class_docstr: A data structure interface of ReID task.
  
  It's used as interfaces between different components.
  
  Meta field:
      img_shape (Tuple): The shape of the corresponding input image.
          Used for visualization.
      ori_shape (Tuple): The original shape of the corresponding image.
          Used for visualization.
      num_classes (int): The number of all categories.
          Used for label format conversion.
  
  Data field:
      gt_label (LabelData): The ground truth label.
      pred_label (LabelData): The predicted label.
      scores (torch.Tensor): The outputs of model.
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code: def gt_label(self, value: LabelData):
      self.set_field(value, "_gt_label", dtype=LabelData)
  
file_path: mmdetection/mmdet/structures/reid_data_sample.py
imports: from numbers import Number
  from typing import Sequence, Union
  import mmengine
  import numpy
  import torch
  from mmengine.structures import BaseDataElement, LabelData
label_desc: Use image node_id 2 for calling the ReIDDataSample obj's underlying member method code with example usage: obj.gt_label(value) without return types