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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. Using the module build will allow your bundler to understand your code better and exclude things you aren't...

...Lanczos resampling ensures quality is not sacrificed for speed. As well as image resizing, operations such as rotation, extraction, compositing and gamma correction are available. Most modern macOS, Windows and Linux systems running Node.js v10+ do not require any additional install or runtime dependencies. This module supports reading JPEG, PNG, WebP, AVIF, TIFF, GIF and SVG images. Output images can be in JPEG, PNG, WebP, AVIF and TIFF formats as well as uncompressed raw pixel data. Streams, Buffer objects and the filesystem can be used for input and output.

SuperEmbed.js detects embedded videos from YouTube, Vimeo, Vine, VideoPress, DailyMotion, and more on webpages and makes them responsive. Essentially, this means they stretch to fill their container while still maintaining the content's original aspect ratio. I created SuperEmbed to fix all my issues with existing solutions, including (but not limited to) unnecessary reliance on other libraries, bloated code, and poor fallback support.

Simply put, CSSgram is a library for editing your images with Instagram-like filters directly using CSS. 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...

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...