class_docstr: Transformation abstract class.
  
  Parameters
  ----------
  p : float or None
      Probability of executing this transform
  data_indices : tuple or None
      Indices where the transforms need to be applied
class_docstr_tok: ["Transformation","abstract","class",".","Parameters","--","--","--","--","--","p",":","float","or","None","Probability","of","executing","this","transform","data_indices",":","tuple","or","None","Indices","where","the","transforms","need","to","be","applied"]
docstr: Method to randomly determine whether to use this transform.
  
  Returns
  -------
  out : bool
      Boolean flag. True if the transform is used.
code: def use_transform(self):
      """
      Method to randomly determine whether to use this transform.
  
      Returns
      -------
      out : bool
          Boolean flag. True if the transform is used.
      """
      if random.random() <= self.p:
          self.state_dict["use"] = True
          return True
  
      self.state_dict["use"] = False
      return False
  
imports: import copy
  import random
  from abc import ABCMeta, abstractmethod
  import cv2
  import numpy
  from solt.utils import Serializable
  from solt.constants import ALLOWED_INTERPOLATIONS, ALLOWED_PADDINGS
  from ._data import DataContainer, Keypoints
  from solt.utils import img_shape_checker, validate_parameter
label_desc: Use image node_id 3 for calling the BaseTransform obj's underlying member method code with example usage: obj.use_transform() and returns: False, True