pypi ultralytics 8.1.0
v8.1.0 - YOLOv8 Oriented Bounding Boxes (OBB)
on Python PyPI

latest releases: 8.3.199, 8.3.198, 8.3.197...
20 months ago

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 almost 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

New Contributors

Full Changelog: https://github.com/ultralytics/ultralytics/commits/v8.1.0

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