code: def get_displacement_mesh(model):
      def get_detailed_mesh(input):
          origin_mesh = input.copy()
          mesh_points = (
              torch.tensor(
                  np.array(origin_mesh.vertices).astype(np.float32)
              )
              .cuda()
              .requires_grad_(True)
          )
          sdfs = model.implicit_network(mesh_points)[:, 0:1]
          sdf_np = sdfs.detach().cpu().numpy()
          vetices_normal = origin_mesh.vertex_normals
          new_vertices = -1.0 * sdf_np * vetices_normal + np.array(
              origin_mesh.vertices
          )
          new_mesh = trimesh.Trimesh(
              vertices=new_vertices,
              faces=origin_mesh.faces,
              process=False,
              visual=origin_mesh.visual,
          )
          print("Detailed mesh created!")
          return new_mesh
  
      orimesh = model.mesh
      subdivision_mesh = orimesh.subdivide()
      new_mesh = get_detailed_mesh(orimesh)
      submesh_full = get_detailed_mesh(subdivision_mesh)
  
      return new_mesh, submesh_full
  
imports: import plotly.graph_objs
  import plotly.offline
  import numpy
  import torch
  from skimage import measure
  import torchvision
  import trimesh
  from PIL import Image
  from utils import rend_util
  import pickle
label_desc: Use image node_id 7 for calling a global function with example usage: get_displacement_mesh(model) and returns: new_mesh,  submesh_full, new_mesh