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# Copyright (C) 2023, Inria
# GRAPHDECO research group, https://team.inria.fr/graphdeco
# All rights reserved.
#
# This software is free for non-commercial, research and evaluation use
# under the terms of the LICENSE.md file.
#
# For inquiries contact george.drettakis@inria.fr
#
from argparse import ArgumentParser, Namespace
import sys
import os
class GroupParams:
pass
class ParamGroup:
def __init__(self, parser: ArgumentParser, name : str, fill_none = False):
group = parser.add_argument_group(name)
for key, value in vars(self).items():
shorthand = False
if key.startswith("_"):
shorthand = True
key = key[1:]
t = type(value)
value = value if not fill_none else None
if shorthand:
if t == bool:
group.add_argument("--" + key, ("-" + key[0:1]), default=value, action="store_true")
else:
group.add_argument("--" + key, ("-" + key[0:1]), default=value, type=t)
else:
if t == bool:
group.add_argument("--" + key, default=value, action="store_true")
else:
group.add_argument("--" + key, default=value, type=t)
def extract(self, args):
group = GroupParams()
for arg in vars(args).items():
if arg[0] in vars(self) or ("_" + arg[0]) in vars(self):
setattr(group, arg[0], arg[1])
return group
class ModelParams(ParamGroup):
def __init__(self, parser, sentinel=False):
self.debug_test = False
self.sh_degree = 3
self._source_path = ""
self._model_path = ""
self._images = "images"
self._resolution = -1
self._white_background = False
self.data_device = "cuda"
self.eval = True
# test/ train split
self.stride = 0
self.waymo_split_mode = ""
# visual
self.render_process=True
# waymo
self.start_time = 0 # now hard-coded
self.end_time = 49
self.original_start_time = 0 # now hard-coded
self.num_objs = 256
self.num_pts = 1500000
# mask loading options
self.load_sky_mask = False
self.load_panoptic_mask = False
self.load_sam_mask = False
self.load_dynamic_mask = True
self.load_feat_map = True
# waymo
self.n_views = 100
self.random_init = False
self.train_split = False
self.num_classes = 200
self.load_intrinsic = False
self.load_c2w = False
# occ grid
self.save_occ_grid = True
self.occ_voxel_size = 0.4
self.recompute_occ_grid = False
super().__init__(parser, "Loading Parameters", sentinel)
def extract(self, args):
g = super().extract(args)
g.source_path = os.path.abspath(g.source_path)
return g
class PipelineParams(ParamGroup):
def __init__(self, parser):
self.convert_SHs_python = True
self.compute_cov3D_python = False
self.debug = False
super().__init__(parser, "Pipeline Parameters")
class OptimizationParams(ParamGroup):
def __init__(self, parser):
self.vis_step = 2000
self.batch_size=1
self.iterations = 50_000 # 30_000
self.coarse_iterations = 5000
self.position_lr_init = 0.00016
self.position_lr_final = 0.0000016
self.position_lr_delay_mult = 0.01
self.position_lr_max_steps = 30_000
self.deformation_lr_init = 0.000016
self.deformation_lr_final = 0.0000016
self.deformation_lr_delay_mult = 0.01
self.grid_lr_init = 0.00016
self.grid_lr_final = 0.000016
self.feature_lr = 0.0025
self.opacity_lr = 0.05
self.scaling_lr = 0.005
self.rotation_lr = 0.001
self.percent_dense = 0.01
self.lambda_dssim = 0.2
self.lambda_depth = 0.5
self.densification_interval = 100 # 100
self.opacity_reset_interval = 3000
self.pruning_interval = 100
self.pruning_from_iter = 500
self.densify_until_iter = 25_000
# self.densify_grad_threshold = 0.0002
self.densify_grad_threshold_coarse = 0.0002
self.densify_grad_threshold_fine_init = 0.0002
self.densify_grad_threshold_after = 0.0002
# self.min_opacity_threshold = 0.005
self.opacity_threshold_coarse = 0.005
self.opacity_threshold_fine_init = 0.005
self.opacity_threshold_fine_after = 0.005
self.random_background = False
# for waymo
self.max_points = 500_000
self.prune_from_iter = 500
self.prune_interval = 100
self.scale_ratio = 1.0 # global-scale = local-norm-scale * voxel_size * scale_ratio
# feat
self.include_feature = True
self.language_feature_lr = 0.0025 # TODO: update
self.feat_dim = 8 #12 # recomplie-cuda SET DISTUTILS_USE_SDK=1
self.feat_conv_lr = 0.0001
self.lambda_feat = 0.001
self.dx_reg = False
self.lambda_dx = 0.001
self.lambda_dshs = 0.001
# TODO: don't use, clean
self.use_bg_gs = True
self.use_bg_model = False
self.bg_aabb_scale = 20.0 #2
self.bg_gs_num = 5000
self.bg_percent_dense = 0.01 #0.01
self.bg_model_type = 'gs' #'mlp'
self.mlp_width = 256
self.bg_grid_res = 10 # aabb/grid_res = grid_size
self.bg_model_lr = 0.0025
self.custom_xyz_scheduler = False
# deprecated
self.densify_from_iter = 500 # 调整至与position_lr_after_iter 一致 # 500
self.position_lr_after_iter = 500
self.scale_ratio_threshold = 5.0
self.hard_alpha_composite = True
self.alpha_mask_threshold = 0.8
super().__init__(parser, "Optimization Parameters")
def get_combined_args(parser : ArgumentParser):
cmdlne_string = sys.argv[1:]
cfgfile_string = "Namespace()"
args_cmdline = parser.parse_args(cmdlne_string)
try:
cfgfilepath = os.path.join(args_cmdline.model_path, "cfg_args")
print("Looking for config file in", cfgfilepath)
with open(cfgfilepath) as cfg_file:
print("Config file found: {}".format(cfgfilepath))
cfgfile_string = cfg_file.read()
except TypeError:
print("Config file not found at")
pass
args_cfgfile = eval(cfgfile_string)
merged_dict = vars(args_cfgfile).copy()
for k,v in vars(args_cmdline).items():
if v != None:
merged_dict[k] = v
return Namespace(**merged_dict)
class ModelHiddenParams(ParamGroup):
def __init__(self, parser):
self.net_width = 64
self.timebase_pe = 4
self.defor_depth = 1
self.posebase_pe = 10
self.scale_rotation_pe = 2
self.opacity_pe = 2
self.timenet_width = 64
self.timenet_output = 32
self.bounds = 1.6
self.plane_tv_weight = 0.0001
self.time_smoothness_weight = 0.01
self.l1_time_planes = 0.0001
self.kplanes_config = {
'grid_dimensions': 2,
'input_coordinate_dim': 4,
'output_coordinate_dim': 32,
'resolution': [64, 64, 64, 25]
}
self.multires = [1, 2, 4, 8]
self.no_dx=False
self.no_grid=False
self.no_ds=True
self.no_dr=True
self.no_do=True
self.no_dshs=False
self.feat_head=True
self.empty_voxel=False
self.grid_pe=0
self.static_mlp=False
self.apply_rotation=False
super().__init__(parser, "ModelHiddenParams")
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