https://github.com/colmap/colmap
COLMAP - Structure-from-Motion and Multi-View Stereo
https://github.com/colmap/colmap
computer-vision geometry multi-view-stereo reconstruction structure-from-motion
Last synced: 8 months ago
JSON representation
COLMAP - Structure-from-Motion and Multi-View Stereo
- Host: GitHub
- URL: https://github.com/colmap/colmap
- Owner: colmap
- License: other
- Created: 2014-08-16T00:55:31.000Z (over 11 years ago)
- Default Branch: main
- Last Pushed: 2025-05-09T20:39:52.000Z (8 months ago)
- Last Synced: 2025-05-12T02:43:21.718Z (8 months ago)
- Topics: computer-vision, geometry, multi-view-stereo, reconstruction, structure-from-motion
- Language: C++
- Homepage: https://colmap.github.io/
- Size: 69 MB
- Stars: 8,595
- Watchers: 177
- Forks: 1,619
- Open Issues: 1,023
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- Contributing: CONTRIBUTING.md
- License: COPYING.txt
Awesome Lists containing this project
- awesome-self-driving - COLMAP
- awesome-mvs - Colmap - View Stereo](https://demuc.de/papers/schoenberger2016mvs.pdf). J. L. Schönberger, E. Zheng, M. Pollefeys, J.-M. Frahm. ECCV 2016. (Paper / Multi-View Stereo)
- AiTreasureBox - colmap/colmap - 11-03_10173_2](https://img.shields.io/github/stars/colmap/colmap.svg)|COLMAP - Structure-from-Motion and Multi-View Stereo| (Repos)
- awesome-3D-vision - Colmap - clause license - Permissive | (SFM / Project&code)
- awesome_3DReconstruction_list - Colmap - clause license - Permissive | (OpenSource SfM (Structure from Motion) / UAV Trajectory Optimization for model completeness)
- StarryDivineSky - colmap/colmap - from-Motion, SfM)和多视角立体视觉(Multi-View Stereo, MVS)技术从图像中生成三维模型。该项目基于C++开发,部分功能通过Python脚本实现,支持多种图像格式(如JPEG、PNG等),可自动完成相机标定、特征提取与匹配、稀疏重建以及密集点云生成等流程。其核心功能包括:1)通过SIFT或SuperPoint等算法提取图像特征并进行匹配;2)利用鲁棒的SfM算法构建相机姿态和稀疏三维点云;3)采用基于块的MVS方法生成密集点云和纹理映射的网格模型。COLMAP的工作原理依赖于多视角图像的几何约束和深度估计,适用于从单张图像到复杂场景的三维重建任务。项目提供命令行接口,包含完整的文档(位于docs目录)和示例数据(位于examples目录),支持Linux、macOS和Windows系统。其特点包括高精度重建、支持大规模数据集处理、模块化设计便于扩展,以及通过可视化工具(如COLMAP Viewer)实时查看重建结果。项目采用BSD-3-Clause开源协议,适合科研和教育用途,但不保证商业可用性。用户可通过GitHub获取源码和详细使用指南,适合需要从图像序列生成三维模型的研究者或开发者。 (3D视觉生成重建 / 资源传输下载)
README
COLMAP
======
About
-----
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo
(MVS) pipeline with a graphical and command-line interface. It offers a wide
range of features for reconstruction of ordered and unordered image collections.
The software is licensed under the new BSD license. If you use this project for
your research, please cite:
@inproceedings{schoenberger2016sfm,
author={Sch\"{o}nberger, Johannes Lutz and Frahm, Jan-Michael},
title={Structure-from-Motion Revisited},
booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2016},
}
@inproceedings{schoenberger2016mvs,
author={Sch\"{o}nberger, Johannes Lutz and Zheng, Enliang and Pollefeys, Marc and Frahm, Jan-Michael},
title={Pixelwise View Selection for Unstructured Multi-View Stereo},
booktitle={European Conference on Computer Vision (ECCV)},
year={2016},
}
If you use the image retrieval / vocabulary tree engine, please also cite:
@inproceedings{schoenberger2016vote,
author={Sch\"{o}nberger, Johannes Lutz and Price, True and Sattler, Torsten and Frahm, Jan-Michael and Pollefeys, Marc},
title={A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval},
booktitle={Asian Conference on Computer Vision (ACCV)},
year={2016},
}
The latest source code is available at https://github.com/colmap/colmap. COLMAP
builds on top of existing works and when using specific algorithms within
COLMAP, please also cite the original authors, as specified in the source code,
and consider citing relevant third-party dependencies (most notably
ceres-solver, poselib, sift-gpu, vlfeat).
Download
--------
* Binaries for **Windows** and other resources can be downloaded
from https://github.com/colmap/colmap/releases.
* Binaries for **Linux/Unix/BSD** are available at
https://repology.org/metapackage/colmap/versions.
* Pre-built **Docker** images are available at
https://hub.docker.com/r/colmap/colmap.
* **Python bindings** are available at https://pypi.org/project/pycolmap.
* To **build from source**, please see https://colmap.github.io/install.html.
Getting Started
---------------
1. Download pre-built binaries or build from source.
2. Download one of the provided datasets at https://demuc.de/colmap/datasets/
or use your own images.
3. Use the **automatic reconstruction** to easily build models
with a single click or command.
Documentation
-------------
The documentation is available at https://colmap.github.io/.
Support
-------
Please, use GitHub Discussions at https://github.com/colmap/colmap/discussions
for questions and the GitHub issue tracker at https://github.com/colmap/colmap
for bug reports, feature requests/additions, etc.
Acknowledgments
---------------
COLMAP was originally written by [Johannes Schönberger](https://demuc.de/) with
funding provided by his PhD advisors Jan-Michael Frahm and Marc Pollefeys.
The team of core project maintainers currently includes
[Johannes Schönberger](https://github.com/ahojnnes),
[Paul-Edouard Sarlin](https://github.com/sarlinpe), and
[Shaohui Liu](https://github.com/B1ueber2y).
The Python bindings in PyCOLMAP were originally added by
[Mihai Dusmanu](https://github.com/mihaidusmanu),
[Philipp Lindenberger](https://github.com/Phil26AT), and
[Paul-Edouard Sarlin](https://github.com/sarlinpe).
The project has also benefitted from countless community contributions, including
bug fixes, improvements, new features, third-party tooling, and community
support (special credits to [Torsten Sattler](https://tsattler.github.io)).
Contribution
------------
Contributions (bug reports, bug fixes, improvements, etc.) are very welcome and
should be submitted in the form of new issues and/or pull requests on GitHub.
License
-------
The COLMAP library is licensed under the new BSD license. Note that this text
refers only to the license for COLMAP itself, independent of its thirdparty
dependencies, which are separately licensed. Building COLMAP with these
dependencies may affect the resulting COLMAP license.
Copyright (c), ETH Zurich and UNC Chapel Hill.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
its contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.