Function rasterization_2dgs

gsplat/rendering.py:1002–1321

Rasterize a set of 2D Gaussians (N) to a batch of image planes (C). This function supports a handful of features, similar to the :func:`rasterization` function. .. warning:: This function is currently not differentiable w.r.t. the camera intrinsics `Ks`. Args: means: T

(
    means: Tensor,
    quats: Tensor,
    scales: Tensor,
    opacities: Tensor,
    colors: Tensor,
    viewmats: Tensor,
    Ks: Tensor,
    width: int,
    height: int,
    near_plane: float = 0.01,
    far_plane: float = 1e10,
    radius_clip: float = 0.0,
    eps2d: float = 0.3,
    sh_degree: Optional[int] = None,
    packed: bool = False,
    tile_size: int = 16,
    backgrounds: Optional[Tensor] = None,
    render_mode: Literal["RGB", "D", "ED", "RGB+D", "RGB+ED"] = "RGB",
    sparse_grad: bool = False,
    absgrad: bool = False,
    distloss: bool = False,
    depth_mode: Literal["expected", "median"] = "expected",
)

###### 2DGS ######
def rasterization_2dgs(
    means: Tensor,
    quats: Tensor,
    scales: Tensor,
    opacities: Tensor,
    colors: Tensor,
    viewmats: Tensor,
    Ks: Tensor,
    width: int,
    height: int,
    near_plane: float = 0.01,
    far_plane: float = 1e10,
    radius_clip: float = 0.0,
    eps2d: float = 0.3,
    sh_degree: Optional[int] = None,
    packed: bool = False,
    tile_size: int = 16,
    backgrounds: Optional[Tensor] = None,
    render_mode: Literal["RGB", "D", "ED", "RGB+D", "RGB+ED"] = "RGB",
    sparse_grad: bool = False,
    absgrad: bool = False,
    distloss: bool = False,
    depth_mode: Literal["expected", "median"] = "expected",
) -> Tuple[Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Dict]:
    """Rasterize a set of 2D Gaussians (N) to a batch of image planes (C).

    This function supports a handful of features, similar to the :func:`rasterization` function.

    .. warning::
        This function is currently not differentiable w.r.t. the camera intrinsics `Ks`.

    Args:
        means: The 3D centers of the Gaussians. [N, 3]
        quats: The quaternions of the Gaussians (wxyz convension). It's not required to be normalized. [N, 4]
        scales: The scales of the Gaussians. [N, 3]
        opacities: The opacities of the Gaussians. [N]
        colors: The colors of the Gaussians. [(C,) N, D] or [(C,) N, K, 3] for SH coefficients.
        viewmats: The world-to-cam transformation of the cameras. [C, 4, 4]
        Ks: The camera intrinsics. [C, 3, 3]
        width: The width of the image.
        height: The height of the image.
        near_plane: The near plane for clipping. Default is 0.01.
        far_plane: The far plane for clipping. Default is 1e10.
        radius_clip: Gaussians with 2D radius smaller or equal than this value will be
            skipped. This is extremely helpful for speeding up large scale scenes.
            Default is 0.0.
        eps2d: An epsilon added to the egienvalues of projected 2D covariance matrices.
            This will prevents the projected GS to be too small. For example eps2d=0.3
            leads to minimal 3 pixel unit. Default is 0.3.
        sh_degree: The SH degree to use, which can be smaller than the total
            number of bands. If set, the `colors` should be [(C,) N, K, 3] SH coefficients,
            else the `colors` should [(C,) N, D] post-activation color values. Default is None.
        packed: Whether to use packed mode which is more memory efficient but might or
            might not be as fast. Default is True.
        tile_size: The size of the tiles for rasterization. Default is 16.
            (Note: other values are not tested)
        backgrounds: The background colors. [C, D]. Default is None.
        render_mode: The rendering mode. Supported modes are "RGB", "D", "ED", "RGB+D",