NormalizeMinMax

class deeptrack.math.NormalizeMinMax(min: float | Callable[[...], float] = 0, max: float | Callable[[...], float] = 1, featurewise=True, **kwargs)

Bases: Feature

Image normalization.

Transforms the input to be between a minimum and a maximum value using a linear transformation.

Parameters

minfloat

The minimum of the transformation.

maxfloat

The maximum of the transformation.

featurewisebool

Whether to normalize each feature independently

Methods Summary

get(image, min, max, **kwargs)

Transform an image [abstract method].

Methods Documentation

get(image, min, max, **kwargs)

Transform an image [abstract method].

Abstract method that defines how the feature transforms the input. The current value of all properties will be passed as keyword arguments.

Parameters

image‘Image’ or List[‘Image’]

The Image or list of images to transform.

**kwargsDict[str, Any]

The current value of all properties in properties as well as any global arguments.

Returns

‘Image’ or List[‘Image’]

The transformed image or list of images.

Raises

NotImplementedError

Must be overridden by subclasses.