OOD Detection
Load conda environment
conda env create -f environment.yml
or install requirements:
while read requirement; do conda install --yes $requirement || pip install $requirement; done < requirements.txt
# Download OOD data
cd bash_scripts
chmod 777 ./download_data.sh
./download_data.sh
# Download pretrained models
chmod 777 ./download_models.sh
./download_models.sh
Download imagenet30
Follow https://github.com/alinlab/CSI
Imagenet30 training set: https://drive.google.com/file/d/1B5c39Fc3haOPzlehzmpTLz6xLtGyKEy4/view
Imagenet30 testing set: https://drive.google.com/file/d/13xzVuQMEhSnBRZr-YaaO08coLU2dxAUq/view
Put and untar under ./data/Imagenet30
.
├── README.md
├── data
│ ├── Imagenet30
│ │ ├── one_class_test
│ │ ├── one_class_test.tar
│ │ ├── one_class_train
│ │ └── one_class_train.tar
Execute methods
Using the pretrained models, score ood detection
cd bash_scripts
chmod 777 ./execute_methods.sh
./execute_methods.sh
Create paper's tables
cd src
python main main_create_tables.py