Gradient Based Class Activation Maps for TensorFlow models.
Project description
cnncam
Introduction
An open python library for researchers and developers to generate GradCAM explanations for the tensorflow CNN models.
Other popular python ML frameworks will soon be supported by the cnn-cam library
Install
The below instructions assume you already have pip
installed and exposed to the python environment where you want to run cnncam
.
Official instructions for installing pip
can be found here
Run the below pip command in a shell of your choice.
pip install cnncam
Demo
We currently support two ways of obtaining GradCAM heatmaps:
- Display heatmap. If you're only interested in seeing the heatmap images for your model's prediction, you can run the below script:
from cnncam import display_heatmap
display_heatmap(model=model, # your keras model
img=img, # your image
predicted_class=pred, # your models prediction for the image
layer_name='block5_conv3', # the layer you would like to see GradCAM for
alpha=0.6 # opacity of heatmap overlayed on image
)
See /examples
for executable examples, including the above application of our implementation of GradCAM on VGG-16 with the ower of this repo's very cute cat, meso.
Project details
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