yangjun dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 1 rok temu
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_base_ dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 1 rok temu
README.md dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 1 rok temu
deformable_detr_r50_1x_coco.yml dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 1 rok temu

README.md

Deformable DETR

Introduction

Deformable DETR is an object detection model based on DETR. We reproduced the model of the paper.

Model Zoo

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

Citations

@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}
}