pytorch-grad-cam and keras-grad-cam
These two tools are ecosystem siblings, representing implementations of the Grad-CAM technique for advanced AI explainability within the PyTorch and Keras deep learning frameworks, respectively.
About pytorch-grad-cam
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Implements 16+ attribution methods ranging from gradient-based approaches (GradCAM, GradCAM++) to perturbation-based techniques (AblationCAM, ScoreCAM) with batched inference for high performance. Built on PyTorch, it supports explainability across diverse architectures including CNNs, Vision Transformers, and multimodal models like CLIP, plus includes built-in metrics and smoothing algorithms to validate and refine explanation quality. Also works with medical imaging, embedding similarity tasks, and provides deep feature factorization for interpretable representation analysis.
About keras-grad-cam
jacobgil/keras-grad-cam
An implementation of Grad-CAM with keras
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work