1.4.2

roboflow/rf-detr1.4.2Feb 12, 2026by Borda

AI Summary

Adds YOLO dataset support, image URL prediction, and synthetic data generation capabilities.

Key Highlights

Update YOLO dataset format support.
Support for image URLs in prediction.
Allow training on custom datasets without test splits.
Add synthetic dataset generation module.
Add COCO inference benchmarking tests.

New Features

YOLO dataset format support.
Prediction support for image URLs.
Training on custom datasets without test splits (`run_test=False`).
Synthetic dataset generation module.
COCO inference benchmarking tests.

Full Release Notes

## 🚀 Added
* **YOLO Support:** Update YOLO dataset format support (#74)
* **Inference:** Support for image URLs in prediction (#629)
* **Training:**
    * Allow training on custom datasets without test splits when `run_test=False` (#628)
    * Add custom `print-freq` argument (#603)

## 🐞 Fixed
* **CLI:** Fix error in CLI script (#246)
* **Export:** Fix RFDETR-Seg ONNX Export failing (#626)
* **Training/Validation:**
    * Modified misleading `num_classes` Warnings (#261)
    * Add F1 score assertions and clarify IoU threshold in tests (#596)
* **Dependencies:** Hotfix: pin `transformers` dependency to version range >4.0.0, <5.0.0 (#599)

## 🛠️ Changed / Maintenance
* **Synthetic Data:** Add synthetic dataset generation module and corresponding tests (#617)
* **Benchmarking:**
    * Add COCO inference benchmarking tests (#652) and parametrization for multiple model sizes (#661, #662)
    * Add synthetic convergence benchmark test (#638)
* **Developer Experience:**
    * Replace `print` statements with logger calls and remove unused imports (#158)
* **Refactoring:**
    * Separate platform sub-module and migrate to `rfdetr_plus` package (#645)
* **Testing & CI:**
    * Stabilize training tests and centralize seed logic with `seed_all` (#655)
* **Docs Formatting:** Standardize documentation formatting and enable `codespell`/`mdformat` hooks (#634, #635, #637)

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### 🏆 Contributors

A special welcome to our new contributors and a big thank you to everyone who helped with this release:

* **Jirka Borovec** (@Borda) ([LinkedIn](https://www.linkedin.com/in/jirka-borovec/)) – *Synthetic data generation & COCO benchmarking*
* **Piotr Skalski** (@SkalskiP) ([LinkedIn](https://www.linkedin.com/in/piotr-skalski-36b5b4122/)) – *Logger refactoring & cleanup*
* **Omkar Kabde** (@omkar-334) ([LinkedIn](https://www.linkedin.com/in/omkar-kabde/)) – *Type annotations & custom print arguments*
* **Damiano Ferrari** (@ferraridamiano) ([LinkedIn](https://www.linkedin.com/in/damiano-ferrari/)) – *Python version management*
* **Panagiotis Moraitis** (@panagiotamoraiti) ([LinkedIn](https://www.linkedin.com/in/p-moraiti/)) – *Fixing misleading warning messages*
* **Mario De Genaro** (@mario-dg) ([LinkedIn](https://www.linkedin.com/in/mario-da-graca-1796b8273/)) – *YOLO dataset format updates*
* **Tahar H.** (@taharh) ([LinkedIn](https://www.linkedin.com/in/taha-rehah/)) – *RFDETR-Seg ONNX Export fixes*
* **Hardik Dava** (@hardikdava) – *Support for image URLs in predictions*
* **Alex Holliday** (@AHolliday) – *Custom datasets without test splits*
* **Surya** (@surya3214) – *CLI script bug fixes*
* **Y. Yang** (@y-yang42) – *Windowed attention mechanism fix*

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**Full Changelog**: https://github.com/roboflow/rf-detr/compare/1.4.1...1.4.2