v8.1.0
版本发布时间: 2024-01-10 11:09:06
ultralytics/assets最新发布版本:v8.2.0(2024-04-17 13:32:48)
Ultralytics v8.1.0 Release Notes
Introduction
Ultralytics proudly announces the v8.1.0 release of YOLOv8, celebrating a year of remarkable achievements and advancements. This version continues our commitment to making AI technology accessible and powerful, reflected in our latest breakthroughs and improvements.
2023 in Review
- Record-Breaking Engagement: Over 20 million downloads of the Ultralytics package, with 4 million in December alone! 📈
- Massive Model Training: An incredible 19 million YOLOv8 models were trained in 2023, showing the widespread adoption and versatility of our platform. 🌐
- Diverse Model Usage: 64% of these models were for object detection, 20% for instance segmentation, 15% for pose estimation, and 1% for image classification. 📊
- Expanding Global Reach: YOLOv8 reached 5 million users in 2023 and was run in 15 billion inference jobs across various industries, showcasing its real-world impact. 🌍
- Documentation in Multiple Languages: Our docs are now available in 11 languages, catering to our diverse global community. 📚
Ultralytics v8.1.0 Key Highlights
- YOLOv8 OBB Models: The introduction of Oriented Bounding Box models in YOLOv8 marks a significant step in object detection, especially for angled or rotated objects, enhancing accuracy and reducing background noise in various applications such as aerial imagery and text detection.
- Segmentation Support & Enhancements: Enhanced segmentation capabilities offer more precise image analysis, with improved classification augmentations integrated into Ultralytics training pipelines.
- Performance Optimizations: Since our initial release last year we've focused on optimizing every aspect of the YOLOv8 framework, including training, validation, inference, and export, ensuring speed and efficiency without compromising performance.
- Enhanced Model Architecture & Training Features: Incremental updates in model architecture, training features, and dataset support, including integration with Open Images V7 dataset and improved image classification models.
- API and CLI Improvements: Enhanced user experience with refined API and CLI, including the Ultralytics Explorer tool for advanced dataset exploration and interaction.
- PaddlePaddle, NCNN, PNNX, TensorRT & Other Integrations: Strengthened integration with multiple other platforms, offering users more deployment flexibility and compatibility for YOLOv8 users.
- Diverse Contributions & Ultralytics HUB Evolution: The integration of over 1000 pull requests by 230 contributors and the growth of Ultralytics HUB, with it's own series of version updates, highlights the community's vital role in the development of YOLOv8.
Community Engagement and Support
- Expanding Documentation: Our documentation now spans 11 languages, with over 200 pages, providing comprehensive guides for various real-world applications.
- Custom-Trained YOLOv8 Models: With the ability to train models on custom data, 19 million YOLOv8 models were trained in 2023 alone, catering to diverse needs across object detection, segmentation, pose estimation, and image classification.
- User Contributions: We encourage and appreciate user-contributed examples and stories, showcasing the versatility and real-world impact of YOLOv8.
Summary
Ultralytics v8.1.0 is a testament to a year of innovation, with the integration of Oriented Object Detection, enhanced classification models, and a strong focus on user experience and community engagement. We thank our users and contributors for their invaluable support and look forward to another year of groundbreaking advancements in the field of AI and computer vision in 2024! 🌟🚀🎉
What's Changed
- Update YOLOv5 v7.0 Banner Assets by @pderrenger in https://github.com/ultralytics/assets/pull/2
- Add files via upload by @glenn-jocher in https://github.com/ultralytics/assets/pull/3
- Add files via upload by @glenn-jocher in https://github.com/ultralytics/assets/pull/4
- Add files via upload by @glenn-jocher in https://github.com/ultralytics/assets/pull/7
- Update LICENSE to AGPL-3.0 by @glenn-jocher in https://github.com/ultralytics/assets/pull/8
- Update Neural Magic logos by @glenn-jocher in https://github.com/ultralytics/assets/pull/9
- Update HUB banner with Pose runner by @glenn-jocher in https://github.com/ultralytics/assets/pull/10
- Add tasks banner-tasks.png by @glenn-jocher in https://github.com/ultralytics/assets/pull/11
- docs: add assets for docs hub projects by @sergiuwaxmann in https://github.com/ultralytics/assets/pull/12
- docs: add assets for docs hub datasets by @sergiuwaxmann in https://github.com/ultralytics/assets/pull/13
- docs: add assets for docs hub models by @sergiuwaxmann in https://github.com/ultralytics/assets/pull/14
- Add files via upload by @glenn-jocher in https://github.com/ultralytics/assets/pull/19
- Add #YV23 banner by @glenn-jocher in https://github.com/ultralytics/assets/pull/20
- Create README.md by @glenn-jocher in https://github.com/ultralytics/assets/pull/21
- Add discord emotes by @glenn-jocher in https://github.com/ultralytics/assets/pull/23
- Update README.md by @glenn-jocher in https://github.com/ultralytics/assets/pull/22
- Improve README by @pderrenger in https://github.com/ultralytics/assets/pull/25
- Update github banner by @glenn-jocher in https://github.com/ultralytics/assets/pull/26
- Update contributors by @glenn-jocher in https://github.com/ultralytics/assets/pull/28
- Update format.yml by @UltralyticsAssistant in https://github.com/ultralytics/assets/pull/32
- Add files via upload by @glenn-jocher in https://github.com/ultralytics/assets/pull/33
- Update Actions with Lychee and GitHub Token by @pderrenger in https://github.com/ultralytics/assets/pull/34
New Contributors
- @pderrenger made their first contribution in https://github.com/ultralytics/assets/pull/2
- @glenn-jocher made their first contribution in https://github.com/ultralytics/assets/pull/3
- @sergiuwaxmann made their first contribution in https://github.com/ultralytics/assets/pull/12
- @UltralyticsAssistant made their first contribution in https://github.com/ultralytics/assets/pull/32
Full Changelog: https://github.com/ultralytics/assets/compare/v0.0.0...v8.1.0
1、 calibration_image_sample_data_20x128x128x3_float32.npy.zip 1.11MB
2、 FastSAM-s.pt 22.73MB
3、 FastSAM-x.pt 138.23MB
4、 instances_val2017.json 19.06MB
5、 mobile_sam.pt 38.84MB
6、 person_keypoints_val2017.json 9.56MB
7、 rtdetr-l.pt 63.42MB
8、 rtdetr-x.pt 129.45MB
9、 sam_b.pt 357.67MB
10、 sam_l.pt 1.16GB
11、 Ultralytics_brand.zip 50.93KB
12、 Ultralytics_brand_all.zip 208KB
13、 Ultralytics_HUB_brand.zip 61.26KB
14、 Ultralytics_YOLO_brand.zip 61.3KB
15、 yolov3-sppu.pt 200.21MB
16、 yolov3-tinyu.pt 23.3MB
17、 yolov3u.pt 198.21MB
18、 yolov5l6u.pt 164.81MB
19、 yolov5lu.pt 101.9MB
20、 yolov5m6u.pt 79.09MB
21、 yolov5mu.pt 48.2MB
22、 yolov5n6u.pt 8.61MB
23、 yolov5nu.pt 5.27MB
24、 yolov5s6u.pt 29.56MB
25、 yolov5su.pt 17.68MB
26、 yolov5x6u.pt 297.4MB
27、 yolov5xu.pt 186.02MB
28、 yolov8l-cls.pt 71.69MB
29、 yolov8l-obb.pt 85.36MB
30、 yolov8l-oiv7.pt 84.44MB
31、 yolov8l-pose.pt 85.25MB
32、 yolov8l-seg.pt 88.11MB
33、 yolov8l-v8loader.pt 83.65MB
34、 yolov8l.pt 83.7MB
35、 yolov8m-cls.pt 32.68MB
36、 yolov8m-obb.pt 50.84MB
37、 yolov8m-oiv7.pt 50.26MB
38、 yolov8m-pose.pt 50.8MB
39、 yolov8m-seg.pt 52.36MB
40、 yolov8m-v8loader.pt 49.67MB
41、 yolov8m.pt 49.7MB
42、 yolov8n-cls.pt 5.3MB
43、 yolov8n-obb.pt 6.24MB
44、 yolov8n-oiv7.pt 6.87MB
45、 yolov8n-pose.pt 6.51MB
46、 yolov8n-seg.pt 6.73MB
47、 yolov8n-v8loader.pt 6.2MB
48、 yolov8n.pt 6.23MB
49、 yolov8s-cls.pt 12.25MB
50、 yolov8s-obb.pt 22.17MB
51、 yolov8s-oiv7.pt 21.9MB
52、 yolov8s-pose.pt 22.42MB
53、 yolov8s-seg.pt 22.79MB
54、 yolov8s-v8loader.pt 21.5MB
55、 yolov8s.pt 21.53MB
56、 yolov8x-cls.pt 109.74MB
57、 yolov8x-obb.pt 133.07MB
58、 yolov8x-oiv7.pt 131.47MB
59、 yolov8x-pose-p6.pt 189.81MB
60、 yolov8x-pose.pt 132.96MB
61、 yolov8x-seg.pt 137.4MB
62、 yolov8x-v8loader.pt 130.48MB
63、 yolov8x.pt 130.53MB
64、 yolov8x6-500.pt 186.47MB
65、 yolov8x6-oiv7.pt 187.64MB
66、 yolov8x6.pt 186.47MB
67、 yolo_nas_l.pt 328.35MB
68、 yolo_nas_m.pt 248.46MB
69、 yolo_nas_s.pt 83.29MB