class_docstr: Dataset for dsdl detection.
  
  Args:
      with_bbox(bool): Load bbox or not, defaults to be True.
      with_polygon(bool): Load polygon or not, defaults to be False.
      with_mask(bool): Load seg map mask or not, defaults to be False.
      with_imagelevel_label(bool): Load image level label or not,
          defaults to be False.
      with_hierarchy(bool): Load hierarchy information or not,
          defaults to be False.
      specific_key_path(dict): Path of specific key which can not
          be loaded by it's field name.
      pre_transform(dict): pre-transform functions before loading.
docstr: Filter annotations according to filter_cfg.
  
  Returns:
      List[dict]: Filtered results.
code: def filter_data(self) -> List[dict]:
      """Filter annotations according to filter_cfg.
  
      Returns:
          List[dict]: Filtered results.
      """
      if self.test_mode:
          return self.data_list
  
      filter_empty_gt = (
          self.filter_cfg.get("filter_empty_gt", False)
          if self.filter_cfg is not None
          else False
      )
      min_size = (
          self.filter_cfg.get("min_size", 0)
          if self.filter_cfg is not None
          else 0
      )
  
      valid_data_list = []
      for i, data_info in enumerate(self.data_list):
          width = data_info["width"]
          height = data_info["height"]
          if filter_empty_gt and len(data_info["instances"]) == 0:
              continue
          if min(width, height) >= min_size:
              valid_data_list.append(data_info)
  
      return valid_data_list
  
file_path: mmdetection/mmdet/datasets/dsdl.py
imports: import os
  from typing import List
  from mmdet.registry import DATASETS
  from .base_det_dataset import BaseDetDataset
label_desc: Use image node_id 3 for calling the DSDLDetDataset obj's underlying member method code with example usage: obj.filter_data() and returns: valid_data_list, self