class_docstr: This structure stores a list of boxes as a Nx4 torch.Tensor.
  It supports some common methods about boxes
  (`area`, `clip`, `nonempty`, etc),
  and also behaves like a Tensor
  (support indexing, `to(device)`, `.device`, and iteration over all boxes)
  
  Attributes:
      tensor (torch.Tensor): float matrix of Nx4. Each row is (x1, y1, x2, y2).
class_docstr_tok: ["This","structure","stores","a","list","of","boxes","as","a","Nx4","torch.Tensor",".","It","supports","some","common","methods","about","boxes","(","`","area","`",",","`","clip","`",",","`","nonempty","`",",","etc",")",",","and","also","behaves","like","a","Tensor","(","support","indexing",",","`","to","(","device",")","`",",","`",".device","`",",","and","iteration","over","all","boxes",")","Attributes",":","tensor","(","torch.Tensor",")",":","float","matrix","of","Nx4",".","Each","row","is","(","x1",",","y1",",","x2",",","y2",")","."]
docstr: Returns:
      The box centers in a Nx2 array of (x, y).
docstr_tok: ["Returns",":","The","box","centers","in","a","Nx2","array","of","(","x",",","y",")","."]
code: def get_centers(self) -> torch.Tensor:
      """
      Returns:
          The box centers in a Nx2 array of (x, y).
      """
      return (self.tensor[:, :2] + self.tensor[:, 2:]) / 2
  
imports: import math
  from enum import IntEnum, unique
  from typing import Any, List, Tuple, Union
  import numpy
  import torch
label_desc: Use image node_id 11 for calling the Boxes obj's underlying member method code with example usage: obj.get_centers() and returns: unknown