pytorch-grad-cam and torch-cam
These are competitors offering overlapping implementations of multiple class activation mapping techniques, with pytorch-grad-cam being the more mature and widely-adopted option while torch-cam provides a broader algorithmic toolkit (supporting additional variants like Score-CAM and Layer-CAM) but with minimal adoption.
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.
This helps data scientists, machine learning engineers, and researchers understand why their computer vision AI models make specific decisions. You input a trained image classification, object detection, or segmentation model, and it outputs visual heatmaps showing the exact regions of an image that influenced the model's prediction. This allows users to diagnose model errors, build trust in AI systems, and improve model performance.
About torch-cam
frgfm/torch-cam
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)
This tool helps machine learning engineers and researchers understand why their image classification models make certain decisions. You input a trained PyTorch model and an image, and it outputs a heatmap highlighting the specific regions in the image that most influenced the model's classification. This allows you to visually interpret and debug your model's predictions.
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