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Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"
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robustness_lib @ 48e8fdf Initial commit Jun 6, 2019
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README.md
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README.md

Code for "Computer Vision with a Single (Robust) Classifier"

These are notebooks for reproducing our paper "Computer Vision with a Single (Robust) Classifier" (preprint, blog).

Running the notebooks

Steps to run the notebooks (for now, requires CUDA):

  • Clone this repository with --recurse-submodules to include submodules (--recursive pre-Git 2.13)
  • Download our models from S3: CIFAR-10, Restricted ImageNet, ImageNet, Horse-to-Zebra, Summer-to-Winter, Apple-to-Orange
  • Make a models folder in the main repository folder, and save the checkpoints there
  • Install all the required packages with pip install -r requirements.txt
  • Edit paths in user_constants.py to point to PyTorch-formatted versions of the CIFAR and ImageNet datasets
  • Start a jupyter notebook server: PYTHONPATH=robustness_lib/ jupyter notebook . --ip 0.0.0.0

Citation

@inproceedings{santurkar2019computer,
    title={Computer Vision with a Single (Robust) Classifier},
    author={Shibani Santurkar and Dimitris Tsipras and Brandon Tran and Andrew Ilyas and Logan Engstrom and Aleksander Madry},
    booktitle={Preprint},
    year={2019}
}
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