Load multidimensional image stacks using lazy loading.
A simple class to load OctopusLite data from a directory. Caches data once
it is loaded to prevent excessive I/O to the data server. Can directly
address different channels using the `Channels` enumerator.
Usage
-----
>>> images = DaskOctopusLiteLoader(path = '/path/to/your/data/',
crop = (1200,1600),
transforms = 'path/to/transform_array.npy',
remove_background = True)
>>> gfp = images["GFP"]
>>> gfp_filenames = images.files("GFP")
Parameters
----------
path : str
The path to the dataset.
crop : tuple, optional
An optional tuple which can be used to perform a centred crop on the data.
transforms : np.ndarray, optional
Transforms to be applied to the image stack.
remove_background : bool, optional
Use a estimated polynomial surface to remove uneven illumination.