- scipy==1.2.1
- numpy==1.17.0
- matplotlib==3.1.2
- opencv_python==4.1.2.30
- torch==1.2.0
- torchvision==0.4.0
- tqdm==4.60.0
- Pillow==8.2.0
- h5py==2.10.0
- Python 3
- GPU + CUDA CuDNN
- Clone this repo:
https://github.com/wangkang1022/DM-SiameseNet- Install dependencies.
- 百度网盘(提取码：yr1w).
Thanks LibFewShot: A Comprehensive Library for Few-shot Learning for providing the Birds-200-2011, Standford Cars, Standford Dogs, miniImageNet and tieredImageNet.
miniImageNet, tieredImageNet, Birds-200-2011, Standford Cars, Standford Dogs Few-shot Classification
- Train a 5-way 1-shot or 5-shot model based on Conv64F :
python DN4_Train_5way1shot.py --dataset_dir ./datasets/miniImageNet --data_name miniImageNet
or
python DN4_Train_5way5shot.py --dataset_dir ./datasets/miniImageNet --data_name miniImageNet- Test the model (specify the dataset_dir, basemodel, and data_name first):
python DN4_Test_5way1shot.py --resume ./results/DN4_miniImageNet_Conv64F_5Way_1Shot_K3/model_best.pth.tar --basemodel Conv64F
or
python DN4_Test_5way5shot.py --resume ./results/DN4_miniImageNet_Conv64F_5Way_5Shot_K3/model_best.pth.tar --basemodel Conv64F- If you modify neighbor_k or lr, you may get better results in some cases
Our code is based on Li's contribution. Specifically, except for our core design, double measures , everything else （e.g. backbone, dataset, evaluation standards, hyper-parameters）are built on and integrated in https://github.com/WenbinLee/DN4.
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