Search Results for "one-wire"
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Showing 88 open source projects for "one-wire"
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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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Secdev Scapy
Scapy: the Python-based interactive packet manipulation program
Scapy is a powerful interactive packet manipulation libary written in Python. Scapy is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. Scapy can be used as a REPL or as a library. It provides all the tools and documentation to quickly add custom network layers. Scapy runs natively on Linux, macOS, most Unixes, and on Windows with Npcap. It is published under GPLv2. Starting from version 2.5.0+, it supports Python 3.7+ (and PyPy). ... -
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Buildozer
Generic Python packager for Android and iOS
...Buildozer manages a file named buildozer.spec in your application directory, describing your application requirements and settings such as title, icon, included modules, etc. It will use the specification file to create a package for Android, iOS, and more. The goal is to have one "buildozer.spec" file in your app directory, describing your application requirements and settings such as title, icon, included modules etc. Buildozer will use that spec to create a package for Android, iOS, Windows, OSX and/or Linux. -
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PyTensor
Python library for defining and optimizing mathematical expressions
...Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano. -
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pikepdf
A Python library for reading and writing PDF, powered by QPDF
pikepdf is a Python library allowing the creation, manipulation, and repair of PDFs. It provides a Pythonic wrapper around the C++ PDF content transformation library, QPDF. Python + QPDF = “py” + “qpdf” = “pyqpdf”, which looks like a dyslexia test and is no fun to type. But say “pyqpdf” out loud, and it sounds like “pikepdf”. pikepdf is a library intended for developers who want to create, manipulate, parse, repair, and abuse the PDF format. It supports reading and write PDFs, including... -
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PDFSticher
Code repository for PDFStitcher, a utility to stitch together PDFs
The open source PDF stitching software for sewists, by sewists. PDFSticher is a utility for stitching together many PDF pages from one document into a single page. This is also called "N-Up" or page imposition. This program was created in order to convert sewing patterns into a convenient format for projecting, though it could be used to stitch together any PDF. Since version 0.4, it is also possible to select layers for inclusion/exclusion in the final output. Additionally, line properties can be modified for each layer if the input PDF is compatible. -
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SciPy
SciPy library main repository
This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. ... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. Aim is an open-source experiment tracker that logs your training runs, and enables a beautiful UI to compare them. -
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ART ASCII Library
ASCII art library for Python
ASCII art is also known as "computer text art". It involves the smart placement of typed special characters or letters to make a visual shape that is spread over multiple lines of text. ART is a Python lib for text converting to ASCII art fancy. -
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DocTR
Library for OCR-related tasks powered by Deep Learning
...End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). As such, you can select the architecture used for text detection, and the one for text recognition from the list of available implementations. -
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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spaCy
Industrial-strength Natural Language Processing (NLP)
...It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. It's blazing fast, easy to install and comes with a simple and productive API. -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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borb
borb is a library for reading, creating and manipulating PDF files
borb is a library for creating and manipulating PDF files in python. borb is a pure python library to read, write, and manipulate PDF documents. It represents a PDF document as a JSON-like data structure of nested lists, dictionaries and primitives (numbers, string, booleans, etc) This is currently a one-man project, so the focus will always be to support those use-cases that are more common in favor of those that are rare. -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to plug in custom models, track experiments, tune hyperparameters, and generate visualizations that highlight anomalous regions. ... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock prices is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. ... -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Validate the functions that produce your data by automatically generating test cases for them. Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects. -
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MediaManager
A modern selfhosted media management system for your media library
...Rather than relying on separate tools patched together, MediaManager offers a streamlined interface and workflow where media metadata, collection insights, and automation policies live side-by-side in one system. It is designed for ease of deployment with Docker, supports standardized metadata sources such as TMDB and TVDB, and integrates OAuth/OIDC for secure authentication. Users can browse, search, and manage their media with a responsive web frontend while developers benefit from a clean codebase that uses Python and modern web technologies. ... -
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sqlite-utils
Python CLI utility and library for manipulating SQLite databases
...It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a library, it exposes high-level APIs for inserting records, creating or transforming tables, normalizing schemas, and running migrations that SQLite’s limited ALTER TABLE cannot handle directly. ... -
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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. Each day mixes explanation with at least one concrete project or lab, such as deploying applications on EC2, designing secure VPCs, setting up CI/CD pipelines, or configuring CloudWatch monitoring. ... -
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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... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively... -
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py2many
Transpiler of Python to many other languages
...Specialized languages such as wuffs exist to address this use case. py2many can be a more general-purpose solution to the problem where you can verify the source via unit tests before you transpile. Swift and Kotlin dominate the mobile app development workflow. However, there is no one solution that works well for lower level libraries where there is desire to share code between platforms. Kotlin Mobile Multiplatform (KMM) is a player in this place, but it hasn't really caught on. py2many provides an alternative. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU. -
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django-split-settings
Organize Django settings into multiple files and directories
...Use wildcards in settings file paths and mark settings files as optional. Managing Django’s settings might be tricky. There are severals issues which are encountered by any Django developer along the way. First one is caused by the default project structure. Django clearly offers us a single settings.py file. It seams reasonable at the first glance. And it is actually easy to use just after the start. But when it comes to the real-world it only causes misunderstanding and frustration. At some point, you will need to put some kind of personal settings in the main file: certificate paths, your username or password, database connection, etc. ... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL benchmarks (similar to what has been done for torchvision). Provides all the necessary utilities concerning model training. This includes simple and efficient ways of implementing new continual learning strategies as well as a set of pre-implemented CL baselines and state-of-the-art algorithms you will be able to use for comparison! ... -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. ...