Unify parameters

[ternaus]

Summary by Sourcery

Unify parameter names across transformation classes, deprecating old names and introducing new ones for consistency. Update documentation and tests to reflect these changes.

Enhancements:

• Unify parameter names across various transformation classes to improve consistency and readability.
• Deprecate old parameter names and introduce new ones, such as replacing 'value' with 'fill' and 'mask_value' with 'fill_mask'.
• Add model validators to ensure deprecated fields are correctly mapped to new fields.

Documentation:

• Update documentation to reflect changes in parameter names and usage, ensuring clarity for users.

Tests:

• Modify tests to align with the new parameter naming conventions, ensuring they validate the updated functionality.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request unifies and standardizes parameter naming across various transforms in the library, particularly focusing on parameters related to border handling and fill values. The main changes involve renaming parameters to be more consistent, deprecating old parameter names while maintaining backward compatibility, and updating the documentation accordingly.

Class diagram for updated transform parameters

classDiagram
    class BaseDistortion {
        -interpolation: int
        -mask_interpolation: int
        +apply(img: np.ndarray, map_x: np.ndarray, map_y: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, map_x: np.ndarray, map_y: np.ndarray, **params: Any): np.ndarray
    }
    class ElasticTransform {
        -interpolation: int
        -mask_interpolation: int
        +apply(img: np.ndarray, map_x: np.ndarray, map_y: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, map_x: np.ndarray, map_y: np.ndarray, **params: Any): np.ndarray
    }
    class Perspective {
        -border_mode: int
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, matrix, max_width, max_height, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, matrix, max_width, max_height, **params: Any): np.ndarray
    }
    class Affine {
        -border_mode: int
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, matrix, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, matrix, **params: Any): np.ndarray
    }
    class Pad {
        -border_mode: BorderModeType
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, **params: Any): np.ndarray
    }
    class PadIfNeeded {
        -border_mode: int
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, **params: Any): np.ndarray
    }
    class Rotate {
        -border_mode: int
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, matrix, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, matrix, **params: Any): np.ndarray
    }
    class SafeRotate {
        -border_mode: int
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, matrix, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, matrix, **params: Any): np.ndarray
    }
    class CropAndPad {
        -border_mode: BorderModeType
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, crop_params: Sequence[int], pad_params: Sequence[int], **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, crop_params: Sequence[int], pad_params: Sequence[int], **params: Any): np.ndarray
    }
    class XYMasking {
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, **params: Any): np.ndarray
    }
    class CoarseDropout {
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, **params: Any): np.ndarray
    }
    class Erasing {
        -fill: ColorType
        -fill_mask: ColorType
        +apply(img: np.ndarray, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, **params: Any): np.ndarray
    }
    class MaskDropout {
        -fill: float | Literal["inpaint"]
        -fill_mask: float
        +apply(img: np.ndarray, dropout_mask: np.ndarray | None, **params: Any): np.ndarray
        +apply_to_mask(mask: np.ndarray, dropout_mask: np.ndarray | None, **params: Any): np.ndarray
    }

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File-Level Changes

Change	Details	Files
Standardize border and fill value parameters across transforms	Rename 'value' to 'fill' for image fill values Rename 'mask_value' to 'fill_mask' for mask fill values Rename 'border_mode' to be consistent across all transforms Add deprecation warnings for old parameter names Update parameter validation logic to handle both old and new parameter names	albumentations/augmentations/geometric/transforms.py albumentations/augmentations/geometric/rotate.py albumentations/augmentations/crops/transforms.py
Remove redundant random transform classes	Remove RandomAffine in favor of Affine Remove RandomErasing in favor of Erasing Remove RandomRotation in favor of Rotate Remove other redundant Random* classes	README.md tests/test_augmentations.py
Update transform initialization and parameter handling	Standardize parameter order in init methods Move p and always_apply parameters to end of parameter list Update parameter validation in model schemas Add proper type hints for parameters	albumentations/augmentations/dropout/transforms.py albumentations/augmentations/geometric/resize.py albumentations/core/transforms_interface.py

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[sourcery-ai]

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

Overall Comments:

• Please document the transforms that were removed (like RandomRotation, RandomHorizontalFlip etc.) in the PR description, explaining the rationale for their removal. This will help users understand and adapt to the breaking changes.

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟡 Testing: 2 issues found
• 🟡 Complexity: 2 issues found
• 🟢 Documentation: all looks good

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[codecov]

Codecov Report

Attention: Patch coverage is 93.77593% with 15 lines in your changes missing coverage. Please review.

Project coverage is 89.72%. Comparing base (b1a79c2) to head (858eccb).
Report is 292 commits behind head on main.

Files with missing lines	Patch %	Lines
albumentations/augmentations/crops/transforms.py	92.10%	6 Missing ⚠️
...bumentations/augmentations/geometric/transforms.py	93.58%	5 Missing ⚠️
albumentations/augmentations/dropout/xy_masking.py	80.00%	2 Missing ⚠️
albumentations/augmentations/geometric/rotate.py	91.66%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2160       +/-   ##
=========================================
+ Coverage      0   89.72%   +89.72%     
=========================================
  Files         0       47       +47     
  Lines         0     8469     +8469     
=========================================
+ Hits          0     7599     +7599     
- Misses        0      870      +870     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

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