def marchingSquares(image, level = 0, variant = True, border = True,
initialize = True, markOuter = 1):
"""Return a new GeoMap with sub-pixel level contours extracted by
the marching squares method. (Pixels with values < level are
separated from pixels >= level.)
If the image does not have an attribute 'siv', standard linear
interpolation is used. If image.siv exists, it should be a
SplineImageView that is used for the Newton-Raphson method to
perform another subsequent sub-pixel correction.
The optional parameter `variant` determines the handling of the
ambiguous diagonal configuration:
`variant` = True (default)
always let the two sampling points above `level` be connected
`variant` = False
always let the two opposite sampling points < `level` be connected
`variant` = SplineImageView(...)
for each ambiguous configuration, check the midpoint of the
square; then handle as if variant = (midpoint >= level)
If `initialize` is a true value (default), the map will be
initialized.
If markOuter is != 0, the faces above(outer == 1) / below(outer == -1)
the threshold are marked with the OUTER_FACE flag (this only works
if the map is initialized)."""
connections1 = ((1, 0), (0, 2), (1, 2), (3, 1), (3, 0), (0, 2), (3, 1), (3, 2), (2, 3), (1, 0), (2, 3), (0, 3), (1, 3), (2, 1), (2, 0), (0, 1))
connections2 = ((1, 0), (0, 2), (1, 2), (3, 1), (3, 0), (0, 1), (3, 2), (3, 2), (2, 3), (1, 3), (2, 0), (0, 3), (1, 3), (2, 1), (2, 0), (0, 1))
configurations = (0, 0, 1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 13, 14, 15, 16, 16)
result = geomap.GeoMap(image.shape)
def addNodeDirectX(x, y, ofs):
pos = Vector2(x+ofs, y)
# out of three successive pixels, the middle one may be the
# threshold, then we would get duplicate points already in the
# horizontal pass:
node = result.nearestNode(pos, 1e-8)
return node or result.addNode(pos)
def addNodeDirectY(x, y, ofs):
pos = Vector2(x, y+ofs)
node = result.nearestNode(pos, 1e-8) # already exists? (e.g. hNodes?)
return node or result.addNode(pos)
def addNodeNewtonRefinementX(x, y, ofs):
for i in range(100):
o = -(image.siv(x+ofs, y)-level) / image.siv.dx(x+ofs, y)
if abs(o) > 0.5:
o = vigra.sign(o)*0.05
ofs += o
if ofs <= 0 or ofs >= 1:
ofs -= o
break
if abs(o) < 1e-4:
break
return addNodeDirectX(x, y, ofs)
def addNodeNewtonRefinementY(x, y, ofs):
for i in range(100):
o = -(image.siv(x, y+ofs)-level) / image.siv.dy(x, y+ofs)
if abs(o) > 0.5:
o = vigra.sign(o)*0.05
ofs += o
if ofs <= 0 or ofs >= 1:
ofs -= o
break
if abs(o) < 1e-4:
break
return addNodeDirectY(y, y, ofs)
if hasattr(image, "siv"):
addNodeX = addNodeNewtonRefinementX
addNodeY = addNodeNewtonRefinementY
else:
addNodeX = addNodeDirectX
addNodeY = addNodeDirectY
hNodes = vigra.Image(image.shape, numpy.uint32)
v1 = image[:-1]
v2 = image[1:]
ofs = (level - v1)/(v2 - v1)
for x, y in numpy.transpose(numpy.nonzero((v1 < level) != (v2 < level))):
hNodes[x, y] = addNodeX(x, y, ofs).label()
vNodes = vigra.Image(image.shape, numpy.uint32)
v1 = image[:,:-1]
v2 = image[:,1:]
ofs = (level - v1)/(v2 - v1)
for x, y in numpy.transpose(numpy.nonzero((v1 < level) != (v2 < level))):
vNodes[x, y] = addNodeY(x, y, ofs).label()
nodes = (hNodes, vNodes, vNodes, hNodes)
offsets = numpy.array(((0, 0), (0, 0), (1, 0), (0, 1)))
defaultConnections = connections1
if variant == False:
defaultConnections = connections2
if isinstance(variant, bool):
variant = None
configurations = ((image[:-1,:-1] < level) +
(image[ 1:,:-1] < level)*2 +
(image[:-1, 1:] < level)*4 +
(image[ 1:, 1:] < level)*8)
for x, y in numpy.transpose(numpy.nonzero(configurations)):
config = configurations[x,y]
connections = connections1
if variant is not None and config in (6, 9):
if variant(x + 0.5, y + 0.5) < level:
connections = connections2
for s, e in connections[
configurations[config]:configurations[config+1]]:
startNode = result.node(int(nodes[s][tuple(offsets[s] + (x, y))]))
endNode = result.node(int(nodes[e][tuple(offsets[e] + (x, y))]))
if startNode != endNode:
result.addEdge(startNode, endNode,
[startNode.position(), endNode.position()])
maputils.mergeDegree2Nodes(result) # node suppression
result = maputils.copyMapContents(result)[0] # compress edge labels
if border:
maputils.connectBorderNodes(result, 0.5)
result.sortEdgesEventually(0.4, 0.01)
if not initialize:
return result
result.initializeMap()
if markOuter:
markOuter = markOuter > 0
it = result.faceIter()
if border:
it.next().setFlag(flag_constants.OUTER_FACE)
for face in it:
face.setFlag(flag_constants.OUTER_FACE,
(face.contours().next().label() < 0) == markOuter)
return result
maputils.removeCruft(spmap, 7)
assert checkSaddles(spmap, img.spws.saddles(), flowlines)
checkPassValues(spmap, img.gm.siv)
# --------------------------------------------------------------------
import pixelmap
lab, count = labelImage4(spmap.labelImage())
cm = pixelmap.crackEdgeMap(lab)
assert cm.faceCount == count + 1
# --------------------------------------------------------------------
map = GeoMap(maxima1, [], Size2D(256, 256))
maputils.addFlowLinesToMap(flowlines1, map)
maputils.connectBorderNodes(map, 0.1)
map.sortEdgesEventually(stepDist=0.2, minDist=0.05)
map.initializeMap()
assert map.checkConsistency(), "map inconsistent"
assert maputils.checkLabelConsistency(map), "map.labelImage() inconsistent"
# showMapStats(map)
# bg = readImage("../../../Testimages/blox.gif")
# d = MapDisplay(bg, map)
labels = [
map.faceAt(p).label()
for p in [Vector2(91, 86.4),
Vector2(91, 85.8),
Vector2(91.4, 85.8)]
]
maputils.removeCruft(spmap, 7)
assert checkSaddles(spmap, img.spws.saddles(), flowlines)
checkPassValues(spmap, img.gm.siv)
# --------------------------------------------------------------------
import pixelmap
lab, count = labelImage4(spmap.labelImage())
cm = pixelmap.crackEdgeMap(lab)
assert cm.faceCount == count + 1
# --------------------------------------------------------------------
map = GeoMap(maxima1, [], Size2D(256, 256))
maputils.addFlowLinesToMap(flowlines1, map)
maputils.connectBorderNodes(map, 0.1)
map.sortEdgesEventually(stepDist = 0.2, minDist = 0.05)
map.initializeMap()
assert map.checkConsistency(), "map inconsistent"
assert maputils.checkLabelConsistency(map), "map.labelImage() inconsistent"
# showMapStats(map)
# bg = readImage("../../../Testimages/blox.gif")
# d = MapDisplay(bg, map)
labels = [map.faceAt(p).label() for p in
[Vector2(91, 86.4), Vector2(91, 85.8), Vector2(91.4, 85.8)]]
assert len(dict.fromkeys(labels).keys()) == 3, \
"those nearby positions point to three pairwise different faces"
# --------------------------------------------------------------------
def marchingSquares(image,
level=0,
variant=True,
border=True,
initialize=True,
markOuter=1):
"""Return a new GeoMap with sub-pixel level contours extracted by
the marching squares method. (Pixels with values < level are
separated from pixels >= level.)
If the image does not have an attribute 'siv', standard linear
interpolation is used. If image.siv exists, it should be a
SplineImageView that is used for the Newton-Raphson method to
perform another subsequent sub-pixel correction.
The optional parameter `variant` determines the handling of the
ambiguous diagonal configuration:
`variant` = True (default)
always let the two sampling points above `level` be connected
`variant` = False
always let the two opposite sampling points < `level` be connected
`variant` = SplineImageView(...)
for each ambiguous configuration, check the midpoint of the
square; then handle as if variant = (midpoint >= level)
If `initialize` is a true value (default), the map will be
initialized.
If markOuter is != 0, the faces above(outer == 1) / below(outer == -1)
the threshold are marked with the OUTER_FACE flag (this only works
if the map is initialized)."""
connections1 = ((1, 0), (0, 2), (1, 2), (3, 1), (3, 0), (0, 2), (3, 1),
(3, 2), (2, 3), (1, 0), (2, 3), (0, 3), (1, 3), (2, 1),
(2, 0), (0, 1))
connections2 = ((1, 0), (0, 2), (1, 2), (3, 1), (3, 0), (0, 1), (3, 2),
(3, 2), (2, 3), (1, 3), (2, 0), (0, 3), (1, 3), (2, 1),
(2, 0), (0, 1))
configurations = (0, 0, 1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 13, 14, 15, 16, 16)
result = geomap.GeoMap(image.shape)
def addNodeDirectX(x, y, ofs):
pos = Vector2(x + ofs, y)
# out of three successive pixels, the middle one may be the
# threshold, then we would get duplicate points already in the
# horizontal pass:
node = result.nearestNode(pos, 1e-8)
return node or result.addNode(pos)
def addNodeDirectY(x, y, ofs):
pos = Vector2(x, y + ofs)
node = result.nearestNode(pos, 1e-8) # already exists? (e.g. hNodes?)
return node or result.addNode(pos)
def addNodeNewtonRefinementX(x, y, ofs):
for i in range(100):
o = -(image.siv(x + ofs, y) - level) / image.siv.dx(x + ofs, y)
if abs(o) > 0.5:
o = vigra.sign(o) * 0.05
ofs += o
if ofs <= 0 or ofs >= 1:
ofs -= o
break
if abs(o) < 1e-4:
break
return addNodeDirectX(x, y, ofs)
def addNodeNewtonRefinementY(x, y, ofs):
for i in range(100):
o = -(image.siv(x, y + ofs) - level) / image.siv.dy(x, y + ofs)
if abs(o) > 0.5:
o = vigra.sign(o) * 0.05
ofs += o
if ofs <= 0 or ofs >= 1:
ofs -= o
break
if abs(o) < 1e-4:
break
return addNodeDirectY(y, y, ofs)
if hasattr(image, "siv"):
addNodeX = addNodeNewtonRefinementX
addNodeY = addNodeNewtonRefinementY
else:
addNodeX = addNodeDirectX
addNodeY = addNodeDirectY
hNodes = vigra.Image(image.shape, numpy.uint32)
v1 = image[:-1]
v2 = image[1:]
ofs = (level - v1) / (v2 - v1)
for x, y in numpy.transpose(numpy.nonzero((v1 < level) != (v2 < level))):
hNodes[x, y] = addNodeX(x, y, ofs).label()
vNodes = vigra.Image(image.shape, numpy.uint32)
v1 = image[:, :-1]
v2 = image[:, 1:]
ofs = (level - v1) / (v2 - v1)
for x, y in numpy.transpose(numpy.nonzero((v1 < level) != (v2 < level))):
vNodes[x, y] = addNodeY(x, y, ofs).label()
nodes = (hNodes, vNodes, vNodes, hNodes)
offsets = numpy.array(((0, 0), (0, 0), (1, 0), (0, 1)))
defaultConnections = connections1
if variant == False:
defaultConnections = connections2
if isinstance(variant, bool):
variant = None
configurations = ((image[:-1, :-1] < level) +
(image[1:, :-1] < level) * 2 +
(image[:-1, 1:] < level) * 4 +
(image[1:, 1:] < level) * 8)
for x, y in numpy.transpose(numpy.nonzero(configurations)):
config = configurations[x, y]
connections = connections1
if variant is not None and config in (6, 9):
if variant(x + 0.5, y + 0.5) < level:
connections = connections2
for s, e in connections[configurations[config]:configurations[config +
1]]:
startNode = result.node(int(nodes[s][tuple(offsets[s] + (x, y))]))
endNode = result.node(int(nodes[e][tuple(offsets[e] + (x, y))]))
if startNode != endNode:
result.addEdge(startNode, endNode,
[startNode.position(),
endNode.position()])
maputils.mergeDegree2Nodes(result) # node suppression
result = maputils.copyMapContents(result)[0] # compress edge labels
if border:
maputils.connectBorderNodes(result, 0.5)
result.sortEdgesEventually(0.4, 0.01)
if not initialize:
return result
result.initializeMap()
if markOuter:
markOuter = markOuter > 0
it = result.faceIter()
if border:
it.next().setFlag(flag_constants.OUTER_FACE)
for face in it:
face.setFlag(flag_constants.OUTER_FACE,
(face.contours().next().label() < 0) == markOuter)
return result
