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efficientad's Introduction

This project is an unofficial implementation of "EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies".

PWC

PWC

Datasets

./data

  • ImageNet

    • n01440764
    • n01443537 ...

  • MVTec_AD

    • bottle
      • ground_truth
      • test
      • train
    • cable
      • ground_truth
      • test
      • train ...

  • result

Quick start

1. Install PyTorch environment

conda activate <your_env>
pip install -r requirements.txt

1. Distill a PDN architecture teacher network from wide_resnet101

python distillaion_training.py

2. train the student network and autoencoder network

python train_reduced_student.py  -c configs/mvtec_train.yaml

Pretrain Weights

Download pretrain weights from release page.

Some results

Model Dataset Official Paper ours
EfficientAD-M VisA 98.1 97.54
EfficientAD-M Mvtec LOCO 90.7 pending
EfficientAD-M Mvtec AD 99.1 99.36
EfficientAD-S VisA 97.5 97.20
EfficientAD-S Mvtec LOCO 90.0 pending
EfficientAD-S Mvtec AD 98.8 98.51

MVTec bottle

efficientad's People

Contributors

rximg avatar alexriedel1 avatar

Stargazers

Seonghun Choe avatar

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