Getting Started

Install

Rust

[dependencies]
trackforge = "0.4"

The default build is light and pulls no image codecs. Every tracker runs on detections you pass in, and the appearance trackers run on embeddings you pass in. To have the library produce embeddings for you by running a model over a frame, enable the reid-model feature, which adds the AppearanceExtractor trait and the DeepSort and DeepOcSort wrappers along with the image crate.

[dependencies]
trackforge = { version = "0.3", features = ["reid-model"] }

Python

pip install trackforge

Your first tracker

The detection format is the same everywhere: a list of ([x, y, w, h], score, class_id) tuples, where x, y is the top-left corner in pixels.

Rust

#![allow(unused)]
fn main() {
use trackforge::trackers::byte_track::ByteTrack;

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

let detections = vec![
    ([100.0, 100.0, 50.0, 100.0], 0.9, 0),
    ([200.0, 200.0, 60.0, 120.0], 0.85, 0),
];

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

Python

from trackforge import BYTETRACK

tracker = BYTETRACK(track_thresh=0.5, track_buffer=30, match_thresh=0.8, det_thresh=0.6)

detections = [
    ([100.0, 100.0, 50.0, 100.0], 0.9, 0),
    ([200.0, 200.0, 60.0, 120.0], 0.85, 0),
]

for track_id, tlwh, score, class_id in tracker.update(detections):
    print(f"ID: {track_id}, Box: {tlwh}")

Call update once per frame. Each tracker keeps its own state and returns the confirmed tracks for the current frame.