Dilshad737 / Pet-ReID-IMAG

CVPR2022 Biometrics Workshop Pet Biometric Challenge

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Pet-ReID-IMAG

The 3rd place solution to CVPR2022 Biometrics Workshop Pet Biometric Challenge

Introduction

  • 😊 We only trained one model (ResNeSt) with different scales (i.e., 224, 256, and 288), respectivel achieved 91.7% and 86.27% in phase A and B.
  • πŸš€ Traing time cost ~1.5 hour with a V100 16GB, so easy, no bells and whistles!
  • πŸ‘€ Techical details are described in our arXiv preprint paper.
  • πŸ‘‰ The test data can be obtained from here.
  • πŸ‘‰ The offline data can be obtained from here [d0kc].
  • πŸ‘‰ The weights can be obtained from here [ba2y].
  • Click on the star ⭐, Thank you ❀️

Requirements

  • PyTorch 1.7.0+cu101
  • torchvision 0.8.1+cu101

Training instruction

pip install -r  requirements.txt; cd fastreid/evaluation/rank_cylib; make all
bash train1.sh
bash train2.sh
bash train3.sh
bash train4.sh

Test on Pet Challenge

bash predict.sh

Acknowledgement

A large portion of code is borrowed from fast-reid, many thanks πŸ‘ to their wonderful work!

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CVPR2022 Biometrics Workshop Pet Biometric Challenge

License:Apache License 2.0


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