:py:mod:`wsinfer.patchlib.segment`
==================================

.. py:module:: wsinfer.patchlib.segment

.. autoapi-nested-parse::

   Segment thumbnail of a whole slide image.



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


Functions
~~~~~~~~~

.. autoapisummary::

   wsinfer.patchlib.segment.segment_tissue



.. py:function:: segment_tissue(im_arr: numpy.typing.NDArray, median_filter_size: int = 7, binary_threshold: int = 7, closing_kernel_size: int = 6, min_object_size_px: int = 512, min_hole_size_px: int = 1024) -> numpy.typing.NDArray[numpy.bool_]

   Create a binary tissue mask from an image.

   :param im_arr: RGB image array (uint8) with shape (rows, cols, 3).
   :type im_arr: array-like
   :param median_filter_size: The kernel size for median filtering. Must be odd and greater than one.
   :type median_filter_size: int
   :param binary_threshold: The pixel threshold for image binarization.
   :type binary_threshold: int
   :param closing_kernel_size: The kernel size for morphological closing (in pixel units).
   :type closing_kernel_size: int
   :param min_object_size_px: The minimum area of an object in pixels. If an object is smaller than this area,
                              it is removed and is made into background.
   :type min_object_size_px: int
   :param min_hole_size_px: The minimum area of a hole in pixels. If a hole is smaller than this area, it is
                            filled and is made into foreground.
   :type min_hole_size_px: int

   :returns: Boolean array, where True values indicate presence of tissue.
   :rtype: mask