code: def bbox_center_distance(bboxes: Tensor, priors: Tensor) -> Tensor:
      """Compute the center distance between bboxes and priors.
  
      Args:
          bboxes (Tensor): Shape (n, 4) for , "xyxy" format.
          priors (Tensor): Shape (n, 4) for priors, "xyxy" format.
  
      Returns:
          Tensor: Center distances between bboxes and priors.
      """
      bbox_cx = (bboxes[:, 0] + bboxes[:, 2]) / 2.0
      bbox_cy = (bboxes[:, 1] + bboxes[:, 3]) / 2.0
      bbox_points = torch.stack((bbox_cx, bbox_cy), dim=1)
  
      priors_cx = (priors[:, 0] + priors[:, 2]) / 2.0
      priors_cy = (priors[:, 1] + priors[:, 3]) / 2.0
      priors_points = torch.stack((priors_cx, priors_cy), dim=1)
  
      distances = (
          (priors_points[:, None, :] - bbox_points[None, :, :])
          .pow(2)
          .sum(-1)
          .sqrt()
      )
  
      return distances
  
file_path: mmdetection/mmdet/models/task_modules/assigners/atss_assigner.py
imports: import warnings
  from typing import List, Optional
  import torch
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import TASK_UTILS
  from mmdet.utils import ConfigType
  from .assign_result import AssignResult
  from .base_assigner import BaseAssigner
label_desc: Use image node_id 1 for calling a global function with example usage: bbox_center_distance(bboxes, priors) and returns: distances