On an iPhone 4S, this framework can easily process 1080p video at over 60 FPS. This is particularly noticeable in mobile or embedded devices. By relying on the GPU to run these operations, performance improvements of 100X or more over CPU-bound code can be realized. 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. 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. 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. GPUImage2 - GPUImage 2 is a BSD-licensed Swift framework for GPU-accelerated video and image processing Largely driven by Apple's deprecation of OpenGL (ES) on their platforms in favor of Metal, it will allow for exploring performance optimizations over OpenGL and a tighter integration with Metal-based frameworks and operations. This version of the framework replaces OpenGL (ES) with Metal. Previous iterations of this framework wrapped OpenGL (ES), hiding much of the boilerplate code required to render images on the GPU using custom vertex and fragment shaders. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, the second iteration rewritten in Swift using OpenGL to target Mac, iOS, and Linux, and now this third generation is redesigned to use Metal in place of OpenGL. GPUImage 3 is the third generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac and iOS. GPUImage3 - GPUImage 3 is a BSD-licensed Swift framework for GPU-accelerated video and image processing using Metal
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