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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import json
import mmengine
from mmengine.config import Config, DictAction
from mmengine.evaluator import Evaluator
from mmengine.registry import init_default_scope
def parse_args():
parser = argparse.ArgumentParser(description='Offline evaluation of the '
'prediction saved in pkl format')
parser.add_argument('config', help='Config of the model')
parser.add_argument(
'pkl_results', help='Path to the predictions in '
'pickle format')
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.')
args = parser.parse_args()
return args
def main():
args = parse_args()
# load config
cfg = Config.fromfile(args.config)
init_default_scope(cfg.get('default_scope', 'mmocr'))
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
predictions = mmengine.load(args.pkl_results)
evaluator = Evaluator(cfg.test_evaluator)
eval_results = evaluator.offline_evaluate(predictions)
print(json.dumps(eval_results))
if __name__ == '__main__':
main()
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