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规范类名及命名空间名称

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李伟
2026-04-13 14:35:37 +08:00
parent c430ec229b
commit ace1c70ddf
217 changed files with 1271 additions and 1384 deletions
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XP.ImageProcessing.Processors/检测分析/VoidMeasurementProcessor.cs
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// ============================================================================
// 文件� VoidMeasurementProcessor.cs
// �述: 空隙测�算�
//
// 处��程:
// 1. 构建多边形ROI掩�，计算ROI�积
// 2. 在ROI内进行�阈值分割��气泡区�
// 3. 形�学膨胀�并相邻气泡
// 4. 轮廓检测，计算�个气泡�积
// 5. 计算空隙�= 总气泡��/ ROI�积
// ============================================================================
using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Structure;
using Emgu.CV.Util;
using Serilog;
using System.Drawing;
using XP.ImageProcessing.Core;
namespace XP.ImageProcessing.Processors;
public class VoidMeasurementProcessor : ImageProcessorBase
{
private static readonly ILogger _logger = Log.ForContext<VoidMeasurementProcessor>();
public VoidMeasurementProcessor()
{
Name = LocalizationHelper.GetString("VoidMeasurementProcessor_Name");
Description = LocalizationHelper.GetString("VoidMeasurementProcessor_Description");
}
protected override void InitializeParameters()
{
// ── 多边形ROI（由UI注入，最�2个点�──
Parameters.Add("PolyCount", new ProcessorParameter("PolyCount", "PolyCount", typeof(int), 0, null, null, "") { IsVisible = false });
for (int i = 0; i < 32; i++)
{
Parameters.Add($"PolyX{i}", new ProcessorParameter($"PolyX{i}", $"PolyX{i}", typeof(int), 0, null, null, "") { IsVisible = false });
Parameters.Add($"PolyY{i}", new ProcessorParameter($"PolyY{i}", $"PolyY{i}", typeof(int), 0, null, null, "") { IsVisible = false });
}
// ── 气泡检测��──
Parameters.Add("MinThreshold", new ProcessorParameter(
"MinThreshold",
LocalizationHelper.GetString("VoidMeasurementProcessor_MinThreshold"),
typeof(int), 128, 0, 255,
LocalizationHelper.GetString("VoidMeasurementProcessor_MinThreshold_Desc")));
Parameters.Add("MaxThreshold", new ProcessorParameter(
"MaxThreshold",
LocalizationHelper.GetString("VoidMeasurementProcessor_MaxThreshold"),
typeof(int), 255, 0, 255,
LocalizationHelper.GetString("VoidMeasurementProcessor_MaxThreshold_Desc")));
Parameters.Add("MinVoidArea", new ProcessorParameter(
"MinVoidArea",
LocalizationHelper.GetString("VoidMeasurementProcessor_MinVoidArea"),
typeof(int), 10, 1, 100000,
LocalizationHelper.GetString("VoidMeasurementProcessor_MinVoidArea_Desc")));
Parameters.Add("MergeRadius", new ProcessorParameter(
"MergeRadius",
LocalizationHelper.GetString("VoidMeasurementProcessor_MergeRadius"),
typeof(int), 3, 0, 30,
LocalizationHelper.GetString("VoidMeasurementProcessor_MergeRadius_Desc")));
Parameters.Add("BlurSize", new ProcessorParameter(
"BlurSize",
LocalizationHelper.GetString("VoidMeasurementProcessor_BlurSize"),
typeof(int), 3, 1, 31,
LocalizationHelper.GetString("VoidMeasurementProcessor_BlurSize_Desc")));
Parameters.Add("VoidLimit", new ProcessorParameter(
"VoidLimit",
LocalizationHelper.GetString("VoidMeasurementProcessor_VoidLimit"),
typeof(double), 25.0, 0.0, 100.0,
LocalizationHelper.GetString("VoidMeasurementProcessor_VoidLimit_Desc")));
}
public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
{
int minThresh = GetParameter<int>("MinThreshold");
int maxThresh = GetParameter<int>("MaxThreshold");
int minVoidArea = GetParameter<int>("MinVoidArea");
int mergeRadius = GetParameter<int>("MergeRadius");
int blurSize = GetParameter<int>("BlurSize");
double voidLimit = GetParameter<double>("VoidLimit");
if (blurSize % 2 == 0) blurSize++;
OutputData.Clear();
int w = inputImage.Width, h = inputImage.Height;
// ── 构建多边形ROI掩� ──
int polyCount = GetParameter<int>("PolyCount");
Image<Gray, byte>? roiMask = null;
Point[]? roiPoints = null;
if (polyCount >= 3)
{
roiPoints = new Point[polyCount];
for (int i = 0; i < polyCount; i++)
roiPoints[i] = new Point(GetParameter<int>($"PolyX{i}"), GetParameter<int>($"PolyY{i}"));
roiMask = new Image<Gray, byte>(w, h);
using var vop = new VectorOfPoint(roiPoints);
using var vvop = new VectorOfVectorOfPoint(vop);
CvInvoke.DrawContours(roiMask, vvop, 0, new MCvScalar(255), -1);
}
else
{
// 无ROI时使用全�
roiMask = new Image<Gray, byte>(w, h);
roiMask.SetValue(new Gray(255));
}
int roiArea = CvInvoke.CountNonZero(roiMask);
_logger.Debug("VoidMeasurement: ROI area={Area}, Thresh=[{Min},{Max}], MergeR={MR}",
roiArea, minThresh, maxThresh, mergeRadius);
// ── 高斯模糊�噪 ──
var blurred = new Image<Gray, byte>(w, h);
CvInvoke.GaussianBlur(inputImage, blurred, new Size(blurSize, blurSize), 0);
// ── �阈值分割��气泡（亮区域） ──
var voidImg = new Image<Gray, byte>(w, h);
byte[,,] srcData = blurred.Data;
byte[,,] dstData = voidImg.Data;
byte[,,] maskData = roiMask.Data;
for (int y = 0; y < h; y++)
{
for (int x = 0; x < w; x++)
{
if (maskData[y, x, 0] > 0)
{
byte val = srcData[y, x, 0];
dstData[y, x, 0] = (val >= minThresh && val <= maxThresh) ? (byte)255 : (byte)0;
}
}
}
// ── 形�学膨胀�并相邻气泡 ──
if (mergeRadius > 0)
{
int kernelSize = mergeRadius * 2 + 1;
using var kernel = CvInvoke.GetStructuringElement(ElementShape.Ellipse,
new Size(kernelSize, kernelSize), new Point(-1, -1));
CvInvoke.Dilate(voidImg, voidImg, kernel, new Point(-1, -1), 1, BorderType.Default, new MCvScalar(0));
// 与ROI掩��交集，防止膨胀超出ROI
CvInvoke.BitwiseAnd(voidImg, roiMask, voidImg);
}
// ── 轮廓检�──
using var contours = new VectorOfVectorOfPoint();
using var hierarchy = new Mat();
CvInvoke.FindContours(voidImg, contours, hierarchy, RetrType.External, ChainApproxMethod.ChainApproxSimple);
var voids = new List<VoidRegionInfo>();
int totalVoidArea = 0;
for (int i = 0; i < contours.Size; i++)
{
double area = CvInvoke.ContourArea(contours[i]);
if (area < minVoidArea) continue;
var moments = CvInvoke.Moments(contours[i]);
if (moments.M00 < 1) continue;
int intArea = (int)Math.Round(area);
totalVoidArea += intArea;
voids.Add(new VoidRegionInfo
{
Index = voids.Count + 1,
CenterX = moments.M10 / moments.M00,
CenterY = moments.M01 / moments.M00,
Area = intArea,
AreaPercent = roiArea > 0 ? area / roiArea * 100.0 : 0,
BoundingBox = CvInvoke.BoundingRectangle(contours[i]),
ContourPoints = contours[i].ToArray()
});
}
// 按�积从大到�排�
voids.Sort((a, b) => b.Area.CompareTo(a.Area));
for (int i = 0; i < voids.Count; i++) voids[i].Index = i + 1;
double voidRate = roiArea > 0 ? (double)totalVoidArea / roiArea * 100.0 : 0;
string classification = voidRate <= voidLimit ? "PASS" : "FAIL";
int maxVoidArea = voids.Count > 0 ? voids[0].Area : 0;
_logger.Information("VoidMeasurement: VoidRate={Rate:F1}%, Voids={Count}, MaxArea={Max}, {Class}",
voidRate, voids.Count, maxVoidArea, classification);
// ── 输出数� ──
OutputData["VoidMeasurementResult"] = true;
OutputData["RoiArea"] = roiArea;
OutputData["RoiPoints"] = roiPoints;
OutputData["TotalVoidArea"] = totalVoidArea;
OutputData["VoidRate"] = voidRate;
OutputData["VoidLimit"] = voidLimit;
OutputData["VoidCount"] = voids.Count;
OutputData["MaxVoidArea"] = maxVoidArea;
OutputData["Classification"] = classification;
OutputData["Voids"] = voids;
OutputData["ResultText"] = $"Void: {voidRate:F1}% | {classification} | {voids.Count} voids | ROI: {roiArea}px";
blurred.Dispose();
voidImg.Dispose();
roiMask.Dispose();
return inputImage.Clone();
}
}
/// <summary>
/// �个空隙区域信�
/// </summary>
public class VoidRegionInfo
{
public int Index { get; set; }
public double CenterX { get; set; }
public double CenterY { get; set; }
public int Area { get; set; }
public double AreaPercent { get; set; }
public Rectangle BoundingBox { get; set; }
public Point[] ContourPoints { get; set; } = Array.Empty<Point>();
}