Class Affine

monai/transforms/spatial/array.py:2179–2383

Transform ``img`` given the affine parameters. A tutorial is available: https://github.com/Project-MONAI/tutorials/blob/0.6.0/modules/transforms_demo_2d.ipynb. This transform is capable of lazy execution. See the :ref:`Lazy Resampling topic ` for more information.

class Affine(InvertibleTransform, LazyTransform):
    """
    Transform ``img`` given the affine parameters.
    A tutorial is available: https://github.com/Project-MONAI/tutorials/blob/0.6.0/modules/transforms_demo_2d.ipynb.

    This transform is capable of lazy execution. See the :ref:`Lazy Resampling topic<lazy_resampling>`
    for more information.
    """

    backend = list(set(AffineGrid.backend) & set(Resample.backend))

    def __init__(
        self,
        rotate_params: Sequence[float] | float | None = None,
        shear_params: Sequence[float] | float | None = None,
        translate_params: Sequence[float] | float | None = None,
        scale_params: Sequence[float] | float | None = None,
        affine: NdarrayOrTensor | None = None,
        spatial_size: Sequence[int] | int | None = None,
        mode: str | int = GridSampleMode.BILINEAR,
        padding_mode: str = GridSamplePadMode.REFLECTION,
        normalized: bool = False,
        device: torch.device | None = None,
        dtype: DtypeLike = np.float32,
        align_corners: bool = False,
        image_only: bool = False,
        lazy: bool = False,
    ) -> None:
        """
        The affine transformations are applied in rotate, shear, translate, scale order.

        Args:
            rotate_params: a rotation angle in radians, a scalar for 2D image, a tuple of 3 floats for 3D.
                Defaults to no rotation.
            shear_params: shearing factors for affine matrix, take a 3D affine as example::

                [
                    [1.0, params[0], params[1], 0.0],
                    [params[2], 1.0, params[3], 0.0],
                    [params[4], params[5], 1.0, 0.0],
                    [0.0, 0.0, 0.0, 1.0],
                ]

                a tuple of 2 floats for 2D, a tuple of 6 floats for 3D. Defaults to no shearing.
            translate_params: a tuple of 2 floats for 2D, a tuple of 3 floats for 3D. Translation is in
                pixel/voxel relative to the center of the input image. Defaults to no translation.
            scale_params: scale factor for every spatial dims. a tuple of 2 floats for 2D,
                a tuple of 3 floats for 3D. Defaults to `1.0`.
            affine: If applied, ignore the params (`rotate_params`, etc.) and use the
                supplied matrix. Should be square with each side = num of image spatial
                dimensions + 1.
            spatial_size: output image spatial size.
                if `spatial_size` and `self.spatial_size` are not defined, or smaller than 1,
                the transform will use the spatial size of `img`.
                if some components of the `spatial_size` are non-positive values, the transform will use the
                corresponding components of img size. For example, `spatial_size=(32, -1)` will be adapted
                to `(32, 64)` if the second spatial dimension size of img is `64`.
            mode: {``"bilinear"``, ``"nearest"``} or spline interpolation order 0-5 (integers).