Add bboxes to grid shuffle

[ternaus]

Fixes: #1948

Summary by Sourcery

Add support for grid shuffle transformations on bounding boxes and enhance the RandomGridShuffle transformation to include bounding boxes as a target. Introduce a new function bboxes_grid_shuffle and provide comprehensive tests for its functionality.

New Features:

• Introduce a new function bboxes_grid_shuffle to apply grid shuffle transformations to bounding boxes, allowing for more flexible data augmentation.

Enhancements:

• Refactor the RandomGridShuffle transformation to include bounding boxes as a target, enhancing its functionality.

Tests:

• Add comprehensive tests for the new bboxes_grid_shuffle function, covering various scenarios including basic functionality, minimum area and visibility filters, and handling of extra fields.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR adds support for bounding boxes in the RandomGridShuffle transform by implementing a new bboxes_grid_shuffle function and reorganizing related code. The implementation handles splitting and merging of bounding boxes when they cross tile boundaries, with options to filter based on minimum area and visibility requirements.

Class diagram for RandomGridShuffle and related functions

classDiagram
    class RandomGridShuffle {
        - grid: tuple[int, int]
        - p: float
        - always_apply: bool | None
        + apply(img: np.ndarray, tiles: np.ndarray, mapping: list[int], **params: Any) np.ndarray
        + apply_to_bboxes(bboxes: np.ndarray, tiles: np.ndarray, mapping: np.ndarray, **params: Any) np.ndarray
        + apply_to_keypoints(keypoints: np.ndarray, tiles: np.ndarray, mapping: np.ndarray, **params: Any) np.ndarray
        + get_params_dependent_on_data(params: dict[str, Any], data: dict[str, Any]) dict[str, np.ndarray]
        + get_transform_init_args_names() tuple[str, ...]
    }

    class fgeometric {
        + swap_tiles_on_image(image: np.ndarray, tiles: np.ndarray, mapping: list[int] | None) np.ndarray
        + swap_tiles_on_keypoints(keypoints: np.ndarray, tiles: np.ndarray, mapping: np.ndarray) np.ndarray
        + bboxes_grid_shuffle(bboxes: np.ndarray, tiles: np.ndarray, mapping: list[int], image_shape: tuple[int, int], min_area: float | None, min_visibility: float | None) np.ndarray
        + create_shape_groups(tiles: np.ndarray) dict[tuple[int, int], list[int]]
        + shuffle_tiles_within_shape_groups(shape_groups: dict[tuple[int, int], list[int]], random_generator: np.random.Generator) list[int]
    }

    RandomGridShuffle --> fgeometric : uses

Loading

File-Level Changes

Change	Details	Files
Added bounding box support to RandomGridShuffle transform	Implemented bboxes_grid_shuffle function to handle bbox transformations Added min_area and min_visibility filtering options for split bboxes Updated transform targets to include bboxes Added comprehensive test cases for bbox handling	albumentations/augmentations/geometric/functional.py albumentations/augmentations/geometric/transforms.py tests/test_bbox.py README.md
Reorganized code structure for better maintainability	Moved geometric-related functions from functional.py to geometric/functional.py Moved RandomGridShuffle from transforms.py to geometric/transforms.py Updated import statements and references accordingly	albumentations/augmentations/geometric/functional.py albumentations/augmentations/geometric/transforms.py albumentations/augmentations/transforms.py albumentations/augmentations/functional.py
Enhanced test coverage	Added tests for basic bbox grid shuffle functionality Added tests for min_area and min_visibility filtering Added tests for bbox splitting and component handling Updated existing tests to reflect code reorganization	tests/test_bbox.py tests/test_targets.py tests/test_transforms.py tests/test_serialization.py

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟡 Testing: 2 issues found
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 90.39%. Comparing base (b1a79c2) to head (71125c1).
Report is 252 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2057       +/-   ##
=========================================
+ Coverage      0   90.39%   +90.39%     
=========================================
  Files         0       46       +46     
  Lines         0     7652     +7652     
=========================================
+ Hits          0     6917     +6917     
- Misses        0      735      +735     

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