You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
|
|
|
---
|
|
|
|
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/Zgi9g1ksQHc", conf=0.3, iou=0.5, show=True)
|
|
|
|
```
|
|
|
|
=== "CLI"
|
|
|
|
|
|
|
|
```bash
|
|
|
|
yolo track model=yolov8n.pt source="https://youtu.be/Zgi9g1ksQHc" conf=0.3, iou=0.5 show
|
|
|
|
```
|