ultralytics 8.4.63

v8.4.63 - NVIDIA TensorRT 11 support with ModelOpt FP16 and INT8 quantization (#24735)

on Python PyPI

🌟 Summary

🚀 Ultralytics v8.4.63 mainly adds TensorRT 11 export support with FP16 and INT8 quantization via NVIDIA ModelOpt, while also expanding built-in multi-object tracking with several new tracker options and improving reliability, performance, and docs.

📊 Key Changes

• 🧠 Major export upgrade: TensorRT 11 support

  • The standout update in this release is PR #24735 by @onuralpszr.
  • Ultralytics now supports exporting models to NVIDIA TensorRT 11, which had previously broken due to API changes in TensorRT 11.
  • For FP16 and INT8 export on TensorRT 11, Ultralytics now uses NVIDIA ModelOpt instead of the older TensorRT builder flags and calibrator interface.
  • This keeps export working across:
    • TensorRT 7–10 with the legacy path
    • TensorRT 11 with the new strongly-typed ModelOpt path
  • Tested successfully for:
    • fp32
    • fp16
    • int8
    • including INT8 with dynamic shapes on TensorRT 11 ✅

• ⚡ Better quantization workflow for modern NVIDIA deployment

  • FP16 is now applied by baking mixed precision into the ONNX graph before engine build.
  • INT8 is now applied through explicit quantization in the ONNX graph with calibration data.
  • This is especially important because TensorRT 11 removed the old methods many exporters depended on.

• 🎯 Big tracking expansion: 4 new built-in trackers

  • PR #24371 added four new multi-object trackers alongside BoT-SORT and ByteTrack:
    • OC-SORT
    • Deep OC-SORT
    • FastTracker
    • TrackTrack
  • These are now documented and wired into the tracking system with YAML configs like:
    • ocsort.yaml
    • deepocsort.yaml
    • fasttrack.yaml
    • tracktrack.yaml

• 🏃 Tracking docs and selection guidance improved

  • Tracking docs were expanded to explain the strengths of each tracker and how to choose between them.
  • This makes the tracking feature much easier to use for both beginners and advanced users.

• 📹 Video stream loading is safer

  • PR #24749 improves cleanup when stream initialization fails.
  • If one stream fails while others already opened, Ultralytics now properly closes those partially-opened resources instead of leaking threads or capture handles.

• ⚡ AI Gym pose workflow is faster

  • PR #24744 reduces repeated GPU-to-CPU syncs in the workout monitoring loop by transferring keypoints to CPU in one go instead of piece by piece.
  • Same behavior, better efficiency.

• 🧪 Validation mixed precision handling simplified

  • PR #24736 consolidates validation autocast into one cleaner scope during training validation.
  • This helps keep mixed-precision behavior simpler and more robust.

• 📝 Documentation improvements

  • Added new Rust inference documentation for running YOLO models through ONNX Runtime without Python.
  • Expanded tracking docs and reference pages.
  • Updated TensorRT and Jetson docs to explain TensorRT 11 behavior and DLA limitations.
  • Refreshed guides like Coral Edge TPU and semantic image search.

🎯 Purpose & Impact

• 🚀 TensorRT 11 users can export again

  • This is the biggest user-facing change in the release.
  • If you deploy on modern NVIDIA systems using TensorRT 11, exports that were failing should now work again.
  • This is especially valuable for production inference pipelines and edge/server deployment.

• ⚙️ Future-proofs NVIDIA deployment

  • TensorRT 11 changed how precision and quantization are handled.
  • By moving to a ModelOpt-based workflow, Ultralytics stays compatible with newer NVIDIA tooling instead of relying on removed APIs.

• 💾 Smaller, faster engines remain accessible

  • FP16 and INT8 exports are still available even with TensorRT 11’s breaking changes.
  • That means users can continue optimizing for:
    • faster inference
    • lower memory use
    • better deployment efficiency

• 📦 Dynamic INT8 export support is especially useful

  • Supporting INT8 with dynamic shapes on TensorRT 11 can help users deploying across varying input sizes without giving up quantization benefits.

• 👀 Tracking becomes more flexible for real-world scenarios

  • The new trackers give users more choices depending on their needs:
    • simple baseline tracking
    • crowded-scene tracking
    • appearance-aware tracking
    • occlusion-heavy tracking
  • This can improve results in surveillance, sports, traffic, and retail use cases.

• 🔒 More stable long-running applications

  • Stream cleanup improvements reduce the chance of lingering resources in apps that open cameras or network streams.
  • This matters most for production or multi-stream systems.

• ⚡ Small but meaningful performance wins

  • AI Gym and validation updates help reduce overhead and improve runtime efficiency without changing how users interact with the API.

Overall, v8.4.63 is a strong deployment-focused release 📦—with the headline improvement being restored and modernized TensorRT 11 export support, plus a major boost to tracking capabilities and several reliability/performance refinements.

What's Changed

• Consolidate validation autocast scope by @glenn-jocher in #24736
• Convert SAM3 docstrings to Google style by @glenn-jocher in #24741
• Merge isolated_model and isolated_task_model into isolated_model_path by @Laughing-q in #24742
• Avoid per-keypoint gpu sync in workout monitoring loop by @raimbekovm in #24744
• New TrackTrack, FastTracker, OC-SORT and Deep OC-SORT Trackers by @onuralpszr in #24371
• Reduce CI PyTorch index flakiness by @glenn-jocher in #24753
• Fix Codecov OIDC uploads by @glenn-jocher in #24754
• docs: 📝 Add Rust Inference documentation by @onuralpszr in #24712
• Report SystemLogger disk list by @glenn-jocher in #24758
• Fix instances count logging by @Y-T-G in #24738
• Clean up partially-initialized LoadStreams on failure by @raimbekovm in #24749
• Restructure Coral Edge TPU guide and fix FAQ Edge TPU model filename by @raimbekovm in #24745
• Restructure semantic image search guide by @raimbekovm in #24746
• NVIDIA TensorRT 11 support with ModelOpt FP16 and INT8 quantization by @onuralpszr in #24735

Full Changelog: v8.4.62...v8.4.63