class_docstr: Apply zoom blur transform. See https://arxiv.org/abs/1903.12261.
  
  Args:
      max_factor ((float, float) or float): range for max factor for blurring.
          If max_factor is a single float, the range will be (1, limit). Default: (1, 1.31).
          All max_factor values should be larger than 1.
      step_factor ((float, float) or float): If single float will be used as step parameter for np.arange.
          If tuple of float step_factor will be in range `[step_factor[0], step_factor[1])`. Default: (0.01, 0.03).
          All step_factor values should be positive.
      p (float): probability of applying the transform. Default: 0.5.
  
  Targets:
      image
  
  Image types:
      Any
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code: def get_params(self) -> Dict[str, Any]:
      max_factor = random.uniform(
          self.max_factor[0], self.max_factor[1]
      )
      step_factor = random.uniform(
          self.step_factor[0], self.step_factor[1]
      )
      return {"zoom_factors": np.arange(1.0, max_factor, step_factor)}
  
imports: import random
  import warnings
  from typing import Any, Dict, List, Sequence, Tuple
  import cv2
  import numpy
  from albumentations import random_utils
  from albumentations.augmentations import functional
  from albumentations.augmentations.blur import functional
  from albumentations.core.transforms_interface import ImageOnlyTransform, ScaleFloatType, ScaleIntType, to_tuple
label_desc: Use image node_id 3 for calling the ZoomBlur obj's underlying member method code with example usage: obj.get_params() and returns: dict