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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import argparse | |
| import os | |
| import os.path as osp | |
| from mmengine.config import Config, DictAction | |
| from mmengine.registry import RUNNERS | |
| from mmengine.runner import Runner | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description='Test (and eval) a model') | |
| parser.add_argument('config', help='Test config file path') | |
| parser.add_argument('checkpoint', help='Checkpoint file') | |
| parser.add_argument( | |
| '--work-dir', | |
| help='The directory to save the file containing evaluation metrics') | |
| parser.add_argument( | |
| '--save-preds', | |
| action='store_true', | |
| help='Dump predictions to a pickle file for offline evaluation') | |
| parser.add_argument( | |
| '--show', action='store_true', help='Show prediction results') | |
| parser.add_argument( | |
| '--show-dir', | |
| help='Directory where painted images will be saved. ' | |
| 'If specified, it will be automatically saved ' | |
| 'to the work_dir/timestamp/show_dir') | |
| parser.add_argument( | |
| '--wait-time', type=float, default=2, help='The interval of show (s)') | |
| parser.add_argument( | |
| '--cfg-options', | |
| nargs='+', | |
| action=DictAction, | |
| help='Override some settings in the used config, the key-value pair ' | |
| 'in xxx=yyy format will be merged into config file. If the value to ' | |
| 'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' | |
| 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' | |
| 'Note that the quotation marks are necessary and that no white space ' | |
| 'is allowed.') | |
| parser.add_argument( | |
| '--launcher', | |
| choices=['none', 'pytorch', 'slurm', 'mpi'], | |
| default='none', | |
| help='Job launcher') | |
| parser.add_argument( | |
| '--tta', action='store_true', help='Test time augmentation') | |
| # When using PyTorch version >= 2.0.0, the `torch.distributed.launch` | |
| # will pass the `--local-rank` parameter to `tools/test.py` instead | |
| # of `--local_rank`. | |
| parser.add_argument('--local_rank', '--local-rank', type=int, default=0) | |
| args = parser.parse_args() | |
| if 'LOCAL_RANK' not in os.environ: | |
| os.environ['LOCAL_RANK'] = str(args.local_rank) | |
| return args | |
| def trigger_visualization_hook(cfg, args): | |
| default_hooks = cfg.default_hooks | |
| if 'visualization' in default_hooks: | |
| visualization_hook = default_hooks['visualization'] | |
| # Turn on visualization | |
| visualization_hook['enable'] = True | |
| visualization_hook['draw_gt'] = True | |
| visualization_hook['draw_pred'] = True | |
| if args.show: | |
| visualization_hook['show'] = True | |
| visualization_hook['wait_time'] = args.wait_time | |
| if args.show_dir: | |
| cfg.visualizer['save_dir'] = args.show_dir | |
| cfg.visualizer['vis_backends'] = [dict(type='LocalVisBackend')] | |
| else: | |
| raise RuntimeError( | |
| 'VisualizationHook must be included in default_hooks.' | |
| 'refer to usage ' | |
| '"visualization=dict(type=\'VisualizationHook\')"') | |
| return cfg | |
| def main(): | |
| args = parse_args() | |
| # load config | |
| cfg = Config.fromfile(args.config) | |
| 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 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 | |
| # TODO: It will be supported after refactoring the visualizer | |
| if args.show and args.show_dir: | |
| raise NotImplementedError('--show and --show-dir cannot be set ' | |
| 'at the same time') | |
| if args.show or args.show_dir: | |
| cfg = trigger_visualization_hook(cfg, args) | |
| if args.tta: | |
| cfg.test_dataloader.dataset.pipeline = cfg.tta_pipeline | |
| cfg.tta_model.module = cfg.model | |
| cfg.model = cfg.tta_model | |
| # save predictions | |
| if args.save_preds: | |
| dump_metric = dict( | |
| type='DumpResults', | |
| out_file_path=osp.join( | |
| cfg.work_dir, | |
| f'{osp.basename(args.checkpoint)}_predictions.pkl')) | |
| if isinstance(cfg.test_evaluator, (list, tuple)): | |
| cfg.test_evaluator = list(cfg.test_evaluator) | |
| cfg.test_evaluator.append(dump_metric) | |
| else: | |
| cfg.test_evaluator = [cfg.test_evaluator, dump_metric] | |
| # 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__': | |
| main() | |