コード例 #1
0
def main():
    args = parse_args()
    cfg = Config.fromfile(args.config)
    if args.work_dir is not None:
        cfg.work_dir = args.work_dir
    if args.checkpoint is not None:
        cfg.load_from = args.checkpoint
    # init distributed env first
    if args.launcher == 'none':
        distributed = False
    else:
        distributed = True
        init_dist(args.launcher, **cfg.dist_params)

    # init logger
    logger = get_root_logger(cfg.log_level)
    logger.info('Distributed test: {}'.format(distributed))

    # build model and load checkpoint
    if args.stage == 'GMM':
        # test geometric matching
        # data loader
        dataset = get_dataset(cfg.data.test.GMM)
        print('GMM dataset loaded')

        model = build_geometric_matching(cfg.GMM)
        print('GMM model built')
        load_checkpoint(model, cfg.load_from, map_location='cpu')
        print('load checkpoint from: {}'.format(cfg.load_from))

        test_geometric_matching(model,
                                dataset,
                                cfg,
                                distributed=distributed,
                                validate=False,
                                logger=logger)

    elif args.stage == 'TOM':
        # test tryon module
        dataset = get_dataset(cfg.data.test.TOM)
        print('TOM dataset loaded')

        model = build_tryon(cfg.TOM)
        print('TOM model built')
        load_checkpoint(model, cfg.load_from, map_location='cpu')
        print('load checkpoint from: {}'.format(cfg.load_from))

        test_tryon(model,
                   dataset,
                   cfg,
                   distributed=distributed,
                   validate=False,
                   logger=logger)
コード例 #2
0
ファイル: test_predictor.py プロジェクト: won21kr/mmfashion
def main():
    args = parse_args()
    cfg = Config.fromfile(args.config)
    if args.work_dir is not None:
        cfg.work_dir = args.work_dir
    if args.checkpoint is not None:
        cfg.load_from = args.checkpoint
    # init distributed env first
    if args.launcher == 'none':
        distributed = False
    else:
        distributed = True
        init_dist(args.launcher, **cfg.dist_params)

    # init logger
    logger = get_root_logger(cfg.log_level)
    logger.info('Distributed test: {}'.format(distributed))

    # data loader
    dataset = get_dataset(cfg.data.test)
    print('dataset loaded')

    # build model and load checkpoint
    model = build_predictor(cfg.model)
    print('model built')

    load_checkpoint(model, cfg.load_from, map_location='cpu')
    print('load checkpoint from: {}'.format(cfg.load_from))

    # test
    test_predictor(
        model,
        dataset,
        cfg,
        distributed=distributed,
        validate=args.validate,
        logger=logger)