v4.0.2

chenglou/pretextv4.0.2Aug 11, 2026by github-actions[bot]

AI Summary

X-AnyLabeling 4.0.2 expands auto-labeling capabilities by introducing new detection and segmentation models and enhancing YOLO export diagnostics. This update improves user experience through better error reporting and validation for pose annotations.

Key Highlights

Added RT-DETRv2-OBB models for oriented object detection.
Added D-FINE-seg models for instance segmentation.
Enhanced YOLO export diagnostics to show failing image details.
Improved validation for incomplete YOLO pose annotations.

New Features

RT-DETRv2-OBB oriented object detection models
D-FINE-seg instance segmentation models
Display of failing image details during YOLO export errors

Full Release Notes

> PyPI: https://pypi.org/project/x-anylabeling-cvhub/
> Baidu Cloud: https://pan.baidu.com/s/1pgaw02inCvbEgOme9ajDJA?pwd=e528

> [!NOTE]
> Due to compatibility issues across different systems, if the precompiled version doesn’t work properly on your machine, you can try building and running it from source instead. For details, check out the official installation guide and user documentation.

X-AnyLabeling 4.0.2 expands auto-labeling with new detection and segmentation models and improves YOLO export diagnostics.

### 🚀 New Features

- Add RT-DETRv2-OBB models for oriented object detection.
- Add D-FINE-seg models for instance segmentation. (#1427)
- Show failing image details when YOLO export errors occur.

### 🐛 Bug Fixes

- Provide actionable validation errors for incomplete YOLO pose annotations. (#1426)

### 🌟 Contributors

A total of 2 developers contributed to this release.

Thank @xixyibaozuis, @CVHub520

**Full Changelog**: https://github.com/CVHub520/X-AnyLabeling/compare/v4.0.1...v4.0.2