trackers

trackers gives you clean, modular re-implementations of leading multi-object tracking algorithms released under the permissive Apache 2.0 license. You combine them with any detection model you already use.

You can install and use trackers in a Python>=3.10 environment. For detailed installation instructions, including installing from source and setting up a local development environment, check out our install page.

pip install trackers

pip install https://github.com/roboflow/trackers/archive/refs/heads/develop.zip

Use the trackers CLI to quickly test how our tracking algorithms perform on your videos and streams. This feature is experimental; see the CLI documentation for details.

trackers track --source source.mp4 --output output.mp4 --model rfdetr-nano --tracker bytetrack

trackers gives you clean, modular re-implementations of leading multi-object tracking algorithms. The package currently supports SORT and ByteTrack. OC-SORT, BoT-SORT, and McByte support is coming soon. For comparisons, see the tracker comparison page.

With a modular design, trackers lets you combine object detectors from different libraries with the tracker of your choice.

import cv2
from rfdetr import RFDETRNano
from trackers import ByteTrackTracker

model = RFDETRNano()
tracker = ByteTrackTracker()

cap = cv2.VideoCapture("source.mp4")
while True:
    ret, frame = cap.read()
    if not ret:
        break

    frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    detections = model.predict(frame_rgb)
    detections = tracker.update(detections)

import cv2
import supervision as sv
from inference import get_model
from trackers import ByteTrackTracker

model = get_model(model_id="rfdetr-nano")
tracker = ByteTrackTracker()

cap = cv2.VideoCapture("source.mp4")
while True:
    ret, frame = cap.read()
    if not ret:
        break

    result = model.infer(frame)[0]
    detections = sv.Detections.from_inference(result)
    detections = tracker.update(detections)

import cv2
import supervision as sv
from ultralytics import YOLO
from trackers import ByteTrackTracker

model = YOLO("yolo11n.pt")
tracker = ByteTrackTracker()

cap = cv2.VideoCapture("source.mp4")
while True:
    ret, frame = cap.read()
    if not ret:
        break

    result = model(frame)[0]
    detections = sv.Detections.from_ultralytics(result)
    detections = tracker.update(detections)

The code is released under the Apache 2.0 license.

We welcome all contributions—whether it’s reporting issues, suggesting features, or submitting pull requests. Please read our contributor guidelines to learn about our processes and best practices.