def compute_dense_rag_table(volume):
"""
Find all voxel-level adjacencies in the volume,
except for adjacencies to ID 0.
Returns:
dataframe with columns:
['label_a', 'label_b', 'forwardness', 'z', 'y', 'x', 'axis']
where ``label_a < label_b`` for all rows, and `forwardness` indicates whether
label_a is on the 'left' (upper) or on the 'right' (lower) side
of the voxel boundary.
"""
assert volume.dtype == np.uint32
rag = Rag(vigra.taggedView(volume, 'zyx'))
# Edges are stored by axis -- concatenate them all.
edges_z, edges_y, edges_x = rag.dense_edge_tables.values()
del rag
if len(edges_z) == len(edges_y) == len(edges_x) == 0:
return None # No edges detected
edges_z['axis'] = 'z'
edges_y['axis'] = 'y'
edges_x['axis'] = 'x'
all_edges = list(filter(len, [edges_z, edges_y, edges_x]))
edges_df = pd.concat(all_edges, ignore_index=True)
edges_df.rename(columns={'sp1': 'label_a', 'sp2': 'label_b'}, inplace=True)
del edges_df['edge_label']
# Filter: not interested in label 0
edges_df.query("label_a != 0 and label_b != 0", inplace=True)
return edges_df
def rag(superpixels):
return Rag(vigra.taggedView(superpixels, axistags="yxc").withAxes("yx"))