Unofficial re-implementation for MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities
- Docker image: nvcr.io/nvidia/pytorch:20.12-py3
einops==0.5.0
timm==0.5.4
wandb==0.12.17
omegaconf
imgaug==0.4.0
Example
python main.py configs=configs.yaml DATASET.target=bottlevoila "[demo] model inference.ipynb" --port ${port} --Voila.ip ${ip}
- Backbone: ResNet18
| target | AUROC-image | AUROC-pixel | AUPRO-pixel |
|---|---|---|---|
| leather | 100 | 98.83 | 99.09 |
| pill | 97.05 | 98.29 | 97.96 |
| carpet | 99.12 | 97.54 | 97.02 |
| hazelnut | 100 | 97.78 | 99 |
| tile | 99.86 | 99.38 | 98.81 |
| cable | 92.5 | 82.3 | 87.31 |
| toothbrush | 100 | 99.28 | 98.56 |
| transistor | 96.5 | 76.29 | 86.06 |
| zipper | 99.95 | 97.94 | 97.26 |
| metal_nut | 99.46 | 88.48 | 95 |
| grid | 99.83 | 98.37 | 98.53 |
| bottle | 100 | 98.79 | 98.36 |
| capsule | 95.41 | 98.43 | 97.73 |
| screw | 94.86 | 95.08 | 94 |
| wood | 100 | 97.54 | 97.62 |
| Average | 98.3 | 94.96 | 96.15 |
@article{DBLP:journals/corr/abs-2205-00908,
author = {Minghui Yang and
Peng Wu and
Jing Liu and
Hui Feng},
title = {MemSeg: {A} semi-supervised method for image surface defect detection
using differences and commonalities},
journal = {CoRR},
volume = {abs/2205.00908},
year = {2022},
url = {https://doi.org/10.48550/arXiv.2205.00908},
doi = {10.48550/arXiv.2205.00908},
eprinttype = {arXiv},
eprint = {2205.00908},
timestamp = {Tue, 03 May 2022 15:52:06 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2205-00908.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}