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| import argparse | |
| import mmcv | |
| from mmcv import Config, DictAction | |
| from mmdet.datasets import build_dataset | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description='Evaluate metric of the ' | |
| 'results saved in pkl format') | |
| parser.add_argument('config', help='Config of the model') | |
| parser.add_argument('pkl_results', help='Results in pickle format') | |
| parser.add_argument( | |
| '--format-only', | |
| action='store_true', | |
| help='Format the output results without perform evaluation. It is' | |
| 'useful when you want to format the result to a specific format and ' | |
| 'submit it to the test server') | |
| parser.add_argument( | |
| '--eval', | |
| type=str, | |
| nargs='+', | |
| help='Evaluation metrics, which depends on the dataset, e.g., "bbox",' | |
| ' "segm", "proposal" for COCO, and "mAP", "recall" for PASCAL VOC') | |
| 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( | |
| '--eval-options', | |
| nargs='+', | |
| action=DictAction, | |
| help='custom options for evaluation, the key-value pair in xxx=yyy ' | |
| 'format will be kwargs for dataset.evaluate() function') | |
| args = parser.parse_args() | |
| return args | |
| def main(): | |
| args = parse_args() | |
| cfg = Config.fromfile(args.config) | |
| assert args.eval or args.format_only, ( | |
| 'Please specify at least one operation (eval/format the results) with ' | |
| 'the argument "--eval", "--format-only"') | |
| if args.eval and args.format_only: | |
| raise ValueError('--eval and --format_only cannot be both specified') | |
| if args.cfg_options is not None: | |
| cfg.merge_from_dict(args.cfg_options) | |
| # import modules from string list. | |
| if cfg.get('custom_imports', None): | |
| from mmcv.utils import import_modules_from_strings | |
| import_modules_from_strings(**cfg['custom_imports']) | |
| cfg.data.test.test_mode = True | |
| dataset = build_dataset(cfg.data.test) | |
| outputs = mmcv.load(args.pkl_results) | |
| kwargs = {} if args.eval_options is None else args.eval_options | |
| if args.format_only: | |
| dataset.format_results(outputs, **kwargs) | |
| if args.eval: | |
| eval_kwargs = cfg.get('evaluation', {}).copy() | |
| # hard-code way to remove EvalHook args | |
| for key in [ | |
| 'interval', 'tmpdir', 'start', 'gpu_collect', 'save_best', | |
| 'rule' | |
| ]: | |
| eval_kwargs.pop(key, None) | |
| eval_kwargs.update(dict(metric=args.eval, **kwargs)) | |
| print(dataset.evaluate(outputs, **eval_kwargs)) | |
| if __name__ == '__main__': | |
| main() | |