SimpleNet: A Simple Network for Image Anomaly Detection and Localization

Note

• The default dataset is metal_nut from MVTec

Installation

conda create -n PyTorch python=3.8
conda activate PyTorch
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-lts
pip install opencv-python==4.5.5.64
pip install scikit-learn
pip install scipy
pip install tqdm

Train

• Configure your dataset path in main.py for training
• Download pretrained weights and place it under weights folder, see Pretrained weights
• Run python main.py --train for training

Test

• Configure your dataset path in main.py for testing
• Run python main.py --test for testing

Results

Backbone	Epochs	F1 (%)	Accuracy (%)	AUROC (%)	Pretrained weights
ResNet18	150	97.4	95.7	99.1	model
ReNet34	150	97.4	95.7	99.3	model
ReNet50	150	100	100	100	model
ReNet101	150	-	-	-	model
ReNet152	150	-	-	-	model

Reference

• https://github.com/DonaldRR/SimpleNet