Search Results for "linux utilities" - Page 11
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Showing 383 open source projects for "linux utilities"
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VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
VideoPose3D is a deep learning framework that reconstructs 3D human poses from 2D keypoint sequences extracted from videos. It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. By using only 2D... -
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Jeffy
Serverless Application Framework for Python AWS Lambda
Jeffy is a Serverless "Application" Framework for Python consisting of a suite of Utilities for Lambda functions that make developing serverless applications easy. There are three main things that Jeffy is focused on: 1. Logging - Jeffy provides easy to see JSON format logging. All events, responses and errors are captured and you can make configurations for any additional attributes you'd like to see on the logs. 2. Decorators - Jeffy has an extensive range of decorators/ event... -
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NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional... -
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Higher
higher is a pytorch library
higher is a specialized library designed to extend PyTorch’s capabilities by enabling higher-order differentiation and meta-learning through differentiable optimization loops. It allows developers and researchers to compute gradients through entire optimization processes, which is essential for tasks like meta-learning, hyperparameter optimization, and model adaptation. The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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BPF Performance Tools
Official repository for the BPF Performance Tools book
BPF Performance Tools Book is the companion repository for Brendan Gregg’s book on Linux performance analysis using eBPF and BCC tracing technologies. The project contains scripts, examples, and reference material that demonstrate how to inspect kernel behavior, application performance, CPU usage, networking activity, file systems, and system bottlenecks in real time. It serves as both an educational resource and a practical toolkit for Linux engineers, SREs, and performance analysts working... -
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Retro
Retro Games in Gym
RETRO (Retrieval-Enhanced Transformer) is a large language model architecture developed by OpenAI that augments transformer models with a retrieval mechanism. Instead of relying solely on learned parameters, RETRO retrieves relevant documents from a large external database during inference, allowing it to ground responses in external knowledge. This design improves factual accuracy, reduces hallucinations, and enables smaller models to perform comparably to much larger ones by leveraging... -
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sysadmin-util
Tools for Linux/Unix sysadmins
sysadmin-util is a compact collection of small, practical command-line utilities gathered for everyday system administration tasks. The repository contains a variety of single-purpose scripts that solve common problems such as determining file ages, testing SSH connectivity, checking MySQL slave status, expanding IPv6 addresses, sending metrics to Graphite, and working with IP ranges. The project intentionally keeps the set small and focused, emphasising quality and personal usefulness over... -
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VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies... -
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EverydayWechat
Python tool that automates WeChat messages, replies, & group utilities
EverydayWechat is a Python-based automation tool designed to enhance and automate interactions on the WeChat messaging platform. Built using Python 3 and the Itchat library, it connects to the web version of WeChat to perform various automated messaging tasks. It allows users to send scheduled messages to friends or group chats, including daily weather updates, reminders, inspirational quotes, and other personalized content. It also supports intelligent automatic replies to incoming messages... -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as... -
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DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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yapyutils
Utilities for platform indepentent low-level system APIs.
The 'yapyutils' - Yet Another Python Utils - package provides miscellaneous *Python* utilities for the adaptation of platform independent APIs of the low-level part of the software stack. These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. The more complex and complete data packages are provided for higher application layer... -
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
PyTorch-BigGraph (PBG) is a system for learning embeddings on massive graphs—think billions of nodes and edges—using partitioning and distributed training to keep memory and compute tractable. It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. PBG supports multi-relation graphs (knowledge graphs) with relation-specific scoring functions,... -
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Spotlight
Deep recommender models using PyTorch
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various pointwise and pairwise ranking losses), representations (shallow factorization representations, deep sequence models), and utilities for fetching (or generating) recommendation datasets, it aims to be a tool for rapid exploration and prototyping of new recommender models. Spotlight offers a slew of popular datasets, including Movielens 100K, 1M,... -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The... -
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PyRobot
An Open Source Robotics Research Platform
PyRobot is a high-level robotics API that simplifies controlling real and simulated robots through a consistent Python interface. Instead of fighting ROS internals, you call clear methods for things like base navigation, arm manipulation, and camera capture, and PyRobot handles the plumbing. It was built to make research repeatable on accessible platforms—most notably low-cost mobile manipulators—while still scaling to richer hardware. The library exposes canonical abstractions (base, arm,... -
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually... -
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numpy_exercises
Numpy exercises
numpy_exercises is a collection of short practice problems designed to teach numerical computing through individual NumPy functions. The material is organized as Jupyter notebooks so learners can work interactively and compare their answers with companion solution notebooks. Exercises cover array creation, manipulation, string operations, help utilities, input and output, and linear algebra. Additional sections address discrete Fourier transforms, logic functions, mathematics, random... -
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CrimeKgAssitant
Crime assistant including crime type prediction
CrimeKgAssitant is a Chinese-language legal NLP project that combines offense prediction, consultation classification, automated answers, and knowledge graph queries. It organizes data around criminal charges, sentencing cases, legal question-and-answer pairs, and related legal information. A multiclass model predicts likely offense categories from written case descriptions using document embeddings and a support vector machine. Separate classifiers sort consultation questions into... -
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Finetune Transformer LM
Code for "Improving Language Understanding by Generative Pre-Training"
finetune-transformer-lm is a research codebase that accompanies the paper “Improving Language Understanding by Generative Pre-Training,” providing a minimal implementation focused on fine-tuning a transformer language model for evaluation tasks. The repository centers on reproducing the ROCStories Cloze Test result and includes a single-command training workflow to run the experiment end to end. It documents that runs are non-deterministic due to certain GPU operations and reports a median... -
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LUMINOTH
Deep Learning toolkit for Computer Vision
LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. Luminoth includes support for popular object... -
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Spatial Media
Specifications and tools for 360º video and spatial audio
spatial-media provides tools for working with spherical video and spatial audio metadata so players and platforms can correctly render immersive media. The utilities inject, inspect, and extract metadata in common container formats (MP4/WebM) to signal 360° projection type, stereoscopy mode, and spatial audio layout. Creators use it to prepare 360/VR180 assets for upload so services know whether a video is monoscopic, top-bottom stereo, or side-by-side, and whether ambisonic audio is...
