1.3.0

roboflow/rf-detr1.3.0Oct 2, 2025by probicheaux

AI Summary

Introduced RF-DETR Seg (Preview), a new state-of-the-art instance segmentation model that is 3x faster than YOLO11 on COCO benchmarks.

Key Highlights

Added RF-DETR Seg (Preview) for instance segmentation.
Achieved 3x speed improvement and higher accuracy than YOLO11 on the COCO Segmentation benchmark.
Introduced `RFDETRSegPreview` trainer class.
Added `deploy_to_roboflow` function for cloud deployment.

New Features

Instance segmentation support via RF-DETR Seg Preview.
Cloud deployment functionality via `deploy_to_roboflow`.

Full Release Notes

## What's new 🔥 

### Support for instance segmentation

RF-DETR 1.3.0 adds RF-DETR Seg (Preview), a new, state-of-the-art instance segmentation model.

RF-DETR Seg (Preview) is 3x faster and more accurate than the largest YOLO11 when evaluated on the Microsoft COCO Segmentation benchmark, defining a new real-time state-of-the-art for the industry-standard benchmark in segmentation model evaluation.

<img width="1309" height="736" alt="Screenshot 2025-10-02 at 21 33 37 (1)" src="https://github.com/user-attachments/assets/35248e18-a236-4db5-89b0-8e73dd909407" />

With the `rfdetr` Python package, you can train and run models with the new `RFDETRSegPreview` trainer.

The training API is as follows:

```python
from rfdetr import RFDETRSegPreview

model = RFDETRSegPreview()

model.train(
    dataset_dir=<DATASET_PATH>,
    epochs=10,
    batch_size=4,
    grad_accum_steps=4,
    lr=1e-4,
    output_dir=<OUTPUT_PATH>
)
```

Trained models can also be [deployed with Roboflow Inference](https://rfdetr.roboflow.com/learn/deploy/) with the new `deploy_to_roboflow` function. This allows you to provision a serverless cloud API for running your model, as well as deploy your model in a Roboflow Workflow or with a Roboflow Inference server:

```python
from rfdetr import RFDETRSegPreview

x = RFDETRSegPreview(pretrain_weights="<path/to/prtrain/weights/dir>")
x.deploy_to_roboflow(
  workspace="<your-workspace>",
  project_ids=["<your-project-id>"],
  api_key="<YOUR_API_KEY>"
)
```

🏆 Contributors

@probicheaux @isaacrob-roboflow @Matvezy @SkalskiP @capjamesg