code: def transform_mesh(mesh, name, trans_dir):
      """Transform mesh back to the same coordinate of ground truth.
  
      Args:
        mesh: trimesh.Trimesh, predicted mesh before transformation.
        name: Tensor, hash name of the mesh as recorded in the dataset.
        trans_dir: string, path to the directory for loading transformations.
  
      Returns:
        mesh: trimesh.Trimesh, the transformed mesh.
      """
      if trans_dir is None:
          raise ValueError(
              "Need to specify args.trans_dir for loading pred-to-target"
              "transformations."
          )
      cls_name, obj_name = mesh_name_helper(name)
      with tf.io.gfile.GFile(
          path.join(
              trans_dir,
              "test",
              cls_name,
              obj_name,
              "occnet_to_gaps.txt",
          ),
          "r",
      ) as fin:
          tx = np.loadtxt(fin).reshape([4, 4])
          mesh.apply_transform(np.linalg.inv(tx))
      return mesh
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from os import path
  import numpy
  import scipy
  from skimage import measure
  import tensorflow.compat.v1
  from tensorflow_graphics.projects.cvxnet.lib import datasets
  from tensorflow_graphics.projects.cvxnet.lib import models
  from tensorflow_graphics.projects.cvxnet.lib.libmise import mise
  import trimesh
label_desc: Use image node_id 4 for calling a global function with example usage: transform_mesh(mesh, name, trans_dir) and returns: mesh