code: import numpy as np
  import cv2
  
  def load_batch(ls,od,data_path,batch_size,which_batch):
      image_list=[]
      for i in range(which_batch*batch_size,(which_batch+1)*batch_size):
          image=[]
          image.append(cv2.imread(data_path+ls[od[i]]+'_red.png',0))
          image.append(cv2.imread(data_path+ls[od[i]]+'_green.png',0))
          image.append(cv2.imread(data_path+ls[od[i]]+'_blue.png',0))
          image.append(cv2.imread(data_path+ls[od[i]]+'_yellow.png',0))
          image=np.asarray(image).T
          image_list.append(image)
      image_list=np.asarray(image_list)
      return image_list
  
  def normalize(image_list):
      ma=max(image_list.flatten())
      mi=min(image_list.flatten())
      mean = float((ma+mi)/2.0)
      output = (image_list-mean)/(ma-mean)
      return output
  
apis: numpy.asarray