Source code for gsplat.cuda._wrapper

-from typing import Callable, Optional, Tuple
+from typing import Callable, Optional, Tuple, Any
 import warnings
+from typing_extensions import Literal
 
 import torch
 from torch import Tensor
@@ -327,6 +328,16 @@ 
Source code for gsplat.cuda._wrapper
     return call_cuda
 
 
+def _make_lazy_cuda_obj(name: str) -> Any:
+    # pylint: disable=import-outside-toplevel
+    from ._backend import _C
+
+    obj = _C
+    for name_split in name.split("."):
+        obj = getattr(_C, name_split)
+    return obj
+
+
 

 [docs]
 def spherical_harmonics(
@@ -435,7 +446,7 @@ 
Source code for gsplat.cuda._wrapper
     Ks: Tensor,  # [C, 3, 3]
     width: int,
     height: int,
-    ortho: bool,
+    camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
 ) -> Tuple[Tensor, Tensor]:
     """Projection of Gaussians (perspective or orthographic).
 
@@ -459,7 +470,7 @@ 
Source code for gsplat.cuda._wrapper
     means = means.contiguous()
     covars = covars.contiguous()
     Ks = Ks.contiguous()
-    return _Proj.apply(means, covars, Ks, width, height, ortho)

+    return _Proj.apply(means, covars, Ks, width, height, camera_model)

 
 
 
@@ -513,7 +524,7 @@ 
Source code for gsplat.cuda._wrapper
     packed: bool = False,
     sparse_grad: bool = False,
     calc_compensations: bool = False,
-    ortho: bool = False,
+    camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
 ) -> Tuple[Tensor, Tensor, Tensor, Tensor, Tensor]:
     """Projects Gaussians to 2D.
 
@@ -615,7 +626,7 @@ 
Source code for gsplat.cuda._wrapper
             radius_clip,
             sparse_grad,
             calc_compensations,
-            ortho,
+            camera_model,
         )
     else:
         return _FullyFusedProjection.apply(
@@ -632,7 +643,7 @@ 
Source code for gsplat.cuda._wrapper
             far_plane,
             radius_clip,
             calc_compensations,
-            ortho,
+            camera_model,
         )

 
 
@@ -1005,15 +1016,24 @@ 
Source code for gsplat.cuda._wrapper
         Ks: Tensor,  # [C, 3, 3]
         width: int,
         height: int,
-        ortho: bool,
+        camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
     ) -> Tuple[Tensor, Tensor]:
+        camera_model_type = _make_lazy_cuda_obj(
+            f"CameraModelType.{camera_model.upper()}"
+        )
+
         means2d, covars2d = _make_lazy_cuda_func("proj_fwd")(
-            means, covars, Ks, width, height, ortho
+            means,
+            covars,
+            Ks,
+            width,
+            height,
+            camera_model_type,
         )
         ctx.save_for_backward(means, covars, Ks)
         ctx.width = width
         ctx.height = height
-        ctx.ortho = ortho
+        ctx.camera_model_type = camera_model_type
         return means2d, covars2d
 
     @staticmethod
@@ -1021,14 +1041,14 @@ 
Source code for gsplat.cuda._wrapper
         means, covars, Ks = ctx.saved_tensors
         width = ctx.width
         height = ctx.height
-        ortho = ctx.ortho
+        camera_model_type = ctx.camera_model_type
         v_means, v_covars = _make_lazy_cuda_func("proj_bwd")(
             means,
             covars,
             Ks,
             width,
             height,
-            ortho,
+            camera_model_type,
             v_means2d.contiguous(),
             v_covars2d.contiguous(),
         )
@@ -1092,8 +1112,12 @@ 
Source code for gsplat.cuda._wrapper
         far_plane: float,
         radius_clip: float,
         calc_compensations: bool,
-        ortho: bool,
+        camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
     ) -> Tuple[Tensor, Tensor, Tensor, Tensor, Tensor]:
+        camera_model_type = _make_lazy_cuda_obj(
+            f"CameraModelType.{camera_model.upper()}"
+        )
+
         # "covars" and {"quats", "scales"} are mutually exclusive
         radii, means2d, depths, conics, compensations = _make_lazy_cuda_func(
             "fully_fused_projection_fwd"
@@ -1111,7 +1135,7 @@ 
Source code for gsplat.cuda._wrapper
             far_plane,
             radius_clip,
             calc_compensations,
-            ortho,
+            camera_model_type,
         )
         if not calc_compensations:
             compensations = None
@@ -1121,7 +1145,7 @@ 
Source code for gsplat.cuda._wrapper
         ctx.width = width
         ctx.height = height
         ctx.eps2d = eps2d
-        ctx.ortho = ortho
+        ctx.camera_model_type = camera_model_type
 
         return radii, means2d, depths, conics, compensations
 
@@ -1141,7 +1165,7 @@ 
Source code for gsplat.cuda._wrapper
         width = ctx.width
         height = ctx.height
         eps2d = ctx.eps2d
-        ortho = ctx.ortho
+        camera_model_type = ctx.camera_model_type
         if v_compensations is not None:
             v_compensations = v_compensations.contiguous()
         v_means, v_covars, v_quats, v_scales, v_viewmats = _make_lazy_cuda_func(
@@ -1156,7 +1180,7 @@ 
Source code for gsplat.cuda._wrapper
             width,
             height,
             eps2d,
-            ortho,
+            camera_model_type,
             radii,
             conics,
             compensations,
@@ -1191,6 +1215,7 @@ 
Source code for gsplat.cuda._wrapper
             None,
             None,
             None,
+            None,
         )
 
 
@@ -1344,8 +1369,12 @@ 
Source code for gsplat.cuda._wrapper
         radius_clip: float,
         sparse_grad: bool,
         calc_compensations: bool,
-        ortho: bool,
+        camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
     ) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
+        camera_model_type = _make_lazy_cuda_obj(
+            f"CameraModelType.{camera_model.upper()}"
+        )
+
         (
             indptr,
             camera_ids,
@@ -1369,7 +1398,7 @@ 
Source code for gsplat.cuda._wrapper
             far_plane,
             radius_clip,
             calc_compensations,
-            ortho,
+            camera_model_type,
         )
         if not calc_compensations:
             compensations = None
@@ -1389,7 +1418,7 @@ 
Source code for gsplat.cuda._wrapper
         ctx.height = height
         ctx.eps2d = eps2d
         ctx.sparse_grad = sparse_grad
-        ctx.ortho = ortho
+        ctx.camera_model_type = camera_model_type
 
         return camera_ids, gaussian_ids, radii, means2d, depths, conics, compensations
 
@@ -1420,7 +1449,7 @@ 
Source code for gsplat.cuda._wrapper
         height = ctx.height
         eps2d = ctx.eps2d
         sparse_grad = ctx.sparse_grad
-        ortho = ctx.ortho
+        camera_model_type = ctx.camera_model_type
 
         if v_compensations is not None:
             v_compensations = v_compensations.contiguous()
@@ -1436,7 +1465,7 @@ 
Source code for gsplat.cuda._wrapper
             width,
             height,
             eps2d,
-            ortho,
+            camera_model_type,
             camera_ids,
             gaussian_ids,
             conics,
diff --git a/main/_modules/gsplat/rendering.html b/main/_modules/gsplat/rendering.html
index b0d501e98..f3f096b05 100644
--- a/main/_modules/gsplat/rendering.html
+++ b/main/_modules/gsplat/rendering.html
@@ -363,7 +363,7 @@ 
Source code for gsplat.rendering
     rasterize_mode: Literal["classic", "antialiased"] = "classic",
     channel_chunk: int = 32,
     distributed: bool = False,
-    ortho: bool = False,
+    camera_model: Literal["pinhole", "ortho", "fisheye"] = "pinhole",
     covars: Optional[Tensor] = None,
 ) -> Tuple[Tensor, Tensor, Dict]:
     """Rasterize a set of 3D Gaussians (N) to a batch of image planes (C).
@@ -624,7 +624,7 @@ 
Source code for gsplat.rendering
         radius_clip=radius_clip,
         sparse_grad=sparse_grad,
         calc_compensations=(rasterize_mode == "antialiased"),
-        ortho=ortho,
+        camera_model=camera_model,
     )
 
     if packed:
diff --git a/main/apis/rasterization.html b/main/apis/rasterization.html
index 51e20d319..fa1efe4d4 100644
--- a/main/apis/rasterization.html
+++ b/main/apis/rasterization.html
@@ -353,7 +353,7 @@ 
3DGSΒΆ
 

 

-rasterization(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 = 10000000000.0, radius_clip: float = 0.0, eps2d: float = 0.3, sh_degree: int | None = None, packed: bool = True, tile_size: int = 16, backgrounds: Tensor | None = None, render_mode: typing_extensions.Literal[RGB, D, ED, RGB + D, RGB + ED] = 'RGB', sparse_grad: bool = False, absgrad: bool = False, rasterize_mode: typing_extensions.Literal[classic, antialiased] = 'classic', channel_chunk: int = 32, distributed: bool = False, ortho: bool = False, covars: Tensor | None = None) → Tuple[Tensor, Tensor, Dict][source]ΒΆ

+rasterization(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 = 10000000000.0, radius_clip: float = 0.0, eps2d: float = 0.3, sh_degree: int | None = None, packed: bool = True, tile_size: int = 16, backgrounds: Tensor | None = None, render_mode: typing_extensions.Literal[RGB, D, ED, RGB + D, RGB + ED] = 'RGB', sparse_grad: bool = False, absgrad: bool = False, rasterize_mode: typing_extensions.Literal[classic, antialiased] = 'classic', channel_chunk: int = 32, distributed: bool = False, camera_model: typing_extensions.Literal[pinhole, ortho, fisheye] = 'pinhole', covars: Tensor | None = None) → Tuple[Tensor, Tensor, Dict][source]ΒΆ
 
Rasterize a set of 3D Gaussians (N) to a batch of image planes (C).

 
This function provides a handful features for 3D Gaussian rasterization, which
 we detail in the following notes. A complete profiling of the these features
diff --git a/main/apis/utils.html b/main/apis/utils.html
index 05c1bab3e..6b0533e41 100644
--- a/main/apis/utils.html
+++ b/main/apis/utils.html
@@ -371,7 +371,7 @@ 
3DGSΒΆ
 

-proj(means: Tensor, covars: Tensor, Ks: Tensor, width: int, height: int, ortho: bool) → Tuple[Tensor, Tensor][source]ΒΆ

+proj(means: Tensor, covars: Tensor, Ks: Tensor, width: int, height: int, camera_model: typing_extensions.Literal[pinhole, ortho, fisheye] = 'pinhole') → Tuple[Tensor, Tensor][source]ΒΆ
 
Projection of Gaussians (perspective or orthographic).

 

 
Parameters:

@@ -398,7 +398,7 @@ 
3DGSΒΆ
 

-fully_fused_projection(means: Tensor, covars: Tensor | None, quats: Tensor | None, scales: Tensor | None, viewmats: Tensor, Ks: Tensor, width: int, height: int, eps2d: float = 0.3, near_plane: float = 0.01, far_plane: float = 10000000000.0, radius_clip: float = 0.0, packed: bool = False, sparse_grad: bool = False, calc_compensations: bool = False, ortho: bool = False) → Tuple[Tensor, Tensor, Tensor, Tensor, Tensor][source]ΒΆ

+fully_fused_projection(means: Tensor, covars: Tensor | None, quats: Tensor | None, scales: Tensor | None, viewmats: Tensor, Ks: Tensor, width: int, height: int, eps2d: float = 0.3, near_plane: float = 0.01, far_plane: float = 10000000000.0, radius_clip: float = 0.0, packed: bool = False, sparse_grad: bool = False, calc_compensations: bool = False, camera_model: typing_extensions.Literal[pinhole, ortho, fisheye] = 'pinhole') → Tuple[Tensor, Tensor, Tensor, Tensor, Tensor][source]ΒΆ
 
Projects Gaussians to 2D.

 
This function fuse the process of computing covariances
 (quat_scale_to_covar_preci()), transforming to camera space (world_to_cam()),
diff --git a/main/searchindex.js b/main/searchindex.js
index 55c9d9140..2e88c4cc0 100644
--- a/main/searchindex.js
+++ b/main/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"2DGS": [[1, "id1"], [3, "id1"], [11, "id1"]], "3DGS": [[1, "dgs"], [3, "dgs"], [11, "dgs"]], "Basic Usage": [[10, "basic-usage"]], "Citations": [[8, "citations"]], "Color as Spherical Harmonics": [[10, "color-as-spherical-harmonics"]], "Compression": [[0, null]], "Contributing": [[8, "contributing"]], "Conventions": [[8, null]], "Data Conventions": [[4, null]], "Densification": [[2, null]], "Depth Rendering": [[10, "depth-rendering"]], "Evaluation": [[11, null]], "Examples": [[8, null]], "Feature Ablation": [[11, "feature-ablation"]], "Fit a COLMAP Capture": [[5, null]], "Fit a Single Image": [[6, null]], "Installation": [[8, "installation"]], "Links": [[8, "links"]], "Migrate from diff-gaussian-rasterization": [[9, null]], "Migrate from gsplat v0.1.11": [[10, null]], "Migration": [[8, null]], "No Regularization": [[11, "no-regularization"]], "Overview": [[8, "overview"]], "Performance on Mip-NeRF 360 Captures (Averaged Over 7 Scenes)": [[11, "id4"]], "Profiling": [[12, null]], "Python API": [[8, null]], "Rasterization": [[1, null]], "Render Feature Maps: 32 Channel": [[12, "render-feature-maps-32-channel"]], "Render RGB Images": [[12, "render-rgb-images"]], "Render a Large Scene": [[7, null], [12, "render-a-large-scene"]], "Reproduced Metrics": [[11, "reproduced-metrics"], [11, "id2"]], "Rotation Convention": [[4, "rotation-convention"]], "Runtime and GPU Memory": [[11, "runtime-and-gpu-memory"]], "Testing and verifying CUDA implementations": [[13, "testing-and-verifying-cuda-implementations"]], "Tests": [[8, null], [13, null]], "Trains Faster with Less GPU Memory": [[11, "trains-faster-with-less-gpu-memory"]], "Utils": [[3, null]], "View Matrix": [[4, "view-matrix"]], "With Normal Consistency and Distortion Regularization": [[11, "with-normal-consistency-and-distortion-regularization"]], "gsplat": [[8, null]]}, "docnames": ["apis/compression", "apis/rasterization", "apis/strategy", "apis/utils", "conventions/data_conventions", "examples/colmap", "examples/image", "examples/large_scale", "index", "migration/migration_inria", "migration/migration_legacy", "tests/eval", "tests/profile", "tests/tests"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1, "sphinx.ext.viewcode": 1, "sphinxcontrib.bibtex": 9}, "filenames": ["apis/compression.rst", "apis/rasterization.rst", "apis/strategy.rst", "apis/utils.rst", "conventions/data_conventions.rst", "examples/colmap.rst", "examples/image.rst", "examples/large_scale.rst", "index.rst", "migration/migration_inria.rst", "migration/migration_legacy.rst", "tests/eval.rst", "tests/profile.rst", "tests/tests.rst"], "indexentries": {"accumulate() (in module gsplat)": [[3, "gsplat.accumulate", false]], 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