Replace RotationAnalysis.FindBestRotation with PartClassifier.Classify in RunPipeline, propagate ClassificationResult through BuildAngles signatures and FillContext.PartType, and rewrite AngleCandidateBuilder to dispatch on part type (Circle=1 angle, Rectangle=2, Irregular=full sweep). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
143 lines
4.7 KiB
C#
143 lines
4.7 KiB
C#
using OpenNest.Engine.ML;
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using OpenNest.Geometry;
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using OpenNest.Math;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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namespace OpenNest.Engine.Fill
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{
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public class AngleCandidateBuilder
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{
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private readonly HashSet<double> knownGoodAngles = new();
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public bool ForceFullSweep { get; set; }
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public List<double> Build(NestItem item, ClassificationResult classification, Box workArea)
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{
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// User constraints always take precedence over classification.
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if (HasExplicitConstraints(item))
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return BuildFromConstraints(item);
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switch (classification.Type)
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{
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case PartType.Circle:
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return new List<double> { 0 };
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case PartType.Rectangle:
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return new List<double> { classification.PrimaryAngle, classification.PrimaryAngle + Angle.HalfPI };
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default:
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return BuildIrregularAngles(item, classification.PrimaryAngle, workArea);
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}
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}
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private static bool HasExplicitConstraints(NestItem item)
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{
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// Default NestConstraints: Start=0, End=0. Both zero = no constraints.
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return !(item.RotationStart.IsEqualTo(0) && item.RotationEnd.IsEqualTo(0));
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}
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private static List<double> BuildFromConstraints(NestItem item)
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{
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var angles = new List<double>();
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var step = item.StepAngle > Tolerance.Epsilon ? item.StepAngle : Angle.ToRadians(5);
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for (var a = item.RotationStart; a <= item.RotationEnd + Tolerance.Epsilon; a += step)
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{
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if (!ContainsAngle(angles, a))
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angles.Add(a);
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}
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if (angles.Count == 0)
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angles.Add(item.RotationStart);
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return angles;
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}
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private List<double> BuildIrregularAngles(NestItem item, double primaryAngle, Box workArea)
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{
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var baseAngles = new[] { primaryAngle, primaryAngle + Angle.HalfPI };
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if (knownGoodAngles.Count > 0 && !ForceFullSweep)
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return BuildPrunedList(baseAngles);
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var angles = new List<double>(baseAngles);
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// Full 5-degree sweep for irregular parts.
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AddSweepAngles(angles);
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// ML prediction complements the sweep when available.
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angles = ApplyMlPrediction(item, workArea, baseAngles, angles);
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return angles;
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}
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private static void AddSweepAngles(List<double> angles)
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{
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var step = Angle.ToRadians(5);
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for (var a = 0.0; a < System.Math.PI; a += step)
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{
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if (!ContainsAngle(angles, a))
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angles.Add(a);
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}
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}
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private static List<double> ApplyMlPrediction(
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NestItem item, Box workArea, double[] baseAngles, List<double> fallback)
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{
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var features = FeatureExtractor.Extract(item.Drawing);
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if (features == null)
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return fallback;
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var predicted = AnglePredictor.PredictAngles(features, workArea.Width, workArea.Length);
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if (predicted == null)
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return fallback;
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var mlAngles = new List<double>(predicted);
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foreach (var b in baseAngles)
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{
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if (!ContainsAngle(mlAngles, b))
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mlAngles.Add(b);
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}
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// Merge ML angles into the existing sweep so both contribute.
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foreach (var a in fallback)
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{
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if (!ContainsAngle(mlAngles, a))
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mlAngles.Add(a);
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}
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Debug.WriteLine($"[AngleCandidateBuilder] ML: {fallback.Count} sweep + {predicted.Count} predicted = {mlAngles.Count} total");
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return mlAngles;
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}
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private List<double> BuildPrunedList(double[] baseAngles)
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{
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var pruned = new List<double>(baseAngles);
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foreach (var a in knownGoodAngles)
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{
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if (!ContainsAngle(pruned, a))
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pruned.Add(a);
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}
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Debug.WriteLine($"[AngleCandidateBuilder] Pruned to {pruned.Count} angles (known-good)");
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return pruned;
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}
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private static bool ContainsAngle(List<double> angles, double angle)
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{
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return angles.Any(existing => existing.IsEqualTo(angle));
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}
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public void RecordProductive(List<AngleResult> angleResults)
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{
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foreach (var ar in angleResults)
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{
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if (ar.PartCount > 0)
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knownGoodAngles.Add(Angle.ToRadians(ar.AngleDeg));
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}
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}
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}
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}
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