The LightGBM framework uses gradient boosting for ranking, classification, and other machine learning tasks.
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24 alternativesYOLOv8
Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.
About YOLOv8
YOLOv8 is listed here through the Ultralytics YOLO open-source repository on GitHub. The repository provides Python and command-line tools for YOLO computer vision models. Supported tasks include object detection, instance segmentation, semantic segmentation, depth estimation, image classification, pose estimation, and oriented object detection. Detected objects can be tracked across video frames for detection, segmentation, pose, and oriented object detection models.
The library can be installed with pip and used through the yolo command or the Python API. The Python API covers training, validation, prediction, and export, including export to ONNX format. Pretrained models download automatically from the latest Ultralytics release on first use. The page lists the YOLO27 family as not yet available, with no launch date set. Commercial use requires an Enterprise License from Ultralytics. The stated requirements are Python 3.8 or later and PyTorch 1.8 or later.
Key features
- Object detection, instance segmentation, and semantic segmentation across YOLO model versions
- Image classification, pose estimation, and oriented object detection tasks
- Object tracking across video frames for detection, segmentation, pose, and OBB models
- Command-line interface using the yolo command for prediction on images or URLs
- Python API for training, validation, prediction, and model export
- Model export to ONNX format for deployment
Best for: Python developers and researchers who want to build computer vision applications with pretrained YOLO models.
Good for
- Open source, with the source code available in a public GitHub repository
- Covers several computer vision tasks in one library
- Usable from both the command line and Python projects
Watch out for
- The YOLO27 family is not yet available, and no launch date is set
- Commercial use requires an Enterprise License
- Requires Python 3.8 or later and PyTorch 1.8 or later
YOLOv8 at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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YOLOv8 FAQ
How do I install the package?
Run pip install ultralytics in a Python 3.8 or later environment with PyTorch 1.8 or later. The page says Conda, Docker, and source installs are described in the Quickstart Guide.
Can I use it for commercial purposes?
The page says commercial use requires an Enterprise License, which can be requested through Ultralytics Licensing.
Where can I get support?
Support is available through GitHub Issues. Discussions take place on Discord, Reddit, and the Ultralytics Community Forums.
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