def setup_config(cls: type, config_fpath: str, model_fpath: str,
args: argparse.Namespace, opts: List[str]):
cfg = get_cfg()
add_densepose_config(cfg)
add_hrnet_config(cfg)
cfg.merge_from_file(config_fpath)
cfg.merge_from_list(args.opts)
if opts:
cfg.merge_from_list(opts)
cfg.MODEL.WEIGHTS = model_fpath
cfg.freeze()
return cfg
def setup(args):
cfg = get_cfg()
add_dataset_category_config(cfg)
add_densepose_config(cfg)
add_hrnet_config(cfg)
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
default_setup(cfg, args)
# Setup logger for "densepose" module
setup_logger(output=cfg.OUTPUT_DIR, distributed_rank=comm.get_rank(), name="densepose")
return cfg
def setup_config(config_fpath: str, model_fpath: str, opts: List[str]):
opts.append("MODEL.ROI_HEADS.SCORE_THRESH_TEST")
opts.append(0.8) # Min score
cfg = get_cfg()
add_densepose_config(cfg)
add_hrnet_config(cfg)
cfg.merge_from_file(config_fpath)
if opts:
cfg.merge_from_list(opts)
cfg.MODEL.WEIGHTS = model_fpath
cfg.freeze()
return cfg
def _get_model_config(config_file):
"""
Load and return the configuration from the specified file (relative to the base configuration
directory)
"""
cfg = get_cfg()
add_dataset_category_config(cfg)
add_densepose_config(cfg)
add_hrnet_config(cfg)
path = os.path.join(_get_base_config_dir(), config_file)
cfg.merge_from_file(path)
if not torch.cuda.is_available():
cfg.MODEL_DEVICE = "cpu"
return cfg
