def fit(cls, toPts, fromPts):
params0 = cls.getInitParams(toPts, fromPts)
params = optimize(
toPts.flatten(),
lambda params: forwardPts(cls.fromParams(params), fromPts).flatten(
), params0)
return cls.fromParams(params)
def fit(cls, toPts, fromPts):
'''Solve for the best transform parameters given input/output point pairs.'''
params0 = cls.getInitParams(toPts, fromPts)
# lambda is a function that takes "params" as argument
# and returns the toPts calculated from fromPts and params.
params = optimize(
toPts.flatten(),
lambda params: forwardPts(cls.fromParams(params), fromPts).flatten(
), params0)
return cls.fromParams(params)
def reverse(self, vlist):
v = numpy.array(vlist)
# to get a rough initial value, apply the inverse of the simpler
# projective transform. this will give the exact answer if the
# quadratic terms happen to be 0.
u0 = self.proj.reverse(vlist)
# optimize to get an exact inverse.
umin = optimize(v, lambda u: numpy.array(self.forward(u)),
numpy.array(u0))
return umin.tolist()
def reverse(self, vlist):
v = numpy.array(vlist)
# to get a rough initial value, apply the inverse of the simpler
# projective transform. this will give the exact answer if the
# quadratic terms happen to be 0.
u0 = self.proj.reverse(vlist)
# optimize to get an exact inverse.
umin = optimize(v,
lambda u: numpy.array(self.forward(u)),
numpy.array(u0))
return umin.tolist()
def fit(cls, toPts, fromPts, imageId):
# extract width and height of image.
params0 = cls.getInitParams(toPts, fromPts, imageId)
height = params0[len(params0) - 1]
width = params0[len(params0) - 2]
Fy = params0[len(params0) - 3]
Fx = params0[len(params0) - 4]
numPts = len(toPts.flatten())
params0 = params0[:len(params0) - 4]
# optimize params
params = optimize(
toPts.flatten(), lambda params: forwardPts(
cls.fromParams(params, width, height, Fx, Fy), fromPts).
flatten(), params0)
return cls.fromParams(params, width, height, Fx, Fy)
def fit(cls, toPts, fromPts):
params0 = cls.getInitParams(toPts, fromPts)
params = optimize(toPts.flatten(),
lambda params: forwardPts(cls.fromParams(params), fromPts).flatten(),
params0)
return cls.fromParams(params)
