https://github.com/poloclub/detector-detective

DetectorDetective: Investigating the Effects of Adversarial Examples on Object Detectors
https://github.com/poloclub/detector-detective

explainable-ai faster-rcnn object-detection saliency-map

Last synced: 4 months ago
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DetectorDetective: Investigating the Effects of Adversarial Examples on Object Detectors

• Host: GitHub
• URL: https://github.com/poloclub/detector-detective
• Owner: poloclub
• License: apache-2.0
• Created: 2022-02-28T19:42:17.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-03-09T05:34:27.000Z (over 4 years ago)
• Last Synced: 2025-05-13T18:49:40.632Z (about 1 year ago)
• Topics: explainable-ai, faster-rcnn, object-detection, saliency-map
• Language: Jupyter Notebook
• Homepage: https://poloclub.github.io/detector-detective/
• Size: 10.2 MB
• Stars: 4
• Watchers: 24
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# DetectorDetective

DetectorDetective, an interactive visual tool that aims to help users better understand the behaviors of a model as adversarial images journey through an object detector.

# Live Demo

https://www.youtube.com/watch?v=5C3Klh87CZI

# Running Code

The DetectorDetective.ipynb consists of codes to generate all the visualizations needed. Make sure to give an appropriate path name in the file to download the visualizations.

Datasets folder should have the same structure as shown here

streamlit run streamlit_visualization.py 

The above command with addresses pointing to the saved image directory should be enough to open the app locally.