667 lines
22 KiB
C#
667 lines
22 KiB
C#
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;
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型节点名称")]
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[Description("中处理-模型节点名称")]
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public string ModeloutNodeName { get; set; } = "output0";
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型置信度")]
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[Description("中处理-模型置信度")]
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public float ModelconfThreshold { get; set; } = 0.5f;
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[Category("2.中检测（深度学习）")]
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[DisplayName("中检测-模型标签路径")]
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[Description("中处理-模型标签路径")]
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public string in_lable_path { get; set; }
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[Category("4.最终过滤（逻辑过滤）")]
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[DisplayName("过滤器集合")]
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[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")]
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public List<DetectionFilter> DetectionFilterList { get; set; } = new List<DetectionFilter>();
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//[Category("深度学习配置")]
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//[DisplayName("检测配置标签")]
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//[Description("检测配置标签关联")]
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//public List<DetectConfigLabel> DetectConfigLabelList { get; set; } = new List<DetectConfigLabel>();
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public DetectionConfig()
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{
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}
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public DetectionConfig(string name, MLModelType modelType, string modelPath, bool isEnableGPU,string sCameraSourceId)
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{
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ModelPath = modelPath ?? string.Empty;
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Name = name;
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ModelType = modelType;
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IsEnableGPU = isEnableGPU;
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Id = Guid.NewGuid().ToString();
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CameraSourceId = sCameraSourceId;
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}
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}
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/// <summary>
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/// 识别目标定义 class：分类信息 Detection Segmentation：要识别的对象
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/// </summary>
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public class RecongnitionLabel //: IComplexDisplay
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{
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[Category("检测标签定义")]
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[Description("检测标签编码")]
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[ReadOnly(true)]
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public string Id { get; set; } = Guid.NewGuid().ToString();
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[Category("检测标签定义")]
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[DisplayName("检测标签名称")]
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[Description("检测标签名称")]
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public string LabelName { get; set; } = "";
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[Category("检测标签定义")]
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[DisplayName("检测标签描述")]
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[Description("检测标签描述，中文描述")]
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public string LabelDescription { get; set; } = "";
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[Category("检测标签定义")]
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[DisplayName("检测标签分类")]
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[Description("检测标签分类id")]
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//[TypeConverter(typeof(LabelCategoryConverter))]
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public string LabelCategory { get; set; } = "";
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}
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/// <summary>
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/// 检测项识别对象
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/// </summary>
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public class DetectConfigLabel //: IComplexDisplay
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{
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[Category("检测项标签")]
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[DisplayName("检测项标签")]
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[Description("检测标签Id")]
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//[TypeConverter(typeof(DetectionLabelConverter))]
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public string LabelId { get; set; }
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[Browsable(false)]
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//public string LabelName { get => GetLabelName(); }
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[Category("检测项标签")]
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[DisplayName("检测标签优先级")]
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[Description("检测标签优先级，值越小，优先级越高")]
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public int LabelPriority { get; set; } = 0;
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//[Category("检测项标签")]
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//[DisplayName("标签BGR值")]
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//[Description("检测标签BGR值，例如：0,128,0")]
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//public string LabelBGR { 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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//[TypeConverter(typeof(ComplexObjectConvert))]
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//[Editor(typeof(PropertyObjectEditor), typeof(UITypeEditor))]
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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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// string dName = "";
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// if (!string.IsNullOrWhiteSpace(LabelId))
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// {
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// using (var scope = GlobalVar.Container.BeginLifetimeScope())
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// {
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// IProcessConfig config = scope.Resolve<IProcessConfig>();
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// var mlBase = config.DeviceConfigs.FirstOrDefault(c => c is VisionEngineInitialConfigBase) as VisionEngineInitialConfigBase;
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// if (mlBase != null)
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// {
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// var targetLabel = mlBase.RecongnitionLabelList.FirstOrDefault(u => u.Id == LabelId);
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// if (targetLabel != null)
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// {
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// dName = targetLabel.GetDisplayText();
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// }
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// }
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// }
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// }
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// return dName;
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//}
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//public string GetLabelName()
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//{
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// var name = "";
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// var mlBase = iConfig.DeviceConfigs.FirstOrDefault(c => c is VisionEngineInitialConfigBase) as VisionEngineInitialConfigBase;
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// if (mlBase != null)
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// {
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// var label = mlBase.RecongnitionLabelList.FirstOrDefault(u => u.Id == LabelId);
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// if (label != null)
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// {
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// name = label.LabelName;
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// }
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// }
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// return name;
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//}
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}
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/// <summary>
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/// 识别对象定义分类信息 A类B类
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/// </summary>
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public class RecongnitionLabelCategory //: IComplexDisplay
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{
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[Category("检测标签分类")]
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[Description("检测标签分类")]
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[ReadOnly(true)]
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public string Id { get; set; } = Guid.NewGuid().ToString();
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[Category("检测标签分类")]
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[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,
|
||
}
|
||
}
|