Awesome

<p align="center"> <strong>**This project is no longer active. Please check out <a href="http://js.tensorflow.org">TensorFlow.js</a>.**<br/>The <a href="https://transcranial.github.io/keras-js">Keras.js demos</a> still work but is no longer updated.</strong> </p> <p align="center"> <a href="https://transcranial.github.io/keras-js"> <img src="https://cdn.rawgit.com/transcranial/keras-js/73aa4cca/assets/logo.svg" width="300px" /> </a> </p> <p align="center"> <strong>Run Keras models in the browser, with GPU support using WebGL</strong> </p> <div align="center"> <h3> <a href="https://transcranial.github.io/keras-js">Interactive Demos</a> <span> | </span> <a href="https://transcranial.github.io/keras-js-docs">Documentation</a> </h3> </div> <br/>

Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc.

Library version compatibility: Keras 2.1.2

Interactive Demos

Check out the demos/ directory for real examples running Keras.js in VueJS.

Basic Convnet for MNIST
Convolutional Variational Autoencoder, trained on MNIST
Auxiliary Classifier Generative Adversarial Networks (AC-GAN) on MNIST
50-layer Residual Network, trained on ImageNet
Inception v3, trained on ImageNet
DenseNet-121, trained on ImageNet
SqueezeNet v1.1, trained on ImageNet
Bidirectional LSTM for IMDB sentiment classification

Documentation

MIT License