code: def read_img(path):
      # read image by cv2
      # return: Numpy float32, HWC, BGR, [0,1]
      img = cv2.imread(
          path, cv2.IMREAD_UNCHANGED
      )  # cv2.IMREAD_GRAYSCALE
      img = img.astype(np.float32) / 255.0
      if img.ndim == 2:
          img = np.expand_dims(img, axis=2)
      # some images have 4 channels
      if img.shape[2] > 3:
          img = img[:, :, :3]
      return img
  
imports: import os
  import math
  import random
  import numpy
  import torch
  import cv2
  from torchvision.utils import make_grid
  from datetime import datetime
label_desc: Use image node_id 16 for calling a global function with example usage: read_img(path) and returns: img