mirror of
https://github.com/graphdeco-inria/gaussian-splatting
synced 2025-02-18 02:07:12 +00:00
b5a5f72eda
Images are now loaded on the target device as uint8s. Then they are converted to the target data type (eg. fp32 or fp16). This speeds up the loading time. Also, users can opt to store the image as uint8 or as target data type. This will further reduce memory usage.
115 lines
3.8 KiB
Python
115 lines
3.8 KiB
Python
#
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# Copyright (C) 2023, Inria
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# GRAPHDECO research group, https://team.inria.fr/graphdeco
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# All rights reserved.
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#
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# This software is free for non-commercial, research and evaluation use
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# under the terms of the LICENSE.md file.
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#
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# For inquiries contact george.drettakis@inria.fr
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#
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from argparse import ArgumentParser, Namespace
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import sys
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import os
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class GroupParams:
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pass
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class ParamGroup:
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def __init__(self, parser: ArgumentParser, name : str, fill_none = False):
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group = parser.add_argument_group(name)
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for key, value in vars(self).items():
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shorthand = False
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if key.startswith("_"):
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shorthand = True
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key = key[1:]
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t = type(value)
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value = value if not fill_none else None
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if shorthand:
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if t == bool:
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group.add_argument("--" + key, ("-" + key[0:1]), default=value, action="store_true")
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else:
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group.add_argument("--" + key, ("-" + key[0:1]), default=value, type=t)
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else:
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if t == bool:
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group.add_argument("--" + key, default=value, action="store_true")
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else:
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group.add_argument("--" + key, default=value, type=t)
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def extract(self, args):
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group = GroupParams()
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for arg in vars(args).items():
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if arg[0] in vars(self) or ("_" + arg[0]) in vars(self):
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setattr(group, arg[0], arg[1])
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return group
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class ModelParams(ParamGroup):
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def __init__(self, parser, sentinel=False):
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self.sh_degree = 3
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self._source_path = ""
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self._model_path = ""
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self._images = "images"
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self._resolution = -1
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self._white_background = False
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self.data_device = "cuda"
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self.data_dtype = "float32"
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self.store_images_as_uint8 = False
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self.eval = False
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super().__init__(parser, "Loading Parameters", sentinel)
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def extract(self, args):
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g = super().extract(args)
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g.source_path = os.path.abspath(g.source_path)
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return g
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class PipelineParams(ParamGroup):
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def __init__(self, parser):
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self.convert_SHs_python = False
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self.compute_cov3D_python = False
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self.debug = False
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super().__init__(parser, "Pipeline Parameters")
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class OptimizationParams(ParamGroup):
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def __init__(self, parser):
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self.iterations = 30_000
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self.position_lr_init = 0.00016
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self.position_lr_final = 0.0000016
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self.position_lr_delay_mult = 0.01
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self.position_lr_max_steps = 30_000
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self.feature_lr = 0.0025
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self.opacity_lr = 0.05
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self.scaling_lr = 0.005
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self.rotation_lr = 0.001
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self.percent_dense = 0.01
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self.lambda_dssim = 0.2
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self.densification_interval = 100
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self.opacity_reset_interval = 3000
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self.densify_from_iter = 500
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self.densify_until_iter = 15_000
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self.densify_grad_threshold = 0.0002
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self.random_background = False
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super().__init__(parser, "Optimization Parameters")
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def get_combined_args(parser : ArgumentParser):
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cmdlne_string = sys.argv[1:]
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cfgfile_string = "Namespace()"
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args_cmdline = parser.parse_args(cmdlne_string)
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try:
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cfgfilepath = os.path.join(args_cmdline.model_path, "cfg_args")
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print("Looking for config file in", cfgfilepath)
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with open(cfgfilepath) as cfg_file:
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print("Config file found: {}".format(cfgfilepath))
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cfgfile_string = cfg_file.read()
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except TypeError:
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print("Config file not found at")
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pass
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args_cfgfile = eval(cfgfile_string)
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merged_dict = vars(args_cfgfile).copy()
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for k,v in vars(args_cmdline).items():
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if v != None:
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merged_dict[k] = v
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return Namespace(**merged_dict)
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