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Source code for mmocr.datasets.ocr_dataset

# Copyright (c) OpenMMLab. All rights reserved.
from mmdet.datasets.builder import DATASETS

from mmocr.core.evaluation.ocr_metric import eval_ocr_metric
from mmocr.datasets.base_dataset import BaseDataset


[docs]@DATASETS.register_module() class OCRDataset(BaseDataset):
[docs] def pre_pipeline(self, results): results['img_prefix'] = self.img_prefix results['text'] = results['img_info']['text']
[docs] def evaluate(self, results, metric='acc', logger=None, **kwargs): """Evaluate the dataset. Args: results (list): Testing results of the dataset. metric (str | list[str]): Metrics to be evaluated. logger (logging.Logger | str | None): Logger used for printing related information during evaluation. Default: None. Returns: dict[str: float] """ gt_texts = [] pred_texts = [] for i in range(len(self)): item_info = self.data_infos[i] text = item_info['text'] gt_texts.append(text) pred_texts.append(results[i]['text']) eval_results = eval_ocr_metric(pred_texts, gt_texts) return eval_results
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