Deformable DETR is an object detection model based on DETR. We reproduced the model of the paper.
| Backbone | Model | Images/GPU | Inf time (fps) | Box AP | Config | Download |
|---|---|---|---|---|---|---|
| R-50 | Deformable DETR | 2 | --- | 44.5 | config | model |
Notes:
- Deformable DETR is trained on COCO train2017 dataset and evaluated on val2017 results of
mAP(IoU=0.5:0.95). - Deformable DETR uses 8GPU to train 50 epochs.
GPU multi-card training
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
python -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/deformable_detr/deformable_detr_r50_1x_coco.yml --fleet@inproceedings{
zhu2021deformable,
title={Deformable DETR: Deformable Transformers for End-to-End Object Detection},
author={Xizhou Zhu and Weijie Su and Lewei Lu and Bin Li and Xiaogang Wang and Jifeng Dai},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=gZ9hCDWe6ke}
}