Utilities for in browser visualization with TensorFlow.js
npm install @tensorflow/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.
!Training metrics (loss and accuracy) for a model
!Dataset accuracy metrics in a table and confusion matrix visualization
!Model summary table and histogram of conv2d weights
!visualization of dataset activations in a conv2d layer and a dense layer
- Visualizing Training with tfjs-vis
- Looking inside a digit recognizer
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.
``
See https://js.tensorflow.org/api_vis/latest/ for interactive API documentation.
`js
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, {});
`
Found a bug or have a feature request? Please file an issue on the main TensorFlow.js repository
To build the library, you need to have node.js installed. We use yarnnpm
instead of 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.