sbsa/cu130/: pyceres-2.6 metadata and description

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Factor graph optimization with Ceres, in Python

author_email Paul-Edouard Sarlin <paul.edouard.sarlin@gmail.com>, Philipp Lindenberger <plindenbe@ethz.ch>, Shaohui Liu <b1ueber2y@gmail.com>
classifiers
  • License :: OSI Approved :: Apache Software License
  • Programming Language :: Python :: 3 :: Only
description_content_type text/markdown
license Apache-2.0
project_urls
  • Repository, https://github.com/cvg/pyceres
requires_dist
  • numpy
requires_python >=3.9

Because this project isn't in the mirror_whitelist, no releases from root/pypi are included.

File Tox results History
pyceres-2.6-cp312-cp312-linux_aarch64.whl
Size
436 KB
Type
Python Wheel
Python
3.12
  • Replaced 2 time(s)
  • Uploaded to sbsa/cu130 by sbsa 2025-09-02 09:00:20

pyceres

This repository provides minimal Python bindings for the Ceres Solver and the implementation of factor graphs for bundle adjustment and pose graph optimization.

Installation

Wheels for Python 9/10/11/12/13/14 on Linux, macOS 10+ (both Intel and Apple Silicon), and Windows can be installed using pip:

pip install pyceres

To build from source, follow the following steps:

  1. Install the Ceres Solver following the official instructions.
  2. Clone the repository and build the package:
git clone https://github.com/cvg/pyceres.git
cd pyceres
python -m pip install .

Alternatively, you can build the Docker image:

docker build -t pyceres -f Dockerfile .

Factor graph optimization

Factors may be defined in Python (see examples/test_python_cost.py) or in C++ with associated Python bindings. PyCOLMAP provides the following cost functions in pycolmap.cost_functions:

See examples/ to use these factors.

Credits

Pyceres was inspired by the work of Nikolaus Mitchell for ceres_python_bindings and is maintained by Philipp Lindenberger, Paul-Edouard Sarlin, and Shaohui Liu.