Software pro adaptabilní rozpoznávání textu starých tisků

Adaptive OCR for older printed documents

software

In order to use the result by another entity, it is always necessary to acquire a license

The licensor does not require a license fee for the result

Hradiš Michal, Ing., Ph.D. (DCGM)
Kišš Martin, Ing. (DCGM)
Kodym Oldřich, Ing., Ph.D.
Kohút Jan, Ing. (DCGM)
Beneš Karel, Ing. (DCGM)
Buchal Petr, Ing.

OCR, printed documents, page layout analysis, text recognition, language model, Python

This Python package implements the entire OCR pipeline, including page layout analysis, text line detection, text recognition, and text decoding using a language model. The software is focused on processing of low-quality documents (for example documents digitized from microfilms). The package provides a command-line tool and a class that can be integrated into your own software.

https://github.com/DCGM/pero-ocr, pip https://pypi.org/project/pero-ocr/

BSD 3-Clause License

Copyright (c) 2019, DCGM
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
   contributors may be used to endorse or promote products derived from
   this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Advanced content extraction and recognition for printed and handwritten documents for better accessibility and usability, MK, Program na podporu aplikovaného výzkumu a experimentálního vývoje národní a kulturní identity na léta 2016 až 2022 (NAKI II), DG18P02OVV055, 2018-2022, running
Moderní metody zpracování, analýzy a zobrazování multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-20-6460, 2020-2023, completed

Computer Graphics Research Group (RG GRAPH)

Department of Computer Graphics and Multimedia (DCGM)