MinMaxNormalization
Bases: ImageOnlyTransform
__init__ ¶
__init__(amin: float = 0.0, amax: float = 1.0, p: float = 1.0, copy: bool = False, **kwargs) -> None
Min-max normalization. Normalizes to range [amin, amax].
Parameters:
Name | Type | Description | Default |
---|---|---|---|
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 ¶
Apply min-max normalization.
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.