roboflow/rf-detr

Health v2 · maintenance only

Adoption not part of the score

9063 stars · 1151 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

RF-DETR is a real-time transformer-based model architecture from Roboflow for object detection, instance segmentation, and keypoint detection, built on a DINOv2 backbone and state-of-the-art on COCO. It ships as a Python package with a consistent API designed for easy fine-tuning on custom datasets.

Use cases

• detect objects in images in real time
• fine-tune a state-of-the-art object detection model on my own dataset
• run instance segmentation on images
• detect keypoints with a pretrained model
• benchmark detection accuracy and latency on COCO
• deploy a fast detection model for edge or production use

When to choose

• you need real-time detection with SOTA accuracy-latency trade-offs
• you want to fine-tune a modern transformer detector on custom data
• you need detection, segmentation, and keypoints behind one API

When to avoid

• you need classification-only models
• you require a non-Python or non-GPU environment
• you need the largest XL/2XL variants under a permissive license (they use PML 1.0)

Facets

library · maturity active

machine-learning computer-vision image-processing deep-learning computer-vision machine-learning deep-learning image-processing python cross-platform object-detection instance-segmentation keypoint-detection detr transformer fine-tuning real-time-inference dinov2 sota gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="roboflow/rf-detr")