if __name__ == "__main__":
# prepare
parser = create_parser()
args = parser.parse_args()
args.train_joints = np.arange(args.num_classes)
logger.debug(f"Training joints: {args.train_joints}")
logger.debug(f"Acc joints: {args.acc_joints}")
args.checkpoint = (args.checkpoint.replace(" ", "_").replace("(",
"_").replace(
")", "_"))
args.checkpoint = os.path.join(
args.checkpoint,
get_time() + "_{}_{}_{}_{}_{}_{}".format(
"predict" if args.unlabeled else "training",
args.arch,
args.stacks,
args.img_res,
args.blocks,
args.name,
),
)
args.checkpoint = args.checkpoint.replace("__", "_").replace("--", "-")
logger.debug("Checkpoint dir: {}".format(args.checkpoint))
args.checkpoint_image_dir = os.path.join(args.checkpoint, "./images/")
# create checkpoint dir and image dir
if args.unlabeled is None:
os.makedirs(args.checkpoint, exist_ok=True)
parser = create_parser()
args = parser.parse_args()
args.train_joints = np.arange(args.num_classes)
acc_joints_tmp = []
for i in range(3):
p = [(i * 5) + k for k in args.acc_joints]
acc_joints_tmp.extend(p)
args.acc_joints = acc_joints_tmp
getLogger('df3d').setLevel(10)
getLogger('df3d').debug(f"Training joints: {args.train_joints}")
getLogger('df3d').debug(f"Acc joints: {args.acc_joints}")
args.checkpoint = os.path.join(
args.checkpoint,
get_time()
+ "_{}_{}_{}_{}_{}_{}_{}".format(
"predict" if args.unlabeled else "training",
args.arch,
args.stacks,
args.img_res,
args.blocks,
"mv" if args.multiview else "",
"temp" if args.multiview else "",
args.name,
),
)
args.checkpoint = (
args.checkpoint.replace(" ", "_").replace("(", "_").replace(")", "_")
)
args.checkpoint = args.checkpoint.replace("__", "_").replace("--", "-")