points-lsd
Point-seeded LSD (Line Segment Detector) bindings used by UPAL (Unified and Efficient Point-Line Local Features, ECCV 2026).
This is a fork of pytlsd by Iago Suárez, itself a
pybind11 wrapper around the original C implementation of LSD by Rafael Grompone von Gioi.
On top of the upstream bindings it adds lsd_from_points, which grows LSD regions only from a
set of seed pixels (e.g. learned keypoints) instead of scanning the full image, and accepts
externally computed gradients so that a learned line field can steer the detector.
Install
Prebuilt wheels are published for Linux (x86_64, aarch64), macOS (arm64, x86_64) and Windows (AMD64), CPython 3.10–3.14:
pip install points-lsd
Building from source needs a C++17 compiler and CMake ≥ 3.15 (no other native dependencies):
git clone --recursive https://github.com/francois141/points_lsd.git
pip install ./points_lsd
Usage
lsd_from_points needs the image, integer (x, y) seed pixels, and gradient norm/angle maps.
The maps are float64 arrays of the image's shape with undefined pixels set to -1024.0; the
snippet below computes them the way LSD does (2x2 finite differences), but any gradient, such
as one derived from a learned line distance field, can be supplied.
import numpy as np
import points_lsd
gray = ... # H x W float64 (or uint8) image
seeds = np.array([[x0, y0], [x1, y1]], dtype=np.int32) # (x, y) pixel seeds inside the image
def lsd_gradients(img, not_defined=-1024.0, threshold=5.2262518595055063):
norm = np.full(img.shape, not_defined)
angle = np.full(img.shape, not_defined)
a, b, c, d = img[:-1, :-1], img[:-1, 1:], img[1:, :-1], img[1:, 1:]
gx, gy = b + d - a - c, c + d - a - b
norm[:-1, :-1] = 0.5 * np.hypot(gx, gy)
angle[:-1, :-1] = np.arctan2(gx, -gy)
angle[norm <= threshold] = not_defined
return norm, angle
gradnorm, gradangle = lsd_gradients(gray.astype(np.float64))
# N x 5 float32 array: [x1, y1, x2, y2, p] per segment, where p is LSD's angle precision.
segments = points_lsd.lsd_from_points(gray, seeds, 1.0, 0.6, 0.0, gradnorm, gradangle)
# The upstream full-image detector is still available (gradients optional there).
segments = points_lsd.lsd(gray)
Seeds outside the image, seed arrays that are not N x 2, or missing gradient maps raise
ValueError / TypeError. Region growing starts only from seeds whose gradient angle is
defined, so seeds should lie on (or one pixel before) an intensity edge.
Development
pip install -e ".[test]"
pytest tests # test_smoke.py is numpy-only; test_lsd.py needs the [test] extra
Wheels and publishing
Supported wheels
Built with cibuildwheel (config in pyproject.toml
under [tool.cibuildwheel]) for CPython 3.10, 3.11, 3.12, 3.13 and 3.14:
| Platform | Architectures | Wheel tag |
|---|---|---|
| Linux (glibc ≥ 2.24) | x86_64, aarch64 | manylinux_2_24_*.manylinux_2_28_* |
| macOS | arm64 (≥ 11.0), x86_64 (≥ 10.9–10.15, per Python build) | macosx_* |
| Windows | AMD64 | win_amd64 |
That is 25 wheels plus an sdist per release. Not built: musllinux (Alpine), PyPy, free-threaded CPython and 32-bit platforms. On a compatible platform, pip can build from the sdist with a C++17 compiler and CMake ≥ 3.15. The extension has no required external native libraries. OpenMP support and the OpenCV-dependent C++ tests are opt-in and disabled for wheels.
How a release works
.github/workflows/wheels.yml runs on every push to main, every pull request, every
v* tag, and on manual dispatch. Every run builds all wheels and the sdist, smoke-tests
the wheels in clean environments where the runner can execute them (macOS x86_64 is
skipped on the arm64 runner), and runs the full test suite on Linux, macOS and Windows.
What happens with the artifacts depends on the trigger:
| Trigger | Publishes to |
|---|---|
push to main / pull request |
nothing (build + test only) |
| manual run (Actions → Wheels → Run workflow) with Upload to TestPyPI ticked | TestPyPI |
push of a tag vX.Y.Z |
PyPI |
Uploads use PyPI trusted publishing (OIDC),
so no API tokens are stored. Before the first upload to an index, configure that index to
trust this repository's wheels.yml workflow and its corresponding pypi or testpypi
GitHub environment.
The version comes from pyproject.toml, not from git. The tag only triggers the
upload, and the check_version job refuses a tag that does not match
project.version (tag v0.1.0 ↔ version = "0.1.0"). A version can be uploaded to an
index more than once only with new distribution filenames. Existing files cannot be
overwritten, so replacing published artifacts requires a new version number.
Release checklist:
# 1. update project.version in pyproject.toml and land it on main
git add pyproject.toml
git commit -m "release: 0.2.0"
git push origin main # CI must be green
# 2. optional dry run: Actions > Wheels > Run workflow > "Upload to TestPyPI", then
pip install -i https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple "points-lsd==0.2.0"
# 3. publish
git tag v0.2.0
git push origin v0.2.0 # publish_pypi job uploads to PyPI
Building wheels locally
pipx run cibuildwheel --platform linux # needs Docker; native arch, or set CIBW_ARCHS_LINUX
pipx run cibuildwheel --platform macos # needs the python.org CPython installers
CIBW_BUILD="cp313-*" pipx run cibuildwheel --platform linux # one interpreter only
cibuildwheel's Windows build must run on Windows (or in CI). A plain pip wheel . builds
a single wheel for the current interpreter without cibuildwheel's portability repair and
compatibility checks.
License
The binding code and the lsd_from_points extension retain the MIT license of upstream
pytlsd (see LICENSE), while pybind11 is BSD-3-Clause. The bundled core detector
src/lsd.cpp is © Rafael Grompone von Gioi and licensed under the GNU Affero General
Public License v3 or later (see
LICENSES/AGPL-3.0-or-later.txt); it is linked statically,
so the distributed wheels as a whole are subject to the AGPL terms.
1 maintainer
Metadata
1 maintainer
Release files for points-lsd 0.1.0
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Total release size: 4.4 MB
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