Search Results for "python framework" - Page 40
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Showing 1791 open source projects for "python framework"
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid. -
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RCDCap
RCDCap is a remote capture preprocessor
RCDCap is a packet processing framework. At its core, it incorporates basic mechanisms for local and remote capturing and decapsulation of packets (CISCO ERSPAN and HP ERM are supported). It can be extended to support many types of packet-based traffic analysis by creating plug-ins and loading them in the main application. It includes many optimizations to ensure high performance traffic processing. Some of them are: multithreaded traffic processing; explicit thread pinning; configurable... -
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MXNet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning
Apache MXNet is a scalable, efficient open-source deep learning framework—offering a flexible hybrid programming model (symbolic + imperative) and supporting a wide array of languages—designed for training and deploying neural networks across heterogeneous systems. Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the... -
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EasyNLP
EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit
EasyNLP is an easy-to-use NLP development and application toolkit in PyTorch, first released inside Alibaba in 2021. It is built with scalable distributed training strategies and supports a comprehensive suite of NLP algorithms for various NLP applications. EasyNLP integrates knowledge distillation and few-shot learning for landing large pre-trained models, together with various popular multi-modality pre-trained models. It provides a unified framework of model training, inference, and... -
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noteq
Framework for clinical Tinnitology and Epigenetical mechanics.
...https://app.box.com/s/rz6xqjcsno3ffctgu2iyqs4vqfg1x3c4 The Independent Audiology Assistant Association for the Advancement of Tinnitology in public health care and The Independent Loop Quantum Gravity Technology Group. The designer, developer, maintainer, distributor and Python 3-programmer of the API (application programming interface) and Framework for clinical Tinnitology and Epigenetical mechanics. 1990-2022. -
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BINPython
Lightweight and small portable Python, build with pyinstaller
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Kalliope
Kalliope is a framework to create your own personal assistant
Kalliope is a modular always-on voice-controlled personal assistant designed for home automation. Kalliope is a framework that will help you to create your own personal assistant. The concept is to create the brain of your assistant by attaching an input signal (vocal order, scheduled event, MQTT message, GPIO event, etc..) to one or multiple actions called neurons. You can create your own Kalliope bot, by simply choosing and composing the existing neurons without writing any code. But, if... -
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Acme
A library of reinforcement learning components and agents
Acme is a framework from DeepMind for building scalable and reproducible reinforcement learning agents. It emphasizes modular components, distributed training, and ease of experimentation. -
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MeshCNN in PyTorch
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN is a deep learning framework designed specifically for processing 3D triangular mesh data using convolutional neural networks. Unlike traditional CNNs that operate on images or voxel grids, MeshCNN performs convolution operations directly on the edges of mesh structures. This design allows the model to capture geometric relationships between mesh elements while preserving the underlying topology of 3D shapes. The framework introduces specialized layers such as edge-based convolution,... -
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Spyne
A transport agnostic sync/async RPC library
Spyne is a Python RPC toolkit that makes it easy to expose online services that have a well-defined API using multiple protocols and transports. It integrates with popular Python web frameworks as well as libraries like SQLAlchemy to keep your code as DRY as possible. Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple protocols and transports. ... -
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Model Search
Framework that implements AutoML algorithms
Model Search is an AutoML research system for discovering neural network architectures with minimal human intervention. Instead of hand-crafting models, you define a search space and objectives, then the system explores candidate architectures using controllers and population-based strategies. It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of... -
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pwncat
Fancy reverse and bind shell handler
pwncat is a command and control framework that turns a basic reverse or bind shell into a fully-featured exploitation platform. After initial connection, the framework will probe the remote system to identify useful binaries natively available on the target system. It will then attempt to start a pseudoterminal on the remote host and provide you with raw terminal access. pwncat doesn’t stop there, though. On top of raw terminal access, pwncat can programmatically interact with the remote... -
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PCRaster
PCRaster environmental modeling software
...Application domains are amongst others hydrology (rainfall-runoff, global water balance, groundwater (with Modflow)), ecology, or land use change. Two scripting languages (PCRcalc and Python) include a rich set of spatial operations for manipulating and analysing raster maps. A Python framework supports Monte Carlo simulations and data assimilation (Ensemble Kalman Filter and Particle Filter). The Aguila tool allows for the interactive visualisation of stochastic spatio-temporal data. -
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Admin4
portable administration tool for LDAP, DNS, IMAP, PostgreSQL and more
Admin4 is a tool for server maintenance via several plugin modules. Currently, plugins for BIND DNS, LDAP, IMAP and PostgreSQL are included. It is designed as a framework, using Python for fast development of plugins and custom modifications. The DNS plugin should be able to query (axfr) any type of server, and performs updates via DDNS which insures that it won't interfere with other DDNS clients (DHCP, SAMBA4). F The LDAP plugin features browsing and generic editing of all types of LDAP entries with schema support. ... -
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SBW (Systems Biology Workbench)
Framework for Systems Biology
The Systems Biology Workbench(SBW) is a framework for application intercommunications. It uses a broker-based, distributed, message-passing architecture, supports many languages including Java, C++, Perl & Python, and runs under Linux,OSX & Win32. It comes with a large number of modules, encompassing the whole modeling cycle: creating computational models, simulating and analyzing them, visualizing the information, in order to improve the models. -
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VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g.,... -
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proreports
Simple Reporting System
...This type of report templates can be prepared in external editor, such as iReport. Also user can prepare report in internal format of ProReports (simple Visual Programming Language mixed with PHP5 and JAVA or Python). This give him very high flexibility because in this format there are almost no limits and this is the true power of this simple system.To the system we can attach own plug-ins written in PHP5 or JAVA. System is rather framework for programming reports (and not only - is a good tool for building REST API microservices) than drag&drop tool. -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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Nameko
Python framework for building microservices
Write regular Python methods and classes to implement your service. Nameko will manage connections, transports, and concurrency for you. Spin up multiple service instances to easily scale out. Nameko gives you effortless concurrency by yielding workers when they wait for I/O, leaving you free to handle many requests without the worry of threading. Nameko is compatible with almost any protocol, transport or database. Simply use the built-in extensions, build your own or leverage the... -
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Automation Orchestrator
Automation Orchestrator application to orchestrate digital processes
The Automation Orchestrator allows you to run a local Django Web Application to administrate and orchestrate automation scripts such as Nintex RPA botflows but you may also orchestrate other automation such as Python scripts, batch files, and other RPA tools. The Automation Orchestrator is tested with and supports Nintex RPA version = 15.1. As described on the official Django project site, it "is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. ... -
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MoCo v3
PyTorch implementation of MoCo v3
MoCo v3 is a PyTorch reimplementation of Momentum Contrast v3 (MoCo v3), Facebook Research’s state-of-the-art self-supervised learning framework for visual representation learning using ResNet and Vision Transformer (ViT) backbones. Originally developed in TensorFlow for TPUs, this version faithfully reproduces the paper’s results on GPUs while offering an accessible and scalable PyTorch interface. MoCo v3 introduces improvements for training self-supervised ViTs by combining contrastive... -
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MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation
MaskFormer is a unified framework for image segmentation developed by Facebook Research, designed to bridge the gap between semantic, instance, and panoptic segmentation within a single architecture. Unlike traditional segmentation pipelines that treat these tasks separately, MaskFormer reformulates segmentation as a mask classification problem, enabling a consistent and efficient approach across multiple segmentation domains. Built on top of Detectron2, it supports a wide range of datasets...