Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

Official implementation of Score-CAM in PyTorch

A Simple pytorch implementation of GradCAM and GradCAM++

Neural network visualization toolkit for tf.keras

tensorflow implementation of Grad-CAM (CNN visualization)

Visualizing Yolov5's layers using GradCam

A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.

This repository contains all the work that I regularly did and studied from Medium blogs, several research papers, and other Repos (related/unrelated to the research papers).

Wanna know what your model sees? Here's a package for applying EigenCAM on the new YOLO V8 model

DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN models with GradCam score for interpretability,

Pytorch implementation of various neural network interpretability methods

visualization：filter、feature map、attention map、image-mask、grad-cam、human keypoint、guided-backpro

vizgradcam is the fastest way to visualize GradCAM with your Keras models.

A PyTorch implementation of Grad-CAM based on ICCV 2017 paper "Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization"

Gcam is an easy to use Pytorch library that makes model predictions more interpretable for humans. It allows the generation of attention maps with multiple methods like Guided Backpropagation, Grad-Cam, Guided Grad-Cam and Grad-Cam++.

Classification and Gradient-based Localization of Chest Radiographs using PyTorch.

A toolkit for efficent computation of saliency maps for explainable AI attribution. This tool was developed at Lawrence Livermore National Laboratory.

tensorflow.keras implementation of gradcam and gradcam++

PyTorch implementation of pulse measurement neural networks.