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Emgu CV is a cross platform .Net wrapper for OpenCV
Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages such as C#, VB, VC++, IronPython etc. The wrapper can be compiled in Mono and run on Windows, Linux, Mac OS X, iPhone, iPad and Android devices.
Computer vision and image processing library for Qt.
...The library also provides classes for several data types usually required by computer vision and image processing applications such as vectors, matrices, quaternions and images.
Thanks to a large number of wrapper functions these objects can be used with highly efficient functionality from third party libraries such as OpenCV, GNU Scientific Library, Computational Geometry Algorithms Library, Intel's Math Kernel Library and Integrated Performance Primitives, the Octave library, etc...
MDSTk is a collection of 2D/3D image processing tools aimed at medical images. It contains routines for volume data processing (3D filtering, segmentation, etc.) as well as fast low-level vector graphics library for surface and tetrahedral meshing.
MDSTk has been forked by 3Dim Laboratory s.r.o. to provide better support and further push its development forward. Please check VPL (Voxel Processing Library) project available on Bitbucket (https://bitbucket.org/3dimlab/vpl).
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
ImageNets is an computer vision and image processing extension to the OpenCV library for user-friendly programming of Robot Vision algorithms. ImageNets uses Qt by Nokia. ImageNets is ideal for education of image processing.
An implementation of Bruhn et al.'s fast variational optical flow algorithm using the OpenCV image processing library. The code calculates dense flow fields with a user-specified level of precision.