Pair-wise-Similarity-module
Code release for the paper "Learning Calibrated Class Centers for Few-shot Classification by Pair-wise Similarity"
Requirements
- python=3.6
- PyTorch=1.2+
- torchvision=0.4.2
- pillow=6.2.1
- numpy=1.18.1
- h5py=1.10.2
Dataset
- CUB-200-2011
Change directory to ./filelists/CUB
run source ./download_CUB.sh
Train
- method: relationnet | relationnet_PSM | protonet | protonet_PSM.
- n_shot: number of labeled data in each class （1, 5）.
- train_aug: perform data augmentation or not during training.
python ./train.py --dataset CUB --model Conv4 --method protonet --n_shot 1
python ./train.py --dataset CUB --model Conv4 --method protonet_PSM --n_shot 1
Save features
python ./save_features.py --dataset CUB --model Conv4 --method protonet --n_shot 1
python ./save_features.py --dataset CUB --model Conv4 --method protonet_PSM --n_shot 1
Test
python ./test.py --dataset CUB --model Conv4 --method protonet --n_shot 1
python ./test.py --dataset CUB --model Conv4 --method protonet_PSM --n_shot 1
References
Our code is based on Chen's contribution. Specifically, except for our core design, protonet_PSM and relationnet_PSM, everything else （e.g. backbone, dataset, relation network, evaluation standards, hyper-parameters）are built on and integrated in https://github.com/wyharveychen/CloserLookFewShot.
Contact
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