This release is a pre-release and may not be stable for production use.
TracksData
A common data structure and basic tools for multi-object tracking.
Features
- Graph-based representation of tracking problems
- In-memory (RustWorkX) and database-backed (SQL) graph backends
- Nodes and edges can take arbitrary attributes
- SQLGraph backend can index frequently queried attributes for faster filtering
- Standardize API for node operators (e.g. defining objects and their attributes)
- Standardize API for edge operators (e.g. creating edges between nodes)
- Basic tracking solvers: nearest neighbors and integer linear programming
- Compatible with Cell Tracking Challenge (CTC) format
- Efficient subgraphing based on attributes on any graph backend
- Integration with cell tracking evaluation metrics
Installation
pip install tracksdata
Why tracksdata?
TracksData provides a common data structure for multi-object tracking problems. It uses graphs to represent detections (nodes) and their connections (edges), making it easier to work with tracking data across different algorithms.
Key benefits:
- Consistent data representation for tracking problems
- Modular components that can be combined as needed
- Support for both small datasets (in-memory) and large datasets (database)
Documentation
1 maintainer
Release files for tracksdata 0.1.0rc9
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Source distribution (sdist)
| File | Size | Uploaded | |
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| tracksdata-0.1.0rc9.tar.gz | 267.6 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tracksdata-0.1.0rc9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 565.3 kB
Release files / tracksdata-0.1.0rc9.tar.gz
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