def filter_labeled(labeled,
remove_bordering=False,
min_size=None,
max_size=None):
'''Filter labeled regions based on a series of conditions
.. versionadded :: 1.4.1
Parameters
----------
labeled : labeled array
remove_bordering : bool, optional
whether to remove regions that touch the border
min_size : int, optional
Minimum size (in pixels) of objects to keep (default is no minimum)
max_size : int, optional
Maximum size (in pixels) of objects to keep (default is no maximum)
Returns
-------
filtered : labeled array
nr : int
number of new labels
'''
from mahotas.labeled import remove_regions, labeled_size
import mahotas as mh
labeled = _as_labeled(labeled, labeled, 'filter_labeled')
if remove_bordering:
labeled = mh.labeled.remove_bordering(labeled)
labeled, nr = mh.labeled.relabel(labeled)
else:
nr = labeled.max()
to_keep = np.ones(nr + 1, bool)
if min_size is not None or max_size is not None:
sizes = labeled_size(labeled)
if min_size:
to_keep &= (sizes >= min_size)
if max_size:
to_keep &= (sizes <= max_size)
to_keep[0] = True
to_remove = np.where(~to_keep)
labeled = remove_regions(labeled, to_remove)
labeled, nr = mh.labeled.relabel(labeled, inplace=True)
return labeled, nr
def filter_labeled(labeled, remove_bordering=False, min_size=None, max_size=None):
"""Filter labeled regions based on a series of conditions
.. versionadded :: 1.4.1
Parameters
----------
labeled : labeled array
remove_bordering : bool, optional
whether to remove regions that touch the border
min_size : int, optional
Minimum size (in pixels) of objects to keep (default is no minimum)
max_size : int, optional
Maximum size (in pixels) of objects to keep (default is no maximum)
Returns
-------
filtered : labeled array
nr : int
number of new labels
"""
from mahotas.labeled import remove_regions, labeled_size
import mahotas as mh
labeled = _as_labeled(labeled, labeled, "filter_labeled")
if remove_bordering:
labeled = mh.labeled.remove_bordering(labeled)
labeled, nr = mh.labeled.relabel(labeled)
else:
nr = labeled.max()
to_keep = np.ones(nr + 1, bool)
if min_size is not None or max_size is not None:
sizes = labeled_size(labeled)
if min_size:
to_keep &= sizes >= min_size
if max_size:
to_keep &= sizes <= max_size
to_keep[0] = True
to_remove = np.where(~to_keep)
labeled = remove_regions(labeled, to_remove)
labeled, nr = mh.labeled.relabel(labeled, inplace=True)
return labeled, nr
def remove_regions_where(labeled, conditions, inplace=False):
'''Remove regions based on a boolean array
A region is removed if ``conditions[region-id]`` evaluates true.
This function **does not** relabel its arguments. You can use the
``relabel`` function for that::
removed = relabel(remove_regions_where(labeled, conditions))
Or, saving one image allocation::
removed = relabel(remove_regions(labeled, conditions), inplace=True)
This is the same, but reuses the memory in the relabeling operation.
See Also
--------
remove_regions : function
Variation of this function which uses integer indexing
'''
regions, = np.where(conditions)
return remove_regions(labeled, regions, inplace=inplace)
def remove_regions_where(labeled, conditions, inplace=False):
'''Remove regions based on a boolean array
A region is removed if ``conditions[region-id]`` evaluates true.
This function **does not** relabel its arguments. You can use the
``relabel`` function for that::
removed = relabel(remove_regions_where(labeled, conditions))
Or, saving one image allocation::
removed = relabel(remove_regions(labeled, conditions), inplace=True)
This is the same, but reuses the memory in the relabeling operation.
See Also
--------
remove_regions : function
Variation of this function which uses integer indexing
'''
regions, = np.where(conditions)
return remove_regions(labeled, regions, inplace=inplace)
