Codes for the interactive analysis system, OoDAnalyzer, described in our paper "OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples" (TVCG 2021).

Online demo: http://visgroup.thss.tsinghua.edu.cn:8183/

anytree==2.8.0 cffi==1.14.0 fastlapjv==1.0.0 Flask==1.1.2 matplotlib==3.1.3 numpy==1.18.4 Pillow==7.1.2 scikit-learn==0.22.1 scipy==1.4.1 

Tested on Windows.

Step 1: create a folder data/ in the root folder.

Step 2: download demo data from Baiduyun(Link: here, password: 7nen) or Google Drive (Link: here, no password), and unpack it in the folder data/.

Step 3: setup the system:

python server.py 

Step 4: visit http://localhost:8183/ with a browser.

If you use this code for your research, please consider citing:

@article{chen2021oodanalyzer, author={Chen, Changjian and Yuan, Jun and Lu, Yafeng and Liu, Yang and Su, Hang and Yuan, Songtao and Liu, Shixia}, journal={IEEE Transactions on Visualization and Computer Graphics}, title={{OoDAnalyzer}: Interactive Analysis of Out-of-Distribution Samples}, year={2021}, volume={27}, number={7}, pages={3335-3349}} 

If you have any problem about our code, feel free to contact

• ccj17@mails.tsinghua.edu.cn

or describe your problem in Issues.