contour

core/pdf_exporter/geometry.py

@@ -220,18 +220,13 @@ def extract_lineart_edges(mesh_data: Any, max_angle_deg: float = 30.0) -> NDArra
 
     num_unique = len(unique_keys)
 
+    max_cat = np.full(num_unique, -1, dtype=int)
+    min_cat = np.full(num_unique, 999, dtype=int)
+    np.maximum.at(max_cat, inverse_indices, edge_category)
+    np.minimum.at(min_cat, inverse_indices, edge_category)
+
     # Rule 1: Silhouette edge - adjacent faces have different categories
-    # (i.e., not all faces sharing this edge are in the same category)
+    rule1_unique = (counts >= 2) & (max_cat != min_cat)
-    categories_all = edge_category[inverse_indices]
-    rule1_unique = np.zeros(num_unique, dtype=bool)
-    
-    for edge_id in range(num_unique):
-        edge_cats = categories_all[inverse_indices == edge_id]
-        if len(edge_cats) < 2:
-            rule1_unique[edge_id] = False
-        else:
-            all_same = np.all(edge_cats == edge_cats[0])
-            rule1_unique[edge_id] = not all_same
 
     # Rule 2: Boundary edge (owned by 1 face)
     rule2_unique = counts == 1
@@ -477,27 +472,19 @@ def extract_silhouette_contour_edges(mesh_data: Any) -> NDArray[np.float64]:
 
     num_unique = len(unique_keys)
 
-    # For each unique edge, collect the categories of all adjacent faces
+    max_cat = np.full(num_unique, -1, dtype=int)
-    # An edge is a silhouette if it has faces from different categories
+    min_cat = np.full(num_unique, 999, dtype=int)
-    # (i.e., not all faces are in the same category)
+    np.maximum.at(max_cat, inverse_indices, edge_category)
-    
+    np.minimum.at(min_cat, inverse_indices, edge_category)
-    # Get categories for all edge instances
-    categories_all = edge_category[inverse_indices]
-    
-    # For each unique edge, check if all its face categories are the same
-    is_silhouette = np.zeros(num_unique, dtype=bool)
-    
-    for edge_id in range(num_unique):
-        edge_cats = categories_all[inverse_indices == edge_id]
-        # If this edge has only one face, it's a boundary, not silhouette
-        if len(edge_cats) < 2:
-            is_silhouette[edge_id] = False
-        else:
-            # Check if all categories are the same
-            all_same = np.all(edge_cats == edge_cats[0])
-            is_silhouette[edge_id] = not all_same
 
-    return canonical_2d[first_indices[is_silhouette]]
+    # An edge is a silhouette/contour edge if:
+    # 1. It is owned by 1 face (boundary edge of open surface)
+    # OR
+    # 2. Adjacent faces belong to different normal.z orientation categories (e.g. front vs back, front vs vertical)
+    is_silhouette = (counts == 1) | (max_cat != min_cat)
+
+    contour_edges = canonical_2d[first_indices[is_silhouette]]
+    return deduplicate_2d_edges(contour_edges)
 
 
 def extract_outer_contour_edges(mesh_data: Any) -> NDArray[np.float64]:

core/pdf_exporter/writer.py

@@ -126,8 +126,10 @@ def export_mesh_to_pdf(
     if edge_list:
         combined = np.concatenate(edge_list, axis=0)
         edges_to_draw = deduplicate_2d_edges(combined)
-    else:
+    elif draw_wireframe:
         edges_to_draw = edges_2d
+    else:
+        edges_to_draw = np.empty((0, 2, 2), dtype=np.float64)
 
     if len(edges_to_draw) > 0:
         min_x = float(edges_to_draw[:, :, 0].min())

tests/test_pdf_exporter.py

@@ -46,6 +46,7 @@ from NodeSlicer.infra.blender.blender_mesh_capture import SlicingGroup, SlicingC
 from NodeSlicer.core.pdf_exporter import (
     extract_unique_top_view_edges,
     extract_lineart_edges,
+    extract_outer_contour_edges,
     export_wireframe_to_pdf,
     export_mesh_to_pdf,
     MM_TO_PT
@@ -129,6 +130,29 @@ class TestPdfExporter(unittest.TestCase):
         lineart_100 = extract_lineart_edges(so, max_angle_deg=100.0)
         self.assertTrue(len(lineart_100) > 0)
 
+    def test_extract_outer_contour_edges(self):
+        so = SlicingObject()
+        # Top face made of 2 triangles (0,0)-(10,0)-(10,10) and (0,0)-(10,10)-(0,10)
+        # Shared interior diagonal edge: (0,0)-(10,10)
+        # Side wall triangles around the box (vertical wall, normal_z = 0)
+        tri_top1 = np.array([[0.0, 0.0, 10.0], [10.0, 0.0, 10.0], [10.0, 10.0, 10.0], [0.0, 0.0, 1.0]], dtype=np.float64)
+        tri_top2 = np.array([[0.0, 0.0, 10.0], [10.0, 10.0, 10.0], [0.0, 10.0, 10.0], [0.0, 0.0, 1.0]], dtype=np.float64)
+        # Side walls
+        tri_side1 = np.array([[0.0, 0.0, 10.0], [10.0, 0.0, 10.0], [10.0, 0.0, 0.0], [0.0, -1.0, 0.0]], dtype=np.float64)
+        tri_side2 = np.array([[10.0, 0.0, 10.0], [10.0, 10.0, 10.0], [10.0, 10.0, 0.0], [1.0, 0.0, 0.0]], dtype=np.float64)
+        tri_side3 = np.array([[10.0, 10.0, 10.0], [0.0, 10.0, 10.0], [0.0, 10.0, 0.0], [0.0, 1.0, 0.0]], dtype=np.float64)
+        tri_side4 = np.array([[0.0, 10.0, 10.0], [0.0, 0.0, 10.0], [0.0, 0.0, 0.0], [-1.0, 0.0, 0.0]], dtype=np.float64)
+
+        so.mesh = np.array([tri_top1, tri_top2, tri_side1, tri_side2, tri_side3, tri_side4])
+
+        wireframe = extract_unique_top_view_edges(so)
+        # Wireframe contains 4 outer edges + 1 interior diagonal = 5
+        self.assertEqual(len(wireframe), 5)
+
+        contour = extract_outer_contour_edges(so)
+        # Contour should exclude the internal diagonal edge and return only 4 outer boundary edges
+        self.assertEqual(len(contour), 4)
+
     def test_export_pdf_true_1_to_1_scale(self):
         edges_2d = np.array([
             [[0.0, 0.0], [100.0, 0.0]],