Top 3 JavaScript live-coding Projects

shader-park-core

3 700 7.1 JavaScript

A JavaScript library for creating real-time 2D and 3D shaders. JS -> Shader. https://shaderpark.com/ https://twitter.com/shaderpark

Project mention: Painting with Math: A Gentle Study of Raymarching | news.ycombinator.com | 2023-09-15

For anyone interested in playing around with SDFs, my friend and I made this open source library to make working with them more efficient, and you can write shaders using javascript https://github.com/shader-park/shader-park-core

SqueakJS

2 360 9.1 JavaScript

A Squeak Smalltalk VM in Javascript

Project mention: Smalltalk simplicity and consistency vs. other languages (2022) [video] | news.ycombinator.com | 2024-01-14

> And I'd like to be able to create applications that run without shipping the entire Smalltalk VM.
There's always a javascript vm... https://squeak.js.org/

SurveyJS

surveyjs.io sponsored

Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
blackjack-basic-strategy

23 26 2.0 JavaScript

A computer vision powered Blackjack basic strategy app powered by Roboflow.

Project mention: Show HN: Pip install inference, open source computer vision deployment | news.ycombinator.com | 2023-08-23

It’s an easy to use inference server for computer vision models.
The end result is a Docker container that serves a standardized API as a microservice that your application uses to get predictions from computer vision models (though there is also a native Python interface).
It’s backed by a bunch of component pieces:
* a server (so you don’t have to reimplement things like image processing & prediction visualization on every project)
* standardized APIs for computer vision tasks (so switching out the model weights and architecture can be done independently of your application code)
* model architecture implementations (which implement the tensor parsing glue between images & predictions) for supervised models that you've fine-tuned to perform custom tasks
* foundation model implementations (like CLIP & SAM) that tend to chain well with fine-tuned models
* reusable utils to make adding support for new models easier
* a model registry (so your code can be independent from your model weights & you don't have to re-build and re-deploy every time you want to iterate on your model weights)
* data management integrations (so you can collect more images of edge cases to improve your dataset & model the more it sees in the wild)
* ecosystem (there are tens of thousands of fine-tuned models shared by users that you can use off the shelf via Roboflow Universe[1])
Additionally, since it's focused specifically on computer vision, it has specific CV-focused features (like direct camera stream input) and makes some different tradeoffs than other more general ML solutions (namely, optimized for small-fast models that run at the edge & need support for running on many different devices like NVIDIA Jetsons and Raspberry Pis in addition to beefy cloud servers).
[1] https://universe.roboflow.com

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).