Metadata-Version: 2.1
Name: PyTrack-lib
Version: 2.0.0
Summary: a Map-Matching-based Python Toolbox for Vehicle Trajectory Reconstruction
Home-page: https://github.com/cosbidev/PyTrack
Author: Matteo Tortora
Author-email: m.tortora@unicampus.it
License: BSD-3-Clause-Clear
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Description-Content-Type: text/markdown
License-File: LICENSE

<h1 align="center">
<img src="https://raw.githubusercontent.com/cosbidev/PyTrack/main/logo/pytracklogo.svg" width="300">
</h1><br>

-----------------

# PyTrack: a Map-Matching-based Python Toolbox for Vehicle Trajectory Reconstruction
[![All platforms](https://dev.azure.com/conda-forge/feedstock-builds/_apis/build/status/pytrack-feedstock?branchName=main)](https://dev.azure.com/conda-forge/feedstock-builds/_build/latest?definitionId=16366&branchName=main)
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## What is it?
**PyTrack** is a Python package that integrate the recorded GPS coordinates with data provided by the open-source OpenStreetMap (OSM). 
PyTrack can serve the intelligent transport research, e.g. to reconstruct the video of a vehicle’s route by exploiting available data and without equipping it with camera sensors, to update the urban road network, and so on.

## Main Features
The following are the main features that PyTrack includes:
- Generation of the street network graph using geospatial data from OpenStreetMap
- Map-matching
- Data cleaning
- Video reconstruction of the GPS route
- Visualisation and analysis capabilities

## Getting Started
### Installation
The source code is currently hosted on GitHub at:
https://github.com/cosbidev/PyTrack.
PyTrack can be installed using*:
```sh
# conda
conda install pytrack 
```

```sh
# or PyPI
pip install PyTrack-lib
```
**for Mac m1 users, it is recommended to use conda in order to be able to install all dependencies.*
## Documentation
Checkout the official [documentation](https://pytrack-lib.readthedocs.io/en/latest).
The official documentation is currently under construction.
Besides, [here](https://github.com/cosbidev/PyTrack/tree/main/examples) you can see some examples of the application of the library.
## Contributing to PyTrack
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.

## Author
Created by [Matteo Tortora](https://mtortora-ai.github.io) - feel free to contact me!

<!---
## Citation

If you use PyTrack in your work, please cite the [journal paper]().
```bibtex

```
-->

## License
PyTrack is distributed under a [BSD-3-Clause-Clear Licence]().
