revert method_configs.py to original values

nerfstudio/configs/method_configs.py

@@ -69,7 +69,6 @@ from nerfstudio.plugins.registry import discover_methods
 method_configs: Dict[str, TrainerConfig] = {}
 descriptions = {
     "nerfacto": "Recommended real-time model tuned for real captures. This model will be continually updated.",
-    "nerfacto-eyeful-tower": "Variant of nerfacto with settings tuned for EyefulTower dataset scenes.",
     "depth-nerfacto": "Nerfacto with depth supervision.",
     "instant-ngp": "Implementation of Instant-NGP. Recommended real-time model for unbounded scenes.",
     "instant-ngp-bounded": "Implementation of Instant-NGP. Recommended for bounded real and synthetic scenes",
@@ -210,45 +209,6 @@ method_configs["nerfacto-huge"] = TrainerConfig(
     vis="viewer",
 )
 
-method_configs["nerfacto-eyeful-tower"] = TrainerConfig(
-    method_name="nerfacto",
-    steps_per_eval_batch=500,
-    steps_per_save=2000,
-    max_num_iterations=100_000,
-    steps_per_eval_all_images=100_000,
-    mixed_precision=True,
-    pipeline=VanillaPipelineConfig(
-        datamanager=ParallelDataManagerConfig(
-            dataparser=NerfstudioDataParserConfig(),
-            train_num_rays_per_batch=12_800,
-            eval_num_rays_per_batch=4096,
-        ),
-        model=NerfactoModelConfig(
-            eval_num_rays_per_chunk=1 << 15,
-            camera_optimizer=CameraOptimizerConfig(mode="off"),
-            max_res=19_912,
-            log2_hashmap_size=22,
-            far_plane=100.0,
-        ),
-    ),
-    optimizers={
-        "proposal_networks": {
-            "optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
-            "scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
-        },
-        "fields": {
-            "optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
-            "scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
-        },
-        "camera_opt": {
-            "optimizer": AdamOptimizerConfig(lr=1e-3, eps=1e-15),
-            "scheduler": ExponentialDecaySchedulerConfig(lr_final=1e-4, max_steps=5000),
-        },
-    },
-    viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
-    vis="viewer+tensorboard",
-)
-
 method_configs["depth-nerfacto"] = TrainerConfig(
     method_name="depth-nerfacto",
     steps_per_eval_batch=500,
@@ -337,7 +297,8 @@ method_configs["instant-ngp-bounded"] = TrainerConfig(
     viewer=ViewerConfig(num_rays_per_chunk=1 << 12),
     vis="viewer",
 )
-
+#
+#
 method_configs["mipnerf"] = TrainerConfig(
     method_name="mipnerf",
     pipeline=VanillaPipelineConfig(