Search Results for "fast linux" - Page 17
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Showing 707 open source projects for "fast linux"
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and metrics. Full transparency... -
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googler
Google Search, Google Site Search, Google News from the terminal
googler is a power tool to Google (Web & News) and Google Site Search from the command-line. It shows the title, URL and abstract for each result, which can be directly opened in a browser from the terminal. Results are fetched in pages (with page navigation). Supports sequential searches in a single googler instance. googler was initially written to cater to headless servers without X. You can integrate it with a text-based browser. However, it has grown into a very handy and flexible... -
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3DDFA
Fast, accurate and stable 3D dense face alignment
This work extends 3DDFA, named 3DDFA_V2, titled Towards Fast, Accurate and Stable 3D Dense Face Alignment, accepted by ECCV 2020. The supplementary material is here. The gif above shows a webcam demo of the tracking result, in the scenario of my lab. This repo is the official implementation of 3DDFA_V2. Compared to 3DDFA, 3DDFA_V2 achieves better performance and stability. Besides, 3DDFA_V2 incorporates the fast face detector FaceBoxes instead of Dlib. -
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bioweb
polyglot language framework to analyze genetic data
polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences -
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Metrix++
Management of source code quality is possible.
The project has been moved to https://github.com/metrixplusplus/metrixplusplus ______________________ Metrix++ is an extendable tool to collect and analyse code metrics. - Multiple languages supported - Multiple metrics available - Configurable. Every metric has got 'turn-on' and other configuration options. There are no predefined thresholds for metrics or rules. You can choose and configure any limit you want. - High-performance. Processes thousands of files per minutes. -... -
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Nebula-Python-SDK
A python SDK for managing Nebula container orchestrator
A python SDK for managing Nebula container orchestrator. First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free.... -
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LiVES
LiVES is a Video Editing System. It is designed to be simple to use, y
LiVES mixes realtime video performance and non-linear editing in one professional quality application. It is designed to be simple to use, yet powerful. It is small in size, yet it has many advanced features. Using LiVES, you can start editing and making video right away, without having to worry about formats, frame sizes, or framerates. It is a very flexible tool which is used by both professional VJ's and video editors - mix and switch clips from the keyboard, use dozens of realtime... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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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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Delta ML
Deep learning based natural language and speech processing platform
DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train,... -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
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Magnitude
A fast, efficient universal vector embedding utility package
A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP. Published in our paper at EMNLP 2018 and available on arXiv. -
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Coronavirus Tracker API
API for tracking the global coronavirus (COVID-19, SARS-CoV-2)
Provides up-to-date data about Coronavirus outbreak. Includes numbers about confirmed cases, deaths and recovered. Support multiple data sources. Specify source parameter with ?source=nyt. NYT also provides a timeseries! To view timelines of cases by US counties use ?source=nyt&timelines=true. Currently, 3 different data sources are available to retrieve the data. Worldwide Data repository operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). U.S.... -
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DNSGen
Intelligent DNS permutation tool for subdomain discovery
DNSGen is an open source DNS name permutation tool designed primarily for security researchers and penetration testers who need to discover potential subdomains during reconnaissance and attack surface mapping. It analyzes existing domain names and generates numerous intelligent variations that may represent valid subdomains within an organization’s infrastructure. These generated permutations help identify hidden or unlisted services that may not appear in standard DNS queries or public... -
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SCiDA Pro
Program for solar cell production data analysis
The purpose of the SCiDA Pro program is to help with processing solar cell production data. It has the following features: - Able to handle large data sets in a fast way (e.g. plotting 100k cell data takes a few seconds) - Easy data filtering - Easy generation of a data summary report - Extensive data plotting features - Cross-platform (Windows/Linux/MacOS) - Supports multiple languages -
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LuninuxOS
LuninuxOS is a Debian/Ubuntu based Linux distribution.
A Linux operating system, designed and developed to be beautiful, simple, fast, and stable on many computer hardware. -
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hyperjson
Python module for reading/writing JSON data using Rust's serde-json
A hyper-fast, safe Python module to read and write JSON data. Works as a drop-in replacement for Python's built-in json module. This is alpha software and there will be bugs, so maybe don't deploy to production just yet. -
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Yandex Tank
Load and performance benchmark tool
Yandex.Tank is an extensible open-source load testing tool for advanced Linux users which is especially good as a part of an automated load testing suite. Different load generators are supported. Evgeniy Mamchits' phantom is a very fast (100 000+ RPS) shooter written in C++ (default) JMeter is an extendable and widely known one. BFG is a Python-based generator that allows you to write your load scenarios in Python. -
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Bangla TTS
Bangla text to speech synthesis in python
Bangla text to speech Multilingual (Bangla, English) real-time ([almost] in a GPU) speech synthesis library. Installation -------------------------------------- * Install Anaconda * conda create -n new_virtual_env python==3.6.8 * conda activate new_virtual_env * pip install -r requirements.txt * While running for the first time, keep your internet connection on to download the weights of the speech synthesis models (>500 MB) * For... -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable... -
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TooDoo
Todo task manager with simple, fast and intuitive user interface
Todo task manager with simple, fast and intuitive user interface. It supports subtasks, reminders, user defined statuses, categories and filters, custom ordering, text formatting, clickable links etc. Overview of functions: https://sourceforge.net/p/too-doo/wiki/ -
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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this... -
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pythonids
Enumeration of Python implementations and releases
The ‘pythonids‘ package provides the enumeration of Python syntaxes and the categorization of Python implementations. This enables the development of fast and easy portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The current supported syntaxes are Python2.7+ and Python3 for the Python implementations: CPython IPython (based on CPython) IronPython Jython PyPy -
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platformids
OS and Distribution Release Enumeration
...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 version numbering comprise various release schemes such as classical version numbers with variable segments and optional release names, * AlpineLinux-3.8.1 * CentOS-6.10 * Debian-9.6 * Fedora31 * OS-X-10.6.8 * Ubuntu-18.04 * armbian-5.76 * cygwin-2.9.0 * opensuse-15.1 * raspbian-9.4 * slackware-14.2 * solaris-11.3 variations of numbering schemes and continous deployment * CentOS-7.6-1810 * NT-6.3.9600 * archlinux-2018.12.01 * kali-linux-2019.1 * NT-10.0.1809 -
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hug
Embrace the APIs of the future. For developing APIs
hug aims to make developing Python-driven APIs as simple as possible, but no simpler. As a result, it drastically simplifies Python API development. Make developing a Python-driven API as succinct as a written definition. The framework should encourage code that self-documents. It should be fast. A developer should never feel the need to look somewhere else for performance reasons. Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API...
