Showing 59 open source projects for "linux new distribution"

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  • 1
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV...
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  • 2
    Kalliope

    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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  • 3
    Manticore

    Manticore

    Symbolic execution tool

    Manticore helps us quickly take advantage of symbolic execution, taint analysis, and instrumentation to analyze binaries. Parts of Manticore underpinned our symbolic execution capabilities in the Cyber Grand Challenge. As an open-source tool, we hope that others can take advantage of these capabilities in their own projects. We prioritized simplicity and usability while building Manticore. We used minimal external dependencies and our API should look familiar to anyone with exploitation or...
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  • 4
    Model Search

    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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  • 5
    StreamAlert

    StreamAlert

    StreamAlert is a serverless, realtime data analysis framework

    StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs. Rules are written in Python; they can utilize any Python libraries or...
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  • 6
    TorchGAN

    TorchGAN

    Research Framework for easy and efficient training of GANs

    The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to...
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  • 7
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also...
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  • 8
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,...
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  • 9
    PyTorch SimCLR

    PyTorch SimCLR

    PyTorch implementation of SimCLR: A Simple Framework

    For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the...
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  • 10
    HyperGAN

    HyperGAN

    Composable GAN framework with api and user interface

    A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with...
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  • 11
    PyText

    PyText

    A natural language modeling framework based on PyTorch

    PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly...
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  • 12
    Miasm

    Miasm

    Reverse engineering framework in Python

    The Miasm intermediate representation is used for multiple task: emulation through its jitter engine, symbolic execution, DSE, program analysis, but the intermediate representation can be a bit hard to read. We will present in this article new tricks Miasm has learned in 2018. Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout...
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  • 13
    platformids

    platformids

    OS and Distribution Release Enumeration

    The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. The supported...
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  • 14
    Django Celery

    Django Celery

    Old Celery integration project for Django

    Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a...
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  • 15
    Offensive Web Testing Framework

    Offensive Web Testing Framework

    Offensive Web Testing Framework (OWTF), is a framework

    ...Demonstrate true impact despite the short timeframes we are typically given to test. The tool is highly configurable and anybody can trivially create simple plugins or add new tests in the configuration files without having any development experience. OWTF is developed on KaliLinux and macOS but it is made for Kali Linux (or other Debian derivatives).
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  • 16
    Django JET

    Django JET

    Modern responsive template for the Django admin interface

    Django JET has two kinds of licenses: open-source (AGPLv3) and commercial. Please note that using AGPLv3 code in your programs makes them AGPL compatible too. So if you don't want to comply with that we can provide you a commercial license (visit the Home page). The commercial license is designed for using Django JET in commercial products and applications without the provisions of the AGPLv3. Add URL-pattern to the URL patterns of your Django project urls.py file (they are needed for...
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  • 17
    Bowtie

    Bowtie

    Create a dashboard with python!

    Bowtie is a library for writing dashboards in Python. No need to know web frameworks or JavaScript, focus on building functionality in Python. Interactively explore your data in new ways! Deploy and share with others! Bowtie uses Yarn to manage node packages. If you installed Bowtie through conda, Yarn was also installed as a dependency. Yarn can be installed through conda. An early integration with Jupyter has been prototyped. I encourage you to try it out and share feedback. I hope this...
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  • 18

    Aglyph

    Aglyph is a Dependency Injection framework for Python.

    Aglyph is a Dependency Injection framework for Python, supporting type 2 (setter) and type 3 (constructor) injection. Aglyph runs on CPython (http://www.python.org/) 2.7 and 3.4+, and on recent versions of the PyPy (http://pypy.org/>),Jython (http://www.jython.org/), IronPython (http://ironpython.net/), and Stackless Python (http://www.stackless.com/) variants. Aglyph can assemble "prototype" components (a new instance is created every time), "singleton" components (the same instance...
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  • 19
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
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  • 20
    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django - Code Samples

    Code samples from the Django tutorial series. I’m starting a new tutorial series about Django fundamentals. It’s a complete beginner’s guide to start learning Django. The material is divided into seven parts. We’re going to explore all the basic concepts in great detail, from installation, and preparation of the development environment, models, views, templates, URLs to more advanced topics such as migrations, testing, and deployment. I wanted to do something different. A tutorial that would...
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  • 21
    seq2seq

    seq2seq

    A general-purpose encoder-decoder framework for Tensorflow

    seq2seq is an early, influential TensorFlow reference implementation for sequence-to-sequence learning with attention, covering tasks like neural machine translation, summarization, and dialogue. It packaged encoders, decoders, attention mechanisms, and beam search into a modular training and inference framework. The codebase showcased best practices for batching, bucketing by sequence length, and handling variable-length sequences efficiently on GPUs. Researchers used it as a baseline to...
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  • 22
    katana Framework
    katana is the new hacking framework written in python for making penetration testing.
    Downloads: 14 This Week
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  • 23
    SW Test Automation Framework
    The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
    Downloads: 32 This Week
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  • 24
    nacho

    nacho

    Python micro web-framework and asynchronous networking library

    Nacho is an open-source CLI tool (or library) that streamlines the creation of RESTful APIs, scaffolding, or microservices in a chosen framework, reducing boilerplate and enabling rapid building of backend services. It focuses on productivity by providing commands to generate endpoints, data models, controllers, and routing based on standard patterns (CRUD, REST conventions). The tool also includes support for middleware integration, automatic documentation (such as via OpenAPI/Swagger), and...
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  • 25
    GEPETTO - Gene Prioritization in Java

    GEPETTO - Gene Prioritization in Java

    GEPETTO (GEne Prioritization ExTended TOol)

    GEPETTO (GEne PrioriTization ExTended TOol) is an original open-source framework, distributed under the LGPL license, for gene selection and prioritization on a desktop computer that ensures confidentiality of personal data. It takes advantage of the data integration capabilities in the SM2PH-Central Framework(KD4v,MSV3d,BIRD,..), combined with in-house developed gene prioritization methods. It currently incorporates six prioritization modules, based on gene sequence, protein-protein...
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