text: Title: AddToBrightness not deterministic/reproducible
  Body: I have found that the result of `AddToBrightness` is not deterministic, even when a seed is provided. Given that other probabilistic augmentations such as `Dropout` do seem to be deterministic when a seed is provided, I assume this is unexpected behavior.
  
  The behavior can be reproduced with the following snippet:
  ```python
  import hashlib
  
  import imgaug
  import numpy as np
  from imgaug.augmenters import AddToBrightness, Dropout, Sequential
  from numpy.random import default_rng
  
  numpy_random_generator = default_rng(seed=42)
  image = numpy_random_generator.integers(0, 255, (200, 200, 3), dtype=np.uint8)
  
  imgaug_random_generator = imgaug.random.RNG(numpy_random_generator)
  sequential = Sequential(
      children=[
          AddToBrightness(seed=imgaug_random_generator),
          Dropout(seed=imgaug_random_generator),
      ],
      seed=imgaug_random_generator,
  )
  
  image = sequential.augment_image(image)
  
  
  def hash_image(image):
      md5_hash = hashlib.md5()
      md5_hash.update(image.data.tobytes())
      return int(md5_hash.hexdigest(), 16)
  
  
  print(hash_image(image))
  ```
  
  When running this code, the hash will be different each time. I expect the hash to be the same each time, as the seed is provided.
  When commenting out `AddToBrightness` and only applying `Dropout` augmentation, the seed is the same on each run.