DT-LSD: Deformable Transformer-based Line Segment Detection

This repository contains the official implementation for DT-LSD (Deformable Transformer-based Line Segment Detector)

TODO

• [x] Training
• [x] Evaluation
• [x] Upload source code
• [x] Upload weight
• [x] Inference
• [x] Upload arxiv paper

🚀 Updates

• We have released a new model called LINEA.
• LINEA presents a new attention mechanism called line attention.
• LINEA has four model sizes: n, s, and l.
• Try LINEA hugging face space

Results

Installation

1. Clone this repository. sh git clone https://github.com/SebastianJanampa/DTLSD.git cd DTLSD

2. Install Pytorch and torchvision

Follow the instructions on https://pytorch.org/get-started/locally/. sh # an example: conda install -c pytorch pytorch torchvision

1. Install other needed packages sh pip install -r requirements.txt

2. Compiling CUDA operators sh cd models/dtlsd/ops python setup.py build install # unit test (should see all checking is True) python test.py cd ../../..

Dataset

To reproduce our results, you need to process two datasets, ShanghaiTech and YorkUrban.

mkdir data
cd data
wget https://github.com/SebastianJanampa/storage/releases/download/v1.0.0/wireframe_processed.zip
wget https://github.com/SebastianJanampa/storage/releases/download/v1.0.0/york_processed.zip

unzip wireframe_processed.zip
unzip york_processed.zip

rm *zip
cd ..

Pretraining weights

Download the weights from DINO_SWIN_4scales_36_epochs from the DINO repo, and place it in the pretrain folder.

Run

1. Training

bash scripts/train/DTLSD_SWIN_4_scales_24_epochs.sh 

1. Testing

bash scripts/train/DTLSD_SWIN_4_scales_24_epochs.sh

Demo

Download the DTLSD weights

wget https://github.com/SebastianJanampa/storage/releases/download/v1.0.0/DTLSD_checkpoint0035.pth

If wget doesn't work, download it from this link, and place it in the main folder. Then run

python demo.py

Citation

@InProceedings{Janampa_2025_WACV,
    author    = {Janampa, Sebastian and Pattichis, Marios},
    title     = {DT-LSD: Deformable Transformer-Based Line Segment Detection},
    booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
    month     = {February},
    year      = {2025},
    pages     = {3477-3486}
}