Open Source Algorithms - Page 4
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. 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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CryptoSwift
Collection of standard and secure cryptographic algorithms
The master branch follows the latest currently released version of Swift. If you need an earlier version for an older version of Swift, you can specify its version in your Podfile or use the code on the branch for that version. Older branches are unsupported. Swift Package Manager uses debug configuration for debug Xcode build, that may result in significant (up to x10000) worse performance. Performance characteristic is different in Release build. XCFrameworks require Xcode 11 or later and they can be integrated similarly to how we’re used to integrating the .framework format. Embedded frameworks require a minimum deployment target of iOS 9 or macOS Sierra (10.12). CryptoSwift uses array of bytes aka Array<UInt8> as a base type for all operations. Every data may be converted to a stream of bytes. You will find convenience functions that accept String or Data, and it will be internally converted to the array of bytes. -
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DecisionTree.jl
Julia implementation of Decision Tree (CART) Random Forest algorithm
Julia implementation of Decision Tree (CART) and Random Forest algorithms. -
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Delaunator
Fast JavaScript library for Delaunay triangulation of 2D points
Delaunator is a fast library for Delaunay triangulation. It takes as input a set of points. The triangulation is represented as compact arrays of integers. It’s less convenient than other representations but is the reason the library is fast. After constructing a delaunay = Delaunator.from(points) object, it will have a triangles array and a halfedges array, both indexed by half-edge id. What’s a half-edge? A triangle edge may be shared with another triangle. Instead of thinking about each edge A↔︎B, we will use two half-edges A→B and B→A. Having two half-edges is the key to everything this library provides. It will also be useful to have some helper functions to go from one half-edge to the next and previous half-edges in the same triangle. We can draw all the triangle edges without constructing the triangles themselves. -
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FuzzyWuzzy
Fuzzy string matching in Python
We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example completely at random, Cirque du Soleil has a show running in New York called “Zarkana”. When we scour the web to find tickets for sale, mostly those tickets are identified by a title, date, time, and venue. We’ve built up a library of “fuzzy” string matching routines to help us along. And good news! We’re open sourcing it. The library is called “Fuzzywuzzy”, the code is pure python, and it depends only on the (excellent) difflib python library. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
The Grey Wolf Optimizer for Path Planning is a MATLAB-based implementation of the Grey Wolf Optimizer (GWO) algorithm designed for UAV path and trajectory planning. It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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Javascript-Voronoi
JS implementation of Fortune's algorithm to compute Voronoi cells
This repository implements Steven Fortune’s algorithm (sweep-line method) for generating Voronoi diagrams in JavaScript, providing a performant browser-side solution for computational geometry of planar point sets. With this library you can feed a set of sites (points) and compute their Voronoi cells – the partition of the plane into regions closest to each site – in O(n log n) time. It’s especially useful in web UIs, visualizations, interactive maps, and generative-art contexts where you need dynamic tessellations or diagrammatic layouts. The library exposes API functions for computing cells, retrieving neighbors, and drawing results into canvas or SVG. Because it is pure JavaScript and self-contained, it integrates easily with browser or Node.js applications without heavy dependencies. For developers exploring spatial algorithms, generative UI, or interactive diagrams, this codebase is a practical reference and tool to build upon. -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. Researchers can use it to reproduce the experiments presented in the paper, which demonstrate how agents learn behaviors such as coordination, competition, and communication. Although archived, MADDPG remains a widely cited baseline in multi-agent reinforcement learning research and has inspired further algorithmic developments. -
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Pygorithm
A Python module for learning all major algorithms
A Python module to learn all the major algorithms on the go! Purely for educational purposes. If you are using Python 2.7 use pip instead. Depending on your permissions, you might need to use pip install, user pygorithm to install. To see all the available functions in a module, you can just type help() with the module name as an argument. -
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Rubix ML
A high-level machine learning and deep learning library for PHP
Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. Learners such as neural networks will automatically get a performance boost. -
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TBOX
A glib-like multi-platform c library
TBOX is a glib-like cross-platform C library that is simple to use yet powerful in nature. The project focuses on making C development easier and provides many modules (.e.g stream, coroutine, regex, container, algorithm ...), so that any developer can quickly pick it up and enjoy the productivity boost when developing in C language. It supports the following platforms: Windows, Macosx, Linux, Android, iOS, BSD and etc. Supports file, data, http and socket source. Supports the stream filter for gzip, charset. etc. Implements stream transfer. Implements the static buffer stream for parsing data. Supports coroutine and implements asynchronous operation. The coroutine library. Provides high-performance coroutine switch. Supports arm, arm64, x86, x86_64. Provides channel interfaces. Provides semaphore and lock interfaces. Supports io socket and stream operation in coroutine. Provides some io servers (http ..) using coroutine. Provides stackfull and stackless coroutines. -
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TorBot
Dark Web OSINT Tool
Contributions to this project are always welcome. To add a new feature fork the dev branch and give a pull request when your new feature is tested and complete. If its a new module, it should be put inside the modules directory. The branch name should be your new feature name in the format <Feature_featurename_version(optional)>. On Linux platforms, you can make an executable for TorBot by using the install.sh script. You will need to give the script the correct permissions using chmod +x install.sh Now you can run ./install.sh to create the torBot binary. Run ./torBot to execute the program. Crawl custom domains.(Completed). Check if the link is live.(Completed). Built-in Updater.(Completed). TorBot GUI (In progress). Social Media integration.(not Started). -
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Yangshun Lago
Data Structures and Algorithms library in TypeScript and JavaScript
Lago is a study-oriented library of classic data structures and algorithms implemented in JavaScript with an emphasis on readability and learning. Instead of aiming to be a production runtime, it serves as a reference you can step through to understand how arrays, stacks, queues, linked lists, trees, heaps, graphs, and sorting/searching routines actually work. The implementations favor clarity over micro-optimizations, making them approachable for learners who are new to algorithmic thinking or coming from non-CS backgrounds. Because the code is idiomatic JavaScript, it also helps front-end engineers strengthen fundamentals without switching languages. The repository’s structure lets you browse topic by topic and compare trade-offs such as time versus space complexity. It’s a handy companion to interview prep lists: after reading a concept, you can open the matching Lago implementation and trace it line by line. -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python package. For a development installation (used to develop Zipline itself), create and activate a virtualenv, then run the etc/dev-install script. Please note that Zipline is not a community-led project. Zipline is maintained by the Quantopian engineering team, and we are quite small and often busy. -
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java-string-similarity
Implementation of various string similarity and distance algorithms
Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity. A library implementing different string similarity and distance measures. A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. The main characteristics of each implemented algorithm are presented below. The "cost" column gives an estimation of the computational cost to compute the similarity between two strings of length m and n respectively. If the alphabet is finite, it is possible to use the method of four russians (Arlazarov et al. "On economic construction of the transitive closure of a directed graph", 1970) to speedup computation. This was published by Masek in 1980 ("A Faster Algorithm Computing String Edit Distances"). -
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jsprit
Open source toolkit for solving rich vehicle routing problems
jsprit is a java based, open-source toolkit for solving rich Traveling Salesman Problems(TSP) and Vehicle Routing Problems(VRP). It is lightweight, flexible and easy-to-use, and based on a single all-purpose meta-heuristic. Setting up the problem, defining additional constraints, modifying the algorithms and visualizing the discovered solutions is as easy and handy as reading classical VRP instances to benchmark your algorithm. It is fit for change and extension due to its modular design and a comprehensive set of unit and integration tests. Possibility to define additional stateless and stateful constraints/conditions to account for the richness of your problem. GraphHopper invests in an active open source community. Our flagships are the GraphHopper routing engine and jsprit, the toolkit for solving rich vehicle routing problems. We promote a fair & diverse mindset. -
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tsfresh
Automatic extraction of relevant features from time series
tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python. The extracted features can be used to describe or cluster time series based on the extracted characteristics. Further, they can be used to build models that perform classification/regression tasks on the time series. Often the features give new insights into time series and their dynamics. -
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A cross-platform library that computes fast and accurate SIFT image features. libsiftfast provides Octave/Matlab scripts, a command line interface, and a python interface (siftfastpy). Optimized with SIMD instructions and OpenMP .
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Linear Program Solver (Solvexo) is an optimization package intended for solving linear programming problems. The main features of the Solvexo are: · Solvexo solver is based on the efficient implementation of the simplex method (one or two phases); · Solvexo provides not only an answer, but a detailed solution process as a sequence of simplex matrices, so you can use it in studying (teaching) linear programming. · Solvexo provides a solution with the graphic method for problems with tow variables. · This updated version includes two languages English and French. If you have any questions, feel free to contact me: romdhani.mohamed.ali@gmail.com. Any comments and suggestions would be helpful!
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Simd
High performance image processing library in C++
The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems. -
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NeoBio is a Java class library of Computational Biology Algorithms. The current version consists mainly of pairwise sequence alignment algorithms such as the classical dynamic programming methods of Needleman-Wunsch and Smith-Waterman.
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The Safe C Library provides bound checking memory and string functions per ISO/IEC TR24731. These functions are alternative functions to the existing standard C library that promote safer, more secure programming. The ISO/IEC Programming languages — C spec, C11, now includes the bounded APIs in Appendix K, "Bounds-checking interfaces". This latest upload supports building static library, a shared library and a linux kernel module.
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AlgoSim
AlgoSim : création, analyse et exécution des algorithmes
AlgoSim un Logiciel de création, analyse, simulation et exécution des algorithmes. Il ne nécessite aucun apprentissage de langage de programmation. Ce logiciel n'utilise pas un éditeur de texte comme les logiciels classiques de programmation. Ce logiciel peut être utilisé par des débutants pour apprendre la programmation et exercer leurs connaissances. Il peut être utilisé par des professionnel pour tester leurs algorithmes, les vérifier et générer des programme présentables (pseudo-code ou programme Pascal) . -
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libfgen
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.
