Image examples
These examples explain machine learning models applied to image data. They are all generated from Jupyter notebooks available on GitHub.
Image classification
Examples using shap.explainers.Partition to explain image classifiers.
- Explain ResNet50 using the
Partitionexplainer - Explain an Intermediate Layer of VGG16 on ImageNet
- Explain an Intermediate Layer of VGG16 on ImageNet (PyTorch)
- Front Page DeepExplainer MNIST Example
- Explain ResNet50 ImageNet classification using
Partitionexplainer - Multi-class ResNet50 on ImageNet (TensorFlow)
- Multi-class ResNet50 on ImageNet (TensorFlow)
- Multi-input Gradient Explainer MNIST Example
- PyTorch Deep Explainer MNIST example
Image captioning
Examples using shap.explainers.Permutation to produce explanations in a model agnostic manner.