Fixup remaining modules & cleanup

Author: pxl-th

.gitignore

@@ -126,4 +126,5 @@ results
 
 !examples/benchmarks/compression/results/
 
+gsplat/hip/
 *.hip

examples/simple_trainer.py

@@ -52,12 +52,11 @@ class Config:
     render_traj_path: str = "interp"
 
     # Path to the Mip-NeRF 360 dataset
-    # data_dir: str = "data/360_v2/garden"
-    data_dir: str = "/home/pxlth/Videos/gs-videos/pidhaytsi/entrance-1"
+    data_dir: str = "data/360_v2/garden"
     # Downsample factor for the dataset
-    data_factor: int = 2
+    data_factor: int = 4
     # Directory to save results
-    result_dir: str = "results/pidhaytsi-entrance-1"
+    result_dir: str = "results/garden"
     # Every N images there is a test image
     test_every: int = 8
     # Random crop size for training  (experimental)
@@ -117,7 +116,7 @@ class Config:
         default_factory=DefaultStrategy
     )
     # Use packed mode for rasterization, this leads to less memory usage but slightly slower.
-    packed: bool = True
+    packed: bool = False
     # Use sparse gradients for optimization. (experimental)
     sparse_grad: bool = False
     # Use visible adam from Taming 3DGS. (experimental)
@@ -1218,7 +1217,7 @@ def main(local_rank: int, world_rank, world_size: int, cfg: Config):
                 init_scale=0.1,
                 opacity_reg=0.01,
                 scale_reg=0.01,
-                strategy=MCMCStrategy(verbose=True, cap_max=3_000_000),
+                strategy=MCMCStrategy(verbose=True),
             ),
         ),
     }

gsplat/__init__.py

@@ -2,31 +2,31 @@
 
 from .compression import PngCompression
 from .cuda._torch_impl import accumulate
-# from .cuda._torch_impl_2dgs import accumulate_2dgs
+from .cuda._torch_impl_2dgs import accumulate_2dgs
 from .cuda._wrapper import (
     RollingShutterType,
     fully_fused_projection,
-    # fully_fused_projection_2dgs,
-    # fully_fused_projection_with_ut,
+    fully_fused_projection_2dgs,
+    fully_fused_projection_with_ut,
     isect_offset_encode,
     isect_tiles,
     proj,
     quat_scale_to_covar_preci,
     rasterize_to_indices_in_range,
-    # rasterize_to_indices_in_range_2dgs,
+    rasterize_to_indices_in_range_2dgs,
     rasterize_to_pixels,
-    # rasterize_to_pixels_2dgs,
-    # rasterize_to_pixels_eval3d,
+    rasterize_to_pixels_2dgs,
+    rasterize_to_pixels_eval3d,
     spherical_harmonics,
     world_to_cam,
 )
 from .exporter import export_splats
 from .optimizers import SelectiveAdam
 from .rendering import (
     rasterization,
-    # rasterization_2dgs,
-    # rasterization_2dgs_inria_wrapper,
-    # rasterization_inria_wrapper,
+    rasterization_2dgs,
+    rasterization_2dgs_inria_wrapper,
+    rasterization_inria_wrapper,
 )
 from .strategy import DefaultStrategy, MCMCStrategy, Strategy
 from .version import __version__
@@ -37,8 +37,8 @@
     "MCMCStrategy",
     "Strategy",
     "rasterization",
-    # "rasterization_2dgs",
-    # "rasterization_inria_wrapper",
+    "rasterization_2dgs",
+    "rasterization_inria_wrapper",
     "spherical_harmonics",
     "isect_offset_encode",
     "isect_tiles",
@@ -49,14 +49,14 @@
     "world_to_cam",
     "accumulate",
     "rasterize_to_indices_in_range",
-    # "fully_fused_projection_2dgs",
-    # "rasterize_to_pixels_2dgs",
-    # "rasterize_to_indices_in_range_2dgs",
-    # "accumulate_2dgs",
-    # "rasterization_2dgs_inria_wrapper",
+    "fully_fused_projection_2dgs",
+    "rasterize_to_pixels_2dgs",
+    "rasterize_to_indices_in_range_2dgs",
+    "accumulate_2dgs",
+    "rasterization_2dgs_inria_wrapper",
     "RollingShutterType",
-    # "fully_fused_projection_with_ut",
-    # "rasterize_to_pixels_eval3d",
+    "fully_fused_projection_with_ut",
+    "rasterize_to_pixels_eval3d",
     "export_splats",
     "__version__",
 ]