vibrant.js is a JavaScript color extraction library used to identify dominant color palettes from images based on the Android Palette algorithm. It functions as an image palette generator and a color processing tool that converts extracted data between RGB, HSL, and Hexadecimal formats. The library analyzes image pixels to categorize colors into specific profiles, including vibrant, muted, dark, and light. It also includes an accessible text color calculator that determines high-contrast hex colors for text overlays based on a selected background color. The toolset covers automated palette g
Chameleon is a color framework for Swift and Objective-C applications, providing a toolkit for managing dynamic palettes, gradient libraries, and hexadecimal conversions. It functions as a system for creating harmonious color schemes and calculating contrasting text colors based on background luminance. The project includes an image color extractor that analyzes images to generate matching color schemes or calculate average colors for user interfaces. It also features a gradient color library for creating and applying smooth transitions to backgrounds and text elements. The framework covers
Color-thief-py is a Python library designed to analyze digital images for the purpose of extracting prominent color information. It functions as a computer vision tool that processes image files to identify the single most dominant color or to generate a representative color palette based on the visual composition of the source. The library utilizes the Pillow imaging library to handle diverse file formats and load image data into memory as structured pixel arrays. By mapping these pixels into a three-dimensional color space and applying median-cut quantization, the tool identifies statistica
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
This is a jQuery plugin that extracts the dominant color from an image or CSS background image and applies it as a background color on a target element. It uses canvas-based pixel analysis with an RGB quantization algorithm to identify the most prominent color, then injects that color as an inline CSS background-color style.
Die Hauptfunktionen von briangonzalez/jquery.adaptive-backgrounds.js sind: jQuery Plugins, RGB Quantizers, Background Fill Colors, CSS Background Image Analyzers, CSS Background Image Extractors, Image-Derived Backgrounds, Canvas-Based Extractors, Image Color Extractors.
Open-Source-Alternativen zu briangonzalez/jquery.adaptive-backgrounds.js sind unter anderem: jariz/vibrant.js — vibrant.js is a JavaScript color extraction library used to identify dominant color palettes from images based on the… vicc/chameleon — Chameleon is a color framework for Swift and Objective-C applications, providing a toolkit for managing dynamic… fengsp/color-thief-py — Color-thief-py is a Python library designed to analyze digital images for the purpose of extracting prominent color… vibrant-colors/node-vibrant — Node-vibrant is a JavaScript image processing library designed to extract color palettes from media assets for use in… benhowdle89/grade — Grade is a JavaScript library for image color analysis and dynamic theme generation. It extracts the most prominent… lokesh/color-thief — Color-thief is a color quantization library and image color palette extractor designed to identify the most prominent…