Description
hi, Thank you for the open source code.
###questions#######
I would like to ask you some questions. During model training, a point_cloud.ply file was generated at iteration 7000, but no point cloud results were saved at iteration 30000, and there were no error messages either. What could be the reason for this? Thank you very much.
####Training log######
(base) root@VM-0-13-ubuntu:/home/ubuntu/projects/gaussian-splatting# cat train-2-21.log
nohup: ignoring input
Optimizing
Output folder: ./output/52735481-0 [21/02 18:13:22]
Tensorboard not available: not logging progress [21/02 18:13:22]
Reading camera 624/624 [21/02 18:13:26]
Loading Training Cameras [21/02 18:13:26]
Loading Test Cameras [21/02 18:14:40]
Number of points at initialisation : 526103 [21/02 18:14:40]
Training progress: 100%|██████████| 30000/30000 [44:55:29<00:00, 5.39s/it, Loss=0.0217425]
####Training parameters configuration######
the parameters configuration of the train.py ：
if name == "main":
# Set up command line argument parser
parser = ArgumentParser(description="Training script parameters")
lp = ModelParams(parser)
op = OptimizationParams(parser)
pp = PipelineParams(parser)
parser.add_argument('--ip', type=str, default="127.0.0.1")
parser.add_argument('--port', type=int, default=6009)
parser.add_argument('--debug_from', type=int, default=-1)
parser.add_argument('--detect_anomaly', action='store_true', default=False)
parser.add_argument("--test_iterations", nargs="+", type=int, default=[7_000, 30_000])
parser.add_argument("--save_iterations", nargs="+", type=int, default=[7_000, 30_000])
parser.add_argument("--quiet", action="store_true")
parser.add_argument("--checkpoint_iterations", nargs="+", type=int, default=[])
parser.add_argument("--start_checkpoint", type=str, default = None)
args = parser.parse_args(sys.argv[1:])
args.save_iterations.append(args.iterations)
print("Optimizing " + args.model_path)
...
the parameters configuration of the gaussian-splatting/arguments/init.py ：
class ModelParams(ParamGroup):
def init(self, parser, sentinel=False):
self.sh_degree = 3
self._source_path = "/home/ubuntu/projects/gaussian-splatting/datasets/dji_0843_ds15"
self._model_path = ""
self._images = "images"
self._resolution = 2
self._white_background = False
self.data_device = "cpu"
self.eval = False #####False
super().init(parser, "Loading Parameters", sentinel)
...
class OptimizationParams(ParamGroup):
def init(self, parser):
self.iterations = 30_000
self.position_lr_init = 0.000160.1
self.position_lr_final = 0.00000160.1
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 = 0.001
self.rotation_lr = 0.001
self.percent_dense = 0.01
self.lambda_dssim = 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")
...