Rename train_split_percentage with train_split_fraction (#1497)

rename train_split_percentage with train_split_fraction

docs/developer_guides/pipelines/dataparsers.md

@@ -69,8 +69,8 @@ class NerfstudioDataParserConfig(DataParserConfig):
     """How much to scale the region of interest by."""
     orientation_method: Literal["pca", "up"] = "up"
     """The method to use for orientation."""
-    train_split_percentage: float = 0.9
-    """The percent of images to use for training. The remaining images are for eval."""
+    train_split_fraction: float = 0.9
+    """The fraction of images to use for training. The remaining images are for eval."""
 
 @dataclass
 class Nerfstudio(DataParser):

nerfstudio/data/dataparsers/nerfstudio_dataparser.py

@@ -60,8 +60,8 @@ class NerfstudioDataParserConfig(DataParserConfig):
     """Whether to center the poses."""
     auto_scale_poses: bool = True
     """Whether to automatically scale the poses to fit in +/- 1 bounding box."""
-    train_split_percentage: float = 0.9
-    """The percent of images to use for training. The remaining images are for eval."""
+    train_split_fraction: float = 0.9
+    """The fraction of images to use for training. The remaining images are for eval."""
     depth_unit_scale_factor: float = 1e-3
     """Scales the depth values to meters. Default value is 0.001 for a millimeter to meter conversion."""
 
@@ -184,7 +184,7 @@ class Nerfstudio(DataParser):
 
         # filter image_filenames and poses based on train/eval split percentage
         num_images = len(image_filenames)
-        num_train_images = math.ceil(num_images * self.config.train_split_percentage)
+        num_train_images = math.ceil(num_images * self.config.train_split_fraction)
         num_eval_images = num_images - num_train_images
         i_all = np.arange(num_images)
         i_train = np.linspace(

nerfstudio/data/dataparsers/nuscenes_dataparser.py

@@ -66,7 +66,7 @@ class NuScenesDataParserConfig(DataParserConfig):
     mask_dir: Optional[Path] = None
     """Path to masks of dynamic objects."""
 
-    train_split_percentage: float = 0.9
+    train_split_fraction: float = 0.9
     """The percent of images to use for training. The remaining images are for eval."""
 
     verbose: bool = False
@@ -160,7 +160,7 @@ class NuScenes(DataParser):
 
         # filter image_filenames and poses based on train/eval split percentage
         num_snapshots = len(samples)
-        num_train_snapshots = math.ceil(num_snapshots * self.config.train_split_percentage)
+        num_train_snapshots = math.ceil(num_snapshots * self.config.train_split_fraction)
         num_eval_snapshots = num_snapshots - num_train_snapshots
         i_all = np.arange(num_snapshots)
         i_train = np.linspace(

nerfstudio/data/dataparsers/phototourism_dataparser.py

@@ -50,8 +50,8 @@ class PhototourismDataParserConfig(DataParserConfig):
     """How much to scale the camera origins by."""
     alpha_color: str = "white"
     """alpha color of background"""
-    train_split_percentage: float = 0.9
-    """The percent of images to use for training. The remaining images are for eval."""
+    train_split_fraction: float = 0.9
+    """The fraction of images to use for training. The remaining images are for eval."""
     scene_scale: float = 1.0
     """How much to scale the region of interest by."""
     orientation_method: Literal["pca", "up", "none"] = "up"
@@ -119,7 +119,7 @@ class Phototourism(DataParser):
 
         # filter image_filenames and poses based on train/eval split percentage
         num_images = len(image_filenames)
-        num_train_images = math.ceil(num_images * self.config.train_split_percentage)
+        num_train_images = math.ceil(num_images * self.config.train_split_fraction)
         num_eval_images = num_images - num_train_images
         i_all = np.arange(num_images)
         i_train = np.linspace(