albumentations.augmentations.dropout.xy_masking

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Mask images with random horizontal and vertical strips sized in pixels or axis-relative fractions, useful for occlusion and spectrogram augmentation.

Members

classXYMasking

XYMaskingclass

XYMasking(
    num_masks_x_range: tuple[int, int] = (0, 0),
    num_masks_y_range: tuple[int, int] = (0, 0),
    mask_x_length_range: tuple[int | float, int | float] = (0, 0),
    mask_y_length_range: tuple[int | float, int | float] = (0, 0),
    fill: float | tuple[float, ...] | random | random_uniform | inpaint_telea | inpaint_ns | grayscale = 0,
    fill_mask: tuple[float, ...] | float | None,
    p: float = 0.5
)

Mask images with random horizontal and vertical strips sized in pixels or axis-relative fractions, useful for occlusion and spectrogram augmentation. Integer endpoints express strip sizes in pixels. Float endpoints in [0.0, 1.0] scale X lengths by image width and Y lengths by image height.

Parameters

Name	Type	Default	Description
num_masks_x_range	tuple[int, int]	(0, 0)	Range for the number of vertical strips. Defaults to (0, 0).
num_masks_y_range	tuple[int, int]	(0, 0)	Range for the number of horizontal strips. Defaults to (0, 0).
mask_x_length_range	One of: tuple[int \| float, int \| float]	(0, 0)	Range of vertical-strip widths. Use two integers for pixels or two floats in [0.0, 1.0] for fractions of image width. Defaults to (0, 0).
mask_y_length_range	One of: tuple[int \| float, int \| float]	(0, 0)	Range of horizontal-strip heights. Use two integers for pixels or two floats in [0.0, 1.0] for fractions of image height. Defaults to (0, 0).
fill	One of: float tuple[float, ...] random random_uniform inpaint_telea inpaint_ns grayscale	0	Value for the dropped pixels. Can be: - int or float: all channels are filled with this value - tuple: tuple of values for each channel - 'random': each pixel is filled with random values - 'random_uniform': each hole is filled with a single random color - 'inpaint_telea': uses OpenCV Telea inpainting method - 'inpaint_ns': uses OpenCV Navier-Stokes inpainting method - 'grayscale': converts dropped regions to grayscale while preserving channel count Default: 0
fill_mask	One of: tuple[float, ...] float None	-	Fill value for dropout regions in the mask. If None, mask regions corresponding to image dropouts are unchanged. Defaults to None.
p	float	0.5	Probability of applying the transform. Defaults to 0.5.

Examples

Use integer ranges for pixel-based strip sizes:

>>> import albumentations as A
>>> import numpy as np
>>> image = np.full((80, 120, 3), 255, dtype=np.uint8)
>>> pixel_transform = A.XYMasking(
...     num_masks_x_range=(1, 2),
...     num_masks_y_range=(1, 1),
...     mask_x_length_range=(8, 16),
...     mask_y_length_range=(4, 8),
...     fill=0,
...     p=1.0,
... )
>>> pixel_image = pixel_transform(image=image)["image"]

Notes

- Each length range must contain either two integers or two floats; mixed endpoint types are invalid. - Integer lengths are sampled inclusively in pixels. Float lengths are sampled between the endpoints, scaled by the corresponding axis, and rounded down. Zero-length strips are omitted, and 1.0 can span the full axis. - At least one of `mask_x_length_range` and `mask_y_length_range` must have a positive maximum. - When using `fill="grayscale"`, `fill_mask` must be None.