Search Results for "cpu benchmark linux" - Page 3
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Showing 128 open source projects for "cpu benchmark linux"
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fmedia
fast media player/recorder/converter
fmedia is a fast asynchronous media player/recorder/converter for Windows, Linux and FreeBSD. Its goal is to provide smooth playback even if input device is very slow and unresponsive. The architecture allows to extend the functionality of the application in any way: adding a new audio input/output format, a new DSP filter or even a new GUI. fmedia is very small and fast: it has low CPU & memory consumption making it ideal to listen to music or process audio files while running on a notebook's battery. ... -
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3DDFA
Fast, accurate and stable 3D dense face alignment
...A simple 3D render written by c++ and cython is also included. This repo supports the onnxruntime, and the latency of regressing 3DMM parameters using the default backbone is about 1.35ms/image on CPU with a single image as input. See requirements.txt, tested on macOS and Linux platforms. The Windows users may refer to FQA for building issues. Note that this repo uses Python3. The major dependencies are PyTorch, numpy, opencv-python and onnxruntime, etc. -
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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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TrucklistStudio
Media Playlist streaming Software.
TrucklistStudio is a light media playlist broadcasting software. You can easily broadcast videos playlists and create webcasts from any location. TrucklistStudio supports almost every kind of services through FMEs XML configuration files. Different video sources and the mixing module will let you create various screen layouts. All major picture file formats are supported. Putting image as an overlay or background. Video transmitting over LAN. Lower CPU requirements. -
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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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Simd
High performance image processing library in C++
...It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems. -
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cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: ... -
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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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Bullet
JVM Bullet Physics SDK
...Take a look at the tests to see what has been ported and tested to be working. 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. -
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S2CBench
Synthesizable SystemC Benchmark Suite
S2CBench v.2.0 provides 18 programs written in synthesizable SystemC language. Each benchmark is designed for specific domains such as multimedia, digital signal processing, security, image processing, etc. The programs are provided with the objective to enable researchers analyze their innovative algorithms and techniques and help users compare the quality of results of state of the art commercial High Level Synthesis tools available in industry. You can log in to our Youtube channel to... -
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PolyBench/C 4.2 Copyright (c) 2011-2016 the Ohio State University. Contact: Louis-Noel Pouchet <pouchet@cse.ohio-state.edu> Tomofumi Yuki <tomofumi.yuki@inria.fr> PolyBench is a benchmark suite of 30 numerical computations with static control flow, extracted from operations in various application domains (linear algebra computations, image processing, physics simulation, dynamic programming, statistics, etc.). PolyBench features include: - A single file, tunable at...
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Skinner
Special Effects with Skinned Mesh in Unity
Skinner is a collection of real-time special effects for Unity that use vertices of an animating skinned mesh as emission points. Instead of duplicating mesh data on the CPU, it employs a replacement shader to stream vertex positions into GPU-friendly buffers, conserving memory and CPU cycles. With those GPU-side buffers, Skinner can drive effects like trails, particles, or geometry that react to the underlying skinned animation in sophisticated ways. The approach enables complex, performant... -
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Mp3 Tag Editor v4 latest
Best mp3 tag editor working with low CPU hosting
Download free mp3 tag editor v4 latest version php script -
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viewpix
A Landsat 8 scene viewer
...This is the "lite" version of Viewpix as it has no cuda filters installed. Viewpix is written in C. It is tested on Ubuntu and Centos. It should work with most current Linux distributions. Viewpix runs efficiently on computers with modest CPU's such as low power mini-ITX boards. It is known to work nicely on Intel NUC, AMD A6 SOC , and NVIDIA TX2. A multiple core cpu, 8 GB ram, and a large capacity hard drive are suggested. -
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Keras.js
Run Keras models in the browser, with GPU support using WebGL
Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc. Check out the demos/ directory for real examples running Keras.js in VueJS. Library version compatibility, Keras 2.1.2. -
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waifu2x-cpu-torch-vks
waifu2x fork without CUDA
The original is here: https://github.com/nagadomi/waifu2x Differences: - CPU only, no CUDA needed; - double-precision version; - GPU and CPU-trained models (on the fly conversion in memory); - adapted for Lua v5.2 (works with Torch 7 on x32 Ubuntu). 31-12-2016: - removed unneeded data copies, left from CUDA processing; - removed large duplicate files (see "ReadMe" before use). -
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Card Raytracer Benchmark
Short C++/Java/C#/Python benchmark
This is a short C++/Java/C#/Python benchmark. Based on Paul Heckbert's sources. Thank you Paul! -
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OpenGLChecker
Utility application to obtain data about your OpenGL implementation.
OpenGLChecker is a fast and smooth program that retrieves relevant information about your OpenGL implementation. It can also test your computer's performance with fully scripted benchmarks. This allows you to write your own benchmark scripts for testing your OpenGL performance. -
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SFML Voxel Raycaster
Simple voxel raycasting engine in SFML with multithreading support
Voxel raycasting engine written in C++ drawed by SFML, curently in alpha preview state. Currently rays are computed by CPU and performance is low and far away from realtime. -
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x3drenderlibrary
A 3d rendering framework
x3d render library is a 3d graphics framework with implementation of several useful rendering algorithms: a rasterization renderer(with implementation of both builtin software rendering & opengl hardware rendering); a path tracing renderer(cpu based) x3d demoscene is a framework and tool chains dedicated in animation production. x3d render library is used for the rendering component -
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Java Software Renderer
Java implementation of a software renderer.
Java implementation of a software renderer. Software rendering is handled only by a CPU, without any GPU support. Renderer is implemented in pure Java, without any additional frameworks. Additional requirements: JDK / JRE 8
