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.
        p (float): Probability that the transform will be applied.

    Targets:
        image, mask, keypoints

    Image types:
        uint8, float32

    Examples:
        >>> import albumentations as A
        >>> transform = A.Compose([
            A.RandomGridShuffle(grid=(3, 3), p=1.0)
        ])
        >>> transformed = transform(image=my_image, mask=my_mask)
        >>> image, mask = transformed['image'], transformed['mask']
        # This will shuffle the 3x3 grid cells of `my_image` and `my_mask` randomly.
        # Mask and image are shuffled in a consistent way
    Note:
        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.
    

Parameters

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

Targets

• Image
• Mask
• Keypoints

Try it out