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TracksData

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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

Release files for tracksdata 0.1.0rc10

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Source distribution for tracksdata 0.1.0rc10
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Table of built distributions (wheels) for tracksdata 0.1.0rc10
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tracksdata-0.1.0rc10-py3-none-any.whl Python 3 none any Details

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