code: def Segmentation(
      self,
      images=None,
      paths=None,
      batch_size=1,
      input_size=320,
      output_dir="output",
      visualization=False,
  ):
      # 初始化数据处理器
      processor = Processor(paths, images, batch_size, input_size)
  
      # 模型预测
      outputs = self.predict(processor.input_datas)
  
      # 预测结果后处理
      results = processor.postprocess(
          outputs, visualization=visualization, output_dir=output_dir
      )
  
      return results
  
file_path: PaddleHub/modules/image/semantic_segmentation/U2Netp/module.py
imports: import os
  import paddle
  import paddle.nn
  import numpy
  from U2Netp.u2net import U2NETP
  from U2Netp.processor import Processor
  from paddlehub.module.module import moduleinfo
label_desc: Use image node_id 3 for calling the U2Netp obj's underlying member method code with example usage: obj.Segmentation(images, paths, batch_size, input_size, output_dir, visualization) and returns: results