Search Results for "gpu processing"
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Showing 22 open source projects for "gpu processing"
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nunif
Misc; latest version of waifu2x; 2D video to stereo 3D video
nunif is a deep learning–based image processing framework focused on image upscaling, restoration, denoising, and enhancement tasks using neural network models. The project provides a collection of AI-powered utilities designed primarily for anime-style artwork, illustrations, and high-quality image restoration workflows. It includes command-line tools and graphical interfaces for applying trained neural models to improve image resolution and visual clarity while minimizing artifacts. nunif supports GPU acceleration and batch processing, making it suitable for creators, archivists, and enthusiasts handling large image collections. ... -
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FFmpegAndroid
FFmpeg implements video cropping, watermarking, transcoding
FFmpegAndroid is a comprehensive Android-focused multimedia development project that demonstrates how to integrate and use FFmpeg for advanced audio and video processing tasks. It provides a wide range of implementations including video editing, transcoding, watermarking, and GIF generation, all optimized for mobile environments. The project also covers real-time streaming capabilities such as local and live RTMP pushing using H264 encoding, making it suitable for building live broadcasting... -
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Anime4KCPP
A high performance anime upscaler
Anime4KCPP provides an optimized bloc97's Anime4K algorithm version 0.9, and it also provides its own CNN algorithm ACNet, it provides a variety of way to use, including preprocessing and real-time playback, it aims to be a high-performance tool to process both image and video. This project is for learning and the exploration task of the algorithm course in SWJTU. Anime4K is a simple high-quality anime upscale algorithm. Version 0.9 does not use any machine learning approaches and can be... -
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Warlock-Studio
AI Suite for upscaling, interpolating & restoring images/videos
...Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system designed to overcome GPU VRAM limitations. -
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Smooth My Video
Offline AI frame interpolation, upscaling and HDR for NVIDIA GPUs
Turn any video into a buttery-smooth high-frame-rate copy, entirely offline on your NVIDIA GPU. Pick a file, choose a target frame rate (2x, 4x, 8x and up, or match your monitor) and click Smooth It! Five interpolation models: GMFSS (best for anime), RIFE (best for live action) with a DRBA option that preserves anime pacing, NVIDIA DLSS 4.5 Frame Generation, Nvidia Smooth Motion, and SVP's svpflow engine. The same render can AI-upscale to 16K (RTX Video Super Resolution + Real-ESRGAN... -
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Free Fps. Video FPS Converter
Desktop app to change a video FPS
Free FPS is an open‑source desktop app and scripts to change a video file frame rate (FPS) using FFmpeg. Unlike video editors, it does not add effects or alter content - it only adjusts playback speed and, if needed, re-encodes audio as well. Useful if you work with multiple videos shot at different frame rates that cannot be combined or edited without interpolation or frame loss. Also doubles as a fast video compressor: keep the original FPS and raise compression (e.g., higher CRF or... -
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ProPainter
Improving Propagation and Transformer for Video Inpainting
...It provides pretrained models, example inputs, inference scripts, and an interactive demo workflow for object removal. The repository also includes memory-efficient inference features to reduce GPU out-of-memory issues during video processing. ProPainter is useful for research, video editing experiments, object removal prototypes, and completion tasks where consistent motion is important. -
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ffmpeg-gl-transition
FFmpeg filter for applying GLSL transitions between video streams
...It supports customizable parameters such as duration, offset, and shader source files, providing flexibility in transition design. The project requires building FFmpeg with the custom filter, enabling deeper integration into video processing pipelines. It is particularly useful for developers who need advanced transitions without relying on external editing software. Overall, it enhances FFmpeg’s capabilities by introducing GPU-accelerated transition effects. -
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Darknet YOLO
Real-Time Object Detection for Windows and Linux
This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project. -
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jetson-ffmpeg
ffmpeg support on jetson nano
...It provides a bridge between FFmpeg and NVIDIA’s proprietary APIs, allowing developers to leverage on-device hardware encoders and decoders for improved performance. The project includes a library and patch system that modifies FFmpeg builds to enable NVMPI-based acceleration. This allows efficient processing of video streams on embedded systems without overloading CPU resources. jetson-ffmpeg is particularly useful for edge computing applications such as robotics, surveillance, and real-time streaming. It requires building both the library and a patched version of FFmpeg to fully enable hardware features. Overall, it extends FFmpeg functionality to better suit embedded GPU-powered environments. -
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Tdarr V2
Distributed transcode automation using FFmpeg/HandBrake
Tdarr is a distributed media transcoding and automation system designed to manage and optimize large audio and video libraries across multiple machines. It operates through a central server and multiple worker nodes that process files in parallel, leveraging both CPU and GPU resources for efficient transcoding. The system uses FFmpeg and HandBrake to convert media files according to user-defined rules, such as codec standardization, bitrate optimization, or format compatibility. Tdarr also includes advanced features like health checks, plugin-based processing pipelines, and automated scheduling to maintain libraries continuously. ... -
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FastoCloud PRO
IPTV/NVR/CCTV/Video cloud https://fastocloud.com
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: -
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GPUImage 2
Framework for GPU-accelerated video and image processing
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. ... -
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FFmpeg Docker image
Docker build for FFmpeg on Ubuntu / Alpine / Centos / Scratch
FFmpeg Docker image is a collection of Docker images that provide prebuilt FFmpeg environments for media processing, encoding, and streaming tasks. The project compiles FFmpeg from source and packages it with various configurations and dependencies, enabling users to run FFmpeg without installing it directly on their systems. It supports multiple base operating systems such as Ubuntu, Alpine, and CentOS, offering flexibility depending on deployment needs. The images are designed for... -
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openAviToGif
Video to GIF converter
With openAviToGif you can convert video into an animated gif file. What's new in v0.6: -GPU processing -improvements and bugfixes Use your video card to speed up the conversion. Recommended for those who have high-end video cards. -
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Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters, implemented in OpenCL. The framework was mainly designed as a toolkit for the rapid development of interactive art projects that explore dynamics of complex environments. The Scene GUI runs and compiles under Windows, Linux, and MacOS X, and is available in both 32 bit and 64 bit versions.
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GPUImage
iOS framework for GPU-based image and video processing
The GPUImage framework is a BSD-licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a slightly simpler interface. 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... -
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GLIP-LIB
OpenGL Image Processing LIBrary
GLIP-Lib is an OpenGL image processing library written in C++. It features all the necessary tools to quickly build texture filters and pipelines and operate them on the GPU. -
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A gathering of state-of-the-art tools for GPU based image processing. They are the sourcecode for related research articles, and provide the basis for own experimentation. All are being implemented forNVidia GPUs in Linux, hence the name "nvision" ;)
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proGPUKLT is a library for the Processing programming language and environment that wraps a GPU-implementation of the Kanade-Lucas-Tomasi feature tracker used for computer vision applications.
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An OS/hardware vendor independent GPU accelerated image and video processing library written in C. Interface allows easy combination and manipulation of customizable filters. Works with an active OpenGL context.
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