李伟
254 lines
9.6 KiB
C#
254 lines
9.6 KiB
C#
// ============================================================================
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// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
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// 文件名: ContourProcessor.cs
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// 描述: 轮廓查找算子，用于检测和分析图像中的轮廓
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// 功能:
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// - 检测图像中的外部轮廓
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// - 根据面积范围过滤轮廓
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// - 计算轮廓的几何特征（面积、周长、中心、外接矩形等）
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// - 输出轮廓信息供后续处理使用
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// 算法: 基于OpenCV的轮廓检测算法
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// 作者: 李伟 wei.lw.li@hexagon.com
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// ============================================================================
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using Emgu.CV;
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using Emgu.CV.CvEnum;
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using Emgu.CV.Structure;
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using Emgu.CV.Util;
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using XP.ImageProcessing.Core;
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using Serilog;
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using System.Drawing;
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namespace XP.ImageProcessing.Processors;
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/// <summary>
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/// 轮廓查找算子
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/// </summary>
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public class ContourProcessor : ImageProcessorBase
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{
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private static readonly ILogger _logger = Log.ForContext<ContourProcessor>();
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public ContourProcessor()
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{
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Name = LocalizationHelper.GetString("ContourProcessor_Name");
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Description = LocalizationHelper.GetString("ContourProcessor_Description");
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}
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protected override void InitializeParameters()
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{
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Parameters.Add("TargetColor", new ProcessorParameter(
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"TargetColor",
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LocalizationHelper.GetString("ContourProcessor_TargetColor"),
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typeof(string),
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"White",
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null,
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null,
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LocalizationHelper.GetString("ContourProcessor_TargetColor_Desc"),
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new string[] { "White", "Black" }));
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Parameters.Add("UseThreshold", new ProcessorParameter(
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"UseThreshold",
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LocalizationHelper.GetString("ContourProcessor_UseThreshold"),
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typeof(bool),
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false,
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null,
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null,
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LocalizationHelper.GetString("ContourProcessor_UseThreshold_Desc")));
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Parameters.Add("ThresholdValue", new ProcessorParameter(
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"ThresholdValue",
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LocalizationHelper.GetString("ContourProcessor_ThresholdValue"),
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typeof(int),
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120,
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0,
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255,
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LocalizationHelper.GetString("ContourProcessor_ThresholdValue_Desc")));
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Parameters.Add("UseOtsu", new ProcessorParameter(
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"UseOtsu",
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LocalizationHelper.GetString("ContourProcessor_UseOtsu"),
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typeof(bool),
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false,
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null,
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null,
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LocalizationHelper.GetString("ContourProcessor_UseOtsu_Desc")));
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Parameters.Add("MinArea", new ProcessorParameter(
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"MinArea",
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LocalizationHelper.GetString("ContourProcessor_MinArea"),
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typeof(double),
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10.0,
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0.0,
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10000.0,
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LocalizationHelper.GetString("ContourProcessor_MinArea_Desc")));
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Parameters.Add("MaxArea", new ProcessorParameter(
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"MaxArea",
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LocalizationHelper.GetString("ContourProcessor_MaxArea"),
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typeof(double),
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100000.0,
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0.0,
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1000000.0,
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LocalizationHelper.GetString("ContourProcessor_MaxArea_Desc")));
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Parameters.Add("Thickness", new ProcessorParameter(
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"Thickness",
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LocalizationHelper.GetString("ContourProcessor_Thickness"),
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typeof(int),
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2,
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1,
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10,
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LocalizationHelper.GetString("ContourProcessor_Thickness_Desc")));
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_logger.Debug("InitializeParameters");
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}
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public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
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{
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string targetColor = GetParameter<string>("TargetColor");
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bool useThreshold = GetParameter<bool>("UseThreshold");
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int thresholdValue = GetParameter<int>("ThresholdValue");
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bool useOtsu = GetParameter<bool>("UseOtsu");
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double minArea = GetParameter<double>("MinArea");
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double maxArea = GetParameter<double>("MaxArea");
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int thickness = GetParameter<int>("Thickness");
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_logger.Debug("Process started: TargetColor = '{TargetColor}', UseThreshold = {UseThreshold}, ThresholdValue = {ThresholdValue}, UseOtsu = {UseOtsu}",
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targetColor, useThreshold, thresholdValue, useOtsu);
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OutputData.Clear();
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// 创建输入图像的副本用于处理
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Image<Gray, byte> processImage = inputImage.Clone();
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// 步骤1：如果启用阈值分割，先进行二值化
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if (useThreshold)
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{
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_logger.Debug("Applying threshold processing");
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Image<Gray, byte> thresholdImage = new Image<Gray, byte>(processImage.Size);
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if (useOtsu)
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{
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// 使用Otsu自动阈值
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CvInvoke.Threshold(processImage, thresholdImage, 0, 255, ThresholdType.Otsu);
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_logger.Debug("Applied Otsu threshold");
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}
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else
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{
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// 使用固定阈值
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CvInvoke.Threshold(processImage, thresholdImage, thresholdValue, 255, ThresholdType.Binary);
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_logger.Debug("Applied binary threshold with value {ThresholdValue}", thresholdValue);
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}
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// 保存阈值处理后的图像用于调试
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try
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{
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string debugPath = Path.Combine("logs", $"contour_threshold_{DateTime.Now:yyyyMMdd_HHmmss}.png");
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Directory.CreateDirectory("logs");
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thresholdImage.Save(debugPath);
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_logger.Information("Saved threshold image to: {DebugPath}", debugPath);
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}
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catch (Exception ex)
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{
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_logger.Warning(ex, "Failed to save threshold image for debugging");
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}
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processImage.Dispose();
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processImage = thresholdImage;
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}
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// 步骤2：如果目标是黑色区域，需要反转图像
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bool isBlackTarget = targetColor != null &&
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(targetColor.Equals("Black", StringComparison.OrdinalIgnoreCase) ||
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targetColor.Equals("黑色", StringComparison.OrdinalIgnoreCase));
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if (isBlackTarget)
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{
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_logger.Debug("Inverting image for black region detection");
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CvInvoke.BitwiseNot(processImage, processImage);
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// 保存翻转后的图像用于调试
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try
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{
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string debugPath = Path.Combine("logs", $"contour_inverted_{DateTime.Now:yyyyMMdd_HHmmss}.png");
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Directory.CreateDirectory("logs");
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processImage.Save(debugPath);
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_logger.Information("Saved inverted image to: {DebugPath}", debugPath);
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}
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catch (Exception ex)
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{
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_logger.Warning(ex, "Failed to save inverted image for debugging");
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}
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}
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// 步骤3：查找轮廓
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using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
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{
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Mat hierarchy = new Mat();
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CvInvoke.FindContours(processImage, contours, hierarchy, RetrType.External, ChainApproxMethod.ChainApproxSimple);
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_logger.Debug("Found {TotalContours} total contours before filtering", contours.Size);
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List<ContourInfo> contourInfos = new();
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for (int i = 0; i < contours.Size; i++)
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{
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double area = CvInvoke.ContourArea(contours[i]);
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if (area >= minArea && area <= maxArea)
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{
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var moments = CvInvoke.Moments(contours[i]);
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var boundingRect = CvInvoke.BoundingRectangle(contours[i]);
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double perimeter = CvInvoke.ArcLength(contours[i], true);
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var circle = CvInvoke.MinEnclosingCircle(contours[i]);
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contourInfos.Add(new ContourInfo
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{
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Index = i,
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Area = area,
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Perimeter = perimeter,
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CenterX = moments.M10 / moments.M00,
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CenterY = moments.M01 / moments.M00,
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BoundingBox = boundingRect,
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Points = contours[i].ToArray(),
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CircleCenter = circle.Center,
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CircleRadius = circle.Radius
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});
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_logger.Debug("Contour {Index}: Area = {Area}, Center = ({CenterX:F2}, {CenterY:F2})",
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i, area, moments.M10 / moments.M00, moments.M01 / moments.M00);
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}
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else
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{
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_logger.Debug("Contour {Index} filtered out: Area = {Area} (not in range {MinArea} - {MaxArea})",
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i, area, minArea, maxArea);
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}
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}
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OutputData["ContourCount"] = contourInfos.Count;
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OutputData["Contours"] = contourInfos;
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OutputData["Thickness"] = thickness;
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hierarchy.Dispose();
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processImage.Dispose();
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_logger.Information("Process completed: TargetColor = '{TargetColor}', Found {ContourCount} contours (filtered from {TotalContours})",
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targetColor, contourInfos.Count, contours.Size);
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return inputImage.Clone();
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}
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}
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}
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/// <summary>
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/// 轮廓信息
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/// </summary>
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public class ContourInfo
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{
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public int Index { get; set; }
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public double Area { get; set; }
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public double Perimeter { get; set; }
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public double CenterX { get; set; }
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public double CenterY { get; set; }
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public Rectangle BoundingBox { get; set; }
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public Point[] Points { get; set; } = Array.Empty<Point>();
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public PointF CircleCenter { get; set; }
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public float CircleRadius { get; set; }
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} |