Open Source Python Software
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Python Software
Browse free open source Python Software and projects below. Use the toggles on the left to filter open source Python Software by OS, license, language, programming language, and project status.
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GeographicLib
Geographic library
GeographicLib is a small C++ library for: geodesic and rhumb line calculations; conversions between geographic, UTM, UPS, MGRS, geocentric, and local cartesian coordinates; gravity (e.g., EGM2008) and geomagnetic field (e.g., WMM2020) calculations. -
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A cross-platform, open-source, alternative to NIST REFPROP. Based on reference-accuracy equations of state and transport property correlations for refrigerants like Water, CO2, R134a, Nitrogen, Argon, Ammonia, Air, R404a, R410a, Propane and many others. A selection of secondary working fluid properties are also available. Can also make use of REFPROP when available. In addition, calculations for Humid Air Properties based on ASHRAE RP-1485 are provided. Wrappers are available for MATLAB, Octave, Python, C#, Fortran and many more.
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GMAT
General Mission Analysis Tool
The General Mission Analysis Tool (GMAT) is an open-source tool for space mission design and navigation. GMAT is developed by a team of NASA, private industry, and public and private contributors. The GMAT development team is pleased to announce the release of GMAT version R2025a. For a complete list of new features, compatibility changes, and bug fixes, see the R2025a Release Notes in the Users Guide. -
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VGGFace2
VGGFace2 Dataset for Face Recognition
VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc. -
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BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.
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Lenia
Lenia - Mathematical Life Forms
Lenia is a 2D cellular automaton with continuous space, time, and states. It produces a huge variety of interesting life forms. There are various versions available. Python, Matlab, and web (JavaScript) versions are real-time, interactive, and equipped with statistics tools. Jupyter and R versions are non-interactive and just for demonstration purposes. -
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Stanford Machine Learning Course
machine learning course programming exercise
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises. -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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The auditory modeling toolbox (AMT) is a Matlab/Octave toolbox for the development and application of auditory computational models. Over 50 auditory models implemented in Matlab, Octave, C, C++, and Python can be run from Matlab and Octave, on Windows and Linux. The AMT provides a well-structured in-code documentation, includes auditory data required to run the models. It integrates functionality to reproduce the model predictions. Model implementations can be evaluated in two stages, by running so-called demonstrations which are quick presentations of a model and by starting so-called experiments aimed at reproducing results from the corresponding publications. Easy installation and user-friendly access help students and researchers to work with and to advance existing models.
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Yeastar: Business Phone System and Unified CommunicationsUser-friendly, optimized, and scalable, the Yeastar P-Series Phone System redefines business connectivity by bringing together calling, meetings, omnichannel messaging, and integrations in one simple platform—removing the limitations of distance, platforms, and systems.
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
FEATool Multiphysics (https://www.featool.com) is a fully integrated toolbox for computer aided engineering CAE, finite element analysis & fluid dynamics simulations. With a very easy-to-use GUI, anyone is now able to quickly set up and perform large scale dynamical and complex engineering physics simulations, with coupled fluid flow, heat transfer, structural mechanics, chemical transport, and electromagnetics effects, without having to learn complex programming. In addition to built-in CAD and pre/post-processing, automatic mesh generation, and multi-physics solvers, FEATool also seamlessly integrates the state-of-the-art OpenFOAM [1], SU2, and FEniCS CFD and FEA solvers. Moreover, native itegration with MATLAB and Python allows advanced simulation scripts and programmatic use cases such as in AI and machine learning [2]. [1]: https://www.featool.com/Easy-to-Use-OpenFOAM-GUI/ [2]: https://featool.com/model-showcase/2024-11-12-CFD-and-Flow-Prediction-Based-on-Deep-Learning -
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Finite Element Method Magnetics
Finite element analysis of electromagnetic devices
Solves low frequency magnetic, electrostatic, heat flow, and current flow problems on 2D and axisymmetric domains via the finite element method. -
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Ctrax is a machine vision program for estimating the positions and orientations of many walking fruit flies, maintaining their individual identities over long periods of time with minimal supervision, and on average for 1.5 fly-hours automatically.
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. This resource serves as both an educational reference and a foundation for further exploration in image retrieval research.
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RefineNet
RefineNet: Multi-Path Refinement Networks
RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. While this codebase is specific to MATLAB and MatConvNet, a PyTorch implementation and lighter-weight variants are also available from the community. -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. It includes training scripts, evaluation code, and pre-trained models that achieve strong results on popular benchmarks such as AFW, PASCAL Face, FDDB, and WIDER FACE. The framework is optimized for speed and accuracy, making it suitable for both academic research and practical applications in computer vision. -
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niftilib
** MAIN SITE IS NOW: https://github.com/NIFTI-Imaging/nifti_clib **
niftilib is a collection of i/o routines for the nifti1 neuroimage data format. C (nifticlib), Java (niftijlib), Matlab (niftimatlib), and Python (pynifti) code is available. For nifti format info see: http://nifti.nimh.nih.gov/ -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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PROPER Optical Propagation Library
Routines for wavefront propagation in IDL, Matlab, and Python
PROPER is a library of routines for the propagation of wavefronts through an optical system using Fourier-based methods. It was developed at the Jet Propulsion Laboratory for modeling stellar coronagraphs, but it can be applied to other optical systems were diffraction propagation is of concern. It is currently available for IDL (Interactive Data Language), Matlab and Python (3.x). It includes routines for generating complex apertures and obscurations and aberrations (Zernike & PSD-defined). It includes a model of a deformable mirror for wavefront control. The routines perform near and far field propagation with automatic selection of propagators. The latest version is v3.3.1 (IDL & Matlab) and v3.3.4 (Python). Please report any bugs using the Tickets tab. -
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Moved to https://github.com/rdiankov/openrave An open-source, cross-platform, plugin-based robot planning environment for autonomous robotics. Includes services like collision detection, physics, (inverse) kinematics, sensors, robot controls, python bindings, and a network scripting environment.
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NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
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Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It can be used from MATLAB, Python, C++, or Fortran.
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ASALI
ASALI is an open-source code for chemical engineers
Do you work with chemical reactors? Are you curious about them? ASALI is the open-source code that you are looking for. Chemical reactor models, transport/thermodynamic properties of gases, equilibrium calculations. ASALI couples all these features with an user friendly graphical interface. Modeling chemical reactors has never been so easy. -
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This project, developed at UCL London, provides code for tomographic reconstruction. NiftyRec is written in C and has Python and Matlab extensions. Computationally intensive functions have a GPU accelerated version based on CUDA.
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DCT
Diffraction Contrast Tomography analysis code
Diffraction contrast tomography code base, as developed by researchers from beamline ID19 of the ESRF, Grenoble, France, and Manchester University, UK. -
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NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
