docstr: 该方法是专门为cocotools统计标签信息准备，不对图像和标签作任何处理
docstr_tok: ["\u8be5\u65b9\u6cd5\u662f\u4e13\u95e8\u4e3acocotools\u7edf\u8ba1\u6807\u7b7e\u4fe1\u606f\u51c6\u5907\uff0c\u4e0d\u5bf9\u56fe\u50cf\u548c\u6807\u7b7e\u4f5c\u4efb\u4f55\u5904\u7406"]
code: def coco_index(self, index):
      """该方法是专门为cocotools统计标签信息准备，不对图像和标签作任何处理"""
      o_shapes = self.shapes[index][::-1]  # wh to hw
  
      # load labels
      x = self.labels[index]
      labels = x.copy()  # label: class, x, y, w, h
      return torch.from_numpy(labels), o_shapes
  
imports: import math
  import os
  import random
  import shutil
  from pathlib import Path
  import cv2
  import numpy
  import torch
  from PIL import Image, ExifTags
  from torch.utils.data import Dataset
  from tqdm import tqdm
  from build_utils.utils import xyxy2xywh, xywh2xyxy
label_desc: Use image node_id 4 for calling the LoadImagesAndLabels obj's underlying member method code with example usage: obj.coco_index(index) and returns: torch,  o_shapes