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

min: float

The minimum of the transformation.

max: float

The maximum of the transformation.

featurewise: bool

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: np.ndarray or list of np.ndarray or Image or list of Images

The image or list of images to transform.

**kwargs: dict of str to Any

The current value of all properties in properties, as well as any global arguments passed to the feature.

Returns

Image or list of Images

The transformed image or list of images.

Raises

NotImplementedError

Raised if this method is not overridden by subclasses.