open3d_poisson_recon_helpers.py

open3d_poisson_recon_helpers.py

def mesh_cleanup(mesh_o3d):
  mesh_o3d.remove_non_manifold_edges()
  mesh_o3d.merge_close_vertices(0.001)
  mesh_o3d.remove_duplicated_vertices()
  mesh_o3d.remove_duplicated_triangles()
  mesh_o3d.remove_unreferenced_vertices()
  mesh_o3d.remove_degenerate_triangles()
  # This seems to keep the majority normal direction, but without knowing
  # how it works there's the risk that it flips all the faces.
  mesh_o3d.orient_triangles()

  cis, cns, cas = mesh_o3d.cluster_connected_triangles()
  # print("component areas pre-cleanup:", cas)
  max_area = max(cas)
  max_allowed_area = max_area/3
  remove_components = []
  for i, area in enumerate(cas):
    if area < max_allowed_area:
      remove_components.append(i)
  mesh_o3d.remove_triangles_by_mask([ci in remove_components for ci in cis])
  mesh_o3d.remove_unreferenced_vertices()

  # Fill holes: this may help but may also cost us a fair bit of time too.
  # We need to convert to the new o3d format, then it converts to vtk internally
  # (TODO: call vtk directly), which copies the data again...
  # mesh_o3d = o3d.t.geometry.TriangleMesh.from_legacy(m).fill_holes(hole_size=50.0).to_legacy()

  return mesh_o3d

def mesh_report(mesh_o3d, name):
  _, _, cas = mesh_o3d.cluster_connected_triangles()
  n_components = len(cas)
  X = mesh_o3d.euler_poincare_characteristic()
  nonmanifold_edges = mesh_o3d.get_non_manifold_edges(allow_boundary_edges=True)
  boundary_edges = mesh_o3d.get_non_manifold_edges(allow_boundary_edges=False)
  n_boundary_edges = len(boundary_edges) - len(nonmanifold_edges)
  g = networkx.Graph()
  g.add_edges_from(boundary_edges)
  n_boundary_loops = networkx.number_connected_components(g)
  genus =  1 - (X + n_boundary_loops*n_components)/2
  print(name,
    "\tn_components:", n_components,
    "\tareas:", list(map(round, cas)),
    "\tgenus:", genus,
    "\tn_boundary_edges:", n_boundary_edges,
    "\tn_boundary_loops:", n_boundary_loops,
    "\tX:", X)

def poisson_depth_from_width_and_scale(pcd, width, scale_factor):
  bbox = pcd.get_axis_aligned_bounding_box()
  p_min = bbox.get_min_bound()
  p_max = bbox.get_max_bound()
  resolution = max((p_max - p_min) / width)
  resolution *= scale_factor
  depth = 0
  while ((1 << depth) < resolution):
      depth += 1
  return depth

def create_from_point_cloud_poisson(pcd, depth=8, width=0, scale=1.1, **kwargs):
  # Work around open3d's poisson width bug:
  # https://github.com/isl-org/Open3D/issues/5842#issuecomment-2133275951
  if width > 0:
    depth = poisson_depth_from_width_and_scale(pcd, width, scale)
  return o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(
    pcd, width=width, depth=depth, scale=scale, **kwargs
  )