Search Results for "wavelets image processing"

image-to-ascii is a Node.js module that converts raster images into character-based terminal artwork. Input can come from a local file, remote URL, or in-memory Buffer. The converter maps pixel brightness to a configurable sequence of ASCII characters. It can preserve the original colors through ANSI foreground or background styles or generate plain monochrome output.

The typical use case for this high speed Node.js module is to convert large images in common formats to smaller, web-friendly JPEG, PNG, AVIF and WebP images of varying dimensions. Resizing an image is typically 4x-5x faster than using the quickest ImageMagick and GraphicsMagick settings due to its use of libvips. Colour spaces, embedded ICC profiles and alpha transparency channels are all handled correctly. Lanczos resampling ensures quality is not sacrificed for speed. As well as image...

An image processing library for Node written entirely in JavaScript, with zero native dependencies. If you're using this library with TypeScript the method of importing slightly differs from JavaScript. Instead of using require, you must import it with ES6 default import scheme. If you're using a web bundles (webpack, rollup, parcel) you can benefit from using the module build of jimp.

...Rather than building a single web-tool, this repository serves as a knowledge base: descriptions, guidance, and possibly examples or usage notes about a variety of online tools, organized in a way that’s meant to help “make online tools benefit humanity.” For someone who frequently resorts to ad-hoc web tools to solve tasks (text manipulation, image processing, conversion, utilities), OnlineToolsBook acts as an aggregator of “cheat sheets” or curated pointer collection rather than a specific application. The intention appears to be long-term: the repository can be updated to reflect new tools, remove broken ones, organize categories, or provide usage hints — so it becomes a living, crowd-maintained reference.

glfx.js is a JavaScript image-effects library that uses WebGL to apply real-time filters and transformations directly in the browser. It exposes a simple API where images are uploaded into GPU textures, processed with shader-based filters, and rendered to a WebGL canvas. Because the work is done on the GPU, many effects that would be too slow in pure JavaScript (like complex blurs, lens effects, or tilt-shift) can run interactively, even on large images. The library is structured around...

...The library can interpret image metadata, including Exif and IPTC tags, and can extract embedded thumbnails when present, which is handy for building fast image pickers or galleries. One of its key capabilities is correcting Exif Orientation, so photos taken on mobile devices appear upright without additional server-side processing. It also offers the option to preserve or restore image headers when resizing, which helps retain metadata or orientation information in the re-encoded image.

...What we're doing is adding filters to the images, as well as applying color and/or gradient overlays via various blending techniques to mimic filter effects. This means less manual image processing and more fun filter effects on the web! We are using pseudo-elements (i.e. :before and :after) to create the filter effects, so you must apply these filters on a containing element (i.e. not a content-block like <img>. The recommendation is to wrap your images in a <figure> tag. If you use custom naming in your CSS architecture, you can add the .scss files for the provided styles within your project and then @extend the filter effects within your style definitions. ...

The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The...