edgefirst-tracker

ByteTrack multi-object tracking. Installs alone — it does not require the tensor, image, or decoder wheels.

PyPI License

Part of the EdgeFirst HAL

edgefirst-tracker is one of five Python packages built from the EdgeFirst Hardware Abstraction Layer.

The EdgeFirstAI/hal repository is the home for all of them — source, issue tracker, architecture documentation and release notes.

Package Provides
edgefirst-tensor Zero-copy tensor allocation and host/GPU/CUDA mapping
edgefirst-codec JPEG and PNG decoding directly into pre-allocated tensors
edgefirst-image GPU-accelerated colour conversion, resize, letterbox, tiling and drawing
edgefirst-decoder YOLO and ModelPack output decoding
edgefirst-tracker ByteTrack (this package)

Installation

pip install edgefirst-tracker

Requires Python 3.8 or newer and NumPy. Wheels are published for Linux (x86_64, aarch64), macOS (arm64), and Windows (x86_64). This package does not depend on edgefirst-tensor.

Packages install under the PEP 420 edgefirst.* namespace, so the import is edgefirst.tracker.

Quick start

ByteTrack.update takes detections for one timestamp and returns a list of TrackInfo (or None for unmatched rows) of the same length as the input:

import numpy as np
from edgefirst.tracker import ByteTrack

tracker = ByteTrack()

# boxes is (N, 4) XYXY; scores and labels are length N.
boxes = np.array([[0.1, 0.2, 0.3, 0.4]], dtype=np.float32)
scores = np.array([0.9], dtype=np.float32)
labels = np.array([0], dtype=np.intp)
timestamp_ns = 0

tracks = tracker.update(boxes, scores, labels, timestamp_ns)
for t in tracks:
    if t is None:
        continue
    print(t.uuid, t.tracked_location, t.count)

Decoder.decode_tracked on the edgefirst-decoder wheel accepts this ByteTrack (or any object with an update method).

Parameters

Argument Default Meaning
high_conf 0.7 Detections above this score take the first association pass
iou 0.25 IoU gate for matching a detection to a track
update 0.25 Kalman update blending factor
lifespan_ns 500_000_000 Drop a track that has not matched for this many nanoseconds (500 ms)

Errors

update raises if boxes, scores, and labels disagree on N, or if boxes is not shape (N, 4). Empty detections (N == 0) are valid — unmatched tracks age and expire according to lifespan_ns.

Performance

Association is CPU-only (Kalman + IoU). Typical cost is microseconds per frame at tens of detections; it does not allocate GPU tensors and does not link libedgefirst_tensor. Build the tracker once and call update every frame.

Versioning and changelog

All five edgefirst-* packages are versioned and released together with the HAL itself. Release notes live in the single CHANGELOG.md.

Links

License

Apache-2.0

Project links

Data verified by PyPI on Sep 4, 2026
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Key dates

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  • Released:
Newer release available (0.30.0)

1 maintainer

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Avatar for au-zone from gravatar.com au-zone

Credits

PyPI data
Data sourced directly from PyPI's database.

Author: Au-Zone Technologies

GitHub Statistics

Data verified by PyPI on Sep 4, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0
View SPDX License List

Requires

Python >=3.8

Tags

tracking bytetrack object-tracking kalman-filter edge-ai

Classifiers

Report project as malware

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