🌟 Summary

Version 8.3.52 focuses on enhanced CUDA memory management for improved performance, with additional updates to documentation, compatibility for NVIDIA Jetson devices, and refined functionality for YOLO models. 🚀

📊 Key Changes

• 🚀 New cuda_memory_usage Utility: Introduced a tool for dynamic monitoring and management of CUDA memory during operations.
• 💡 Improved Model Profiling: Integrated memory tracking into the profiling process to report GPU memory usage alongside performance stats.
• 🔄 Enhanced Object Segmentation: Modified segment2box for precise bounding box calculations when segments extend beyond the image boundaries.
• 📦 JetPack 6.1 Dockerfile Update: Added compatibility for NVIDIA Jetson Orin Nano Super Developer Kit with dependency upgrades and performance benchmarks.
• 📖 Richer Documentation: Added a CIFAR-100 tutorial video, improved clarity on scale parameter for multiscale training, and updated ROS and NVIDIA Jetson guides.
• 🧹 TFLite Example Cleanup: Removed unnecessary RGB-to-BGR conversions for simpler and clearer example usage.

🎯 Purpose & Impact

• 🚀 Enhanced Performance: The cuda_memory_usage utility ensures more efficient GPU memory handling, reducing the risk of out-of-memory crashes during complex operations.
• 📈 Model Optimization: Developers get richer profiling insights, aiding faster debugging and improving training/production readiness.
• 🖼️ Robust Object Detection: Improved segmentation functionality provides accuracy even with challenging edge cases, making models more reliable.
• 🤖 Wider Compatibility: Updating to JetPack 6.1 enables users to fully leverage NVIDIA Jetson’s latest hardware advancements (e.g., Orin Nano Super’s 67 TOPS).
• 📚 Simplified Learning: Documentation improvements, including engaging tutorials and clarified parameters, lower the barrier to entry for both beginners and experts.
• 🧑‍💻 Beginner-Friendly Examples: Streamlined TFLite examples ensure ease of adoption for new developers.

This release delivers meaningful improvements for developers working across GPU-heavy tasks, embedded systems, and edge AI deployments! 🚀

What's Changed

• Revert segment2box and clip segments by @Laughing-q in https://github.com/ultralytics/ultralytics/pull/18294
• Update JetPack6 Dockerfile with latest JetPack6.1 by @lakshanthad in https://github.com/ultralytics/ultralytics/pull/18295
• Add https://youtu.be/6bZeCs0xwO4 to docs by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18292
• Fix RGB to BGR conversion in TFLite example by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/18305
• Align solutions YAML with default.yaml by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/18300
• Fix incorrect scale description by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/18303
• Update Jetson doc with NVIDIA Jetson Orin Nano Super Developer Kit by @lakshanthad in https://github.com/ultralytics/ultralytics/pull/18289
• ROS Guide, updated YOLO version by @ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/18325
• ultralytics 8.3.52 AutoBatch CUDA computation improvements by @Laughing-q in https://github.com/ultralytics/ultralytics/pull/18291

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.3.51...v8.3.52