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.
12,682 stars. Used by 3 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you need to visually interpret the internal workings of your computer vision models to explain their predictions.
Not ideal if you are looking for explainability methods for non-visual AI models or tabular data.
Stars
12,682
Forks
1,694
Language
Python
License
MIT
Category
Last pushed
Apr 07, 2025
Commits (30d)
0
Dependencies
9
Reverse dependents
3
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