code: def Segmentation(
      self,
      images=None,
      paths=None,
      batch_size=1,
      output_dir="output",
      visualization=False,
  ):
      # 加载数据处理器
      datas = self.load_datas(paths, images)
  
      # 获取输入数据
      input_datas = self.preprocess(datas, batch_size)
  
      # 模型预测
      outputs = [
          self.model(paddle.to_tensor(input_data))
          for input_data in input_datas
      ]
  
      # 结果后处理
      results = self.postprocess(
          outputs, datas, output_dir, visualization
      )
  
      # 返回结果
      return results
  
file_path: PaddleHub/modules/image/semantic_segmentation/SINet_Portrait_Segmentation/module.py
imports: import os
  import cv2
  import paddle
  import numpy
  from paddle.nn import Layer
  from paddlehub.module.module import moduleinfo
label_desc: Use image node_id 5 for calling the SINet_Portrait_Segmentation obj's underlying member method code with example usage: obj.Segmentation(images, paths, batch_size, output_dir, visualization) and returns: results