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