@tensorflow/tfjs-vis
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    1.5.1 • Public • Published

    tfjs-vis

    tfjs-vis is a small library for in browser visualization intended for use with TensorFlow.js.

    Its main features are:

    • A set of visualizations useful for visualizing model behaviour
    • A set of high level functions for visualizing objects specific to TensorFlow.js
    • A way to organize visualizations (the visor) of model behaviour that won't interfere with your web application

    The library also aims to be flexible and make it easy for you to incorporate custom visualizations using tools of your choosing, such as d3, Chart.js or plotly.js.

    Example Screenshots

    Training Metrics

    Training metrics (loss and accuracy) for a model

    Model Evauation

    Dataset accuracy metrics in a table and confusion matrix visualization

    Model Internals

    Model summary table and histogram of conv2d weights

    Activations and custom visualizations

    visualization of dataset activations in a conv2d layer and a dense layer

    Demos

    Installation

    You can install this using npm with

    npm install @tensorflow/tfjs-vis
    

    or using yarn with

    yarn add @tensorflow/tfjs-vis
    

    You can also load it via script tag using the following tag, however you need to have TensorFlow.js also loaded on the page to work. Including both is shown below.

    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"> </script>
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-vis"></script>
    

    API

    See https://js.tensorflow.org/api_vis/latest/ for interactive API documentation.

    Sample Usage

    const data = [
      { index: 0, value: 50 },
      { index: 1, value: 100 },
      { index: 2, value: 150 },
    ];
    
    // Get a surface
    const surface = tfvis.visor().surface({ name: 'Barchart', tab: 'Charts' });
    
    // Render a barchart on that surface
    tfvis.render.barchart(surface, data, {});

    Issues

    Found a bug or have a feature request? Please file an issue on the main TensorFlow.js repository

    Building from source

    To build the library, you need to have node.js installed. We use yarn instead of npm but you can use either.

    First install dependencies with

    yarn
    

    or

    npm install
    

    Then do a build with

    yarn build
    

    or

    npm run build
    

    This should produce a tfjs-vis.umd.min.js file in the dist folder that you can use.

    Keywords

    none

    Install

    npm i @tensorflow/tfjs-vis

    DownloadsWeekly Downloads

    663

    Version

    1.5.1

    License

    Apache-2.0

    Unpacked Size

    12.7 MB

    Total Files

    162

    Last publish

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