code: def _separate_prediction_all_preds(
      prediction: List[np.ndarray],
  ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
      pred_bboxes, pred_labels, det_probs = prediction
      return pred_bboxes, pred_labels, det_probs
  
imports: import warnings
  from cleanlab.internal.constants import ALPHA, CUSTOM_SCORE_WEIGHT_BADLOC, CUSTOM_SCORE_WEIGHT_OVERLOOKED, CUSTOM_SCORE_WEIGHT_SWAP, EUC_FACTOR, HIGH_PROBABILITY_THRESHOLD, LOW_PROBABILITY_THRESHOLD, MAX_ALLOWED_BOX_PRUNE, TINY_VALUE, TEMPERATURE, LABEL_OVERLAP_THRESHOLD
  import copy
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, TypeVar
  import numpy
  from cleanlab.internal.object_detection_utils import softmin1d, assert_valid_aggregation_weights, assert_valid_inputs
label_desc: Use image node_id 7 for calling a global function with example usage: _separate_prediction_all_preds(prediction) and returns: pred_bboxes,  pred_labels,  det_probs