def edit_distance(aseg, gt, size_threshold=1000, sp=None):
"""Find the number of splits and merges needed to convert `aseg` to `gt`.
Parameters
----------
aseg : np.ndarray, int type, arbitrary shape
The candidate automatic segmentation being evaluated.
gt : np.ndarray, int type, same shape as `aseg`
The ground truth segmentation.
size_threshold : int or float, optional
Ignore splits or merges smaller than this number of voxels.
sp : np.ndarray, int type, same shape as `aseg`, optional
A superpixel map. If provided, compute the edit distance to the best
possible agglomeration of `sp` to `gt`, rather than to `gt` itself.
Returns
-------
(false_merges, false_splits) : float
The number of splits and merges needed to convert aseg to gt.
"""
if sp is None:
return raw_edit_distance(aseg, gt, size_threshold)
else:
import agglo
bps = agglo.best_possible_segmentation(sp, gt)
return raw_edit_distance(aseg, bps, size_threshold)
def edit_distance(aseg, gt, size_threshold=1000, sp=None):
"""Find the number of splits and merges needed to convert `aseg` to `gt`.
Parameters
----------
aseg : np.ndarray, int type, arbitrary shape
The candidate automatic segmentation being evaluated.
gt : np.ndarray, int type, same shape as `aseg`
The ground truth segmentation.
size_threshold : int or float, optional
Ignore splits or merges smaller than this number of voxels.
sp : np.ndarray, int type, same shape as `aseg`, optional
A superpixel map. If provided, compute the edit distance to the best
possible agglomeration of `sp` to `gt`, rather than to `gt` itself.
Returns
-------
(false_merges, false_splits) : float
The number of splits and merges needed to convert aseg to gt.
"""
if sp is None:
return raw_edit_distance(aseg, gt, size_threshold)
else:
import agglo
bps = agglo.best_possible_segmentation(sp, gt)
return raw_edit_distance(aseg, bps, size_threshold)
def edit_distance(aseg, gt, ws=None):
if ws is None:
return edit_distance_to_bps(aseg, gt)
import agglo
return edit_distance_to_bps(aseg, agglo.best_possible_segmentation(ws, gt))
def edit_distance(aseg, gt, ws=None):
if ws is None:
return edit_distance_to_bps(aseg, gt)
import agglo
return edit_distance_to_bps(aseg, agglo.best_possible_segmentation(ws, gt))
