evo

Python package for the evaluation of odometry and SLAM

This packages 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 bagfile with geometry_msgs/PoseStamped topics

See here for more infos about the formats.

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, plot 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

Python 3.4+ and Python 2.7 are both supported. If you want to use the ROS bagfile interface, first check which Python version is used by your ROS installation and install accordingly. You might also want to use a virtual environment.

From PyPi

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

pip install evo --upgrade --no-binary evo

This will download the package and its dependencies from PyPi and install them. Depending on your OS, you might be able to use pip2 or pip3 to specify the Python version you want. Tab completion for Bash terminals is supported via the argcomplete package on most UNIX systems - open a new shell after the installation to use it.

From Source

Run this in the repository's base folder:

pip install . --upgrade

Dependencies

Python packages

evo has the following dependencies that are automatically resolved during installation:

numpy, matplotlib, scipy, pandas, seaborn, natsort, argcomplete, colorama, pygments, enum34 (only Python 2.7)

PyQt4 (optional)

It is optional but recommended to install PyQt4 before installation, which will give you the enhanced editing tools for plot figures from the "Qt4Agg" matplotlib backend (otherwise: "TkAgg"). If PyQt4 is already installed when installing this package, it will be used as a default. To change the plot backend afterwards, run evo_config set plot_backend Qt4Agg.

ROS (optional)

To load or export ROS bag files, you need to install ROS - see here. We tested this package with ROS Indigo and Kinetic.

Command Line Interface

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

Metrics:

evo_ape - absolute pose error
evo_rpe - relative pose error
evo_rpe-for-each - sub-sequence-wise averaged 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_fig - (experimental) tool for re-opening serialized plots (saved with --serialize_plot)
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.

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

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 --save_results results/ORB.zip

Second trajectory (S-PTAM):

evo_ape kitti KITTI_00_gt.txt KITTI_00_SPTAM.txt -va --plot --save_results results/SPTAM.zip

Process multiple results from a metric

evo_res can be used to compare multiple result files from the metrics, i.e.:

print infos and statistics (default)
plot the results
save the statistics in a table

Here, we use the results from above to generate a plot and a table:

evo_res results/*.zip -p --save_table results/table.csv

IPython / Jupyter Resources

For an interactive source code documentation, open the Jupyter notebook metrics_tutorial.ipynb in the notebooks folder of the repository. More infos on Jupyter notebooks: see here

If you have IPython installed, you can launch an IPython shell with a custom evo profile with the command evo_ipython.

Trouble

":scream:, this piece of :shit: software doesn't do what I want!!1!1!!"

First aid:

append -h/ --help to your command
check the Wiki
check the previous issues
open a new issue

Jupyter notebook errors

No module named 'evo'

This can be caused if the Kernel version of Jupyter does not match the Python version of the evo installation.

Contributing

Patches are welcome, preferably as pull requests.

License

Free, modifiable open source software as covered by the GNU GPL v3 - see the 'LICENSE' file for full information. If you use this package for your research, a footnote with the link to this repository is appreciated: github.com/MichaelGrupp/evo.

Richard-coder / evo

evo