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import argparse |
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import mmengine |
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from mmengine import Config, DictAction |
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from mmengine.evaluator import Evaluator |
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from mmengine.registry import init_default_scope |
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from mmdet.registry import DATASETS |
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def parse_args(): |
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parser = argparse.ArgumentParser(description='Evaluate metric of the ' |
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'results saved in pkl format') |
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parser.add_argument('config', help='Config of the model') |
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parser.add_argument('pkl_results', help='Results in pickle format') |
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parser.add_argument( |
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'--cfg-options', |
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nargs='+', |
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action=DictAction, |
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help='override some settings in the used config, the key-value pair ' |
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'in xxx=yyy format will be merged into config file. If the value to ' |
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'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' |
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'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' |
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'Note that the quotation marks are necessary and that no white space ' |
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'is allowed.') |
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args = parser.parse_args() |
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return args |
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def main(): |
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args = parse_args() |
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cfg = Config.fromfile(args.config) |
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init_default_scope(cfg.get('default_scope', 'mmdet')) |
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if args.cfg_options is not None: |
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cfg.merge_from_dict(args.cfg_options) |
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dataset = DATASETS.build(cfg.test_dataloader.dataset) |
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predictions = mmengine.load(args.pkl_results) |
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evaluator = Evaluator(cfg.val_evaluator) |
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evaluator.dataset_meta = dataset.metainfo |
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eval_results = evaluator.offline_evaluate(predictions) |
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print(eval_results) |
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if __name__ == '__main__': |
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main() |
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