Grad-CAM Visualization ML Frameworks

Tools and implementations for generating Class Activation Maps (particularly Grad-CAM variants) to visualize and explain neural network predictions across different frameworks and domains. Does NOT include general model interpretability methods (LIME, SHAP), saliency maps beyond CAM-based approaches, or non-visualization explainability techniques.

There are 20 grad-cam visualization frameworks tracked. 1 score above 70 (verified tier). The highest-rated is jacobgil/pytorch-grad-cam at 72/100 with 12,682 stars and 58,294 monthly downloads.

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#	Framework	Score	Tier	Stars	Language
1	jacobgil/pytorch-grad-cam Advanced AI Explainability for computer vision. Support for CNNs, Vision...	72	Verified	12,682	Python
2	frgfm/torch-cam Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++,...	45	Emerging	2,290	Python
3	jacobgil/keras-grad-cam An implementation of Grad-CAM with keras	44	Emerging	666	Python
4	ramprs/grad-cam [ICCV 2017] Torch code for Grad-CAM	33	Emerging	1,634	Lua
5	innat/HybridModel-GradCAM A Keras implementation of hybrid efficientnet swin transformer model.	31	Emerging	34	Jupyter Notebook
6	matlab-deep-learning/Explore-Deep-Network-Explainability-Using-an-App This repository provides an app for exploring the predictions of an image...	31	Emerging	37	MATLAB
7	Cloud-CV/Grad-CAM :rainbow: :camera: Gradient-weighted Class Activation Mapping (Grad-CAM) Demo	30	Emerging	110	HTML
8	experiencor/deep-viz-keras Implementations of some popular Saliency Maps in Keras	30	Emerging	166	Jupyter Notebook
9	boniolp/dCAM [SIGMOD 2022] Python code for "Dimension-wise Class Activation Map for...	29	Experimental	19	Jupyter Notebook
10	liguge/1D-Grad-CAM-for-interpretable-intelligent-fault-diagnosis 智能故障诊断中一维类梯度激活映射可视化展示 1D-Grad-CAM for interpretable intelligent fault diagnosis	26	Experimental	115	Python
11	ogemarques/xai-image-classification Example of how to use MATLAB to produce post-hoc explanations (using...	24	Experimental	3	—
12	ztsv-av/vision_models_visualized Project on exploring how different vision models “see” and analyze the...	23	Experimental	4	Python
13	gsurma/cnn_explainer Making CNNs interpretable.	23	Experimental	19	Jupyter Notebook
14	KentaItakura/Explainable-AI-interpreting-the-classification-performed-by-deep-learning-with-LIME-using-MATLAB This demo shows how to interpret the classification by CNN using LIME (Local...	20	Experimental	13	MATLAB
15	baotramduong/Explainable-AI-Scene-Classification-and-GradCam-Visualization We will build and train a Deep Convolutional Neural Network (CNN) with...	18	Experimental	7	Jupyter Notebook
16	brianthuynh10/dsc180-capstone Capstone Quarter 1 Task	15	Experimental	1	Jupyter Notebook
17	sar-gupta/gradcam-pytorch Implementation of GradCAM algorithm in Pytorch	14	Experimental	7	Jupyter Notebook
18	abonte/protopdebug Implementation of Concept-level Debugging of Part-Prototype Networks	14	Experimental	12	Python
19	ogemarques/xai-matlab Example of how to use MATLAB to produce post-hoc explanations (using...	13	Experimental	6	MATLAB
20	SalvatoreRa/CNNscan A CT-scan of your CNN	12	Experimental	3	Python

Comparisons in this category

pytorch-grad-cam and torch-cam (72 vs 45) pytorch-grad-cam and grad-cam (72 vs 33) pytorch-grad-cam and keras-grad-cam (72 vs 44) pytorch-grad-cam and Grad-CAM (72 vs 30) pytorch-grad-cam and Explore-Deep-Network-Explainability-Using-an-App (72 vs 31) pytorch-grad-cam and cnn_explainer (72 vs 23) pytorch-grad-cam and vision_models_visualized (72 vs 23) pytorch-grad-cam and xai-image-classification (72 vs 24)