v8.3.49
版本发布时间: 2024-12-11 01:30:31
ultralytics/ultralytics最新发布版本:v8.3.52(2024-12-20 20:52:05)
🌟 Summary
Version 8.3.49
introduces key updates across Docker workflows, YOLO evaluation indexing, PyTorch compatibility, and documentation. These changes enhance stability, compatibility, and user experience for developers and end-users. 🚀
📊 Key Changes
-
Docker Enhancements:
- Replaced standard
pip install
withuv pip install
for better Python package management. 🐍🛠️ - System-level package installations across all Dockerfiles for increased reliability.
- Included flags like
--index-strategy
to handle edge cases more robustly.
- Replaced standard
-
YOLO Dataset Compatibility:
- Standardized
category_id
indexing in COCO and LVIS datasets, starting indices from 1 for consistency. 📊
- Standardized
-
PyTorch Version Support:
- Added compatibility for PyTorch
2.5
and Torchvision0.20
versions. 🔄
- Added compatibility for PyTorch
-
Documentation Improvements:
- Updated NVIDIA Jetson guide to explain Deep Learning Accelerator (DLA) functionality and limitations more clearly. 📝
- Refined export format table for YOLOv5 to include improved links to relevant integration guides. 🌐
-
Testing Optimization:
- Removed slow and outdated Google Drive-dependent tests to streamline testing workflows. 🧪
-
GitHub Workflow Update:
- Added a
git pull
step to ensure the latest documentation changes are fetched before updates. ⚙️
- Added a
🎯 Purpose & Impact
-
Enhanced Package Management:
Consolidating Python package installations withuv pip
ensures safer and more predictable setups, reducing dependency issues. 🛡️ -
Better Dataset Compatibility:
Improved indexing logic aligns with common standards, reducing confusion during COCO/LVIS dataset evaluations. 📋 -
Future-Ready PyTorch Support:
Developers leveraging the latest PyTorch and Torchvision versions can seamlessly integrate without compatibility issues, unlocking new features and performance improvements. 🚀 -
Improved Documentation Usability:
Clearer and more accessible docs guide users in leveraging advanced features, such as model exporting and NVIDIA DLA usage, empowering informed decision-making. 📖✨ -
More Efficient Testing:
By removing redundant tests, testing processes are faster and less prone to failure caused by external factors like rate limits. ⏩ -
Robust Documentation Workflow:
Ensures smooth updates and reduces the likelihood of conflicts or overwriting recent changes in collaborative environments. ✅
This update reflects Ultralytics' commitment to improving usability, stability, and developer experience across the board! 🌟
What's Changed
- Bump astral-sh/setup-uv from 3 to 4 in /.github/workflows by @dependabot[bot] in https://github.com/ultralytics/ultralytics/pull/18123
- Update Jetson Doc with DLA info by @lakshanthad in https://github.com/ultralytics/ultralytics/pull/18128
- Update YOLOv5 export table links by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18130
- Update
torchvision
compatibility table by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18117 - Change index to start from 1 by default in
predictions.json
by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/18140 - Remove Google Drive test by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18162
- Git pull docs before updating by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/18163
-
ultralytics 8.3.49
Docker imagesuv pip install
by @pderrenger in https://github.com/ultralytics/ultralytics/pull/18115
Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.3.48...v8.3.49