coerce

deeptrack.image.coerce(images: List[Image | ndarray]) → List[Image]

Coerce a list of images to a consistent type.

This function ensures that all images in the input list are instances of the Image class. Additionally, if any image contains a CuPy array, all images are converted to CuPy arrays to ensure consistency.

Parameters

imagesList[Union[Image, np.ndarray]]

A list of images to be coerced. Each image can be an Image instance or a NumPy array.

Returns

List[Image]

A list of Image instances where all elements are coerced to the same type (CuPy if CuPy arrays are present in any image).

Example

>>> import numpy as np
>>> from deeptrack.image import coerce, Image

Create a list of images:

>>> img1 = Image(np.array([1, 2, 3]))
>>> img2 = np.array([4, 5, 6])

Coerce the images to ensure consistency:

>>> result = coerce([img1, img2])
>>> print([type(img._value) for img in result])
[<class 'numpy.ndarray'>, <class 'numpy.ndarray'>]

If one image is a CuPy array, all are converted:

>>> import cupy
>>> img3 = Image(cupy.array([7, 8, 9]))
>>> result = coerce([img1, img3])
>>> print([type(img._value) for img in result])
[<class 'cupy.ndarray'>, <class 'cupy.ndarray'>]