| comments: true | |
| description: Understand multi-object tracking datasets, upcoming features and how to use them with YOLO in Python and CLI. Dive in now!. | |
| keywords: Ultralytics, YOLO, multi-object tracking, datasets, detection, segmentation, pose models, Python, CLI | |
| # Multi-object Tracking Datasets Overview | |
| ## Dataset Format (Coming Soon) | |
| Multi-Object Detector doesn't need standalone training and directly supports pre-trained detection, segmentation or Pose models. Support for training trackers alone is coming soon | |
| ## Usage | |
| !!! Example | |
| === "Python" | |
| ```python | |
| from ultralytics import YOLO | |
| model = YOLO('yolov8n.pt') | |
| results = model.track(source="https://youtu.be/LNwODJXcvt4", conf=0.3, iou=0.5, show=True) | |
| ``` | |
| === "CLI" | |
| ```bash | |
| yolo track model=yolov8n.pt source="https://youtu.be/LNwODJXcvt4" conf=0.3, iou=0.5 show | |
| ``` | |