Metadata-Version: 2.1
Name: cnspy_spatial_csv_formats
Version: 0.1.0
Summary: Spatial formats for CSV files.
Home-page: https://gitlab.aau.at/aau-cns/py3_pkgs/cnspy_spatial_csv_formats/
Author: Roland Jung
Author-email: roland.jung@aau.at
License: UNKNOWN
Project-URL: Bug Tracker, https://gitlab.aau.at/aau-cns/py3_pkgs/cnspy_spatial_csv_formats/issues
Description: # cnspy_spatial_csv_formats Package
        
        This package holds header and format definitions for [CSV-files](https://en.wikipedia.org/wiki/Comma-separated_values) 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](https://pypi.org/project/pandas/). For convenience, there is a package called [cnspy_csv2dataframe](https://gitlab.aau.at/aau-cns/py3_pkgs/cnspy_csv2dataframe) that does the conversion using the [CSVFormatPose](CSVFormatPose.py) definitions.
        
        
        ## Note
        
        The [CSVFormatPose.TUM](CSVFormatPose.py) format, got it's name for file format used in the [TUM RGB-D benchmark tool](https://vision.in.tum.de/data/datasets/rgbd-dataset/tools#evaluation). 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](ttps://vision.in.tum.de/data/datasets/rgbd-dataset/tools#evaluation), [rpg_trajectory_evaluation](https://github.com/uzh-rpg/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://gitlab.aau.at/aau-cns/py3_pkgs/spatial_csv_formats.git
        cd spatial_csv_formats
        pip install -e .
        ```
        
        
        ## Dependencies
        
        * [enum]()
        
        
        ## License
        
        
        Software License Agreement (GNU GPLv3  License), refer to the LICENSE file.
        
        *Sharing is caring!* - [Roland Jung](https://github.com/jungr-ait)
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
