def get_parser() -> CfgNode: """ """ parser = argparse.ArgumentParser( description='PyTorch Semantic Segmentation') parser.add_argument( '--config', type=str, default=f'{_ROOT}/config/test/default_config_360_ss.yaml', help='config file') parser.add_argument( '--file_save', type=str, default='default', help='eval result to save, when lightweight option is on') parser.add_argument( 'opts', help='see config/ade20k/ade20k_pspnet50.yaml for all options', default=None, nargs=argparse.REMAINDER) # model path is passed in args = parser.parse_args() print(args) assert args.config is not None cfg = config.load_cfg_from_cfg_file(args.config) if args.opts is not None: cfg = config.merge_cfg_from_list(cfg, args.opts) return cfg
def get_parser() -> CfgNode: """ TODO: add to library to avoid replication. """ parser = argparse.ArgumentParser( description='PyTorch Semantic Segmentation') parser.add_argument('--config', type=str, default='config/wilddash_18/wilddash_18_flat.yaml', help='config file') parser.add_argument( '--file_save', type=str, default='default', help='eval result to save, when lightweight option is on') # parser.add_argument('--file_load', type=str, default='', help='possible additional config') # parser.add_argument('--checkpoint_load', type=str, default='', help='possible checkpoint loading directly specified in argument') parser.add_argument( 'opts', help='see config/ade20k/ade20k_pspnet50.yaml for all options', default=None, nargs=argparse.REMAINDER) # model path is passed in args = parser.parse_args() assert args.config is not None cfg = config.load_cfg_from_cfg_file(args.config) if args.opts is not None: cfg = config.merge_cfg_from_list(cfg, args.opts) return cfg
def get_parser(): import argparse from mseg_semantic.utils import config parser = argparse.ArgumentParser(description='PyTorch Semantic Segmentation') parser.add_argument('--config', type=str, default='config/ade20k/ade20k_pspnet50.yaml', help='config file') parser.add_argument('opts', help='see config/ade20k/ade20k_pspnet50.yaml for all options', default=None, nargs=argparse.REMAINDER) args = parser.parse_args() assert args.config is not None cfg = config.load_cfg_from_cfg_file(args.config) if args.opts is not None: cfg = config.merge_cfg_from_list(cfg, args.opts) return cfg
def get_parser() -> CfgNode: """ TODO: add to library to avoid replication. """ parser = argparse.ArgumentParser(description='PyTorch Semantic Segmentation') parser.add_argument('--config', type=str, default='config/wilddash_18/wilddash_18_flat.yaml', help='config file') parser.add_argument('--file_save', type=str, default='default', help='eval result to save, when lightweight option is on') parser.add_argument('opts', help='see mseg_semantic/config/test/default_config_360.yaml for all options, model path should be passed in', default=None, nargs=argparse.REMAINDER) args = parser.parse_args() assert args.config is not None cfg = config.load_cfg_from_cfg_file(args.config) if args.opts is not None: cfg = config.merge_cfg_from_list(cfg, args.opts) return cfg