📓SFDLA DLAdapter

Source-Free Document Layout Analysis

Installation

You can Clone this Git.

In the subfolder 'Docker Environment' there is a Dockerfile that installs the corresponding runtime environment. Ubuntu 18.04 with Anaconda, Cuda 10.2, Python 3.6, Pytorch 1.9 and detectron2 was used. A corresponding Docker Compose file is included.

The Dockerfile can be built like this, for example:

• sudo docker build -t dla_sfda_basic <path_to_dockerfile>

We use 4 NVIDIA GeForce GTX 1080 Ti.

Dataset Preparation

Download the dataset from public sources

• PubLayNet
• DocLayNet
• M⁶Doc

You can create the benchmark datasets with the Python Files in /datasets. Adapt your path variables

Source Models

The source models can be found here: Source Model

Models after Source Free Domain Adaption

The models can be found here: Source-Free Adapted Model

Model Inference

You can use the run_inference_with_evaluation function in /dla-sfda/simple_inference.py. You have to change the Parameter depending on your System.

results = run_inference_with_evaluation(
    dataset_name="name_of_dataset",
    annotation_json_path="/path/to/annotation/file.json",
    image_root_dln_path="/path/to/PNG/",
    repo_source_root="/path/to/Folder/with/dla-sfda/",
    model_config_yaml="dla-sfda/configs/your_detectron_model_config.yaml",
    model_path="/path/to/model/model.pth"
)

A file with the result can be found here: /log_results_source_and_adapted_models.txt

Train the Source Models

You can run /dla-sfda/train_source.py Choose the name parameter in the name function.

For that you have to adapt the paths in /dla-sfda/configs/SourceModelConfig.py and your corresponding config yaml.

Train Source-Free Domain Adaption

You can run /dla-sfda/train_sfdla.py Choose the name parameter in the name function.

For that you have to adapt the paths in /dla-sfda/configs/SFDA_DLA_Configuration_Loader.py and your corresponding config yaml. Further hyperparameters can be controlled in /dla-sfda/train_sfdla.py main function.

🌳 Citation

If you find this code useful for your research, please consider citing:

@misc{tewes2025sfdlasourcefreedocumentlayout,
      title={SFDLA: Source-Free Document Layout Analysis}, 
      author={Sebastian Tewes and Yufan Chen and Omar Moured and Jiaming Zhang and Rainer Stiefelhagen},
      year={2025},
      eprint={2503.18742},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2503.18742}, 
}