DT-LSD: Deformable Transformer-based Line Segment Detection

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

TODO

• Training
• Evaluation
• Upload source code
• Upload weight
• Inference
• 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

Dataset	sAP10	sAP15	APH	FH	FPS
Wireframe	71.7	73.9	89.1	85.8	8.9
YorkUrban	33.2	35.1	65.9	68.0	8.9

Installation

1. Clone this repository.

   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/.

   # an example:
   conda install -c pytorch pytorch torchvision
   

3. Install other needed packages

   pip install -r requirements.txt
   

4. Compiling CUDA operators

   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 

2. 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}
}