def updateD(self, filled=None, fillFront=None, inpainted=None):
if (filled is not None) and (fillFront is not None) and (inpainted is not None):
nr, nc = computeNormal(psiHatP=self,
fillFront=fillFront,
filledImage=filled)
self._normal = (nr, nc)
gr, gc = computeGradient(psiHatP=self,
inpaintedImage=inpainted,
filledImage=filled)
self._grad = (gr, gc)
if (nr is not None) and (nc is not None):
self._D = np.abs(nr*gc-nc*gr)/self._alpha
else:
self._D = 1
def updateD(self, filled=None, fillFront=None, inpainted=None):
if (filled is not None) and (fillFront is not None) and (inpainted is not None):
nr, nc = computeNormal(psiHatP=self,
fillFront=fillFront,
filledImage=filled)
self._normal = (nr, nc)
gr, gc = computeGradient(psiHatP=self,
inpaintedImage=inpainted,
filledImage=filled)
self._grad = (gr, gc)
if (nr is not None) and (nc is not None):
self._D = np.abs(nr*gc-nc*gr)/self._alpha
else:
self._D = 1