def train():
args = parse_args()
if args.config_file is not None:
print("cfg file: %s" % args.config_file)
cfg_from_file(args.config_file)
train_model()
def train():
args = parse_args()
if args.config_file is not None:
cfg_from_file(args.config_file)
logger = setup_logger(cfg)
train_model()
def train():
args = parse_args()
# print(args)
if args.config_file is not None:
cfg_from_file(args.config_file)
from lib.ssds_train import train_model
train_model()
def train():
args = parse_args()
if args.config_file is not None:
cfg_from_file(args.config_file)
train_model()
def train():
cfg_from_file('./experiments/cfgs_new/yolo_v3_small_inceptionv4_v4_8.15.yml')
train_model()
def train():
args = parse_args()
if args.config_file is not None:
cfg_from_file(args.config_file)
# os.environ["CUDA_LAUNCH_BLOCKING"] = "1"
train_model()
