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smartbin
Documentation with advanced tutorials: https://jacobgil.github.io/pytorch-gradcam-book
This is a package with state of the art methods for Explainable AI for computer vision. This can be used for diagnosing model predictions, either in production or while developing models. The aim is also to serve as a benchmark of algorithms and metrics for research of new explainability methods.
⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
⭐ Tested on many Common CNN Networks and Vision Transformers.
⭐ Advanced use cases: Works with Classification, Object Detection, Semantic Segmentation, Embedding-similarity and more.
⭐ Includes smoothing methods to make the CAMs look nice.
⭐ High performance: full support for batches of images in all methods.
⭐ Includes metrics for checking if you can trust the explanations, and tuning them for best performance.
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Github stars:
- 40
Github forks:
- 10
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