RandomGridShuffle

Description

Randomly shuffles the grid's cells on an image, mask, or keypoints,
    effectively rearranging patches within the image.
    This transformation divides the image into a grid and then permutes these grid cells based on a random mapping.

    Args:
        grid (tuple[int, int]): Size of the grid for splitting the image into cells. Each cell is shuffled randomly.
            For example, (3, 3) will divide the image into a 3x3 grid, resulting in 9 cells to be shuffled.
            Default: (3, 3)
        p (float): Probability that the transform will be applied. Should be in the range [0, 1].
            Default: 0.5

    Targets:
        image, mask, keypoints, bboxes

    Image types:
        uint8, float32

    Note:
        - This transform maintains consistency across all targets. If applied to an image and its corresponding
          mask or keypoints, the same shuffling will be applied to all.
        - The number of cells in the grid should be at least 2 (i.e., grid should be at least (1, 2), (2, 1), or (2, 2))
          for the transform to have any effect.
        - Keypoints are moved along with their corresponding grid cell.
        - This transform could be useful when only micro features are important for the model, and memorizing
          the global structure could be harmful. For example:
          - Identifying the type of cell phone used to take a picture based on micro artifacts generated by
            phone post-processing algorithms, rather than the semantic features of the photo.
            See more at https://ieeexplore.ieee.org/abstract/document/8622031
          - Identifying stress, glucose, hydration levels based on skin images.

    Mathematical Formulation:
        1. The image is divided into a grid of size (m, n) as specified by the 'grid' parameter.
        2. A random permutation P of integers from 0 to (m*n - 1) is generated.
        3. Each cell in the grid is assigned a number from 0 to (m*n - 1) in row-major order.
        4. The cells are then rearranged according to the permutation P.

    Example:
        >>> import numpy as np
        >>> import albumentations as A
        >>> image = np.array([
        ...     [1, 1, 1, 2, 2, 2],
        ...     [1, 1, 1, 2, 2, 2],
        ...     [1, 1, 1, 2, 2, 2],
        ...     [3, 3, 3, 4, 4, 4],
        ...     [3, 3, 3, 4, 4, 4],
        ...     [3, 3, 3, 4, 4, 4]
        ... ])
        >>> transform = A.RandomGridShuffle(grid=(2, 2), p=1.0)
        >>> result = transform(image=image)
        >>> transformed_image = result['image']
        # The resulting image might look like this (one possible outcome):
        # [[4, 4, 4, 2, 2, 2],
        #  [4, 4, 4, 2, 2, 2],
        #  [4, 4, 4, 2, 2, 2],
        #  [3, 3, 3, 1, 1, 1],
        #  [3, 3, 3, 1, 1, 1],
        #  [3, 3, 3, 1, 1, 1]]

    

Parameters

• grid: tuple[int, int] (default: (3, 3))
• p: float (default: 0.5)

Targets

• Image
• Mask
• Keypoints
• BBoxes