mirror of
https://github.com/nerfstudio-project/nerfstudio.git
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54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
"""
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Nerfstudio Config
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Define custom method here that registers with Nerfstudio CLI.
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"""
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from __future__ import annotations
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from nerfstudio.lantern.datamanager import HDRVanillaDataManagerConfig
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from nerfstudio.lantern.model import LanternModelConfig
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from nerfstudio.cameras.camera_optimizers import CameraOptimizerConfig
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from nerfstudio.configs.base_config import ViewerConfig
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from nerfstudio.data.dataparsers.nerfstudio_dataparser import \
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NerfstudioDataParserConfig
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from nerfstudio.engine.optimizers import (AdamOptimizerConfig,
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RAdamOptimizerConfig)
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from nerfstudio.engine.schedulers import ExponentialDecaySchedulerConfig
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from nerfstudio.engine.trainer import TrainerConfig
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from nerfstudio.pipelines.base_pipeline import VanillaPipelineConfig
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from nerfstudio.plugins.types import MethodSpecification
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def Get_lantern_config():
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return TrainerConfig(
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method_name="lantern-nerfacto",
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steps_per_eval_batch=500,
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steps_per_save=2000,
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max_num_iterations=30000,
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mixed_precision=True,
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pipeline=VanillaPipelineConfig(
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datamanager=HDRVanillaDataManagerConfig(
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dataparser=NerfstudioDataParserConfig(),
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train_num_rays_per_batch=4096,
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eval_num_rays_per_batch=4096,
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camera_optimizer=CameraOptimizerConfig(
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mode="SO3xR3",
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optimizer=AdamOptimizerConfig(lr=6e-4, eps=1e-8, weight_decay=1e-2),
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scheduler=ExponentialDecaySchedulerConfig(lr_final=6e-6, max_steps=200000),
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),
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),
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model=LanternModelConfig(eval_num_rays_per_chunk=1 << 15),
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),
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optimizers={
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"proposal_networks": {
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"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
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"scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
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},
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"fields": {
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"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
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"scheduler": ExponentialDecaySchedulerConfig(lr_final=0.0001, max_steps=200000),
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},
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},
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viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
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vis="viewer",
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) |