class_docstr: 24 keypoints 3D dataset for pose estimation. 
  
  each item is a list of images
  
  The dataset loads raw features and apply specified transforms
  to return a dict containing the image tensors and other information.
  
  Args:
      dataset_dir (str): Root path to the dataset.
      image_dir (str): Path to a directory where images are held.
class_docstr_tok: ["24","keypoints","3D","dataset","for","pose","estimation",".","each","item","is","a","list","of","images","The","dataset","loads","raw","features","and","apply","specified","transforms","to","return","a","dict","containing","the","image","tensors","and","other","information",".","Args",":","dataset_dir","(","str",")",":","Root","path","to","the","dataset",".","image_dir","(","str",")",":","Path","to","a","directory","where","images","are","held","."]
code: def _generate_multi_frames_list(self):
      act_list = os.listdir(self.dataset_dir)  # 动作列表
      count = 0
      mf_list = []
      annos_dict = {"images": [], "annotations": [], "act_inds": []}
      for act in act_list:  # 对每个动作，生成帧序列
          if "." in act:
              continue
  
          json_path = os.path.join(
              self.dataset_dir, act, self.json_path
          )
          with open(json_path, "r") as j:
              annos = json.load(j)
          length = len(annos["images"])
          for k, v in annos.items():
              if k in annos_dict:
                  annos_dict[k].extend(v)
          annos_dict["act_inds"].extend([act] * length)
  
          mf = [
              [i + j + count for j in range(self.num_frames)]
              for i in range(0, length - self.num_frames + 1)
          ]
          mf_list.extend(mf)
          count += length
  
      print("total data number:", len(mf_list))
      return annos_dict, mf_list
  
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
  from paddle.io import Dataset
label_desc: Use image node_id 2 for calling the Keypoint3DMultiFramesDataset obj's underlying member method code with example usage: obj._generate_multi_frames_list() and returns: annos_dict,  mf_list