nerfstudio-project
AttributeError: 'NerfactoModelConfig' object has no attribute 'camera_optimizer'
I trained the model in Windows and now I want to conduct the inference in Linux. However, model initialization was failed. nerfstudio version is 1.0.2, python version is 3.10 Any ideas?
Cell In[32], line 428, in init_mainModel(project)
426 config = yaml.load(configPath.read_text(), Loader=yaml.Loader)
427 print(config)
--> 428 _, pipeline, _, _ = eval_setup(
429 configPath,
430 eval_num_rays_per_chunk=None,
431 test_mode="inference",
432 )
434 return original_coordinates, nerf_coordinates, utm_coordinates, combined_scale, scale_nerf, scale_subplot, shift, avg_pos_subplot, pipeline
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/utils/eval_utils.py:105, in eval_setup(config_path, eval_num_rays_per_chunk, test_mode, update_config_callback)
103 # setup pipeline (which includes the DataManager)
104 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
--> 105 pipeline = config.pipeline.setup(device=device, test_mode=test_mode)
106 assert isinstance(pipeline, Pipeline)
107 pipeline.eval()
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/configs/base_config.py:54, in InstantiateConfig.setup(self, **kwargs)
52 def setup(self, **kwargs) -> Any:
53 """Returns the instantiated object using the config."""
---> 54 return self._target(self, **kwargs)
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/pipelines/base_pipeline.py:270, in VanillaPipeline.__init__(self, config, device, test_mode, world_size, local_rank, grad_scaler)
267 # TODO(ethan): get rid of scene_bounds from the model
268 assert self.datamanager.train_dataset is not None, "Missing input dataset"
--> 270 self._model = config.model.setup(
271 scene_box=self.datamanager.train_dataset.scene_box,
272 num_train_data=len(self.datamanager.train_dataset),
273 metadata=self.datamanager.train_dataset.metadata,
274 device=device,
275 grad_scaler=grad_scaler,
276 seed_points=seed_pts,
277 )
278 self.model.to(device)
280 self.world_size = world_size
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/configs/base_config.py:54, in InstantiateConfig.setup(self, **kwargs)
52 def setup(self, **kwargs) -> Any:
53 """Returns the instantiated object using the config."""
---> 54 return self._target(self, **kwargs)
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/models/base_model.py:85, in Model.__init__(self, config, scene_box, num_train_data, **kwargs)
82 self.kwargs = kwargs
83 self.collider = None
---> 85 self.populate_modules() # populate the modules
86 self.callbacks = None
87 # to keep track of which device the nn.Module is on
File /panfs/jay/groups/15/jinzn/yang8460/nerfstudio/nerfstudio/models/nerfacto.py:175, in NerfactoModel.populate_modules(self)
155 # Fields
156 self.field = NerfactoField(
157 self.scene_box.aabb,
158 hidden_dim=self.config.hidden_dim,
(...)
172 implementation=self.config.implementation,
173 )
--> 175 self.camera_optimizer: CameraOptimizer = self.config.camera_optimizer.setup(
176 num_cameras=self.num_train_data, device="cpu"
177 )
178 self.density_fns = []
179 num_prop_nets = self.config.num_proposal_iterations
AttributeError: 'NerfactoModelConfig' object has no attribute 'camera_optimizer'
That's strange, maybe the result of a bad merge? It should be defined here: https://github.com/nerfstudio-project/nerfstudio/blob/12195f034f51e229bb9bef3b99925d48979b4a6f/nerfstudio/models/nerfacto.py#L131
Dear kerrj, thanks for your response! I may have some clues, the model was trained by nerfstudio 0.3.4 and in that version there is no definition of the camera_optimizer in the "nerfstudio/nerfstudio/models/nerfacto.py".
Now I am using nerfstudio v1.0.2 to load the model, and it looks like some new features didn't be initialized. I print out the "self.config" before this line, and these is indeed no property named "camera_optimizer".
https://github.com/nerfstudio-project/nerfstudio/blob/12195f034f51e229bb9bef3b99925d48979b4a6f/nerfstudio/models/nerfacto.py#L175
NerfactoModelConfig:
_target: <class 'nerfstudio.models.nerfacto.NerfactoModel'>
appearance_embed_dim: 32
background_color: last_sample
base_res: 16
collider_params: {'far_plane': 6.0, 'near_plane': 2.0}
disable_scene_contraction: False
distortion_loss_mult: 0.002
enable_collider: True
eval_num_rays_per_chunk: 32768
far_plane: 1000.0
features_per_level: 2
hidden_dim: 64
hidden_dim_color: 64
hidden_dim_transient: 64
implementation: tcnn
interlevel_loss_mult: 1.0
log2_hashmap_size: 19
loss_coefficients: {'rgb_loss_coarse': 1.0, 'rgb_loss_fine': 1.0}
max_res: 2048
near_plane: 0.05
num_levels: 16
num_nerf_samples_per_ray: 48
num_proposal_iterations: 2
num_proposal_samples_per_ray: [256
96]
orientation_loss_mult: 0.0001
pred_normal_loss_mult: 0.001
predict_normals: False
prompt: None
proposal_initial_sampler: piecewise
proposal_net_args_list: [{'hidden_dim': 16, 'log2_hashmap_size': 17, 'max_res': 128, 'num_levels': 5, 'use_linear': False}, {'hidden_dim': 16, 'log2_hashmap_size': 17, 'max_res': 256, 'num_levels': 5, 'use_linear': False}]
proposal_update_every: 5
proposal_warmup: 5000
proposal_weights_anneal_max_num_iters: 1000
proposal_weights_anneal_slope: 10.0
use_average_appearance_embedding: True
use_gradient_scaling: False
use_proposal_weight_anneal: True
use_same_proposal_network: False
use_single_jitter: True
Could this be caused by the difference in .yaml files?
Thank you guys. Same problem here. However, I met the issue only when I was rendering the nerfacto-big model. Nerfacto and nerfacto-huge were fine. I trained them with the same version of nerfstudio(1.0.1). I checked the config files, they are the same. I also tried to update the version of ns-studio to 1.0.2, and the problem still occurs.
