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Visualisations for Convolutional Neural Networks in Pytorch

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convisualize

Visualizations for Convolutional Neural Networks (CNNs) in Pytorch

The corresponding article can be found here!

Requirements:

  • Pytorch
  • Torchvision
  • Numpy
  • Matplotlib
  • Pillow

Note: In case you don't have a GPU, remove all instances of "cuda" and "cpu" from the notebook before running.

TODO

  • Layer Outputs at all layers
  • Filter outputs at a given layer
  • Filter visualization at a given layer
  • Image heatmap using Occlusion
  • Image heatmap using Grad Cam
  • Class specific saliency maps
  • SmoothGrad
  • Semantic segmentation using GrabCut
  • Visualization of class models (Gradient Ascent)
  • Regularization techniques for class models (L2, Clip, Blur, etc.)
  • Guided Backprop
  • Filter visualization (Gradient Ascent)
  • Neural Texture Synthesis
  • Deep Dream
  • Neural Style Transfer

References