loki2.utils.tools
=================

.. py:module:: loki2.utils.tools

.. autoapi-nested-parse::

   Utility functions for Loki2.

   This module provides various helper functions for image processing,
   dictionary manipulation, file handling, and other common operations
   used throughout the Loki2 framework.





Module Contents
---------------

.. py:function:: get_bounding_box(img: numpy.ndarray) -> List[int]

   Get bounding box coordinate information.

   :param img: Binary or labeled image array.

   :returns: Bounding box coordinates as [rmin, rmax, cmin, cmax].
   :rtype: List[int]


.. py:function:: remove_small_objects_cp(pred: cupy.ndarray, min_size: int = 64, connectivity: int = 1) -> cupy.ndarray

   Remove connected components smaller than the specified size.

   This function is taken from skimage.morphology.remove_small_objects, but the warning
   is removed when a single label is provided. Uses CuPy for GPU acceleration.

   :param pred: Input labelled array (CuPy array).
   :param min_size: Minimum size of instance in output array. Defaults to 64.
   :param connectivity: The connectivity defining the neighborhood of a pixel.
                        Defaults to 1.

   :returns: Output array with instances removed under min_size.
   :rtype: cp.ndarray

   :raises ValueError: If negative value labels are found in the input.


.. py:function:: remove_small_objects(pred: numpy.ndarray, min_size: int = 64, connectivity: int = 1) -> numpy.ndarray

   Remove connected components smaller than the specified size.

   This function is taken from skimage.morphology.remove_small_objects, but the warning
   is removed when a single label is provided. Uses NumPy/ SciPy for CPU processing.

   :param pred: Input labelled array (NumPy array).
   :param min_size: Minimum size of instance in output array. Defaults to 64.
   :param connectivity: The connectivity defining the neighborhood of a pixel.
                        Defaults to 1.

   :returns: Output array with instances removed under min_size.
   :rtype: np.ndarray

   :raises ValueError: If negative value labels are found in the input.


.. py:function:: unflatten_dict(d: dict, sep: str = '.') -> dict

   Unflatten a flattened dictionary (create a nested dictionary).

   :param d: Dictionary to be nested (with keys separated by separator).
   :param sep: Separator used in flattened keys. Defaults to '.'.

   :returns: Nested dictionary reconstructed from flattened keys.
   :rtype: dict

   .. rubric:: Example

   >>> d = {'a.b': 1, 'a.c': 2}
   >>> unflatten_dict(d)
   {'a': {'b': 1, 'c': 2}}


.. py:function:: remap_label(pred: numpy.ndarray, by_size: bool = False) -> numpy.ndarray

   Rename all instance IDs so that IDs are contiguous (e.g., [0, 1, 2, 3]).

   The ordering of instances (which one comes first) is preserved unless
   by_size=True, in which case instances will be reordered so that larger
   nuclei have smaller IDs.

   :param pred: The 2D array containing instances where each instance is marked
                by a non-zero integer.
   :param by_size: If True, reorder instances so that larger nuclei have smaller
                   IDs. Defaults to False.

   :returns: Array with remapped contiguous instance IDs.
   :rtype: np.ndarray