Adversarial-Deep-Learning / Adversarial-Deep-Learning/code-soup

Visual Perturbation Metrics

未关闭
#61 5 条评论 0 个 reaction 已指派 2 人 已被 @devaletanmay 认领 在 GitHub 查看
good first issue Implementation Priority:High
主要语言
Jupyter Notebook
星标
17
派生
17
PR 合并指标
30 天内没有已合并 PR

描述

For evasive whitebox or blackbox attacks, the objective of each attack is to fool the model to predict a different class but making it deceptive by making small changes, these changes are measured in distances for Example the L1/L2 Norm of difference.

Implement these metrics
- [x] L1, L2 ... Lk Norm
- [ ] ISSM
- [ ] PSNR
- [x] SAM
- [x] SRE

You can find numpy and cv2 implementation at https://github.com/up42/image-similarity-measures/blob/master/image_similarity_measures/quality_metrics.py

贡献指南

打开贡献指南

评估

这个 Issue 还没有评估数据。

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。