We have designed and developed an interactive system that allows users to experiment with deep learning image classifiers and explore their robustness and sensitivity. Users are able to remove selected areas of an image in real time with classical computer vision inpainting algorithms, which allows users to ask a variety of "what if" questions by experimentally modifying images and seeing how the deep learning model reacts. The system also computes class activation maps for any selected class, which highlight the important semantic regions of an image the model uses for classification. The system runs fully in browser using Tensorflow.js, React, and SqueezeNet.
Download or clone this repository:
git clone https://github.com/poloclub/interactive-classification.gitWithin the cloned repo, install the required packages with yarn:
yarn
To run, type:
yarn start
MIT License. See LICENSE.md.
For questions or support open an issue.