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build(deps): update ultralytics requirement from >=8.4.115 to >=8.4.146 in /apps/ai - #242

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dependabot/pip/apps/ai/ultralytics-gte-8.4.146

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@dependabot dependabot Bot commented on behalf of github Sep 13, 2026

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Updates the requirements on ultralytics to permit the latest version.

Release notes

Sourced from ultralytics's releases.

v8.4.146 - Fix RT-DETR inference for small and dynamic inputs (#26120)

🌟 Summary

Ultralytics v8.4.146 improves RT-DETR reliability across small inputs, dynamic exports, and tracking, while updating export portability, Windows training behavior, data downloads, and GPU container environments. 🚀

📊 Key Changes

  • 🛠️ RT-DETR inference fixes

    • Prevents failures when small images produce fewer anchors than the configured query count.
    • Keeps query counts, denoising masks, and learned query embeddings consistent.
    • Preserves the correct detection limit in dynamic ONNX and OpenVINO exports.
    • Makes RT-DETR tracking compatible with TrackTrack by avoiding an unsupported NMS recovery argument.
    • Validated across image sizes from 32 to 640 pixels, TorchScript, CoreML, ONNX, OpenVINO, training, validation, and tracking.
  • 📦 More device-agnostic TorchScript exports

    • Removes hard-coded device assumptions from export-time tensor creation.
    • TorchScript models exported on CUDA or Apple MPS can now be loaded and used on other devices, such as CPU.
    • Fixes dynamic RT-DETR export behavior so bounding boxes remain correct at sizes different from the export size.
  • 🎯 Improved FP16 embedded-NMS inference

    • Converts end-to-end NMS output rows to float32.
    • Prevents segmentation, pose, and OBB FP16 exports from failing during mask or box processing.
  • 🪟 Better Windows CUDA training defaults

    • Stops automatically enabling channels_last memory format on Windows, where it could significantly reduce performance.
    • Users can still explicitly enable it with channels_last=True.
  • 🌐 More reliable NDJSON image downloads

    • Replaces the previous 30-second total timeout with connection and socket-inactivity timeouts.
    • Large images on slow or shared connections are less likely to fail while downloading.
  • 🐳 Updated GPU and export environments

    • AMD64 GPU images now use PyTorch 2.14 with CUDA 13.2.
    • NVIDIA ARM64 images move to NVIDIA PyTorch 26.08 with CUDA 13.4 and updated ONNX Runtime GPU support.
    • GPU runner images now include g++ for compiled training workflows and TensorRT for CUDA 13.
    • LiteRT remains in the Python export image because its current dependencies are not compatible with PyTorch 2.14.
    • Conda Docker builds now use conda-forge PyTorch 2.13, torchvision 0.28, and CUDA 13.0.
  • 🧪 CI and maintenance updates

    • Restores the GPU CI workflow while keeping it temporarily disabled through an explicit condition.
    • Adds disk cleanup before isolated export setup.
    • Updates documentation for CUDA 13, JetPack, TensorRT, DLA, Conda images, and export compatibility.
    • Bumps the package version from 8.4.145 to 8.4.146.

🎯 Purpose & Impact

  • Greater RT-DETR stability: Small images and dynamically sized inputs should no longer trigger query or anchor-related inference failures. ✅
  • More dependable deployment: Models exported on one accelerator can be used on another device more reliably, reducing device-specific TorchScript issues.
  • Safer FP16 workflows: Embedded-NMS exports for segmentation, pose, and OBB models now handle post-processing without dtype errors.
  • Faster Windows training in common cases: Windows CUDA users avoid an automatic memory layout optimization that was measured to slow training substantially.

... (truncated)

Commits
  • 9d45ee4 Fix RT-DETR inference for small and dynamic inputs (#26120)
  • b71b392 Skip channels_last auto-enable on Windows CUDA training (#26105)
  • 515d325 Cast end-to-end NMS rows to float32 so FP16 exports with embedded NMS decode ...
  • 8482f2e Keep TorchScript exports device-agnostic (#26118)
  • a5b2d42 Time NDJSON image downloads by socket inactivity instead of a 30 s total dead...
  • dc33293 Restore GPU CI with a temporary disable condition (#26119)
  • ffc535b Update GPU Docker images to current PyTorch and CUDA releases (#26115)
  • 7866d12 Bump to 8.4.145 for login failure exit status (#26117)
  • 38a876a Return failure status from Platform login (#26116)
  • 1ba77f6 Fix model loading, numerical edge cases, and CI setup (#26106)
  • Additional commits viewable in compare view

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Updates the requirements on [ultralytics](https://github.com/ultralytics/ultralytics) to permit the latest version.
- [Release notes](https://github.com/ultralytics/ultralytics/releases)
- [Commits](ultralytics/ultralytics@v8.4.115...v8.4.146)

---
updated-dependencies:
- dependency-name: ultralytics
  dependency-version: 8.4.146
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Sep 13, 2026
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dependabot Bot commented on behalf of github Sep 20, 2026

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Superseded by #244.

@dependabot dependabot Bot closed this Sep 20, 2026
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dependabot Bot deleted the dependabot/pip/apps/ai/ultralytics-gte-8.4.146 branch September 20, 2026 12:53
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