Search Results for "cpu benchmark linux"
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Showing 21 open source projects for "cpu benchmark linux"
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QtScrcpy
Android real-time display control software
QtScrcpy connects to Android devices via USB (or via TCP/IP) for display and control. It does NOT require the root privileges. It supports three major platforms: GNU/Linux, Windows and MacOS. You can write your own script to map keyboard and mouse actions to touches and clicks of the mobile phone according to your needs. A script for "PUBG mobile" and TikTok mapping is provided by default. Once enabled, you can play the game with your keyboard and mouse as the PC version. or you can use... -
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ffmpeg-android-maker
Contains a script that assembles FFmpeg library for Android
ffmpeg-android-maker is a build automation tool designed to compile FFmpeg for Android platforms with support for various codecs and libraries. It simplifies the complex process of cross-compiling FFmpeg by providing scripts that handle dependencies, configuration, and build steps. The project supports multiple architectures, enabling developers to generate binaries compatible with different Android devices. It includes options for enabling or disabling specific codecs and features, allowing... -
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Riemann
A network event stream processing system, in Clojure
Riemann aggregates events from your servers and applications with a powerful stream processing language. Send an email for every exception in your app. Track the latency distribution of your web app. See the top processes on any host, by memory and CPU. Combine statistics from every Riak node in your cluster and forward to Graphite. Track user activity from second to second. Riemann streams are just functions which accept an event. Events are just structs with some common fields like :host... -
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FFmpeg prebuilt for NW.js
FFmpeg prebuilt binaries for NW.js / Chromium
...The project includes builds with proprietary codec support, enabling broader media compatibility in applications. It supports multiple platforms including Windows, Linux, and macOS, as well as different CPU architectures. The repository also provides scripts and instructions for building custom binaries when needed. It is particularly useful for developers creating multimedia-enabled NW.js apps. Overall, it ensures consistent and ready-to-use FFmpeg environments for application development. -
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rav1e
The fastest and safest AV1 encoder
rav1e is an open-source implementation of an encoder for the AV1 video codec, developed in Rust (with some assembly) by the community around Xiph Foundation. Its design philosophy is to start from a correct, minimal, and fast AV1 encoder — sacrificing some encoding speed/efficiency of reference encoders in exchange for simplicity, stability, and compilability across platforms — and then gradually improve. This makes rav1e particularly attractive for scenarios where you need AV1 encoding but... -
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UpscalerJS
Image Upscaling in Javascript. Increase image resolution up to 4x
Image Upscaling in Javascript. Increase image resolution up to 4x using Tensorflow.js. Open source, browser/Node compatibility, and completely free to use under the MIT license. Scale images up to 4x their original size, all in Javascript. UpscalerJS ships with pre-trained models in the box covering a wide variety of use cases. Or bring your own! Browser, Node (CPU and GPU-accelerated), and Service Worker environments all supported. Supports inputs in a wide variety of formats - URL,... -
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Dozzle
Realtime log viewer for containers. Supports Docker, Swarm and K8s
Dozzle is a lightweight, self-hosted web application for real-time viewing and monitoring of container logs, focused on speed and simplicity rather than building a full log storage pipeline. Instead of indexing or storing logs, it connects to your container runtime and streams live output so you can diagnose issues as they happen. The interface includes practical quality-of-life features like fuzzy searching for containers, regex log search, split-screen viewing for multiple logs, and live... -
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AI Upscaler for Blender
AI Upscaler for Blender using Real-ESRGAN
Blender add-on to dramatically reduce render times using the Real-ESRGAN upscaler. Rendering an HD image in Blender takes 37 minutes. Upscaling can render a similar quality image in 5 mins total. Any PC or laptop can now do 3D rendering. 4k images can be rendered in the time it would take to render HD 1080p images. HD 1080p images can be rendered in record time on low-end hardware. Installation is easy. Just install the addon. No special hardware or GPU is required. Upscaling is done... -
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jetson-ffmpeg
ffmpeg support on jetson nano
jetson-ffmpeg is a specialized integration layer that enables FFmpeg to use hardware-accelerated encoding and decoding on NVIDIA Jetson devices through the L4T Multimedia API. 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... -
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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... -
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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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Anime4kSharp
Anime4K implemented in C#
Anime4KSharp is a .Net Core library that implements bloc97's Anime4K Algorithm version 0.9 and 1.0 RC2. The Algorithm is executed on the CPU, but utilizing all available CPU Cores. This yields to a conversion time of "only" 4432 ms when upscaling from 1080p to 2160p. This time could possibly be reduced with further optimization. Images are processed in four phases that are executed on a pixel- per- pixel basis. Each phase takes a input image and renders it to a output image. This makes it... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured... -
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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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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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TCPCopy
An online request replication tool, also a tcp stream replay tool
TCPCopy is a TCP stream replay tool to support real testing of Internet server applications. Although the real live flow is important for the test of Internet server applications, it is hard to simulate it as online environments are too complex. To support more realistic testing of Internet server applications, we develop a live flow reproduction tool - TCPCopy, which could generate the test workload that is similar to the production workload. Currently, TCPCopy has been widely used by... -
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Livestreamer
Command-line utility that extracts various streams into a video player
Livestreamer is a free command-line utility that extracts video streams from various services and pipes them into a video player of your choice, such as VLC. It allows users to avoid buggy and CPU-heavy flash plugins while still enabling them to enjoy various streamed content. For developers who wish to access the video stream data, API is also available. -
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open-vjj
Open Source VJ Software in Java
An Open Source Java Software for Visual-Artists like VJs written in Java. Using xuggle as video decoder, we are able to read most popular videocodecs. Supports iGuard IP-250E IP/Network Camera. With MJPEG-Stream-Server for multiple clients like VLC. GPU support with OpenCL and jogamp. -
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MplayerXP is branch of well known mplayer (http://mplayerhq.hu) which is based on new (thread based) core. Main goal of this project is to achieve smoothness of video playback due monotonous CPU loading.
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Allows the user to select multiple image files & generates thumbnails. Supports multiple formats. Lets the user specify the percentage resizing on the images.
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