fix(deps): update dependency ultralytics ( 8.4.116 → 8.4.117 ) - #485

v8.4.117: - Route spatial Albumentations by type and carry masks, polygons and keypoints through it (#​25633)

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🌟 Summary

v8.4.117 improves augmentation correctness, model reliability, deployment safety, and documentation across Ultralytics YOLO and YOLO26. 🚀

📊 Key Changes

• 🧩 Albumentations now handles spatial transforms by type

  • PR #​25633 replaces the fragile hardcoded transform-name list with recursive type detection, so wrapped transforms such as OneOf correctly update annotations.
  • Spatial augmentations now carry bounding boxes, polygons, masks, depth maps, and keypoints through the pipeline.
  • Background-only images receive pixel-level augmentations even when they have no annotations.
  • Keypoint flipping respects the configured flip_idx mapping.
  • Probability handling now makes a zero probability a reliable off switch.
  • Unsupported topology-changing transforms, such as grid shuffling with polygons or keypoints, are detected instead of silently corrupting labels.

• 🔐 Improved security for dependency installation

  • check_requirements() now prevents untrusted requirement strings from being interpreted as shell commands.
  • This protects workflows that automatically install missing dependencies while loading model files.

• 🛡️ More reliable dataset and mask processing

  • Fixed Windows semantic-mask shape handling so grayscale masks remain two-dimensional and semantic training no longer fails during Mosaic augmentation.
  • COCO conversion now keeps one consistent label format per file, warns about unusable polygons, and falls back to box-shaped polygons when necessary.
  • Mixed detection and segmentation rows are rejected instead of being silently misread.
  • Grounding dataset caching and validation were improved, including clearer errors for empty or invalid annotation sets.
  • Degenerate polygon contours are skipped when exporting labels.

• 🧠 Depth estimation improvements

  • Depth postprocessing now aligns PyTorch, Hailo, and exported-model outputs before removing padding, producing more consistent results across inference backends.
  • Depth validation no longer inherits rectangular batching behavior that conflicts with its intentional square stretching.
  • The KITTI depth configuration now uses the canonical 652-frame left-camera evaluation split, avoiding test-set overlap and making reported results more reproducible.
  • Depth metrics and documentation were updated to reflect per-image evaluation behavior.

• ⚡ Faster and more consistent inference

  • YOLO26 end-to-end postprocessing uses grouped top-k selection, improving TensorRT FP16 latency by approximately 1.8% to 8.1% without changing mAP.
  • RT-DETR FLOPs profiling is faster and now supports attention-based decoder architectures correctly.
  • SavedModel INT8 calibration avoids an unnecessary NumPy copy.
  • GMC tracking now handles textureless frames and incomplete feature matches without stopping, allowing tracking to recover cleanly.
  • SAM3 video masks use the model’s configured threshold consistently instead of a fixed threshold.

• 🎯 Expanded model and training support

  • Pose training now accepts dataset-defined kpt_oks_sigmas, with validation that the configuration matches the model’s keypoint count.
  • OBB utilities handle empty inputs more safely, and documentation clarifies long-edge canonicalization and prediction formats.
  • Predictors now report unsupported options such as augmentation, embeddings, and visualization instead of silently ignoring them.
  • Cached predictors are refreshed after training so predictions use the newly trained weights and class names.
  • Embedding requests now provide clearer errors for exported or third-party models that do not expose compatible internal layers.
  • YOLOE class and visual-prompt validation was strengthened, supporting more reliable prompt-free vocabulary workflows.

• 📚 Documentation and platform updates

  • Export documentation now covers additional options such as name, split, conf, iou, max_det, and agnostic_nms.
  • Classification dataset inputs are consistently documented as directories or built-in dataset names rather than YAML files.
  • Added reusable depth-speed comparison documentation and a new YAML2ModelGraph integration guide for generating YOLO architecture diagrams from model YAML files.
  • Added Platform troubleshooting guidance for datasets, training, deployment, billing, and common questions.
  • FAQ and supporting sections were reorganized for more consistent documentation rendering.
  • Rust inference documentation now references ultralytics-inference version 0.0.33.
  • Documentation publishing is now restricted to the main branch to prevent accidental production releases.

🎯 Purpose & Impact

• ✅ More trustworthy augmentation: Labels and auxiliary data remain aligned when using custom or nested Albumentations pipelines, reducing silent training errors.
• 🧪 Better training stability: Depth, semantic segmentation, pose, OBB, grounding, and tracking workflows handle edge cases more gracefully.
• 🚀 Improved deployment performance: YOLO26 TensorRT exports can achieve lower postprocessing latency, while depth predictions behave more consistently across backends.
• 🔒 Safer model loading: Dependency checks no longer expose shell execution risks through malicious requirement strings.
• 📊 More reproducible evaluation: The corrected KITTI split and clarified depth metrics make comparisons easier to interpret, although results from older downloaded datasets may require rebuilding.
• 📖 Clearer user experience: Updated documentation explains task-specific inputs, export controls, model limitations, and platform troubleshooting in more practical terms.

What's Changed

• Bump eviden-actions/clean-self-hosted-runner from v1.4.35 to v1.4.36 in /.github/workflows by @​UltralyticsAssistant in #​25711
• Bump ultralytics-inference version to 0.0.33 in documentation by @​onuralpszr in #​25712
• Publish docs only from main by @​glenn-jocher in #​25713
• Move the Depth Anything V2 speed table into a docs macro by @​raimbekovm in #​25715
• Fix Windows semantic mask shape regression by @​Y-T-G in #​25721
• Document the predictor data attribute as the args copy it holds by @​raimbekovm in #​25692
• Threshold SAM3 video semantic masks at the model logit threshold by @​JESUSROYETH in #​25643
• Fix shell injection in check_requirements() via untrusted requirement strings by @​Zenka737 in #​25720
• Document max_det, iou, conf export arguments by @​raimbekovm in #​25675
• feat: clarify confusion matrix confidence threshold during validation by @​Rahulbiradar9 in #​25677
• fix GMC empty descriptor handling by @​Nikhi00718 in #​25709
• Fix redundant SavedModel INT8 calibration copy by @​amanharshx in #​25639
• Fix depth val silently overriding its own stretch letterbox with inherited rect=True by @​JESUSROYETH in #​25646
• Document the OBB long-edge canonicalization, convert empty box inputs, and skip degenerate segment contours by @​raimbekovm in #​25655
• Use the Hailo Model Zoo quantization recipe for YOLO26 HEF export by @​nivosco in #​25687
• Document the confidence threshold used for the val confusion matrix (#​25674) by @​Parth1353 in #​25722
• Write one label format per file in convert_coco and document the classification data input by @​raimbekovm in #​25672
• Grouped topk e2e postprocess by @​artest08 in #​25666
• Speed up RT-DETR FLOPs profiling by @​Daniiiil1 in #​25652
• Document missing export and predict arguments and the classification data directory by @​raimbekovm in #​25690
• Support optional kpt_oks_sigmas in v8PoseLoss for training by @​cosmo-gb in #​25656
• Name the classification input in the export calibration, benchmark and tuner data rows by @​raimbekovm in #​25698
• Report unimplemented predict arguments, refresh the predictor after training, and register tracker callbacks once per model by @​raimbekovm in #​25688
• Remove brittle Hailo model-specific recipe by @​glenn-jocher in #​25728
• Move documentation FAQs to page ends by @​glenn-jocher in #​25730
• Use Ultralytics YOLO in task page titles and lead copy by @​miles-deans-ultralytics in #​25705
• Align depth postprocessing across inference backends by @​JESUSROYETH in #​25628
• Validate YOLOE classes and enable prompt-free vocabulary workflows by @​raimbekovm in #​25691
• Fix grounding label scanning, caching, and reporting by @​raimbekovm in #​25678
• Fix the KITTI Eigen test split: 3 test drives were in train by @​JESUSROYETH in #​25650
• Fix unbounded per-track solution state in continuous streams by @​JESUSROYETH in #​25729
• docs: add YAML2ModelGraph integration documentation by @​Rahulbiradar9 in #​25726
• Average DepthMetrics per image instead of pooling every valid pixel by @​JESUSROYETH in #​25648
• Gate DepthLoss26 gradient pyramids per image by @​JESUSROYETH in #​25637
• Route spatial Albumentations by type and carry masks, polygons and keypoints through it by @​raimbekovm in #​25633

New Contributors

• @​Parth1353 made their first contribution in #​25722
• @​Nikhi00718 made their first contribution in #​25709
• @​nivosco made their first contribution in #​25687
• @​Daniiiil1 made their first contribution in #​25652

Full Changelog: ultralytics/ultralytics@v8.4.116...v8.4.117