ultralytics 8.3.49

v8.3.49 - `ultralytics 8.3.49` Docker images `uv pip install` (#18115)

on Python PyPI

🌟 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 with uv 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.

• YOLO Dataset Compatibility:

  • Standardized category_id indexing in COCO and LVIS datasets, starting indices from 1 for consistency. 📊

• PyTorch Version Support:

  • Added compatibility for PyTorch 2.5 and Torchvision 0.20 versions. 🔄

• 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  • Removed slow and outdated Google Drive-dependent tests to streamline testing workflows.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. ⚙️

🎯 Purpose & Impact

• Enhanced Package Management:
  Consolidating Python package installations with uv 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 #18123
• Update Jetson Doc with DLA info by @lakshanthad in #18128
• Update YOLOv5 export table links by @RizwanMunawar in #18130
• Update torchvision compatibility table by @glenn-jocher in #18117
• Change index to start from 1 by default in predictions.json by @Y-T-G in #18140
• Remove Google Drive test by @glenn-jocher in #18162
• Git pull docs before updating by @glenn-jocher in #18163
• ultralytics 8.3.49 Docker images uv pip install by @pderrenger in #18115

Full Changelog: v8.3.48...v8.3.49