PaddleOCR/ppocr/data/imaug/vqa/token/vqa_re_convert.py

52 lines
2.0 KiB
Python

# copyright (c) 2022 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
class TensorizeEntitiesRelations(object):
def __init__(self, max_seq_len=512, infer_mode=False, **kwargs):
self.max_seq_len = max_seq_len
self.infer_mode = infer_mode
def __call__(self, data):
entities = data['entities']
relations = data['relations']
entities_new = np.full(
shape=[self.max_seq_len + 1, 3], fill_value=-1, dtype='int64')
entities_new[0, 0] = len(entities['start'])
entities_new[0, 1] = len(entities['end'])
entities_new[0, 2] = len(entities['label'])
entities_new[1:len(entities['start']) + 1, 0] = np.array(entities[
'start'])
entities_new[1:len(entities['end']) + 1, 1] = np.array(entities['end'])
entities_new[1:len(entities['label']) + 1, 2] = np.array(entities[
'label'])
relations_new = np.full(
shape=[self.max_seq_len * self.max_seq_len + 1, 2],
fill_value=-1,
dtype='int64')
relations_new[0, 0] = len(relations['head'])
relations_new[0, 1] = len(relations['tail'])
relations_new[1:len(relations['head']) + 1, 0] = np.array(relations[
'head'])
relations_new[1:len(relations['tail']) + 1, 1] = np.array(relations[
'tail'])
data['entities'] = entities_new
data['relations'] = relations_new
return data