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, )