def assertEqualRot(self, image, proof, cases=1):
for n in xrange(cases):
rotIm = numpy.rot90(image, n)
result = list(
IM.checkNeighbours(rotIm)) + [IM.checkTransitions(rotIm)]
self.assertEqual(
result, proof,
"The neighbourhood fingerprint should be %s, but is %s for \n%s!"
% (proof, result, image))
def test3DirectConnectedPixelCorner(self):
"""If three pixels are directly connected at an corner to the central pixel, the latter has 3 neighboured feature pixels, 2 closely neighboured background pixels, and 1 transition from feature to background, while the corner position depends on the orientation of the corner."""
self.binIm[2,:2] = self.F
self.binIm[1,0] = self.F
for n in xrange(4):
proof = [3,2,n+1,1]
rotIm = numpy.rot90(self.binIm,n)
result = list(IM.checkNeighbours(rotIm))+[IM.checkTransitions(rotIm)]
self.assertEqual(result,proof,"The neighbourhood fingerprint should be %s, but is %s for \n%s!"%(proof,result,rotIm))
def test3DirectConnectedPixelCorner(self):
"""If three pixels are directly connected at an corner to the central pixel, the latter has 3 neighboured feature pixels, 2 closely neighboured background pixels, and 1 transition from feature to background, while the corner position depends on the orientation of the corner."""
self.binIm[2,:2] = self.F
self.binIm[1,0] = self.F
for n in xrange(4):
proof = [3,2,n+1,1]
rotIm = numpy.rot90(self.binIm,n)
result = list(IM.checkNeighbours(rotIm))+[IM.checkTransitions(rotIm)]
self.assertEqual(result,proof,"The neighbourhood fingerprint should be %s, but is %s for \n%s!"%(proof,result,rotIm))
def setUp(self):
#Compute thin quarter ring feature
self.quarterRing = ring()
#Computer broad quarter ring feature
self.broadQuarterRing = ring(width=3)
#get Worker
self.worker = IM.SkeletonizeFeature(None)
def setUp(self):
self.dim = 11
self.worker = IM.SkeletonizeFeature(None)
self.feature = TDM.stringFeature(self.dim,
directions=2,
distanceToBorder=2)
self.wideFeature = TDM.stringFeature(self.dim, width=3, directions=2)
def assertEqualRot(self,image,proof,cases=1):
for n in xrange(cases):
rotIm = numpy.rot90(image,n)
result = list(IM.checkNeighbours(rotIm)) + [IM.checkTransitions(rotIm)]
self.assertEqual(result,proof,"The neighbourhood fingerprint should be %s, but is %s for \n%s!"%(proof,result,image))
def setUp(self):
self.dim = 11
self.worker = IM.SkeletonizeFeature(None)
self.skeleton = TDM.stringFeature(self.dim, distanceToBorder=2)
