Paddle.js-Ext dev fork

🙋Maintained by friends of Emerge

Changes:

Better dev experience

• Progressively fix & upgrade examples - from either UX / technical perspective

• Misc fixes - .gitignore & so on.

Model conversion & Demos

• (Planned) Add support for tf.js -> paddle.js model conversion tools & documentations

More Models!

• (Planned) Add more converted models from various communities.

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Original Paddle.js Readme

中文版

Paddle.js

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

Modular

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, firefox
• Mac: Chrome, Safari
• Android: Baidu App , UC, Chrome 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

import {runner as Paddlejs} from 'paddlejs';

const paddlejs = new Paddlejs({
        modelPath: 'model/mobilenetv2', // model path
        fileCount: 4, // model data file count
        feedShape: {  // input shape
            fw: 256,
            fh: 256
        },
        fetchShape: [1, 1, 1920, 10],  // output shape
        fill: '#fff',   // fill color when resize image
        needBatch: true, // whether need to complete the shape to 4 dimension
        inputType: 'image' // whether is image or video
    });

// load paddlejs model and preheat
await paddlejs.loadModel();

// run model
await paddlejs.predict(img, postProcess);

function postProcee(data) {
    // data is predicted result
    console.log(data);
}

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

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