class_docstr: COCO dataset for bottom-up pose estimation. 
  
  The dataset loads raw features and apply specified transforms
  to return a dict containing the image tensors and other information.
  
  COCO keypoint indexes::
  
      0: 'nose',
      1: 'left_eye',
      2: 'right_eye',
      3: 'left_ear',
      4: 'right_ear',
      5: 'left_shoulder',
      6: 'right_shoulder',
      7: 'left_elbow',
      8: 'right_elbow',
      9: 'left_wrist',
      10: 'right_wrist',
      11: 'left_hip',
      12: 'right_hip',
      13: 'left_knee',
      14: 'right_knee',
      15: 'left_ankle',
      16: 'right_ankle'
  
  Args:
      dataset_dir (str): Root path to the dataset.
      anno_path (str): Relative path to the annotation file.
      image_dir (str): Path to a directory where images are held.
          Default: None.
      num_joints (int): keypoint numbers
      transform (composed(operators)): A sequence of data transforms.
      shard (list): [rank, worldsize], the distributed env params
      test_mode (bool): Store True when building test or
          validation dataset. Default: False.
docstr: Args:
      imgs (dict): dict of image info.
  
  Returns:
      tuple: Image name & id mapping dicts.
  
      - id2name (dict): Mapping image id to name.
      - name2id (dict): Mapping image name to id.
docstr_tok: ["Args",":","imgs","(","dict",")",":","dict","of","image","info",".","Returns",":","tuple",":","Image","name","&","id","mapping","dicts",".","-","id2name","(","dict",")",":","Mapping","image","id","to","name",".","-","name2id","(","dict",")",":","Mapping","image","name","to","id","."]
code: def _get_mapping_id_name(imgs):
      """
      Args:
          imgs (dict): dict of image info.
  
      Returns:
          tuple: Image name & id mapping dicts.
  
          - id2name (dict): Mapping image id to name.
          - name2id (dict): Mapping image name to id.
      """
      id2name = {}
      name2id = {}
      for image_id, image in imgs.items():
          file_name = image["file_name"]
          id2name[image_id] = file_name
          name2id[file_name] = image_id
  
      return id2name, name2id
  
imports: import os
  import cv2
  import numpy
  import json
  import copy
  import pycocotools
  from pycocotools.coco import COCO
  from .dataset import DetDataset
  from ppdet.core.workspace import register, serializable
label_desc: Use image node_id 3 for calling the KeypointBottomUpCocoDataset obj's underlying member method code with example usage: obj._get_mapping_id_name(imgs) and returns: id2name,  name2id