add("OuterContours", new List<List<List<Point>>>());
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}
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private void VisualizeSegmentationResult(SegmentationResponse rsp, Mat image, Dictionary<string, double> AreaThresholds, Dictionary<string, double> LongSideThresholds, Dictionary<string, double> ShortSideThresholds, Dictionary<string, double> ClassesScoreThresholds)
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{
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// 预定义类别颜色映射表（支持最多20个类别）
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var classColors = new List<Scalar>
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{
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new Scalar(0, 0, 255), // 0: 红色
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new Scalar(0, 255, 0), // 1: 绿色
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new Scalar(255, 0, 0), // 2: 蓝色
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new Scalar(255, 255, 0), // 3: 青色
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new Scalar(255, 0, 255), // 4: 品红
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new Scalar(0, 255, 255), // 5: 黄色
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new Scalar(128, 0, 0), // 6: 深红
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new Scalar(0, 128, 0), // 7: 深绿
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new Scalar(0, 0, 128), // 8: 深蓝
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new Scalar(128, 128, 0), // 9: 橄榄色
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new Scalar(128, 0, 128), // 10: 紫色
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new Scalar(0, 128, 128), // 11: 靛蓝
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new Scalar(255, 165, 0), // 12: 橙色
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new Scalar(255, 192, 203),// 13: 粉红色
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new Scalar(147, 112, 219),// 14: 紫罗兰
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new Scalar(255, 99, 71), // 15: 番茄红
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new Scalar(255, 20, 147), // 16: 紫色
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new Scalar(30, 144, 255), // 17: 道奇蓝
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new Scalar(255, 69, 0), // 18: 橙红色
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new Scalar(0, 206, 209) // 19: 碧绿色
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};
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Record = new ObjectRecord();
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int Count = 0;
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var ClassIDList = new List<int>();
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var LabelsList = new List<string>();
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var AreaList = new List<double>();
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var LongSideList = new List<double>();
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var ShortSideList = new List<double>();
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var MeanScoreList = new List<double>();
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var XList = new List<double>();
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var YList = new List<double>();
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var HeightList = new List<double>();
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var WidthList = new List<double>();
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var OuterContourList = new List<List<Point>>();
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rsp.LabelMap = null;
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// 使用 RegionInfo 信息可视化
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foreach (var info in rsp.RegionInfos)
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{
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var r_area = info.Area;
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var r_label = info.Label;
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var r_shortSide = info.ShortSide;
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var r_longSide = info.LongSide;
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var r_Id = info.Id;
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var r_MeanScore = info.MeanScore;
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var bbox = info.BoundingRect;
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// 提取轮廓
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var contours = new List<List<Point>> { info.OuterContour.Select(x => new Point(x.X, x.Y)).ToList() };
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List<Point> contour = info.OuterContour.Select(x => new Point((int)x.X, (int)x.Y)).ToList(); // 浮点→整数
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if (r_area >= AreaThresholds[r_label] && r_longSide >= LongSideThresholds[r_label] && r_shortSide >= ShortSideThresholds[r_label] /*&& r_MeanScore >= ClassesScoreThresholds[r_label]*/)
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{
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AreaList.Add(r_area);
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ClassIDList.Add(r_Id);
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LongSideList.Add(r_longSide);
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ShortSideList.Add(r_shortSide);
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MeanScoreList.Add(r_MeanScore);
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LabelsList.Add(r_label);
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XList.Add(bbox.X);
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YList.Add(bbox.Y);
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HeightList.Add(bbox.Height);
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WidthList.Add(bbox.Width);
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OuterContourList.Add(contour);
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// 获取类别颜色（自动循环使用预定义颜色）
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int colorIndex = info.Id % classColors.Count;
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var color = classColors[colorIndex];
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//Cv2.DrawContours(image, contours, -1, color, 2);
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//Cv2.PutText(image, $"{info.Label}, area = {info.Area}", new Point(bbox.X, bbox.Y), HersheyFonts.HersheySimplex, 1, color, 2);
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if (contour == null || contour.Count == 0)
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{
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throw new ArgumentException("轮廓点集合不能为空或无数据");
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}
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HTuple rowTuple = new HTuple(); // Halcon中row对应Y坐标
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HTuple colTuple = new HTuple(); // Halcon中column对应X坐标
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foreach (Point p in contour)
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{
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rowTuple.Append(p.Y);
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colTuple.Append(p.X);
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}
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HOperatorSet.GenContourPolygonXld(out HObject contour1, rowTuple, colTuple);
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((ObjectRecord)Record).AddXld(contour1);
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}
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}
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Count = AreaList.Count();
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if (Count > 0)
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{
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Msg = "检测到缺陷，NG：" + Count;
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Result = false;
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}
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else
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{
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Msg = "运行成功";
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Result = true;
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}
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Params.Outputs["Count"] = Count;
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Params.Outputs["ClassID"] = ClassIDList;
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Params.Outputs["Area"] = AreaList;
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Params.Outputs["LongSideList"] = LongSideList;
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Params.Outputs["ShortSideList"] = ShortSideList;
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Params.Outputs["MeanScore"] = MeanScoreList;
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Params.Outputs["X"] = XList;
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Params.Outputs["Y"] = YList;
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Params.Outputs["Height"] = HeightList;
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Params.Outputs["Width"] = WidthList;
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Params.Outputs["OuterContours"] = OuterContourList;
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}
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private void VisualizeSegmentationResult(SegmentationResponse rsp, Dictionary<string, double> AreaThresholds, Dictionary<string, double> LongSideThresholds, Dictionary<string, double> ShortSideThresholds, Dictionary<string, double> ClassesScoreThresholds)
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{
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// 预定义类别颜色映射表（支持最多20个类别）
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var classColors = new List<Scalar>
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{
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new Scalar(0, 0, 255), // 0: 红色
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new Scalar(0, 255, 0), // 1: 绿色
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new Scalar(255, 0, 0), // 2: 蓝色
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new Scalar(255, 255, 0), // 3: 青色
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new Scalar(255, 0, 255), // 4: 品红
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new Scalar(0, 255, 255), // 5: 黄色
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new Scalar(128, 0, 0), // 6: 深红
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new Scalar(0, 128, 0), // 7: 深绿
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new Scalar(0, 0, 128), // 8: 深蓝
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new Scalar(128, 128, 0), // 9: 橄榄色
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new Scalar(128, 0, 128), // 10: 紫色
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new Scalar(0, 128, 128), // 11: 靛蓝
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new Scalar(255, 165, 0), // 12: 橙色
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new Scalar(255, 192, 203),// 13: 粉红色
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new Scalar(147, 112, 219),// 14: 紫罗兰
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new Scalar(255, 99, 71), // 15: 番茄红
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new Scalar(255, 20, 147), // 16: 紫色
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new Scalar(30, 144, 255), // 17: 道奇蓝
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new Scalar(255, 69, 0), // 18: 橙红色
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new Scalar(0, 206, 209) // 19: 碧绿色
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};
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Record = new ObjectRecord();
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int Count = 0;
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var ClassIDList = new List<int>();
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var LabelsList = new List<string>();
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var AreaList = new List<double>();
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var LongSideList = new List<double>();
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var ShortSideList = new List<double>();
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var MeanScoreList = new List<double>();
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var XList = new List<double>();
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var YList = new List<double>();
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var HeightList = new List<double>();
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var WidthList = new List<double>();
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var OuterContourList = new List<List<Point>>();
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rsp.LabelMap = null;
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// 使用 RegionInfo 信息可视化
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foreach (var info in rsp.RegionInfos)
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{
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var r_area = info.Area;
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var r_label = info.Label;
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var r_shortSide = info.ShortSide;
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var r_longSide = info.LongSide;
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var r_Id = info.Id;
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var r_MeanScore = info.MeanScore;
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var bbox = info.BoundingRect;
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// 提取轮廓
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var contours = new List<List<Point>> { info.OuterContour.Select(x => new Point(x.X, x.Y)).ToList() };
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List<Point> contour = info.OuterContour.Select(x => new Point((int)x.X, (int)x.Y)).ToList(); // 浮点→整数
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if (r_area >= AreaThresholds[r_label] && r_longSide >= LongSideThresholds[r_label] && r_shortSide >= ShortSideThresholds[r_label] /*&& r_MeanScore >= ClassesScoreThresholds[r_label]*/)
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{
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AreaList.Add(r_area);
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ClassIDList.Add(r_Id);
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LongSideList.Add(r_longSide);
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ShortSideList.Add(r_shortSide);
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MeanScoreList.Add(r_MeanScore);
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LabelsList.Add(r_label);
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XList.Add(bbox.X);
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YList.Add(bbox.Y);
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HeightList.Add(bbox.Height);
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WidthList.Add(bbox.Width);
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OuterContourList.Add(contour);
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// 获取类别颜色（自动循环使用预定义颜色）
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int colorIndex = info.Id % classColors.Count;
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var color = classColors[colorIndex];
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//Cv2.DrawContours(image, contours, -1, color, 2);
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//Cv2.PutText(image, $"{info.Label}, area = {info.Area}", new Point(bbox.X, bbox.Y), HersheyFonts.HersheySimplex, 1, color, 2);
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if (contour == null || contour.Count == 0)
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{
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throw new ArgumentException("轮廓点集合不能为空或无数据");
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}
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HTuple rowTuple = new HTuple(); // Halcon中row对应Y坐标
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HTuple colTuple = new HTuple(); // Halcon中column对应X坐标
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foreach (Point p in contour)
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{
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rowTuple.Append(p.Y);
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colTuple.Append(p.X);
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}
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HOperatorSet.GenContourPolygonXld(out HObject contour1, rowTuple, colTuple);
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((ObjectRecord)Record).AddXld(contour1);
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}
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}
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Count = AreaList.Count();
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if (Count > 0)
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{
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Msg = "检测到缺陷，NG：" + Count;
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Result = false;
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}
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else
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{
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Msg = "运行成功";
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Result = true;
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}
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Params.Outputs["Count"] = Count;
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Params.Outputs["ClassID"] = ClassIDList;
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Params.Outputs["Area"] = AreaList;
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Params.Outputs["LongSideList"] = LongSideList;
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Params.Outputs["ShortSideList"] = ShortSideList;
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Params.Outputs["MeanScore"] = MeanScoreList;
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Params.Outputs["X"] = XList;
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Params.Outputs["Y"] = YList;
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Params.Outputs["Height"] = HeightList;
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Params.Outputs["Width"] = WidthList;
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Params.Outputs["OuterContours"] = OuterContourList;
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}
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public override bool Run()
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{
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DateTime StartTime = DateTime.Now;
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InitRunParams();
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HOperatorSet.GenEmptyObj(out HObject EmptyObj);
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OutputImage = EmptyObj;
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// 创建并启动任务
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TAlgorithmMain();
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RunTime = (DateTime.Now - StartTime).TotalMilliseconds;
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return Result;
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}
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/// <summary>
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/// 算子逻辑
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/// </summary>
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public override void TAlgorithmMain()
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{
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//InitRunParams();
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#region 初始化变量
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HObject ho_Regions, ho_ConnectedRegions;
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HOperatorSet.GenEmptyObj(out ho_Regions);
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HOperatorSet.GenEmptyObj(out ho_ConnectedRegions);
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#endregion
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try
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{
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if (InputImage == null)
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{
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Msg = "输入图片为空";
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Result = false;
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return;
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}
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if (!(InputImage is Mat))
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{
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Msg = "输入图片格式不为Mat";
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Result = false;
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return;
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}
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#region 裁剪区域
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object DomainImage = null;
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if (!ReduceDomainImage(InputImage, ref DomainImage))
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{
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Msg = "裁剪区域失败";
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Result = false;
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return;
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}
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Mat hoDomainImage = DomainImage as Mat;
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#endregion
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if (module == null)
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{
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LoadModel();
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Debug.WriteLine("运行逻辑加载模型");
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}
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#region 算子逻辑
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//var ModelPath = ProcessParams.ConvertToString(Params.Inputs["ModelPath"]);
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//var ModuleId = ProcessParams.ConvertToString(Params.Inputs["ModuleId"]);
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//var UseGpu = Convert.ToBoolean(Params.Inputs["UseGpu"]);
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//var DeviceId = Convert.ToInt32(Params.Inputs["DeviceId"]);
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//var BatchSize = Convert.ToInt32(Params.Inputs["BatchSize"]);
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//Dictionary<string, double> AreaThresholds = Params.Inputs["AreaThresholds"] as Dictionary<string, double> ?? new Dictionary<string, double>();
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//Dictionary<string, double> LongSideThresholds = Params.Inputs["LongSideThresholds"] as Dictionary<string, double> ?? new Dictionary<string, double>();
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//Dictionary<string, double> ShortSideThresholds = Params.Inputs["ShortSideThresholds"] as Dictionary<string, double> ?? new Dictionary<string, double>();
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//Dictionary<string, double> ClassesScoreThresholds = Params.Inputs["ClassesScoreThresholds"] as Dictionary<string, double> ?? new Dictionary<string, double>();
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Dictionary<string, double> AreaThresholds = null;
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Dictionary<string, double> LongSideThresholds = null;
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Dictionary<string, double> ShortSideThresholds = null;
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Dictionary<string, double> ClassesScoreThresholds = null;
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// 获取SegmentTool中的阈值字典
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var areaThresholdsObj = Params.Inputs["AreaThresholds"];
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if (areaThresholdsObj is JObject jObject)
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{
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// 最终转换为目标字典类型
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AreaThresholds = jObject.ToObject<Dictionary<string, double>>();
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}
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else if (areaThresholdsObj is Object)
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{
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AreaThresholds = areaThresholdsObj as Dictionary<string, double>;
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if (AreaThresholds == null)
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{
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AreaThresholds = new Dictionary<string, double>();
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foreach (var kvp in areaThresholdsObj as Dictionary<string, object>)
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{
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try
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{
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// 尝试将object转为double
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double value = Convert.ToDouble(kvp.Value);
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AreaThresholds.Add(kvp.Key, value);
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}
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catch (Exception ex)
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{
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// 处理转换失败的情况（可选，比如打印日志、抛自定义异常）
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Debug.WriteLine($"转换键 {kvp.Key} 失败：{ex.Message}");
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}
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}
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}
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}
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else
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{
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//// 处理类型不符的异常情况（可选，增强健壮性）
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//throw new System.Exception("AreaThresholds的实际类型不是JObject，转换失败");
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AreaThresholds = new Dictionary<string, double>();
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}
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var longSideThresholdsObj = Params.Inputs["LongSideThresholds"];
|
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if (longSideThresholdsObj is JObject jObjectL)
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{
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// 最终转换为目标字典类型
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LongSideThresholds = jObjectL.ToObject<Dictionary<string, double>>();
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}
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else if (longSideThresholdsObj is Object)
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{
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LongSideThresholds = longSideThresholdsObj as Dictionary<string, double>;
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if (LongSideThresholds == null)
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{
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LongSideThresholds = new Dictionary<string, double>();
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foreach (var kvp in longSideThresholdsObj as Dictionary<string, object>)
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{
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try
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{
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// 尝试将object转为double
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double value = Convert.ToDouble(kvp.Value);
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LongSideThresholds.Add(kvp.Key, value);
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}
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catch (Exception ex)
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{
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// 处理转换失败的情况（可选，比如打印日志、抛自定义异常）
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Debug.WriteLine($"转换键 {kvp.Key} 失败：{ex.Message}");
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}
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}
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}
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}
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else
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{
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//// 处理类型不符的异常情况（可选，增强健壮性）
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//throw new System.Exception("LongSideThresholds的实际类型不是JObject，转换失败");
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LongSideThresholds = new Dictionary<string, double>();
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}
|
|
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var shortSideThresholdsObj = Params.Inputs["ShortSideThresholds"];
|
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if (shortSideThresholdsObj is JObject jObjectS)
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{
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// 最终转换为目标字典类型
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ShortSideThresholds = jObjectS.ToObject<Dictionary<string, double>>();
|
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}
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else if (shortSideThresholdsObj is Object)
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{
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ShortSideThresholds = shortSideThresholdsObj as Dictionary<string, double>;
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if (ShortSideThresholds == null)
|
{
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ShortSideThresholds = new Dictionary<string, double>();
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foreach (var kvp in shortSideThresholdsObj as Dictionary<string, object>)
|
{
|
try
|
{
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// 尝试将object转为double
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double value = Convert.ToDouble(kvp.Value);
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ShortSideThresholds.Add(kvp.Key, value);
|
}
|
catch (Exception ex)
|
{
|
// 处理转换失败的情况（可选，比如打印日志、抛自定义异常）
|
Debug.WriteLine($"转换键 {kvp.Key} 失败：{ex.Message}");
|
}
|
}
|
}
|
}
|
else
|
{
|
//// 处理类型不符的异常情况（可选，增强健壮性）
|
//throw new System.Exception("shortSideThresholds的实际类型不是JObject，转换失败");
|
ShortSideThresholds = new Dictionary<string, double>();
|
}
|
|
var classesScoreThresholdsObj = Params.Inputs["ClassesScoreThresholds"];
|
|
if (classesScoreThresholdsObj is JObject jObjectC)
|
{
|
// 最终转换为目标字典类型
|
ClassesScoreThresholds = jObjectC.ToObject<Dictionary<string, double>>();
|
|
}
|
else if (classesScoreThresholdsObj is Object)
|
{
|
ClassesScoreThresholds = classesScoreThresholdsObj as Dictionary<string, double>;
|
if (ClassesScoreThresholds == null)
|
{
|
ClassesScoreThresholds = new Dictionary<string, double>();
|
foreach (var kvp in classesScoreThresholdsObj as Dictionary<string, object>)
|
{
|
try
|
{
|
// 尝试将object转为double
|
double value = Convert.ToDouble(kvp.Value);
|
ClassesScoreThresholds.Add(kvp.Key, value);
|
}
|
catch (Exception ex)
|
{
|
// 处理转换失败的情况（可选，比如打印日志、抛自定义异常）
|
Debug.WriteLine($"转换键 {kvp.Key} 失败：{ex.Message}");
|
}
|
}
|
}
|
}
|
else
|
{
|
//// 处理类型不符的异常情况（可选，增强健壮性）
|
//throw new System.Exception("classesScoreThresholds的实际类型不是JObject，转换失败");
|
ClassesScoreThresholds = new Dictionary<string, double>();
|
}
|
|
//判断和加载模型
|
try
|
{
|
//// create an empty solution
|
//{
|
// AsyncLogHelper.Info($"load solution from: {Params.Inputs["MinThreshold"]}");
|
// solution.LoadFromFile(modelPath); // load solution from model.vimosln
|
|
// AsyncLogHelper.Info($"create Module: {modelID}, use gpu: {isUseGPU}, device id: {deviceGPUID}");
|
// module = solution.CreateModule<ISegmentationModule>(modelID, isUseGPU, deviceGPUID, batchSize); // create module
|
// {
|
|
// var segParams = module.Params; // 读取模型参数
|
// segParams.WithMask = false; // 可选，关闭 mask 输出
|
// segParams.WithRegionInfo = true; // 开启 RegionInfo 输出，以便可视化
|
// segParams.RegionInfoFlag = SegRegionInfoFlag.Area
|
// | SegRegionInfoFlag.InnerContours
|
// | SegRegionInfoFlag.OuterContour
|
// | SegRegionInfoFlag.LongSide
|
// | SegRegionInfoFlag.ShortSide;
|
|
// module.Params = segParams; // 设置模型参数
|
|
|
// AsyncLogHelper.Info($"create request from image: " + "imagePath");
|
|
// using (Mat visImage = hoDomainImage.Clone()) // clone request image for visualize
|
// {
|
// var req = new Request(hoDomainImage); // create request from image
|
|
// AsyncLogHelper.Info("run pipelines");
|
// module.Run(req, out SegmentationResponse rsp);
|
// AsyncLogHelper.Info("inference done");
|
|
// AsyncLogHelper.Info("do visualize");
|
|
// VisualizeSegmentationResult(rsp, visImage, AreaThresholds, LongSideThresholds, ShortSideThresholds, ClassesScoreThresholds); // visualize
|
// OutputImage = visImage;
|
// //Console.WriteLine("save vis image to: vis_image.png");
|
// //Cv2.ImWrite("vis_image.png", visImage); // save visualize image
|
// //Console.WriteLine("save vis image done");
|
// }
|
// }
|
//}
|
|
//using (Mat visImage = hoDomainImage.Clone()) // clone request image for visualize
|
//{
|
// Request req = new Request(hoDomainImage); // create request from image
|
|
// AsyncLogHelper.Info("run pipelines");
|
// module.Run(req, out SegmentationResponse rsp);
|
// AsyncLogHelper.Info("inference done");
|
|
// AsyncLogHelper.Info("do visualize");
|
|
// //VisualizeSegmentationResult(rsp, visImage, AreaThresholds, LongSideThresholds, ShortSideThresholds, ClassesScoreThresholds); // visualize
|
// VisualizeSegmentationResult(rsp, AreaThresholds, LongSideThresholds, ShortSideThresholds, ClassesScoreThresholds); // visualize
|
// OutputImage = DomainImage;
|
// //Console.WriteLine("save vis image to: vis_image.png");
|
// //Cv2.ImWrite("vis_image.png", visImage); // save visualize image
|
// //Console.WriteLine("save vis image done");
|
//}
|
|
Request req = new Request(hoDomainImage); // create request from image
|
|
AsyncLogHelper.Info("run pipelines");
|
module.Run(req, out SegmentationResponse rsp);
|
AsyncLogHelper.Info("inference done");
|
|
AsyncLogHelper.Info("do visualize");
|
|
//VisualizeSegmentationResult(rsp, visImage, AreaThresholds, LongSideThresholds, ShortSideThresholds, ClassesScoreThresholds); // visualize
|
VisualizeSegmentationResult(rsp, AreaThresholds, LongSideThresholds, ShortSideThresholds, ClassesScoreThresholds); // visualize
|
OutputImage = DomainImage;
|
//hoDomainImage.Dispose();
|
}
|
catch (Exception ex)
|
{
|
Msg = "生成OutputImage失败,原因是:" + ex.ToString();
|
Result = false;
|
return;
|
}
|
|
#endregion
|
|
//Msg = "运行成功";
|
//Result = true;
|
return;
|
}
|
catch (Exception ex)
|
{
|
Msg = "运行失败,原因是:" + ex.ToString().TrimEnd();
|
OutputImage = null;
|
Result = false;
|
return;
|
}
|
finally
|
{
|
bCompleted = true;
|
#region 内存释放
|
ho_Regions.Dispose();
|
ho_ConnectedRegions.Dispose();
|
#endregion
|
}
|
}
|
|
public override bool Save(string filePath = "")
|
{
|
return base.Save(filePath);
|
}
|
|
public override bool Load(string fullPath = "")
|
{
|
if (base.Load(fullPath))
|
{
|
return LoadModel();
|
}
|
else
|
{
|
return false;
|
}
|
}
|
|
public bool LoadModel(string fullPath = "")
|
{
|
if (!string.IsNullOrEmpty(fullPath) && fullPath.Trim() != "")
|
{
|
this.modelPath = fullPath;
|
Params.Inputs.Add("ModelPath", fullPath);
|
}
|
SegFeatures.Clear();
|
this.modelID = Params.Inputs["ModuleId"]?.ToString();//(JArray.FromObject(Params.Inputs["标签"]))?.ToObject<List<string>>();
|
this.isUseGPU = Convert.ToBoolean(Params.Inputs["UseGpu"]?.ToString());
|
this.deviceGPUID = Convert.ToInt32(Params.Inputs["DeviceId"]?.ToString());
|
this.batchSize = Convert.ToInt32(Params.Inputs["BatchSize"]?.ToString());
|
this.modelPath = Params.Inputs["ModelPath"]?.ToString();
|
if (System.IO.File.Exists(modelPath))
|
{
|
try
|
{
|
if (module != null)
|
{
|
module.Dispose();
|
module = null;
|
}
|
if (solution != null)
|
{
|
solution.Dispose();
|
solution = null;
|
}
|
|
if (solution == null)
|
{
|
solution = new Solution();
|
AsyncLogHelper.Info($"load solution from: {Params.Inputs["ModelPath"]}");
|
solution.LoadFromFile(modelPath); // load solution from model.vimosln
|
}
|
else
|
{
|
solution.Dispose();
|
AsyncLogHelper.Info($"load solution from: {Params.Inputs["ModelPath"]}");
|
solution.LoadFromFile(modelPath); // load solution from model.vimosln
|
}
|
if (module == null)
|
{
|
AsyncLogHelper.Info($"create Module: {modelID}, use gpu: {isUseGPU}, device id: {deviceGPUID}");
|
module = solution.CreateModule<ISegmentationModule>(modelID, isUseGPU, deviceGPUID, batchSize); // create module
|
}
|
else
|
{
|
module.Dispose();
|
AsyncLogHelper.Info($"create Module: {modelID}, use gpu: {isUseGPU}, device id: {deviceGPUID}");
|
module = solution.CreateModule<ISegmentationModule>(modelID, isUseGPU, deviceGPUID, batchSize); // create module
|
}
|
segParams = module.Params; // 读取模型参数
|
segParams.WithMask = false; // 可选，关闭 mask 输出
|
segParams.WithRegionInfo = true; // 开启 RegionInfo 输出，以便可视化
|
segParams.RegionInfoFlag = SegRegionInfoFlag.Area
|
| SegRegionInfoFlag.InnerContours
|
| SegRegionInfoFlag.OuterContour
|
| SegRegionInfoFlag.LongSide
|
| SegRegionInfoFlag.ShortSide;
|
|
module.Params = segParams; // 设置模型参数
|
foreach (var item in solution.ModuleInfoList)
|
{
|
foreach (var item1 in item.Features.ToList())
|
{
|
SegFeatures.Add(item1);
|
}
|
}
|
// 加载模型后先运行下空图片进行缓存 下次运行时提速[无效]
|
//image_predict(new Mat(1920, 1080, MatType.CV_16UC3));
|
}
|
catch (Exception ex)
|
{
|
Msg = $"创建分割模型接口失败，请检查参数，{ex.Message}";
|
return false;
|
}
|
}
|
else
|
{
|
Msg = "模型路径不存在";
|
return false;
|
}
|
return true;
|
}
|
|
}
|
|
}
|
