Announcing Ultralytics v8.2.64 Release!
Hello Ultralytics Community!
We are excited to announce the release of Ultralytics v8.2.64! This update brings a host of improvements and new features designed to enhance your experience and streamline your workflows. Here’s what’s new:
Summary
The v8.2.64
release for Ultralytics provides critical updates including better token management for GitHub actions, enhancements in documentation for object detection models, expanded TensorFlow export support, and various compatibility improvements across the codebase.
Key Changes
- GitHub Workflow Update: Improved secret token management in
.github/workflows/format.yml
. PR #123 by @glenn-jocher - Documentation Update: Changes in the bounding box format within the datasets documentation, fixing markup issues. PR #124 by @RizwanMunawar
- Model Export Enhancements: Expanded support for TensorFlow (
TF SavedModel
,TF GraphDef
,TF Lite
) formats. PR #125 by @AyushExel - New Utility Functions: Introduction of
torch_load
in utility patches andautocast
intorch_utils
for better AMP compatibility. PR #126 by @glenn-jocher - Miscellaneous Code Improvements: Adjustments in model loading for YOLO-NAS, TensorFlow export options, and improved interpolation handling in image transformation functions. PR #127 by @glenn-jocher
Purpose & Impact
- Better Token Management: Fixes the token usage in GitHub workflows to offer more robust and flexible secret management. This ensures smoother and more secure CI/CD flows.
- Enhanced Documentation: Improved bounding box format descriptions for more accurate and easy-to-understand object detection model training guidance. Makes it easier for users to train models with precise annotations.
- Broader Export Compatibility: Adding TensorFlow formats support means users can now export models in more formats, making it easier to integrate with a wider array of applications and tools.
- Utility Enhancements: The new
torch_load
function andautocast
method offer greater flexibility and efficiency in model handling and automatic mixed precision (AMP) training, respectively, ensuring compatibility with both newer and older PyTorch versions. - Overall Stability: Various bug fixes and improvements across the codebase improve the robustness, performance, and user-friendliness of the Ultralytics repository.
These updates further streamline the user experience, enhance compatibility across various platforms, and ensure the code adheres to the latest practices, significantly benefiting both expert developers and those newer to model training and deployment.
We encourage you to try out the new release and share your feedback with us. Your insights are invaluable in helping us improve and evolve Ultralytics.
Check out the full release notes and download the update here: Ultralytics v8.2.64 Release
Happy coding!
The Ultralytics Team