Switch to use the official nerfacc (add support for alpha rendering f…

…rom v0.2.2).

README.md

@@ -21,7 +21,6 @@ This repository contains a concise and extensible implementation of NeRF and Neu
 ### Environments
 - Install PyTorch>=1.10 [here](https://pytorch.org/get-started/locally/) based the package management tool you used and your cuda version (older PyTorch versions may work but have not been tested)
 - Install tiny-cuda-nn PyTorch extension: `pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch`
-- Install my fork of nerfacc (with support for NeuS training): `pip install git+https://github.com/bennyguo/nerfacc/`
 - `pip install -r requirements.txt`
 
 

models/nerf.py

@@ -73,10 +73,10 @@ def rgb_sigma_fn(t_starts, t_ends, ray_indices):
             )   
 
         rgb, opacity, depth = rendering(
-            rgb_sigma_fn,
             packed_info,
             t_starts,
             t_ends,
+            rgb_sigma_fn=rgb_sigma_fn,
             render_bkgd=self.background_color
         )
 

models/neus.py

@@ -6,7 +6,7 @@
 from models.base import BaseModel
 from models.utils import chunk_batch
 from systems.utils import update_module_step
-from nerfacc import ContractionType, OccupancyGrid, ray_marching_alpha, rendering_alpha
+from nerfacc import ContractionType, OccupancyGrid, ray_marching, rendering
 
 
 class VarianceNetwork(nn.Module):
@@ -121,7 +121,7 @@ def rgb_alpha_fn(t_starts, t_ends, ray_indices):
             return rgb, alpha[...,None]
 
         with torch.no_grad():
-            packed_info, t_starts, t_ends = ray_marching_alpha(
+            packed_info, t_starts, t_ends = ray_marching(
                 rays_o, rays_d,
                 scene_aabb=self.scene_aabb,
                 grid=self.occupancy_grid if self.config.grid_prune else None,
@@ -133,11 +133,11 @@ def rgb_alpha_fn(t_starts, t_ends, ray_indices):
                 alpha_thre=0.0
             )
 
-        rgb, opacity, depth = rendering_alpha(
-            rgb_alpha_fn,
+        rgb, opacity, depth = rendering(
             packed_info,
             t_starts,
             t_ends,
+            rgb_alpha_fn=rgb_alpha_fn,
             render_bkgd=self.background_color,
         )
 

requirements.txt

@@ -1,5 +1,6 @@
 pytorch-lightning==1.7.7
 omegaconf==2.2.3
+nerfacc==0.2.2
 matplotlib
 opencv-python
 imageio