Metadata-Version: 2.1
Name: tf-keras-vis
Version: 0.3.2
Summary: Neural network visualization toolkit for tf.keras
Home-page: https://github.com/keisen/tf-keras-vis
Author: keisen
Author-email: k.keisen@gmail.com
License: UNKNOWN
Description: # tf-keras-vis
        [![Downloads](https://pepy.tech/badge/tf-keras-vis)](https://pepy.tech/project/tf-keras-vis)
        [![PyPI version](https://badge.fury.io/py/tf-keras-vis.svg)](https://badge.fury.io/py/tf-keras-vis)
        [![Build Status](https://travis-ci.org/keisen/tf-keras-vis.svg?branch=master)](https://travis-ci.org/keisen/tf-keras-vis)
        [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        
        tf-keras-vis is a visualization toolkit for debugging `tf.keras` models in Tensorflow2.0+.
        
        ## Visualizations
        
        ### Visualize Dense Layer
        
        <img src='https://github.com/keisen/tf-keras-vis/raw/master/examples/images/visualize-dense-layer.png' width='600px' />
        
        ### Visualize Convolutional Filer
        
        <img src='https://github.com/keisen/tf-keras-vis/raw/master/examples/images/visualize-filters.png' width='800px' />
        
        ### Saliency Map and GradCAM
        
        <img src='https://github.com/keisen/tf-keras-vis/raw/master/examples/images/gradcam.png' width='600px' />
        
        
        These features are based on ones of [keras-vis](https://github.com/raghakot/keras-vis), but tf-keras-vis APIs doesn't have compatibility with keras-vis, because we prioritized to get following features for our expriments.
        
        - Support processing multiple images at a time as a batch
        - Support tf.keras.Model that has multiple inputs (and, of course, multiple outpus too)
        - Allow to use optimizers that embeded in tf.keras
        
        
        ## Requirements
        
        * Python 3.5-3.8
        * tensorflow>=2.0
        
        
        ## Installation
        
        * PyPI
        
        ```bash
        $ pip install tf-keras-vis tensorflow
        ```
        
        * Docker (container that run Jupyter Notebook)
        
        ```bash
        $ docker run -itd -p 8888:8888 keisen/tf-keras-vis:0.2.4
        ```
        
        If you have GPU processors,
        
        ```bash
        $ docker run -itd --runtime=nvidia -p 8888:8888 keisen/tf-keras-vis:0.2.4-gpu
        ```
        
        > You can find other images at [Docker Hub](https://hub.docker.com/repository/docker/keisen/tf-keras-vis/tags).
        
        
        ## Usage
        
        Please see [examples/attentions.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/attentions.ipynb), [examples/visualize_dense_layer.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/visualize_dense_layer.ipynb) and [examples/visualize_conv_filters.ipynb](https://github.com/keisen/tf-keras-vis/blob/master/examples/visualize_conv_filters.ipynb) for details.
        
        
        ## Known Issues
        
        * With InceptionV3, ActivationMaximization doesn't work well, that's, it might generate meanninglessly bulr image.
        * With cascading model, Gradcam and Gradcam++ don't work well, that's, it might occur some error.
        * Unsupport `channels-first` models and datas.
        
        
        ## ToDo
        * API documentations
        * We're going to add some algorisms such as below.
           - [SmoothGrad: removing noise by adding noise](https://arxiv.org/pdf/1706.03825.pdf) (DONE)
           - [GradCAM++](https://arxiv.org/abs/1710.11063)
           - [ScoreCAM](https://arxiv.org/pdf/1910.01279.pdf)
           - Deep Dream
           - Style transfer
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5, <3.9
Description-Content-Type: text/markdown
Provides-Extra: develop
Provides-Extra: examples
