class_docstr: Basic Reader Class
class_docstr_tok: ["Basic","Reader","Class"]
code: def __init__(self, scp_path, value_processor=lambda x: x):
      self.index_dict = parse_scripts(
          scp_path, value_processor=value_processor, num_tokens=2
      )
      self.index_keys = list(self.index_dict.keys())
      self.face_align_model = face_alignment.FaceAlignment(
          face_alignment.LandmarksType._2D,
          flip_input=False,
          device="cuda:0" if torch.cuda.is_available() else "cpu",
      )
  
imports: import cvtransforms
  import face_alignment
  import numpy
  import skimage.transform
  import skvideo.io
  import torch
  from models import pretrained
label_desc: Use image node_id 1 to create a new VideoReader object from inherited base classes: object with example: obj = VideoReader(scp_path, value_processor)