nerfstudio
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nerfstudio-project
Unable to run ns-train nerfacto
Describe the bug Getting error while running ns-train
To Reproduce Steps to reproduce the behavior:
- Run
ns-train nerfacto --data .\data\nerfstudio\kitchen\
Expected behavior Training should run.
Screenshots Stacktrace:
(nerfstudio) PS C:\Users\Divya\nerfstudio> ns-train nerfacto --data .\data\nerfstudio\kitchen\
[15:20:44] Using --data alias for --data.pipeline.datamanager.data train.py:230
──────────────────────────────────────────────────────── Config ────────────────────────────────────────────────────────
TrainerConfig(
_target=<class 'nerfstudio.engine.trainer.Trainer'>,
output_dir=WindowsPath('outputs'),
method_name='nerfacto',
experiment_name=None,
project_name='nerfstudio-project',
timestamp='2024-02-27_152044',
machine=MachineConfig(seed=42, num_devices=1, num_machines=1, machine_rank=0, dist_url='auto', device_type='cuda'),
logging=LoggingConfig(
relative_log_dir=WindowsPath('.'),
steps_per_log=10,
max_buffer_size=20,
local_writer=LocalWriterConfig(
_target=<class 'nerfstudio.utils.writer.LocalWriter'>,
enable=True,
stats_to_track=(
<EventName.ITER_TRAIN_TIME: 'Train Iter (time)'>,
<EventName.TRAIN_RAYS_PER_SEC: 'Train Rays / Sec'>,
<EventName.CURR_TEST_PSNR: 'Test PSNR'>,
<EventName.VIS_RAYS_PER_SEC: 'Vis Rays / Sec'>,
<EventName.TEST_RAYS_PER_SEC: 'Test Rays / Sec'>,
<EventName.ETA: 'ETA (time)'>
),
max_log_size=10
),
profiler='basic'
),
viewer=ViewerConfig(
relative_log_filename='viewer_log_filename.txt',
websocket_port=None,
websocket_port_default=7007,
websocket_host='0.0.0.0',
num_rays_per_chunk=32768,
max_num_display_images=512,
quit_on_train_completion=False,
image_format='jpeg',
jpeg_quality=75,
make_share_url=False,
camera_frustum_scale=0.1,
default_composite_depth=True
),
pipeline=VanillaPipelineConfig(
_target=<class 'nerfstudio.pipelines.base_pipeline.VanillaPipeline'>,
datamanager=ParallelDataManagerConfig(
_target=<class 'nerfstudio.data.datamanagers.parallel_datamanager.ParallelDataManager'>,
data=WindowsPath('data/nerfstudio/kitchen'),
masks_on_gpu=False,
images_on_gpu=False,
dataparser=NerfstudioDataParserConfig(
_target=<class 'nerfstudio.data.dataparsers.nerfstudio_dataparser.Nerfstudio'>,
data=WindowsPath('.'),
scale_factor=1.0,
downscale_factor=None,
scene_scale=1.0,
orientation_method='up',
center_method='poses',
auto_scale_poses=True,
eval_mode='fraction',
train_split_fraction=0.9,
eval_interval=8,
depth_unit_scale_factor=0.001,
mask_color=None,
load_3D_points=False
),
train_num_rays_per_batch=4096,
train_num_images_to_sample_from=-1,
train_num_times_to_repeat_images=-1,
eval_num_rays_per_batch=4096,
eval_num_images_to_sample_from=-1,
eval_num_times_to_repeat_images=-1,
eval_image_indices=(0,),
collate_fn=<function nerfstudio_collate at 0x0000026EB493AAF0>,
camera_res_scale_factor=1.0,
patch_size=1,
camera_optimizer=None,
pixel_sampler=PixelSamplerConfig(
_target=<class 'nerfstudio.data.pixel_samplers.PixelSampler'>,
num_rays_per_batch=4096,
keep_full_image=False,
is_equirectangular=False,
ignore_mask=False,
fisheye_crop_radius=None,
rejection_sample_mask=True,
max_num_iterations=100
),
num_processes=1,
queue_size=2,
max_thread_workers=None
),
model=NerfactoModelConfig(
_target=<class 'nerfstudio.models.nerfacto.NerfactoModel'>,
enable_collider=True,
collider_params={'near_plane': 2.0, 'far_plane': 6.0},
loss_coefficients={'rgb_loss_coarse': 1.0, 'rgb_loss_fine': 1.0},
eval_num_rays_per_chunk=32768,
prompt=None,
near_plane=0.05,
far_plane=1000.0,
background_color='last_sample',
hidden_dim=64,
hidden_dim_color=64,
hidden_dim_transient=64,
num_levels=16,
base_res=16,
max_res=2048,
log2_hashmap_size=19,
features_per_level=2,
num_proposal_samples_per_ray=(256, 96),
num_nerf_samples_per_ray=48,
proposal_update_every=5,
proposal_warmup=5000,
num_proposal_iterations=2,
use_same_proposal_network=False,
proposal_net_args_list=[
{'hidden_dim': 16, 'log2_hashmap_size': 17, 'num_levels': 5, 'max_res': 128, 'use_linear': False},
{'hidden_dim': 16, 'log2_hashmap_size': 17, 'num_levels': 5, 'max_res': 256, 'use_linear': False}
],
proposal_initial_sampler='piecewise',
interlevel_loss_mult=1.0,
distortion_loss_mult=0.002,
orientation_loss_mult=0.0001,
pred_normal_loss_mult=0.001,
use_proposal_weight_anneal=True,
use_appearance_embedding=True,
use_average_appearance_embedding=True,
proposal_weights_anneal_slope=10.0,
proposal_weights_anneal_max_num_iters=1000,
use_single_jitter=True,
predict_normals=False,
disable_scene_contraction=False,
use_gradient_scaling=False,
implementation='tcnn',
appearance_embed_dim=32,
average_init_density=0.01,
camera_optimizer=CameraOptimizerConfig(
_target=<class 'nerfstudio.cameras.camera_optimizers.CameraOptimizer'>,
mode='SO3xR3',
trans_l2_penalty=0.01,
rot_l2_penalty=0.001,
optimizer=None,
scheduler=None
)
)
),
optimizers={
'proposal_networks': {
'optimizer': AdamOptimizerConfig(
_target=<class 'torch.optim.adam.Adam'>,
lr=0.01,
eps=1e-15,
max_norm=None,
weight_decay=0
),
'scheduler': ExponentialDecaySchedulerConfig(
_target=<class 'nerfstudio.engine.schedulers.ExponentialDecayScheduler'>,
lr_pre_warmup=1e-08,
lr_final=0.0001,
warmup_steps=0,
max_steps=200000,
ramp='cosine'
)
},
'fields': {
'optimizer': AdamOptimizerConfig(
_target=<class 'torch.optim.adam.Adam'>,
lr=0.01,
eps=1e-15,
max_norm=None,
weight_decay=0
),
'scheduler': ExponentialDecaySchedulerConfig(
_target=<class 'nerfstudio.engine.schedulers.ExponentialDecayScheduler'>,
lr_pre_warmup=1e-08,
lr_final=0.0001,
warmup_steps=0,
max_steps=200000,
ramp='cosine'
)
},
'camera_opt': {
'optimizer': AdamOptimizerConfig(
_target=<class 'torch.optim.adam.Adam'>,
lr=0.001,
eps=1e-15,
max_norm=None,
weight_decay=0
),
'scheduler': ExponentialDecaySchedulerConfig(
_target=<class 'nerfstudio.engine.schedulers.ExponentialDecayScheduler'>,
lr_pre_warmup=1e-08,
lr_final=0.0001,
warmup_steps=0,
max_steps=5000,
ramp='cosine'
)
}
},
vis='viewer',
data=WindowsPath('data/nerfstudio/kitchen'),
prompt=None,
relative_model_dir=WindowsPath('nerfstudio_models'),
load_scheduler=True,
steps_per_save=2000,
steps_per_eval_batch=500,
steps_per_eval_image=500,
steps_per_eval_all_images=25000,
max_num_iterations=30000,
mixed_precision=True,
use_grad_scaler=False,
save_only_latest_checkpoint=True,
load_dir=None,
load_step=None,
load_config=None,
load_checkpoint=None,
log_gradients=False,
gradient_accumulation_steps={}
)
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Saving config to: outputs\kitchen\nerfacto\2024-02-27_152044\config.yml experiment_config.py:136
Saving checkpoints to: outputs\kitchen\nerfacto\2024-02-27_152044\nerfstudio_models trainer.py:136
Auto image downscale factor of 1 nerfstudio_dataparser.py:484
Dataset is overriding orientation method to none nerfstudio_dataparser.py:232
[15:20:45] Dataset is overriding orientation method to none nerfstudio_dataparser.py:232
Dataset is overriding orientation method to none nerfstudio_dataparser.py:232
Loading data batch ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:02
Traceback (most recent call last):
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\Users\Divya\.conda\envs\nerfstudio\Scripts\ns-train.exe\__main__.py", line 7, in <module>
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\scripts\train.py", line 262, in entrypoint
main(
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\scripts\train.py", line 247, in main
launch(
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\scripts\train.py", line 189, in launch
main_func(local_rank=0, world_size=world_size, config=config)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\scripts\train.py", line 99, in train_loop
trainer.setup()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\engine\trainer.py", line 149, in setup
self.pipeline = self.config.pipeline.setup(
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\configs\base_config.py", line 54, in setup
return self._target(self, **kwargs)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\pipelines\base_pipeline.py", line 254, in __init__
self.datamanager: DataManager = config.datamanager.setup(
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\configs\base_config.py", line 54, in setup
return self._target(self, **kwargs)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\data\datamanagers\parallel_datamanager.py", line 178, in __init__
super().__init__()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\data\datamanagers\base_datamanager.py", line 181, in __init__
self.setup_train()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\data\datamanagers\parallel_datamanager.py", line 255, in setup_train
proc.start()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\process.py", line 121, in start
self._popen = self._Popen(self)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\context.py", line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\context.py", line 327, in _Popen
return Popen(process_obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\popen_spawn_win32.py", line 93, in __init__
reduction.dump(process_obj, to_child)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\reduction.py", line 63, in dump
ForkingPickler(file, protocol, *args, **kwds).dump(obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 420, in dump
StockPickler.dump(self, obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 487, in dump
self.save(obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 603, in save
self.save_reduce(obj=obj, *rv)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 717, in save_reduce
save(state)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 1217, in save_module_dict
StockPickler.save_dict(pickler, obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 971, in save_dict
self._batch_setitems(obj.items())
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 997, in _batch_setitems
save(v)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 1217, in save_module_dict
StockPickler.save_dict(pickler, obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 971, in save_dict
self._batch_setitems(obj.items())
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 997, in _batch_setitems
save(v)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 603, in save
self.save_reduce(obj=obj, *rv)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 692, in save_reduce
save(args)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 901, in save_tuple
save(element)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 603, in save
self.save_reduce(obj=obj, *rv)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 692, in save_reduce
save(args)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 886, in save_tuple
save(element)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 414, in save
StockPickler.save(self, obj, save_persistent_id)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 801, in save_bytes
self._write_large_bytes(BINBYTES8 + pack("<Q", n), obj)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\pickle.py", line 260, in write_large_bytes
write(payload)
OSError: [Errno 22] Invalid argument
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\spawn.py", line 116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\spawn.py", line 126, in _main
self = reduction.pickle.load(from_parent)
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 289, in load
return Unpickler(file, ignore=ignore, **kwds).load()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\dill\_dill.py", line 444, in load
obj = StockUnpickler.load(self)
_pickle.UnpicklingError: pickle data was truncated
Exception ignored in: <function ParallelDataManager.__del__ at 0x0000026EB4A1EE50>
Traceback (most recent call last):
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\nerfstudio\data\datamanagers\parallel_datamanager.py", line 339, in __del__
proc.terminate()
File "C:\Users\Divya\.conda\envs\nerfstudio\lib\site-packages\multiprocess\process.py", line 133, in terminate
self._popen.terminate()
AttributeError: 'NoneType' object has no attribute 'terminate'
Additional context Add any other context about the problem here.
