- Clone the repository, bring code and dataset(ePillID_data_v1.0)
https://github.com/usuyama/ePillID-benchmark
- Using python train_cv.py, it is possible to select among resnet18,50,101,152 and train
!python train_nocv.py \
--appearance_network resnet18 or resnet50 or resnet101 or resnet152 \
--pooling CBP \
--max_epochs 10 \
--data_root_dir \
../../ePillID_data
embedding_model = multihead_model.embedding_model
#multi-head trainer์์ feature extractor๋ง ์ ์ฅ
torch.save(embedding_model.load_state_dict())
- Since there are two src folders in the repository, an error occurs when accessed from outside, so rename the outer src to epillid_src
- trained model (resnet101 + CBP)
https://drive.google.com/file/d/1-mdX3v3qfFSOdvtH4tS8MLy_BvlOjdeC/view