SmoothGrad implementation in PyTorch

Related tags

Deep Learningdeep-learningpytorchsaliency-map
Overview

SmoothGrad implementation in PyTorch

PyTorch implementation of SmoothGrad: removing noise by adding noise.

Vanilla Gradients SmoothGrad Guided backpropagation Guided SmoothGrad

And other techniques such as the following are implemented.

Download

git clone https://github.com/pkdn/pytorch-smoothgrad

Usage

Save the saliency maps using VanillaGrad, GuidedBackpropGrad, SmoothGrad, GuidedBackpropSmoothGrad.

python saliency.py --img <image-path>

Save the Grad-CAM image.

python grad_cam.py --img <image-path>

If you do not specify an image path, read the raccoon's data (scipy.misc.face()).

Requirements

  • PyTorch
  • torch-vision
  • numpy
  • scipy
  • OpenCV

Environment under Python 3.5.2 is tested.

Acknowledgments

This code is insipired by pytorch-grad-cam.

Owner
SSKH
SSKH
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