code: def preprocess(self):
      input_datas = []
  
      # 数据预处理
      for i, img in enumerate(self.datas):
          # 图像缩放
          img = cv2.resize(img, (256, 256))
  
          # 归一化
          img = (img.astype("float32") / 255.0 - 0.5) / 0.5
  
          # 转置
          img = img.transpose((2, 0, 1))
  
          # 增加维度
          img = np.expand_dims(img, axis=0)
  
          # 加入输入数据列表
          input_datas.append(img)
  
      # 数据按batch_size切分
      input_datas = np.concatenate(input_datas, 0)
      split_num = (
          len(self.datas) // self.batch_size + 1
          if len(self.datas) % self.batch_size != 0
          else len(self.datas) // self.batch_size
      )
      input_datas = np.array_split(input_datas, split_num)
  
      # 返回预处理完成的数据
      return input_datas
  
file_path: PaddleHub/modules/image/Image_gan/style_transfer/UGATIT_100w/processor.py
imports: import os
  import cv2
  import time
  import base64
  import numpy
label_desc: Use image node_id 3 for calling the Processor obj's underlying member method code with example usage: obj.preprocess() and returns: input_datas