Fix random rain

[ternaus]

Summary by Sourcery

Allow the drop_length parameter in RandomRain to be None, which will cause the drop length to be automatically calculated based on the image height.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request modifies the RandomRain transform to allow the raindrop length to be dynamically calculated based on the image height. This is achieved by allowing the drop_length parameter to be set to None, in which case the raindrop length is calculated as height // 8. This change ensures that the rain effect scales appropriately with different image sizes.

Updated class diagram for RandomRain

classDiagram
  class RandomRain {
    -slant_range: tuple[float, float]
    -drop_length: int | None
    -drop_width: int
    -drop_color: tuple[int, int, int]
    -blur_value: int
    -rain_type: str
    -p: float
    __init__(
      slant_range: tuple[float, float],
      drop_length: int | None,
      drop_width: int,
      drop_color: tuple[int, int, int],
      blur_value: int,
      rain_type: str,
      p: float
    )
    get_params_dependent_on_data(img: np.ndarray, params: dict) dict
  }
  note for RandomRain "drop_length can now be None, defaulting to height // 8"

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File-Level Changes

Change	Details	Files
Allow dynamic raindrop length based on image height.	Modified the drop_length parameter in RandomRain to accept None as a valid value. When drop_length is None, the raindrop length is calculated dynamically as height // 8. Updated the schema to allow None as a valid value for drop_length.	albumentations/augmentations/transforms.py

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes - here's some feedback:

Overall Comments:

• Consider adding a short integration test to verify the new drop_length functionality.

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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