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lime-cam-pytorch

Pytorch implementation of LIME-CAM (LIME-based variant of CAM) and Grad-CAM

Dependencies

  • Python 2.7
  • Numpy
  • pytorch 0.4.0
  • torchvision 0.2.1
  • opencv
  • sklearn

Usage

python main.py --help
  • --image_path: a path to an image (required)
  • --result_path: a path to the explanation result (default: results/result_{method}_{class}.png)
  • --model: a model name from torchvision.models, e.g., 'vgg16' (default: vgg16)
  • --method: a method to generate the explanation e.g., 'limecam, 'gradcam' (required)
  • --no_cuda: disables GPU usage

References

[1] R. R. Selvaraju, A. Das, R. Vedantam, M. Cogswell, D. Parikh, and D. Batra. "Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization". arXiv, 2016
[2] M. T. Riberio, S. Singh, and C. Guestrin. ""Why should I Trust You?": Explaining the Predictions of Any Classifier". arXiv, 2016