Search Results for "cpu"

This library provides an async image downloader with cache support. For convenience, we added categories for UI elements like UIImageView, UIButton, MKAnnotationView. SD is the prefix for Simple Design (which is the team name in Daily Motion company from the author Olivier Poitrey) Image formats supported by Apple system (JPEG, PNG, TIFF, BMP, ...), including GIF/APNG animated image. In order to keep SDWebImage focused and limited to the core features, but also allow extensibility and custom...

With the AR MultiPendulum app, I created the world’s first AR headset experience that does not rely on expensive specialized hardware. Using Google Cardboard, a standard iPhone, and video footage from the phone’s camera, the app creates an AR headset experience by rendering the user’s surroundings in VR. Augmented reality (AR) is a technology that overlays virtual objects over the real world. For years, AR experiences have been available on smartphones through handheld AR apps. In 2016,...

Forma is an experimental vector graphics renderer written in Rust, developed by Google to explore high-performance, parallelized rendering techniques across multiple platforms. The project aims to achieve portability, performance, simplicity, and small footprint through a streamlined four-stage rendering pipeline. Forma provides both CPU (software) and GPU (hardware) backends, relying on Rust’s SIMD auto-vectorization, Rayon for multithreading, and WebGPU (wgpu) for hardware acceleration. The renderer processes Bézier curves, line segments, and pixels through stages of flattening, rasterization, sorting, and painting, updating only changed tiles for efficiency. This design allows Forma to render complex vector scenes—such as large-scale SVGs—at interactive frame rates even on CPUs.

IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch Mozaic Many Outputs Physical Inputs Streaming Protocols File Formats Presets Vods/Series server-side support Pay per view channels Channels on demand HTTP Live Streaming (HLS) server-side support Public API, client server communication via JSON RPC Protocol gzip compression Deep learning video analysis Supported deep learning frameworks: Tensorflow NCSDK Caffe ML Hardware:

...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.

...A high-end desktop GPU, such as an AMD Radeon 7970 or NVIDIA GTX 680 or better. We succesfully tested the software under Windows, Linux and Mac OSX. The software currently doesn't work on OpenCL CPU devices. It might run on a laptop GPU but performance will not likely be very good. Note that often an OpenCL drivers fails to compile a kernel. Some unit tests exist to track down the issue, but more work is required to cover all OpenCL kernels.

...However, it currently lacks some of the more advanced features of Core Image, such as facial detection. GPUImage uses OpenGL ES 2.0 shaders to perform image and video manipulation much faster than could be done in CPU-bound routines. It hides the complexity of interacting with the OpenGL ES API in a simplified Objective-C interface. This interface lets you define input sources for images and video, attach filters in a chain, and send the resulting processed image or video to the screen, to a UIImage, or to a movie on disk. Images or frames of video are uploaded from source objects, which are subclasses of GPUImageOutput.