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param tweaks, change density bias scheduling

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This commit is contained in:
Justin 2023-02-21 20:20:48 +00:00
parent 7ab04622d0
commit 2efd4c88b6
2 changed files with 14 additions and 13 deletions
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8
nerfstudio/configs/method_configs.py
View File

@ -353,7 +353,7 @@ method_configs["dreamfusion"] = TrainerConfig(
model=DreamFusionModelConfig(
eval_num_rays_per_chunk=1 << 15,
distortion_loss_mult=0.02,
interlevel_loss_mult=100,
interlevel_loss_mult=100.0,
orientation_loss_mult=0.1,
max_res=256,
sphere_collider=True,
@ -371,12 +371,12 @@ method_configs["dreamfusion"] = TrainerConfig(
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-8, eps=1e-15),
"scheduler": WarmupSchedulerConfig(lr_init=1e-8,lr_max=1e-3,lr_final=1e-6,warmup_steps=2000,max_steps=10000),
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None#WarmupSchedulerConfig(lr_init=1e-8,lr_max=1e-3,lr_final=1e-6,warmup_steps=2000,max_steps=20000),
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-8, eps=1e-15),
"scheduler": WarmupSchedulerConfig(lr_init=1e-8,lr_max=1e-3,lr_final=1e-6,warmup_steps=2000,max_steps=10000),
"scheduler": WarmupSchedulerConfig(lr_init=1e-8,lr_max=1e-3,lr_final=1e-6,warmup_steps=2000,max_steps=20000),
},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 15),

19
nerfstudio/models/dreamfusion.py
View File

@ -77,8 +77,10 @@ class DreamFusionModelConfig(ModelConfig):
"""Randomizes light source per output."""
initialize_density: bool = True
"""Initialize density in center of scene."""
init_density_strength: float = 0.1
"""Initial strength of center density"""
taper_range: Tuple[int,int] = (0,1000)
'''Range of step values for the density tapering'''
taper_strength:Tuple[float,float] = (1.0,0.0)
"""Strength schedule of center density"""
sphere_collider: bool = True
"""Use spherical collider instead of box"""
random_background: bool = True
@ -114,7 +116,7 @@ class DreamFusionModelConfig(ModelConfig):
"""Slope of the annealing function for the proposal weights."""
proposal_weights_anneal_max_num_iters: int = 500
"""Max num iterations for the annealing function."""
use_single_jitter: bool = False
use_single_jitter: bool = True
"""Whether use single jitter or not for the proposal networks."""
interlevel_loss_mult: float = 1.0
"""Proposal loss multiplier."""
@ -234,7 +236,7 @@ class DreamFusionModel(Model):
single_jitter=self.config.use_single_jitter,
update_sched=update_schedule,
initial_sampler=UniformSampler(single_jitter=self.config.use_single_jitter),
pdf_histogram_padding=0.001,
pdf_histogram_padding=0.005,
)
# renderers
@ -264,7 +266,7 @@ class DreamFusionModel(Model):
def taper_density(
self, training_callback_attributes: TrainingCallbackAttributes, step: int # pylint: disable=unused-argument
):
self.density_strength -= 0.25
self.density_strength = np.interp(step,self.config.taper_range,self.config.taper_strength)
def start_training_normals(
self, training_callback_attributes: TrainingCallbackAttributes, step: int # pylint: disable=unused-argument
@ -298,8 +300,8 @@ class DreamFusionModel(Model):
callbacks = [
TrainingCallback(
where_to_run=[TrainingCallbackLocation.AFTER_TRAIN_ITERATION],
iters=(150, 300, 450, 600),
func=taper_density,
update_every_num_iters=1,
args=[self, training_callback_attributes],
),
TrainingCallback(
@ -352,11 +354,10 @@ class DreamFusionModel(Model):
if self.initialize_density and self.training:
pos = ray_samples.frustums.get_positions()
density_blob = (
self.config.init_density_strength
* self.density_strength
self.density_strength
* torch.exp(-torch.norm(pos, dim=-1) / (2 * 0.04))[..., None]
)
density += density_blob
density = density + density_blob
accumulation = self.renderer_accumulation(weights)
depth = self.renderer_depth(weights, ray_samples)