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- import Levenshtein
- class RecMetric(object):
- def __init__(self, main_indicator='acc', **kwargs):
- self.main_indicator = main_indicator
- self.reset()
- def __call__(self, pred_label, *args, **kwargs):
- preds, labels = pred_label
- correct_num = 0
- all_num = 0
- norm_edit_dis = 0.0
- for (pred, pred_conf), (target, _) in zip(preds, labels):
- pred = pred.replace(" ", "")
- target = target.replace(" ", "")
- norm_edit_dis += Levenshtein.distance(pred, target) / max(
- len(pred), len(target), 1)
- if pred == target:
- correct_num += 1
- all_num += 1
- self.correct_num += correct_num
- self.all_num += all_num
- self.norm_edit_dis += norm_edit_dis
- return {
- 'acc': correct_num / all_num,
- 'norm_edit_dis': 1 - norm_edit_dis / all_num
- }
- def get_metric(self):
- """
- return metrics {
- 'acc': 0,
- 'norm_edit_dis': 0,
- }
- """
- acc = 1.0 * self.correct_num / self.all_num
- norm_edit_dis = 1 - self.norm_edit_dis / self.all_num
- self.reset()
- return {'acc': acc, 'norm_edit_dis': norm_edit_dis}
- def reset(self):
- self.correct_num = 0
- self.all_num = 0
- self.norm_edit_dis = 0
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