ruff formatting

nerfstudio/data/dataparsers/nerfstudio_dataparser.py

@@ -335,30 +335,34 @@ def _generate_dataparser_outputs(self, split="train"):
             elif colmap_path.exists():
                 from rich.prompt import Confirm
 
-                # check if user wants to make a point cloud from colmap points 
-                self.create_pc = Confirm.ask("load_3D_points is true, but the dataset was processed with an outdated ns-process-data that didn't convert colmap points to .ply! Update the colmap dataset automatically?")
-
+                # check if user wants to make a point cloud from colmap points
+                self.create_pc = Confirm.ask(
+                    "load_3D_points is true, but the dataset was processed with an outdated ns-process-data that didn't convert colmap points to .ply! Update the colmap dataset automatically?"
+                )
+
                 if self.create_pc:
                     import json
 
                     from nerfstudio.process_data.colmap_utils import create_ply_from_colmap
 
                     with open(self.config.data / "transforms.json") as f:
                         transforms = json.load(f)
-                    
+
                     print(self.config.data)
                     create_ply_from_colmap(recon_dir=colmap_path, output_dir=self.config.data)
-                    ply_file_path = data_dir / 'sparse_pc.ply'
+                    ply_file_path = data_dir / "sparse_pc.ply"
                     transforms["ply_file_path"] = "sparse_pc.ply"
 
                     with open(self.config.data / "transforms.json", "w", encoding="utf-8") as f:
                         json.dump(transforms, f, indent=4)
                 else:
                     ply_file_path = None
             else:
-                CONSOLE.print("[bold yellow]Warning: load_3D_points set to true but no point cloud found. gaussian-splatting models will use random point cloud initialization.")
+                CONSOLE.print(
+                    "[bold yellow]Warning: load_3D_points set to true but no point cloud found. gaussian-splatting models will use random point cloud initialization."
+                )
                 ply_file_path = None
-                
+
             if ply_file_path:
                 sparse_points = self._load_3D_points(ply_file_path, transform_matrix, scale_factor)
                 if sparse_points is not None:
@@ -393,7 +397,6 @@ def _load_3D_points(self, ply_file_path: Path, transform_matrix: torch.Tensor, s
         """
         import open3d as o3d  # Importing open3d is slow, so we only do it if we need it.
 
-
         pcd = o3d.io.read_point_cloud(str(ply_file_path))
 
         # if no points found don't read in an initial point cloud

nerfstudio/process_data/colmap_utils.py

@@ -462,7 +462,7 @@ def colmap_to_json(
 
     # create ply from colmap
     create_ply_from_colmap(recon_dir, output_dir)
-    out["ply_file_path"] = 'sparse_pc.ply'
+    out["ply_file_path"] = "sparse_pc.ply"
 
     with open(output_dir / "transforms.json", "w", encoding="utf-8") as f:
         json.dump(out, f, indent=4)
@@ -657,14 +657,14 @@ def create_ply_from_colmap(recon_dir, output_dir):
         colmap_points = read_points3D_text(recon_dir / "points3D.txt")
     else:
         raise ValueError(f"Could not find points3D.txt or points3D.bin in {recon_dir}")
-    
+
     # Load point Positions
     points3D = torch.from_numpy(np.array([p.xyz for p in colmap_points.values()], dtype=np.float32))
     # Load point colours
     points3D_rgb = torch.from_numpy(np.array([p.rgb for p in colmap_points.values()], dtype=np.uint8))
 
     # write ply
-    with open(output_dir / 'sparse_pc.ply', 'w') as f:
+    with open(output_dir / "sparse_pc.ply", "w") as f:
         # Header
         f.write("ply\n")
         f.write("format ascii 1.0\n")
@@ -680,4 +680,4 @@ def create_ply_from_colmap(recon_dir, output_dir):
         for coord, color in zip(points3D, points3D_rgb):
             x, y, z = coord.to(torch.float)
             r, g, b = (color * 255).to(torch.uint8)
-            f.write(f"{x:8f} {y:8f} {z:8f} {r} {g} {b}\n")
+            f.write(f"{x:8f} {y:8f} {z:8f} {r} {g} {b}\n")