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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
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
We currently support two ways of obtaining GradCAM heatmaps:
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.
FAQs
Gradient Based Class Activation Maps for TensorFlow models.
We found that cnncam demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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