cnspy-spatial-csv-formats 0.1.1

Spatial formats for CSV files.

cnspy_spatial_csv_formats Package

This package holds header and format definitions for CSV-files that hold timestamped 3D spatial information. By spatial

• 3-DoF relative position (),
• 3-DoF attitude (orientation represented by quaternions),
• 6-DoF pose (position + attitude)
• 6-DoF pose with uncertainty.

File headers are in the first line of a CSV file starting with a #, followed by a sequence of unique comma separated strings/chars.

It is highly recommended to load the CSV files into a pandas.DataFrame. For convenience, there is a package called cnspy_csv2dataframe that does the conversion using the CSVFormatPose definitions.

Note

The CSVFormatPose.TUM format, got it's name for file format used in the TUM RGB-D benchmark tool. Noticeable, is that the order of quaternion is non-alphabetically ([q_x,q_y,q_z, q_w] instead of [q_w, q_x, q_y, q_z]), meaning that first comes the imaginary part, then the real part, but this is just a matter of taste and definition! To be backward compatible with older/other tools (TUM RGB-D benchmark tool, rpg_trajectory_evaluation, etc.), we follow this non-alphabetically order!

Installation

Install the current code base from GitHub and pip install a link to that cloned copy

git clone https://github.com/aau-cns/spatial_csv_formats.git
cd spatial_csv_formats
pip install -e .

Dependencies

It is part of the cnspy eco-system of the cns-github group.

• enum

License

Software License Agreement (GNU GPLv3 License), refer to the LICENSE file.

Sharing is caring! - Roland Jung