Combine

class deeptrack.features.Combine(features: list[Feature], **kwargs: dict[str, Any])

Bases: StructuralFeature

Combine multiple features into a single feature.

This feature sequentially resolves a list of features and returns their results as a list. Each feature in the features parameter operates on the same input, and their outputs are aggregated into a single list.

Parameters

features: list of Features

A list of features to combine. Each feature will be resolved in the order they appear in the list.

**kwargs: dict of str to Any, optional

Additional keyword arguments passed to the parent StructuralFeature class.

Methods

get(image_list: Any, **kwargs: dict[str, Any]) -> list[Any]

Resolves each feature in the features list on the input image and returns their results as a list.

Examples

>>> import deeptrack as dt
>>> import numpy as np

Define a list of features to combine GaussianBlur and Add: >>> blur_feature = dt.GaussianBlur(sigma=2) >>> add_feature = dt.Add(value=10)

Combine the features: >>> combined_feature = dt.Combine([blur_feature, add_feature])

Define an input image: >>> input_image = np.ones((10, 10))

Apply the combined feature: >>> output_list = combined_feature(input_image)

Methods Summary

get(image_list, **kwargs)

Resolve each feature in the features list on the input image.

Methods Documentation

get(image_list: Any, **kwargs: dict[str, Any]) → list[Any]

Resolve each feature in the features list on the input image.

Parameters

image_list: Any

The input image or list of images to process.

**kwargs: dict of str to Any

Additional arguments passed to each feature’s resolve method.

Returns

list[Any]

A list containing the outputs of each feature applied to the input.