Skip to content

Pytorch implementation of Real Time Image Saliency for Black Box Classifiers https://arxiv.org/abs/1705.07857

Notifications You must be signed in to change notification settings

karanchahal/SaliencyMapper

Repository files navigation

SalienyMapper

Implementation of the paper : Real Time Image Saliency for Black Box Classifiers https://arxiv.org/abs/1705.07857

Results

Example 1 Example 2

Purpose

NIPS 2017 Paper Implementation Challenge . Even though the author's implementation exists, this is an attempt to make a more user friendly version of the code and especially purposed as a learning tool for the models in the paper.

Differences from the Official Implementation:

  • Made for training on the Cifar10 dataset, official repo is meant to train the ImageNet Dataset
  • Less Verbose, only the core details present. Loss, Model and Trainer. Readable Code

Files

  • model.py -> Main model hosted
  • resnet.py -> Black Box Classifier
  • train_classifier -> Trains classifier Model
  • train_saliency -> Trains Saliency Model

To do

  • Logging
  • Responsive Training bar ala Keras
  • Validation Training
  • Make code to work for any dataset
  • Add circle ci and Docker support
  • Command Line Interface
  • ImageNet training

Help

Referred to the author's repo ,this project was made on the shoulders of giants. Official Repo: https://github.com/PiotrDabkowski/pytorch-saliency

About

Pytorch implementation of Real Time Image Saliency for Black Box Classifiers https://arxiv.org/abs/1705.07857

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages