code: def depth_estimation(
      self,
      images=None,
      paths=None,
      batch_size=1,
      output_dir="output",
      visualization=False,
  ):
      # 加载数据
      datas = self.load_datas(paths, images)
  
      # 数据预处理
      input_datas = self.preprocess(datas)
  
      # 模型预测
      results = self.model(input_datas, batch_size=batch_size)[0]
  
      # 结果后处理
      outputs = self.postprocess(
          datas, results, output_dir, visualization
      )
  
      return outputs
  
file_path: PaddleHub/modules/image/depth_estimation/MiDaS_Small/module.py
imports: import os
  import cv2
  import numpy
  from paddlehub import Module
  from paddlehub.module.module import moduleinfo
  from paddle.vision.transforms import Compose
  from MiDaS_Small.utils import write_depth
  from MiDaS_Small.inference import InferenceModel
  from MiDaS_Small.transforms import Resize, NormalizeImage, PrepareForNet
label_desc: Use image node_id 5 for calling the MiDaS_Small obj's underlying member method code with example usage: obj.depth_estimation(images, paths, batch_size, output_dir, visualization) and returns: outputs