GitHub Trends

#javascript#3d_gaussian_splatting#game_development#game_engine#gamedev#gaussian_splatting#gltf#hacktoberfest#javascript#nodejs#playcanvas#typescript#virtual_reality#webgl#webgl2#webgpu#webxr PlayCanvas is an open-source game engine that lets you create 3D and 2D games or apps that run in any browser, using WebGL and WebGPU for fast, high-quality graphics. It supports advanced features like animation, physics, sound, and asset streaming, and you can write code in JavaScript or TypeScript. The engine is free, easy to set up, and works well for both simple projects and complex games, making it simple to build and share interactive content online. https://github.com/playcanvas/engine

#javascript#3d#augmented_reality#canvas#html5#javascript#svg#virtual_reality#webaudio#webgl#webgl2#webgpu#webxr Three.js is a powerful and easy-to-use JavaScript library that helps you create 3D graphics and animations on the web with much less code than using WebGL directly. It handles complex tasks like rendering and math calculations, so you can focus on designing your 3D scenes. It supports WebGL and WebGPU, with additional options like SVG and CSS3D. Three.js has excellent documentation, many examples, and a large, active community that provides support and updates. This makes it ideal for quickly building interactive 3D content that works across browsers, improving your web projects with engaging visuals and smooth performance[1][3][5]. https://github.com/mrdoob/three.js

#typescript#data_visualization#geospatial_analysis#javascript#maps#python#visualization#webgl deck.gl is a powerful tool that helps you create fast, interactive, and visually impressive maps and data visualizations using WebGL technology. It lets you turn large sets of data into layers like icons, polygons, and text, which you can view in different ways such as maps or 3D scenes. It works well with popular map providers like Google Maps and Mapbox, and supports easy interaction like clicking and filtering. You can use it simply by adding a script or installing it via npm or Python. This makes it easier for you to build custom, high-performance visualizations quickly and with less coding effort. https://github.com/visgl/deck.gl