Coverage for trimesh/decomposition.py: 100%

1import numpy as np 

2 

3 

4def convex_decomposition(mesh, **kwargs) -> list[dict]: 

5 """ 

6 Compute an approximate convex decomposition of a mesh. 

7 

8 VHACD Parameters which can be passed as kwargs: 

9 

10 Name Default 

11 ----------------------------------------- 

12 maxConvexHulls 64 

13 resolution 400000 

14 minimumVolumePercentErrorAllowed 1.0 

15 maxRecursionDepth 10 

16 shrinkWrap True 

17 fillMode "flood" 

18 maxNumVerticesPerCH 64 

19 asyncACD True 

20 minEdgeLength 2 

21 findBestPlane False 

22 

23 Parameters 

24 ---------- 

25 mesh : trimesh.Trimesh 

26 Mesh to be decomposed into convex parts 

27 **kwargs : VHACD keyword arguments 

28 

29 Returns 

30 ------- 

31 mesh_args : list 

32 List of **kwargs for Trimeshes that are nearly 

33 convex and approximate the original. 

34 """ 

35 from vhacdx import compute_vhacd 

36 

37 # the faces are triangulated in a (len(face), ...vertex-index) 

38 # for vtkPolyData 

39 # i.e. so if shaped to four columns the first column is all 3 

40 faces = ( 

41 np.column_stack((np.ones(len(mesh.faces), dtype=np.int64) * 3, mesh.faces)) 

42 .ravel() 

43 .astype(np.uint32) 

44 ) 

45 

46 return [ 

47 {"vertices": v, "faces": f} 

48 for v, f in compute_vhacd(mesh.vertices, faces, **kwargs) 

49 ]