docstr: vis_root (string): Root directory of videos.
  ann_root (string): directory to store the annotation file
  split (string): val or test
docstr_tok: ["vis_root","(","string",")",":","Root","directory","of","videos",".","ann_root","(","string",")",":","directory","to","store","the","annotation","file","split","(","string",")",":","val","or","test"]
code: def __init__(
      self, vis_processor, text_processor, vis_root, ann_paths
  ):
      """
      vis_root (string): Root directory of videos.
      ann_root (string): directory to store the annotation file
      split (string): val or test
      """
  
      super().__init__(
          vis_processor, text_processor, vis_root, ann_paths
      )
  
      self.text = []
      self.image = []
      self.txt2img = {}
      self.img2txt = {}
  
      txt_id = 0
      for img_id, ann in enumerate(self.annotation):
          self.image.append(ann["video"])
          self.img2txt[img_id] = []
          for i, caption in enumerate(ann["caption"]):
              self.text.append(self.text_processor(caption))
              self.img2txt[img_id].append(txt_id)
              self.txt2img[txt_id] = img_id
              txt_id += 1
  
imports: import os
  from collections import OrderedDict
  from lavis.datasets.datasets.base_dataset import BaseDataset
  from PIL import Image
label_desc: Use image node_id 1 to create a new VideoRetrievalEvalDataset object from inherited base classes: BaseDataset, __DisplMixin with example: obj = VideoRetrievalEvalDataset(vis_processor, text_processor, vis_root, ann_paths)