上传视觉检测模块
This commit is contained in:
parent
af2e65dd58
commit
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<TargetFramework>net8.0</TargetFramework>
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<TargetFramework>net8.0</TargetFramework>
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<ImplicitUsings>enable</ImplicitUsings>
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<ImplicitUsings>enable</ImplicitUsings>
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<Nullable>enable</Nullable>
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<Nullable>enable</Nullable>
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<Platforms>AnyCPU;X64</Platforms>
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<Platforms>AnyCPU;x64</Platforms>
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</PropertyGroup>
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</PropertyGroup>
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</Project>
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</Project>
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@ -19,7 +19,7 @@
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<ItemGroup>
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<ItemGroup>
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<Reference Include="DVPCameraCS64">
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<Reference Include="DVPCameraCS64">
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<HintPath>..\X64\Debug\DVPCameraCS64.dll</HintPath>
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<HintPath>..\x64\Debug\DVPCameraCS64.dll</HintPath>
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</Reference>
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</Reference>
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</ItemGroup>
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</ItemGroup>
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@ -22,7 +22,7 @@
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<ItemGroup>
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<ItemGroup>
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<Reference Include="HslCommunication">
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<Reference Include="HslCommunication">
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<HintPath>..\X64\Debug\HslCommunication.dll</HintPath>
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<HintPath>..\x64\Debug\HslCommunication.dll</HintPath>
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</Reference>
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</Reference>
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</ItemGroup>
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</ItemGroup>
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@ -11,6 +11,9 @@
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<Platforms>AnyCPU;x64</Platforms>
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<Platforms>AnyCPU;x64</Platforms>
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</PropertyGroup>
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</PropertyGroup>
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<ItemGroup>
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<ItemGroup>
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<PackageReference Include="Newtonsoft.Json" Version="13.0.3" />
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<PackageReference Include="Newtonsoft.Json" Version="13.0.3" />
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<PackageReference Include="OpenCvSharp4" Version="4.10.0.20241108" />
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<PackageReference Include="OpenCvSharp4" Version="4.10.0.20241108" />
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666
DH.Devices.Vision/DetectionConfig.cs
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666
DH.Devices.Vision/DetectionConfig.cs
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using OpenCvSharp;
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using System.ComponentModel;
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using System.Drawing;
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using static OpenCvSharp.AgastFeatureDetector;
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using System.Text.RegularExpressions;
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using System.Text;
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using System.Drawing.Design;
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namespace DH.Devices.Vision
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{
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public enum MLModelType
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{
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[Description("图像分类")]
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ImageClassification = 1,
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[Description("目标检测")]
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ObjectDetection = 2,
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//[Description("图像分割")]
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//ImageSegmentation = 3
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[Description("语义分割")]
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SemanticSegmentation = 3,
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[Description("实例分割")]
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InstanceSegmentation = 4,
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[Description("目标检测GPU")]
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ObjectGPUDetection = 5
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}
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public class ModelLabel
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{
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public string LabelId { get; set; }
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[Category("模型标签")]
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[DisplayName("模型标签索引")]
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[Description("模型识别的标签索引")]
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public int LabelIndex { get; set; }
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[Category("模型标签")]
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[DisplayName("模型标签")]
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[Description("模型识别的标签名称")]
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public string LabelName { get; set; }
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//[Category("模型配置")]
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//[DisplayName("模型参数配置")]
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//[Description("模型参数配置集合")]
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//public ModelParamSetting ModelParamSetting { get; set; } = new ModelParamSetting();
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public string GetDisplayText()
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{
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return $"{LabelId}-{LabelName}";
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}
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}
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public class MLRequest
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{
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public int ImageChannels = 3;
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public Mat mImage;
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public int ResizeWidth;
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public int ResizeHeight;
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public float confThreshold;
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public float iouThreshold;
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//public int ImageResizeCount;
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public bool IsCLDetection;
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public int ProCount;
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public string in_node_name;
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public string out_node_name;
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public string in_lable_path;
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public int ResizeImageSize;
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public int segmentWidth;
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public int ImageWidth;
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// public List<labelStringBase> OkClassTxtList;
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public List<ModelLabel> LabelNames;
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}
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public enum ResultState
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{
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[Description("检测NG")]
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DetectNG = -3,
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//[Description("检测不足TBD")]
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// ShortageTBD = -2,
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[Description("检测结果TBD")]
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ResultTBD = -1,
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[Description("OK")]
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OK = 1,
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// [Description("NG")]
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// NG = 2,
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//统计结果
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[Description("A类NG")]
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A_NG = 25,
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[Description("B类NG")]
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B_NG = 26,
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[Description("C类NG")]
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C_NG = 27,
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}
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/// <summary>
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/// 深度学习 识别结果明细 面向业务：detect 面向深度学习：Recongnition、Inference
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/// </summary>
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public class DetectionResultDetail
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{
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public string LabelBGR { get; set; }//识别到对象的标签BGR
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public int LabelNo { get; set; } // 识别到对象的标签索引
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public string LabelName { get; set; }//识别到对象的标签名称
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public double Score { get; set; }//识别目标结果的可能性、得分
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public string LabelDisplay { get; set; }//识别到对象的 显示信息
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public double Area { get; set; }//识别目标的区域面积
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public Rectangle Rect { get; set; }//识别目标的外接矩形
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public RotatedRect MinRect { get; set; }//识别目标的最小外接矩形(带角度)
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public ResultState InferenceResult { get; set; }//只是模型推理 label的结果
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public double DistanceToImageCenter { get; set; } //计算矩形框到图像中心的距离
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public ResultState FinalResult { get; set; }//模型推理+其他视觉、逻辑判断后 label结果
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}
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public class MLResult
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{
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public bool IsSuccess = false;
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public string ResultMessage;
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public Bitmap ResultMap;
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public List<DetectionResultDetail> ResultDetails = new List<DetectionResultDetail>();
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}
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public class MLInit
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{
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public string ModelFile;
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public string InferenceDevice;
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public int InferenceWidth;
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public int InferenceHeight;
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public string InputNodeName;
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public int SizeModel;
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public bool bReverse;//尺寸测量正反面
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//目标检测Gpu
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public bool IsGPU;
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public int GPUId;
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public float Score_thre;
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public MLInit(string modelFile, bool isGPU, int gpuId, float score_thre)
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{
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ModelFile = modelFile;
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IsGPU = isGPU;
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GPUId = gpuId;
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Score_thre = score_thre;
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}
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public MLInit(string modelFile, string inputNodeName, string inferenceDevice, int inferenceWidth, int inferenceHeight)
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{
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ModelFile = modelFile;
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InferenceDevice = inferenceDevice;
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InferenceWidth = inferenceWidth;
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InferenceHeight = inferenceHeight;
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InputNodeName = inputNodeName;
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}
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}
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public class DetectStationResult
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{
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public string Pid { get; set; }
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public string TempPid { get; set; }
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/// <summary>
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/// 检测工位名称
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/// </summary>
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public string DetectName { get; set; }
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/// <summary>
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/// 深度学习 检测结果
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/// </summary>
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public List<DetectionResultDetail> DetectDetails = new List<DetectionResultDetail>();
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/// <summary>
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/// 工位检测结果
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/// </summary>
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public ResultState ResultState { get; set; } = ResultState.ResultTBD;
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public double FinalResultfScore { get; set; } = 0.0;
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public string ResultLabel { get; set; } = "";// 多个ng时，根据label优先级，设定当前检测项的label
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public string ResultLabelCategoryId { get; set; } = "";// 多个ng时，根据label优先级，设定当前检测项的label
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public int PreTreatState { get; set; }
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public bool IsPreTreatDone { get; set; } = true;
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public bool IsAfterTreatDone { get; set; } = true;
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public bool IsMLDetectDone { get; set; } = true;
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/// <summary>
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/// 预处理阶段已经NG
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/// </summary>
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public bool IsPreTreatNG { get; set; } = false;
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/// <summary>
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/// 目标检测NG
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/// </summary>
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public bool IsObjectDetectNG { get; set; } = false;
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public DateTime EndTime { get; set; }
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public int StationDetectElapsed { get; set; }
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public static string NormalizeAndClean(string input)
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{
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if (input == null) return null;
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// Step 1: 标准化字符编码为 Form C (规范组合)
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string normalizedString = input.Normalize(NormalizationForm.FormC);
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// Step 2: 移除所有空白字符，包括制表符和换行符
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string withoutWhitespace = Regex.Replace(normalizedString, @"\s+", "");
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// Step 3: 移除控制字符 (Unicode 控制字符，范围 \u0000 - \u001F 和 \u007F)
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string withoutControlChars = Regex.Replace(withoutWhitespace, @"[\u0000-\u001F\u007F]+", "");
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// Step 4: 移除特殊的不可见字符（如零宽度空格等）
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string cleanedString = Regex.Replace(withoutControlChars, @"[\u200B\u200C\u200D\uFEFF]+", "");
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return cleanedString;
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}
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}
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public class RelatedCamera
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{
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[Category("关联相机")]
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[DisplayName("关联相机")]
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[Description("关联相机描述")]
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//[TypeConverter(typeof(CollectionCountConvert))]
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public string CameraSourceId { get; set; } = "";
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public RelatedCamera()
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{
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}
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public RelatedCamera(string cameraSourceId)
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{
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CameraSourceId = cameraSourceId;
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}
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}
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public class DetectionConfig
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{
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[ReadOnly(true)]
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public string Id { get; set; } = Guid.NewGuid().ToString();
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[Category("检测配置")]
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[DisplayName("检测配置名称")]
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[Description("检测配置名称")]
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public string Name { get; set; }
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[Category("关联相机")]
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[DisplayName("关联相机")]
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[Description("关联相机描述")]
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public string CameraSourceId { get; set; } = "";
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[Category("关联相机集合")]
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[DisplayName("关联相机集合")]
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[Description("关联相机描述")]
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//[TypeConverter(typeof(DeviceIdSelectorConverter<CameraBase>))]
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public List<RelatedCamera> CameraCollects { get; set; } = new List<RelatedCamera>();
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[Category("启用配置")]
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[DisplayName("是否启用GPU检测")]
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[Description("是否启用GPU检测")]
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public bool IsEnableGPU { get; set; } = false;
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[Category("启用配置")]
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[DisplayName("是否混料模型")]
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[Description("是否混料模型")]
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public bool IsMixModel { get; set; } = false;
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[Category("启用配置")]
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[DisplayName("是否启用该检测")]
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[Description("是否启用该检测")]
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public bool IsEnabled { get; set; }
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[Category("启用配置")]
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[DisplayName("是否加入检测工位")]
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[Description("是否加入检测工位")]
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public bool IsAddStation { get; set; } = true;
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型类型")]
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[Description("模型类型：ImageClassification-图片分类；ObjectDetection：目标检测；Segmentation-图像分割")]
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//[TypeConverter(typeof(EnumDescriptionConverter<MLModelType>))]
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public MLModelType ModelType { get; set; } = MLModelType.ObjectDetection;
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//[Category("2.中检测（深度学习）")]
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//[DisplayName("中检测-GPU索引")]
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//[Description("GPU索引")]
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//public int GPUIndex { get; set; } = 0;
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型文件路径")]
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[Description("中处理 深度学习模型文件路径，路径中不可含有中文字符，一般情况可以只配置中检测模型，当需要先用预检测过滤一次时，请先配置好与预检测相关配置")]
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public string ModelPath { get; set; }
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型宽度")]
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[Description("中处理-模型宽度")]
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public int ModelWidth { get; set; } = 640;
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型高度")]
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[Description("中处理-模型高度")]
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|
||||||
|
public int ModelHeight { get; set; } = 640;
|
||||||
|
|
||||||
|
[Category("2.中检测（深度学习）")]
|
||||||
|
[DisplayName("中检测-模型节点名称")]
|
||||||
|
[Description("中处理-模型节点名称")]
|
||||||
|
|
||||||
|
public string ModeloutNodeName { get; set; } = "output0";
|
||||||
|
|
||||||
|
[Category("2.中检测（深度学习）")]
|
||||||
|
[DisplayName("中检测-模型置信度")]
|
||||||
|
[Description("中处理-模型置信度")]
|
||||||
|
|
||||||
|
public float ModelconfThreshold { get; set; } = 0.5f;
|
||||||
|
|
||||||
|
[Category("2.中检测（深度学习）")]
|
||||||
|
[DisplayName("中检测-模型标签路径")]
|
||||||
|
[Description("中处理-模型标签路径")]
|
||||||
|
|
||||||
|
public string in_lable_path { get; set; }
|
||||||
|
|
||||||
|
[Category("4.最终过滤（逻辑过滤）")]
|
||||||
|
[DisplayName("过滤器集合")]
|
||||||
|
[Description("最后的逻辑过滤：可根据 识别出对象的 宽度、高度、面积、得分来设置最终检测结果，同一识别目标同一判定，多项过滤器之间为“或”关系")]
|
||||||
|
|
||||||
|
public List<DetectionFilter> DetectionFilterList { get; set; } = new List<DetectionFilter>();
|
||||||
|
|
||||||
|
//[Category("深度学习配置")]
|
||||||
|
//[DisplayName("检测配置标签")]
|
||||||
|
//[Description("检测配置标签关联")]
|
||||||
|
|
||||||
|
//public List<DetectConfigLabel> DetectConfigLabelList { get; set; } = new List<DetectConfigLabel>();
|
||||||
|
|
||||||
|
|
||||||
|
public DetectionConfig()
|
||||||
|
{
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
public DetectionConfig(string name, MLModelType modelType, string modelPath, bool isEnableGPU,string sCameraSourceId)
|
||||||
|
{
|
||||||
|
ModelPath = modelPath ?? string.Empty;
|
||||||
|
Name = name;
|
||||||
|
ModelType = modelType;
|
||||||
|
IsEnableGPU = isEnableGPU;
|
||||||
|
Id = Guid.NewGuid().ToString();
|
||||||
|
CameraSourceId = sCameraSourceId;
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
|
/// <summary>
|
||||||
|
/// 识别目标定义 class：分类信息 Detection Segmentation：要识别的对象
|
||||||
|
/// </summary>
|
||||||
|
public class RecongnitionLabel //: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("检测标签定义")]
|
||||||
|
[Description("检测标签编码")]
|
||||||
|
[ReadOnly(true)]
|
||||||
|
public string Id { get; set; } = Guid.NewGuid().ToString();
|
||||||
|
|
||||||
|
[Category("检测标签定义")]
|
||||||
|
[DisplayName("检测标签名称")]
|
||||||
|
[Description("检测标签名称")]
|
||||||
|
public string LabelName { get; set; } = "";
|
||||||
|
|
||||||
|
[Category("检测标签定义")]
|
||||||
|
[DisplayName("检测标签描述")]
|
||||||
|
[Description("检测标签描述，中文描述")]
|
||||||
|
public string LabelDescription { get; set; } = "";
|
||||||
|
|
||||||
|
[Category("检测标签定义")]
|
||||||
|
[DisplayName("检测标签分类")]
|
||||||
|
[Description("检测标签分类id")]
|
||||||
|
//[TypeConverter(typeof(LabelCategoryConverter))]
|
||||||
|
public string LabelCategory { get; set; } = "";
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
/// <summary>
|
||||||
|
/// 检测项识别对象
|
||||||
|
/// </summary>
|
||||||
|
public class DetectConfigLabel //: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("检测项标签")]
|
||||||
|
[DisplayName("检测项标签")]
|
||||||
|
[Description("检测标签Id")]
|
||||||
|
//[TypeConverter(typeof(DetectionLabelConverter))]
|
||||||
|
public string LabelId { get; set; }
|
||||||
|
|
||||||
|
[Browsable(false)]
|
||||||
|
//public string LabelName { get => GetLabelName(); }
|
||||||
|
|
||||||
|
[Category("检测项标签")]
|
||||||
|
[DisplayName("检测标签优先级")]
|
||||||
|
[Description("检测标签优先级，值越小，优先级越高")]
|
||||||
|
public int LabelPriority { get; set; } = 0;
|
||||||
|
|
||||||
|
//[Category("检测项标签")]
|
||||||
|
//[DisplayName("标签BGR值")]
|
||||||
|
//[Description("检测标签BGR值，例如：0,128,0")]
|
||||||
|
//public string LabelBGR { get; set; }
|
||||||
|
|
||||||
|
//[Category("模型配置")]
|
||||||
|
//[DisplayName("模型参数配置")]
|
||||||
|
//[Description("模型参数配置集合")]
|
||||||
|
//[TypeConverter(typeof(ComplexObjectConvert))]
|
||||||
|
//[Editor(typeof(PropertyObjectEditor), typeof(UITypeEditor))]
|
||||||
|
//public ModelParamSetting ModelParamSetting { get; set; } = new ModelParamSetting();
|
||||||
|
|
||||||
|
//public string GetDisplayText()
|
||||||
|
//{
|
||||||
|
// string dName = "";
|
||||||
|
// if (!string.IsNullOrWhiteSpace(LabelId))
|
||||||
|
// {
|
||||||
|
// using (var scope = GlobalVar.Container.BeginLifetimeScope())
|
||||||
|
// {
|
||||||
|
// IProcessConfig config = scope.Resolve<IProcessConfig>();
|
||||||
|
|
||||||
|
// var mlBase = config.DeviceConfigs.FirstOrDefault(c => c is VisionEngineInitialConfigBase) as VisionEngineInitialConfigBase;
|
||||||
|
// if (mlBase != null)
|
||||||
|
// {
|
||||||
|
// var targetLabel = mlBase.RecongnitionLabelList.FirstOrDefault(u => u.Id == LabelId);
|
||||||
|
// if (targetLabel != null)
|
||||||
|
// {
|
||||||
|
// dName = targetLabel.GetDisplayText();
|
||||||
|
// }
|
||||||
|
// }
|
||||||
|
// }
|
||||||
|
// }
|
||||||
|
// return dName;
|
||||||
|
//}
|
||||||
|
//public string GetLabelName()
|
||||||
|
//{
|
||||||
|
// var name = "";
|
||||||
|
|
||||||
|
|
||||||
|
// var mlBase = iConfig.DeviceConfigs.FirstOrDefault(c => c is VisionEngineInitialConfigBase) as VisionEngineInitialConfigBase;
|
||||||
|
// if (mlBase != null)
|
||||||
|
// {
|
||||||
|
// var label = mlBase.RecongnitionLabelList.FirstOrDefault(u => u.Id == LabelId);
|
||||||
|
// if (label != null)
|
||||||
|
// {
|
||||||
|
// name = label.LabelName;
|
||||||
|
// }
|
||||||
|
// }
|
||||||
|
|
||||||
|
|
||||||
|
// return name;
|
||||||
|
//}
|
||||||
|
}
|
||||||
|
|
||||||
|
/// <summary>
|
||||||
|
/// 识别对象定义分类信息 A类B类
|
||||||
|
/// </summary>
|
||||||
|
public class RecongnitionLabelCategory //: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("检测标签分类")]
|
||||||
|
[Description("检测标签分类")]
|
||||||
|
[ReadOnly(true)]
|
||||||
|
public string Id { get; set; } = Guid.NewGuid().ToString();
|
||||||
|
|
||||||
|
[Category("检测标签分类")]
|
||||||
|
[DisplayName("检测标签分类名称")]
|
||||||
|
[Description("检测标签分类名称")]
|
||||||
|
public string CategoryName { get; set; } = "A-NG";
|
||||||
|
|
||||||
|
[Category("检测标签分类")]
|
||||||
|
[DisplayName("检测标签分类优先级")]
|
||||||
|
[Description("检测标签分类优先级，值越小，优先级越高")]
|
||||||
|
public int CategoryPriority { get; set; } = 0;
|
||||||
|
|
||||||
|
public string GetDisplayText()
|
||||||
|
{
|
||||||
|
return CategoryPriority + ":" + CategoryName;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/// <summary>
|
||||||
|
/// 检测过滤
|
||||||
|
/// </summary>
|
||||||
|
public class DetectionFilter ///: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("过滤器基础信息")]
|
||||||
|
[DisplayName("检测标签")]
|
||||||
|
[Description("检测标签信息")]
|
||||||
|
//[TypeConverter(typeof(DetectionLabelConverter))]
|
||||||
|
public string LabelId { get; set; }
|
||||||
|
|
||||||
|
// [Browsable(false)]
|
||||||
|
public string LabelName { get; set; }
|
||||||
|
|
||||||
|
[Category("过滤器基础信息")]
|
||||||
|
[DisplayName("是否启用过滤器")]
|
||||||
|
[Description("是否启用过滤器")]
|
||||||
|
public bool IsEnabled { get; set; }
|
||||||
|
|
||||||
|
[Category("过滤器判定信息")]
|
||||||
|
[DisplayName("判定结果")]
|
||||||
|
[Description("过滤器默认判定结果")]
|
||||||
|
public ResultState ResultState { get; set; } = ResultState.ResultTBD;
|
||||||
|
|
||||||
|
[Category("过滤条件")]
|
||||||
|
[DisplayName("过滤条件集合")]
|
||||||
|
[Description("过滤条件集合，集合之间为“且”关系")]
|
||||||
|
//[TypeConverter(typeof(CollectionCountConvert))]
|
||||||
|
// [Editor(typeof(ComplexCollectionEditor<FilterConditions>), typeof(UITypeEditor))]
|
||||||
|
public List<FilterConditions> FilterConditionsCollection { get; set; } = new List<FilterConditions>();
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
public bool FilterOperation(DetectionResultDetail recongnitionResult)
|
||||||
|
{
|
||||||
|
return FilterConditionsCollection.All(u =>
|
||||||
|
{
|
||||||
|
return u.FilterConditionCollection.Any(c =>
|
||||||
|
{
|
||||||
|
double compareValue = 0;
|
||||||
|
|
||||||
|
switch (c.FilterPropperty)
|
||||||
|
{
|
||||||
|
case DetectionFilterProperty.Width:
|
||||||
|
compareValue = recongnitionResult.Rect.Width;
|
||||||
|
break;
|
||||||
|
case DetectionFilterProperty.Height:
|
||||||
|
compareValue = recongnitionResult.Rect.Height;
|
||||||
|
break;
|
||||||
|
case DetectionFilterProperty.Area:
|
||||||
|
compareValue = recongnitionResult.Area;
|
||||||
|
break;
|
||||||
|
case DetectionFilterProperty.Score:
|
||||||
|
compareValue = recongnitionResult.Score;
|
||||||
|
break;
|
||||||
|
//case RecongnitionTargetFilterProperty.Uncertainty:
|
||||||
|
// compareValue = 0;
|
||||||
|
// //defect.Uncertainty;
|
||||||
|
// break;
|
||||||
|
}
|
||||||
|
|
||||||
|
return compareValue >= c.MinValue && compareValue <= c.MaxValue;
|
||||||
|
});
|
||||||
|
});
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
public class FilterConditions //: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("过滤条件")]
|
||||||
|
[DisplayName("过滤条件集合")]
|
||||||
|
[Description("过滤条件集合，集合之间为“或”关系")]
|
||||||
|
//[TypeConverter(typeof(CollectionCountConvert))]
|
||||||
|
//[Editor(typeof(ComplexCollectionEditor<FilterCondition>), typeof(UITypeEditor))]
|
||||||
|
public List<FilterCondition> FilterConditionCollection { get; set; } = new List<FilterCondition>();
|
||||||
|
|
||||||
|
//public string GetDisplayText()
|
||||||
|
//{
|
||||||
|
// if (FilterConditionCollection.Count == 0)
|
||||||
|
// {
|
||||||
|
// return "空";
|
||||||
|
// }
|
||||||
|
// else
|
||||||
|
// {
|
||||||
|
// var desc = string.Join(" OR ", FilterConditionCollection.Select(u => u.GetDisplayText()));
|
||||||
|
|
||||||
|
// if (FilterConditionCollection.Count > 1)
|
||||||
|
// {
|
||||||
|
// desc = $"({desc})";
|
||||||
|
// }
|
||||||
|
|
||||||
|
// return desc;
|
||||||
|
// }
|
||||||
|
//}
|
||||||
|
}
|
||||||
|
|
||||||
|
public class FilterCondition //: IComplexDisplay
|
||||||
|
{
|
||||||
|
[Category("识别目标属性")]
|
||||||
|
[DisplayName("过滤属性")]
|
||||||
|
[Description("识别目标过滤针对的属性")]
|
||||||
|
//[TypeConverter(typeof(EnumDescriptionConverter<DetectionFilterProperty>))]
|
||||||
|
public DetectionFilterProperty FilterPropperty { get; set; } = DetectionFilterProperty.Width;
|
||||||
|
|
||||||
|
[Category("过滤值")]
|
||||||
|
[DisplayName("最小值")]
|
||||||
|
[Description("最小值")]
|
||||||
|
public double MinValue { get; set; } = 1;
|
||||||
|
|
||||||
|
[Category("过滤值")]
|
||||||
|
[DisplayName("最大值")]
|
||||||
|
[Description("最大值")]
|
||||||
|
public double MaxValue { get; set; } = 99999999;
|
||||||
|
|
||||||
|
//public string GetDisplayText()
|
||||||
|
//{
|
||||||
|
// return $"{FilterPropperty.GetEnumDescription()}:{MinValue}-{MaxValue}";
|
||||||
|
//}
|
||||||
|
}
|
||||||
|
|
||||||
|
public enum DetectionFilterProperty
|
||||||
|
{
|
||||||
|
[Description("宽度")]
|
||||||
|
Width = 1,
|
||||||
|
[Description("高度")]
|
||||||
|
Height = 2,
|
||||||
|
[Description("面积")]
|
||||||
|
Area = 3,
|
||||||
|
[Description("得分")]
|
||||||
|
Score = 4,
|
||||||
|
//[Description("不确定性")]
|
||||||
|
//Uncertainty = 5,
|
||||||
|
}
|
||||||
|
}
|
||||||
244
DH.Devices.Vision/SimboDetection.cs
Normal file
244
DH.Devices.Vision/SimboDetection.cs
Normal file
@ -0,0 +1,244 @@
|
|||||||
|
#define USE_MULTI_THREAD
|
||||||
|
|
||||||
|
using OpenCvSharp;
|
||||||
|
using OpenCvSharp.Extensions;
|
||||||
|
using System;
|
||||||
|
using System.Collections.Generic;
|
||||||
|
using System.Diagnostics;
|
||||||
|
using System.Drawing;
|
||||||
|
using System.Linq;
|
||||||
|
using System.Runtime.ExceptionServices;
|
||||||
|
using System.Threading;
|
||||||
|
using System.Threading.Tasks;
|
||||||
|
using System.Security.Cryptography.Xml;
|
||||||
|
using System.Runtime.InteropServices;
|
||||||
|
using Newtonsoft.Json;
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
namespace DH.Devices.Vision
|
||||||
|
{
|
||||||
|
|
||||||
|
|
||||||
|
/// <summary>
|
||||||
|
/// 目标检测 GPU
|
||||||
|
/// </summary>
|
||||||
|
public class SimboDetection : SimboVisionMLBase
|
||||||
|
{
|
||||||
|
|
||||||
|
public override bool Load(MLInit mLInit)
|
||||||
|
{
|
||||||
|
bool res = false;
|
||||||
|
try
|
||||||
|
{
|
||||||
|
Model = MLGPUEngine.InitModel(mLInit.ModelFile, 1, mLInit.Score_thre, mLInit.GPUId, 3, 8);
|
||||||
|
|
||||||
|
//Model = MLEngine.InitModel(mLInit.ModelFile, 1, 0.45f, 0, 3);
|
||||||
|
|
||||||
|
res = true;
|
||||||
|
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
IsCreated = true;
|
||||||
|
if (IsCreated)
|
||||||
|
{
|
||||||
|
_runHandleBefore ??= new AutoResetEvent(false);
|
||||||
|
_runHandleAfter ??= new ManualResetEvent(false);
|
||||||
|
|
||||||
|
_runTask ??= Task.Factory.StartNew(() =>
|
||||||
|
{
|
||||||
|
while (IsCreated)
|
||||||
|
{
|
||||||
|
_runHandleBefore.WaitOne();
|
||||||
|
|
||||||
|
if (IsCreated)
|
||||||
|
{
|
||||||
|
_result = RunInferenceFixed(_req);
|
||||||
|
_runHandleAfter.Set();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}, TaskCreationOptions.LongRunning);
|
||||||
|
}
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
catch (Exception ex)
|
||||||
|
{
|
||||||
|
throw ex;
|
||||||
|
}
|
||||||
|
return res;
|
||||||
|
}
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
MLRequest _req = null;
|
||||||
|
MLResult _result = null;
|
||||||
|
public bool IsCreated { get; set; } = false;
|
||||||
|
Task _runTask = null;
|
||||||
|
AutoResetEvent _runHandleBefore = new AutoResetEvent(false);
|
||||||
|
ManualResetEvent _runHandleAfter = new ManualResetEvent(false);
|
||||||
|
object _runLock = new object();
|
||||||
|
#endif
|
||||||
|
[HandleProcessCorruptedStateExceptions]
|
||||||
|
public override MLResult RunInference(MLRequest req)
|
||||||
|
{
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
MLResult mlResult = null;
|
||||||
|
lock (_runLock)
|
||||||
|
{
|
||||||
|
_result = new MLResult();
|
||||||
|
|
||||||
|
_req = req;
|
||||||
|
|
||||||
|
_runHandleAfter.Reset();
|
||||||
|
_runHandleBefore.Set();
|
||||||
|
_runHandleAfter.WaitOne();
|
||||||
|
|
||||||
|
mlResult = _result;
|
||||||
|
}
|
||||||
|
|
||||||
|
return mlResult;
|
||||||
|
#else
|
||||||
|
return RunInferenceFixed(req);
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
private void ConvertJsonResult(string json, ref MLResult result)
|
||||||
|
{
|
||||||
|
// json = "{\"FastDetResult\":[{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654843,\"rect\":[175,99,110,594]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654589,\"rect\":[2608,19,104,661]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654285,\"rect\":[1275,19,104,662]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.620762,\"rect\":[1510,95,107,600]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.617812,\"rect\":[2844,93,106,602]}]}";
|
||||||
|
//
|
||||||
|
Console.WriteLine("检测结果JSON：" + json);
|
||||||
|
HYoloResult detResult = JsonConvert.DeserializeObject<HYoloResult>(json);
|
||||||
|
if (detResult == null)
|
||||||
|
{
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
int iNum = detResult.HYolo.Count;
|
||||||
|
int IokNum = 0;
|
||||||
|
for (int ix = 0; ix < iNum; ix++)
|
||||||
|
{
|
||||||
|
var det = detResult.HYolo[ix];
|
||||||
|
|
||||||
|
var rect = det.rect;
|
||||||
|
DetectionResultDetail detectionResultDetail = new DetectionResultDetail();
|
||||||
|
// detectionResultDetail.LabelNo = det.classId;
|
||||||
|
//todo: 标签名相对应
|
||||||
|
detectionResultDetail.LabelDisplay = det.classname;
|
||||||
|
detectionResultDetail.Rect = new Rectangle(rect[0], rect[1], rect[2], rect[3]);
|
||||||
|
detectionResultDetail.Score = det.fScore;
|
||||||
|
detectionResultDetail.LabelName = det.classname;
|
||||||
|
detectionResultDetail.Area = rect[2] * rect[3];
|
||||||
|
detectionResultDetail.InferenceResult = ResultState.DetectNG;
|
||||||
|
|
||||||
|
result.ResultDetails.Add(detectionResultDetail);
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
[HandleProcessCorruptedStateExceptions]
|
||||||
|
public MLResult RunInferenceFixed(MLRequest req)
|
||||||
|
{
|
||||||
|
MLResult mlResult = new MLResult();
|
||||||
|
Mat originMat = new Mat();
|
||||||
|
Mat detectMat = new Mat();
|
||||||
|
|
||||||
|
try
|
||||||
|
{
|
||||||
|
if (req.mImage == null)
|
||||||
|
{
|
||||||
|
mlResult.IsSuccess = false;
|
||||||
|
mlResult.ResultMessage = "异常：mat为null，无法执行推理！";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
|
||||||
|
// resize
|
||||||
|
detectMat = req.mImage;//1ms
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
int iWidth = detectMat.Cols;
|
||||||
|
int iHeight = detectMat.Rows;
|
||||||
|
|
||||||
|
// 如果是单通道图像，转换为三通道 RGB 格式
|
||||||
|
if (detectMat.Channels() == 1)
|
||||||
|
{
|
||||||
|
// 将灰度图像转换为RGB格式（三通道）
|
||||||
|
|
||||||
|
Cv2.CvtColor(detectMat, originMat, ColorConversionCodes.GRAY2BGR);
|
||||||
|
|
||||||
|
}
|
||||||
|
else if (detectMat.Channels() == 3)
|
||||||
|
{
|
||||||
|
// 如果已经是三通道（BGR），则直接转换为RGB
|
||||||
|
|
||||||
|
Cv2.CvtColor(detectMat, originMat, ColorConversionCodes.BGR2RGB);
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
//输入数据转化为字节
|
||||||
|
var inputByte = new byte[originMat.Total() * 3];//这里必须乘以通道数，不然数组越界，也可以用w*h*c，差不多
|
||||||
|
Marshal.Copy(originMat.Data, inputByte, 0, inputByte.Length);
|
||||||
|
|
||||||
|
byte[] labellist = new byte[40960]; //新建字节数组：label1_str label2_str
|
||||||
|
|
||||||
|
byte[] outputByte = new byte[originMat.Total() * 3];
|
||||||
|
|
||||||
|
Stopwatch sw = new Stopwatch();
|
||||||
|
sw.Start();
|
||||||
|
|
||||||
|
//mlResult.IsSuccess = true;
|
||||||
|
unsafe
|
||||||
|
{
|
||||||
|
//mlResult.IsSuccess = MLGPUEngine.Inference(Model, inputByte, iWidth, iHeight, 3, req.in_lable_path, ref outputByte[0], ref labellist[0]);
|
||||||
|
|
||||||
|
mlResult.IsSuccess = MLGPUEngine.Inference2(Model, inputByte, iWidth, iHeight, 3, req.in_lable_path, ref labellist[0]);
|
||||||
|
}
|
||||||
|
|
||||||
|
sw.Stop();
|
||||||
|
|
||||||
|
|
||||||
|
if (mlResult.IsSuccess)
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"深度学习推理成功，耗时：{sw.ElapsedMilliseconds} ms";
|
||||||
|
|
||||||
|
//将字节数组转换为字符串
|
||||||
|
mlResult.ResultMap = originMat.ToBitmap();//4ms
|
||||||
|
string strGet = System.Text.Encoding.Default.GetString(labellist, 0, labellist.Length);
|
||||||
|
|
||||||
|
if (strGet == null)
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"异常：深度学习执行推理失败！";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
|
||||||
|
ConvertJsonResult(strGet, ref mlResult);
|
||||||
|
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"异常：深度学习执行推理失败！";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
catch (Exception ex)
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"深度学习执行推理异常";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
finally
|
||||||
|
{
|
||||||
|
|
||||||
|
originMat?.Dispose();
|
||||||
|
originMat = null;
|
||||||
|
//maskMat?.Dispose();
|
||||||
|
// maskMat = null;
|
||||||
|
detectMat?.Dispose();
|
||||||
|
detectMat = null;
|
||||||
|
// maskWeighted?.Dispose();
|
||||||
|
// maskWeighted = null;
|
||||||
|
// GC.Collect();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
264
DH.Devices.Vision/SimboInstanceSegmentation.cs
Normal file
264
DH.Devices.Vision/SimboInstanceSegmentation.cs
Normal file
@ -0,0 +1,264 @@
|
|||||||
|
//#define USE_MULTI_THREAD
|
||||||
|
|
||||||
|
using OpenCvSharp;
|
||||||
|
using OpenCvSharp.Extensions;
|
||||||
|
using System;
|
||||||
|
using System.Collections.Generic;
|
||||||
|
using System.Diagnostics;
|
||||||
|
using System.Drawing;
|
||||||
|
using System.Linq;
|
||||||
|
using System.Runtime.ExceptionServices;
|
||||||
|
using System.Threading;
|
||||||
|
using System.Threading.Tasks;
|
||||||
|
using System.Runtime.InteropServices;
|
||||||
|
using Newtonsoft.Json;
|
||||||
|
|
||||||
|
|
||||||
|
namespace DH.Devices.Vision
|
||||||
|
{
|
||||||
|
|
||||||
|
/// <summary>
|
||||||
|
/// 实例分割 maskrcnn
|
||||||
|
/// </summary>
|
||||||
|
public class SimboInstanceSegmentation : SimboVisionMLBase
|
||||||
|
{
|
||||||
|
public override bool Load(MLInit mLInit)
|
||||||
|
{
|
||||||
|
bool res = false;
|
||||||
|
try
|
||||||
|
{
|
||||||
|
|
||||||
|
|
||||||
|
Model = MLEngine.InitModel(mLInit.ModelFile,
|
||||||
|
mLInit.InferenceDevice,
|
||||||
|
mLInit.InputNodeName,
|
||||||
|
1, 3,
|
||||||
|
mLInit.InferenceWidth,
|
||||||
|
mLInit.InferenceHeight,5);
|
||||||
|
res = true;
|
||||||
|
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
|
||||||
|
IsCreated = true;
|
||||||
|
if (IsCreated)
|
||||||
|
{
|
||||||
|
if (_runHandleBefore == null)
|
||||||
|
{
|
||||||
|
_runHandleBefore = new AutoResetEvent(false);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (_runHandleAfter == null)
|
||||||
|
{
|
||||||
|
_runHandleAfter = new ManualResetEvent(false);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (_runTask == null)
|
||||||
|
{
|
||||||
|
_runTask = Task.Factory.StartNew(() =>
|
||||||
|
{
|
||||||
|
while (IsCreated)
|
||||||
|
{
|
||||||
|
_runHandleBefore.WaitOne();
|
||||||
|
|
||||||
|
if (IsCreated)
|
||||||
|
{
|
||||||
|
_result = RunInferenceFixed(_req);
|
||||||
|
_runHandleAfter.Set();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}, TaskCreationOptions.LongRunning);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
#endif
|
||||||
|
}
|
||||||
|
catch (Exception ex)
|
||||||
|
{
|
||||||
|
throw ex;
|
||||||
|
}
|
||||||
|
return res;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
MLRequest _req = null;
|
||||||
|
MLResult _result = null;
|
||||||
|
|
||||||
|
|
||||||
|
public bool IsCreated { get; set; } = false;
|
||||||
|
Task _runTask = null;
|
||||||
|
AutoResetEvent _runHandleBefore = new AutoResetEvent(false);
|
||||||
|
ManualResetEvent _runHandleAfter = new ManualResetEvent(false);
|
||||||
|
object _runLock = new object();
|
||||||
|
#endif
|
||||||
|
|
||||||
|
[HandleProcessCorruptedStateExceptions]
|
||||||
|
public override MLResult RunInference(MLRequest req)
|
||||||
|
{
|
||||||
|
#if USE_MULTI_THREAD
|
||||||
|
MLResult mlResult = null;
|
||||||
|
lock (_runLock)
|
||||||
|
{
|
||||||
|
_result = new MLResult();
|
||||||
|
|
||||||
|
_req = req;
|
||||||
|
|
||||||
|
_runHandleAfter.Reset();
|
||||||
|
_runHandleBefore.Set();
|
||||||
|
_runHandleAfter.WaitOne();
|
||||||
|
|
||||||
|
mlResult = _result;
|
||||||
|
}
|
||||||
|
|
||||||
|
return mlResult;
|
||||||
|
#else
|
||||||
|
return RunInferenceFixed(req);
|
||||||
|
#endif
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
private void ConvertJsonResult(string json, ref MLResult result)
|
||||||
|
{
|
||||||
|
// json = "{\"FastDetResult\":[{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654843,\"rect\":[175,99,110,594]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654589,\"rect\":[2608,19,104,661]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.654285,\"rect\":[1275,19,104,662]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.620762,\"rect\":[1510,95,107,600]},{\"cls_id\":0,\"cls\":\"liewen\",\"fScore\":0.617812,\"rect\":[2844,93,106,602]}]}";
|
||||||
|
//
|
||||||
|
Console.WriteLine("检测结果JSON：" + json);
|
||||||
|
SegResult detResult = JsonConvert.DeserializeObject<SegResult>(json);
|
||||||
|
if (detResult == null)
|
||||||
|
{
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
int iNum = detResult.SegmentResult.Count;
|
||||||
|
int IokNum = 0;
|
||||||
|
for (int ix = 0; ix < iNum; ix++)
|
||||||
|
{
|
||||||
|
var det = detResult.SegmentResult[ix];
|
||||||
|
|
||||||
|
var rect = det.rect;
|
||||||
|
DetectionResultDetail detectionResultDetail = new DetectionResultDetail();
|
||||||
|
detectionResultDetail.LabelNo = det.classId;
|
||||||
|
//todo: 标签名相对应
|
||||||
|
detectionResultDetail.LabelDisplay = det.classname;
|
||||||
|
detectionResultDetail.Rect = new Rectangle(rect[0], rect[1], rect[2], rect[3]);
|
||||||
|
detectionResultDetail.Score = det.fScore;
|
||||||
|
detectionResultDetail.LabelName = det.classname;
|
||||||
|
detectionResultDetail.Area = det.area;
|
||||||
|
detectionResultDetail.InferenceResult = ResultState.DetectNG;
|
||||||
|
|
||||||
|
result.ResultDetails.Add(detectionResultDetail);
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
[HandleProcessCorruptedStateExceptions]
|
||||||
|
public MLResult RunInferenceFixed(MLRequest req)
|
||||||
|
{
|
||||||
|
MLResult mlResult = new MLResult();
|
||||||
|
Mat originMat = new Mat();
|
||||||
|
Mat detectMat = new Mat();
|
||||||
|
|
||||||
|
try
|
||||||
|
{
|
||||||
|
if (req.mImage == null)
|
||||||
|
{
|
||||||
|
mlResult.IsSuccess = false;
|
||||||
|
mlResult.ResultMessage = "异常：mat为null，无法执行推理！";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
|
||||||
|
// resize
|
||||||
|
detectMat = req.mImage;//1ms
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
int iWidth = detectMat.Cols;
|
||||||
|
int iHeight = detectMat.Rows;
|
||||||
|
|
||||||
|
// 如果是单通道图像，转换为三通道 RGB 格式
|
||||||
|
if (detectMat.Channels() == 1)
|
||||||
|
{
|
||||||
|
// 将灰度图像转换为RGB格式（三通道）
|
||||||
|
|
||||||
|
Cv2.CvtColor(detectMat, originMat, ColorConversionCodes.GRAY2BGR);
|
||||||
|
|
||||||
|
}
|
||||||
|
else if (detectMat.Channels() == 3)
|
||||||
|
{
|
||||||
|
// 如果已经是三通道（BGR），则直接转换为RGB
|
||||||
|
|
||||||
|
Cv2.CvtColor(detectMat, originMat, ColorConversionCodes.BGR2RGB);
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
//输入数据转化为字节
|
||||||
|
var inputByte = new byte[originMat.Total() * 3];//这里必须乘以通道数，不然数组越界，也可以用w*h*c，差不多
|
||||||
|
Marshal.Copy(originMat.Data, inputByte, 0, inputByte.Length);
|
||||||
|
|
||||||
|
byte[] labellist = new byte[40960]; //新建字节数组：label1_str label2_str
|
||||||
|
|
||||||
|
byte[] outputByte = new byte[originMat.Total() * 3];
|
||||||
|
|
||||||
|
Stopwatch sw = new Stopwatch();
|
||||||
|
sw.Start();
|
||||||
|
unsafe
|
||||||
|
{
|
||||||
|
|
||||||
|
mlResult.IsSuccess = MLEngine.seg_ModelPredict(Model, inputByte, iWidth, iHeight, 3,
|
||||||
|
req.in_lable_path, req.confThreshold, req.iouThreshold, req.confThreshold, req.segmentWidth, ref outputByte[0], ref labellist[0]);
|
||||||
|
//mlResult.IsSuccess = true;
|
||||||
|
}
|
||||||
|
sw.Stop();
|
||||||
|
|
||||||
|
if (mlResult.IsSuccess)
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"深度学习推理成功，耗时：{sw.ElapsedMilliseconds} ms";
|
||||||
|
|
||||||
|
//将字节数组转换为字符串
|
||||||
|
mlResult.ResultMap = originMat.ToBitmap();//4ms
|
||||||
|
string strGet = System.Text.Encoding.Default.GetString(labellist, 0, labellist.Length);
|
||||||
|
|
||||||
|
|
||||||
|
Console.WriteLine("strGet:", strGet);
|
||||||
|
|
||||||
|
|
||||||
|
ConvertJsonResult(strGet, ref mlResult);
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
//解析json字符串
|
||||||
|
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"异常：深度学习执行推理失败！";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
catch (Exception ex)
|
||||||
|
{
|
||||||
|
mlResult.ResultMessage = $"深度学习执行推理异常";
|
||||||
|
return mlResult;
|
||||||
|
}
|
||||||
|
finally
|
||||||
|
{
|
||||||
|
|
||||||
|
originMat?.Dispose();
|
||||||
|
originMat = null;
|
||||||
|
|
||||||
|
|
||||||
|
// GC.Collect();
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
@ -17,23 +17,7 @@ using Newtonsoft.Json;
|
|||||||
namespace DH.Devices.Vision
|
namespace DH.Devices.Vision
|
||||||
{
|
{
|
||||||
|
|
||||||
//public class SegResult
|
|
||||||
//{
|
|
||||||
// public List<Result> SegmentResult;
|
|
||||||
// public class Result
|
|
||||||
// {
|
|
||||||
|
|
||||||
// public double fScore;
|
|
||||||
// public int classId;
|
|
||||||
// public string classname;
|
|
||||||
|
|
||||||
// public double area;
|
|
||||||
// public List<int> rect;
|
|
||||||
|
|
||||||
|
|
||||||
// }
|
|
||||||
|
|
||||||
//}
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
@ -157,7 +141,6 @@ namespace DH.Devices.Vision
|
|||||||
}
|
}
|
||||||
|
|
||||||
int iNum = detResult.SegmentResult.Count;
|
int iNum = detResult.SegmentResult.Count;
|
||||||
int IokNum = 0;
|
|
||||||
for (int ix = 0; ix < iNum; ix++)
|
for (int ix = 0; ix < iNum; ix++)
|
||||||
{
|
{
|
||||||
var det = detResult.SegmentResult[ix];
|
var det = detResult.SegmentResult[ix];
|
||||||
@ -188,7 +171,7 @@ namespace DH.Devices.Vision
|
|||||||
{
|
{
|
||||||
MLResult mlResult = new MLResult();
|
MLResult mlResult = new MLResult();
|
||||||
Mat originMat=new Mat() ;
|
Mat originMat=new Mat() ;
|
||||||
Mat tempMat;
|
Mat detectMat;
|
||||||
try
|
try
|
||||||
{
|
{
|
||||||
if (req.mImage == null)
|
if (req.mImage == null)
|
||||||
@ -199,26 +182,26 @@ namespace DH.Devices.Vision
|
|||||||
}
|
}
|
||||||
|
|
||||||
// resize
|
// resize
|
||||||
tempMat = req.mImage;//1ms
|
detectMat = req.mImage;//1ms
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
int iWidth = tempMat.Cols;
|
int iWidth = detectMat.Cols;
|
||||||
int iHeight = tempMat.Rows;
|
int iHeight = detectMat.Rows;
|
||||||
|
|
||||||
// 如果是单通道图像，转换为三通道 RGB 格式
|
// 如果是单通道图像，转换为三通道 RGB 格式
|
||||||
if (tempMat.Channels() == 1)
|
if (detectMat.Channels() == 1)
|
||||||
{
|
{
|
||||||
// 将灰度图像转换为RGB格式（三通道）
|
// 将灰度图像转换为RGB格式（三通道）
|
||||||
|
|
||||||
Cv2.CvtColor( tempMat,originMat, ColorConversionCodes.GRAY2BGR);
|
Cv2.CvtColor( detectMat,originMat, ColorConversionCodes.GRAY2BGR);
|
||||||
|
|
||||||
}
|
}
|
||||||
else if (tempMat.Channels() == 3)
|
else if (detectMat.Channels() == 3)
|
||||||
{
|
{
|
||||||
// 如果已经是三通道（BGR），则直接转换为RGB
|
// 如果已经是三通道（BGR），则直接转换为RGB
|
||||||
|
|
||||||
Cv2.CvtColor( tempMat,originMat, ColorConversionCodes.BGR2RGB);
|
Cv2.CvtColor( detectMat,originMat, ColorConversionCodes.BGR2RGB);
|
||||||
|
|
||||||
}
|
}
|
||||||
|
|
||||||
@ -250,9 +233,6 @@ namespace DH.Devices.Vision
|
|||||||
{
|
{
|
||||||
mlResult.ResultMessage = $"深度学习推理成功，耗时：{sw.ElapsedMilliseconds} ms";
|
mlResult.ResultMessage = $"深度学习推理成功，耗时：{sw.ElapsedMilliseconds} ms";
|
||||||
|
|
||||||
//Mat maskWeighted = new Mat(iHeight, iWidth, MatType.CV_8UC3, outputByte);
|
|
||||||
|
|
||||||
//mlResult.ResultMap = BitmapConverter.ToBitmap(maskWeighted);//4ms
|
|
||||||
//将字节数组转换为字符串
|
//将字节数组转换为字符串
|
||||||
mlResult.ResultMap = originMat.ToBitmap();//4ms
|
mlResult.ResultMap = originMat.ToBitmap();//4ms
|
||||||
string strGet = System.Text.Encoding.Default.GetString(labellist, 0, labellist.Length);
|
string strGet = System.Text.Encoding.Default.GetString(labellist, 0, labellist.Length);
|
||||||
@ -261,9 +241,6 @@ namespace DH.Devices.Vision
|
|||||||
|
|
||||||
ConvertJsonResult(strGet, ref mlResult);
|
ConvertJsonResult(strGet, ref mlResult);
|
||||||
|
|
||||||
//maskWeighted?.Dispose();
|
|
||||||
//maskWeighted = null;
|
|
||||||
|
|
||||||
// 解析json字符串
|
// 解析json字符串
|
||||||
return mlResult;
|
return mlResult;
|
||||||
}
|
}
|
||||||
|
|||||||
18
DH.Devices.Vision/SimboVisionDriver.cs
Normal file
18
DH.Devices.Vision/SimboVisionDriver.cs
Normal file
@ -0,0 +1,18 @@
|
|||||||
|
using OpenCvSharp;
|
||||||
|
using System;
|
||||||
|
using System.Collections.Generic;
|
||||||
|
using System.Diagnostics;
|
||||||
|
using System.Linq;
|
||||||
|
using System.Runtime.ExceptionServices;
|
||||||
|
using System.Text;
|
||||||
|
using System.Threading.Tasks;
|
||||||
|
using System.Xml.Linq;
|
||||||
|
|
||||||
|
namespace DH.Devices.Vision
|
||||||
|
{
|
||||||
|
public class SimboVisionDriver
|
||||||
|
{
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
}
|
||||||
@ -44,6 +44,31 @@ namespace DH.Devices.Vision
|
|||||||
// ColorLut = new Mat(1, 256, MatType.CV_8UC3, ColorMap);
|
// ColorLut = new Mat(1, 256, MatType.CV_8UC3, ColorMap);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
public class HYoloResult
|
||||||
|
{
|
||||||
|
//{
|
||||||
|
// "HYolo": [{
|
||||||
|
// "fScore": "0.687012",
|
||||||
|
// "classId": 0,
|
||||||
|
// "classname": "quejiao",
|
||||||
|
// "rect": [421, 823, 6, 8]
|
||||||
|
// }]
|
||||||
|
//}
|
||||||
|
public List<Result> HYolo;
|
||||||
|
public class Result
|
||||||
|
{
|
||||||
|
|
||||||
|
public double fScore;
|
||||||
|
public int classId;
|
||||||
|
public string classname;
|
||||||
|
|
||||||
|
//public double area;
|
||||||
|
public List<int> rect;
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
public class SegResult
|
public class SegResult
|
||||||
{
|
{
|
||||||
public List<Result> SegmentResult;
|
public List<Result> SegmentResult;
|
||||||
|
|||||||
@ -1,299 +0,0 @@
|
|||||||
using OpenCvSharp;
|
|
||||||
using System.ComponentModel;
|
|
||||||
using System.Drawing;
|
|
||||||
using static OpenCvSharp.AgastFeatureDetector;
|
|
||||||
using System.Text.RegularExpressions;
|
|
||||||
using System.Text;
|
|
||||||
|
|
||||||
namespace DH.Devices.Vision
|
|
||||||
{
|
|
||||||
public enum MLModelType
|
|
||||||
{
|
|
||||||
[Description("图像分类")]
|
|
||||||
ImageClassification = 1,
|
|
||||||
[Description("目标检测")]
|
|
||||||
ObjectDetection = 2,
|
|
||||||
//[Description("图像分割")]
|
|
||||||
//ImageSegmentation = 3
|
|
||||||
[Description("语义分割")]
|
|
||||||
SemanticSegmentation = 3,
|
|
||||||
[Description("实例分割")]
|
|
||||||
InstanceSegmentation = 4,
|
|
||||||
[Description("目标检测GPU")]
|
|
||||||
ObjectGPUDetection = 5
|
|
||||||
}
|
|
||||||
public class MLRequest
|
|
||||||
{
|
|
||||||
public int ImageChannels = 3;
|
|
||||||
public Mat mImage;
|
|
||||||
public int ResizeWidth;
|
|
||||||
public int ResizeHeight;
|
|
||||||
|
|
||||||
public float confThreshold;
|
|
||||||
|
|
||||||
public float iouThreshold;
|
|
||||||
|
|
||||||
//public int ImageResizeCount;
|
|
||||||
public bool IsCLDetection;
|
|
||||||
public int ProCount;
|
|
||||||
public string in_node_name;
|
|
||||||
|
|
||||||
public string out_node_name;
|
|
||||||
|
|
||||||
public string in_lable_path;
|
|
||||||
|
|
||||||
public int ResizeImageSize;
|
|
||||||
public int segmentWidth;
|
|
||||||
public int ImageWidth;
|
|
||||||
|
|
||||||
// public List<labelStringBase> OkClassTxtList;
|
|
||||||
|
|
||||||
|
|
||||||
// public List<ModelLabel> LabelNames;
|
|
||||||
|
|
||||||
public float Score;
|
|
||||||
|
|
||||||
}
|
|
||||||
public enum ResultState
|
|
||||||
{
|
|
||||||
|
|
||||||
[Description("检测NG")]
|
|
||||||
DetectNG = -3,
|
|
||||||
|
|
||||||
//[Description("检测不足TBD")]
|
|
||||||
// ShortageTBD = -2,
|
|
||||||
[Description("检测结果TBD")]
|
|
||||||
ResultTBD = -1,
|
|
||||||
[Description("OK")]
|
|
||||||
OK = 1,
|
|
||||||
// [Description("NG")]
|
|
||||||
// NG = 2,
|
|
||||||
//统计结果
|
|
||||||
[Description("A类NG")]
|
|
||||||
A_NG = 25,
|
|
||||||
[Description("B类NG")]
|
|
||||||
B_NG = 26,
|
|
||||||
[Description("C类NG")]
|
|
||||||
C_NG = 27,
|
|
||||||
}
|
|
||||||
/// <summary>
|
|
||||||
/// 深度学习 识别结果明细 面向业务：detect 面向深度学习：Recongnition、Inference
|
|
||||||
/// </summary>
|
|
||||||
public class DetectionResultDetail
|
|
||||||
{
|
|
||||||
public string LabelBGR { get; set; }//识别到对象的标签BGR
|
|
||||||
|
|
||||||
|
|
||||||
public int LabelNo { get; set; } // 识别到对象的标签索引
|
|
||||||
|
|
||||||
public string LabelName { get; set; }//识别到对象的标签名称
|
|
||||||
|
|
||||||
public double Score { get; set; }//识别目标结果的可能性、得分
|
|
||||||
|
|
||||||
public string LabelDisplay { get; set; }//识别到对象的 显示信息
|
|
||||||
|
|
||||||
public double Area { get; set; }//识别目标的区域面积
|
|
||||||
|
|
||||||
public Rectangle Rect { get; set; }//识别目标的外接矩形
|
|
||||||
|
|
||||||
public RotatedRect MinRect { get; set; }//识别目标的最小外接矩形(带角度)
|
|
||||||
|
|
||||||
public ResultState InferenceResult { get; set; }//只是模型推理 label的结果
|
|
||||||
|
|
||||||
public double DistanceToImageCenter { get; set; } //计算矩形框到图像中心的距离
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
public ResultState FinalResult { get; set; }//模型推理+其他视觉、逻辑判断后 label结果
|
|
||||||
}
|
|
||||||
public class MLResult
|
|
||||||
{
|
|
||||||
public bool IsSuccess = false;
|
|
||||||
public string ResultMessage;
|
|
||||||
public Bitmap ResultMap;
|
|
||||||
public List<DetectionResultDetail> ResultDetails = new List<DetectionResultDetail>();
|
|
||||||
}
|
|
||||||
public class MLInit
|
|
||||||
{
|
|
||||||
public string ModelFile;
|
|
||||||
public string InferenceDevice;
|
|
||||||
|
|
||||||
|
|
||||||
public int InferenceWidth;
|
|
||||||
public int InferenceHeight;
|
|
||||||
|
|
||||||
public string InputNodeName;
|
|
||||||
|
|
||||||
|
|
||||||
public int SizeModel;
|
|
||||||
|
|
||||||
public bool bReverse;//尺寸测量正反面
|
|
||||||
//目标检测Gpu
|
|
||||||
public bool IsGPU;
|
|
||||||
public int GPUId;
|
|
||||||
public float Score_thre;
|
|
||||||
public MLInit(string modelFile, bool isGPU, int gpuId, float score_thre)
|
|
||||||
{
|
|
||||||
ModelFile = modelFile;
|
|
||||||
IsGPU = isGPU;
|
|
||||||
GPUId = gpuId;
|
|
||||||
Score_thre = score_thre;
|
|
||||||
}
|
|
||||||
|
|
||||||
public MLInit(string modelFile, string inputNodeName, string inferenceDevice, int inferenceWidth, int inferenceHeight)
|
|
||||||
{
|
|
||||||
ModelFile = modelFile;
|
|
||||||
InferenceDevice = inferenceDevice;
|
|
||||||
|
|
||||||
InferenceWidth = inferenceWidth;
|
|
||||||
InferenceHeight = inferenceHeight;
|
|
||||||
InputNodeName = inputNodeName;
|
|
||||||
|
|
||||||
|
|
||||||
}
|
|
||||||
}
|
|
||||||
public class DetectStationResult
|
|
||||||
{
|
|
||||||
public string Pid { get; set; }
|
|
||||||
|
|
||||||
public string TempPid { get; set; }
|
|
||||||
|
|
||||||
/// <summary>
|
|
||||||
/// 检测工位名称
|
|
||||||
/// </summary>
|
|
||||||
public string DetectName { get; set; }
|
|
||||||
|
|
||||||
|
|
||||||
/// <summary>
|
|
||||||
/// 深度学习 检测结果
|
|
||||||
/// </summary>
|
|
||||||
public List<DetectionResultDetail> DetectDetails = new List<DetectionResultDetail>();
|
|
||||||
|
|
||||||
|
|
||||||
/// <summary>
|
|
||||||
/// 工位检测结果
|
|
||||||
/// </summary>
|
|
||||||
public ResultState ResultState { get; set; } = ResultState.ResultTBD;
|
|
||||||
|
|
||||||
|
|
||||||
public double FinalResultfScore { get; set; } = 0.0;
|
|
||||||
|
|
||||||
|
|
||||||
public string ResultLabel { get; set; } = "";// 多个ng时，根据label优先级，设定当前检测项的label
|
|
||||||
|
|
||||||
public string ResultLabelCategoryId { get; set; } = "";// 多个ng时，根据label优先级，设定当前检测项的label
|
|
||||||
|
|
||||||
public int PreTreatState { get; set; }
|
|
||||||
public bool IsPreTreatDone { get; set; } = true;
|
|
||||||
|
|
||||||
public bool IsAfterTreatDone { get; set; } = true;
|
|
||||||
|
|
||||||
public bool IsMLDetectDone { get; set; } = true;
|
|
||||||
|
|
||||||
/// <summary>
|
|
||||||
/// 预处理阶段已经NG
|
|
||||||
/// </summary>
|
|
||||||
public bool IsPreTreatNG { get; set; } = false;
|
|
||||||
|
|
||||||
/// <summary>
|
|
||||||
/// 目标检测NG
|
|
||||||
/// </summary>
|
|
||||||
public bool IsObjectDetectNG { get; set; } = false;
|
|
||||||
|
|
||||||
public DateTime EndTime { get; set; }
|
|
||||||
|
|
||||||
public int StationDetectElapsed { get; set; }
|
|
||||||
public static string NormalizeAndClean(string input)
|
|
||||||
{
|
|
||||||
if (input == null) return null;
|
|
||||||
|
|
||||||
// Step 1: 标准化字符编码为 Form C (规范组合)
|
|
||||||
string normalizedString = input.Normalize(NormalizationForm.FormC);
|
|
||||||
|
|
||||||
// Step 2: 移除所有空白字符，包括制表符和换行符
|
|
||||||
string withoutWhitespace = Regex.Replace(normalizedString, @"\s+", "");
|
|
||||||
|
|
||||||
// Step 3: 移除控制字符 (Unicode 控制字符，范围 \u0000 - \u001F 和 \u007F)
|
|
||||||
string withoutControlChars = Regex.Replace(withoutWhitespace, @"[\u0000-\u001F\u007F]+", "");
|
|
||||||
|
|
||||||
// Step 4: 移除特殊的不可见字符（如零宽度空格等）
|
|
||||||
string cleanedString = Regex.Replace(withoutControlChars, @"[\u200B\u200C\u200D\uFEFF]+", "");
|
|
||||||
|
|
||||||
return cleanedString;
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
public class RelatedCamera
|
|
||||||
{
|
|
||||||
|
|
||||||
[Category("关联相机")]
|
|
||||||
[DisplayName("关联相机")]
|
|
||||||
[Description("关联相机描述")]
|
|
||||||
|
|
||||||
//[TypeConverter(typeof(CollectionCountConvert))]
|
|
||||||
public string CameraSourceId { get; set; } = "";
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
}
|
|
||||||
public class VisionEngine
|
|
||||||
{
|
|
||||||
[ReadOnly(true)]
|
|
||||||
public string Id { get; set; } = Guid.NewGuid().ToString();
|
|
||||||
|
|
||||||
|
|
||||||
[Category("检测配置")]
|
|
||||||
[DisplayName("检测配置名称")]
|
|
||||||
[Description("检测配置名称")]
|
|
||||||
public string Name { get; set; }
|
|
||||||
|
|
||||||
[Category("关联相机")]
|
|
||||||
[DisplayName("关联相机")]
|
|
||||||
[Description("关联相机描述")]
|
|
||||||
|
|
||||||
|
|
||||||
public string CameraSourceId { get; set; } = "";
|
|
||||||
|
|
||||||
|
|
||||||
[Category("关联相机集合")]
|
|
||||||
[DisplayName("关联相机集合")]
|
|
||||||
[Description("关联相机描述")]
|
|
||||||
//[TypeConverter(typeof(DeviceIdSelectorConverter<CameraBase>))]
|
|
||||||
|
|
||||||
public List<RelatedCamera> CameraCollects { get; set; } = new List<RelatedCamera>();
|
|
||||||
|
|
||||||
|
|
||||||
[Category("启用配置")]
|
|
||||||
[DisplayName("是否启用GPU检测")]
|
|
||||||
[Description("是否启用GPU检测")]
|
|
||||||
public bool IsEnableGPU { get; set; } = false;
|
|
||||||
|
|
||||||
[Category("2.中检测（深度学习）")]
|
|
||||||
[DisplayName("中检测-模型类型")]
|
|
||||||
[Description("模型类型：ImageClassification-图片分类；ObjectDetection：目标检测；Segmentation-图像分割")]
|
|
||||||
//[TypeConverter(typeof(EnumDescriptionConverter<MLModelType>))]
|
|
||||||
public MLModelType ModelType { get; set; } = MLModelType.ObjectDetection;
|
|
||||||
|
|
||||||
//[Category("2.中检测（深度学习）")]
|
|
||||||
//[DisplayName("中检测-GPU索引")]
|
|
||||||
//[Description("GPU索引")]
|
|
||||||
//public int GPUIndex { get; set; } = 0;
|
|
||||||
|
|
||||||
[Category("2.中检测（深度学习）")]
|
|
||||||
[DisplayName("中检测-模型文件路径")]
|
|
||||||
[Description("中处理 深度学习模型文件路径，路径中不可含有中文字符，一般情况可以只配置中检测模型，当需要先用预检测过滤一次时，请先配置好与预检测相关配置")]
|
|
||||||
|
|
||||||
public string ModelPath { get; set; }
|
|
||||||
|
|
||||||
public VisionEngine(string name, MLModelType modelType, string modelPath, bool isEnableGPU,string sCameraSourceId)
|
|
||||||
{
|
|
||||||
ModelPath = modelPath ?? string.Empty;
|
|
||||||
Name = name;
|
|
||||||
ModelType = modelType;
|
|
||||||
IsEnableGPU = isEnableGPU;
|
|
||||||
Id = Guid.NewGuid().ToString();
|
|
||||||
CameraSourceId = sCameraSourceId;
|
|
||||||
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
@ -17,60 +17,60 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Commons", "Commons", "{0AB4
|
|||||||
EndProject
|
EndProject
|
||||||
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "DH.Commons", "DH.Commons\DH.Commons.csproj", "{027373EC-C5CB-4161-8D43-AB6009371FDE}"
|
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "DH.Commons", "DH.Commons\DH.Commons.csproj", "{027373EC-C5CB-4161-8D43-AB6009371FDE}"
|
||||||
EndProject
|
EndProject
|
||||||
Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "DH.Devices.Vision", "DH.Devices.Vision\DH.Devices.Vision.csproj", "{97B55FCF-54A3-449E-8437-735E65C35291}"
|
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "DH.Devices.Vision", "DH.Devices.Vision\DH.Devices.Vision.csproj", "{97B55FCF-54A3-449E-8437-735E65C35291}"
|
||||||
EndProject
|
EndProject
|
||||||
Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "DH.Devices.Camera", "DH.Devices.Camera\DH.Devices.Camera.csproj", "{1378A932-1C25-40EF-BA31-A3463B23F4E5}"
|
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "DH.Devices.Camera", "DH.Devices.Camera\DH.Devices.Camera.csproj", "{1378A932-1C25-40EF-BA31-A3463B23F4E5}"
|
||||||
EndProject
|
EndProject
|
||||||
Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "DH.Devices.PLC", "DH.Devices.PLC\DH.Devices.PLC.csproj", "{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}"
|
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "DH.Devices.PLC", "DH.Devices.PLC\DH.Devices.PLC.csproj", "{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}"
|
||||||
EndProject
|
EndProject
|
||||||
Global
|
Global
|
||||||
GlobalSection(SolutionConfigurationPlatforms) = preSolution
|
GlobalSection(SolutionConfigurationPlatforms) = preSolution
|
||||||
Debug|Any CPU = Debug|Any CPU
|
Debug|Any CPU = Debug|Any CPU
|
||||||
Debug|X64 = Debug|X64
|
Debug|x64 = Debug|x64
|
||||||
Release|Any CPU = Release|Any CPU
|
Release|Any CPU = Release|Any CPU
|
||||||
Release|X64 = Release|X64
|
Release|x64 = Release|x64
|
||||||
EndGlobalSection
|
EndGlobalSection
|
||||||
GlobalSection(ProjectConfigurationPlatforms) = postSolution
|
GlobalSection(ProjectConfigurationPlatforms) = postSolution
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|X64.ActiveCfg = Debug|X64
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|x64.ActiveCfg = Debug|x64
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|X64.Build.0 = Debug|X64
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Debug|x64.Build.0 = Debug|x64
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|Any CPU.Build.0 = Release|Any CPU
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|Any CPU.Build.0 = Release|Any CPU
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|X64.ActiveCfg = Release|X64
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|x64.ActiveCfg = Release|x64
|
||||||
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|X64.Build.0 = Release|X64
|
{17CC10DC-9132-4A03-AADA-2D1070418C9B}.Release|x64.Build.0 = Release|x64
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|X64.ActiveCfg = Debug|X64
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|x64.ActiveCfg = Debug|x64
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|X64.Build.0 = Debug|X64
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Debug|x64.Build.0 = Debug|x64
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|Any CPU.Build.0 = Release|Any CPU
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|Any CPU.Build.0 = Release|Any CPU
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|X64.ActiveCfg = Release|X64
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|x64.ActiveCfg = Release|x64
|
||||||
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|X64.Build.0 = Release|X64
|
{027373EC-C5CB-4161-8D43-AB6009371FDE}.Release|x64.Build.0 = Release|x64
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|X64.ActiveCfg = Debug|X64
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|x64.ActiveCfg = Debug|x64
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|X64.Build.0 = Debug|X64
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Debug|x64.Build.0 = Debug|x64
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|Any CPU.Build.0 = Release|Any CPU
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|Any CPU.Build.0 = Release|Any CPU
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|X64.ActiveCfg = Release|X64
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|x64.ActiveCfg = Release|x64
|
||||||
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|X64.Build.0 = Release|X64
|
{97B55FCF-54A3-449E-8437-735E65C35291}.Release|x64.Build.0 = Release|x64
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|X64.ActiveCfg = Debug|x64
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|x64.ActiveCfg = Debug|x64
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|X64.Build.0 = Debug|x64
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Debug|x64.Build.0 = Debug|x64
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|Any CPU.Build.0 = Release|Any CPU
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|Any CPU.Build.0 = Release|Any CPU
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|X64.ActiveCfg = Release|x64
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|x64.ActiveCfg = Release|x64
|
||||||
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|X64.Build.0 = Release|x64
|
{1378A932-1C25-40EF-BA31-A3463B23F4E5}.Release|x64.Build.0 = Release|x64
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|Any CPU.Build.0 = Debug|Any CPU
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|X64.ActiveCfg = Debug|x64
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|x64.ActiveCfg = Debug|x64
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|X64.Build.0 = Debug|x64
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Debug|x64.Build.0 = Debug|x64
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|Any CPU.ActiveCfg = Release|Any CPU
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|Any CPU.Build.0 = Release|Any CPU
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|Any CPU.Build.0 = Release|Any CPU
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|X64.ActiveCfg = Release|x64
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|x64.ActiveCfg = Release|x64
|
||||||
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|X64.Build.0 = Release|x64
|
{458B2CF6-6F1B-4B8B-BB85-C6FD7F453A5D}.Release|x64.Build.0 = Release|x64
|
||||||
EndGlobalSection
|
EndGlobalSection
|
||||||
GlobalSection(SolutionProperties) = preSolution
|
GlobalSection(SolutionProperties) = preSolution
|
||||||
HideSolutionNode = FALSE
|
HideSolutionNode = FALSE
|
||||||
|
|||||||
@ -25,7 +25,7 @@
|
|||||||
|
|
||||||
<ItemGroup>
|
<ItemGroup>
|
||||||
<Reference Include="DVPCameraCS64">
|
<Reference Include="DVPCameraCS64">
|
||||||
<HintPath>..\X64\Debug\DVPCameraCS64.dll</HintPath>
|
<HintPath>..\x64\Debug\DVPCameraCS64.dll</HintPath>
|
||||||
</Reference>
|
</Reference>
|
||||||
</ItemGroup>
|
</ItemGroup>
|
||||||
|
|
||||||
|
|||||||
@ -13,6 +13,7 @@ using System;
|
|||||||
using System.CodeDom;
|
using System.CodeDom;
|
||||||
using System.Collections.Concurrent;
|
using System.Collections.Concurrent;
|
||||||
using System.Collections.Generic;
|
using System.Collections.Generic;
|
||||||
|
using System.Diagnostics;
|
||||||
using System.Drawing;
|
using System.Drawing;
|
||||||
using System.Linq;
|
using System.Linq;
|
||||||
using System.Runtime.InteropServices;
|
using System.Runtime.InteropServices;
|
||||||
@ -258,41 +259,111 @@ namespace DHSoftware
|
|||||||
public volatile int ProductNum_Total = 0;
|
public volatile int ProductNum_Total = 0;
|
||||||
public volatile int ProductNum_OK = 0;
|
public volatile int ProductNum_OK = 0;
|
||||||
private readonly object _cameraSummaryLock = new object();
|
private readonly object _cameraSummaryLock = new object();
|
||||||
|
List<DetectionConfig> detectionList = new List<DetectionConfig>();
|
||||||
|
public List<RecongnitionLabel> RecongnitionLabelList { get; set; } = new List<RecongnitionLabel>();
|
||||||
public DateTime sraerttime;
|
public DateTime sraerttime;
|
||||||
private void HandleStartButton()
|
private void HandleStartButton()
|
||||||
{
|
{
|
||||||
CurrentMachine = true;
|
CurrentMachine = true;
|
||||||
List<VisionEngine> detectionList = new List<VisionEngine>();
|
//[Category("深度学习检测配置")]
|
||||||
detectionList.Add(new VisionEngine("相机1", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam1"));
|
//[DisplayName("检测标签定义集合")]
|
||||||
detectionList.Add(new VisionEngine("相机2", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam2"));
|
//[Description("定义检测标签的集合，例如：Seg/Detection模式：断裂、油污、划伤...；Class模式：ok、ng、上面、下面、套环、正常...")]
|
||||||
detectionList.Add(new VisionEngine("相机3", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam3"));
|
//[TypeConverter(typeof(CollectionCountConvert))]
|
||||||
detectionList.Add(new VisionEngine("相机4", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam4"));
|
//[Editor(typeof(ComplexCollectionEditor<RecongnitionLabel>), typeof(UITypeEditor))]
|
||||||
|
RecongnitionLabel recongnition=new RecongnitionLabel
|
||||||
|
{
|
||||||
|
LabelName="youwu",
|
||||||
|
LabelDescription="油污",
|
||||||
|
LabelCategory="A_NG"
|
||||||
|
};
|
||||||
|
RecongnitionLabel recongnition2 = new RecongnitionLabel
|
||||||
|
{
|
||||||
|
LabelName = "youwu",
|
||||||
|
LabelDescription = "油污",
|
||||||
|
LabelCategory = "A_NG"
|
||||||
|
};
|
||||||
|
RecongnitionLabel recongnition3 = new RecongnitionLabel
|
||||||
|
{
|
||||||
|
LabelName = "youwu",
|
||||||
|
LabelDescription = "油污",
|
||||||
|
LabelCategory = "A_NG"
|
||||||
|
};
|
||||||
|
RecongnitionLabelList.Add(recongnition);
|
||||||
|
RecongnitionLabelList.Add(recongnition2);
|
||||||
|
RecongnitionLabelList.Add(recongnition3);
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
var det1 = new DetectionConfig("相机1", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam1");
|
||||||
|
var det2 = new DetectionConfig("相机2", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam2");
|
||||||
|
var det3 = new DetectionConfig("相机3", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam3");
|
||||||
|
var det4 = new DetectionConfig("相机4", MLModelType.ObjectDetection, @"D:\DHSoftware\DHSoftware\Models\yolov3.cfg", false, "Cam4");
|
||||||
|
List<RelatedCamera> CameraCollects=new List<RelatedCamera>();
|
||||||
|
CameraCollects.Add(new RelatedCamera("Cam1"));
|
||||||
|
List<RelatedCamera> CameraCollects2 = new List<RelatedCamera>();
|
||||||
|
CameraCollects2.Add(new RelatedCamera("Cam2"));
|
||||||
|
List<RelatedCamera> CameraCollects3 = new List<RelatedCamera>();
|
||||||
|
CameraCollects3.Add(new RelatedCamera("Cam3"));
|
||||||
|
List<RelatedCamera> CameraCollects4 = new List<RelatedCamera>();
|
||||||
|
CameraCollects4.Add(new RelatedCamera("Cam4"));
|
||||||
|
List<RelatedCamera> CameraCollects5 = new List<RelatedCamera>();
|
||||||
|
CameraCollects5.Add(new RelatedCamera("Cam5"));
|
||||||
|
float Conf = 0.5f;
|
||||||
|
det1.CameraCollects = CameraCollects;
|
||||||
|
det1.ModelconfThreshold = Conf;
|
||||||
|
det1.ModelWidth = 640;
|
||||||
|
det1.ModelHeight = 640;
|
||||||
|
det1.in_lable_path = " D:\\PROJECTS\\MaodingTest1\\Vision\\cam1.txt";
|
||||||
|
|
||||||
|
|
||||||
|
det2.CameraCollects = CameraCollects2;
|
||||||
|
det1.ModelconfThreshold = Conf;
|
||||||
|
det1.ModelWidth = 640;
|
||||||
|
det1.ModelHeight = 640;
|
||||||
|
det1.in_lable_path = " D:\\PROJECTS\\MaodingTest1\\Vision\\cam2.txt";
|
||||||
|
|
||||||
|
det3.CameraCollects = CameraCollects3;
|
||||||
|
det1.ModelconfThreshold = Conf;
|
||||||
|
det1.ModelWidth = 640;
|
||||||
|
det1.ModelHeight = 640;
|
||||||
|
det1.in_lable_path = " D:\\PROJECTS\\MaodingTest1\\Vision\\cam3.txt";
|
||||||
|
|
||||||
|
det4.CameraCollects = CameraCollects4;
|
||||||
|
det1.ModelconfThreshold = Conf;
|
||||||
|
det1.ModelWidth = 640;
|
||||||
|
det1.ModelHeight = 640;
|
||||||
|
det1.in_lable_path = " D:\\PROJECTS\\MaodingTest1\\Vision\\cam4.txt";
|
||||||
|
|
||||||
|
detectionList.Add(det1);
|
||||||
|
detectionList.Add(det2);
|
||||||
|
detectionList.Add(det3);
|
||||||
|
detectionList.Add(det4);
|
||||||
|
Cameras.Clear();
|
||||||
|
Dectection.Clear();
|
||||||
_cameraRelatedDetectionDict = new();
|
_cameraRelatedDetectionDict = new();
|
||||||
|
|
||||||
|
|
||||||
detectionList.ForEach(detection =>
|
detectionList.ForEach(detection =>
|
||||||
{
|
{
|
||||||
|
|
||||||
// detection.CameraCollects.ForEach(cam =>
|
detection.CameraCollects.ForEach(cam =>
|
||||||
{
|
{
|
||||||
List<string> Dets = new List<string>
|
List<string> Dets = new List<string>
|
||||||
{
|
{
|
||||||
detection.Id
|
detection.Id
|
||||||
};
|
};
|
||||||
if (!_cameraRelatedDetectionDict.ContainsKey(detection.CameraSourceId))
|
if (!_cameraRelatedDetectionDict.ContainsKey(cam.CameraSourceId))
|
||||||
{
|
{
|
||||||
_cameraRelatedDetectionDict.Add(detection.CameraSourceId, Dets);
|
_cameraRelatedDetectionDict.Add(cam.CameraSourceId, Dets);
|
||||||
}
|
}
|
||||||
else
|
else
|
||||||
{
|
{
|
||||||
_cameraRelatedDetectionDict[detection.CameraSourceId].Add(detection.Id);
|
_cameraRelatedDetectionDict[cam.CameraSourceId].Add(detection.Id);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
}
|
}
|
||||||
//);
|
);
|
||||||
});
|
});
|
||||||
|
|
||||||
//Add the code for the "启动" button click here
|
//Add the code for the "启动" button click here
|
||||||
@ -310,10 +381,7 @@ namespace DHSoftware
|
|||||||
do3ThinkCamera2.CameraConnect();
|
do3ThinkCamera2.CameraConnect();
|
||||||
do3ThinkCamera1.OnHImageOutput += OnCameraHImageOutput;
|
do3ThinkCamera1.OnHImageOutput += OnCameraHImageOutput;
|
||||||
do3ThinkCamera2.OnHImageOutput += OnCameraHImageOutput;
|
do3ThinkCamera2.OnHImageOutput += OnCameraHImageOutput;
|
||||||
var simbo1 = new SimboObjectDetection
|
var simbo1 = new SimboObjectDetection();
|
||||||
{
|
|
||||||
|
|
||||||
};
|
|
||||||
MLInit mLInit;
|
MLInit mLInit;
|
||||||
string inferenceDevice = "CPU";
|
string inferenceDevice = "CPU";
|
||||||
|
|
||||||
@ -321,12 +389,11 @@ namespace DHSoftware
|
|||||||
|
|
||||||
|
|
||||||
simbo1.Load(mLInit);
|
simbo1.Load(mLInit);
|
||||||
Dectection.Add(do3ThinkCamera1.CameraName, simbo1);
|
|
||||||
|
|
||||||
var simbo2 = new SimboObjectDetection
|
|
||||||
{
|
|
||||||
|
|
||||||
};
|
Dectection.Add(det1.Id, simbo1);
|
||||||
|
|
||||||
|
var simbo2 = new SimboObjectDetection();
|
||||||
MLInit mLInit2;
|
MLInit mLInit2;
|
||||||
string inferenceDevice2 = "CPU";
|
string inferenceDevice2 = "CPU";
|
||||||
|
|
||||||
@ -334,7 +401,11 @@ namespace DHSoftware
|
|||||||
|
|
||||||
|
|
||||||
simbo2.Load(mLInit2);
|
simbo2.Load(mLInit2);
|
||||||
Dectection.Add(do3ThinkCamera2.CameraName, simbo2);
|
for(int i = 0;i<Dectection.Count;i++)
|
||||||
|
{
|
||||||
|
|
||||||
|
}
|
||||||
|
Dectection.Add(det1.Id, simbo2);
|
||||||
|
|
||||||
PLC.IP = "192.168.6.6";
|
PLC.IP = "192.168.6.6";
|
||||||
PLC.Port = 502;
|
PLC.Port = 502;
|
||||||
@ -375,10 +446,7 @@ namespace DHSoftware
|
|||||||
|
|
||||||
PieceCount++;
|
PieceCount++;
|
||||||
|
|
||||||
Task.Run(() => {
|
|
||||||
this.BeginInvoke(new MethodInvoker(delegate () { richTextBox1.AppendText("入料成功" + PieceCount); }));
|
|
||||||
|
|
||||||
});
|
|
||||||
int index = PieceNumberToIndex(pieceNumber);
|
int index = PieceNumberToIndex(pieceNumber);
|
||||||
// productDatas.Add(pData);
|
// productDatas.Add(pData);
|
||||||
//转盘2 的物料是不是重新覆盖之前的pDta
|
//转盘2 的物料是不是重新覆盖之前的pDta
|
||||||
@ -387,6 +455,11 @@ namespace DHSoftware
|
|||||||
ProductData pData = new ProductData("", pieceNumber, ProductBaseCount);
|
ProductData pData = new ProductData("", pieceNumber, ProductBaseCount);
|
||||||
_productLists[index][pieceNumber] = pData;
|
_productLists[index][pieceNumber] = pData;
|
||||||
}
|
}
|
||||||
|
string logStr = $"时间：{DateTime.Now} 轴{axisIndex}新产品{pieceNumber}加入队列{index}----入料计数{PieceCount}\n";
|
||||||
|
Task.Run(() => {
|
||||||
|
this.BeginInvoke(new MethodInvoker(delegate () { richTextBox1.AppendText(logStr); }));
|
||||||
|
|
||||||
|
});
|
||||||
DateTime dtNow = DateTime.Now;
|
DateTime dtNow = DateTime.Now;
|
||||||
UpdateCT(null, (float)(dtNow - _ctTime).TotalSeconds);
|
UpdateCT(null, (float)(dtNow - _ctTime).TotalSeconds);
|
||||||
_ctTime = dtNow;
|
_ctTime = dtNow;
|
||||||
@ -472,28 +545,173 @@ namespace DHSoftware
|
|||||||
|
|
||||||
for (int i = 0; i < detectionDict.Count; i++)
|
for (int i = 0; i < detectionDict.Count; i++)
|
||||||
{
|
{
|
||||||
string d = detectionDict[i];
|
string detectionId = detectionDict[i];
|
||||||
try
|
try
|
||||||
{
|
{
|
||||||
|
DetectionConfig detectConfig = null;
|
||||||
|
//找到对应的配置
|
||||||
|
if (!string.IsNullOrWhiteSpace(detectionId))
|
||||||
|
{
|
||||||
|
detectConfig = detectionList.FirstOrDefault(u => u.Id == detectionId);
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
detectConfig = detectionList.FirstOrDefault(u => u.CameraSourceId == camera.CameraName);
|
||||||
|
}
|
||||||
|
|
||||||
// LogAsync(DateTime.Now, LogLevel.Information, $"{camera.Name} 推理进度1.3，产品{productNumber}");
|
if (detectConfig == null)
|
||||||
|
{
|
||||||
|
|
||||||
|
//未能获得检测配置
|
||||||
|
return ;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
#region 1.预处理
|
||||||
|
#endregion
|
||||||
|
#region 2.深度学习推理
|
||||||
var req = new MLRequest();
|
var req = new MLRequest();
|
||||||
|
|
||||||
req.mImage = imageSet.Clone();
|
req.mImage = imageSet.Clone();
|
||||||
req.ResizeWidth = 640;
|
req.ResizeWidth = detectConfig.ModelWidth;
|
||||||
req.ResizeHeight = 640;
|
req.ResizeHeight = detectConfig.ModelHeight;
|
||||||
req.confThreshold = 0.5f;
|
req.confThreshold = detectConfig.ModelconfThreshold;
|
||||||
req.iouThreshold = 0.3f;
|
req.iouThreshold = 0.3f;
|
||||||
req.out_node_name = "output0";
|
req.out_node_name = detectConfig.ModeloutNodeName;
|
||||||
req.in_lable_path = "D:\\PROJECTS\\MaodingTest1\\Vision\\cam1.txt";
|
req.in_lable_path = detectConfig.in_lable_path;
|
||||||
//req.LabelNames = dc.GetLabelNames();
|
//req.LabelNames = dc.GetLabelNames();
|
||||||
req.Score = 0.5f;
|
|
||||||
//HOperatorSet.WriteImage(req.HImage, "png", 0, @"D:\\666.png");
|
//HOperatorSet.WriteImage(req.HImage, "png", 0, @"D:\\666.png");
|
||||||
var result = Dectection[camera.CameraName].RunInference(req);
|
Stopwatch
|
||||||
|
sw = new Stopwatch();
|
||||||
|
sw.Start();
|
||||||
|
|
||||||
this.BeginInvoke(new MethodInvoker(delegate () {
|
|
||||||
pictureBox1.Image = result.ResultMap; richTextBox1.AppendText("推理成功" + productNumber+ result.IsSuccess+ "\n"); }));
|
|
||||||
|
|
||||||
|
var result = Dectection[detectionId].RunInference(req);
|
||||||
|
sw.Stop();
|
||||||
|
//LogAsync(DateTime.Now, LogLevel.Information, $"{camera.Name} 推理进度1.1，产品{productNumber}，耗时{sw.ElapsedMilliseconds}ms");
|
||||||
|
#endregion
|
||||||
|
#region 3.后处理
|
||||||
|
DetectStationResult detectResult = new DetectStationResult();
|
||||||
|
if (result == null || (result != null && !result.IsSuccess))
|
||||||
|
{
|
||||||
|
detectResult.IsMLDetectDone = false;
|
||||||
|
}
|
||||||
|
if (result != null && result.IsSuccess)
|
||||||
|
{
|
||||||
|
detectResult.DetectDetails = result.ResultDetails;
|
||||||
|
if (detectResult.DetectDetails != null)
|
||||||
|
{
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
detectResult.IsMLDetectDone = false;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
#endregion
|
||||||
|
#region 3.后处理
|
||||||
|
#endregion
|
||||||
|
//根据那些得分大于阈值的推理结果，判断产品是否成功
|
||||||
|
#region 4.最终过滤（逻辑过滤）
|
||||||
|
detectResult.DetectDetails?.ForEach(d =>
|
||||||
|
{
|
||||||
|
|
||||||
|
|
||||||
|
//当前检测项的 过滤条件
|
||||||
|
//var conditionList = detectConfig.DetectionFilterList
|
||||||
|
// .Where(u => u.IsEnabled && u.LabelName == d.LabelName)
|
||||||
|
// .GroupBy(u => u.ResultState)
|
||||||
|
// .OrderBy(u => u.Key)
|
||||||
|
// .ToList();
|
||||||
|
//当前检测项的 过滤条件
|
||||||
|
var conditionList = detectConfig.DetectionFilterList
|
||||||
|
.Where(u => u.IsEnabled && u.LabelName == d.LabelName)
|
||||||
|
.GroupBy(u => u.ResultState)
|
||||||
|
.OrderBy(u => u.Key)
|
||||||
|
.ToList();
|
||||||
|
|
||||||
|
if (conditionList.Count == 0)
|
||||||
|
{
|
||||||
|
|
||||||
|
if (d.LabelName.ToLower() == "ok")
|
||||||
|
{
|
||||||
|
d.FinalResult = d.InferenceResult = ResultState.OK;
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
d.FinalResult = d.InferenceResult = ResultState.DetectNG;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
if (detectConfig.IsMixModel)
|
||||||
|
{
|
||||||
|
d.FinalResult = d.InferenceResult = ResultState.A_NG;
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
//将所有已将筛选出来的缺陷进行过滤
|
||||||
|
d.FinalResult = d.InferenceResult = ResultState.OK;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
foreach (IGrouping<ResultState, DetectionFilter> group in conditionList)
|
||||||
|
{
|
||||||
|
bool b = group.ToList().Any(f =>
|
||||||
|
{
|
||||||
|
return f.FilterOperation(d);
|
||||||
|
});
|
||||||
|
|
||||||
|
|
||||||
|
if (b)
|
||||||
|
{
|
||||||
|
d.FinalResult = group.Key;
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
//else
|
||||||
|
//{
|
||||||
|
// d.FinalResult = d.InferenceResult = ResultState.OK;
|
||||||
|
//}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
#endregion
|
||||||
|
#region 5.统计缺陷过滤结果或预处理直接NG
|
||||||
|
if (detectResult.DetectDetails?.Count > 0)
|
||||||
|
{
|
||||||
|
detectResult.ResultState = detectResult.DetectDetails.GroupBy(u => u.FinalResult).OrderBy(u => u.Key).First().First().FinalResult;
|
||||||
|
detectResult.ResultLabel = detectResult.ResultLabel;
|
||||||
|
detectResult.ResultLabelCategoryId = detectResult.ResultLabel;//TODO:设置优先级
|
||||||
|
//////根据优先级设置ResultLabel
|
||||||
|
//if (detectionLabels.Count > 0)
|
||||||
|
//{
|
||||||
|
// foreach (var l in detectionLabels)
|
||||||
|
// {
|
||||||
|
// var isExist = DetectDetails.Any(o => NormalizeAndClean(o.LabelName) == NormalizeAndClean(l.LabelName) && o.FinalResult == ResultState.DetectNG);
|
||||||
|
// if (isExist)
|
||||||
|
// {
|
||||||
|
|
||||||
|
// ResultLabelCategoryId = l.LabelCategoryId;
|
||||||
|
// break;
|
||||||
|
// }
|
||||||
|
// }
|
||||||
|
//}
|
||||||
|
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
#endregion
|
||||||
|
|
||||||
|
|
||||||
|
resultStates.Add(detectResult.ResultState);
|
||||||
|
|
||||||
|
product.ResultCollection.Add(detectResult);
|
||||||
|
this.BeginInvoke(new MethodInvoker(delegate ()
|
||||||
|
{
|
||||||
|
pictureBox1.Image = result.ResultMap; richTextBox1.AppendText($"推理成功{productNumber}，{result.IsSuccess} 推理耗时{sw.ElapsedMilliseconds}ms，总推理耗时\n");
|
||||||
|
|
||||||
|
}));
|
||||||
//DetectStationResult temp;
|
//DetectStationResult temp;
|
||||||
////LogAsync(DateTime.Now, LogLevel.Information, $"{camera.Name} 推理进度1.4，产品{productNumber}");
|
////LogAsync(DateTime.Now, LogLevel.Information, $"{camera.Name} 推理进度1.4，产品{productNumber}");
|
||||||
//// 检测结果
|
//// 检测结果
|
||||||
@ -541,10 +759,7 @@ namespace DHSoftware
|
|||||||
|
|
||||||
if (!product.InferenceFinished())
|
if (!product.InferenceFinished())
|
||||||
{
|
{
|
||||||
//if (!(camera.Name == "Cam8"))
|
|
||||||
//{
|
|
||||||
// return;
|
|
||||||
//}
|
|
||||||
return;
|
return;
|
||||||
}
|
}
|
||||||
ProductNum_Total++;
|
ProductNum_Total++;
|
||||||
@ -559,6 +774,30 @@ namespace DHSoftware
|
|||||||
richTextBox1.SelectionStart = richTextBox1.TextLength;
|
richTextBox1.SelectionStart = richTextBox1.TextLength;
|
||||||
richTextBox1.ScrollToCaret();
|
richTextBox1.ScrollToCaret();
|
||||||
}));
|
}));
|
||||||
|
#region 6.统计产品结果
|
||||||
|
if (product.ResultCollection.Any(u => u.ResultState != ResultState.OK))
|
||||||
|
{
|
||||||
|
//检测结果TBD
|
||||||
|
// CurTrigger = TriggerSettings.FirstOrDefault(u => u.TriggerType == TriggerType.B_NG);
|
||||||
|
product.ProductResult = ResultState.B_NG;
|
||||||
|
product.ProductLabelCategory = ResultState.B_NG.GetEnumDescription();
|
||||||
|
product.ProductLabel = ResultState.B_NG.GetEnumDescription();
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
// CurTrigger = TriggerSettings.FirstOrDefault(u => u.TriggerType == TriggerType.OK);
|
||||||
|
product.ProductResult = ResultState.OK;
|
||||||
|
product.ProductLabelCategory = ResultState.OK.GetEnumDescription();
|
||||||
|
product.ProductLabel = ResultState.OK.GetEnumDescription();
|
||||||
|
}
|
||||||
|
#endregion
|
||||||
|
#region 7.产品吹气
|
||||||
|
|
||||||
|
#endregion
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
//LogAsync(DateTime.Now, LogLevel.Information, $"推理完成，产品{product.PieceNumber}获取结果");
|
//LogAsync(DateTime.Now, LogLevel.Information, $"推理完成，产品{product.PieceNumber}获取结果");
|
||||||
|
|
||||||
@ -661,9 +900,19 @@ namespace DHSoftware
|
|||||||
|
|
||||||
if (isSuccess)
|
if (isSuccess)
|
||||||
{
|
{
|
||||||
// LogAsync(DateTime.Now, LogLevel.Assist, $"产品{productNumber}出列成功：{isSuccess}，" +
|
string logStr =$"{DateTime.Now}产品{productNumber}出列成功：{isSuccess}，" +
|
||||||
//$"产品结果：{temp.ProductResult.GetEnumDescription()}，" +
|
$"产品结果：{temp.ProductResult.GetEnumDescription()}，" +
|
||||||
//$"当前队列产品数量：{tmpDic.Count}");
|
$"当前队列产品数量：{tmpDic.Count}";
|
||||||
|
this.BeginInvoke(new MethodInvoker(delegate () {
|
||||||
|
|
||||||
|
int currentScrollPosition = richTextBox1.GetPositionFromCharIndex(richTextBox1.TextLength).Y;
|
||||||
|
|
||||||
|
richTextBox1.AppendText(logStr);
|
||||||
|
|
||||||
|
// 设置回原来的滚动位置
|
||||||
|
richTextBox1.SelectionStart = richTextBox1.TextLength;
|
||||||
|
richTextBox1.ScrollToCaret();
|
||||||
|
}));
|
||||||
}
|
}
|
||||||
tryTimes--;
|
tryTimes--;
|
||||||
Thread.Sleep(1);
|
Thread.Sleep(1);
|
||||||
@ -703,6 +952,29 @@ namespace DHSoftware
|
|||||||
}
|
}
|
||||||
});
|
});
|
||||||
}
|
}
|
||||||
|
public void SetResult()
|
||||||
|
{
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
//// detectResult.IsPreTreatDone = detectResult.VisionImageSet.PreTreatedFlag
|
||||||
|
////2024-02-29 目标检测不能全是NG
|
||||||
|
//if (IsPreTreatNG || IsObjectDetectNG)
|
||||||
|
//{
|
||||||
|
// return;
|
||||||
|
//}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
//if (IsPreTreatDone && IsMLDetectDone && IsAfterTreatDone)
|
||||||
|
//{
|
||||||
|
// ResultState = ResultState.OK;
|
||||||
|
// ResultLabel = ResultState.OK.GetEnumDescription();
|
||||||
|
//}
|
||||||
|
|
||||||
|
}
|
||||||
private void HandleStopButton()
|
private void HandleStopButton()
|
||||||
{
|
{
|
||||||
Cameras.Clear();
|
Cameras.Clear();
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user