feat(engine): add AnglePredictor ONNX inference class

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-14 20:27:44 -04:00
parent eee2d0e3fe
commit 8cc14997af
1 changed files with 119 additions and 0 deletions
--- a/OpenNest.Engine/ML/AnglePredictor.cs
+++ b/OpenNest.Engine/ML/AnglePredictor.cs
@@ -0,0 +1,119 @@
+using System;
+using System.Collections.Generic;
+using System.Diagnostics;
+using System.IO;
+using System.Linq;
+using Microsoft.ML.OnnxRuntime;
+using Microsoft.ML.OnnxRuntime.Tensors;
+using OpenNest.Math;
+
+namespace OpenNest.Engine.ML
+{
+    public static class AnglePredictor
+    {
+        private static InferenceSession _session;
+        private static bool _loadAttempted;
+        private static readonly object _lock = new();
+
+        public static List<double> PredictAngles(
+            PartFeatures features, double sheetWidth, double sheetHeight,
+            double threshold = 0.3)
+        {
+            var session = GetSession();
+            if (session == null)
+                return null;
+
+            try
+            {
+                var input = new float[11];
+                input[0] = (float)features.Area;
+                input[1] = (float)features.Convexity;
+                input[2] = (float)features.AspectRatio;
+                input[3] = (float)features.BoundingBoxFill;
+                input[4] = (float)features.Circularity;
+                input[5] = (float)features.PerimeterToAreaRatio;
+                input[6] = features.VertexCount;
+                input[7] = (float)sheetWidth;
+                input[8] = (float)sheetHeight;
+                input[9] = (float)(sheetWidth / (sheetHeight > 0 ? sheetHeight : 1.0));
+                input[10] = (float)(features.Area / (sheetWidth * sheetHeight));
+
+                var tensor = new DenseTensor<float>(input, new[] { 1, 11 });
+                var inputs = new List<NamedOnnxValue>
+                {
+                    NamedOnnxValue.CreateFromTensor("features", tensor)
+                };
+
+                using var results = session.Run(inputs);
+                var probabilities = results.First().AsEnumerable<float>().ToArray();
+
+                var angles = new List<(double angleDeg, float prob)>();
+                for (var i = 0; i < 36 && i < probabilities.Length; i++)
+                {
+                    if (probabilities[i] >= threshold)
+                        angles.Add((i * 5.0, probabilities[i]));
+                }
+
+                // Minimum 3 angles — take top by probability if fewer pass threshold.
+                if (angles.Count < 3)
+                {
+                    angles = probabilities
+                        .Select((p, i) => (angleDeg: i * 5.0, prob: p))
+                        .OrderByDescending(x => x.prob)
+                        .Take(3)
+                        .ToList();
+                }
+
+                // Always include 0 and 90 as safety fallback.
+                var result = angles.Select(a => Angle.ToRadians(a.angleDeg)).ToList();
+
+                if (!result.Any(a => a.IsEqualTo(0)))
+                    result.Add(0);
+                if (!result.Any(a => a.IsEqualTo(Angle.HalfPI)))
+                    result.Add(Angle.HalfPI);
+
+                return result;
+            }
+            catch (Exception ex)
+            {
+                Debug.WriteLine($"[AnglePredictor] Inference failed: {ex.Message}");
+                return null;
+            }
+        }
+
+        private static InferenceSession GetSession()
+        {
+            if (_loadAttempted)
+                return _session;
+
+            lock (_lock)
+            {
+                if (_loadAttempted)
+                    return _session;
+
+                _loadAttempted = true;
+
+                try
+                {
+                    var dir = Path.GetDirectoryName(typeof(AnglePredictor).Assembly.Location);
+                    var modelPath = Path.Combine(dir, "Models", "angle_predictor.onnx");
+
+                    if (!File.Exists(modelPath))
+                    {
+                        Debug.WriteLine($"[AnglePredictor] Model not found: {modelPath}");
+                        return null;
+                    }
+
+                    _session = new InferenceSession(modelPath);
+                    Debug.WriteLine("[AnglePredictor] Model loaded successfully");
+                }
+                catch (Exception ex)
+                {
+                    Debug.WriteLine($"[AnglePredictor] Failed to load model: {ex.Message}");
+                }
+
+                return _session;
+            }
+        }
+    }
+}