class_docstr: An interface between the Scenic DETR implementation and COCO evaluators.
code: def __init__(self, dataset_name: str, **kwargs):
      del dataset_name  # Unused.
  
      self.coco_evaluator = coco_eval.DetectionEvaluator(
          threshold=0.0, **kwargs
      )
      self._included_image_ids = set()
      self._num_examples_added = 0
  
imports: import copy
  import json
  import os
  from typing import Any, Dict, Optional, Set
  from absl import logging
  from flax import core
  from flax import optim
  from flax import traverse_util
  import jax
  from jax.example_libraries import optimizers
  import jax.numpy
  import numpy
  import PIL
  import PIL.ImageDraw
  import PIL.ImageFont
  from scenic.common_lib import image_utils
  from scenic.dataset_lib.coco_dataset import coco_eval
  from scenic.model_lib.base_models import box_utils
  from scenic.train_lib_deprecated import optimizers
  from scenic.train_lib_deprecated import train_utils
  import scipy.special
  import tensorflow
label_desc: Use image node_id 1 to create a new DetrGlobalEvaluator object  with example: obj = DetrGlobalEvaluator(dataset_name)