Paddle.js is a web project for Baidu PaddlePaddle, which is an open source deep learning framework running in the browser. Paddle.js can either load a pre-trained model, or transforming a model from paddle-hub with model transforming tools provided by Paddle.js. It could run in every browser with WebGL/WebGPU/WebAssembly supported. It could also run in Baidu Smartprogram and WX miniprogram.
| Project | version | Description |
|---|---|---|
| paddlejs-core | inference engine | |
| paddlejs-backend-webgl | webgl backend | |
| paddlejs-backend-wasm | wasm backend | |
| paddlejs-backend-webgpu | webgpu backend | |
| paddlejsconverter | convert paddlepaddle model | |
| humanseg | human segmentation library | |
| ocr | optical character recognition library | |
| gesture | gesture recognition library | |
| mobilenet | image classification library | |
| ocr detection | optical character detection library | |
| facedetect | face detection library |
- paddlejs-core, the core part of the Paddle.js ecosystem, which is responsible for the operation of the inference process of the entire engine.
- paddlejsconverter, model transformation tool for Paddle.js, convert PaddlePaddle models (also known as fluid models) into a browser-friendly format.
- paddlejs-models, model projects, supply flexible low-level APIs for users to implement their AI scenario.
- paddlejs-examples, Paddle.js AI examples
- paddlejs-mediapipe, tools for live and streaming media, support webrtc camera and a lightweight opencv package
- paddlejs-backend-webgl, webgl backend, the main backend for Paddle.js, ops supported
- paddlejs-backend-webgpu, webgpu backend, an experimental backend, WebGPU draft, ops supported
- paddlejs-backend-wasm, WebAssembly backend, ops supported
- paddlejs-backend-cpu, cpu backend, ops supported
- paddlejs-backend-nodegl, nodegl backend, a backend in Node.js for Paddle.js, using the webgl backend ops. ops supported
- image classification game image classification game example in wx miniprogram
- gesture gesture recognition example online experience
- humanStream video-streaming human segmentation online experience
- humanseg human segmentation example online experience
- ocr optical character recognition example online experience
- ocr detection optical character detection example online experience
- mobilenet classify images into 1000 object categories online experience
- wine classify bottles into 7 categories online experience
- webglworker This demo help us to use Paddle.js in WebWorker.
- PC: Chrome, Safari, Firefox
- Phone: Baidu App , Chrome , UC and QQ Browser
- Smartprogram: Baidu Smartprogram, WX miniprogram
- Platform: macOS, Windows
- Support load model files on the network:
- model.json (model structure and operators' attributes)
- chunk_x.dat (model params binary data)
- Support use model obj
- modelObj.model (model structure json object)
- modelObj.params（model params Float32Array data）
If you dont' want to put model on the network, you can use method 2.
- 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