def test_edge_decisions_from_groundtruth(self):
# 1 2
# 3 4
vol1 = np.zeros((20,20), dtype=np.uint32)
vol1[ 0:10, 0:10] = 1
vol1[ 0:10, 10:20] = 2
vol1[10:20, 0:10] = 3
vol1[10:20, 10:20] = 4
vol1 = vigra.taggedView(vol1, 'yx')
rag = Rag(vol1)
# 2 3
# 4 5
vol2 = vol1.copy() + 1
decisions = rag.edge_decisions_from_groundtruth(vol2)
assert decisions.all()
# 7 7
# 4 5
vol2[( vol2 == 2 ).nonzero()] = 7
vol2[( vol2 == 3 ).nonzero()] = 7
decision_dict = rag.edge_decisions_from_groundtruth(vol2, asdict=True)
assert decision_dict[(1,2)] == False
assert decision_dict[(1,3)] == True
assert decision_dict[(2,4)] == True
assert decision_dict[(3,4)] == True
def test_naive_segmentation_from_edge_decisions(self):
superpixels = generate_random_voronoi((100,200), 200)
rag = Rag( superpixels )
# The 'groundtruth' is just divided into quadrants
groundtruth = np.zeros_like(superpixels)
groundtruth[0:50, 0:100] = 1
groundtruth[50:100, 0:100] = 2
groundtruth[0:50, 100:200] = 3
groundtruth[50:100, 100:200] = 4
decisions = rag.edge_decisions_from_groundtruth(groundtruth)
segmentation = rag.naive_segmentation_from_edge_decisions(decisions)
# We don't know where the exact boundary is, but pixels
# near the corners should definitely be homogenous
assert (segmentation[:20, :20] == segmentation[0, 0]).all()
assert (segmentation[:20, -20:] == segmentation[0, -1]).all()
assert (segmentation[-20:, :20] == segmentation[-1, 0]).all()
assert (segmentation[-20:, -20:] == segmentation[-1,-1]).all()