# layoutparser-ort

A simplified port of [LayoutParser](https://github.com/Layout-Parser/layout-parser) for detecting layout elements on documents. Runs Detectron2 and YOLOX layout models from [unstructured-inference](https://github.com/Unstructured-IO/unstructured-inference/) in ONNX format through onnxruntime (bindings via [ort](https://github.com/pykeio/ort)). [Check out the examples for a quick start!](examples/)

## License

`layoutparser-ort` mirrors its API from [LayoutParser](https://github.com/Layout-Parser/layout-parser) and includes preprocessing code derived from [unstructured-inference](https://github.com/Unstructured-IO/unstructured-inference/), both licensed under the Apache License 2.0. Likewise, `layoutparser-ort` is licensed under the Apache License 2.0.

## Appendix: Similar libraries
- [surya](https://github.com/VikParuchuri/surya): OCR, layout analysis, reading order, line detection in 90+ languages
    - SegFormer (transformers: SegFormer), Donut (transformers: Donut), CRAFT (pytorch)
    - License: GPLv3.0 (code), cc-by-nc-sa-4.0 (models)
        - cc-by-nc-sa-4.0: noncommerical but author "waive[s] that for any organization under $5M USD in gross revenue in the most recent 12-month period."
- [unstructured-inference](https://github.com/Unstructured-IO/unstructured-inference/): hosted model inference code for layout parsing models
    - Models: Detectron2 (LayoutParser-PubLayNet-PyTorch, LayoutParser-PubLayNet-ONNX), YOLOX (probably trained on DocLayNet, Quantized, ONNX), Table-Transformer (transformers: Table Transformer), Donut (transformers: Donut)
    - License: Apache 2.0
- [LayoutParser](https://github.com/Layout-Parser/layout-parser): A Unified Toolkit for Deep Learning Based Document Image Analysis 
    - Models: Detectron2
    - License: Apache 2.0
    - Documentation: https://layout-parser.readthedocs.io/en/latest/api_doc/elements.html