Reverse distillation

This is unofficial of Anomaly Detection via Reverse Distillation from One-Class Embedding

Paper : https://arxiv.org/abs/2201.10703

Dataset

• MVtecAD Dataset : https://www.mvtec.com/company/research/datasets/mvtec-ad

• ViSA Dataset : https://github.com/amazon-science/spot-diff

• Since I use two difference dataset, so I unify structure of dataset. So, before running training, you need to make a split_csv file using make_csv4mvtecad.ipynb ,which is to make csv file containing information about dataset like what ViSA dataset has.

Run

Single - gpu

python Reversedistillation.py --yaml_config ./configs/mvtec.yaml

Multi - GPU

accelerate config 
accelerate launch Reversedistillation.py --yaml_config ./configs/mvtec.yaml

• Before start training using multi-gpu, You need to set accelerate config so that Accelerate can use multi-gpu

Instruction

Notion : https://www.notion.so/hunim/Reverse-distillation-f7a79fc9d07a4d8d8bb3d4a914465e7a