Open Source Networking Software
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Networking Software
View 339 business solutionsBrowse free open source Networking software and projects below. Use the toggles on the left to filter open source Networking software by OS, license, language, programming language, and project status.
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Zenflow- The AI Workflow Engine for Software DevsZenflow is the AI workflow engine built for real teams. Parallel agents plan, code, test, and verify in one workflow. With spec-driven development and deep context, Zenflow turns requirements into production-ready output so teams ship faster and stay in flow.
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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Model Context Protocol (MCP) Servers
Model Context Protocol Servers
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. -
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howmanypeoplearearound
Count the number of people around you by monitoring wifi signals
howmanypeoplearearound calculates the number of people in the vicinity using the approximate number of smartphones as a proxy (since ~70% of people have smartphones nowadays). A cellphone is determined to be in proximity to the computer based on sniffing WiFi probe requests. Possible uses of howmanypeoplearearound include, monitoring foot traffic in your house with Raspberry Pis, seeing if your roommates are home, etc. There are a number of possible USB WiFi adapters that support monitor mode. Namely you want to find a USB adapter with one of the following chipsets: Atheros AR9271, Ralink RT3070, Ralink RT3572, or Ralink RT5572. You will be prompted for the WiFi adapter to use for scanning. Make sure to use an adapter that supports "monitor" mode. You can modify the scan time, designate the adapter, or modify the output using some command-line options. -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). -
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SPM - Monitoring system
Monitoring Tool for your IT Environment
SPM Monitoring System - Complete Solution for Efficient Monitoring and Alerting SPM Monitoring System is an all-in-one monitoring solution for IT environments that offers comprehensive features to ensure high availability, stability, and optimal performance of your infrastructure. With SPM Monitoring Systems, you can monitor your network, servers, applications, and services with ease, and receive timely alerts when issues arise. Host Availability Monitoring. Agent-Based Monitoring: CPU,RAM,Storage,Network,EventLogs etc. SNMP Monitoring. Web Site Monitoring. Notification System: E-Mail, SMS, Push, Telegram Bot (also control via telegram bot) and Sound Notifications. Logging. Web Console. Control by Telegram Bot. Agents for Windows and Linux. SPM Monitoring Systems is a reliable and efficient solution for monitoring your IT environment. With its comprehensive features and flexible notification system, you can stay on top of your infrastructure's health and performance. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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playqt
GUI version of ffplay for Windows
playqt is a Windows GUI version of the well known ffplay program and has been enhanced with Object Detection capabilities. It can process multiple types of media including real time streams. An integrated camera control feature allows control over the camera parameters as well as automatic network configuration and connection. See the README under the files tab for configuration info. Real time object counting is implemented using YOLO detection algorithm. The program can be used with standard or customized models. A reduced version of the COCO dataset for most commonly observed types is available here. The program is based on ffplay and will respond to the familiar options if launched from the command line. This allows the program to be used with other command line tools such as youtube-dl. The source code is open and available here. It may be compiled using the contrib library provided along with Qt6, MSVC 2019 and NVIDIA cuda development library. -
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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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AcoPath
Ant Colony Optimization algorithm for the shortest path problem.
The shortest path problem is solved by many methods. Heuristics offer lower complexity in expense of accuracy. There are many use cases where the lower accuracy is acceptable in return of lower consumption of computing resources. The basic idea of the Ant System is that virtual ants are exploited for finding paths with a specific property, e.g., short distance between physical nodes, in the same way nature guides physical ants. Development takes place at https://github.com/zfoxer/AcoPath -
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AcoPath for Java
Ant Colony Optimization algorithm for the shortest path problem.
The shortest path problem is solved by many methods. Heuristics offer lower complexity in expense of accuracy. There are many use cases where the lower accuracy is acceptable in return of lower consumption of computing resources. The basic idea of the Ant System is that virtual ants are exploited for finding paths with a specific property, e.g., short distance between physical nodes, in the same way nature guides physical ants. -
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Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained model on the APPA-REAL (validation) dataset. We pose the age regression problem as a deep classification problem followed by a softmax expected value refinement and show improvements over direct regression training of CNNs. Our proposed method, Deep EXpectation (DEX) of apparent age, first detects the face in the test image and then extracts the CNN predictions from an ensemble of 20 networks on the cropped face. -
Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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Agent.GUI
The Project moved to github https://github.com/EnFlexIT/AgentWorkbench
The project has moved to github https://github.com/EnFlexIT/AgentWorkbench Agent.GUI is a simulation framework and toolkit based on the JADE framework. It provides functionalities for time aspects, agent-environment interaction, visualization and load balancing, Furthermore, the included application focuses the usability for end users. -
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AlertsOnWings
Pinger alert
AlertsOnWings is web-based interface for viewing a `heartbeat` of network by pinging hosts. No extra files, only DB. All reports generated "on-the-fly". And we got personal cabinet for each user. -
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Astrape
Optical-packet node transceiver frequency allocation
In an optical network scenario which consists of multiple nodes (whiteboxes) at its edges and ROADMs in-between, the coherent transceiver average laser configuration time is improved. The process is evaluated according to a testbed setup. This is facilitated in the appropriate lab equipment (or via simulation when required). For that purpose, a software agent (Netconf server) residing at the whiteboxes, is developed receiving input from the Software-Defined Networking (SDN) packet controller (PacketCTL - a Netconf client). Then, configuration of the local transceiver laser frequencies of the controlled pluggable devices takes place, for facilitating the connectivity in-between the ROADM network. Also, the agent records and reports back telemetry data (feedback) which is used by the PacketCTL's resource-allocating mechanism to improve efficiency within the network topology. -
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It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.
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CAMA (Context-Aware Mobile Agents) is a middleware for supporting mobile agents coordination. It is based on Linda-style coordination and provides numerous extentions for interoperability and fault-tolerance. It supports portable platforms such as PDAs.
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CLIP-as-service
Embed images and sentences into fixed-length vectors
CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks. Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing. Easy-to-use. No learning curve, minimalist design on client and server. Intuitive and consistent API for image and sentence embedding. Async client support. Easily switch between gRPC, HTTP, WebSocket protocols with TLS and compression. Smooth integration with neural search ecosystem including Jina and DocArray. Build cross-modal and multi-modal solutions in no time. -
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The Citizen Privacy Service is an asynchronous component using artificial intelligence capabilities including DL decidability and first order logic provenance that provide policy decision and policy enforcement points based on the US Privacy Act of 1974.
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Color Expansion is a logical game with network play support. Strong AI included - try it! Also this project is the home for the Color Expansion AI contest.
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CommunityBackup
...a work in progress.
Setup files are quite old. -
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Deep Learning with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in the development version). The goal of libgpuarray is (from the documentation) make a common GPU ndarray (n dimensions array) that can be reused by all projects that is as future proof as possible, while keeping it easy to use for simple need/quick test. The easiest way to get (most) these is to use an all-in-one installer such as Anaconda from Continuum. These are available for multiple architectures. -
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A feedback-enhanced framework for routing in wireless sensor networks. Speeds up the process of implementing routing techniques. Enables piggybacking of routing information on data packets. Written for the Omnet++ simulator and the Mobility Framework.
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network is needed after all. And so research continues. For simpler training, you can directly supply text strings instead of precomputing text encodings. (Although for scaling purposes, you will definitely want to precompute the textual embeddings + mask) -
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WHEREAMI is an intelligent and self-learning network detection and configuration utility. With this capability, a user can just walk to a network range and WHEREAMI will self determine and connect to that network with relevant policies.
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Agent inter-platform mobility service for the well-known JADE agent platform. This service allows software agents to move from one execution platform to the next, carrying their own data and state, and resuming their execution upon arrival.
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Kally is a software agent embedded in OpenOffice. We have created a simple interface to allow agents powered by GLORIA (gloria.sourceforge.net) to act as help assistants for users of OpenOffice, the office suite.
