Search Results for "process" - Page 4
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Showing 165 open source projects for "process"
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Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
...DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one to incorporate docking into the generative process, thus providing the agent with 3D structural information. -
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pbxproj
A python module to manipulate XCode projects
...The file is usually called project.pbxproj and can be found inside the .xcodeproj bundle. Because some tasks cannot be done by clicking on a UI or opening Xcode to do it for you, this Python module lets you automate the modification process. The typical tasks with an Xcode project are adding files to the project and setting some standard compilation flags. -
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IOS13-SimulateTouch
iOS Automation Framework iOS Touch Simulation Library
A system-wide touch event simulation library for iOS 11.0 - 14. This library enables you to simulate touch events on iOS 11.0 - 14 with just one line of code! Currently, the repository is mainly for programmers. In the future, I will make it suitable for people who do not understand how to code. -
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peda
Python Exploit Development Assistance for GDB
...Search for all addresses/references to addresses which belong to a memory range. Generate or download common shellcodes. Generate python exploit code template. Get virtual mapping address ranges of section(s) in debugged process. XOR a memory region with a key. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). ... -
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
...During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage. -
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macOS Simple KVM
Tools to set up a quick macOS VM in QEMU, accelerated by KVM
macOS-Simple-KVM is a project that provides scripts and configuration files to easily set up and run macOS in a virtual machine using QEMU and KVM. It simplifies what is typically a complex process by offering a straightforward approach to creating a macOS VM on Linux systems with hardware virtualization support. The repository includes tools for preparing installation media, configuring virtual hardware, and managing VM launch scripts. By using KVM acceleration, the virtual machine runs with near-native performance, making it useful for testing, development, or personal experimentation. ... -
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Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
...The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available. -
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Chisel
A collection of LLDB commands to assist debugging iOS apps
Chisel is a collection of LLDB commands designed to assist you in the process of debugging iOS apps. All of the commands provided by Chisel come with verbose help. Be sure to read it when in doubt! You can add local, custom commands. There's also builtin support to make it super easy to specify the arguments and options that a command takes. See the border and pinvocation commands for example use. Developing commands, whether for local use or contributing to Chisel directly, both follow the same workflow. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. ... -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
...The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile for performance analysis. It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. The framework includes a comprehensive set of predefined benchmarks covering areas such as compute, storage, networking, and distributed systems workloads. It is widely used by researchers, engineers, and organizations to evaluate cloud architectures and make informed infrastructure decisions. -
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SkyWater PDK
Open source process design kit for usage with SkyWater Technology
...Documentation and example flows show how to assemble complete toolchains, from RTL to sign-off, using open EDA components. The project effectively lowers the barrier to custom silicon, catalyzing an ecosystem around an accessible 130-nm process. -
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Clay Golem
Golem is creating a global market for computing power
...Golem’s democratized access combined with a unique peer-to-peer exchange creates an unstoppable ecosystem for a myriad of use-cases to be born, allowing software developers to leverage their creativity more than ever before. The Golem Network, through its cutting-edge architecture, lets developers create ambitious projects without constraints, enabling users to process them at top speeds. -
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Kopf
A Python framework to write Kubernetes operators
Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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sublime-jekyll
A Sublime Text package for Jekyll static sites
This package is aimed at streamlining the process of managing and creating new Jekyll posts. It does this by providing quick and easy access to new post and draft commands, snippets and completions for Liquid template tags and filters, as well as some handy commands for adding dates and upload links to your posts. -
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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. -
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pybag
Crossplatform files synchronization and backup portable tool.
...You can specify rules for automatic conflict resolution. With PYBAG, you can backup files and synchronize any changes made to the original files with the bag. The synchronization process will only copy changed files. The program is cross-platform and independent from the OS and file system. You may easily synchronize files between Windows and Linux, for example. Symbolic links are supported on all systems (if the OS or file system does not support symlinks, then they are emulated). This program has a GUI and a command line interface. -
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Coach
Enables easy experimentation with state of the art algorithms
...It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. Coach supports a large number of environments which can be solved using reinforcement learning. -
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pipupgrade
Like yarn outdated/upgrade, but for pip
pipupgrade is a command-line utility designed to streamline the management of Python package dependencies. It automates the process of identifying and upgrading outdated packages across various Python environments, including system-wide installations, virtual environments, and project-specific setups. By analyzing semantic versioning, pipupgrade categorizes updates into major, minor, and patch changes, allowing developers to make informed decisions about which packages to upgrade. ... -
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Walle 2.0
Walle 2.0 web
...Permissions, notifications, file fingerprints. Independent space resources like gitlab. Custom environment, environment variables. Project administrator, a notification mechanism, custom hooks in each process. Get through server management, grayscale release. Advanced gitlab-like user management mode. Online order application, review, grayscale release, real-time websocket. Walle allows users to release code and finally can not only choose jenkins! Support various web code releases, release and rollback of php, java, python, go and other codes can be completed with one click through the web. walle is a freely configurable project, more user-friendly, high-value, an open source online deployment system that supports git, multi-user, multi-language, multi-project, and multi-environment simultaneous deployment. -
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pangu.py
Paranoid text spacing in Python
...Mixed-script text often becomes cramped or ambiguous, and this library applies simple but effective typography rules to make it instantly more readable. It works both as a Python library and a command-line utility, so you can process strings in code, tidy files in bulk, or wire it into documentation and build pipelines. The transformation is idempotent: running it multiple times won’t keep adding spaces, which makes it safe in automated workflows. It’s designed to be pragmatic and lightweight, with sensible defaults that handle common edge cases found in websites, blogs, and multilingual technical docs. ... -
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PySys is a Python based framework for the organisation and execution of system level automated and manual testcases. PROJECT MOVED: As of April 2019, PySys has moved to GitHub and is no longer maintained on SourceForge, so for the development project go to https://github.com/pysys-test/pysys-test or for end-users of PySys go to https://pypi.org/project/PySys/
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etalon
Standards Document Redaction System
The best process for creating standards is that of the IETF’s RFCs. Standard documents are written, submitted for publication, reviewed, and finally approved. Then they get a official number and hence can be referenced. Some can even be blessed to be an official standard. Etalon will implement this whole process, web-based and with markdown documents. -
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Dr0p1t-Framework
A framework that create an advanced stealthy dropper
Dr0p1t-Framework is a penetration testing tool designed to generate advanced and stealthy droppers capable of delivering and executing payloads on target systems while evading detection mechanisms. A dropper is a type of malware used to download and install additional malicious software, and this framework focuses on making that process more flexible and difficult to detect. It provides a wide range of modules that allow users to customize payload delivery, persistence mechanisms, and execution methods. The framework includes features such as antivirus evasion, privilege escalation, and system persistence, enabling it to maintain access on compromised systems. ... -
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Compare GAN
Compare GAN code
...With configuration-driven experiments, you can sweep hyperparameters, run ablations, and log results at scale. The goal is to turn GAN experimentation into a disciplined, repeatable process rather than a patchwork of scripts. It also provides baselines strong enough to serve as starting points for new ideas without re-implementing the world.
