class_docstr: An interface between the Scenic DETR implementation and COCO evaluators.
docstr: Computes the metrics for all added predictions.
docstr_tok: ["Computes","the","metrics","for","all","added","predictions","."]
code: def compute_metrics(
      self,
      included_image_ids: Optional[Set[int]] = None,
      clear_annotations: Optional[bool] = True,
  ) -> Dict[str, Any]:
      """Computes the metrics for all added predictions."""
      if included_image_ids is not None:
          self.coco_evaluator.coco.reload_ground_truth(
              included_image_ids
          )
      return self.coco_evaluator.compute_coco_metrics(
          clear_annotations=clear_annotations
      )
  
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 3 for calling the DetrGlobalEvaluator obj's underlying member method code with example usage: obj.compute_metrics(included_image_ids, clear_annotations) and returns: self