Function main

tools/test.py:105–153

()

def main():
    args = parse_args()

    # load config
    cfg = Config.fromfile(args.config)

    # TODO: We will unify the ceph support approach with other OpenMMLab repos
    # if args.ceph:
    #     cfg = replace_ceph_backend(cfg)

    cfg.launcher = args.launcher
    if args.cfg_options is not None:
        cfg.merge_from_dict(args.cfg_options)

    # work_dir is determined in this priority: CLI > segment in file > filename
    if args.work_dir is not None:
        # update configs according to CLI args if args.work_dir is not None
        cfg.work_dir = args.work_dir
    elif args.task_name is not None:
        cfg.work_dir = osp.join('./work_dirs', args.task_name)
    elif cfg.get('work_dir', None) is None:
        # use config filename as default work_dir if cfg.work_dir is None
        cfg.work_dir = osp.join('./work_dirs',
                                osp.splitext(osp.basename(args.config))[0])

    cfg.load_from = args.checkpoint

    if args.show or args.show_dir:
        cfg = trigger_visualization_hook(cfg, args)

    if args.tta:
        # Currently, we only support tta for 3D segmentation
        # TODO: Support tta for 3D detection
        assert 'tta_model' in cfg, 'Cannot find ``tta_model`` in config.'
        assert 'tta_pipeline' in cfg, 'Cannot find ``tta_pipeline`` in config.'
        cfg.test_dataloader.dataset.pipeline = cfg.tta_pipeline
        cfg.model = ConfigDict(**cfg.tta_model, module=cfg.model)

    # build the runner from config
    if 'runner_type' not in cfg:
        # build the default runner
        runner = Runner.from_cfg(cfg)
    else:
        # build customized runner from the registry
        # if 'runner_type' is set in the cfg
        runner = RUNNERS.build(cfg)

    # start testing
    runner.test()


if __name__ == '__main__':