License

MIT License

Copyright (c) 2024 Margot Belot

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Third-Party Licenses

This project incorporates several open-source libraries and tools, each with their own licenses:

Core Dependencies

TensorFlow

Apache License 2.0 https://github.com/tensorflow/tensorflow/blob/master/LICENSE

PyTorch

BSD-3-Clause License https://github.com/pytorch/pytorch/blob/master/LICENSE

OpenCV

Apache License 2.0 https://github.com/opencv/opencv/blob/master/LICENSE

NumPy

BSD-3-Clause License https://github.com/numpy/numpy/blob/main/LICENSE.txt

Pandas

BSD-3-Clause License https://github.com/pandas-dev/pandas/blob/main/LICENSE

Matplotlib

PSF-based License https://github.com/matplotlib/matplotlib/blob/main/LICENSE/LICENSE

scikit-learn

BSD-3-Clause License https://github.com/scikit-learn/scikit-learn/blob/main/COPYING

Pillow

HPND License https://github.com/python-pillow/Pillow/blob/main/LICENSE

OCR Dependencies

Tesseract

Apache License 2.0 https://github.com/tesseract-ocr/tesseract/blob/master/LICENSE

pytesseract

Apache License 2.0 https://github.com/madmaze/pytesseract/blob/master/LICENSE

Google Cloud Vision

Apache License 2.0 https://cloud.google.com/terms/

Google GenAI (Gemini)

Apache License 2.0 https://github.com/googleapis/python-genai/blob/main/LICENSE

Web and GUI Dependencies

Flask

BSD-3-Clause License https://github.com/pallets/flask/blob/main/LICENSE.rst

Flask-CORS

MIT License https://github.com/corydolphin/flask-cors/blob/master/LICENSE

Development Dependencies

pytest

MIT License https://github.com/pytest-dev/pytest/blob/main/LICENSE

Black

MIT License https://github.com/psf/black/blob/main/LICENSE

isort

MIT License https://github.com/PyCQA/isort/blob/main/LICENSE

flake8

MIT License https://github.com/PyCQA/flake8/blob/main/LICENSE

Documentation Dependencies

Sphinx

BSD-2-Clause License https://github.com/sphinx-doc/sphinx/blob/master/LICENSE

Read the Docs Sphinx Theme

MIT License https://github.com/readthedocs/sphinx_rtd_theme/blob/master/LICENSE

Models and Training Data

Detection Models

The label detection models included in this project are trained on curated datasets of entomological specimen labels. These models are provided under the same MIT license as the main software.

Classification Models

The label classification models are trained on publicly available datasets and proprietary museum collections. The models themselves are licensed under MIT, but users should respect the terms of the original training data sources.

Usage Terms

Commercial Use

This software is free for commercial use under the MIT license terms. However, please note:

  • Google Cloud Vision and Gemini API usage is subject to Google’s pricing and terms

  • Some training datasets may have restrictions on commercial use

  • Users are responsible for compliance with all applicable laws and regulations

Academic Use

This software is freely available for academic research and educational purposes. If you use this software in academic work, please consider citing:

[Citation information will be provided upon publication]

Attribution

While not required by the MIT license, attribution is appreciated:

  • Include a reference to this project in derivative works

  • Acknowledge the contributors in academic publications

  • Consider contributing improvements back to the project

Disclaimer

This software is provided “as is” without warranty of any kind. The authors make no representations about the suitability of this software for any purpose. Users are responsible for:

  • Validating results for their specific use case

  • Ensuring compliance with applicable regulations

  • Maintaining appropriate data privacy and security

  • Testing thoroughly before production use

The performance of machine learning models may vary depending on:

  • Input image quality

  • Domain-specific characteristics

  • Hardware capabilities

  • Configuration settings

Contact

For licensing questions or commercial inquiries, please contact:

Margot Belot Email: [contact information] GitHub: https://github.com/MargotBelot/entomological-label-information-extraction