Add round half up mode to colmap

README.md

@@ -149,6 +149,9 @@ You can use `utils/image_downsample.py` to downsample your images, e.g. 4x downs
   --data.parser.down_sample_factor 4 \
   ...
 ```
+
+Rounding mode is specified by `--data.parser.down_sample_rounding_model`. Available values are `floor`, `round`, `round_half_up`, `ceil`. Default is `round`.
+
 * Load large dataset without OOM
 ```bash
 ... fit \

internal/dataparsers/colmap_dataparser.py

@@ -54,7 +54,7 @@ class Colmap(DataParserConfig):
 
     down_sample_factor: int = 1
 
-    down_sample_rounding_model: Literal["floor", "round", "ceil"] = "round"
+    down_sample_rounding_model: Literal["floor", "round", "round_half_up", "ceil"] = "round"
 
     def instantiate(self, path: str, output_path: str, global_rank: int) -> DataParser:
         return ColmapDataParser(path, output_path, global_rank, self)
@@ -68,6 +68,9 @@ def __init__(self, path: str, output_path: str, global_rank: int, params: Colmap
         self.global_rank = global_rank
         self.params = params
 
+    def _round_half_up(self, i: torch.Tensor):
+        return torch.floor(i + 0.5)
+
     def detect_sparse_model_dir(self) -> str:
         if os.path.isdir(os.path.join(self.path, "sparse", "0")):
             return os.path.join(self.path, "sparse", "0")
@@ -344,7 +347,10 @@ def get_outputs(self) -> DataParserOutputs:
 
         # recalculate intrinsics if down sample enabled
         if self.params.down_sample_factor != 1:
-            rounding_func = getattr(torch, self.params.down_sample_rounding_model)
+            if self.params.down_sample_rounding_model == "round_half_up":
+                rounding_func = self._round_half_up
+            else:
+                rounding_func = getattr(torch, self.params.down_sample_rounding_model)
             down_sampled_width = rounding_func(width.to(torch.float) / self.params.down_sample_factor)
             down_sampled_height = rounding_func(height.to(torch.float) / self.params.down_sample_factor)
             width_scale_factor = down_sampled_width / width

utils/eval_mipnerf360.py

@@ -19,10 +19,6 @@
 
 
 def start(command: str, scene: str, extra_args: list = None):
-    down_sample_rounding_model = "ceil"
-    if scene == "garden":
-        down_sample_rounding_model = "round"
-
     arg_list = [
         "python",
         "main.py",
@@ -31,7 +27,7 @@ def start(command: str, scene: str, extra_args: list = None):
         "--data.parser", "Colmap",
         "--data.parser.down_sample_factor", "4",
         "--data.parser.split_mode", "experiment",
-        "--data.parser.down_sample_rounding_model", down_sample_rounding_model,
+        "--data.parser.down_sample_rounding_model", "round_half_up",
         "--cache_all_images",
         "--logger", "wandb",
         "--output", os.path.join("outputs", args.project),
@@ -43,7 +39,7 @@ def start(command: str, scene: str, extra_args: list = None):
     if extra_args is not None:
         arg_list += extra_args
 
-    subprocess.call(arg_list)
+    return subprocess.call(arg_list)
 
 
 with tqdm(scenes) as t: