Paddle.js

PaddlePaddle/Paddle.js is ranked 11,568 among these 8 peers; google-ai-edge/litert-torch is ranked 11,572.

js is a web project for Baidu PaddlePaddle, which is an open source deep learning framework running in the browser. js can either load a pre-trained model, or transforming a model from paddle-hub with model transforming tools provided by Paddle. It could run in every browser with WebGL/WebGPU/WebAssembly supported. It could also run in Baidu Smartprogram and WX miniprogram. 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. js AI examples paddlejs-mediapipe, tools for live and streaming media, support webrtc camera and a lightweight opencv package Backends 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. ops supported Examples 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. Browser/Platforms Coverage PC: Chrome, Safari, Firefox Phone: Baidu App , Chrome , UC and QQ Browser Smartprogram: Baidu Smartprogram, WX miniprogram Platform: macOS, Windows Load Model 1. Support load model files on the network: model. json (model structure and operators' attributes) chunk_x. 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. 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！