DeepLSD — weight mirror
Unmodified mirror of the two checkpoints published for DeepLSD (CVPR 2023, Pautrat et al.), a hybrid line segment detector: a network predicts a line distance and angle field, and a modified LSD reads the segments off those predicted fields instead of off the image gradient.
Upstream ships no Hugging Face repo and serves these files from a university web server. This
repo exists so they can be fetched with huggingface_hub and loaded offline afterwards.
Nothing here is retrained, converted or quantised — the files are byte-identical to the
upstream artefacts listed below. (They are torch.save archives despite the .tar extension,
which is upstream's naming.)
Contents
| File | Bytes | SHA-256 |
|---|---|---|
deeplsd_md.tar |
102,898,193 | 56e9bae263977caa289ae49802987a67d4f00f376ae7e542176c8ae0a6cc2083 |
deeplsd_wireframe.tar |
102,898,321 | 6d0c1bc78f79eb9e564404e4fef797d12ab18f30ba596208cca16116c2429406 |
Which one to use
| File | Trained on / suited to |
|---|---|
deeplsd_md.tar |
Trained on MegaDepth. The generic checkpoint: outdoor scenes and harder images (night, fog, blur). Upstream's own demo default. |
deeplsd_wireframe.tar |
Trained on the Wireframe dataset. Clean man-made scenes -- documents, floorplans, CAD exports, indoor rooms. |
Provenance
| File | Upstream source |
|---|---|
deeplsd_md.tar |
https://cvg-data.inf.ethz.ch/DeepLSD/deeplsd_md.tar |
deeplsd_wireframe.tar |
https://cvg-data.inf.ethz.ch/DeepLSD/deeplsd_wireframe.tar |
Each file was verified before upload by loading it into DeepLSD's own network and requiring an
exact fit — zero missing and zero unexpected state_dict keys.
Usage
import torch
from huggingface_hub import hf_hub_download
# DeepLSD ships no pip package; see the upstream repo for the model definition.
from deeplsd.models.deeplsd_inference import DeepLSD
path = hf_hub_download("xboix/deeplsd", "deeplsd_md.tar")
net = DeepLSD({"detect_lines": True})
net.load_state_dict(torch.load(path, map_location="cpu")["model"])
net = net.eval()
Citation
@InProceedings{pautrat_suarez_2023_deeplsd,
title={DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients},
author={Pautrat, R{\'e}mi and Barath, Daniel and Larsson, Viktor and Oswald, Martin R. and Pollefeys, Marc},
booktitle={Computer Vision and Pattern Recognition (CVPR)},
year={2023},
}