UniqAI/gaussian-splatting
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update script

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liuzhi 2024-05-10 23:29:29 +08:00
parent 29de835916
commit 1dd0a100b5
2 changed files with 6 additions and 6 deletions
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3
run_code.txt
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Running: Running:
# Train with train/test split # Train with train/test split
python train.py --source_path <path to COLMAP or NeRF Synthetic dataset> --model_path <保存路径> --eval python train.py --source_path <path to COLMAP or NeRF Synthetic dataset> --model_path <保存路径> --eval
python train.py --source_path ../../Dataset/3DGS_Dataset/科技馆 --model_path output/kejiguan --eval --resolution 1 python train.py --source_path ../../Dataset/3DGS_Dataset/linggongtang --model_path output/linggongtang --data_device 'cpu' --eval --resolution 1
python train.py --source_path ../../Dataset/3DGS_Dataset/xiangjiadang --model_path output/xiangjiadang --data_device 'cpu' --eval --resolution 1
--source_path / -s：COLMAP 或合成 Synthetic NeRF data set的源目录的路径。COLMAP类型包含 images/, sparse/0 --source_path / -s：COLMAP 或合成 Synthetic NeRF data set的源目录的路径。COLMAP类型包含 images/, sparse/0
--model_path / -m：训练模型的存储路径，默认为 output/<random> --model_path / -m：训练模型的存储路径，默认为 output/<random>

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run_train_ours.py
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# python train.py --source_path ../../Dataset/3DGS_Dataset/凌公塘 --model_path output/linggongtang --eval --resolution 1 # python train.py --source_path ../../Dataset/3DGS_Dataset/linggongtang --model_path output/linggongtang --data_device 'cpu' --eval --resolution 1
# scene: {'科技馆': 'kejiguan', '万佛塔': 'wanfota', '植物': 'zhiwu', '凌公塘': 'linggongtang', '湘家荡': 'xiangjiadang', '寺平古宅': 'sipingguzhai'} # scene: {'kejiguan': 'cuda', 'wanfota': 'cuda', 'zhiwu': 'cuda', 'linggongtang': 'cpu', 'xiangjiadang': 'cpu', 'sipingguzhai': 'cpu'}
# : {'科技馆': ['kejiguan', 'cuda'], '万佛塔': ['wanfota', 'cuda'], '植物': ['zhiwu', 'cuda'], '凌公塘': ['linggongtang', 'cpu'], '湘家荡': ['xiangjiadang', 'cpu'], '寺平古宅': ['sipingguzhai', 'cpu']}
# device = cuda: 科技馆、万佛塔、植物 # device = cuda: 科技馆、万佛塔、植物
# = cpu: 凌公塘、湘家荡、寺平古宅 # = cpu: 凌公塘、湘家荡、寺平古宅
import os import os
for cuda, scene in enumerate({'科技馆': ['kejiguan', 'cuda'], '湘家荡': ['xiangjiadang', 'cpu'], '凌公塘': ['linggongtang', 'cpu'], '寺平古宅': ['sipingguzhai', 'cpu'],}.items()): for cuda, scene in enumerate({'linggongtang': 'cpu', 'xiangjiadang': 'cpu', 'sipingguzhai': 'cpu'}.items()):
print('---------------------------------------------------------------------------------') print('---------------------------------------------------------------------------------')
one_cmd = f'python train.py --source_path ../../Dataset/3DGS_Dataset/{scene[0]} --model_path output/{scene[1][0]} --data_device "{scene[1][1]}" --resolution 1 --eval' one_cmd = f'python train.py --source_path ../../Dataset/3DGS_Dataset/{scene[0]} --model_path output/{scene[0]} --data_device "{scene[1]}" --resolution 1 --eval'
os.system(one_cmd) os.system(one_cmd)