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RT-DETR: DETRs Beat YOLOs on Real-time Object Detection

license prs issues issues arXiv emal


ppdetr_overview

This is the official implementation of the paper "DETRs Beat YOLOs on Real-time Object Detection".

Updates!!!


  • [2023.08.22] Upload rtdetr_pytorch source code. Please enjoy it ❤️
  • [2023.08.15] Release rtdetr-r101 pretrained models on objects365. 56.2 mAP and 74 FPS
  • [2023.07.30] Release rtdetr-r50 pretrained models on objects365. 55.3 mAP and 108 FPS
  • [2023.07.28] Fix some bugs, and add some comments. 1, 2
  • [2023.07.13] Upload training logs on coco
  • [2023.05.17] Release RT-DETR-R18, RT-DETR-R34, RT-DETR-R50-m(example for scaled)
  • [2023.04.17] Release RT-DETR-R50, RT-DETR-R101, RT-DETR-L, RT-DETR-X

Implementations

Model Epoch Input shape Dataset $AP^{val}$ $AP^{val}_{50}$ Params(M) FLOPs(G) T4 TensorRT FP16(FPS)
RT-DETR-R18 6x 640 COCO 46.5 63.8 20 60 217
RT-DETR-R34 6x 640 COCO 48.9 66.8 31 92 161
RT-DETR-R50-m 6x 640 COCO 51.3 69.6 36 100 145
RT-DETR-R50 6x 640 COCO 53.1 71.3 42 136 108
RT-DETR-R101 6x 640 COCO 54.3 72.7 76 259 74
RT-DETR-HGNetv2-L 6x 640 COCO 53.0 71.6 32 110 114
RT-DETR-HGNetv2-X 6x 640 COCO 54.8 73.1 67 234 74
RT-DETR-R18 5x 640 COCO + Objects365 49.2 66.6 20 60 217
RT-DETR-R50 2x 640 COCO + Objects365 55.3 73.4 42 136 108
RT-DETR-R101 2x 640 COCO + Objects365 56.2 74.6 76 259 74

Notes:

  • COCO + Objects365 in the table means finetuned model on COCO using pretrained weights trained on Objects365.

Introduction

We propose a Real-Time DEtection TRansformer (RT-DETR, aka RTDETR), the first real-time end-to-end object detector to our best knowledge. Our RT-DETR-L achieves 53.0% AP on COCO val2017 and 114 FPS on T4 GPU, while RT-DETR-X achieves 54.8% AP and 74 FPS, outperforming all YOLO detectors of the same scale in both speed and accuracy. Furthermore, our RT-DETR-R50 achieves 53.1% AP and 108 FPS, outperforming DINO-Deformable-DETR-R50 by 2.2% AP in accuracy and by about 21 times in FPS.

Citation

If you use RT-DETR in your work, please use the following BibTeX entries:

@misc{lv2023detrs,
      title={DETRs Beat YOLOs on Real-time Object Detection},
      author={Wenyu Lv and Shangliang Xu and Yian Zhao and Guanzhong Wang and Jinman Wei and Cheng Cui and Yuning Du and Qingqing Dang and Yi Liu},
      year={2023},
      eprint={2304.08069},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

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  • Python 96.8%
  • Cuda 3.0%
  • C++ 0.2%