class_docstr: XML dataset for detection.
  
  Args:
      img_subdir (str): Subdir where images are stored. Default: JPEGImages.
      ann_subdir (str): Subdir where annotations are. Default: Annotations.
      backend_args (dict, optional): Arguments to instantiate the
          corresponding backend. Defaults to None.
docstr: Filter annotations according to filter_cfg.
  
  Returns:
      List[dict]: Filtered results.
docstr_tok: ["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_infos = []
      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_infos.append(data_info)
  
      return valid_data_infos
  
file_path: mmdetection/mmdet/datasets/xml_style.py
imports: import os.path
  import xml.etree.ElementTree
  from typing import List, Optional, Union
  import mmcv
  from mmengine.fileio import get, get_local_path, list_from_file
  from mmdet.registry import DATASETS
  from .base_det_dataset import BaseDetDataset
label_desc: Use image node_id 7 for calling the XMLDataset obj's underlying member method code with example usage: obj.filter_data() and returns: valid_data_infos, self