HARFANG 3D source code public repository
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Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
CodeCompass is a software comprehension tool for large scale software written in C/C++, C# and Python.
Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.
2D/3D simplicial mesh generator interface for Python (Triangle, TetGen, gmsh)
The ultimate Python binding for Vulkan API
Run any site JavaScript from Python with the real Firefox engine. Headless SpiderMonkey + Necko for automation and scraping.
TTK - Topological Data Analysis and Visualization - Source Code
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
Binary Editor for Qt
Universal cheminformatics toolkit, utilities and database search tools
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
Official library for RaBitQ vector quantization and approximate nearest-neighbor search, in C++ and Python.
Native PC compatibility project for The Order: 1886 (PS4, CUSA00076). Windows launcher, Vulkan graphics. In development: 3D cinematics observed; gameplay validation ongoing. Uses your own dump; no game files included. | Projeto para PC em desenvolvimento; usa seu próprio dump.
Loopcut: an AI agent that works inside Blender. A fork of Blender (GPL).
C++ API for LibAV / FFMpeg
A framework for high-performance domain decomposition methods.
Git super project for PySide
Port of Python's Turtle to C++
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Ultra high-performance secp256k1 ECC engine | Python, Node.js, Rust, Go, C#, Swift, Java bindings | CUDA, Metal, OpenCL GPU | ECDSA, Schnorr, FROST, MuSig2, BIP-352 | 15+ platforms