code: def pc_norm(pc):
      """pc: NxC, return NxC"""
      centroid = np.mean(pc, axis=0)
      pc = pc - centroid
      m = np.max(np.sqrt(np.sum(pc**2, axis=1)))
      pc = pc / m
      return pc
  
imports: from lavis.common.registry import registry
  from lavis.processors.blip_processors import BlipImageBaseProcessor
  from omegaconf import OmegaConf
  import torchvision.transforms
  from lavis.models.ulip_models.utils.io import IO
  import numpy
  from PIL import Image
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: pc_norm(pc) and returns: pc