code: def compute_surface_metrics(mesh, name, mesh_dir):
      """Compute surface metrics (chamfer distance and f-score) for one example.
  
      Args:
        mesh: trimesh.Trimesh, the mesh to evaluate.
        name: Tensor, hash name of the mesh as recorded in the dataset.
        mesh_dir: string, path to the directory for loading ground truth meshes.
  
      Returns:
        chamfer: float, chamfer distance.
        fscore: float, f-score.
      """
      if mesh_dir is None:
          raise ValueError(
              "Need to specify args.mesh_dir for loading ground truth."
          )
      cls_name, obj_name = mesh_name_helper(name)
      with tf.io.gfile.GFile(
          path.join(
              mesh_dir, "test", cls_name, obj_name, "model_occnet.ply"
          ),
          "rb",
      ) as fin:
          mesh_gt = trimesh.Trimesh(
              **trimesh.exchange.ply.load_ply(fin)
          )
  
      # Chamfer
      eval_points = 100000
      point_gt = mesh_gt.sample(eval_points)
      point_gt = point_gt.astype(np.float32)
      point_pred = mesh.sample(eval_points)
      point_pred = point_pred.astype(np.float32)
  
      pred_to_gt = distance_field_helper(point_pred, point_gt)
      gt_to_pred = distance_field_helper(point_gt, point_pred)
  
      chamfer = np.mean(pred_to_gt**2) + np.mean(gt_to_pred**2)
  
      # Fscore
      tau = 1e-4
      eps = 1e-9
  
      pred_to_gt = pred_to_gt**2
      gt_to_pred = gt_to_pred**2
  
      prec_tau = (pred_to_gt <= tau).astype(np.float32).mean() * 100.0
      recall_tau = (gt_to_pred <= tau).astype(np.float32).mean() * 100.0
  
      fscore = (2 * prec_tau * recall_tau) / max(
          prec_tau + recall_tau, eps
      )
  
      # Following the tradition to scale chamfer distance up by 10.
      return chamfer * 100.0, fscore
  
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 7 for calling a global function with example usage: compute_surface_metrics(mesh, name, mesh_dir) and returns: unknown,  fscore