class_docstr: PriorBox
  
  Anchor boxes utility for decoding the prior box.
  
  Args:
      cfg (`Dict`):
          retinaface configs.
      image_size (`Linst[int]`):
          input image size.
code: def __init__(self, cfg: Dict, image_size: List[int] = None):
      super().__init__()
      self.min_sizes = cfg["min_sizes"]
      self.steps = cfg["steps"]
      self.clip = cfg["clip"]
      self.image_size = image_size
      self.feature_maps = [
          [
              ceil(self.image_size[0] / step),
              ceil(self.image_size[1] / step),
          ]
          for step in self.steps
      ]
  
imports: from itertools import product
  from typing import Dict, List
  from math import ceil
  import torch
label_desc: Use image node_id 1 to create a new PriorBox object from inherited base classes: object with example: obj = PriorBox(cfg, image_size)