evo is a free, open source monitoring & observability project written in Python and released under GPL-3.0. It has 4,316 GitHub stars, 797 forks and 7 open issues, and was last pushed 10 days ago. On this registry it ranks #101 of 191 tracked projects in Monitoring & Observability, with 5 head-to-head comparisons available.

evo

Python package for the evaluation of odometry and SLAM

Linux / macOS / Windows / ROS / ROS2
CI

This package provides executables and a small library for handling, evaluating and comparing the trajectory output of odometry and SLAM algorithms.

Supported trajectory formats:

  • 'TUM' trajectory files
  • 'KITTI' pose files
  • 'EuRoC MAV' (.csv groundtruth and TUM trajectory file)
  • ROS and ROS2 bagfile with geometry_msgs/PoseStamped, geometry_msgs/TransformStamped, geometry_msgs/PoseWithCovarianceStamped, geometry_msgs/PointStamped or nav_msgs/Odometry topics or TF messages

See here for more infos about the formats.

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Why?

evo has several advantages over other public benchmarking tools:

  • common tools for different formats
  • algorithmic options for association, alignment, scale adjustment for monocular SLAM etc.
  • flexible options for output, plotting, visualization or export (e.g. LaTeX plots or Excel tables)
  • a powerful, configurable CLI that can cover many use cases
  • modular core and tools libraries for custom extensions
  • faster than other established Python-based tools (see here)

What it's not: a 1-to-1 re-implementation of a particular evaluation protocol tailored to a specific dataset.


Installation / Upgrade

Installation is easy-peasy if you're familiar with this: https://xkcd.com/1987/#

The latest version of evo supports Python 3.10+.

Please use pip only in a proper environment (e.g. uv/uvx, pipx, venv, Pixi or a classic virtual environment).

⚠️ ☠️☠️☠️ ⚠️

Whatever you do, don't use: pip install --user / anything with --break-system-packages / or worst: sudo pip install

From PyPi

If you just want to use the executables of the latest release version, the easiest way is to run:

pip install evo

This will download the package and its dependencies from PyPI and install or upgrade them. If you want, you can subscribe to new releases via https://libraries.io/pypi/evo.

To upgrade to a newer version: pip install --upgrade evo

From Source

Run this in the repository's base folder:

pip install --editable .

Pixi

Pixi is an easy-to-use alternative if you want to have an isolated development environment. Run pixi add evo if you have an existing environment, or clone this repository and run pixi shell to open a dev shell.

Tab completion

Tab completion is supported via the argcomplete package. Run activate-global-python-argcomplete after the installation to use it.

Dependencies

Python packages

evo has some required dependencies that are automatically resolved during installation with pip. See the pyproject.toml file for all details.

PyQt6 (optional)

PyQt6 will give you the enhanced GUI for plot figures from the "qtagg" matplotlib backend (otherwise: "TkAgg"). If PyQt6 is already installed when installing this package, it will be used as a default (see evo_config show). To change the plot backend afterwards, run evo_config set plot_backend qtagg.

If you run into issues with installing tkinter, trying PyQt6 is a good idea.

ROS (optional)

Some ROS-related features require a ROS installation, see here. We are testing this package with ROS Lyrical.

Reading ROS bag files works also without a ROS installation thanks to the great rosbags package that is installed together with evo. This allows you also to read ROS 1 & 2 bags even if you don't have one of those ROS distros installed. (except for reading /tf topics, because there we need the buffer implementation from ROS)

contextily (optional)

contextily is required for adding map tiles to plots of geo-referenced data.

Rerun (optional)

You can send data also to the rerun viewer. Just pip install rerun-sdk and add --rerun to your command. See the related Wiki page for more details.

evo evo

Command Line Interface

After installation with pip, the following executables can be called globally from your command-line:

Metrics:

  • evo_ape - absolute pose error
  • evo_rpe - relative pose error

Tools:

  • evo_traj - tool for analyzing, plotting or exporting one or more trajectories
  • evo_res - tool for comparing one or multiple result files from evo_ape or evo_rpe
  • evo_config - tool for global settings and config file manipulation

Call the commands with --help to see the options, e.g. evo_ape --help. Tab-completion of command line parameters is available on UNIX-like systems.

More documentation Check out the Wiki on GitHub.


Example Workflow

There are some example trajectories in the source folder in test/data.

1.) Plot multiple trajectories

Here, we plot two KITTI pose files and the ground truth using evo_traj:

cd test/data
evo_traj kitti KITTI_00_ORB.txt KITTI_00_SPTAM.txt --ref=KITTI_00_gt.txt -p --plot_mode=xz
evo evo

2.) Run a metric on trajectories

For example, here we calculate the absolute pose error for two trajectories from ORB-SLAM and S-PTAM using evo_ape (KITTI_00_gt.txt is the reference (ground truth)) and plot and save the individual results to .zip files for evo_res:

First trajectory (ORB Stereo):

mkdir results
evo_ape kitti KITTI_00_gt.txt KITTI_00_ORB.txt -va --plot --plot_mode xz --save_results results/ORB.zip
evo evo

Second trajectory (S-PTAM):

evo_ape kitti KITTI_00_gt.txt KITTI_00_S

readme truncated — read the full docs on github

Frequently asked questions

Is evo free to use?

evo is open source under the GPL-3.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does evo do?

Python package for the evaluation of odometry and SLAM

What is evo written in?

evo is primarily written in Python. Its source is publicly available at https://github.com/MichaelGrupp/evo, and it has 4,316 GitHub stars.