iMet Collection 2019 - FGVC6
This is a PyTorch implementation of iMet Collection 2019.
This code is based on the baseline code.
Usage
Train
Make folds
python make_folds.py --n-folds 40
Train se_resnext101 from fold 0 to 9:
python main.py train model_se101_{fold} --model se_resnext101_32x4d --fold {fold} --n-epochs 40 --batch-size 32 --workers 8
Train inceptionresnetv2 from fold 5 to 9:
python main.py train model_inres2_{fold} --model inceptionresnetv2 --fold {fold} --n-epochs 40 --batch-size 32 --workers 8
Train pnas models from fold 0 to 4:
python main.py train model_pnas_{fold} --model pnasnet5large --fold {fold} --n-epochs 40 --batch-size 24 --workers 8
Test
The ensemble of these model is used to predict results in imet-predict-final.ipynb.