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- # Copyright (c) OpenMMLab. All rights reserved.
- 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()
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