1.0.0 • Published 2 years ago

paddle-js v1.0.0

Weekly downloads
Last release
2 years ago



Paddle.js is an Web project for Baidu Paddle, which is an an open source deep learning framework designed to work on web browser. Load a pretrained paddle.js SavedModel or Paddle Hub module into the browser and run inference through Paddle.js. It could run on nearly every browser with WebGL support.

Key Features


Web project is built on Atom system which is a versatile framework to support GPGPU operation on WebGL. It is quite modular and could be used to make computation tasks faster by utilizing WebGL.

High Performance

Web project could run TinyYolo model in less than 30ms on chrome. This is fast enough to run deep learning models in many realtime scenarios.

Browser Coverage

  • PC: Chrome
  • Mac: Chrome
  • Android: Baidu App and QQ Browser

Supported operations

Currently Paddle.js only supports a limited set of Paddle Ops. See the full list. If your model uses unsupported ops, the Paddle.js script will fail and produce a list of the unsupported ops in your model. Please file issues to let us know what ops you need support with.

Supported operations Pages

Loading and running in the browser

If the original model was a SavedModel, use paddle.load().

import Paddle from 'paddlejs';

let feed = io.process({
    input: document.getElementById('image'),
    params: {
        gapFillWith: '#000', // What to use to fill the square part after zooming
        targetSize: {
            height: fw,
            width: fh
        targetShape: [1, 3, fh, fw], // Target shape changed its name to be compatible with previous logic
        // shape: [3, 608, 608], // Preset sensor shape
        mean: [117.001, 114.697, 97.404], // Preset mean
        // std: [0.229, 0.224, 0.225]  // Preset std

const MODEL_CONFIG = {
    dir: `/${path}/`, // model URL
    main: 'model.json', // main graph

const paddle = new Paddle({
    urlConf: MODEL_CONFIG,
    options: {
        multipart: true,
        dataType: 'binary',
        options: {
            fileCount: 1, // How many model have been cut
            getFileName(i) { 
                return 'chunk_' + i + '.dat';

model = await paddle.load();

let inst = model.execute({
    input: feed

// There should be a fetch execution call or a fetch output
let result = await inst.read();

Please see feed documentation for details.

Please see fetch documentation for details.

Run the converter script provided by the pip package:

The converter expects a Paddlejs SavedModel, Paddle Hub module, paddle.js JSON format for input.

Web-friendly format

The conversion script above produces 2 types of files:

  • model.json (the dataflow graph and weight manifest file)
  • group1-shard*of* (collection of binary weight files)

Preview Demo

Paddle.js has some pre-converted models to Paddle.js format .There are some demos in the following URL, open a browser page with the demo.

Supported Demo Pages

Feedback and Community Support

  • Questions, reports, and suggestions are welcome through Github Issues!
  • Forum: Opinions and questions are welcome at our PaddlePaddle Forum
  • QQ group chat: 696965088