SMPLer-X / main /config.py
onescotch
clean up for zero gpus
010a8bc
import os
import os.path as osp
import sys
import datetime
from mmengine.config import Config as MMConfig
class Config:
def get_config_fromfile(self, config_path):
self.config_path = config_path
cfg = MMConfig.fromfile(self.config_path)
self.__dict__.update(dict(cfg))
# update dir
self.cur_dir = osp.dirname(os.path.abspath(__file__))
self.root_dir = osp.join(self.cur_dir, '..')
self.data_dir = osp.join(self.root_dir, 'dataset')
self.human_model_path = osp.join(self.root_dir, 'common', 'utils', 'human_model_files')
## add some paths to the system root dir
sys.path.insert(0, osp.join(self.root_dir, 'common'))
def prepare_dirs(self, exp_name):
time_str = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
self.output_dir = osp.join(self.root_dir, f'{exp_name}_{time_str}')
self.model_dir = osp.join(self.output_dir, 'model_dump')
self.vis_dir = osp.join(self.output_dir, 'vis')
self.log_dir = osp.join(self.output_dir, 'log')
self.code_dir = osp.join(self.output_dir, 'code')
self.result_dir = osp.join(self.output_dir, 'result')
from utils.dir import make_folder
make_folder(self.model_dir)
make_folder(self.vis_dir)
make_folder(self.log_dir)
make_folder(self.code_dir)
make_folder(self.result_dir)
## copy some code to log dir as a backup
copy_files = ['main/train.py', 'main/test.py', 'common/base.py',
'common/nets', 'main/SMPLer_X.py',
'data/dataset.py', 'data/MSCOCO/MSCOCO.py', 'data/AGORA/AGORA.py']
for file in copy_files:
os.system(f'cp -r {self.root_dir}/{file} {self.code_dir}')
def update_test_config(self, testset, agora_benchmark, shapy_eval_split, pretrained_model_path, use_cache,
eval_on_train=False, vis=False):
self.testset = testset
self.agora_benchmark = agora_benchmark
self.pretrained_model_path = pretrained_model_path
self.shapy_eval_split = shapy_eval_split
self.use_cache = use_cache
self.eval_on_train = eval_on_train
self.vis = vis
def update_config(self, num_gpus, pretrained_model_path, output_folder, device):
self.num_gpus = num_gpus
self.pretrained_model_path = pretrained_model_path
self.log_dir = output_folder
self.device = device
# Save
cfg_save = MMConfig(self.__dict__)
cfg = Config()