class_docstr: RefCOCO dataset.
  
  Only support evaluation now.
code: def load_data_list(self) -> List[dict]:
      with get_local_path(
          self.ann_file, backend_args=self.backend_args
      ) as local_path:
          coco = COCO(local_path)
  
      img_ids = coco.get_img_ids()
  
      data_infos = []
      for img_id in img_ids:
          raw_img_info = coco.load_imgs([img_id])[0]
          ann_ids = coco.get_ann_ids(img_ids=[img_id])
          raw_ann_info = coco.load_anns(ann_ids)
  
          data_info = {}
          img_path = osp.join(
              self.data_prefix["img"], raw_img_info["file_name"]
          )
          data_info["img_path"] = img_path
          data_info["img_id"] = img_id
          data_info["height"] = raw_img_info["height"]
          data_info["width"] = raw_img_info["width"]
          data_info["dataset_mode"] = raw_img_info["dataset_name"]
  
          data_info["text"] = raw_img_info["caption"]
          data_info["custom_entities"] = False
          data_info["tokens_positive"] = -1
  
          instances = []
          for i, ann in enumerate(raw_ann_info):
              instance = {}
              x1, y1, w, h = ann["bbox"]
              bbox = [x1, y1, x1 + w, y1 + h]
              instance["bbox"] = bbox
              instance["bbox_label"] = ann["category_id"]
              instance["ignore_flag"] = 0
              instances.append(instance)
  
          data_info["instances"] = instances
          data_infos.append(data_info)
      return data_infos
  
file_path: mmdetection/mmdet/datasets/mdetr_style_refcoco.py
imports: import os.path
  from typing import List
  from mmengine.fileio import get_local_path
  from mmdet.datasets import BaseDetDataset
  from mmdet.registry import DATASETS
  from .api_wrappers import COCO
label_desc: Use image node_id 1 for calling the MDETRStyleRefCocoDataset obj's underlying member method code with example usage: obj.load_data_list() and returns: data_infos