code: def export(
      mesh_file,
      agg_file,
      seg_file,
      meta_file,
      label_map_file,
      output_file=None,
  ):
      """points are XYZ RGB (RGB in 0-255),
      semantic label as nyu40 ids,
      instance label as 1-#instance,
      box as (cx,cy,cz,dx,dy,dz,semantic_label)
      """
      label_map = read_label_mapping(
          label_map_file, label_from="raw_category", label_to="nyu40id"
      )
      mesh_vertices = read_mesh_vertices_rgb(mesh_file)
  
      # Load scene axis alignment matrix
      lines = open(meta_file).readlines()
      for line in lines:
          if "axisAlignment" in line:
              axis_align_matrix = [
                  float(x)
                  for x in line.rstrip()
                  .strip("axisAlignment = ")
                  .split(" ")
              ]
              break
      axis_align_matrix = np.array(axis_align_matrix).reshape((4, 4))
      pts = np.ones((mesh_vertices.shape[0], 4))
      pts[:, 0:3] = mesh_vertices[:, 0:3]
      pts = np.dot(pts, axis_align_matrix.transpose())  # Nx4
      mesh_vertices[:, 0:3] = pts[:, 0:3]
  
      # Load semantic and instance labels
      object_id_to_segs, label_to_segs = read_aggregation(agg_file)
      seg_to_verts, num_verts = read_segmentation(seg_file)
      label_ids = np.zeros(
          shape=(num_verts), dtype=np.uint32
      )  # 0: unannotated
      object_id_to_label_id = {}
      for label, segs in label_to_segs.items():
          label_id = label_map[label]
          for seg in segs:
              verts = seg_to_verts[seg]
              label_ids[verts] = label_id
      instance_ids = np.zeros(
          shape=(num_verts), dtype=np.uint32
      )  # 0: unannotated
      num_instances = len(np.unique(list(object_id_to_segs.keys())))
      for object_id, segs in object_id_to_segs.items():
          for seg in segs:
              verts = seg_to_verts[seg]
              instance_ids[verts] = object_id
              if object_id not in object_id_to_label_id:
                  object_id_to_label_id[object_id] = label_ids[verts][0]
      instance_bboxes = np.zeros((num_instances, 7))
      for obj_id in object_id_to_segs:
          label_id = object_id_to_label_id[obj_id]
          obj_pc = mesh_vertices[instance_ids == obj_id, 0:3]
          if len(obj_pc) == 0:
              continue
          # Compute axis aligned box
          # An axis aligned bounding box is parameterized by
          # (cx,cy,cz) and (dx,dy,dz) and label id
          # where (cx,cy,cz) is the center point of the box,
          # dx is the x-axis length of the box.
          xmin = np.min(obj_pc[:, 0])
          ymin = np.min(obj_pc[:, 1])
          zmin = np.min(obj_pc[:, 2])
          xmax = np.max(obj_pc[:, 0])
          ymax = np.max(obj_pc[:, 1])
          zmax = np.max(obj_pc[:, 2])
          bbox = np.array(
              [
                  (xmin + xmax) / 2.0,
                  (ymin + ymax) / 2.0,
                  (zmin + zmax) / 2.0,
                  xmax - xmin,
                  ymax - ymin,
                  zmax - zmin,
                  label_id,
              ]
          )
          # NOTE: this assumes obj_id is in 1,2,3,.,,,.NUM_INSTANCES
          instance_bboxes[obj_id - 1, :] = bbox
  
      return (
          mesh_vertices.astype(np.float32),
          label_ids.astype(np.int),
          instance_ids.astype(np.int),
          instance_bboxes.astype(np.float32),
          object_id_to_label_id,
      )
  
imports: import os
  import os.path
  import shutil
  import json
  import torch
  from glob import glob
  import sys
  import csv
  import logging
  import numpy
  from plyfile import PlyData, PlyElement
  from torch_geometric.data import Data, InMemoryDataset, download_url, extract_zip
  import torch_geometric.transforms
  import multiprocessing
  import pandas
  import tempfile
  import urllib
  from urllib.request import urlopen
  from torch_points3d.datasets.base_dataset import BaseDataset
  import torch_points3d.core.data_transform
  from .None import IGNORE_LABEL
label_desc: Use image node_id 12 for calling a global function with example usage: export(mesh_file, agg_file, seg_file, meta_file, label_map_file, output_file) and returns: mesh_vertices,  label_ids,  instance_ids,  instance_bboxes,  object_id_to_label_id