Open Source Swift Image Processing Software

Kingfisher is a powerful, pure-Swift library for downloading and caching images from the web. It provides you a chance to use a pure-Swift way to work with remote images in your next app. Asynchronous image downloading and caching. Loading image from either URLSession-based networking or local provided data. Useful image processors and filters provided. Multiple-layer hybrid cache for both memory and disk. Fine control on cache behavior. Customizable expiration date and size limit. Cancelable downloading and auto-reusing previous downloaded content to improve performance. Independent components. Use the downloader, caching system, and image processors separately as you need. Prefetching images and showing them from the cache to boost your app. View extensions for UIImageView, NSImageView, NSButton and UIButton to directly set an image from a URL. Built-in transition animation when setting images. Customizable placeholder and indicator while loading images.

Nuke ILS provides an efficient way to download and display images in your app. It's easy to learn and use thanks to a clear and concise API. Its architecture enables many powerful features while offering virtually unlimited possibilities for customization. Despite the number of features, the framework is lean and compiles in just under 3 seconds¹. Nuke has an automated test suite 2x the size of the codebase itself, ensuring excellent reliability. Every feature is carefully designed and optimized for performance. Fast LRU memory cache, native HTTP disk cache, and custom aggressive LRU disk cache. Customize image pipeline using built-in Alamofire, Gifu, FLAnimatedImage, WebP plugins or create your own. Enable progressive decoding with a single line of code. Nuke supports progressive JPEG out of the box, and WebP via a plugin built by the community. Automatically prefetch images ahead of time using either Preheat or native table and collection view prefetching APIs.

AppIcon generates *.appiconset contains each resolution image for iOS, MacOS. AppIcon needs path of base image(.png). The size of base image is 1024x1024 pixel preferably.

GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. By relying on the GPU to run these operations, performance improvements of 100X or more over CPU-bound code can be realized. This is particularly noticeable in mobile or embedded devices. On an iPhone 4S, this framework can easily process 1080p video at over 60 FPS. On a Raspberry Pi 3, it can perform Sobel edge detection on live 720p video at over 20 FPS.