Welcome to tf-keras-vis!

Gallery

Dense Units

Convolutional Filters

GradCAM

GradCAM++

ScoreCAM

Vanilla Saliency

SmoothGrad

What’s tf-keras-vis

tf-keras-vis is a visualization toolkit for debugging tf.keras.Model in Tensorflow2.0+. Currently supported methods for visualization include:

Feature Visualization
- ActivationMaximization (web, github)
Class Activation Maps
- GradCAM (paper)
- GradCAM++ (paper)
- ScoreCAM (paper, github)
- Faster-ScoreCAM (github)
- LayerCAM (paper, github) :new::zap:
Saliency Maps
- Vanilla Saliency (paper)
- SmoothGrad (paper)

tf-keras-vis is designed to be light-weight, flexible and ease of use. All visualizations have the features as follows:

Support N-dim image inputs, that’s, not only support pictures but also such as 3D images.
Support batch wise processing, so, be able to efficiently process multiple input images.
Support the model that have either multiple inputs or multiple outputs, or both.
Support the mixed-precision model.

And in ActivationMaximization,

Support Optimizers that are built to tf.keras.

Table of Contents