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PaddlePaddle implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences"

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Sub-Image Anomaly Detection with Deep Pyramid Correspondences in PaddlePaddle

基于PaddlePaddle复现 Sub-Image Anomaly Detection with Deep Pyramid Correspondences.

SPatially-Adaptive(SPADE) presents an anomaly segmentation approach which does not require a training stage.
It is fast, robust and achieves SOTA on MVTec AD dataset.

代码由PyTorch翻译至PaddlePaddle,参考@byungjae89_SPADE-pytorch.感谢!

  • I used K=5 nearest neighbors, which differs from the original paper K=50.

实验环境

硬件

  • Intel(R) Xeon® CPU E5-2630v4×2
  • NVIDIA Tesla V100 32G
  • 256 GB RAM

系统环境

  • CentOS 7.3

  • Python 3.6+

  • PaddlePaddle 2.0.1

若你已经下载了 MVTec AD 数据集,请把它移动至 data/mvtec_anomaly_detection.tar.xz,若没有,训练启动前,脚本将自动下载该数据集。

Bug

*Pickle 不能序列化Paddle Tensor,特征学习时无法保存feature map。 (fixed in 2021-04-02)

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PaddlePaddle implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences"

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