HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Update Docs README (#8919)

Browse source
This commit is contained in:
Glenn Jocher 2024-03-13 16:17:57 +01:00 • committed by GitHub
parent e8de3fa693
commit 5c1277113b
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
3 changed files with 100 additions and 64 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/en/index.md
View file

@ -69,7 +69,7 @@ Explore the YOLOv8 Docs, a comprehensive resource designed to help you understan
- [YOLOv6](https://github.com/meituan/YOLOv6) was open-sourced by [Meituan](https://about.meituan.com/) in 2022 and is in use in many of the company's autonomous delivery robots.
- [YOLOv7](https://github.com/WongKinYiu/yolov7) added additional tasks such as pose estimation on the COCO keypoints dataset.
- [YOLOv8](https://github.com/ultralytics/ultralytics) is the latest version of YOLO by Ultralytics. As a cutting-edge, state-of-the-art (SOTA) model, YOLOv8 builds on the success of previous versions, introducing new features and improvements for enhanced performance, flexibility, and efficiency. YOLOv8 supports a full range of vision AI tasks, including [detection](tasks/detect.md), [segmentation](tasks/segment.md), [pose estimation](tasks/pose.md), [tracking](modes/track.md), and [classification](tasks/classify.md). This versatility allows users to leverage YOLOv8's capabilities across diverse applications and domains.
- [YOLOv9] (https://github.com/WongKinYiu/yolov9) Introduces innovative methods like Programmable Gradient Information (PGI) and the Generalized Efficient Layer Aggregation Network (GELAN).
- [YOLOv9](models/yolov9.md) Introduces innovative methods like Programmable Gradient Information (PGI) and the Generalized Efficient Layer Aggregation Network (GELAN).
## YOLO Licenses: How is Ultralytics YOLO licensed?