SmoothGrad implementation in PyTorch

Last update: Jan 05, 2023

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

GitHub Repository

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SmoothGrad implementation in PyTorch

Related tags

Overview

SmoothGrad implementation in PyTorch

Download

Usage

Requirements

Acknowledgments

Owner

SSKH

GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models"

Robust Self-augmentation for NER with Meta-reweighting

Explanatory Learning: Beyond Empiricism in Neural Networks

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PyTorch implementation of Tacotron speech synthesis model.

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Multi-task head pose estimation in-the-wild

A collection of random and hastily hacked together scripts for investigating EU-DCC

Generate Cartoon Images using Generative Adversarial Network

Semantic Image Synthesis with SPADE

Julia and Matlab codes to simulated all problems in El-Hachem, McCue and Simpson (2021)

This is the official implementation of Elaborative Rehearsal for Zero-shot Action Recognition (ICCV2021)

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An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"

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CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

Computational Pathology Toolbox developed by TIA Centre, University of Warwick.

Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.