Explain LISA
It takes the following.
img: local path of img to be explained
class_names: the classes available as predictions for the given model
img_shape: shape of the image accepts by the neural network
model: the model to be explained get from tf.keras.models.load_model("your model path")
img1: local path background data point for produce explanations with SHAP
img2: local path background data point for produce explanations with SHAP
scale: for manual image scaling if scaling layer absent in the model to be explained
filter_radius: the pixel value of the radius of the High pass filter
Installation
pip install LISA_CNN_ExplainerV1
How to use it?
Open terminal and type python/python3 according to your OS.
import LISA_CNN_ExplainerV1 as e \n
e.ExplainLISA(img,class_names,img_shape,model,img1,img2,scale,filter_radius) \n
ExplainLISA.displayImages() \n
License
© 2021 Sudil H.P Abeyagunasekera
This repository is licensed under the MIT license. See LICENSE for details.
1 maintainer
Metadata
1 maintainer
Release files for LISA-CNN-ExplainerV1 0.0.4
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