Search Results for "processing" - Page 84
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Showing 6571 open source projects for "processing"
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discogs_prices
Adds prices to a Discogs.com exported Collections/Wantlist CSV File
Takes a discogs.com exported csv file of a collection or wantlist and processes each line of the file. While processing each line, it will get the "release" number field, go to the specific "release" web page on discogs.com and download the page. As it downloads the page, it extracts the Lowest, Median, and highest price values and appends the information to the end of each line to a new csv file. That's it! Online version is available her: http://kiria.duckdns.org/discogs -
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WePY
Framework that allows programs to support componentized development
...Through polyfill, the mini program perfectly supports Promise and solves callback troubles. Features such as Generator Function / Class / Async Function can be used to greatly improve development efficiency. Support a variety of plug-in processing, such as file compression, image compression, content replacement, etc., easy to expand and easy to use. -
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Program wordTabulator is intended for text analysis. It can generate index of word elements extracted from defined text set. Word elements may be words, N-grams or phrases (syntagmes). The program can process texts as in ordinary 1-byte encoding (ANSI), as in multibyte UTF-8 encoding.
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...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 creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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Processing
Source code for the processing core and development environment
Processing is a flexible software sketchbook and a language for learning how to code within the context of the visual arts. Since 2001, Processing has promoted software literacy within the visual arts and visual literacy within technology. There are tens of thousands of students, artists, designers, researchers, and hobbyists who use processing for learning and prototyping. -
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Trinity
Android video record editor muxer sdk
trinity is an open-source shooting and short video processing tool, written in kotlin and C++, which implements most of the popular features of short video editing software. -
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
...The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. Users can adapt the examples to their own data sources, financial instruments, and modeling techniques. -
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FavFreak
Favicon hash–based reconnaissance tool for security research
FavFreak is an open source reconnaissance tool designed to assist security researchers, bug bounty hunters, and penetration testers in identifying web technologies using favicon hashes. It works by taking one or more URLs as input and automatically retrieving the favicon.ico file associated with each target website. After fetching the favicon, it calculates a hash value and organizes the scanned domains, subdomains, or IP addresses according to these hashes. FavFreak then compares the... -
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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EpMedia
The video processing framework based on FFmpeg developed on Android
The video processing framework based on FFmpeg developed on Android is simple, easy to use, and small in size, helping users quickly realize video processing functions. Contains the following functions: editing, cropping, rotating, etc. -
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PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
PyCBC is a software developed by a collaboration of LIGO, Virgo, and independent scientists. It is open source and freely available. We use PyCBC in the detection of gravitational waves from binary mergers such as GW150914. These examples explore how to analyze gravitational wave data, how we find potential signals and learn about them. Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like... -
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exchange-core java
Ultra-fast matching engine written in Java based on LMAX Disruptor
...HFT optimized. Priority is a limit-order-move operation mean latency (currently ~0.5µs). Cancel operation takes ~0.7µs, placing new order ~1.0µs. Pipelined multi-core processing (based on LMAX Disruptor): each CPU core is responsible for certain processing stage, user accounts shard, or symbol order books shard. -
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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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FREE CSV & Text (TXT) File Splitter
Ability to work with large csv files and cut them down to run in Excel
This CSV and TXT file splitter firstly allows you to work with large data files. We have tested this on the largest CSV file we could find. It had over 25.6 Million rows. Microsoft Excel can only load 1 Million rows. So the challenege was on! Splitting a file in this case by 990,000 rows made sure that it was more than capable to load into excel. Splitting 25.6Million rows took aroud 50 minutes. Has been tested reading 25Million rows which took around 15 seconds to read. Its... -
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uTensor
TinyML AI inference library
...Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized inference kernels suitable for constrained environments. This approach allows developers to build machine learning models using standard frameworks and then deploy them to devices with extremely limited memory and processing power. The runtime library is intentionally lightweight and optimized for platforms such as Arm Cortex-M microcontrollers, making it suitable for real-time edge applications. -
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Xi Editor
A modern editor with a backend written in Rust
...Its architecture splits a thin UI layer from a high-performance core engine (written in Rust) that handles buffer editing, syntax highlighting, undo/redo, searching, and background processing asynchronously. This separation lets the core focus on speed and concurrency, while multiple frontends (macOS, GTK, web) handle rendering, input, and platform bridging. Xi is designed to scale to huge files (gigabyte scale) without lag, thanks to a rope data structure and efficient diffing algorithms. Plugins communicate with the core via JSON-RPC, enabling asynchronous extensions without blocking editing responsiveness. ... -
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Albedo
A recommender system for discovering GitHub repos
...It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. ... -
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Forms
An easy way to create, parse and validate forms in node.js
...Forms also provides utilities for rendering HTML form elements, reducing the need for manual template coding. It integrates with popular Node.js web frameworks, enabling seamless handling of form submissions and data processing. The design emphasizes reusability and maintainability, allowing developers to define forms once and use them across different parts of an application. -
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Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more. -
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opencv4nodejs
Nodejs bindings to OpenCV 3 and OpenCV 4
OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition. -
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NVComponents
Components and tools for signal processing and visualisation
TNVCoordSys is a simple component for scientific data plotting; NVCommon file contains classes for handling of dynamic arrays of real points (X,Y:float) and of real numbers. Llist contains class for handling of circular double-linked list. NVFilters contains implementation of Gaussian, moving average and median filters for signal processing. NVNumericEdits contains TFloatEdit component. NumericInputDialogs contains function FloatInputDialog. They all use uTypes unit from DMath library for use of Float type, which may be Single, Double or Extended, depending of compilation flag. You can define Float = double (for example) yourself, if you do not want to depend on this library. ... -
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G Desktop Suite
Google Suite as a desktop app. Made possible with Electron
Have you ever wished you had a no-frills, word-processing desktop app dedicated to just Google Drive? Annoyed at having to click the Go to My Drive button every time you visit drive.google? Want a Microsoft Word-esque experience for your Google Drive? Or simply looking to separate Google Drive from the other bazillion tabs that you opened for your research paper? Look no further! G Desktop Suite is a desktop wrapper for Google Drive built with ElectronJS. -
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ffmpeg.js
Port of FFmpeg with Emscripten
ffmpeg.js is a JavaScript port of the FFmpeg multimedia framework compiled with Emscripten, enabling video and audio processing directly within browsers or Node.js environments. It provides prebuilt modules optimized for web use, balancing performance and file size while supporting common encoding and decoding tasks. By running entirely in JavaScript through asm.js, it allows developers to manipulate media files without requiring native binaries or server-side processing. ... -
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BRIC
BRIC is a powerful tool for batch image processing.
Bric is a cross-platform batch image processor. You can convert, resize, rotate and add watermark to your images. Multiple file types are supported for input and output. The project started back in 2011 and was maintained for a couple of years. In 2020 BRIC is again in active development, so some of the features written below might be outdated. Please be patient, until everything is reviewed and rewritten.
