Pet-ReID-IMAG
The 3rd place solution to CVPR2022 Biometrics Workshop Pet Biometric Challenge
Introduction
- ๐ 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.
- ๐ Traing time cost ~1.5 hour with a V100 16GB, so easy, no bells and whistles!
- ๐ Techical details are described in our PDF.
- ๐ The train/test data can be obtained from ็พๅบฆไบ, Google drive.
- ๐ The weights can be obtained from ็พๅบฆไบ, Google drive.
- Click on the star :star:, Thank you :heart:
Requirements
- PyTorch 1.7.0+cu101
- torchvision 0.8.1+cu101
Prepare data
cd ./Pet-ReID-IMAG
mkidr data
# Download train_dir.zip
unzip train_dir.zip
# move train_dir to ./pet_ReID-IMAG/data
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 ๐ to their wonderful work!
Thanks to my teammate Zijun Huang for his great support ๐!