This repository provides minimal Python bindings for the Ceres Solver and the implementation of factor graphs for bundle adjustment and pose graph optimization.
- Clone the repository and its submodule by running:
git clone --recursive [email protected]:cvg/pyceres.git cd pyceres
Build the package:
pip install -e .
Factor graph optimization
For now we support the following cost functions, defined in
- camera reprojection error (with fixed or variable pose)
- rig reprojection error (with fixed or variable rig extrinsics)
- relative pose prior
- absolute pose prior
All factors support basic observation covariances. Reprojection error costs rely on camera models defined in COLMAP. Absolute poses are represented as quaternions and are expressed in the sensor frame, so are pose residuals, which use the right-hand convention as in the GTSAM library.
See the Jupyter notebooks in
- Define a clean interface for covariances, like in GTSAM
- Add bindings for Ceres covariance estimation
- Use proper objects for poses, e.g. from Sophus
- Proper benchmark against GTSAM