Remove unused config param

docs/developer_guides/pipelines/datamanagers.md

@@ -62,8 +62,6 @@ class VanillaDataManagerConfig(InstantiateConfig):
     """number of rays per batch to use per eval iteration"""
     eval_num_images_to_sample_from: int = -1
     """number of images to sample during eval iteration"""
-    eval_image_indices: Optional[Tuple[int, ...]] = (0,)
-    """specifies the image indices to use during eval; if None, uses all"""
     camera_optimizer: CameraOptimizerConfig = CameraOptimizerConfig()
     """specifies the camera pose optimizer used during training"""
 ```

nerfstudio/data/datamanagers/base_datamanager.py

@@ -335,8 +335,6 @@ class VanillaDataManagerConfig(DataManagerConfig):
     eval_num_times_to_repeat_images: int = -1
     """When not evaluating on all images, number of iterations before picking
     new images. If -1, never pick new images."""
-    eval_image_indices: Optional[Tuple[int, ...]] = (0,)
-    """Specifies the image indices to use during eval; if None, uses all."""
     camera_optimizer: CameraOptimizerConfig = CameraOptimizerConfig()
     """Specifies the camera pose optimizer used during training. Helpful if poses are noisy, such as for data from
     Record3D."""

nerfstudio/scripts/render.py

@@ -624,7 +624,6 @@ def main(self):
         def update_config(config: TrainerConfig) -> TrainerConfig:
             data_manager_config = config.pipeline.datamanager
             assert isinstance(data_manager_config, VanillaDataManagerConfig)
-            data_manager_config.eval_image_indices = None
             data_manager_config.eval_num_images_to_sample_from = -1
             data_manager_config.eval_num_times_to_repeat_images = -1
             data_manager_config.train_num_images_to_sample_from = -1

nerfstudio/utils/eval_utils.py

@@ -26,7 +26,6 @@
 import yaml
 
 from nerfstudio.configs.method_configs import all_methods
-from nerfstudio.data.datamanagers.base_datamanager import VanillaDataManagerConfig
 from nerfstudio.engine.trainer import TrainerConfig
 from nerfstudio.pipelines.base_pipeline import Pipeline
 from nerfstudio.utils.rich_utils import CONSOLE
@@ -100,8 +99,6 @@ def eval_setup(
     # load checkpoints from wherever they were saved
     # TODO: expose the ability to choose an arbitrary checkpoint
     config.load_dir = config.get_checkpoint_dir()
-    if isinstance(config.pipeline.datamanager, VanillaDataManagerConfig):
-        config.pipeline.datamanager.eval_image_indices = None
 
     # setup pipeline (which includes the DataManager)
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

tests/data/configs/test_config1.yml

@@ -111,8 +111,6 @@ pipeline: !!python/object:nerfstudio.pipelines.base_pipeline.VanillaPipelineConf
       - data
       - varun
       - cheezit-scaled
-    eval_image_indices: !!python/tuple
-    - 0
     eval_num_images_to_sample_from: -1
     eval_num_rays_per_batch: 4096
     eval_num_times_to_repeat_images: -1

tests/data/configs/test_config2.yml

@@ -105,8 +105,6 @@ pipeline: !!python/object:nerfstudio.pipelines.base_pipeline.VanillaPipelineConf
       - data
       - varun
       - cheezit-scaled
-    eval_image_indices: !!python/tuple
-    - 0
     eval_num_images_to_sample_from: -1
     eval_num_rays_per_batch: 4096
     eval_num_times_to_repeat_images: -1