return args if __name__ == '__main__': # ------------------------------------ # args # ------------------------------------ args = parse_args() print('Called with args:') print(args) # ------------------------------------ # cfg # ------------------------------------ if args.cfg is not None: cfg_from_file(os.path.join('experiments', 'cfgs', args.cfg + '.yml')) cfg.DEBUG = args.debug if cfg.LABEL_MAP != '': _, weights = Dataset.load_mapping(cfg.LABEL_MAP) cfg.NORMALIZE_WEIGHTS = [] for weight in weights: if weight > 0: cfg.NORMALIZE_WEIGHTS.append(weight) cfg.NUM_CLASSES = len(cfg.NORMALIZE_WEIGHTS) print('Using configs:') pprint.pprint(cfg) # ------------------------------------ # gpu # ------------------------------------ os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
args.imdbval_name = "imagenet_val" args.set_cfgs = [ 'ANCHOR_SCALES', '[8, 16, 32]', 'ANCHOR_RATIOS', '[0.5,1,2]' ] elif args.dataset == "vg": args.imdb_name = "vg_150-50-50_minitrain" args.imdbval_name = "vg_150-50-50_minival" args.set_cfgs = [ 'ANCHOR_SCALES', '[4, 8, 16, 32]', 'ANCHOR_RATIOS', '[0.5,1,2]' ] args.cfg_file = ("config/{}_ls.yml".format(args.net) if args.large_scale else "config/{}.yml".format(args.net)) if args.cfg_file is not None: cfg_from_file(args.cfg_file) if args.set_cfgs is not None: cfg_from_list(args.set_cfgs) print('Using config:') pprint.pprint(cfg) cfg.TRAIN.USE_FLIPPED = False imdb, roidb, ratio_list, ratio_index = combined_roidb( args.imdbval_name, False) imdb.competition_mode(on=True) print('{:d} roidb entries'.format(len(roidb))) input_dir = args.load_dir + "/" + args.net + "/" + args.dataset if not os.path.exists(input_dir):
args = parser.parse_args() return args if __name__ == '__main__': # ------------------------------------ # args # ------------------------------------ args = parse_args() print('Called with args:') print(args) # ------------------------------------ # cfg # ------------------------------------ if args.cfg is not None: cfg_from_file(os.path.join('experiments', 'cfgs', args.cfg + '.yml')) cfg.DEBUG = args.debug if cfg.LABEL_MAP != '': _, weights = Dataset.load_mapping(cfg.LABEL_MAP) cfg.NORMALIZE_WEIGHTS = [] for weight in weights: if weight > 0: cfg.NORMALIZE_WEIGHTS.append(weight) cfg.NUM_CLASSES = len(cfg.NORMALIZE_WEIGHTS) print('Using configs:') pprint.pprint(cfg) # ------------------------------------ # gpu # ------------------------------------ os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu