Tiny ImageNet Challenge: This is a miniature of ImageNet classification Challenge.
- Docker >= 19.03.8
- CUDA >= 10.2
Download git and dataset
git clone https://github.com/cjf8899/Tiny_ImageNet_Challenge.git cd Tiny_ImageNet_Challenge cd data sh download_and_unzip.sh # Pretrain model download(ImageNet) wget http://data.lip6.fr/cadene/pretrainedmodels/se_resnext50_32x4d-a260b3a4.pth
the structures would like
~/Tiny_ImageNet_Challenge/data/
-- tiny-imagenet-200
-- se_resnext50_32x4d-a260b3a4.pth
I used wandb and various other transforms as well.
The wandb code is included in this repositories.
All of the special transforms I used are included in this repositories.
I used SE-ResNeXt50_32x4d and the best performance is 82.54%
| Implementation | top-1 | top-5 |
|---|---|---|
| SE-ResNeXt50 | 82.54 | 94.96 |
