def watershed_distance(img, label, container, holder, ERODI=5,
DEBRISAREA=50, DISPLACEMENT=50, MASSTHRES=0.2):
'''watershed existing label, meaning make a cut at the deflection.
After the cuts, objects will be linked if they are within DISPLACEMENT and MASSTHRES.
If two candidates are found, it will pick a closer one.
Args:
ERODI (int): Erosion size element for generating watershed seeds.
Smaller ERODI will allow more cuts.
DISPLACEMENT (int): The maximum distance (in pixel)
MASSTHRES (float): The maximum difference of total intensity changes.
0.2 means it allows for 20% total intensity changes.
'''
untr_prev, untr_curr = container.unlinked
mask_untracked = container._label_untracked.astype(bool)
wshed_label = watershed(mask_untracked, ERODI)
wshed_label = skilabel(sizefilterandopen(wshed_label, DEBRISAREA, np.Inf, 0))
newcells = CellListMaker(img, wshed_label, holder, holder.frame).make_list()
distanceUntracked = _distance_diff(untr_prev, newcells)
masschangeUntracked = _totalintensity_difference(untr_prev, newcells)
withinarea = distanceUntracked < DISPLACEMENT
withinmass = abs(masschangeUntracked) < MASSTHRES
withinareaMass = withinarea * withinmass
withinareaMass = pick_closer_binarycostmat(withinareaMass, distanceUntracked)
good_curr_idx, good_prev_idx = find_one_to_one_assign(withinareaMass)
# update the link
for ci, pi in zip(good_curr_idx, good_prev_idx):
untr_prev[pi].next = newcells[ci]
# Get all linear coordinates from good newly segmented cells
good_curr_coords = [newcells[n].prop.coords for n in good_curr_idx]
lin_curr_coords = [convert_coords_to_linear(i, holder.img_shape) for i in flatlist(good_curr_coords)]
# find cells in old mask (in current) that overlaps with good new cells
old_cells_to_remove, lin_old_coords_remove = find_coords_overlap_coords(untr_curr, lin_curr_coords, holder.img_shape)
# find cells in new mask which overlaps with the cells in old mask
newcells_to_update = find_cells_overlap_linear_coords(newcells, lin_old_coords_remove, holder.img_shape)
# remove old cells
for old_cell in old_cells_to_remove:
container.curr_cells.remove(old_cell)
# add new cells
container.curr_cells.extend(newcells_to_update)
return container
def devide_and_label_objects(bw, REGWSHED):
label = skilabel(bw).astype(np.int64)
if REGWSHED > 0:
label = watershed(label, REGWSHED)
return label