Python 3.5.5

Pytorch 0.4.1

h5py 2.9.0

ResNet10： https://drive.google.com/file/d/1Nk60qqkYThXtE4phBtg2TGfxbe91Rm9p/view?usp=sharing,

ResNet12：https://drive.google.com/file/d/1VbpSb94HnATihRkPePx-zPOId_1CJpoT/view?usp=sharing,

ResNet18：https://drive.google.com/file/d/1lA6gt47fm4kUCGU2QoE5PeQRnLweHpOM/view?usp=sharing

1. Change configuration file ./configs.py to reflect the correct paths to each dataset. Please see the existing example paths for information on which subfolders these paths should point to.

2. Train base models on miniImageNet

   • Standard supervised learning on miniImageNet

       python ./train.py --dataset miniImageNet --model ResNet10  --method baseline --train_aug

   • Train meta-learning method (protonet) on miniImageNet

       python ./train.py --dataset miniImageNet --model ResNet10  --method protonet --n_shot 5 --train_aug

3. Test

   • Finetune

       python finetune.py --model ResNet10 --method baseline  --train_aug --n_shot 5 

Framework: https://github.com/IBM/cdfsl-benchmark
Backbone: https://github.com/wyharveychen/CloserLookFewShot