menpo/image/boolean.py
def bounds_false(self, boundary=0, constrain_to_bounds=True):
        r"""
        Returns the minimum to maximum indices along all dimensions that the
        mask includes which fully surround the False mask values. In the case
        of a 2D Image for instance, the min and max define two corners of a
        rectangle bounding the False pixel values.

        Parameters
        ----------
        boundary : `int` >= 0, optional
            A number of pixels that should be added to the extent. A
            negative value can be used to shrink the bounds in.
        constrain_to_bounds: `bool`, optional
            If ``True``, the bounding extent is snapped to not go beyond
            the edge of the image. If ``False``, the bounds are left unchanged.

        Returns
        -------
        min_b : ``(D,)`` `ndarray`
            The minimum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        max_b : ``(D,)`` `ndarray`
            The maximum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        """
        return self.invert().bounds_true(
            boundary=boundary, constrain_to_bounds=constrain_to_bounds)
r"""
        Returns the minimum to maximum indices along all dimensions that the
        mask includes which fully surround the False mask values. In the case
        of a 2D Image for instance, the min and max define two corners of a
        rectangle bounding the False pixel values.

        Parameters
        ----------
        boundary : `int` >= 0, optional
            A number of pixels that should be added to the extent. A
            negative value can be used to shrink the bounds in.
        constrain_to_bounds: `bool`, optional
            If ``True``, the bounding extent is snapped to not go beyond
            the edge of the image. If ``False``, the bounds are left unchanged.

        Returns
        -------
        min_b : ``(D,)`` `ndarray`
            The minimum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        max_b : ``(D,)`` `ndarray`
            The maximum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        
r"""
Returns the minimum to maximum indices along all dimensions that the
mask includes which fully surround the False mask values. In the case
of a 2D Image for instance, the min and max define two corners of a
rectangle bounding the False pixel values.

Parameters

boundary : `int` >= 0, optional
A number of pixels that should be added to the extent. A
negative value can be used to shrink the bounds in.

Returns


r " " " Returns the minimum to maximum indices along all dimensions that the mask includes which fully surround the False mask values . In the case of a 2D Image for instance the min and max define two corners of a rectangle bounding the False pixel values . Parameters boundary : ` int ` > = 0 optional A number of pixels that should be added to the extent . A negative value can be used to shrink the bounds in . Returns
def bounds_false(self, boundary=0, constrain_to_bounds=True):
        return self.invert().bounds_true(
            boundary=boundary, constrain_to_bounds=constrain_to_bounds)
def bounds_false ( self , boundary = 0 , constrain_to_bounds = True ) : return self . invert ( ) . bounds_true ( boundary = boundary , constrain_to_bounds = constrain_to_bounds )
r"""
Returns the minimum to maximum indices along all dimensions that the
mask includes which fully surround the False mask values.
r " " " Returns the minimum to maximum indices along all dimensions that the mask includes which fully surround the False mask values .
r"""
        Returns the minimum to maximum indices along all dimensions that the
        mask includes which fully surround the False mask values. In the case
        of a 2D Image for instance, the min and max define two corners of a
        rectangle bounding the False pixel values.

        Parameters
        ----------
        boundary : `int` >= 0, optional
            A number of pixels that should be added to the extent. A
            negative value can be used to shrink the bounds in.
        constrain_to_bounds: `bool`, optional
            If ``True``, the bounding extent is snapped to not go beyond
            the edge of the image. If ``False``, the bounds are left unchanged.

        Returns
        -------
        min_b : ``(D,)`` `ndarray`
            The minimum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        max_b : ``(D,)`` `ndarray`
            The maximum extent of the ``True`` mask region with the boundary
            along each dimension. If ``constrain_to_bounds=True``,
            is clipped to legal image bounds.
        """
self
boundary
constrain_to_bounds