ultralytics 8.4.151

v8.4.151 - Preserve conf=0.0 in nms=True exports instead of baking 0.25 into the graph (#26163)

on Python PyPI

🌟 Summary

Ultralytics 8.4.151 improves export correctness, TensorRT QAT performance, tracking behavior, model diagnostics, and documentation—while introducing no new runtime arguments. 🚀

📊 Key Changes

• Preserved conf=0.0 in NMS exports 🎯

  • The most important fix ensures an explicit zero confidence threshold is written into exported ONNX and other NMS-enabled graphs.
  • The default confidence of 0.25 is now applied only when conf is omitted or set to None.
  • Added an ONNX regression test that verifies the serialized threshold.

• Faster QAT TensorRT engines ⚡

  • Quantization-aware training exports now run unquantized TensorRT layers in FP16 instead of FP32.
  • Applies to TensorRT 10 and TensorRT 11 while preserving INT8 quantization ranges.
  • Reported benchmarks show QAT INT8 performance improving substantially, with no changes to standard post-training INT8 or FP16 exports.

• Explicit zero confidence preserved in tracking 🎥

  • model.track(conf=0.0) now keeps the requested value instead of replacing it with the default 0.1.
  • Omitted confidence values still default to 0.1, maintaining existing tracking behavior.

• Warnings for blank class labels ⚠️

  • AutoBackend now warns when model class names are empty or contain only whitespace.
  • The original names remain unchanged, and repeated access does not produce repeated warnings.

• Expanded tracking and validation documentation 📚

  • Solution guides now document all forwarded tracking arguments, including imgsz, max_det, and quantize.
  • Validation documentation now explains the fraction option for selecting subsets of training, validation, or test data.
  • Corrected the documented YOLO26n-depth parameter count.

• Improved PyTorch hook guidance 🧩

  • Added a runnable example showing how to register forward hooks after the training model is initialized.
  • Clarifies behavior with distributed training, EMA checkpoints, validation, prediction, and tracking.

• Updated YOLO27 preview documentation 🔭

  • Reorganized the preview page, clarified NMS and NMS-free detection heads, removed unsupported performance claims, and linked the preview from relevant YOLO26, task, and mode pages.
  • YOLO27 remains unreleased; YOLO26 continues to be the recommended stable model family.

• Documentation rendering and layout fixes 🖼️

  • Corrected isolated-object images that previously displayed raw Markdown syntax.
  • Shortened an Intel DL Streamer heading to prevent table-of-contents overflow.

🎯 Purpose & Impact

• More predictable exports: Users can intentionally export with conf=0.0 without the value being silently changed to 0.25. ✅
• Better deployment speed: QAT TensorRT engines should make more effective use of FP16 hardware acceleration, particularly on GPUs where FP32 fallback was slowing inference.
• More reliable tracking controls: Confidence thresholds now behave consistently when users explicitly provide zero or other numeric values.
• Easier troubleshooting: Warnings for blank class names help identify why detections may appear without visible labels.
• Clearer documentation: Expanded argument tables, hook examples, validation guidance, and YOLO27 status notes make the platform easier to use and reduce ambiguity for both new and experienced developers. 📖

What's Changed

• Clarify YOLO27 preview documentation and lead with the page heading by @glenn-jocher in #26162
• Render the isolated-object figures as HTML and shorten the DL Streamer heading by @raimbekovm in #26168
• Document the forwarded solution track args, val fraction and the fused depth params by @raimbekovm in #26166
• Link the YOLO27 preview from the task, mode and YOLO26 pages by @raimbekovm in #26165
• Warn on empty class names when initializing AutoBackend by @cainiao33 in #26164
• Preserve explicit zero confidence in track mode by @aswanth-07 in #26161
• Document forward hooks across training model rebuilds by @aswanth-07 in #26157
• Run the float head of QAT TensorRT engines in FP16 by @Y-T-G in #26167
• Preserve conf=0.0 in nms=True exports instead of baking 0.25 into the graph by @cainiao33 in #26163

Full Changelog: v8.4.150...v8.4.151