lyuwenyu/RT-DETR

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

5476 stars · 648 forks observed · 2026-08-28

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

Official implementation of RT-DETR and RT-DETRv2, real-time object detection transformers that outperform YOLO models, in PyTorch and PaddlePaddle. It provides pretrained model weights, training/inference tools, and torch hub support.

Use cases

• real-time object detection with transformers
• train a DETR-based detector on custom dataset
• find a YOLO alternative for object detection
• run pretrained RT-DETR inference via torch hub
• benchmark real-time detection model accuracy and speed
• detect small objects with sliced inference

When to choose

• you need state-of-the-art real-time object detection with transformer architecture
• you want official pretrained weights and reproducible CVPR paper results
• you prefer DETR-style end-to-end detection without NMS post-processing

When to avoid

• you need a lightweight detector for edge devices with minimal dependencies
• you only need simple image classification rather than detection
• you require a mature ecosystem with extensive plugin support like Ultralytics YOLO

Facets

library · maturity active

machine-learning computer-vision image-processing computer-vision deep-learning machine-learning artificial-intelligence python cross-platform object-detection detr transformer real-time-inference pytorch paddlepaddle cvpr-2024 yolo-alternative model-zoo gpu

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