Pool

class deeptrack.math.Pool(pooling_function: Callable, ksize: int | Callable[[...], int] = 3, **kwargs)

Bases: Feature

Downsamples the image by applying a function to local regions of the image.

This class reduces the resolution of an image by dividing it into non-overlapping blocks of size ksize and applying the specified pooling function to each block.

Parameters

pooling_function: function

A function that is applied to each local region of the image. DOES NOT NEED TO BE WRAPPED IN A ANOTHER FUNCTION. Must support the axis argument. Examples include np.mean, np.max, np.min, etc.

ksize: int

Size of the pooling kernel.

cval: number

Value to pad edges with if necessary.

func_kwargs: dict

Additional parameters sent to the pooling function.

Methods Summary

get(image, ksize, **kwargs)

Transform an image [abstract method].

Methods Documentation

get(image, ksize, **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.