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evo

*Python package for the evaluation of odometry and SLAM*

This packages provides executables and a small library for handling and evaluating and 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

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 the dependencies accordingly, if required. 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

This will download the package and its dependencies from PyPi and install them. 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.

Run Executables

After installation with setup.sh, setup.py or from pip, the following console commands 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 systems.

Configurations

Some global settings of the package (see evo_config show) can be changed via evo_config set.

Configuration JSON files can be used to store command line parameters of an experiment and can be passed to the executables via --config/-c - see config_ape.example.json and config_rpe.example.json in the source folder for examples. Use evo_config generate to quickly generate such config files.

Example Workflow

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

  1. *Plot multiple trajectories*

Here, we plot two KITTI pose files and the ground truth using evo_traj: cd evo/test/data evo_traj kitti KITTI_00_ORB.txt KITTI_00_SPTAM.txt --ref=KITTI_00_gt.txt -p --plot_mode=xz

  1. *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 and plot and save the individual results to .zip files:

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

  1. *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

Jupyter Notebooks

For an interactive source code documentation, open the Jupyter notebook metrics_tutorial.ipynb

To install Jupyter, call pip install jupyter or use the --with_jupyter flag for setup.sh.

Local Jupyter notebook access

Go to the evo source folder in a terminal and run: jupyter notebook (starts server and opens browser window with notebook).

Remote Jupyter notebook access

Notebook servers can also be accessed via the browser of a remote PC on the local network without installing Jupyter.

Do once:

  • disable tokens on your server side:
  • jupyter notebook --generate-config
  • go to the generated config file, uncomment and change the c.NotebookApp.token parameter to an empty string
  • TODO: enable password authentication without annoying tokens

Anytime you want to start a server:

  • start the notebook on the server: jupyter notebook --no-browser --port=8888
  • access notebook on remote PC:
  • establish SSH forwarding: ssh username@remotehost -L 8889:localhost:8888
  • this forwards remote 8888 port to local 8889 (numbers are just examples)
  • open the notebook in a browser: localhost:8889

Trouble

Append -h/ --help or --debug to your command.

Warnings from `transformations.py <evo/algorithms/transformations.py>`__:

UserWarning: failed to import module _transformations

Can be ignored, as written here.

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.

*For any other problems, feel free to open an issue on GitHub!*

License

Free, modifiable open source software as covered by the GNU GPL v3 - see the 'LICENSE' file for full information.