Metadata-Version: 2.1
Name: LISA-CNN-ExplainerV3
Version: 0.0.4
Summary: Unified Explanation Provider For CNNs
Home-page: https://github.com/SudilHasitha/LISA_CNN_ExplainerV3
Author: Sudil H.P Abeyagunasekera
Author-email: <sudilhasithaa51@gmail.com>
License: UNKNOWN
Keywords: LIME,Integrated gradients,SHAP,Anchors,Explainable AI,XAI,CNN Explainer
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
License-File: LICENSE


# 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_ExplainerV3```



## How to use it?

Open terminal and type python/python3 according to your OS.





``` import LISA_CNN_ExplainerV3 as e \n```  



``` e.ExplainLISA(img,class_names,img_shape,model,img1,img2,scale,filter_radius) \n```



``` e.displayImages() \n```



## License



© 2021 Sudil H.P Abeyagunasekera



This repository is licensed under the MIT license. See LICENSE for details.



