wasmoon
pcl.js
wasmoon | pcl.js | |
---|---|---|
3 | 9 | |
414 | 408 | |
- | - | |
6.3 | 7.3 | |
about 1 month ago | 10 months ago | |
TypeScript | TypeScript | |
MIT License | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
wasmoon
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The influence of Neovim on Vim development
You could still use lua: https://github.com/ceifa/wasmoon
- A real lua VM with JavaScript bindings made with WebAssembly
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A real lua VM with JS bindings made with webassembly
ceifa/wasmoon: A real lua VM with JS bindings made with webassembly (github.com)
pcl.js
- Pcl.js – Porting the large C++ library PCL to the browser via WebAssembly
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I ported a large C++ library to the browser
pcl.js is a Point Cloud Library (PCL) that runs in the browser, powered by Emscripten and WebAssembly. Point Cloud Library (PCL) is a standalone, large scale, open C++ project for 2D/3D image and point cloud processing.
Github: https://github.com/luoxuhai/pcl.js
- u/XuhaiLuo ported pcl to javascript. Could be helpful for folks working on js-based robotics projects.
- I ported a large C++ library to the browser!
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I ported the Point Cloud Library (PCL) to the browser!
Github:https://github.com/luoxuhai/pcl.js
What are some alternatives?
lua-repl
icpts - TypeScript implementation of iterative closest point (ICP) for point cloud registration
love-webplayer - WebPlayer for Love2D engine games (webgl+javascript)
noita-tools - A collection of tools for Nolla Game's Noita that help get insight into seeds and find ones with special constraints.
AOE4-TSTL - Very experimental project to allow writing TypeScript for Age of Empires 4 modding using TypeScriptToLua
x-python - A complete solution for python-in-browser 🚀
Vim - The official Vim repository
js-diary - 📙In-browser live coding environment with markdown & JSX support for JavaScript
copilot.vim - Neovim plugin for GitHub Copilot
asdom - Use DOM APIs in AssemblyScript
Porcupine - On-device wake word detection powered by deep learning