PaddleOCR MCP Server

# 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