Crate trackforge

Version: 0.1.8

Trackforge is a unified, high-performance computer vision tracking library, implemented in Rust and exposed as a Python package.

It provides state-of-the-art tracking algorithms like ByteTrack, optimized for speed and ease of use in both Rust and Python environments.

Features

• High Performance: Native Rust implementation for maximum speed and memory safety.
• Python Bindings: Seamless integration with the Python ecosystem using pyo3.
• Unified API: Consistent interface for tracking tasks across both languages.
• ByteTrack: Robust multi-object tracking using Kalman filters and IoU matching.

Usage (Rust)

use trackforge::trackers::byte_track::ByteTrack;

// Initialize ByteTrack
let mut tracker = ByteTrack::new(0.5, 30, 0.8, 0.6);

// Detections: Vec<([f32; 4], f32, i64)>
let detections = vec![
    ([100.0, 100.0, 50.0, 100.0], 0.9, 0),
];

// Update
let tracks = tracker.update(detections);

for t in tracks {
    println!("ID: {}, Box: {:?}", t.track_id, t.tlwh);
}

Quick Reference

Modules

• trackers — Implementation of various multi-object tracking (MOT) algorithms.
• traits
• types — Common types used across the Trackforge library.
• utils — Utility functions for geometry and Kalman filtering.