# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np from ppocr.metrics.det_metric import DetMetric class TableStructureMetric(object): def __init__(self, main_indicator='acc', eps=1e-6, **kwargs): self.main_indicator = main_indicator self.eps = eps self.reset() def __call__(self, pred_label, batch=None, *args, **kwargs): preds, labels = pred_label pred_structure_batch_list = preds['structure_batch_list'] gt_structure_batch_list = labels['structure_batch_list'] correct_num = 0 all_num = 0 for (pred, pred_conf), target in zip(pred_structure_batch_list, gt_structure_batch_list): pred_str = ''.join(pred) target_str = ''.join(target) if pred_str == target_str: correct_num += 1 all_num += 1 self.correct_num += correct_num self.all_num += all_num def get_metric(self): """ return metrics { 'acc': 0, } """ acc = 1.0 * self.correct_num / (self.all_num + self.eps) self.reset() return {'acc': acc} def reset(self): self.correct_num = 0 self.all_num = 0 self.len_acc_num = 0 self.token_nums = 0 self.anys_dict = dict() from collections import defaultdict self.error_num_dict = defaultdict(int) class TableMetric(object): def __init__(self, main_indicator='acc', compute_bbox_metric=False, point_num=4, **kwargs): """ @param sub_metrics: configs of sub_metric @param main_matric: main_matric for save best_model @param kwargs: """ self.structure_metric = TableStructureMetric() self.bbox_metric = DetMetric() if compute_bbox_metric else None self.main_indicator = main_indicator self.point_num = point_num self.reset() def __call__(self, pred_label, batch=None, *args, **kwargs): self.structure_metric(pred_label) if self.bbox_metric is not None: self.bbox_metric(*self.prepare_bbox_metric_input(pred_label)) def prepare_bbox_metric_input(self, pred_label): pred_bbox_batch_list = [] gt_ignore_tags_batch_list = [] gt_bbox_batch_list = [] preds, labels = pred_label batch_num = len(preds['bbox_batch_list']) for batch_idx in range(batch_num): # pred pred_bbox_list = [ self.format_box(pred_box) for pred_box in preds['bbox_batch_list'][batch_idx] ] pred_bbox_batch_list.append({'points': pred_bbox_list}) # gt gt_bbox_list = [] gt_ignore_tags_list = [] for gt_box in labels['bbox_batch_list'][batch_idx]: gt_bbox_list.append(self.format_box(gt_box)) gt_ignore_tags_list.append(0) gt_bbox_batch_list.append(gt_bbox_list) gt_ignore_tags_batch_list.append(gt_ignore_tags_list) return [ pred_bbox_batch_list, [0, 0, gt_bbox_batch_list, gt_ignore_tags_batch_list] ] def get_metric(self): structure_metric = self.structure_metric.get_metric() if self.bbox_metric is None: return structure_metric bbox_metric = self.bbox_metric.get_metric() if self.main_indicator == self.bbox_metric.main_indicator: output = bbox_metric for sub_key in structure_metric: output["structure_metric_{}".format( sub_key)] = structure_metric[sub_key] else: output = structure_metric for sub_key in bbox_metric: output["bbox_metric_{}".format(sub_key)] = bbox_metric[sub_key] return output def reset(self): self.structure_metric.reset() if self.bbox_metric is not None: self.bbox_metric.reset() def format_box(self, box): if self.point_num == 4: x1, y1, x2, y2 = box box = [[x1, y1], [x2, y1], [x2, y2], [x1, y2]] elif self.point_num == 8: x1, y1, x2, y2, x3, y3, x4, y4 = box box = [[x1, y1], [x2, y2], [x3, y3], [x4, y4]] return box