def oversegment_aff(aff_3d):
# Thresholds from Zletaski 2009, p. 19
"""
T_h = 0.98
T_l = 0.2
T_e = 0.1
T_s = 25
"""
# Thresholds from Aleks's code.
T_h = 0.99
T_l = 0.3
T_s = 25
if aff_3d.dtype == formats.WEIGHT_DTYPE_UINT:
T_h = int(T_h * formats.WEIGHT_MAX_UINT)
T_l = int(T_l * formats.WEIGHT_MAX_UINT)
T_e = int(T_e * formats.WEIGHT_MAX_UINT)
# Set each vertex's weight to the max of its adjacent edges
affv_3d = formats.aff2affv(aff_3d)
labels_3d = np.zeros(aff_3d.shape[:-1], dtype=formats.LABELS_DTYPE)
n_labels = 0
sizes = {}
# Watershed with edges >= T_h merged, and edges < T_l not considered
n_labels = connected_components(aff_3d, affv_3d, T_h, labels_3d, n_labels, sizes)
# We are allowed to apply watershed with some pixels already labeled
# and without a quick-union structure because, due to the
# connected_components algo, those labels always contain mins.
n_labels = watershed(aff_3d, affv_3d, T_l, labels_3d, n_labels, sizes)
# Create the region graph, and list their edges in decreasing order
# Ignore unlabeled vertices, since they are "single-vertex segments" and
# I think they'll be unlikely to reach size > T_s even after the next step.
# region_graph = get_region_graph(aff_3d, labels_3d, n_labels)
# For all edges with affinity >= T_e, merge if any segment has size < T_s.
# n_labels = merge_segments(aff_3d, region_graph, labels_3d, n_labels, sizes, T_s)
return labels_3d, n_labels
def oversegment_aff(aff_3d):
# Set each vertex's weight to the max of its adjacent edges
affv_3d = formats.aff2affv(aff_3d)
labels_3d = np.zeros(aff_3d.shape[:-1], dtype=formats.LABELS_DTYPE)
n_labels = 0
aff_dtype = aff_3d.dtype
for t_cc, t_ws in ((.9,.8),):# (.8,.7), (.7,.6), (.6,.2)):
if aff_dtype == formats.WEIGHT_DTYPE_UINT:
t_cc = int(t_cc * formats.WEIGHT_MAX_UINT)
t_ws = int(t_ws * formats.WEIGHT_MAX_UINT)
n_labels = connected_components(aff_3d, affv_3d, t_cc, labels_3d, n_labels)
# We are allowed to apply watershed with some pixels already labeled
# and without a quick-union structure because, due to the
# connected_components algo, those labels always contain mins.
n_labels = watershed(aff_3d, affv_3d, t_ws, labels_3d, n_labels)
return labels_3d, n_labels
