3 dépôts
Distributing computer vision tasks to background threads to maintain high UI frame rates.
Distinct from Worker Thread Patterns: Specific to offloading heavy image analysis, not generic thread patterns or UI messaging.
Explore 3 awesome GitHub repositories matching software engineering & architecture · Image Processing Offloading. Refine with filters or upvote what's useful.
AR.js is a web-based augmented reality framework used to create immersive experiences directly in a browser using WebGL and WebRTC. It provides a cross-platform runtime that executes on mobile devices and head-mounted displays without requiring a dedicated application installation. The framework includes a marker-based engine for detecting physical patterns or barcodes to anchor digital overlays, a location-based tool for positioning entities via GPS coordinates, and a face tracking library for anchoring content to human facial features. It supports multi-marker simultaneous tracking, custom
Offloads heavy image processing and pattern matching to background threads to maintain high performance.
jspaint is a web-based reimplementation of Microsoft Paint, built entirely in JavaScript to run in a browser. It recreates the classic desktop application by reverse-engineering the original Win32 API calls and event handling, rendering the entire interface onto an HTML5 canvas for pixel-perfect retro graphics. The project preserves the original file format compatibility with BMP, PNG, GIF, and JPEG, ensuring exact pixel data matches the legacy application. The application maintains a complete undo history stack using compressed image snapshots, and offloads computationally intensive image pr
Offloads computationally intensive image processing operations to background web workers for UI responsiveness.
Node-vibrant is a JavaScript image processing library designed to extract color palettes from media assets for use in dynamic user interface theming. It functions as an automated design tool that identifies dominant and muted hues to maintain visual harmony across application interfaces. The library utilizes quantization-based color clustering and heuristic-based scoring to group pixel data into representative color sets. By offloading these computationally intensive analysis tasks to background threads, the project ensures that the main execution thread remains responsive during image proces
Distributes image analysis tasks to background threads to maintain high UI frame rates.