def __init__(self,
*,
threshold: float,
preprocessor: Operator[DataRoi, Array5D] = OpRetriever()):
self.preprocessor = preprocessor
self.threshold = threshold
def __init__(
self, *, ilp_scale: float, axis_2d: Optional[Axis2D], preprocessor: Operator[DataRoi, Array5D] = OpRetriever(axiskeys_hint="ctzyx")
):
super().__init__(ilp_scale=ilp_scale, preprocessor=preprocessor, axis_2d=axis_2d)
capped_scale = min(ilp_scale, 1.0)
self._op = StructureTensorEigenvalues(
innerScale=capped_scale,
outerScale=0.5 * capped_scale,
axis_2d=axis_2d,
preprocessor=self.presmoother,
)
def __init__(
self, ilp_scale: float, axis_2d: Optional[Axis2D], preprocessor: Operator[DataRoi, Array5D] = OpRetriever(axiskeys_hint="ctzyx")
):
super().__init__(ilp_scale=ilp_scale, axis_2d=axis_2d, preprocessor=preprocessor)
self._op = GaussianGradientMagnitude(
preprocessor=self.presmoother,
sigma=min(ilp_scale, 1.0),
axis_2d=axis_2d,
)
def __init__(
self, ilp_scale: float, axis_2d: Optional[Axis2D], preprocessor: Operator[DataRoi, Array5D] = OpRetriever(axiskeys_hint="ctzyx")
):
super().__init__(ilp_scale=ilp_scale, axis_2d=axis_2d, preprocessor=preprocessor)
capped_scale = min(ilp_scale, 1.0)
self._op = DifferenceOfGaussians(
preprocessor=self.presmoother,
sigma0=capped_scale,
sigma1=capped_scale * 0.66,
axis_2d=axis_2d,
)
