class_docstr: Randomly crop a tensor image and its boxes
  
  Args:
  ----
      scale: tuple of floats, relative (min_area, max_area) of the crop
      ratio: tuple of float, relative (min_ratio, max_ratio) where ratio = h/w
code: def __init__(
      self,
      scale: Tuple[float, float] = (0.08, 1.0),
      ratio: Tuple[float, float] = (0.75, 1.33),
  ) -> None:
      self.scale = scale
      self.ratio = ratio
  
imports: import math
  import random
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import numpy
  from doctr.utils.repr import NestedObject
  from ..None import functional
label_desc: Use image node_id 1 to create a new RandomCrop object from inherited base classes: NestedObject with example: obj = RandomCrop(scale, ratio)