LISA-CNN-ExplainerV1 0.0.4

Unified Explanation Provider For CNNs

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.