PercentileNormalization

Bases: ImageOnlyTransform

init ¶

__init__(lower: float = 0.01, upper: float = 99.99, p: float = 1.0, copy: bool = False, **kwargs) -> None

Percentile normalization. Normalizes to percentile range [lower, upper].

Parameters:

Name	Type	Description	Default
`lower`	`float, default=0.01`	Lower percentile.	`0.01`
`upper`	`float, default=99.99`	Clamp max value. No clamping performed if None.	`99.99`
`p`	`float, default=1.0`	Probability of applying the transformation.	`1.0`
`copy`	`bool, default=False`	If True, normalize the copy of the input.	`False`

apply(image: ndarray, **kwargs) -> np.ndarray

Apply percentile normalization to input image.

Parameters:

Name	Type	Description	Default
`image`	`ndarray`	Input image to be normalized. Shape (H, W, C)\|(H, W).	required

Returns:

Type	Description
`ndarray`	np.ndarray: Normalized image. Same shape as input. dtype: float32.

get_transform_init_args_names()

Get the names of the transformation arguments.