Ultralytics YOLO

🌟 Summary

The release of Ultralytics v8.3.76 introduces improved dynamic batch inference for ONNX models with NMS export, a better object tracking experience, and various code and documentation enhancements. 🚀

📊 Key Changes

• Dynamic Batch Improvements:

  • Solved issues with dynamic=True and nms=True where the batch size was fixed at export.
  • Enabled dynamic input handling by introducing padding for unmatched batch sizes during ONNX exports.

• Tracking Enhancements:

  • Addressed errors when processing Torch tensors in model.track().
  • Improved integration of original input images with trackers for accuracy.

• Performance Accuracy:

  • Fixed GPU memory conversion errors for logging VRAM usage to ensure accurate reporting.

• Documentation Updates:

  • Standardized formatting in documentation for better consistency.
  • Enhanced examples for interpreting prediction results across detection, pose, segmentation, and more.

• Other Code Refinements:

  • Addressed layer miscount in logging by ensuring layers with no parameters are also displayed.
  • Enhanced GitHub issue templates for clearer differentiation between bug reports and feature requests.

🎯 Purpose & Impact

• 🛠 Improved Model Deployment: Dynamic padding during export ensures robust handling of varying batch sizes while maintaining compatibility with ONNX workflows.
• 🎥 Better Tracking: Smoother operation for streamed data and enhanced consistency in object tracking results benefit both developers and end-users.
• 📋 Accurate Logging: Correct VRAM usage metrics improve debugging and resource optimization.
• 📚 Developer Friendliness: Updated docs and examples make it easier for users to understand and utilize prediction results effectively.
• 🚀 Efficiency Boost: Code tweaks and fixes culminate in faster, more accurate model handling without disruptions.

This release addresses several community-reported issues, focusing on operational accuracy and usability across export, tracking, and development workflows! 🙌

What's Changed

• Initialize model_name attribute by @LoveAndHope-dev in https://github.com/ultralytics/ultralytics/pull/19224
• Update results.boxes docs: boxes.id may be None by @shankangke in https://github.com/ultralytics/ultralytics/pull/19227
• Fix bytes to GB conversion for logged VRAM usage by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19254
• Fix memory conversion by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19256
• Use new "Issue Type" in templates by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19257
• Add https://youtu.be/im7xBCnPURg to docs by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19265
• Support CoreML NMS export for Segment, Pose and OBB by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19173
• Fix layer count; show layers with no params in detailed log by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19202
• Standardize str formatting in docs by @lakshanthad in https://github.com/ultralytics/ultralytics/pull/19276
• Add detailed usage with demos to reCamera doc by @lakshanthad in https://github.com/ultralytics/ultralytics/pull/19275
• Add examples showing how to use result for all tasks by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19282
• Update model_data.py by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19267
• Revert "Support CoreML NMS export for Segment, Pose and OBB" by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19273
• Fix error with torch tensor input in model.track() by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19278
• ultralytics 8.3.76 fix dynamic batch inference with NMS export by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/19249

New Contributors

• @LoveAndHope-dev made their first contribution in https://github.com/ultralytics/ultralytics/pull/19224

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.3.75...v8.3.76