code: def _euc_dis(box1: List[float], box2: List[float]) -> float:
      """Calculates the Euclidean distance between `box1` and `box2`."""
      x1, y1 = (box1[0] + box1[2]) / 2, (box1[1] + box1[3]) / 2
      x2, y2 = (box2[0] + box2[2]) / 2, (box2[1] + box2[3]) / 2
      p1 = np.array([x1, y1])
      p2 = np.array([x2, y2])
      val2 = np.exp(-np.linalg.norm(p1 - p2) * EUC_FACTOR)
      return val2
  
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 16 for calling a global function with example usage: _euc_dis(box1, box2) and returns: val2