code: def lighting(im, alpha_std, eig_val, eig_vec):
      """Performs AlexNet-style PCA jitter (used for training)."""
      alpha = np.random.normal(0, alpha_std, size=(1, 3))
      alpha = np.repeat(alpha, 3, axis=0)
      eig_val = np.repeat(np.array(eig_val), 3, axis=0)
      rgb = np.sum(np.array(eig_vec) * alpha * eig_val, axis=1)
      for i in range(3):
          im[:, :, i] = im[:, :, i] + rgb[i]
      return im
  
file_path: pycls/pycls/datasets/transforms.py
imports: from math import ceil, sqrt
  import cv2
  import numpy
  from PIL import Image
  from pycls.datasets.augment import make_augment
label_desc: Use image node_id 5 for calling a global function with example usage: lighting(im, alpha_std, eig_val, eig_vec) and returns: im