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Running
on
Zero
File size: 4,185 Bytes
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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.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 = False
self.num_frames = 18
self.radius = 2.0
self.elevation = 0.0
self.fov = 60.0
self.reso = 512
self.images = []
self.masks = []
self.num_pts = 100_000
self.train = True
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 = False
self.compute_cov3D_python = False
self.debug = False
super().__init__(parser, "Pipeline Parameters")
class OptimizationParams(ParamGroup):
def __init__(self, parser):
self.iterations = 30_000
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.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_lpips = 0.2
self.densification_interval = 100
self.opacity_reset_interval = 3000
self.densify_from_iter = 500
self.densify_until_iter = 15_000
self.densify_grad_threshold = 0.0002
self.random_background = False
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)
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