trackers is a unified library offering clean room re-implementations of leading multi-object tracking algorithms. Its modular design allows you to easily swap trackers and integrate them with object detectors from various libraries like ultralytics, inference, mmdetection, or transformers.
Pip install the trackers package in a Python>=3.9 environment.
pip install trackersInstall from source
By installing trackers from source, you can explore the most recent features and enhancements that have not yet been officially released. Please note that these updates are still in development and may not be as stable as the latest published release.
pip install git+https://github.com/roboflow/trackers.gitWith a modular design, trackers lets you combine object detectors from different libraries (such as ultralytics, inference, mmdetection, or transformers) with the tracker of your choice. Here's how you can use SORTTracker with various detectors:
import supervision as sv
from trackers import SORTTracker
from inference import get_model
tracker = SORTTracker()
model = get_model(model_id="yolov11m-640")
annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
def callback(frame, _):
result = model.infer(frame)[0]
detections = sv.Detections.from_inference(result)
detections = tracker.update(detections)
return annotator.annotate(frame, detections, labels=detections.tracker_id)
sv.process_video(
source_path="input.mp4",
target_path="output.mp4",
callback=callback,
)import supervision as sv
from trackers import SORTTracker
from ultralytics import YOLO
tracker = SORTTracker()
model = YOLO("yolo11m.pt")
annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
def callback(frame, _):
result = model(frame)[0]
detections = sv.Detections.from_ultralytics(result)
detections = tracker.update(detections)
return annotator.annotate(frame, detections, labels=detections.tracker_id)
sv.process_video(
source_path="input.mp4",
target_path="output.mp4",
callback=callback,
)trackers-2.0.0rc0-promo.mp4
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.