CUDA Templates and Python DSLs for High-Performance Linear Algebra
- cuda
- deep-learning
- deep-learning-library
- cpp
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CUDA Templates and Python DSLs for High-Performance Linear Algebra
Read-only mirror of https://gitlab.gnome.org/GNOME/gimp
🎨 Powerful, minimalistic, cross-platform, opensource note-taking app
Dart Image Library for opening, manipulating, and saving various different image file formats.
Structured Edge Detection Toolbox
Create localized App Store screenshots
A Python package to visualise neuroanatomical data in atlas space
Generative d.Art with Flutter
HDR Toolbox for processing High Dynamic Range (HDR) images into MATLAB and Octave
Generate required icon sizes and iconset from a master application icon.
VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.
LidarView performs real-time reception, recording, visualization and processing of 3D LiDAR data. This repository is a mirror of https://gitlab.kitware.com/LidarView/lidarview.
Open source math and physics engine that executes MATLAB-syntax code. Features a modern compiler, automatic GPU acceleration for large calculations, and support for math on geometry / FEA calculations.
🧑🎨 Mobile app for drawing 2D animations
Accurate and efficient spot detection for microscopy data
C++ implementation of the Local Binary Pattern texture descriptors. This class integrates with OpenCV and FFTW3 to bring a complete and fast implementation of the popular descriptors: LBP u2, ri, riu2 & hf. The routines for calculating these descriptors are inspired by the Matlab code of the original authors.
A command line utility to convert heavy GIS sources into elegant administrative & topographic topojson files, raster files, and web friendly svg maps.
Lattice light-sheet post-processing utility.
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.