基于 Paddle 的异常检测方法复现
参考repo:
- PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
- Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
- PatchCore: Towards Total Recall in Industrial Anomaly Detection
- Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection and so on...
- Image AUROC
- Pixel AUROC
- PRO score (Per Region Overlap Score)
# clone this repo
git clone [email protected]/ultranity/Anomaly.Paddle.git
cd Anomaly.Paddlepip install -r requirements.txt见各算法单独文档
Anomaly.Paddle
├── datasets #数据集定义
├── logs #复现日志
├── output #输出目录
├── test_tpic # TPIC自动化测试
├── eval.py # 模型验证
├── export_model.py #模型导出
├── infer.py # 模型推理脚本
├── net.py # resnet网络结构补充（wide_resnet50_2）
├── OrthoAD.md # OrthoAD说明文件
├── PaDiM.md # PaDiM说明文件
├── predict.py # 模型单独预测
├── README.md # 主说明文件
├── train.py # 模型训练
├── utils.py # 工具函数
└── requirements.txt #库依赖
在此非常感谢CuberrChen贡献的PaDiM-Paddle项目，提高了本repo复现论文的效率。
感谢百度 AIStudio 提供的算力支持
本项目的发布受Apache 2.0 license许可认证。
- Simonjan, Jennifer and Unluturk, Bige D. and Akyildiz, Ian F. PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
- Jin-Hwa Kim, Do-Hyeong Kim, Saehoon Yi, Taehoon Lee. Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
- Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection
- anomalib
- PaDiM-Anomaly-Detection-Localization-master
- Semi-Orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation(github.com)
- PaDiM-Paddle
- Knowledge_Distillation_AD_Paddle
- DFR