dcnum.segm.segm_thresh
======================

.. py:module:: dcnum.segm.segm_thresh


Classes
-------

.. autoapisummary::

   dcnum.segm.segm_thresh.SegmentThresh


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

.. py:class:: SegmentThresh(*, num_workers: int | None = None, kwargs_mask: dict | None = None, debug: bool = False, **kwargs)

   Bases: :py:obj:`dcnum.segm.segmenter_mpo.MPOSegmenter`


   Segmenter with multiprocessing operation

   :param num_workers: Number of workers (processes) to spawn
   :param kwargs_mask: Keyword arguments for mask post-processing (see `process_labels`)
   :type kwargs_mask: dict
   :param debug: Debugging parameters
   :type debug: bool
   :param kwargs: Additional, optional keyword arguments for ``segment_algorithm``
                  defined in the subclass.


   .. py:attribute:: mask_postprocessing
      :value: True


      Whether to enable mask post-processing.
      If disabled, you should make sure that your mask is properly defined
      and cleaned or you have to call `process_labels` in your
      ``segment_algorithm`` implementation.


   .. py:attribute:: mask_default_kwargs

      Default keyword arguments for mask post-processing.
      See `process_labels` for available options.


   .. py:attribute:: requires_background_correction
      :value: True


      Whether the segmenter requires a background-corrected image


   .. py:method:: segment_algorithm(image, *, thresh: float = -6)
      :staticmethod:


      Mask retrieval using basic thresholding

      :param image: Background-corrected frame image
      :type image: 2d ndarray
      :param thresh: Threshold value for creation of binary mask; a negative value
                     means that pixels darker than the background define the threshold
                     level.
      :type thresh: float

      :returns: **mask** -- Mask image for the given index
      :rtype: 2d boolean ndarray