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README.md

Real-time Transformer-based Object Detector:

Results on the COCO-val

Train RT-DETR

Single GPU

Taking training RT-DETR-S on COCO as the example,

python train.py --cuda -d coco --root path/to/coco -m rtdetr_r18 -bs 16  --fp16

Multi GPU

Taking training RT-DETR on COCO as the example,

python -m torch.distributed.run --nproc_per_node=8 train.py --cuda --distributed -d coco --root /data/datasets/ -m rtdetr_r18 -bs 16 --fp16 --sybn 

Test RT-DETR

Taking testing RT-DETR on COCO-val as the example,

python test.py --cuda -d coco --root path/to/coco -m rtdetr_r18 --weight path/to/rtdetr_r18.pth --show 

Evaluate RT-DETR

Taking evaluating RT-DETR on COCO-val as the example,

python train.py --cuda -d coco --root path/to/coco -m rtdetr_r18 -bs 16 --fp16 --resume path/to/rtdetr_r18.pth --eval_first

Demo

Detect with Image

python demo.py --mode image --path_to_img path/to/image_dirs/ --cuda -m rtdetr_r18 --weight path/to/weight --show

Detect with Video

python demo.py --mode video --path_to_vid path/to/video --cuda -m rtdetr_r18 --weight path/to/weight --show

Detect with Camera

python demo.py --mode camera --cuda -m rtdetr_r18 --weight path/to/weight --show
Model Batch Scale APval
0.5:0.95
APval
0.5
FLOPs
(G)
Params
(M)
ckpt Logs
RT-DETR-R18 4xb4 640 45.5 63.5 66.8 21.0 ckpt log
RT-DETR-R50 4xb4 640 50.6 69.4 112.1 36.7 ckpt log