code: def numpy_to_pil(images):
      """
      Convert a numpy image or a batch of images to a PIL image.
      """
      if images.ndim == 3:
          images = images[None, ...]
      images = (images * 255).round().astype("uint8")
      pil_images = [Image.fromarray(image) for image in images]
  
      return pil_images
  
file_path: NeMo/examples/multimodal/text_to_image/controlnet/controlnet_infer.py
imports: import os
  import time
  import cv2
  import einops
  import torch
  from PIL import Image
  from nemo.collections.multimodal.models.text_to_image.controlnet import get_preprocessing_function
  from nemo.collections.multimodal.models.text_to_image.controlnet.controlnet import MegatronControlNet
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers.ddim import DDIMSampler
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers.plms import PLMSSampler
  from nemo.collections.multimodal.parts.utils import setup_trainer_and_model_for_inference
  from nemo.core.config import hydra_runner
label_desc: Use image node_id 6 for calling a global function with example usage: numpy_to_pil(images) and returns: pil_images